Article
Astronomy & Astrophysics
Azadeh Moradinezhad Dizgah, Matteo Biagetti, Emiliano Sefusatti, Vincent Desjacques, Jorge Norena
Summary: Upcoming galaxy redshift surveys are expected to improve limits on primordial non-Gaussianity (PNG) through measurements in Fourier space. A Monte-Carlo Markov Chain analysis was performed to confront perturbation theory predictions with N-body simulations, focusing on the local model of PNG parameterized by f(NL). Informative priors on the linear non-Gaussian bias parameter can significantly improve constraints on f(NL) in statistical inference.
JOURNAL OF COSMOLOGY AND ASTROPARTICLE PHYSICS
(2021)
Article
Astronomy & Astrophysics
Matteo Biagetti, Alex Cole, Gary Shiu
Summary: The study presents an analysis pipeline utilizing persistent homology to characterize the topology of large scale structure and extract cosmological constraints. By examining the impact of primordial local non-Gaussianity on dark matter halo distribution through N-body simulations, they detected non-zero f(NL)(loc) on multiple cubic volumes. The method effectively addresses degeneracies between different topological signatures and provides interpretable statistics for both reproducing previous results and making new predictions.
JOURNAL OF COSMOLOGY AND ASTROPARTICLE PHYSICS
(2021)
Article
Astronomy & Astrophysics
Daniel Baumann, Daniel Green
Summary: This paper discusses the impact of nonlinear structure formation on the study of primordial non-Gaussianity and proposes a method to measure non-Gaussianity in the position space maps of the large-scale structure. The study shows that map-level analysis can significantly improve the constraining power over non-Gaussianity.
JOURNAL OF COSMOLOGY AND ASTROPARTICLE PHYSICS
(2022)
Article
Astronomy & Astrophysics
Raphael Sgier, Janis Fluri, Jorg Herbel, Alexandre Refregier, Adam Amara, Tomasz Kacprzak, Andrina Nicola
Summary: The extension of the UFALCON lightcone generator allows for the simulation of a self-consistent set of maps for different cosmological probes, providing more accurate multi-probe covariance matrix for forecasting cosmological parameter constraints in the future.
JOURNAL OF COSMOLOGY AND ASTROPARTICLE PHYSICS
(2021)
Article
Astronomy & Astrophysics
Jaiyul Yoo, Nastassia Grimm, Ermis Mitsou
Summary: This study investigates the three-point correlation function of observed matter density fluctuations in a squeezed triangular configuration in a Lambda CDM universe under a single-field inflationary scenario. The study finds that the theoretical descriptions of galaxy bias in general relativity are incomplete due to ambiguities in spatial gauge choice, and a proper relativistic description of galaxy bias is needed for definitive conclusions in galaxy clustering. Additionally, it demonstrates that gauge-invariant calculations of cosmological observables are unaffected by extra coordinate transformations and that relativistic effects associated with light propagation cancel each other.
JOURNAL OF COSMOLOGY AND ASTROPARTICLE PHYSICS
(2022)
Article
Astronomy & Astrophysics
Andrei Lazanu
Summary: Machine learning techniques accurately extract cosmological parameters Omega(m) and sigma(8) from N-body simulations, and also find these parameters from the non-linear matter power spectrum using random forest regressors and deep neural networks. The power spectrum provides competitive results in terms of accuracy compared to using simulations, and the scalar spectral index ns can also be estimated from the power spectrum with lower precision.
JOURNAL OF COSMOLOGY AND ASTROPARTICLE PHYSICS
(2021)
Article
Astronomy & Astrophysics
Thomas Floss, Tim de Wild, P. Daniel Meerburg, Leon V. E. Koopmans
Summary: In this study, we investigate the possibility of using tomography of 21-cm brightness temperature fluctuations during the Dark Ages as a means to constrain primordial non-Gaussianity. We improve previous models by including the effect of the free electron fraction and derive the secondary bispectrum as well as the secondary trispectrum of 21-cm brightness temperature fluctuations. We find that although secondary non-Gaussianity dominates the signal, primordial non-Gaussianity can still be extracted with significantly higher signal-to-noise ratios than current and future CMB experiments.
JOURNAL OF COSMOLOGY AND ASTROPARTICLE PHYSICS
(2022)
Article
Astronomy & Astrophysics
Benedict Bahr-Kalus, Daniele Bertacca, Licia Verde, Alan Heavens
Summary: In this study, the impact of the observer's motion on the clustering signal in galaxy distribution and the Kaiser rocket effect is examined both analytically and numerically. While the Kaiser rocket effect can significantly bias cosmological parameter inference in idealistic full-sky surveys dominated by cosmic variance, it is not a major concern for forthcoming surveys with realistic masks and selection functions, except for possible implications on primordial non-Gaussianity studies. This systematic effect is well understood and should be accounted for using various approaches.
JOURNAL OF COSMOLOGY AND ASTROPARTICLE PHYSICS
(2021)
Article
Astronomy & Astrophysics
Fabian Schmidt
Summary: A forward model for matter and biased tracers at arbitrary order in Lagrangian perturbation theory is introduced, including complete LPT displacement field and relevant bias operators. Validation tests show subpercent agreement with N-body simulations, demonstrating the effectiveness and accuracy of the model. This method has broad applications in cosmology research.
JOURNAL OF COSMOLOGY AND ASTROPARTICLE PHYSICS
(2021)
Article
Astronomy & Astrophysics
Alexandre Barreira
Summary: The scale-dependent bias effect is a promising way to study the primordial non-Gaussianity parameter f(NL), but our limited knowledge of the linear PNG galaxy bias parameter b(phi) currently prevents us from accurately constraining f(NL).
JOURNAL OF COSMOLOGY AND ASTROPARTICLE PHYSICS
(2022)
Article
Astronomy & Astrophysics
Andrija Kostic, Nhat-Minh Nguyen, Fabian Schmidt, Martin Reinecke
Summary: In this paper, we investigate the performance of field-based forward modeling approach to galaxy clustering using the effective field theory (EFT) framework. By conducting consistency and convergence tests on synthetic datasets, we find that the EFT framework allows for robust, unbiased joint inference of cosmological parameters, initial conditions, and bias and noise parameters even in the presence of model mis-specifications.
JOURNAL OF COSMOLOGY AND ASTROPARTICLE PHYSICS
(2023)
Article
Astronomy & Astrophysics
Alexandre Barreira
Summary: In this study, hydrodynamical separate universe simulations with the IllustrisTNG model were used to predict the local primordial non-Gaussianity (PNG) bias parameters b(phi) and b(phi delta), which play a leading role in the analysis of galaxy power spectrum and bispectrum. It was found that the popular assumption of universality overpredicts the relation between b(phi delta) and linear density bias in the range of 1 ≤ b(1) ≤ 3 for dark matter halos. The study also revealed that the relations between b(phi)(b(1)) and b(phi delta)(b(1)) are redshift-dependent and sensitive to the selection of galaxies. The uncertainties in these bias parameters have a significant impact on the constraints of the local PNG parameter fnl. Moreover, it was shown that priors on galaxy bias are useful even in analyses that fit for products f(NL)b(phi) and f(NL)b(phi delta). The strategies discussed in this study can be implemented in existing f(NL) constraint analyses.
JOURNAL OF COSMOLOGY AND ASTROPARTICLE PHYSICS
(2022)
Article
Astronomy & Astrophysics
Alexandre Barreira, Titouan Lazeyras, Fabian Schmidt
Summary: The study uses field-level forward models of galaxy clustering and EFT likelihood formalism to infer the relations between linear bias parameters (b(1), b(2), b(K2)) in self-consistently simulated galaxies. It finds that bias relations in total mass selected objects are broadly preserved in simulated galaxies selected by various characteristics, and shows good agreement with observed galaxy samples. The use of EFT likelihood also recovers sigma(8) values from different galaxy samples, demonstrating the potential of forward models in inferring cosmological information from galaxy data.
JOURNAL OF COSMOLOGY AND ASTROPARTICLE PHYSICS
(2021)
Article
Astronomy & Astrophysics
Alessandra Fumagalli, Matteo Biagetti, Alex Saro, Emiliano Sefusatti, Anze Slosar, Pierluigi Monaco, Alfonso Veropalumbo
Summary: In cosmological data analysis, reliable covariance matrices are required, which often necessitate a large number of simulations for accuracy. However, when a theoretical model for the covariance matrix exists, fewer simulations can be used to fit the model parameters. This study presents a likelihood-based method for such fitting and tests the model covariance matrix by examining the appropriate X-2 distributions from simulations. By combining these steps, reliable covariances can be produced without a large number of simulations.
JOURNAL OF COSMOLOGY AND ASTROPARTICLE PHYSICS
(2022)
Article
Astronomy & Astrophysics
Cristiano G. Sabiu, Kenji Kadota, Jacobo Asorey, Inkyu Park
Summary: We present forecasts on the detectability of Ultra-light axion-like particles (ULAP) from future 21 cm radio observations during the epoch of reionization (EoR). The study shows that the presence of axions as the dominant dark matter component has a significant impact on the reionization history. Using numerical simulations and a convolutional neural network, the research successfully predicts the input axion mass from mock observations, even in the presence of noise and resolution constraints.
JOURNAL OF COSMOLOGY AND ASTROPARTICLE PHYSICS
(2022)