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6/8/26, 9:15 AMOpening/Closing Remarks
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Carolina Cuesta-Lazaro (Flatiron Institute)6/8/26, 9:30 AMConference Talk
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Oleg Savchenko (GRAPPA Institute, University of Amsterdam)6/8/26, 11:00 AMContributed Talk
Simulation-based inference (SBI) enables Bayesian analysis of complex cosmological data when only a forward model is available, while field-level inference (FLI) aims to perform inference in a maximally efficient way and retain more information than summary-statistic pipelines. In this talk, I will highlight recent advances and applications of SBI and FLI in cosmology. First, I will show how...
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Justine Zeghal (Université de Montréal, Mila)6/8/26, 11:20 AMContributed Talk
Weak lensing convergence maps are expected to be significantly non-Gaussian on small scales, causing the power spectrum to fail as a sufficient statistic for cosmological parameters by discarding information encoded in higher-order correlations. This limitation is particularly pressing in the context of next-generation surveys, which will improve the signal-to-noise ratio and grant access to...
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Madeline Casas (The University of Texas at Austin)6/8/26, 11:40 AMContributed Talk
Simulation-based inference (SBI) has recently emerged as a promising avenue for inferring cosmological parameters from the 3D distribution of galaxies from large spectroscopic surveys (DESI, PFS, DESI-II). The first iteration of the SimBIG project demonstrated a proof-of-concept for this approach, using a forward-modeling pipeline built from high-fidelity QUIJOTE N-body simulations applied to...
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Yashar Hezaveh6/8/26, 1:30 PMConference Talk
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Kangning Diao (UC Berkeley)6/8/26, 3:00 PMContributed Talk
Simulation-based inference (SBI) provides a powerful framework for extracting rich information from nonlinear scales in current and upcoming cosmological surveys, and ensuring its robustness requires stringent validation of forward models. In this work, we recast forward model validation as an out-of-distribution (OoD) detection problem within the framework of machine learning (ML)-based SBI....
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Benjamin Remy (The University of Chicago)6/8/26, 3:20 PMContributed Talk
Upcoming Stage-IV galaxy surveys will map the large-scale structure of the Universe with unprecedented precision, requiring analysis methods that can exploit information beyond traditional two-point statistics. Field-level inference offers a principled path forward by working directly with the observed fields, capturing non-Gaussian signatures that summary statistics discard. However, existing...
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Ivan Espinoza Bustamante (The University of Arizona)6/8/26, 3:40 PMContributed Talk
We will present KARMMA, a field-level inference designed to enable joint inference of cosmology and the convergence field from cosmic shear data. KARMMA is a full-sky Bayesian algorithm that forward-models the convergence field as an augmented lognormal realization. Using N-body simulations, we generate mock cosmic shear observations and use these to validate the cosmological inferences from...
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Fabian Schmidt (Max Planck Institute for Astrophysics)6/9/26, 9:30 AMConference Talk
I will discuss how field-level inference can be connected with summary statistics in the context of a perturbative forward model, and what this implies for the information gain obtainable at the field level. I will also present recent quantitative results on the information gain.
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Drew Jamieson (Max Planck Institute for Astrophysics)6/9/26, 11:00 AMContributed Talk
Simulating inflation is emerging as a powerful technique for studying inflationary phenomenology beyond the standard paradigm of single-field, slow-roll, and perturbative dynamics. In this talk, I will present recent results from lattice simulations of axion-gauge inflationary models that exhibit a rich phenomenology, including an enhanced small-scale power spectrum, a blue-tilted...
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Amanda Lue (Columbia University)6/9/26, 11:20 AMContributed Talk
Cosmological studies with surveys such as DESI, Roman and Euclid will be most powerful if they can exploit the rich information on small, nonlinear scales, which are often removed by conservative cuts due to the difficulty of robustly modelling baryonic physics. We present an accelerated forward-modelling framework aimed at enabling simulation based inference (SBI) while marginalizing over...
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Daniela Saadeh (Durham University)6/9/26, 11:40 AMContributed Talk
We present a field-level framework to emulate the effects of extra fundamental forces on the cosmic web. This approach is designed to enable field-level inference with data from Stage IV cosmological surveys. Building on the reaction method, which models the nonlinear matter power spectrum in modified gravity as corrections to a "pseudo'' $\Lambda$CDM cosmology, we extend the method to full...
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Jens Jasche6/9/26, 1:30 PM
Traditional cosmological analyses describe ensemble-averaged properties of structure formation. Bayesian field-level inference offers a fundamentally different capability: by constructing posterior ensembles of initial conditions directly constrained by galaxy survey data, one recovers physically consistent realizations of the specific Universe we inhabit. This eliminates cosmic variance as a...
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Ewoud Wempe (CNRS / LIRA, Observatoire de Paris)6/9/26, 3:00 PMContributed Talk
I will present a Bayesian hierarchical field-level inference framework for the Local Group and its immediate cosmological environment. ΛCDM initial conditions are conditioned on observational constraints on the masses, relative position, and velocities of the Milky Way and M31 haloes, and on the surrounding velocity field traced by isolated galaxies within 5 Mpc. This yields statistically...
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Mahmoud Osman (LPNHE/IN2P3/CNRS)6/9/26, 3:20 PMContributed Talk
Peculiar velocities of matter tracers, arising from gravitational infall into large-scale structures, can be used to determine the growth rate of cosmic structure, $f\sigma_8$,providing a direct test of General Relativity. Measurements of velocity fields therefore constitute an important probe of the standard cosmological model.
In this talk, I will present our methodology based on the...
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Mikhail Ivanov6/9/26, 3:40 PMConference Talk
I will overview recent advances in modeling of the high-redshift tracers, such as the Lyman-alpha forest, Lyman-alpha emitting galaxies, and Lyman-break galaxies at the field level using large-scale structure effective field theory. I will then discuss various new opportunities that this modeling offers, including generation of high-quality mock catalogs and simulation-based priors for...
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Adrian Bayer6/10/26, 9:30 AMConference Talk
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Toka Alokda (Argelander Institute for Astronomy, University of Bonn)6/10/26, 11:00 AMContributed Talk
Simulation-based inference (SBI) is increasingly used to extract cosmological information from complex observables, with reliability typically validated through coverage-based diagnostics such as simulation-based calibration (SBC) and the coverage test of accuracy with random points (TARP). These tests check whether posteriors contain the true parameter value with the expected frequency; a...
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Benjamin Horowitz (Kavli IPMU)6/10/26, 11:20 AMContributed Talk
Understanding the complex interplay of gas and dark matter is critical for the next generation of cosmological surveys and related inference. While many techniques seek to marginalize over these uncertainties, there is a wealth of information from across astrophysics than can better constrain properties like galaxy formation and evolution.
In this talk, I will introduce recent developments...
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Hugo Simon (CEA Paris-Saclay)6/10/26, 11:40 AMContributed Talk
Field-Level Inference (FLI) needs to be made more tractable and robust at survey scale. To this purpose, I developed fast, differentiable cosmological simulators and introduced a standardized benchmark, showing how to reduce the required model evaluations by orders of magnitude. Building on this, I am working toward FLI constraints on local Primordial Non-Gaussianity (PNG) from DESI. I will...
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Azadeh Moradinezhad (CNRS - LAPTh)6/10/26, 1:30 PMConference Talk
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Lucia Perez (Flatiron Institute)6/10/26, 3:00 PMContributed Talk
As part of the Learning the Universe collaboration, we have pushed the CAMELS-SAM simulation suite into observational photometric space, and present initial results for constraints on cosmological and astrophysical parameters for galaxy population statistics for the SDSS Main Galaxy Sample. CAMELS-SAM already included more than 1000 N-body simulations of (100 cMpc)$^3$, covering a vast...
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Giulio Scelfo (SISSA)6/10/26, 3:20 PMContributed Talk
Simulation-Based Inference (SBI) overcomes problems of likelihood-based estimators allowing for the extraction of information at full-field level. I present a proof-of-concept SBI pipeline to marginally constrain the cosmological parameters $\{\Omega_m, \sigma_8\}$ from large-scale structure observables. Our approach combines fast dark matter simulations with neural emulators that generate...
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6/10/26, 3:40 PMDiscussion
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Uros Seljak6/11/26, 9:30 AMConference Talk
I will present recent results of field level inference applied to three different cosmological probes. In the case of gravitational lensing of cosmic microwave background, explicit field level inference can extract both the lensing potential and delensed CMB. Recent developments in MCMC sampling have enabled full hierarchical Bayesian analysis. For galaxy clustering and Baryonic Acoustic...
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Shu-Fan Chen (Columbia University)6/11/26, 11:00 AMContributed Talk
We investigate the cosmological information content of higher-order statistics of the CMB lensing convergence field for near-term experiments similar to the Simons Observatory. Using a field-level forward-modeling pipeline based on ray-traced $N$-body simulations with realistic SO-like lensing reconstruction, we measure non-Gaussian statistics such as Minkowski functionals, peak/minima counts,...
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Jonah Rose (Princeton Univeristy)6/11/26, 11:20 AMContributed Talk
We introduce a novel framework for simulation-based inference using the DREAMS Project, a suite of 1,024 cosmological hydrodynamical zoom-in simulations of Milky Way-mass halos. This suite is designed to systematically disentangle theoretical uncertainties in galaxy formation physics from intrinsic halo-to-halo variance by varying key astrophysical parameters governing supernova wind energy,...
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Ethan Lilie (Princeton University)6/11/26, 11:40 AMContributed Talk
Dark matter direct detection experiments require information about the local dark matter speed distribution to produce constraints on dark matter candidates, or infer their properties in the event of a discovery. I will discuss how the uncertainty in the dark matter speed distribution near the Sun is affected by baryonic feedback, halo-to-halo variance, and halo mass. I will utilize the...
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Camille Avestruz (University of Michigan–Ann Arbor - Department of Physics)6/11/26, 1:30 PMContributed Talk
Stage-IV dark energy wide-field surveys, such as the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST), will observe an unprecedented number density of galaxies. As a result, the majority of imaged galaxies will visually overlap, a phenomenon known as blending. Blending is expected to be a leading source of systematic error in astronomical measurements. We present the Bayesian...
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Supranta Sarma Boruah (University of Pennsylvania)6/11/26, 1:50 PMContributed Talk
Upcoming photometric surveys such as LSST, Roman, and Euclid will map billions of galaxies, opening the door to field-level cosmological analyses. In this talk, I will present a density-slab framework for performing a field-level analog of the standard 3x2pt analysis, where we model galaxy and weak lensing observables by forward modeling density slabs of O[100 Mpc] at the map level rather than...
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Alexander Tong (University of Pennsylvania)6/11/26, 2:10 PMContributed Talk
The work presented in this talk is part of a program of performing field-level cosmological analyses using galaxy and weak lensing observables in density slabs of $O[100\ \mathrm{Mpc}]$. The inference pipeline requires a model for the mass overdensity field which is accurate to scales of a few Mpc across cosmologies, and also fast in the generation of sample fields. I will describe a scheme in...
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Fei Ge (CalTech)6/11/26, 3:00 PM
I will present the cosmological analysis from the simultaneous Bayesian estimates of gravitational-lensing potential bandpowers and unlensed cosmic microwave background (CMB) EE bandpowers directly using the polarization maps from the South Pole Telescope (SPT) observed in 2019/20. These observations produce the deepest high-angular-resolution CMB polarization maps at 90, 150, and 220 GHz to...
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Adriaan Duivenvoorden6/12/26, 9:30 AMConference Talk
Polarized Galactic emission is the foremost challenge for searches for a background of primordial gravitational waves imprinted in the polarization of the CMB. We argue that current methods struggle to address this challenge, either by being overly susceptible to model misspecification, or by failing to properly propagate the uncertainty due to residual Galactic emission after foreground...
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Roger de Belsunce (MIT)6/12/26, 11:00 AMContributed Talk
Current and future high-redshift spectroscopic surveys such as DESI, DESI-II, and Spec-S5 raise the question of how to fully extract the information contained in these datasets. Field-level inference is opening a new frontier in cosmology by enabling analyses that capture the full information content of cosmological observations, rather than relying on two- or three-point summary statistics....
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James Sullivan (MIT)6/12/26, 11:20 AMContributed Talk
The future of large-scale structure is at high redshift. In particular, the surveys of the next decade that will be at the vanguard of precision cosmology will target star-forming galaxies at z>2. Field-level inference efforts will, therefore, inevitably turn toward high-redshift samples in the near future, the clustering of which is not yet well-understood. The computational intractability of...
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Francesco Sinigaglia (Institute for Fundamental Physics of the Universe / SISSA)6/12/26, 11:40 AMContributed Talk
We perform for the first time full simulation-based inference on the Lyman-$\alpha$ forest 1D power spectrum. In particular, we consider the prediction of the Lyman-$\alpha$ forest $P_{\rm 1D}(k)$ at $2.0<z<3.5$ from the \texttt{CAMELS} cosmological hydrodynamic simulations run with the \texttt{IllustrisTNG} and \texttt{SIMBA} galaxy formation models. We train a normalizing flow to perform...
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Natali de Santi6/12/26, 1:30 PMConference Talk
Galaxies are the primary tracers of the large-scale structure of the Universe and are traditionally used through summary statistics such as correlation functions and power spectra to constrain cosmological models. However, galaxy populations themselves contain rich information through their spatial distribution, environments, and internal properties, potentially extending beyond the...
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6/12/26, 3:00 PMDiscussion
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6/12/26, 4:00 PMOpening/Closing Remarks
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