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20162025
most citedHow Gaussian can our Universe be?

56 citations · 200 across the 11 of their papers we have counts for

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Showing astro-ph.COShow all

10 papers · 1 filter

astro-ph.CO2025★ 1 cited

Non-Gaussian Galaxy Stochasticity and the Noise-Field Formulation

Henrique Rubira, Fabian Schmidt

We revisit the stochastic, or noise, contributions to the galaxy density field within the effective field theory (EFT) of large-scale structure. Starting from the general, all-orde…

astro-ph.CO2025★ 1 cited

Parity Violation in Galaxy Shapes: Primordial Non-Gaussianity

Toshiki Kurita, Drew Jamieson, Eiichiro Komatsu +1

We present a comprehensive study of galaxy intrinsic alignment (IA) as a probe of parity-violating primordial non-Gaussianity (PNG). Within the effective field theory (EFT) framewo…

astro-ph.CO2025

Mixed Dark Matter and Galaxy Clustering: The Importance of Relative Perturbations

Şafak Çelik, Fabian Schmidt

We develop a perturbative model to describe large-scale structure in cosmologies where dark matter consists of a mixture of cold (CDM) and warm (WDM) components. In such mixed dark…

astro-ph.CO2024★ 17 cited

Structure formation with primordial black holes: collisional dynamics, binaries, and gravitational waves

M. Sten Delos, Antti Rantala, Sam Young +1

Primordial black holes (PBHs) could compose the dark matter content of the Universe. We present the first simulations of cosmological structure formation with PBH dark matter that…

astro-ph.CO2023

Galaxy bias renormalization group

Henrique Rubira, Fabian Schmidt

The effective field theory of large-scale structure allows for a consistent perturbative bias expansion of the rest-frame galaxy density field. In this work, we present a systemati…

astro-ph.CO2023★ 15 cited

Halo assembly bias from a deep learning model of halo formation

Luisa Lucie-Smith, Alexandre Barreira, Fabian Schmidt

We build a deep learning framework that connects the local formation process of dark matter halos to the halo bias. We train a convolutional neural network (CNN) to predict the fin…

astro-ph.CO2023★ 1 cited

Effective Field Theory of Intrinsic Alignments at One Loop Order: a Comparison to Dark Matter Simulations

Thomas Bakx, Toshiki Kurita, Nora Elisa Chisari +2

We test the regime of validity of the effective field theory (EFT) of intrinsic alignments (IA) at the one-loop level by comparing with 3D halo shape statistics in N-body simulatio…

astro-ph.CO2023★ 28 cited

Cosmology inference at the field level from biased tracers in redshift-space

Julia Stadler, Fabian Schmidt, Martin Reinecke

Cosmology inference of galaxy clustering at the field level with the EFT likelihood in principle allows for extracting all non-Gaussian information from quasi-linear scales, while…

astro-ph.CO2022★ 39 cited

Assembly bias in the local PNG halo bias and its implication for constraints

Titouan Lazeyras, Alexandre Barreira, Fabian Schmidt +1

We use -body simulations to study halo assembly bias (i.e., the dependence of halo clustering on properties beyond total mass) in the density and primordial non-Gaussianity (PNG…

astro-ph.CO2018★ 42 cited

Imprints of Oscillatory Bispectra on Galaxy Clustering

Giovanni Cabass, Enrico Pajer, Fabian Schmidt

Long-short mode coupling during inflation, encoded in the squeezed bispectrum of curvature perturbations, induces a dependence of the local, small-scale power spectrum on long-wave…