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Found 9 papers, 7 papers with code
Scaling-laws for Large Time-series Models
Scaling laws for large language models (LLMs) have provided useful guidance on how to train ever larger models for predictable performance gains.
Optimal simulation-based Bayesian decisions
We present a framework for the efficient computation of optimal Bayesian decisions under intractable likelihoods, by learning a surrogate model for the expected utility (or its distribution) as a function of the action and data spaces.
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
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
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
