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Found 20 papers, 15 papers with code
Bayesian Simulation-based Inference for Cosmological Initial Conditions
The proposed technique is applicable to generic (non-differentiable) forward simulators and allows sampling from the posterior for the underlying field.
Simulation-based Inference with the Generalized Kullback-Leibler Divergence
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.
Balancing Simulation-based Inference for Conservative Posteriors
We show empirically that the balanced versions tend to produce conservative posterior approximations on a wide variety of benchmarks.
Contrastive Neural Ratio Estimation
Likelihood-to-evidence ratio estimation is usually cast as either a binary (NRE-A) or a multiclass (NRE-B) classification task.
Fast and Credible Likelihood-Free Cosmology with Truncated Marginal Neural Ratio Estimation
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.
Truncated Marginal Neural Ratio Estimation
Parametric stochastic simulators are ubiquitous in science, often featuring high-dimensional input parameters and/or an intractable likelihood.
Towards constraining warm dark matter with stellar streams through neural simulation-based inference
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.
Simulation-efficient marginal posterior estimation with swyft: stop wasting your precious time
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.
Transient Radio Signatures from Neutron Star Encounters with QCD Axion Miniclusters
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
Stellar Disruption of Axion Miniclusters in the Milky Way
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
Lightning-Fast Gravitational Wave Parameter Inference through Neural Amortization
Gravitational waves from compact binaries measured by the LIGO and Virgo detectors are routinely analyzed using Markov Chain Monte Carlo sampling algorithms.
Targeted Likelihood-Free Inference of Dark Matter Substructure in Strongly-Lensed Galaxies
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
Green Bank and Effelsberg Radio Telescope Searches for Axion Dark Matter Conversion in Neutron Star Magnetospheres
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
Differentiable Strong Lensing: Uniting Gravity and Neural Nets through Differentiable Probabilistic Programming
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
Paleo-Detectors for Galactic Supernova Neutrinos
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
Primordial Black Holes as Silver Bullets for New Physics at the Weak Scale
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
Digging for Dark Matter: Spectral Analysis and Discovery Potential of Paleo-Detectors
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
Dark Matter Model or Mass, but Not Both: Assessing Near-Future Direct Searches with Benchmark-free Forecasting
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
swordfish: Efficient Forecasting of New Physics Searches without Monte Carlo
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
A Fresh Approach to Forecasting in Astroparticle Physics and Dark Matter Searches
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
