no code implementations • 5 Feb 2025 • Oleg Savchenko, Guillermo Franco Abellán, Florian List, Noemi Anau Montel, Christoph Weniger
We show how simulation-based inference (SBI) can be used to tackle this problem and to obtain data-constrained realisations of the primordial dark matter density field in a simulation-efficient way with general non-differentiable simulators.
no code implementations • 9 Jan 2025 • Kristian G. Barman, Sascha Caron, Emily Sullivan, Henk W. de Regt, Roberto Ruiz de Austri, Mieke Boon, Michael Färber, Stefan Fröse, Faegheh Hasibi, Andreas Ipp, Rukshak Kapoor, Gregor Kasieczka, Daniel Kostić, Michael Krämer, Tobias Golling, Luis G. Lopez, Jesus Marco, Sydney Otten, Pawel Pawlowski, Pietro Vischia, Erik Weber, Christoph Weniger
This paper explores ideas and provides a potential roadmap for the development and evaluation of physics-specific large-scale AI models, which we call Large Physics Models (LPMs).
no code implementations • 19 Dec 2024 • Noemi Anau Montel, James Alvey, Christoph Weniger
Model misspecification analysis strategies, such as anomaly detection, model validation, and model comparison are a key component of scientific model development.
no code implementations • 21 Oct 2024 • Oleg Savchenko, Florian List, Guillermo Franco Abellán, Noemi Anau Montel, Christoph Weniger
Reconstructing cosmological initial conditions (ICs) from late-time observations is a difficult task, which relies on the use of computationally expensive simulators alongside sophisticated statistical methods to navigate multi-million dimensional parameter spaces.
no code implementations • 30 Oct 2023 • Florian List, Noemi Anau Montel, Christoph Weniger
The proposed technique is applicable to generic (non-differentiable) forward simulators and allows sampling from the posterior for the underlying field.
no code implementations • 3 Oct 2023 • Benjamin Kurt Miller, Marco Federici, Christoph Weniger, Patrick Forré
The objective recovers Neural Posterior Estimation when the model class is normalized and unifies it with Neural Ratio Estimation, combining both into a single objective.
1 code implementation • 21 Apr 2023 • Arnaud Delaunoy, Benjamin Kurt Miller, Patrick Forré, Christoph Weniger, Gilles Louppe
We show empirically that the balanced versions tend to produce conservative posterior approximations on a wide variety of benchmarks.
1 code implementation • 11 Oct 2022 • Benjamin Kurt Miller, Christoph Weniger, Patrick Forré
In contrast to the binary classification framework, the current formulation of the multiclass version has an intrinsic and unknown bias term, making otherwise informative diagnostics unreliable.
4 code implementations • 15 Nov 2021 • Alex Cole, Benjamin Kurt Miller, Samuel J. Witte, Maxwell X. Cai, Meiert W. Grootes, Francesco Nattino, Christoph Weniger
Sampling-based inference techniques are central to modern cosmological data analysis; these methods, however, scale poorly with dimensionality and typically require approximate or intractable likelihoods.
2 code implementations • NeurIPS 2021 • Benjamin Kurt Miller, Alex Cole, Patrick Forré, Gilles Louppe, Christoph Weniger
Parametric stochastic simulators are ubiquitous in science, often featuring high-dimensional input parameters and/or an intractable likelihood.
1 code implementation • 30 Nov 2020 • Joeri Hermans, Nilanjan Banik, Christoph Weniger, Gianfranco Bertone, Gilles Louppe
A statistical analysis of the observed perturbations in the density of stellar streams can in principle set stringent contraints on the mass function of dark matter subhaloes, which in turn can be used to constrain the mass of the dark matter particle.
1 code implementation • 27 Nov 2020 • Benjamin Kurt Miller, Alex Cole, Gilles Louppe, Christoph Weniger
We present algorithms (a) for nested neural likelihood-to-evidence ratio estimation, and (b) for simulation reuse via an inhomogeneous Poisson point process cache of parameters and corresponding simulations.
1 code implementation • 10 Nov 2020 • Thomas D. P. Edwards, Bradley J. Kavanagh, Luca Visinelli, Christoph Weniger
The QCD axion is expected to form dense structures known as axion miniclusters if the Peccei-Quinn symmetry is broken after inflation.
High Energy Physics - Phenomenology Cosmology and Nongalactic Astrophysics Astrophysics of Galaxies
1 code implementation • 10 Nov 2020 • Bradley J. Kavanagh, Thomas D. P. Edwards, Luca Visinelli, Christoph Weniger
Although we present results for a particular initial halo mass function, our simulations can be easily recast to different models using the provided data and code.
Astrophysics of Galaxies Cosmology and Nongalactic Astrophysics High Energy Physics - Phenomenology
no code implementations • 24 Oct 2020 • Arnaud Delaunoy, Antoine Wehenkel, Tanja Hinderer, Samaya Nissanke, Christoph Weniger, Andrew R. Williamson, Gilles Louppe
Gravitational waves from compact binaries measured by the LIGO and Virgo detectors are routinely analyzed using Markov Chain Monte Carlo sampling algorithms.
no code implementations • 14 Oct 2020 • Adam Coogan, Konstantin Karchev, Christoph Weniger
The analysis of optical images of galaxy-galaxy strong gravitational lensing systems can provide important information about the distribution of dark matter at small scales.
Cosmology and Nongalactic Astrophysics Astrophysics of Galaxies Instrumentation and Methods for Astrophysics High Energy Physics - Phenomenology
1 code implementation • 31 Mar 2020 • Joshua W. Foster, Yonatan Kahn, Oscar Macias, Zhiquan Sun, Ralph P. Eatough, Vladislav I. Kondratiev, Wendy M. Peters, Christoph Weniger, Benjamin R. Safdi
Axion dark matter (DM) may convert to radio-frequency electromagnetic radiation in the strong magnetic fields around neutron stars.
Cosmology and Nongalactic Astrophysics High Energy Astrophysical Phenomena High Energy Physics - Phenomenology
no code implementations • 14 Oct 2019 • Marco Chianese, Adam Coogan, Paul Hofma, Sydney Otten, Christoph Weniger
The careful analysis of strongly gravitationally lensed radio and optical images of distant galaxies can in principle reveal DM (sub-)structures with masses several orders of magnitude below the mass of dwarf spheroidal galaxies.
Cosmology and Nongalactic Astrophysics Astrophysics of Galaxies Instrumentation and Methods for Astrophysics High Energy Physics - Phenomenology
1 code implementation • 13 Jun 2019 • Sebastian Baum, Thomas D. P. Edwards, Bradley J. Kavanagh, Patrick Stengel, Andrzej K. Drukier, Katherine Freese, Maciej Górski, Christoph Weniger
Natural minerals on Earth are as old as $\mathcal{O}(1)\,$Gyr and, in many minerals, the damage tracks left by recoiling nuclei are also preserved for timescales long compared to 1 Gyr once created.
Astrophysics of Galaxies Cosmology and Nongalactic Astrophysics High Energy Physics - Phenomenology
1 code implementation • 3 May 2019 • Gianfranco Bertone, Adam Coogan, Daniele Gaggero, Bradley J. Kavanagh, Christoph Weniger
Observational constraints on gamma rays produced by the annihilation of weakly interacting massive particles around primordial black holes (PBHs) imply that these two classes of Dark Matter candidates cannot coexist.
High Energy Physics - Phenomenology High Energy Astrophysical Phenomena
3 code implementations • 26 Nov 2018 • Thomas D. P. Edwards, Bradley J. Kavanagh, Christoph Weniger, Sebastian Baum, Andrzej K. Drukier, Katherine Freese, Maciej Górski, Patrick Stengel
We find that in the most optimistic case of a %-level understanding of the background shape, we can achieve sensitivity to DM-nucleon scattering cross sections up to a factor of 100 smaller than current XENON1T bounds for DM masses above $100\,$GeV.
High Energy Physics - Phenomenology Cosmology and Nongalactic Astrophysics Instrumentation and Methods for Astrophysics
2 code implementations • 10 May 2018 • Thomas D. P. Edwards, Bradley J. Kavanagh, Christoph Weniger
Forecasting the signal discrimination power of dark matter (DM) searches is commonly limited to a set of arbitrary benchmark points.
High Energy Physics - Phenomenology Cosmology and Nongalactic Astrophysics Data Analysis, Statistics and Probability
1 code implementation • 14 Dec 2017 • Thomas D. P. Edwards, Christoph Weniger
We introduce swordfish, a Monte-Carlo-free Python package to predict expected exclusion limits, the discovery reach and expected confidence contours for a large class of experiments relevant for particle- and astrophysics.
High Energy Physics - Phenomenology Data Analysis, Statistics and Probability
1 code implementation • 18 Apr 2017 • Thomas D. P. Edwards, Christoph Weniger
It is a powerful and flexible tool ready to be used as core concept for informed strategy development in astroparticle physics and searches for particle dark matter.
Instrumentation and Methods for Astrophysics Cosmology and Nongalactic Astrophysics High Energy Physics - Phenomenology Data Analysis, Statistics and Probability