arXiv subjects

Eleni Tsaprazi

Publications and source records attributed to Eleni Tsaprazi.

11 recordsLinked to original sources

arXiv2026

Differentiable Forward Modeling for Efficient and Accurate Shear Inference

Forthcoming Stage-IV dark energy optical surveys, such as LSST, have the ambitious goal of measuring cosmological parameters at sub-percent precision. Realizing their full scientific potential requires very precise measurement of the cosmic shear signal and control of corresponding systematics. In this work, we present a modern implementation of the Bayesian shear inference framework in Schneider et al. (2015), in the case that the PSF and sky background are known. This framework automatically propagates the pixel-noise measurement error from each galaxy into the final shear estimate, and thus requires no external calibration to handle noise bias. As a first application of this new implementation, we infer the cosmic shear posterior from simulated images consisting of isolated exponential galaxies with semi-realistic noise levels. In this simplified scenario, we estimate the absolute multiplicative bias $|m|$ of our approach to be below $0.9 \times 10^{-3}\,[3σ]$ when the intrinsic distribution of galaxy properties is known, and below $1.3 \times 10^{-3}\,[3σ]$ when these distributions are inferred alongside shear. Additionally, we make progress towards the algorithm's computational feasibility in the context of modern wide-field surveys, where billions of galaxies must be processed, by leveraging differentiable forward models of galaxies, gradient-based samplers, and GPUs. Our final galaxy-fitting MCMC produces $300$ effective samples of galaxy properties in $0.45$ seconds per galaxy using a single A100 GPU. In the future, we seek to generalize our algorithm to handle selection, detection, and model shear biases so it can be applied to real survey data.

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arXiv2026

Cluster gravitational redshifts: uncertainties and survey requirements

We investigate the impact of observational and theoretical uncertainties in cluster gravitational redshifts as a probe of modified gravity using an end-to-end forecasting pipeline. We use a generative model to build a halo catalogue with $M_{500}\ge 3\times 10^{13}\,M_\odot$, populate haloes with member galaxies via a five-parameter halo occupation distribution (HOD), assign projected positions from radial density profiles, apply survey-like selections, and infer a linear rescaling of the gravitational potential, $α_\mathrm{MG}$, to parameterise modifications to general relativity (GR). We vary redshift uncertainties, radial and mass-redshift completeness, member abundance, minimum mass and maximum redshift, as well as mis-specify the clusters density and velocity profiles, centres, and mass function. We find that the intracluster velocity dispersion sets an effective floor: improving redshift precision beyond $σ_z\sim 10^{-4}(1+z)$ brings no improvement in the precision of $α_\mathrm{MG}$. Realistic redshift and mass cuts primarily remove low-mass haloes and have minimal impact on the $α_\mathrm{MG}$ precision. In this setting, we find that shallow, narrower spectroscopic surveys are preferable to deep, wide photometric ones for precise modified gravity constraints. We further find that mis-centring can mimic significant departures from GR. Baryonic deviations from a Navarro-Frenk-White profile and velocity anisotropies do not introduce appreciable biases. In the high-S/N regime of upcoming surveys, accurate determination of cluster centres will be essential to avoid interpreting systematic effects as new physics. The Spectroscopic Stage-5 Experiment and the Widefield Spectroscopic Telescope provide a clear route toward establishing gravitational redshifts as a competitive probe of modified gravity.

astro-ph.CO↗

arXiv2026

Two per cent measurement of $H_0$ from Cepheids alone

One of the most pressing problems in current cosmology is the cause of the Hubble tension. We revisit a two-rung distance ladder, composed only of Cepheid periods and magnitudes, anchor distances in the Milky Way, Large Magellanic Cloud, NGC 4258, and host galaxy redshifts. We adopt the SH0ES data for the most up-to-date and carefully vetted measurements, where the Cepheid hosts were selected to harbour also Type Ia supernovae. We introduce two important improvements: a rigorous selection modelling and a state-of-the-art density and peculiar velocity model using Manticore-Local, based on the Bayesian Origin Reconstruction from Galaxies (BORG) algorithm. We infer $H_0 = 71.1 \pm 1.4~\mathrm{km}\,\mathrm{s}^{-1}\,\mathrm{Mpc}^{-1}$, assuming the Cepheid host sample was selected by supernova magnitudes. However, the actual selection criteria are not clear, and other assumptions can increase $H_0$ by up to one statistical standard deviation. The posterior has a lower central value and a 41 per cent smaller uncertainty than a previous study using the same distance-ladder data. This result is lower than the supernova-based SH0ES inferred value of $H_0 = 73.2 \pm 0.9~\mathrm{km}\,\mathrm{s}^{-1}\,\mathrm{Mpc}^{-1}$ at about $1.3σ$, and is in $2.8σ$ tension with the latest cosmic microwave background results in the standard cosmological model. These results demonstrate that a measurement of $H_0$ of sufficient precision to weigh in on the Hubble tension is achievable using second-rung data alone, underscoring the importance of robust and accurate statistical and velocity-field modelling.

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arXiv2025

Beyond general relativity: probing gravity with gravitational redshifts

Despite the success of general relativity (GR), the unexplained nature of dark energy on cosmological scales leaves open the question of whether GR provides a complete description of gravity. This quest is further motivated by growing tensions among cosmological observations when interpreted within $Λ$CDM. Gravitational redshifts of cluster member galaxies probe cluster potentials on megaparsec scales directly, complementing conventional large-scale structure tests. Here, we investigate how redshift precision and survey design propagate into constraints on modified gravity using an end-to-end pipeline run on mock catalogues, focusing on mis-centring and spectroscopic completeness. We find that competitive measurements require wide-field spectroscopic cluster surveys explicitly designed to maximise the number of spectroscopically confirmed members per cluster, to enable high-purity stacking, and to control systematic effects.

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arXiv2025

Field-level inference of $H_0$ from simulated type Ia supernovae in a local Universe analogue

Two particular challenges face type Ia supernovae (SNeIa) as probes of the expansion rate of the Universe. One is that they may not be fair tracers of the matter velocity field, and the second is that their peculiar velocities distort the Hubble expansion. Although the latter has been estimated at $\lesssim1.5\%$ for $z>0.023$, this is based either on constrained linear or unconstrained (random) non-linear velocity simulations. In this paper, we address both challenges by incorporating a physical model for the locations of supernovae, and develop a Bayesian Hierarchical Model that accounts for non-linear peculiar velocities in our local Universe, inferred from a Bayesian analysis of the 2M++ spectroscopic galaxy catalogue. With simulated data, the model recovers the ground truth value of the Hubble constant $H_0$ in the presence of peculiar velocities including their correlated uncertainties arising from the Bayesian inference, opening up the potential of including lower redshift SNeIa to measure $H_0$. Ignoring peculiar velocities, the inferred $H_0$ increases minimally by $\sim 0.4 \pm 0.5$ km s$^{-1}$ Mpc$^{-1}$ in the range $0.023<z<0.046$. We conclude it is unlikely that the $H_0$ tension originates in unaccounted-for non-linear velocity dynamics.

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arXiv2024

The IA Guide: A Breakdown of Intrinsic Alignment Formalisms

We summarize common notations and concepts in the field of Intrinsic Alignments (IA). IA refers to physical correlations involving galaxy shapes, galaxy spins, and the underlying cosmic web. Its characterization is an important aspect of modern cosmology, particularly in weak lensing analyses. This resource is both a reference for those already familiar with IA and designed to introduce someone to the field by drawing from various studies and presenting a collection of IA formalisms, estimators, modeling approaches, alternative notations, and useful references.

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arXiv2023

LyAl-Net: A high-efficiency Lyman-$α$ forest simulation with a neural network

The inference of cosmological quantities requires accurate and large hydrodynamical cosmological simulations. Unfortunately, their computational time can take millions of CPU hours for a modest coverage in cosmological scales ($\approx (100 {h^{-1}}\,\text{Mpc})^3)$). The possibility to generate large quantities of mock Lyman-$α$ observations opens up the possibility of much better control on covariance matrices estimate for cosmological parameters inference, and on the impact of systematics due to baryonic effects. We present a machine learning approach to emulate the hydrodynamical simulation of intergalactic medium physics for the Lyman-$α$ forest called LyAl-Net. The main goal of this work is to provide highly efficient and cheap simulations retaining interpretation abilities about the gas field level, and as a tool for other cosmological exploration. We use a neural network based on the U-net architecture, a variant of convolutional neural networks, to predict the neutral hydrogen physical properties, density, and temperature. We train the LyAl-Net model with the Horizon-noAGN simulation, though using only 9% of the volume. We also explore the resilience of the model through tests of a transfer learning framework using cosmological simulations containing different baryonic feedback. We test our results by analysing one and two-point statistics of emulated fields in different scenarios, as well as their stochastic properties. The ensemble average of the emulated Lyman-$α$ forest absorption as a function of redshift lies within 2.5% of one derived from the full hydrodynamical simulation. The computation of individual fields from the dark matter density agrees well with regular physical regimes of cosmological fields. The results tested on IllustrisTNG100 showed a drastic improvement in the Lyman-$α$ forest flux without arbitrary rescaling.

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arXiv2023

Higher-order statistics of the large-scale structure from photometric redshifts

The large-scale structure is a major source of cosmological information. However, next-generation photometric galaxy surveys will only provide a distorted view of cosmic structures due to large redshift uncertainties. To address the need for accurate reconstructions of the large-scale structure in presence of photometric uncertainties, we present a framework that constrains the three-dimensional dark matter density jointly with galaxy photometric redshift probability density functions (PDFs), exploiting information from galaxy clustering. Our forward model provides Markov Chain Monte Carlo realizations of the primordial and present-day dark matter density, inferred jointly from data. Our method goes beyond 2-point statistics via field-level inference. It accounts for all observational uncertainties and the survey geometry. We showcase our method using mock catalogs that emulate next-generation surveys with a worst-case redshift uncertainty, equivalent to ${\sim}300$ Mpc. On scales $150$ Mpc, we improve the cross-correlation of the photometric galaxy positions with the ground truth from $28\%$ to $86\%$. The improvement is significant down to $13$ Mpc. On scales $150$ Mpc, we achieve a cross-correlation of $80-90\%$ with the ground truth for the dark matter density, radial peculiar velocities, tidal shear and gravitational potential.

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arXiv2022

Field-level inference of galaxy intrinsic alignment from the SDSS-III BOSS survey

As a large-scale overdensity collapses, it affects the orientation and shape of galaxies that form, by exerting tidal shear along their axes. Therefore, the shapes of elliptical galaxies align with the tidal field of cosmic structures. This intrinsic alignment provides insights into galaxy formation and the primordial universe, complements late-time cosmological probes and constitutes a significant systematic effect for weak gravitational lensing observations. In the present study, we provide constraints on the linear alignment model using a fully Bayesian field-level approach, using galaxy shape measurements from the SDSS-III BOSS LOWZ sample and three-dimensional tidal fields constrained with the LOWZ and CMASS galaxy samples of the SDSS-III BOSS survey. We find 4$σ$ evidence of intrinsic alignment, with an amplitude of $A_I=2.9 \pm 0.7$ at 20$h^{-1}\;\mathrm{Mpc}$.

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arXiv2021

The large-scale environment of thermonuclear and core-collapse supernovae

The new generation of wide-field time-domain surveys has made it feasible to study the clustering of supernova (SN) host galaxies in the large-scale structure (LSS) for the first time. We investigate the LSS environment of SN populations, using 106 dark matter density realisations with a resolution of $\sim$ 3.8 Mpc, constrained by the 2M++ galaxy survey. We limit our analysis to redshift $z<0.036$, using samples of 498 thermonuclear and 782 core-collapse SNe from the Zwicky Transient Facility's Bright Transient Survey and Census of the Local Universe catalogues. We detect clustering of SNe with high significance; the observed clustering of the two SNe populations is consistent with each other. Further, the clustering of SN hosts is consistent with that of the Sloan Digital Sky Survey (SDSS) Baryon Oscillation Spectroscopic Survey (BOSS) DR12 spectroscopic galaxy sample in the same redshift range. Using a tidal shear classifier, we classify the LSS into voids, sheets, filaments and knots. We find that both SNe and SDSS galaxies are predominantly found in sheets and filaments. SNe are significantly under-represented in voids and over-represented in knots compared to the volume fraction in these structures. This work opens the potential for using forthcoming wide-field deep SN surveys as a complementary LSS probe.

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arXiv2020

Relativistic approach to the kinematics of large-scale peculiar motions

We consider the linear kinematics of large-scale peculiar motions in a perturbed Friedmann universe. In so doing, we take the viewpoint of the "real" observers that move along with the peculiar flow, relative to the smooth Hubble expansion. Using relativistic cosmological perturbation theory, we study the linear evolution of the peculiar velocity field, as well as the expansion/contraction, the shear and the rotation of the bulk motion. Our solutions show growth rates considerably stronger than those of the earlier treatments, which were mostly Newtonian. On scales near and beyond the Hubble radius, namely at the long-wavelength limit, peculiar velocities are found to grow as $a^2$, in terms of the scale factor, instead of the Newtonian $a^{1/2}$-law. We attribute this to the fact that, in general relativity, the energy flux, triggered here by the peculiar motion of the matter, also contributes to the local gravitational field. In a sense, the bulk flow gravitates, an effect that has been bypassed in related relativistic studies. These stronger growth-rates imply faster peculiar velocities at horizon crossing and higher residual values for the peculiar-velocity field. Alternatively, one could say that our study favours bulk peculiar flows larger and faster than anticipated.

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