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  • 1.
    Alsing, Justin
    et al.
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC).
    Peiris, Hiranya
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC). University College London, UK.
    Mortlock, Daniel
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC). Imperial College London, UK.
    Leja, Joel
    Leistedt, Boris
    Forward Modeling of Galaxy Populations for Cosmological Redshift Distribution Inference2023In: Astrophysical Journal Supplement Series, ISSN 0067-0049, E-ISSN 1538-4365, Vol. 264, no 2, article id 29Article in journal (Refereed)
    Abstract [en]

    We present a forward-modeling framework for estimating galaxy redshift distributions from photometric surveys. Our forward model is composed of: a detailed population model describing the intrinsic distribution of the physical characteristics of galaxies, encoding galaxy evolution physics; a stellar population synthesis model connecting the physical properties of galaxies to their photometry; a data model characterizing the observation and calibration processes for a given survey; and explicit treatment of selection cuts, both into the main analysis sample and for the subsequent sorting into tomographic redshift bins. This approach has the appeal that it does not rely on spectroscopic calibration data, provides explicit control over modeling assumptions and builds a direct bridge between photo-z inference and galaxy evolution physics. In addition to redshift distributions, forward modeling provides a framework for drawing robust inferences about the statistical properties of the galaxy population more generally. We demonstrate the utility of forward modeling by estimating the redshift distributions for the Galaxy And Mass Assembly (GAMA) survey and the Vimos VLT Deep Survey (VVDS), validating against their spectroscopic redshifts. Our baseline model is able to predict tomographic redshift distributions for GAMA and VVDS with respective biases of Δz ≲ 0.003 and Δz ≃ 0.01 on the mean redshift—comfortably accurate enough for Stage III cosmological surveys—without any hyperparameter tuning (i.e., prior to doing any fitting to those data). We anticipate that with additional hyperparameter fitting and modeling improvements, forward modeling will provide a path to accurate redshift distribution inference for Stage IV surveys.

  • 2.
    Alsing, Justin
    et al.
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC).
    Peiris, Hiranya V.
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC). University College London, UK.
    Leja, Joel
    Hahn, ChangHoon
    Tojeiro, Rita
    Mortlock, Daniel
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC). Imperial College London, UK.
    Leistedt, Boris
    Johnson, Benjamin D.
    Conroy, Charlie
    SPECULATOR: Emulating Stellar Population Synthesis for Fast and Accurate Galaxy Spectra and Photometry2020In: Astrophysical Journal Supplement Series, ISSN 0067-0049, E-ISSN 1538-4365, Vol. 249, no 1, article id 5Article in journal (Refereed)
    Abstract [en]

    We presentspeculator-a fast, accurate, and flexible framework for emulating stellar population synthesis (SPS) models for predicting galaxy spectra and photometry. For emulating spectra, we use a principal component analysis to construct a set of basis functions and neural networks to learn the basis coefficients as a function of the SPS model parameters. For photometry, we parameterize the magnitudes (for the filters of interest) as a function of SPS parameters by a neural network. The resulting emulators are able to predict spectra and photometry under both simple and complicated SPS model parameterizations to percent-level accuracy, giving a factor of 10(3)-10(4)speedup over direct SPS computation. They have readily computable derivatives, making them amenable to gradient-based inference and optimization methods. The emulators are also straightforward to call from a GPU, giving an additional order of magnitude speedup. Rapid SPS computations delivered by emulation offers a massive reduction in the computational resources required to infer the physical properties of galaxies from observed spectra or photometry and simulate galaxy populations under SPS models, while maintaining the accuracy required for a range of applications.

  • 3. Alves, Catarina S.
    et al.
    Peiris, Hiranya
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC). University College London, UK.
    Lochner, Michelle
    McEwen, Jason D.
    Allam, Tarek
    Biswas, Rahul
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC).
    Considerations for Optimizing the Photometric Classification of Supernovae from the Rubin Observatory2022In: Astrophysical Journal Supplement Series, ISSN 0067-0049, E-ISSN 1538-4365, Vol. 258, no 2, article id 23Article in journal (Refereed)
    Abstract [en]

    The Vera C. Rubin Observatory will increase the number of observed supernovae (SNe) by an order of magnitude; however, it is impossible to spectroscopically confirm the class for all SNe discovered. Thus, photometric classification is crucial, but its accuracy depends on the not-yet-finalized observing strategy of Rubin Observatory's Legacy Survey of Space and Time (LSST). We quantitatively analyze the impact of the LSST observing strategy on SNe classification using simulated multiband light curves from the Photometric LSST Astronomical Time-Series Classification Challenge (PLAsTiCC). First, we augment the simulated training set to be representative of the photometric redshift distribution per SNe class, the cadence of observations, and the flux uncertainty distribution of the test set. Then we build a classifier using the photometric transient classification library snmachine, based on wavelet features obtained from Gaussian process fits, yielding a similar performance to the winning PLAsTiCC entry. We study the classification performance for SNe with different properties within a single simulated observing strategy. We find that season length is important, with light curves of 150 days yielding the highest performance. Cadence also has an important impact on SNe classification; events with median inter-night gap <3.5 days yield higher classification performance. Interestingly, we find that large gaps (>10 days) in light-curve observations do not impact performance if sufficient observations are available on either side, due to the effectiveness of the Gaussian process interpolation. This analysis is the first exploration of the impact of observing strategy on photometric SN classification with LSST.

  • 4. Alves, Catarina S.
    et al.
    Peiris, Hiranya V.
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC). University College London, UK.
    Lochner, Michelle
    McEwen, Jason D.
    Kessler, Richard
    The LSST Dark Energy Science Collaboration,
    Impact of Rubin Observatory Cadence Choices on Supernovae Photometric Classification2023In: Astrophysical Journal Supplement Series, ISSN 0067-0049, E-ISSN 1538-4365, Vol. 265, no 2, article id 43Article in journal (Refereed)
    Abstract [en]

    The Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST) will discover an unprecedented number of supernovae (SNe), making spectroscopic classification for all the events infeasible. LSST will thus rely on photometric classification, whose accuracy depends on the not-yet-finalized LSST observing strategy. In this work, we analyze the impact of cadence choices on classification performance using simulated multiband light curves. First, we simulate SNe with an LSST baseline cadence, a nonrolling cadence, and a presto-color cadence, which observes each sky location three times per night instead of twice. Each simulated data set includes a spectroscopically confirmed training set, which we augment to be representative of the test set as part of the classification pipeline. Then we use the photometric transient classification library snmachine to build classifiers. We find that the active region of the rolling cadence used in the baseline observing strategy yields a 25% improvement in classification performance relative to the background region. This improvement in performance in the actively rolling region is also associated with an increase of up to a factor of 2.7 in the number of cosmologically useful Type Ia SNe relative to the background region. However, adding a third visit per night as implemented in presto-color degrades classification performance due to more irregularly sampled light curves. Overall, our results establish desiderata on the observing cadence related to classification of full SNe light curves, which in turn impacts photometric SNe cosmology with LSST.

  • 5. Barack, Leor
    et al.
    Cardoso, Vitor
    Nissanke, Samaya
    Sotiriou, Thomas P.
    Askar, Abbas
    Belczynski, Chris
    Bertone, Gianfranco
    Bon, Edi
    Blas, Diego
    Brito, Richard
    Bulik, Tomasz
    Burrage, Clare
    Byrnes, Christian T.
    Caprini, Chiara
    Chernyakova, Masha
    Chruściel, Piotr
    Colpi, Monica
    Ferrari, Valeria
    Gaggero, Daniele
    Gair, Jonathan
    García-Bellido, Juan
    Hassan, Sayed Fawad
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC).
    Heisenberg, Lavinia
    Hendry, Martin
    Heng, Ik Siong
    Herdeiro, Carlos
    Hinderer, Tanja
    Horesh, Assaf
    Kavanagh, Bradley J.
    Kocsis, Bence
    Kramer, Michael
    Le Tiec, Alexandre
    Mingarelli, Chiara
    Nardini, Germano
    Nelemans, Gijs
    Palenzuela, Carlos
    Pani, Paolo
    Perego, Albino
    Porter, Edward K.
    Rossi, Elena M.
    Schmidt, Patricia
    Sesana, Alberto
    Sperhake, Ulrich
    Stamerra, Antonio
    Stein, Leo C.
    Tamanini, Nicola
    Tauris, Thomas M.
    Arturo Urena-López, L.
    Vincent, Frederic
    Volonteri, Marta
    Wardell, Barry
    Wex, Norbert
    Yagi, Kent
    Abdelsalhin, Tiziano
    Ángel Aloy, Miguel
    Amaro-Seoane, Pau
    Annulli, Lorenzo
    Arca-Sedda, Manuel
    Bah, Ibrahima
    Barausse, Enrico
    Barakovic, Elvis
    Benkel, Robert
    Bennett, Charles L.
    Bernard, Laura
    Bernuzzi, Sebastiano
    Berry, Christopher P. L.
    Berti, Emanuele
    Bezares, Miguel
    Juan Blanco-Pillado, Jose
    Blázquez-Salcedo, Jose Luis
    Bonetti, Matteo
    Bošković, Mateja
    Bosnjak, Zeljka
    Bricman, Katja
    Brügmann, Bernd
    Capelo, Pedro R.
    Carloni, Sante
    Cerdá-Durán, Pablo
    Charmousis, Christos
    Chaty, Sylvain
    Clerici, Aurora
    Coates, Andrew
    Colleoni, Marta
    Collodel, Lucas G.
    Compère, Geoffrey
    Cook, William
    Cordero-Carríon, Isabel
    Correia, Miguel
    de la Cruz-Dombriz, Álvaro
    Czinner, Viktor G.
    Destounis, Kyriakos
    Dialektopoulos, Kostas
    Doneva, Daniela
    Dotti, Massimo
    Drew, Amelia
    Eckner, Christopher
    Edholm, James
    Emparan, Roberto
    Erdem, Recai
    Ferreira, Miguel
    Ferreira, Pedro G.
    Finch, Andrew
    Font, Jose A.
    Franchini, Nicola
    Fransen, Kwinten
    Gal'tsov, Dmitry
    Ganguly, Apratim
    Gerosa, Davide
    Glampedakis, Kostas
    Gomboc, Andreja
    Goobar, Ariel
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC).
    Gualtieri, Leonardo
    Guendelman, Eduardo
    Haardt, Francesco
    Harmark, Troels
    Hejda, Filip
    Hertog, Thomas
    Hopper, Seth
    Husa, Sascha
    Ihanec, Nada
    Ikeda, Taishi
    Jaodand, Amruta
    Jetzer, Philippe
    Jimenez-Forteza, Xisco
    Kamionkowski, Marc
    Kaplan, David E.
    Kazantzidis, Stelios
    Kimura, Masashi
    Kobayashi, Shiho
    Kokkotas, Kostas
    Krolik, Julian
    Kunz, Jutta
    Lämmerzahl, Claus
    Lasky, Paul
    Lemos, José P. S.
    Said, Jackson Levi
    Liberati, Stefano
    Lopes, Jorge
    Luna, Raimon
    Ma, Yin-Zhe
    Maggio, Elisa
    Mangiagli, Alberto
    Montero, Marina Martinez
    Maselli, Andrea
    Mayer, Lucio
    Mazumdar, Anupam
    Messenger, Christopher
    Ménard, Brice
    Minamitsuji, Masato
    Moore, Christopher J.
    Mota, David
    Nampalliwar, Sourabh
    Nerozzi, Andrea
    Nichols, David
    Nissimov, Emil
    Obergaulinger, Martin
    Obers, Niels A.
    Oliveri, Roberto
    Pappas, George
    Pasic, Vedad
    Peiris, Hiranya
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC).
    Petrushevska, Tanja
    Pollney, Denis
    Pratten, Geraint
    Rakic, Nemanja
    Racz, Istvan
    Radia, Miren
    Ramazanoglu, Fethi M.
    Ramos-Buades, Antoni
    Raposo, Guilherme
    Rogatko, Marek
    Rosca-Mead, Roxana
    Rosinska, Dorota
    Rosswog, Stephan
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC).
    Ruiz-Morales, Ester
    Sakellariadou, Mairi
    Sanchis-Gual, Nicolás
    Salafia, Om Sharan
    Samajdar, Anuradha
    Sintes, Alicia
    Smole, Majda
    Sopuerta, Carlos
    Souza-Lima, Rafael
    Stalevski, Marko
    Stergioulas, Nikolaos
    Stevens, Chris
    Tamfal, Tomas
    Torres-Forne, Alejandro
    Tsygankov, Sergey
    Ünlütürk, Kivanç I.
    Valiante, Rosa
    van de Meent, Maarten
    Velhinho, José
    Verbin, Yosef
    Vercnocke, Bert
    Vernieri, Daniele
    Vicente, Rodrigo
    Vitagliano, Vincenzo
    Weltman, Amanda
    Whiting, Bernard
    Williamson, Andrew
    Witek, Helvi
    Wojnar, Aneta
    Yakut, Kadri
    Yan, Haopeng
    Yazadjiev, Stoycho
    Zaharijas, Gabrijela
    Zilhão, Miguel
    Black holes, gravitational waves and fundamental physics: a roadmap2019In: Classical and quantum gravity, ISSN 0264-9381, E-ISSN 1361-6382, Vol. 36, no 14, article id 143001Article, review/survey (Refereed)
    Abstract [en]

    The grand challenges of contemporary fundamental physics dark matter, dark energy, vacuum energy, inflation and early universe cosmology, singularities and the hierarchy problem all involve gravity as a key component. And of all gravitational phenomena, black holes stand out in their elegant simplicity, while harbouring some of the most remarkable predictions of General Relativity: event horizons, singularities and ergoregions. The hitherto invisible landscape of the gravitational Universe is being unveiled before our eyes: the historical direct detection of gravitational waves by the LIGO-Virgo collaboration marks the dawn of a new era of scientific exploration. Gravitational-wave astronomy will allow us to test models of black hole formation, growth and evolution, as well as models of gravitational-wave generation and propagation. It will provide evidence for event horizons and ergoregions, test the theory of General Relativity itself, and may reveal the existence of new fundamental fields. The synthesis of these results has the potential to radically reshape our understanding of the cosmos and of the laws of Nature. The purpose of this work is to present a concise, yet comprehensive overview of the state of the art in the relevant fields of research, summarize important open problems, and lay out a roadmap for future progress. This write-up is an initiative taken within the framework of the European Action on 'Black holes, Gravitational waves and Fundamental Physics'.

  • 6. Bianco, Federica B.
    et al.
    Ivezić, Željko
    Jones, R. Lynne
    Graham, Melissa L.
    Marshall, Phil
    Saha, Abhijit
    Strauss, Michael A.
    Yoachim, Peter
    Ribeiro, Tiago
    Anguita, Timo
    Bauer, A. E.
    Bauer, Franz E.
    Bellm, Eric C.
    Blum, Robert D.
    Brandt, William N.
    Brough, Sarah
    Catelan, Márcio
    Clarkson, William
    Connolly, Andrew J.
    Gawiser, Eric
    Gizis, John E.
    Hložek, Renée
    Kaviraj, Sugata
    Liu, Charles T.
    Lochner, Michelle
    Mahabal, Ashish A.
    Mandelbaum, Rachel
    McGehee, Peregrine
    Neilsen, Eric H. Jr Jr
    Olsen, Knut A. G.
    Peiris, Hiranya
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC). University College London, UK.
    Rhodes, Jason
    Richards, Gordon T.
    Ridgway, Stephen
    Schwamb, Megan E.
    Scolnic, Dan
    Shemmer, Ohad
    Slater, Colin T.
    Slosar, Anže
    Smartt, Stephen J.
    Strader, Jay
    Street, Rachel
    Trilling, David E.
    Verma, Aprajita
    Vivas, A. K.
    Wechsler, Risa H.
    Willman, Beth
    Optimization of the Observing Cadence for the Rubin Observatory Legacy Survey of Space and Time: A Pioneering Process of Community-focused Experimental Design2022In: Astrophysical Journal Supplement Series, ISSN 0067-0049, E-ISSN 1538-4365, Vol. 258, no 1, article id 1Article in journal (Refereed)
    Abstract [en]

    Vera C. Rubin Observatory is a ground-based astronomical facility under construction, a joint project of the National Science Foundation and the U.S. Department of Energy, designed to conduct a multipurpose 10 yr optical survey of the Southern Hemisphere sky: the Legacy Survey of Space and Time. Significant flexibility in survey strategy remains within the constraints imposed by the core science goals of probing dark energy and dark matter, cataloging the solar system, exploring the transient optical sky, and mapping the Milky Way. The survey's massive data throughput will be transformational for many other astrophysics domains and Rubin's data access policy sets the stage for a huge community of potential users. To ensure that the survey science potential is maximized while serving as broad a community as possible, Rubin Observatory has involved the scientific community at large in the process of setting and refining the details of the observing strategy. The motivation, history, and decision-making process of this strategy optimization are detailed in this paper, giving context to the science-driven proposals and recommendations for the survey strategy included in this Focus Issue.

  • 7. Bird, Simeon
    et al.
    Rogers, Keir K.
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC).
    Peiris, Hiranya V.
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC).
    Verde, Licia
    Font-Ribera, Andreu
    Pontzen, Andrew
    An emulator for the Lyman-alpha forest2019In: Journal of Cosmology and Astroparticle Physics, E-ISSN 1475-7516, no 2, article id 050Article in journal (Refereed)
    Abstract [en]

    We present methods for interpolating between the 1-D flux power spectrum of the Lyman-alpha forest, as output by cosmological hydrodynamic simulations. Interpolation is necessary for cosmological parameter estimation due to the limited number of simulations possible. We construct an emulator for the Lyman-alpha forest flux power spectrum from 21 small simulations using Latin hypercube sampling and Gaussian process interpolation. We show that this emulator has a typical accuracy of 1 : 5% and a worst-case accuracy of 4%, which compares well to the current statistical error of 3-5% at z < 3 from BOSS DR9. We compare to the previous state of the art, quadratic polynomial interpolation. The Latin hypercube samples the entire volume of parameter space, while quadratic polynomial emulation samples only lower-dimensional subspaces. The Gaussian process provides an estimate of the emulation error and we show using test simulations that this estimate is reasonable. We construct a likelihood function and use it to show that the posterior constraints generated using the emulator are unbiased. We show that our Gaussian process emulator has lower emulation error than quadratic polynomial interpolation and thus produces tighter posterior confidence intervals, which will be essential for future Lyman-alpha surveys such as DESI.

  • 8. Braden, Jonathan
    et al.
    Johnson, Matthew C.
    Peiris, Hiranya
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC). University College London, United Kingdom.
    Pontzen, Andrew
    Weinfurtner, Silke
    New Semiclassical Picture of Vacuum Decay2019In: Physical Review Letters, ISSN 0031-9007, E-ISSN 1079-7114, Vol. 123, no 3, article id 031601Article in journal (Refereed)
    Abstract [en]

    We introduce a new picture of vacuum decay which, in contrast to existing semiclassical techniques, provides a real-time description and does not rely on classically forbidden tunneling paths. Using lattice simulations, we observe vacuum decay via bubble formation by generating realizations of vacuum fluctuations and evolving with the classical equations of motion. The decay rate obtained from an ensemble of simulations is in excellent agreement with existing techniques. Future applications include bubble correlation functions, fast decay rates, and decay of nonvacuum states.

  • 9. Braden, Jonathan
    et al.
    Johnson, Matthew C.
    Peiris, Hiranya
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC). University College London, U.K..
    Pontzen, Andrew
    Weinfurtner, Silke
    Nonlinear dynamics of the cold atom analog false vacuum2019In: Journal of High Energy Physics (JHEP), ISSN 1126-6708, E-ISSN 1029-8479, no 10, article id 174Article in journal (Refereed)
    Abstract [en]

    We investigate the nonlinear dynamics of cold atom systems that can in principle serve as quantum simulators of false vacuum decay. The analog false vacuum manifests as a metastable vacuum state for the relative phase in a two-species Bose-Einstein condensate (BEC), induced by a driven periodic coupling between the two species. In the appropriate low energy limit, the evolution of the relative phase is approximately governed by a relativistic wave equation exhibiting true and false vacuum configurations. In previous work, a linear stability analysis identified exponentially growing short-wavelength modes driven by the time-dependent coupling. These modes threaten to destabilize the analog false vacuum. Here, we employ numerical simulations of the coupled Gross-Pitaevski equations (GPEs) to determine the non-linear evolution of these linearly unstable modes. We find that unless a physical mechanism modifies the GPE on short length scales, the analog false vacuum is indeed destabilized. We briefly discuss various physically expected corrections to the GPEs that may act to remove the exponentially unstable modes. To investigate the resulting dynamics in cases where such a removal mechanism exists, we implement a hard UV cutoff that excludes the unstable modes as a simple model for these corrections. We use this to study the range of phenomena arising from such a system. In particular, we show that by modulating the strength of the time-dependent coupling, it is possible to observe the crossover between a second and first order phase transition out of the false vacuum.

  • 10. Braden, Jonathan
    et al.
    Johnson, Matthew C.
    Peiris, Hiranya V.
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC). University College London, United Kingdom.
    Aguirre, Anthony
    Constraining cosmological ultralarge scale structure using numerical relativity2017In: Physical Review D: covering particles, fields, gravitation, and cosmology, ISSN 2470-0010, E-ISSN 2470-0029, Vol. 96, no 2, article id 023541Article in journal (Refereed)
    Abstract [en]

    Cosmic inflation, a period of accelerated expansion in the early universe, can give rise to large amplitude ultralarge scale inhomogeneities on distance scales comparable to or larger than the observable universe. The cosmic microwave background (CMB) anisotropy on the largest angular scales is sensitive to such inhomogeneities and can be used to constrain the presence of ultralarge scale structure (ULSS). We numerically evolve nonlinear inhomogeneities present at the beginning of inflation in full general relativity to assess the CMB quadrupole constraint on the amplitude of the initial fluctuations and the size of the observable universe relative to a length scale characterizing the ULSS. To obtain a statistically meaningful ensemble of simulations, we adopt a toy model in which inhomogeneities are injected along a preferred direction. We compute the likelihood function for the CMB quadrupole including both ULSS and the standard quantum fluctuations produced during inflation. We compute the posterior given the observed CMB quadrupole, finding that when including gravitational nonlinearities, ULSS curvature perturbations of order unity are allowed by the data, even on length scales not too much larger than the size of the observable universe. To demonstrate the robustness of our conclusions, we also explore a semianalytic model for the ULSS which reproduces our numerical results for the case of planar symmetry, and which can be extended to ULSS with a three-dimensional inhomogeneity structure. Our results illustrate the utility and importance of numerical relativity for constraining early universe cosmology.

  • 11. Braden, Jonathan
    et al.
    Johnson, Matthew C.
    Peiris, Hiranya V.
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC). University College London, United Kingdom.
    Pontzen, Andrew
    Weinfurtner, Silke
    Mass renormalization in lattice simulations of false vacuum decay2023In: Physical Review D: covering particles, fields, gravitation, and cosmology, ISSN 2470-0010, E-ISSN 2470-0029, Vol. 107, no 8, article id 083509Article in journal (Refereed)
    Abstract [en]

    False vacuum decay, a quantum mechanical first-order phase transition in scalar field theories, is an important phenomenon in early Universe cosmology. Recently, real-time semiclassical techniques based on ensembles of lattice simulations were applied to the problem of false vacuum decay. In this context, or any other lattice simulation, the effective potential experienced by long-wavelength modes is not the same as the bare potential. To make quantitative predictions using the real-time semiclassical techniques, it is therefore necessary to understand the redefinition of model parameters and the corresponding deformation of the vacuum state, as well as stochastic contributions that require modeling of unresolved subgrid modes. In this work, we focus on the former corrections and compute the expected modification of the true and false vacuum effective mass, which manifests as a modified dispersion relationship for linear fluctuations about the vacuum. We compare these theoretical predictions to numerical simulations and find excellent agreement. Motivated by this, we use the effective masses to fix the shape of a parametrized effective potential, and explore the modeling uncertainty associated with nonlinear corrections. We compute the decay rates in both the Euclidean and real-time formalisms, finding qualitative agreement in the dependence on the UV cutoff. These calculations further demonstrate that a quantitative understanding of the rates requires additional corrections.

  • 12. Braden, Jonathan
    et al.
    Johnson, Matthew C.
    Peiris, Hiranya V.
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC). University College London, U.K..
    Weinfurtner, Silke
    Towards the cold atom analog false vacuum2018In: Journal of High Energy Physics (JHEP), ISSN 1126-6708, E-ISSN 1029-8479, no 7, article id 014Article in journal (Refereed)
    Abstract [en]

    Analog condensed matter systems present an exciting opportunity to simulate early Universe models in table-top experiments. We consider a recent proposal for an analog condensed matter experiment to simulate the relativistic quantum decay of the false vacuum. In the proposed experiment, two ultra-cold condensates are coupled via a time-varying radio-frequency field. The relative phase of the two condensates in this system is approximately described by a relativistic scalar field with a potential possessing a series of false and true vacuum local minima. If the system is set up in a false vacuum, it would then decay to a true vacuum via quantum mechanical tunnelling. Should such an experiment be realized, it would be possible to answer a number of open questions regarding non-perturbative phenomena in quantum field theory and early Universe cosmology. In this paper, we illustrate a possible obstruction: the time-varying coupling that is invoked to create a false vacuum for the long-wavelength modes of the condensate leads to a destabilization of shorter wavelength modes within the system via parametric resonance. We focus on an idealized setup in which the two condensates have identical properties and identical background densities. Describing the system by the coupled Gross-Pitaevskii equations (GPE), we use the machinery of Floquet theory to perform a linear stability analysis, calculating the wavenumber associated with the first instability band for a variety of experimental parameters. However, we demonstrate that, by tuning the frequency of the time-varying coupling, it may be possible to push the first instability band outside the validity of the GPE, where dissipative effects are expected to damp any instabilities. This provides a viable range of experimental parameters to perform analog experiments of false vacuum decay.

  • 13. Cadiou, Corentin
    et al.
    Pontzen, Andrew
    Peiris, Hiranya
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC). University College London, UK.
    Stellar angular momentum can be controlled from cosmological initial conditions2022In: Monthly notices of the Royal Astronomical Society, ISSN 0035-8711, E-ISSN 1365-2966, Vol. 517, no 3, p. 3459-3468Article in journal (Refereed)
    Abstract [en]

    The angular momentum of galaxies controls the kinematics of their stars, which in turn drives observable quantities such as the apparent radius, the bulge fraction, and the alignment with other nearby structures. To show how angular momentum of galaxies is determined, we build high (35 pc) resolution numerical experiments in which we increase or decrease the angular momentum of the Lagrangian patches in the early universe. We perform cosmological zoom-in simulations of three galaxies over their histories from z = 200 to z = 2, each with five different choices for the angular momentum (15 simulations in total). Our results show that altering early universe angular momentum changes the timing and orbital parameters of mergers, which in turn changes the total stellar angular momentum within a galaxy’s virial radius in a predictable manner. Of our three galaxies, one has no large satellite at z = 2; in this case, the specific angular momentum is concentrated in the central galaxy. Our changes to the initial conditions result in its stellar angular momentum changing over 0.7 dex (from 61 to 320 kpc km s−1⁠) at z = 2. This causes its effective radius to grow by 40 per cent, its v/σ parameter to grow by a factor of 2.6, and its bulge fraction to decrease from 0.72 to 0.57. This proof of concept illustrates how causal studies can contribute to a better understanding of the origin of galaxy scaling relations and intrinsic alignments.

  • 14. Cadiou, Corentin
    et al.
    Pontzen, Andrew
    Peiris, Hiranya
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC). University College London, UK.
    Lucie-Smith, Luisa
    The causal effect of environment on halo mass and concentration2021In: Monthly notices of the Royal Astronomical Society, ISSN 0035-8711, E-ISSN 1365-2966, Vol. 508, no 1, p. 1189-1194Article in journal (Refereed)
    Abstract [en]

    Understanding the impact of environment on the formation and evolution of dark matter haloes and galaxies is a crucial open problem. Studying statistical correlations in large simulated populations sheds some light on these impacts, but the causal effect of an environment on individual objects is harder to pinpoint. Addressing this, we present a new method for resimulating a single dark matter halo in multiple large-scale environments. In the initial conditions, we 'splice' (i.e. insert) the Lagrangian region of a halo into different Gaussian random fields, while enforcing consistency with the statistical properties of Lambda cold dark matter. Applying this technique, we demonstrate that the mass of haloes is primarily determined by the density structure inside their Lagrangian patches, while the haloes' concentration is more strongly affected by environment. The splicing approach will also allow us to study, for example, the impact of the cosmic web on accretion processes and galaxy quenching.

  • 15. Cadiou, Corentin
    et al.
    Pontzen, Andrew
    Peiris, Hiranya V.
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC). University College London, UK.
    Angular momentum evolution can be predicted from cosmological initial conditions2021In: Monthly notices of the Royal Astronomical Society, ISSN 0035-8711, E-ISSN 1365-2966, Vol. 502, no 4, p. 5480-5486Article in journal (Refereed)
    Abstract [en]

    The angular momentum of dark matter haloes controls their spin magnitude and orientation, which in turn influences the galaxies therein. However, the process by which dark matter haloes acquire angular momentum is not fully understood; in particular, it is unclear whether angular momentum growth is stochastic. To address this question, we extend the genetic modification technique to allow control over the angular momentum of any region in the initial conditions. Using this technique to produce a sequence of modified simulations, we can then investigate whether changes to the angular momentum of a specified region in the evolved universe can be accurately predicted from changes in the initial conditions alone. We find that the angular momentum in regions with modified initial conditions can be predicted between 2 and 4 times more accurately than expected from applying tidal torque theory. This result is masked when analysing the angular momentum of haloes, because particles in the outskirts of haloes dominate the angular momentum budget. We conclude that the angular momentum of Lagrangian patches is highly predictable from the initial conditions, with apparent chaotic behaviour being driven by stochastic changes to the arbitrary boundary defining the halo.

  • 16. Elsner, Franz
    et al.
    Leistedt, Boris
    Peiris, Hiranya V.
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC). Univesity College London, UK.
    Unbiased pseudo-C power spectrum estimation with mode projection2017In: Monthly notices of the Royal Astronomical Society, ISSN 0035-8711, E-ISSN 1365-2966, Vol. 465, no 2, p. 1847-1855Article in journal (Refereed)
    Abstract [en]

    With the steadily improving sensitivity afforded by current and future galaxy surveys, a robust extraction of two-point correlation function measurements may become increasingly hampered by the presence of astrophysical foregrounds or observational systematics. The concept of mode projection has been introduced as a means to remove contaminants for which it is possible to construct a spatialmap, reflecting the expected signal contribution. Owing to its computational efficiency compared to minimum-variance methods, the sub-optimal pseudo-C-l (PCL) power spectrum estimator is a popular tool for the analysis of high-resolution data sets. Here, we integrate mode projection into the framework of PCL power spectrum estimation. In contrast to results obtained with optimal estimators, we show that the uncorrected projection of template maps leads to biased power spectra. Based on analytical calculations, we find exact closed-form expressions for the expectation value of the bias and demonstrate that they can be recast in a form which allows a numerically efficient evaluation, preserving the favourable O(l(max)(3)) time complexity of PCL estimator algorithms. Using simulated data sets, we assess the scaling of the bias with various analysis parameters and demonstrate that it can be reliably removed. We conclude that in combination with mode projection, PCL estimators allow for a fast and robust computation of power spectra in the presence of systematic effects - properties in high demand for the analysis of ongoing and future large-scale structure surveys.

  • 17. Feeney, Stephen M.
    et al.
    Gudmundsson, Jón E.
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC). Stockholm University, Nordic Institute for Theoretical Physics (Nordita).
    Peiris, Hiranya V.
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC). University College London, UK.
    Verde, Licia
    Errard, Josquin
    Cosmic microwave background science at commercial airline altitudes2017In: Monthly notices of the Royal Astronomical Society, ISSN 0035-8711, E-ISSN 1365-2966, Vol. 469, no 1, p. l6-L10Article in journal (Refereed)
    Abstract [en]

    Obtaining high-sensitivity measurements of degree-scale cosmic microwave background (CMB) polarization is the most direct path to detecting primordial gravitational waves. Robustly recovering any primordial signal from the dominant foreground emission will require high-fidelity observations at multiple frequencies, with excellent control of systematics. We explore the potential for a new platform for CMB observations, the Airlander 10 hybrid air vehicle, to perform this task. We show that the Airlander 10 platform, operating at commercial airline altitudes, is well suited to mapping frequencies above 220 GHz, which are critical for cleaning CMB maps of dust emission. Optimizing the distribution of detectors across frequencies, we forecast the ability of Airlander 10 to clean foregrounds of varying complexity as a function of altitude, demonstrating its complementarity with both existing (Planck) and ongoing (C-BASS) foreground observations. This novel platform could play a key role in defining our ultimate view of the polarized microwave sky.

  • 18. Feeney, Stephen M.
    et al.
    Peiris, Hiranya V.
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC). University College London, United Kingdom.
    Nissanke, Samaya M.
    Mortlock, Daniel J.
    Stockholm University, Faculty of Science, Department of Astronomy. Imperial College London, United Kingdom.
    Prospects for Measuring the Hubble Constant with Neutron-Star-Black-Hole Mergers2021In: Physical Review Letters, ISSN 0031-9007, E-ISSN 1079-7114, Vol. 126, no 17, article id 171102Article in journal (Refereed)
    Abstract [en]

    Gravitational wave (GW) and electromagnetic (EM) observations of neutron-star-black-hole (NSBH) mergers can provide precise local measurements of the Hubble constant (H-0), ideal for resolving the current H-0 tension. We perform end-to-end analyses of realistic populations of simulated NSBHs, incorporating both GW and EM selection for the first time. We show that NSBHs could achieve unbiased 1.5%-2.4% precision H-0 estimates by 2030. The achievable precision is strongly affected by the details of spin precession and tidal disruption, highlighting the need for improved modeling of NSBH mergers.

  • 19. Feeney, Stephen M.
    et al.
    Peiris, Hiranya V.
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC). University College London, United Kingdom.
    Williamson, Andrew R.
    Nissanke, Samaya M.
    Mortlock, Daniel J.
    Stockholm University, Faculty of Science, Department of Astronomy. Imperial College London, United Kingdom.
    Alsing, Justin
    Scolnic, Dan
    Prospects for Resolving the Hubble Constant Tension with Standard Sirens2019In: Physical Review Letters, ISSN 0031-9007, E-ISSN 1079-7114, Vol. 122, no 6, article id 061105Article in journal (Refereed)
    Abstract [en]

    The Hubble constant (H-0) estimated from the local Cepheid-supernova distance ladder is in 3-sigma tension with the value extrapolated from cosmic microwave background (CMB) data assuming the standard cosmological model. Whether this tension represents newphysics or systematic effects is the subject of intense debate. Here, we investigate how new, independent H-0 estimates can arbitrate this tension, assessing whether the measurements are consistent with being derived from the same model using the posterior predictive distribution (PPD). We show that, with existing data, the inverse distance ladder formed from BOSS baryon acoustic oscillation measurements and the Pantheon supernova sample yields an H-0 posterior near identical to the Planck CMB measurement. The observed local distance ladder value is a very unlikely draw from the resulting PPD. Turning to the future, we find that a sample of similar to 50 binary neutron star standard sirens (detectable within the next decade) will be able to adjudicate between the local and CMB estimates.

  • 20. Handley, Will J.
    et al.
    Lasenby, Anthony N.
    Peiris, Hiranya V.
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC). University College London, United Kingdom.
    Hobson, Michael P.
    Bayesian inflationary reconstructions from Planck 2018 data2019In: Physical Review D: covering particles, fields, gravitation, and cosmology, ISSN 2470-0010, E-ISSN 2470-0029, Vol. 100, no 10, article id 103511Article in journal (Refereed)
    Abstract [en]

    We present three nonparametric Bayesian primordial reconstructions using Planck 2018 polarization data: linear spline primordial power spectrum reconstructions, cubic spline inflationary potential reconstructions, and sharp-featured primordial power spectrum reconstructions. All three methods conditionally show hints of an oscillatory feature in the primordial power spectrum in the multipole range l similar to 20 to l similar to 50, which is to some extent preserved upon marginalization. We find no evidence for deviations from a pure power law across a broad observable window (50 less than or similar to l less than or similar to 2000), but find that parametrizations are preferred which are able to account for lack of resolution at large angular scales due to cosmic variance, and at small angular scales due to Planck instrument noise. Furthermore, the late-time cosmological parameters are unperturbed by these extensions to the primordial power spectrum. This work is intended to provide a background and give more details of the Bayesian primordial reconstruction work found in the Planck 2018 papers.

  • 21. Hlozek, R.
    et al.
    Malz, A. I.
    Ponder, K. A.
    Dai, M.
    Narayan, G.
    Ishida, E. E. O.
    Allam Jr, T.
    Bahmanyar, A.
    Bi, X.
    Biswas, Rahul
    Stockholm University.
    Boone, K.
    Chen, S.
    Du, N.
    Erdem, A.
    Galbany, L.
    Garreta, A.
    Jha, S. W.
    Jones, D. O.
    Kessler, R.
    Lin, M.
    Liu, J.
    Lochner, M.
    Mahabal, A. A.
    Mandel, K. S.
    Margolis, P.
    Martinez-Galarza, J. R.
    McEwen, J. D.
    Muthukrishna, D.
    Nakatsuka, Y.
    Noumi, T.
    Oya, T.
    Peiris, H. V.
    Peters, C. M.
    Puget, J. F.
    Setzer, Christian N.
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC).
    Siddhartha, S.
    Stefanov, S.
    Xie, T.
    Yan, L.
    Yeh, K. -h.
    Zuo, W.
    Results of the Photometric LSST Astronomical Time-series Classification Challenge (PLAsTiCC)2023In: Astrophysical Journal Supplement Series, ISSN 0067-0049, E-ISSN 1538-4365, Vol. 267, no 2, article id 25Article in journal (Refereed)
    Abstract [en]

    Next-generation surveys like the Legacy Survey of Space and Time (LSST) on the Vera C. Rubin Observatory (Rubin) will generate orders of magnitude more discoveries of transients and variable stars than previous surveys. To prepare for this data deluge, we developed the Photometric LSST Astronomical Time-series Classification Challenge (PLAsTiCC), a competition that aimed to catalyze the development of robust classifiers under LSST-like conditions of a nonrepresentative training set for a large photometric test set of imbalanced classes. Over 1000 teams participated in PLAsTiCC, which was hosted in the Kaggle data science competition platform between 2018 September 28 and 2018 December 17, ultimately identifying three winners in 2019 February. Participants produced classifiers employing a diverse set of machine-learning techniques including hybrid combinations and ensemble averages of a range of approaches, among them boosted decision trees, neural networks, and multilayer perceptrons. The strong performance of the top three classifiers on Type Ia supernovae and kilonovae represent a major improvement over the current state of the art within astronomy. This paper summarizes the most promising methods and evaluates their results in detail, highlighting future directions both for classifier development and simulation needs for a next-generation PLAsTiCC data set.

  • 22. Leistedt, Boris
    et al.
    Alsing, Justin
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC).
    Peiris, Hiranya
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC). University College London, UK.
    Mortlock, Daniel J.
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC). Imperial College London, UK.
    Leja, Joel
    Hierarchical Bayesian Inference of Photometric Redshifts with Stellar Population Synthesis Models2023In: Astrophysical Journal Supplement Series, ISSN 0067-0049, E-ISSN 1538-4365, Vol. 264, no 1, article id 23Article in journal (Refereed)
    Abstract [en]

    We present a Bayesian hierarchical framework to analyze photometric galaxy survey data with stellar population synthesis (SPS) models. Our method couples robust modeling of spectral energy distributions with a population model and a noise model to characterize the statistical properties of the galaxy populations and real observations, respectively. By self-consistently inferring all model parameters, from high-level hyperparameters to SPS parameters of individual galaxies, one can separate sources of bias and uncertainty in the data. We demonstrate the strengths and flexibility of this approach by deriving accurate photometric redshifts for a sample of spectroscopically confirmed galaxies in the COSMOS field, all with 26-band photometry and spectroscopic redshifts. We achieve a performance competitive with publicly released photometric redshift catalogs based on the same data. Prior to this work, this approach was computationally intractable in practice due to the heavy computational load of SPS model calls; we overcome this challenge by the addition of neural emulators. We find that the largest photometric residuals are associated with poor calibration for emission-line luminosities and thus build a framework to mitigate these effects. This combination of physics-based modeling accelerated with machine learning paves the path toward meeting the stringent requirements on the accuracy of photometric redshift estimation imposed by upcoming cosmological surveys. The approach also has the potential to create new links between cosmology and galaxy evolution through the analysis of photometric data sets.

  • 23. Lochner, Michelle
    et al.
    Scolnic, Dan
    Almoubayyed, Husni
    Anguita, Timo
    Awan, Humna
    Gawiser, Eric
    Gontcho A. Gontcho, Satya
    Graham, Melissa L.
    Gris, Philippe
    Huber, Simon
    Jha, Saurabh W.
    Lynne Jones, R.
    Kim, Alex G.
    Mandelbaum, Rachel
    Marshall, Phil
    Petrushevska, Tanja
    Regnault, Nicolas
    Setzer, Christian N.
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC).
    Suyu, Sherry H.
    Yoachim, Peter
    Biswas, Rahul
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC).
    Blaineau, Tristan
    Hook, Isobel
    Moniez, Marc
    Neilsen, Eric
    Peiris, Hiranya
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC).
    Rothchild, Daniel
    Stubbs, Christopher
    The Impact of Observing Strategy on Cosmological Constraints with LSST2022In: Astrophysical Journal Supplement Series, ISSN 0067-0049, E-ISSN 1538-4365, Vol. 259, no 2, article id 58Article in journal (Refereed)
    Abstract [en]

    The generation-defining Vera C. Rubin Observatory will make state-of-the-art measurements of both the static and transient universe through its Legacy Survey for Space and Time (LSST). With such capabilities, it is immensely challenging to optimize the LSST observing strategy across the survey's wide range of science drivers. Many aspects of the LSST observing strategy relevant to the LSST Dark Energy Science Collaboration, such as survey footprint definition, single-visit exposure time, and the cadence of repeat visits in different filters, are yet to be finalized. Here, we present metrics used to assess the impact of observing strategy on the cosmological probes considered most sensitive to survey design; these are large-scale structure, weak lensing, type Ia supernovae, kilonovae, and strong lens systems (as well as photometric redshifts, which enable many of these probes). We evaluate these metrics for over 100 different simulated potential survey designs. Our results show that multiple observing strategy decisions can profoundly impact cosmological constraints with LSST; these include adjusting the survey footprint, ensuring repeat nightly visits are taken in different filters, and enforcing regular cadence. We provide public code for our metrics, which makes them readily available for evaluating further modifications to the survey design. We conclude with a set of recommendations and highlight observing strategy factors that require further research.

  • 24. Lochner, Michelle
    et al.
    Scolnic, Daniel M.
    Awan, Humna
    Regnault, Nicolas
    Gris, Philippe
    Mandelbaum, Rachel
    Gawiser, Eric
    Almoubayyed, Husni
    Setzer, Christian N.
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC).
    Huber, Simon
    Graham, Melissa L.
    Hlozek, Renee
    Biswas, Rahul
    Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC).
    Eifler, Tim
    Rothchild, Daniel
    Allam Jr., Tarek
    Blazek, Jonathan
    Chang, Chihway
    Collett, Thomas
    Goobar, Ariel
    Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC). Stockholm University, Faculty of Science, Department of Physics.
    Hook, Isobel M.
    Jarvis, Mike
    Jha, Saurabh W.
    Kim, Alex G.
    Marshall, Phil
    McEwen, Jason D.
    Moniez, Marc
    Newman, Jeffrey A.
    Peiris, Hiranya V.
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC). University College London, UK.
    Petrushevska, Tanja
    Rhodes, Jason
    Sevilla-Noarbe, Ignacio
    Slosar, Anze
    Suyu, Sherry H.
    Tyson, J. Anthony
    Yoachim, Peter
    Optimizing the LSST Observing Strategy for Dark Energy Science: DESC Recommendations for the Wide-Fast-Deep Survey2018Manuscript (preprint) (Other academic)
    Abstract [en]

    Cosmology is one of the four science pillars of LSST, which promises to be transformative for our understanding of dark energy and dark matter. The LSST Dark Energy Science Collaboration (DESC) has been tasked with deriving constraints on cosmological parameters from LSST data. Each of the cosmological probes for LSST is heavily impacted by the choice of observing strategy. This white paper is written by the LSST DESC Observing Strategy Task Force (OSTF), which represents the entire collaboration, and aims to make recommendations on observing strategy that will benefit all cosmological analyses with LSST. It is accompanied by the DESC DDF (Deep Drilling Fields) white paper (Scolnic et al.). We use a variety of metrics to understand the effects of the observing strategy on measurements of weak lensing, large-scale structure, clusters, photometric redshifts, supernovae, strong lensing and kilonovae. In order to reduce systematic uncertainties, we conclude that the current baseline observing strategy needs to be significantly modified to result in the best possible cosmological constraints. We provide some key recommendations: moving the WFD (Wide-Fast-Deep) footprint to avoid regions of high extinction, taking visit pairs in different filters, changing the 2x15s snaps to a single exposure to improve efficiency, focusing on strategies that reduce long gaps (>15 days) between observations, and prioritizing spatial uniformity at several intervals during the 10-year survey.

  • 25. Lockhart, K. E.
    et al.
    Lu, J. R.
    Peiris, Hiranya V.
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC). University College London, UK.
    Rich, R. M.
    Bouchez, A.
    Ghez, A. M.
    A Slowly Precessing Disk in the Nucleus of M31 as the Feeding Mechanism for a Central Starburst2018In: Astrophysical Journal, ISSN 0004-637X, E-ISSN 1538-4357, Vol. 854, no 2, article id 121Article in journal (Refereed)
    Abstract [en]

    We present a kinematic study of the nuclear stellar disk in M31 at infrared wavelengths using high spatial resolution integral field spectroscopy. The spatial resolution achieved, FWHM = 0.'' 12 (0.45 pc at the distance of M31), has only previously been equaled in spectroscopic studies by space-based long-slit observations. Using adaptive optics-corrected integral field spectroscopy from the OSIRIS instrument at the W. M. Keck Observatory, we map the line-of-sight kinematics over the entire old stellar eccentric disk orbiting the supermassive black hole (SMBH) at a distance of r<4 pc. The peak velocity dispersion is 381 +/- 55 km/s(-1), offset by 0.'' 13 +/- 0.'' 03 from the SMBH, consistent with previous high-resolution long-slit observations. There is a lack of near-infrared (NIR) emission at the position of the SMBH and young nuclear cluster, suggesting a spatial separation between the young and old stellar populations within the nucleus. We compare the observed kinematics with dynamical models from Peiris & Tremaine (2003). The best-fit disk orientation to the NIR flux is [theta(l), theta(i), theta(a)] = [-33 +/- 4 degrees, 44 +/- 2 degrees, -15 +/- 15 degrees}], which is tilted with respect to both the larger-scale galactic disk and the best-fit orientation derived from optical observations. The precession rate of the old disk is Omega(P) = 0.0 +/- 3.9 km/s(-1)pc(-1), lower than the majority of previous observations. This slow precession rate suggests that stellar winds from the disk will collide and shock, driving rapid gas inflows and fueling an episodic central starburst as suggested in Chang et al.

  • 26. Lucie-Smith, Luisa
    et al.
    Peiris, Hiranya
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC). University College London, UK.
    Pontzen, Andrew
    An interpretable machine-learning framework for dark matter halo formation2019In: Monthly notices of the Royal Astronomical Society, ISSN 0035-8711, E-ISSN 1365-2966, Vol. 490, no 1, p. 331-342Article in journal (Refereed)
    Abstract [en]

    We present a generalization of our recently proposed machine-learning framework, aiming to provide new physical insights into dark matter halo formation. We investigate the impact of the initial density and tidal shear fields on the formation of haloes over the mass range 11.4 <= log (M/M-circle dot) = 13.4. The algorithm is trained on an N-body simulation to infer the final mass of the halo to which each dark matter particle will later belong. We then quantify the difference in the predictive accuracy between machine-learning models using a metric based on the Kullback-Leibler divergence. We first train the algorithm with information about the density contrast in the particles' local environment. The addition of tidal shear information does not yield an improved halo collapse model over one based on density information alone; the difference in their predictive performance is consistent with the statistical uncertainty of the density-only based model. This result is confirmed as we verify the ability of the initial conditions-to-halo mass mapping learnt from one simulation to generalize to independent simulations. Our work illustrates the broader potential of developing interpretable machine-learning frameworks to gain physical understanding of non-linear large-scale structure formation.

  • 27. Lucie-Smith, Luisa
    et al.
    Peiris, Hiranya
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC). University College London, UK.
    Pontzen, Andrew
    Nord, Brian
    Thiyagalingam, Jeyan
    Piras, Davide
    Discovering the building blocks of dark matter halo density profiles with neural networks2022In: Physical Review D: covering particles, fields, gravitation, and cosmology, ISSN 2470-0010, E-ISSN 2470-0029, Vol. 105, no 10, article id 103533Article in journal (Refereed)
    Abstract [en]

    The density profiles of dark matter halos are typically modeled using empirical formulas fitted to the density profiles of relaxed halo populations. We present a neural network model that is trained to learn the mapping from the raw density field containing each halo to the dark matter density profile. We show that the model recovers the widely used Navarro-Frenk-White profile out to the virial radius and can additionally describe the variability in the outer profile of the halos. The neural network architecture consists of a supervised encoder-decoder framework, which first compresses the density inputs into a low-dimensional latent representation, and then outputs ρ(r) for any desired value of radius r. The latent representation contains all the information used by the model to predict the density profiles. This allows us to interpret the latent representation by quantifying the mutual information between the representation and the halos’ ground-truth density profiles. A two-dimensional representation is sufficient to accurately model the density profiles up to the virial radius; however, a three-dimensional representation is required to describe the outer profiles beyond the virial radius. The additional dimension in the representation contains information about the infalling material in the outer profiles of dark matter halos, thus discovering the splashback boundary of halos without prior knowledge of the halos’ dynamical history.

  • 28. Lucie-Smith, Luisa
    et al.
    Peiris, Hiranya V.
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC). University College London, UK.
    Pontzen, Andrew
    Lochner, Michelle
    Machine learning cosmological structure formation2018In: Monthly notices of the Royal Astronomical Society, ISSN 0035-8711, E-ISSN 1365-2966, Vol. 479, no 3, p. 3405-3414Article in journal (Refereed)
    Abstract [en]

    We train a machine learning algorithm to learn cosmological structure formation from N-body simulations. The algorithm infers the relationship between the initial conditions and the final dark matter haloes, without the need to introduce approximate halo collapse models. We gain insights into the physics driving halo formation by evaluating the predictive performance of the algorithm when provided with different types of information about the local environment around dark matter particles. The algorithm learns to predict whether or not dark matter particles will end up in haloes of a given mass range, based on spherical overdensities. We show that the resulting predictions match those of spherical collapse approximations such as extended Press-Schechter theory. Additional information on the shape of the local gravitational potential is not able to improve halo collapse predictions; the linear density field contains sufficient information for the algorithm to also reproduce ellipsoidal collapse predictions based on the Sheth-Tormen model. We investigate the algorithm's performance in terms of halo mass and radial position and perform blind analyses on independent initial conditions realizations to demonstrate the generality of our results.

  • 29. Mahony, Constance
    et al.
    Leistedt, Boris
    Peiris, Hiranya V.
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC). University College London, UK.
    Braden, Jonathan
    Joachimi, Benjamin
    Korn, Andreas
    Cremonesi, Linda
    Nichol, Ryan
    Target neutrino mass precision for determining the neutrino hierarchy2020In: Physical Review D: covering particles, fields, gravitation, and cosmology, ISSN 2470-0010, E-ISSN 2470-0029, Vol. 101, no 8, article id 083513Article in journal (Refereed)
    Abstract [en]

    Recent works combining neutrino oscillation and cosmological data to determine the neutrino hierarchy found a range of odds in favor of the normal hierarchy. These results arise from differing approaches to incorporating prior knowledge about neutrinos. We develop a hierarchy-agnostic prior and show that the hierarchy cannot be conclusively determined with current data. The determination of the hierarchy is limited by the neutrino mass scale Sigma(nu) measurement. We obtain a target precision of sigma(Sigma(nu)) = 0.014 eV, necessary for conclusively establishing the normal hierarchy with future data.

  • 30. Malz, A.
    et al.
    Hložek, R.
    Allam, T.
    Bahmanyar, A.
    Biswas, Rahul
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC).
    Dai, M.
    Galbany, L.
    Ishida, E. E. O.
    Jha, S. W.
    Jones, D. O.
    Kessler, R.
    Lochner, M.
    Mahabal, A. A.
    Mandel, K. S.
    Martínez-Galarza, J. R.
    McEwen, J. D.
    Muthukrishna, D.
    Narayan, G.
    Peiris, Hiranya
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC). University College London, UK.
    Peters, C. M.
    Ponder, K.
    Setzer, Christian N.
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC).
    The Photometric LSST Astronomical Time-series Classification Challenge PLAsTiCC: Selection of a Performance Metric for Classification Probabilities Balancing Diverse Science Goals2019In: Astronomical Journal, ISSN 0004-6256, E-ISSN 1538-3881, Vol. 158, no 5, article id 171Article in journal (Refereed)
    Abstract [en]

    Classification of transient and variable light curves is an essential step in using astronomical observations to develop an understanding of the underlying physical processes from which they arise. However, upcoming deep photometric surveys, including the Large Synoptic Survey Telescope (LSST), will produce a deluge of low signal-to-noise data for which traditional type estimation procedures are inappropriate. Probabilistic classification is more appropriate for such data but is incompatible with the traditional metrics used on deterministic classifications. Furthermore, large survey collaborations like LSST intend to use the resulting classification probabilities for diverse science objectives, indicating a need for a metric that balances a variety of goals. We describe the process used to develop an optimal performance metric for an open classification challenge that seeks to identify probabilistic classifiers that can serve many scientific interests. The Photometric LSST Astronomical Time-series Classification Challenge (PLASTICC) aims to identify promising techniques for obtaining classification probabilities of transient and variable objects by engaging a broader community beyond astronomy. Using mock classification probability submissions emulating realistically complex archetypes of those anticipated of PLASTICC, we compare the sensitivity of two metrics of classification probabilities under various weighting schemes, finding that both yield results that are qualitatively consistent with intuitive notions of classification performance. We thus choose as a metric for PLASTICC a weighted modification of the cross-entropy because it can be meaningfully interpreted in terms of information content. Finally, we propose extensions of our methodology to ever more complex challenge goals and suggest some guiding principles for approaching the choice of a metric of probabilistic data products.

  • 31. McEwen, J. D.
    et al.
    Feeney, S. M.
    Peiris, Hiranya V.
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC). University College London, UK.
    Wiaux, Y.
    Ringeval, C.
    Bouchet, F. R.
    Wavelet-Bayesian inference of cosmic strings embedded in the cosmic microwave background2017In: Monthly notices of the Royal Astronomical Society, ISSN 0035-8711, E-ISSN 1365-2966, Vol. 472, no 4, p. 4081-4098Article in journal (Refereed)
    Abstract [en]

    Cosmic strings are a well-motivated extension to the standard cosmological model and could induce a subdominant component in the anisotropies of the cosmic microwave background (CMB), in addition to the standard inflationary component. The detection of strings, while observationally challenging, would provide a direct probe of physics at very high-energy scales. We develop a framework for cosmic string inference from observations of the CMB made over the celestial sphere, performing a Bayesian analysis in wavelet space where the string-induced CMB component has distinct statistical properties to the standard inflationary component. Our wavelet-Bayesian framework provides a principled approach to compute the posterior distribution of the string tension G mu and the Bayesian evidence ratio comparing the string model to the standard inflationary model. Furthermore, we present a technique to recover an estimate of any string-induced CMB map embedded in observational data. Using Planck-like simulations, we demonstrate the application of our framework and evaluate its performance. The method is sensitive to G mu similar to 5 x 10(-7) for Nambu-Goto string simulations that include an integrated Sachs-Wolfe contribution only and do not include any recombination effects, before any parameters of the analysis are optimized. The sensitivity of the method compares favourably with other techniques applied to the same simulations.

  • 32.
    Millar, Alexander J.
    et al.
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC). Stockholm University, Nordic Institute for Theoretical Physics (Nordita). Fermi National Accelerator Laboratory, USA.
    Anlage, Steven M.
    Balafendiev, Rustam
    Belov, Pavel
    van Bibber, Karl
    Conrad, Jan
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC).
    Demarteau, Marcel
    Droster, Alexander
    Dunne, Katherine
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC).
    Rosso, Andrea Gallo
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC).
    Gudmundsson, Jón E.
    Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC). Stockholm University, Faculty of Science, Department of Physics. University of Iceland, Iceland .
    Jackson, Heather
    Kaur, Gagandeep
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC). Indian Institute of Technology Kanpur, India.
    Klaesson, Tove
    Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC). Stockholm University, Faculty of Science, Department of Physics.
    Kowitt, Nolan
    Lawson, Matthew
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC). Stockholm University, Nordic Institute for Theoretical Physics (Nordita).
    Leder, Alexander
    Miyazaki, Akira
    Morampudi, Sid
    Peiris, Hiranya V.
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC). University College London, United Kingdom.
    Røising, Henrik S.
    Singh, Gaganpreet
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC).
    Sun, Dajie
    Thomas, Jacob H.
    Wilczek, Frank
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC). MIT, USA; Shanghai Jiao Tong University, China; Arizona State University, USA.
    Withington, Stafford
    Wooten, Mackenzie
    Searching for dark matter with plasma haloscopes2023In: Physical Review D: covering particles, fields, gravitation, and cosmology, ISSN 2470-0010, E-ISSN 2470-0029, Vol. 107, no 5, article id 055013Article in journal (Refereed)
    Abstract [en]

    We summarize the recent progress of the Axion Longitudinal Plasma Haloscope (ALPHA) Consortium, a new experimental collaboration to build a plasma haloscope to search for axions and dark photons. The plasma haloscope is a novel method for the detection of the resonant conversion of light dark matter to photons. ALPHA will be sensitive to QCD axions over almost a decade of parameter space, potentially discovering dark matter and resolving the strong CP problem. Unlike traditional cavity haloscopes, which are generally limited in volume by the Compton wavelength of the dark matter, plasma haloscopes use a wire metamaterial to create a tuneable artificial plasma frequency, decoupling the wavelength of light from the Compton wavelength and allowing for much stronger signals. We develop the theoretical foundations of plasma haloscopes and discuss recent experimental progress. Finally, we outline a baseline design for ALPHA and show that a full-scale experiment could discover QCD axions over almost a decade of parameter space.

  • 33.
    Mortlock, Daniel J.
    et al.
    Stockholm University, Faculty of Science, Department of Astronomy. Imperial College London, United Kingdom.
    Feeney, Stephen M.
    Peiris, Hiranya V.
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC). University College London, United Kingdom.
    Williamson, Andrew R.
    Nissanke, Samaya M.
    Unbiased Hubble constant estimation from binary neutron star mergers2019In: Physical Review D: covering particles, fields, gravitation, and cosmology, ISSN 2470-0010, E-ISSN 2470-0029, Vol. 100, no 10, article id 103523Article in journal (Refereed)
    Abstract [en]

    Gravitational-wave (GW) observations of binary neutron star (BNS) mergers can be used to measure luminosity distances and hence, when coupled with estimates for the mergers' host redshifts, infer the Hubble constant H-0. These observations are, however, affected by GW measurement noise, uncertainties in host redshifts and peculiar velocities, and are potentially biased by selection effects and the misspecification of the cosmological model or the BNS population. The estimation of H-0 from samples of BNS mergers with optical counterparts is tested here by using a phenomenological model for the GW strains that captures both the data-driven event selection and the distance-inclination degeneracy, while being simple enough to facilitate large numbers of simulations. A rigorous Bayesian approach to analyzing the data from such simulated BNS merger samples is shown to yield results that are unbiased, have the appropriate uncertainties, and arc robust to model misspecification. Applying such methods to a sample of N similar or equal to 50 BNS merger events, as LIGO + Virgo could produce in the next similar to 5 years, should yield robust and accurate Hubble constant estimates that are precise to a level of less than or similar to 2 km s(-1) Mpc(-1), sufficient to reliably resolve the current tension between local and cosmological measurements of H-0.

  • 34. Pedersen, Christian
    et al.
    Font-Ribera, Andreu
    Rogers, Keir K.
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC). University of Toronto, Canada.
    McDonald, Patrick
    Peiris, Hiranya V.
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC). University College London, United Kingdom.
    Pontzen, Andrew
    Slosar, Anže
    An emulator for the Lyman-α forest in beyond-ΛCDM cosmologies2021In: Journal of Cosmology and Astroparticle Physics, E-ISSN 1475-7516, no 5, article id 033Article in journal (Refereed)
    Abstract [en]

    Interpreting observations of the Lyman-alpha forest flux power spectrum requires interpolation between a small number of expensive simulations. We present a Gaussian process emulator modelling the 1D flux power spectrum as a function of the amplitude and slope of the small-scale linear matter power spectrum, and the state of the intergalactic medium at the epoch of interest (2 < z < 4). This parameterisation enables the prediction of the flux power spectrum in extended cosmological models that are not explicitly included in the training set, eliminating the need to construct bespoke emulators for a number of extensions to Lambda CDM. Our emulator is appropriate for cosmologies in which the linear matter power spectrum is described to percent level accuracy by just an amplitude and slope across the epoch of interest, and in the regime probed by eBOSS/DESI data. We demonstrate this for massive neutrino cosmologies, where the emulator is able to predict the flux power spectrum in a Sigma m(nu) = 0.3 eV neutrino cosmology to sub-percent accuracy, without including massive neutrinos in the training simulations. Further parameters would be required to describe models with sharp features in the linear power, such as warm or light axion dark matter. This work will facilitate the combination of upcoming DESI data with observations of the cosmic microwave background, to obtain constraints on neutrino mass and other extensions to Lambda CDM cosmology.

  • 35. Piras, Davide
    et al.
    Peiris, Hiranya V
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC). Department of Physics & Astronomy, University College London, United Kingdom.
    Pontzen, Andrew
    Lucie-Smith, Luisa
    Guo, Ningyuan
    Nord, Brian
    A robust estimator of mutual information for deep learning interpretability2023In: Machine Learning: Science and Technology, E-ISSN 2632-2153, Vol. 4, no 2, article id 025006Article in journal (Refereed)
    Abstract [en]

    We develop the use of mutual information (MI), a well-established metric in information theory, to interpret the inner workings of deep learning (DL) models. To accurately estimate MI from a finite number of samples, we present GMM-MI (pronounced 'Jimmie'), an algorithm based on Gaussian mixture models that can be applied to both discrete and continuous settings. GMM-MI is computationally efficient, robust to the choice of hyperparameters and provides the uncertainty on the MI estimate due to the finite sample size. We extensively validate GMM-MI on toy data for which the ground truth MI is known, comparing its performance against established MI estimators. We then demonstrate the use of our MI estimator in the context of representation learning, working with synthetic data and physical datasets describing highly non-linear processes. We train DL models to encode high-dimensional data within a meaningful compressed (latent) representation, and use GMM-MI to quantify both the level of disentanglement between the latent variables, and their association with relevant physical quantities, thus unlocking the interpretability of the latent representation. We make GMM-MI publicly available in this GitHub repository.

  • 36. Pyne, Susan
    et al.
    Joachimi, Benjamin
    Peiris, Hiranya V.
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC). University College London, U.K..
    Weak lensing deflection of three-point correlation functions2017In: Journal of Cosmology and Astroparticle Physics, E-ISSN 1475-7516, no 12, article id 043Article in journal (Refereed)
    Abstract [en]

    Weak gravitational lensing alters the apparent separations between observed sources, potentially affecting clustering statistics. We derive a general expression for the lensing deflection which is valid for any three-point statistic, and investigate its effect on the three-point clustering correlation function. We find that deflection of the clustering correlation function is greatest at around z = 2. It is most prominent in regions where the correlation function varies rapidly, in particular at the baryon acoustic oscillation scale where it smooths out the peaks and troughs, reducing the peak-to-trough difference by about 0.1 percent at z = 1 and around 2.3 percent at z = 10. The modification due to lensing deflection is typically at the per cent level of the expected errors in a Euclid-like survey and therefore undetectable.

  • 37.
    Rogers, Keir K.
    et al.
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC). University College London, UK.
    Bird, Simeon
    Peiris, Hiranya V.
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC). University College London, UK.
    Pontzen, Andrew
    Font-Ribera, Andreu
    Leistedt, Boris
    Correlations in the three-dimensional Lyman-alpha forest contaminated by high column density absorbers2018In: Monthly notices of the Royal Astronomical Society, ISSN 0035-8711, E-ISSN 1365-2966, Vol. 476, no 3, p. 3716-3728Article in journal (Refereed)
    Abstract [en]

    Correlations measured in three dimensions in the Lyman-alpha forest are contaminated by the presence of the damping wings of high column density (HCD) absorbing systems of neutral hydrogen (H I; having column densities N(H I) > 1.6 x 10(17) atoms cm(-2)), which extend significantly beyond the redshift-space location of the absorber. We measure this effect as a function of the column density of the HCD absorbers and redshift by measuring threedimensional (3D) flux power spectra in cosmological hydrodynamical simulations from the Illustris project. Survey pipelines exclude regions containing the largest damping wings. We find that, even after this procedure, there is a scale-dependent correction to the 3D Lyman alpha forest flux power spectrum from residual contamination. We model this residual using a simple physical model of the HCD absorbers as linearly biased tracers of the matter density distribution, convolved with their Voigt profiles and integrated over the column density distribution function. We recommend the use of this model over existing models used in data analysis, which approximate the damping wings as top-hats and so miss shape information in the extended wings. The simple 'linear Voigt model' is statistically consistent with our simulation results for a mock residual contamination up to small scales (vertical bar k vertical bar < 1 h Mpc(-1)). It does not account for the effect of the highest column density absorbers on the smallest scales (e.g. vertical bar k vertical bar > 0.4 h Mpc(-1) for small damped Lyman-alpha absorbers; HCD absorbers with N(H-I) similar to 10(21) atoms cm(-2)). However, these systems are in any case preferentially removed from survey data. Our model is appropriate for an accurate analysis of the baryon acoustic oscillations feature. It is additionally essential for reconstructing the full shape of the 3D flux power spectrum.

  • 38. Rogers, Keir K.
    et al.
    Bird, Simeon
    Peiris, Hiranya V.
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC). University College London, UK.
    Pontzen, Andrew
    Font-Ribera, Andreu
    Leistedt, Boris
    Simulating the effect of high column density absorbers on the one-dimensional Lyman alpha forest flux power spectrum2018In: Monthly notices of the Royal Astronomical Society, ISSN 0035-8711, E-ISSN 1365-2966, Vol. 474, no 3, p. 3032-3042Article in journal (Refereed)
    Abstract [en]

    We measure the effect of high column density absorbing systems of neutral hydrogen (H I) on the one-dimensional (1D) Lyman alpha forest flux power spectrum using cosmological hydrodynamical simulations from the Illustris project. High column density absorbers (which we define to be those with HI column densities N(H I) > 1.6 x 10(17) atoms cm(-2)) cause broadened absorption lines with characteristic damping wings. These damping wings bias the 1D Lyman alpha forest flux power spectrum by causing absorption in quasar spectra away from the location of the absorber itself. We investigate the effect of high column density absorbers on the Lyman alpha forest using hydrodynamical simulations for the first time. We provide templates as a function of column density and redshift, allowing the flexibility to accurately model residual contamination, i.e. if an analysis selectively clips out the largest damping wings. This flexibility will improve cosmological parameter estimation, for example, allowing more accurate measurement of the shape of the power spectrum, with implications for cosmological models containing massive neutrinos or a running of the spectral index. We provide fitting functions to reproduce these results so that they can be incorporated straightforwardly into a data analysis pipeline.

  • 39. Rogers, Keir K.
    et al.
    Dvorkin, Cora
    Peiris, Hiranya
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC). University College London, UK.
    Limits on the Light Dark Matter–Proton Cross Section from Cosmic Large-Scale Structure2022In: Physical Review Letters, ISSN 0031-9007, E-ISSN 1079-7114, Vol. 128, no 17, article id 171301Article in journal (Refereed)
    Abstract [en]

    We set the strongest limits to date on the velocity-independent dark matter (DM)–proton cross section σ for DM masses m=10  keV to 100 GeV, using large-scale structure traced by the Lyman-alpha forest: e.g., a 95% lower limit σ<6×10−30  cm2, for m=100  keV. Our results complement direct detection, which has limited sensitivity to sub-GeV DM. We use an emulator of cosmological simulations, combined with data from the smallest cosmological scales used to date, to model and search for the imprint of primordial DM–proton collisions. Cosmological bounds are improved by up to a factor of 25.

  • 40.
    Rogers, Keir K.
    et al.
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC).
    Peiris, Hiranya V.
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC). University College London, UK.
    General framework for cosmological dark matter bounds using N-body simulations2021In: Physical Review D: covering particles, fields, gravitation, and cosmology, ISSN 2470-0010, E-ISSN 2470-0029, Vol. 103, no 4, article id 043526Article in journal (Refereed)
    Abstract [en]

    We present a general framework for obtaining robust bounds on the nature of dark matter using cosmological N-body simulations and Lyman-alpha forest data. We construct an emulator of hydrodynamical simulations, which is a flexible, accurate and computationally efficient model for predicting the response of the Lyman-alpha forest flux power spectrum to different dark matter models, the state of the intergalactic medium (IGM) and the primordial power spectrum. The emulator combines a flexible parametrization for the small-scale suppression in the matter power spectrum arising in noncold dark matter models, with an improved IGM model. We then demonstrate how to optimize the emulator for the case of ultralight axion dark matter, presenting tests of convergence. We also carry out cross-validation tests of the accuracy of flux power spectrum prediction. This framework can be optimized for the analysis of many other dark matter candidates, e.g., warm or interacting dark matter. Our work demonstrates that a combination of an optimized emulator and cosmological effective theories, where many models are described by a single set of equations, is a powerful approach for robust and computationally efficient inference from the cosmic large-scale structure.

  • 41.
    Rogers, Keir K.
    et al.
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC).
    Peiris, Hiranya V.
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC). University College London, United Kingdom.
    Strong Bound on Canonical Ultralight Axion Dark Matter from the Lyman-Alpha Forest2021In: Physical Review Letters, ISSN 0031-9007, E-ISSN 1079-7114, Vol. 126, no 7, article id 071302Article in journal (Refereed)
    Abstract [en]

    We present a new bound on the ultralight axion (ULA) dark matter mass m(a), using the Lyman-alpha forest to look for suppressed cosmic structure growth: a 95% lower limit m(a) > 2 x 10(-20) eV. This strongly disfavors (>99.7% credibility) the canonical ULA with 10(-22) eV < m(a) < 10(-21) eV, motivated by the string axiverse and solutions to possible tensions in the cold dark matter model. We strengthen previous equivalent bounds by about an order of magnitude. We demonstrate the robustness of our results using an optimized emulator of improved hydrodynamical simulations.

  • 42.
    Rogers, Keir K.
    et al.
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC).
    Peiris, Hiranya V.
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC). University College London, U.K.
    Pontzen, Andrew
    Bird, Simeon
    Verde, Licia
    Font-Ribera, Andreu
    Bayesian emulator optimisation for cosmology: application to the Lyman-alpha forest2019In: Journal of Cosmology and Astroparticle Physics, E-ISSN 1475-7516, no 2, article id 031Article in journal (Refereed)
    Abstract [en]

    The Lyman-alpha forest provides strong constraints on both cosmological parameters and intergalactic medium astrophysics, which are forecast to improve further with the next generation of surveys including eBOSS and DESI. As is generic in cosmological inference, extracting this information requires a likelihood to be computed throughout a high-dimensional parameter space. Evaluating the likelihood requires a robust and accurate mapping between the parameters and observables, in this case the 1D flux power spectrum. Cosmological simulations enable such a mapping, but due to computational time constraints can only be evaluated at a handful of sample points; emulators are designed to interpolate between these. The problem then reduces to placing the sample points such that an accurate mapping is obtained while minimising the number of expensive simulations required. To address this, we introduce an emulation procedure that employs Bayesian optimisation of the training set for a Gaussian process interpolation scheme. Starting with a Latin hypercube sampling (other schemes with good space-filling properties can be used), we iteratively augment the training set with extra simulations at new parameter positions which balance the need to reduce interpolation error while focussing on regions of high likelihood. We show that smaller emulator error from the Bayesian optimisation propagates to smaller widths on the posterior distribution. Even with fewer simulations than a Latin hypercube, Bayesian optimisation shrinks the 95% credible volume by 90% and, e.g., the 1 sigma error on the amplitude of small-scale primordial fluctuations by 38%. This is the first demonstration of Bayesian optimisation applied to large-scale structure emulation, and we anticipate the technique will generalise to many other probes such as galaxy clustering, weak lensing and 21cm.

  • 43.
    Setzer, Christian N.
    et al.
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC).
    Biswas, Rahul
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC).
    Peiris, Hiranya V.
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC). University College London, UK.
    Rosswog, Stephan
    Stockholm University, Faculty of Science, Department of Astronomy. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC).
    Korobkin, Oleg
    Wollaeger, Ryan T.
    Serendipitous discoveries of kilonovae in the LSST main survey: maximizing detections of sub-threshold gravitational wave events2019In: Monthly notices of the Royal Astronomical Society, ISSN 0035-8711, E-ISSN 1365-2966, Vol. 485, no 3, p. 4260-4273Article in journal (Refereed)
    Abstract [en]

    We investigate the ability of the Large Synoptic Survey Telescope (LSST) to discover kilonovae (kNe) from binary neutron star (BNS) and neutron star-black hole (NSBH) mergers, focusing on serendipitous detections in the Wide-Fast-Deep (WFD) survey. We simulate observations of kNe with proposed LSST survey strategies, focusing on cadence choices that are compatible with the broader LSST cosmology programme. If all kNe are identical to GW170817, we find the baseline survey strategy will yield 58 kNe over the survey lifetime. If we instead assume a representative population model of BNS kNe, we expect to detect only 27 kNe. However, we find the choice of survey strategy significantly impacts these numbers and can increase them to 254 and 82 kNe over the survey lifetime, respectively. This improvement arises from an increased cadence of observations between different filters with respect to the baseline. We then consider the detectability of these BNS mergers by the Advanced LIGO/Virgo (ALV) detector network. If the optimal survey strategy is adopted, 202 of the GW170817-like kNe and 56 of the BNS population model kNe are detected with LSST but are below the threshold for detection by the ALV network. This represents, for both models, an increase by a factor greater than 4.5 in the number of detected sub-threshold events over the baseline strategy. These subthreshold events would provide an opportunity to conduct electromagnetic-triggered searches for signals in gravitational-wave data and assess selection effects in measurements of the Hubble constant from standard sirens, e.g. viewing angle effects.

  • 44.
    Setzer, Christian N.
    et al.
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC).
    Peiris, Hiranya V.
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC). University College London, UK.
    Korobkin, Oleg
    Rosswog, Stephan
    Stockholm University, Faculty of Science, Department of Astronomy. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC).
    Modelling populations of kilonovae2023In: Monthly notices of the Royal Astronomical Society, ISSN 0035-8711, E-ISSN 1365-2966, Vol. 520, no 2, p. 2829-2842Article in journal (Refereed)
    Abstract [en]

    The 2017 detection of a kilonova coincident with gravitational-wave emission has identified neutron star mergers as the major source of the heaviest elements and dramatically constrained alternative theories of gravity. Observing a population of such sources has the potential to transform cosmology, nuclear physics, and astrophysics. However, with only one confident multi-messenger detection currently available, modelling the diversity of signals expected from such a population requires improved theoretical understanding. In particular, models that are quick to evaluate and are calibrated with more detailed multi-physics simulations are needed to design observational strategies for kilonovae detection and to obtain rapid-response interpretations of new observations. We use grey-opacity models to construct populations of kilonovae, spanning ejecta parameters predicted by numerical simulations. Our modelling focuses on wavelengths relevant for upcoming optical surveys, such as the Rubin Observatory Legacy Survey of Space and Time (LSST). In these simulations, we implement heating rates that are based on nuclear reaction network calculations. We create a Gaussian-process emulator for kilonova grey opacities, calibrated with detailed radiative transfer simulations. Using recent fits to numerical relativity simulations, we predict how the ejecta parameters from binary neutron star (BNS) mergers shape the population of kilonovae, accounting for the viewing-angle dependence. Our simulated population of BNS mergers produce peak i-band absolute magnitudes of −20 ≤ Mi ≤ −11. A comparison with detailed radiative transfer calculations indicates that further improvements are needed to accurately reproduce spectral shapes over the full light curve evolution. 

  • 45. Sooknunan, K.
    et al.
    Lochner, M.
    Bassett, Bruce A.
    Peiris, Hiranya V.
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC). University College London, United Kingdom.
    Fender, R.
    Stewart, A. J.
    Pietka, M.
    Woudt, P. A.
    McEwen, J. D.
    Lahav, O.
    Classification of multiwavelength transients with machine learning2021In: Monthly notices of the Royal Astronomical Society, ISSN 0035-8711, E-ISSN 1365-2966, Vol. 502, no 1, p. 206-224Article in journal (Refereed)
    Abstract [en]

    With the advent of powerful telescopes such as the Square Kilometer Array and the Vera C. Rubin Observatory, we are entering an era of multiwavelength transient astronomy that will lead to a dramatic increase in data volume. Machine learning techniques are well suited to address this data challenge and rapidly classify newly detected transients. We present a multiwavelength classification algorithm consisting of three steps: (1) interpolation and augmentation of the data using Gaussian processes; (2) feature extraction using wavelets; and (3) classification with random forests. Augmentation provides improved performance at test time by balancing the classes and adding diversity into the training set. In the first application of machine learning to the classification of real radio transient data, we apply our technique to the Green Bank Interferometer and other radio light curves. We find we are able to accurately classify most of the 11 classes of radio variables and transients after just eight hours of observations, achieving an overall test accuracy of 78 per cent. We fully investigate the impact of the small sample size of 82 publicly available light curves and use data augmentation techniques to mitigate the effect. We also show that on a significantly larger simulated representative training set that the algorithm achieves an overall accuracy of 97 per cent, illustrating that the method is likely to provide excellent performance on future surveys. Finally, we demonstrate the effectiveness of simultaneous multiwavelength observations by showing how incorporating just one optical data point into the analysis improves the accuracy of the worst performing class by 19 per cent.

  • 46. Stopyra, Stephen
    et al.
    Peiris, Hiranya
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC). University College London, UK.
    Pontzen, Andrew
    Jasche, Jens
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC).
    Natarajan, Priyamvada
    Quantifying the rarity of the local super-volume2021In: Monthly notices of the Royal Astronomical Society, ISSN 0035-8711, E-ISSN 1365-2966, Vol. 507, no 4, p. 5425-5431Article in journal (Refereed)
    Abstract [en]

    We investigate the extent to which the number of clusters of mass exceeding 1015 M h−1 within the local super-volume(< 135 Mpc h−1) is compatible with the standard CDM cosmological model. Depending on the mass estimator used, we findthat the observed number N of such massive structures can vary between 0 and 5. Adopting N = 5 yields CDM likelihoods aslow as 2.4 × 10−3 (with σ 8 = 0.81) or 3.8 × 10−5 (with σ 8 = 0.74). However, at the other extreme (N = 0), the likelihood is oforder unity. Thus, while potentially very powerful, this method is currently limited by systematic uncertainties in cluster massestimates. This motivates efforts to reduce these systematics with additional observations and improved modelling.

  • 47. Stopyra, Stephen
    et al.
    Peiris, Hiranya V.
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC). University College London, UK.
    Pontzen, Andrew
    How to build a catalogue of linearly evolving cosmic voids2021In: Monthly notices of the Royal Astronomical Society, ISSN 0035-8711, E-ISSN 1365-2966, Vol. 500, no 3, p. 4173-4180Article in journal (Refereed)
    Abstract [en]

    Cosmic voids provide a powerful probe of the origin and evolution of structures in the Universe because their dynamics can remain near-linear to the present day. As a result, they have the potential to connect large-scale structure at late times to early Universe physics. Existing 'watershed'-based algorithms, however, define voids in terms of their morphological properties at low redshift. The degree to which the resulting regions exhibit linear dynamics is consequently uncertain, and there is no direct connection to their evolution from the initial density field. A recent void definition addresses these issues by considering 'anti-haloes'. This approach consists of inverting the initial conditions of an N-body simulation to swap overdensities and underdensities. After evolving the pair of initial conditions, anti-haloes are defined by the particles within the inverted simulation that are inside haloes in the original (uninverted) simulation. In this work, we quantify the degree of non-linearity of both anti-haloes and watershed voids using the Zel'dovich approximation. We find that non-linearities are introduced by voids with radii less than 5 Mpc h(-1), and that both anti-haloes and watershed voids can be made into highly linear sets by removing these voids.

  • 48.
    Stopyra, Stephen
    et al.
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC).
    Peiris, Hiranya V.
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC). University College London, UK.
    Pontzen, Andrew
    Jasche, Jens
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC).
    Lavaux, Guilhem
    Towards accurate field-level inference of massive cosmic structures2023In: Monthly notices of the Royal Astronomical Society, ISSN 0035-8711, E-ISSN 1365-2966, Vol. 527, no 1, p. 1244-1256Article in journal (Refereed)
    Abstract [en]

    We investigate the accuracy requirements for field-level inference of cluster and void masses using data from galaxy surveys. We introduce a two-step framework that takes advantage of the fact that cluster masses are determined by flows on larger scales than the clusters themselves. First, we determine the integration accuracy required to perform field-level inference of cosmic initial conditions on these large scales by fitting to late-time galaxy counts using the Bayesian Origin Reconstruction from Galaxies (BORG) algorithm. A 20-step COLA integrator is able to accurately describe the density field surrounding the most massive clusters in the local super-volume (⁠<135ℎ−1Mpc⁠), but does not by itself lead to converged virial mass estimates. Therefore, we carry out ‘posterior resimulations’, using full N-body dynamics while sampling from the inferred initial conditions, and thereby obtain estimates of masses for nearby massive clusters. We show that these are in broad agreement with existing estimates, and find that mass functions in the local super-volume are compatible with ΛCDM.

  • 49. Stopyra, Stephen
    et al.
    Pontzen, Andrew
    Peiris, Hiranya
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC). University College London, UK.
    Roth, Nina
    Rey, Martin P.
    GenetIC—A New Initial Conditions Generator to Support Genetically Modified Zoom Simulations2021In: Astrophysical Journal Supplement Series, ISSN 0067-0049, E-ISSN 1538-4365, Vol. 252, no 2, article id 28Article in journal (Refereed)
    Abstract [en]

    We present genetIC, a new code for generating initial conditions for cosmological N-body simulations. The code allows precise, user-specified alterations to be made to arbitrary regions of the simulation (while maintaining consistency with the statistical ensemble). These genetic modifications allow, for example, the history, mass, or environment of a target halo to be altered in order to study the effect on their evolution. The code natively supports initial conditions with nested zoom regions at progressively increasing resolution. Modifications in the high-resolution region must propagate self-consistently onto the lower-resolution grids; to enable this while maintaining a small memory footprint, we introduce a Fourier-space filtering approach to generating fields at variable resolution. Due to a close correspondence with modifications, constrained initial conditions can also be produced by genetIC (for example, with the aim of matching structures in the local universe). We test the accuracy of modifications performed within zoom initial conditions. The code achieves subpercent precision, which is easily sufficient for current applications in galaxy formation.

  • 50. Traykova, Dina
    et al.
    Braden, Jonathan
    Peiris, Hiranya V.
    Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC). University College London, UK.
    Accretion of a symmetry-breaking scalar field by a Schwarzschild black hole2018In: Philosophical Transactions. Series A: Mathematical, physical, and engineering science, ISSN 1364-503X, E-ISSN 1471-2962, Vol. 376, no 2114, article id 20170122Article in journal (Refereed)
    Abstract [en]

    We simulate the behaviour of a Higgs-like field in the vicinity of a Schwarzschild black hole using a highly accurate numerical framework. We consider both the limit of the zero-temperature Higgs potential and a toy model for the time-dependent evolution of the potential when immersed in a slowly cooling radiation bath. Through these numerical investigations, we aim to improve our understanding of the non-equilibrium dynamics of a symmetry-breaking field (such as the Higgs) in the vicinity of a compact object such as a black hole. Understanding this dynamics may suggest new approaches for studying properties of scalar fields using black holes as a laboratory. This article is part of the Theo Murphy meeting issue 'Higgs Cosmology'.

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