arXiv subjects

Juan Calles

Publications and source records attributed to Juan Calles.

6 recordsLinked to original sources

arXiv2025

Primordial non-Gaussianity -- Fast simulations and persistent summary statistics

We investigate the sensitivity of topological and traditional summary statistics to primordial non-Gaussianity (PNG) using two suites of simulations. First, we introduce a new simulation suite for PNG, PNG-pmwd, comprising more than $20{,}000$ halo catalogs that vary individually local and equilateral shapes, together with variations in $\Omega_m$ and $\sigma_8$. Second, we carry out a systematic comparison of topological descriptors, as well as powerspectrum and bispectrum measurements, evaluating their constraining power on both local and equilateral $f_{\rm NL}$ and how this sensitivity varies with halo mass. This dataset enables likelihood-free neural regression of $f_{\rm NL}$ across multiple halo mass bins for a wide range of summary statistics. Third, we assess the transferability of these learned mappings by testing whether models trained on fast pmwd simulations can robustly infer on simulations from the QuijotePNG suite. We find that a combination of simple descriptive statistics of the topological features (PD-statistics) leads to the best performance to constrain equilateral PNG. We observe that the constraining power of these summaries comes from large-mass halos, with small-mass halos adding noise and degrading performance. Similarly, we find that the transferability of the learned mappings, for both topological and powerspectrum plus bispectrum, degrades if small scales or small-mass halos are included.

astro-ph.CO↗

arXiv2024

Cosmology with Persistent Homology: Parameter Inference via Machine Learning

Building upon [2308.02636], we investigate the constraining power of persistent homology on cosmological parameters and primordial non-Gaussianity in a likelihood-free inference pipeline utilizing machine learning. We evaluate the ability of Persistence Images (PIs) to infer parameters, comparing them to the combined Power Spectrum and Bispectrum (PS/BS). We also compare two classes of models: neural-based and tree-based. PIs consistently lead to better predictions compared to the combined PS/BS for parameters that can be constrained, i.e., for $\{\Omega_{\rm m}, \sigma_8, n_{\rm s}, f_{\rm NL}^{\rm loc}\}$. PIs perform particularly well for $f_{\rm NL}^{\rm loc}$, highlighting the potential of persistent homology for constraining primordial non-Gaussianity. Our results indicate that combining PIs with PS/BS provides only marginal gains, indicating that the PS/BS contains little additional or complementary information to the PIs. Finally, we provide a visualization of the most important topological features for $f_{\rm NL}^{\rm loc}$ and for $\Omega_{\rm m}$. This reveals that clusters and voids (0-cycles and 2-cycles) are most informative for $\Omega_{\rm m}$, while $f_{\rm NL}^{\rm loc}$ is additionally informed by filaments (1-cycles).

astro-ph.CO↗

arXiv2022

A Model for the Squeezed Bispectrum in the Non-Linear Regime

We present a model for the squeezed dark matter bispectrum, where the short modes are deep in the non-linear regime. We exploit the consistency relations for large-scale structures combined with a response function approach to write the squeezed bispectrum in terms of a few unknown functions of the short modes. We provide an ansatz for a fitting function for these response functions, checking that the resulting model is reliable when compared to the one-loop squeezed bispectrum. We then test the model against measured bispectra from numerical simulations for short modes ranging between $k \sim 0.1 \, h/$Mpc, and $k \sim 0.7 \, h/$Mpc at redshift $z=0$. To evaluate the goodness of the fit of our model we implement a non-Gaussian covariance and find agreement within $1$-$\sigma$ standard deviation of the simulated data.

astro-ph.CO↗

arXiv2022

Fisher Forecasts for Primordial non-Gaussianity from Persistent Homology

We study the information content of summary statistics built from the multi-scale topology of large-scale structures on primordial non-Gaussianity of the local and equilateral type. We use halo catalogs generated from numerical N-body simulations of the Universe on large scales as a proxy for observed galaxies. Besides calculating the Fisher matrix for halos in real space, we also check more realistic scenarios in redshift space. Without needing to take a distant observer approximation, we place the observer on a corner of the box. We also add redshift errors mimicking spectroscopic and photometric samples. We perform several tests to assess the reliability of our Fisher matrix, including the Gaussianity of our summary statistics and convergence. We find that the marginalized 1-$\sigma$ uncertainties in redshift space are $\Delta f_{\rm NL}^{\rm loc} \sim 16$ and $\Delta f_{\rm NL}^{\rm equi} \sim 41 $ on a survey volume of $1$ $($Gpc$/h)^3$. These constraints are weakly affected by redshift errors. We close by speculating as to how this approach can be made robust against small-scale uncertainties by exploiting (non)locality.

astro-ph.CO↗

arXiv2021

Conformal Isometries and Curvature Collineations of an Impulsive Plane Wave: a distributional approach

By extending the notion of Lie derivative to distribution-valued tensor fields of order $m$, Lie derivatives with respect to $C^k$ vector fields, $k\geqslant m+1$, can be shown to be well defined. Geometric symmetries, definable in terms of these Lie derivatives, can then be considered. In particular, for spacetimes of low regularity, geometric symmetries generated by vector fields of regularity as low as $C^1$ are definable. We find that the conformal algebra of the impulsive plane wave spacetime (with $+$ polarization) described by the continuous Baldwin-Jeffery-Rosen form of the metric has the maximal dimension seven. The curvature of this metric is well defined as a distribution and since this spacetime is Ricci-flat, we show that all the vector fields in the conformal algebra are special curvature collineations. We find also the general form of these last ones. Finally, we find the conformal Killing vector fields of this spacetime when using the distributional Brinkmann form of the metric.

gr-qc↗

arXiv2019

From matter to galaxies: General relativistic bias for the one-loop bispectrum

We write down the Lagrangian bias expansion in general relativity up to 4th order in terms of operators describing the curvature of an early-time hypersurface for comoving observers. They can be easily expanded in synchronous or comoving gauges. This is necessary for the computation of the one-loop halo bispectrum, where relativistic effects can be degenerate with a primordial non-Gaussian signal. Since the bispectrum couples scales, an accurate prediction of the squeezed limit behavior needs to be both non-linear and relativistic. We then evolve the Lagrangian bias operators in time in comoving gauge, obtaining non-local operators analogous to what is known in the Newtonian limit. Finally, we show how to renormalize the bias expansion at an arbitrary time and find that this is crucial in order to cancel unphysical $1/k^2$ divergences in the large-scale power spectrum and bispectrum that could be mistaken for a contamination to the non-Gaussian signal.

astro-ph.CO↗