Presents a practical fully time-domain end-to-end likelihood for gravitational-wave inference with structured linear algebra and GPU acceleration.
Dynamic temperature selection for parallel-tempering in Markov chain Monte Carlo simulations
8 Pith papers cite this work. Polarity classification is still indexing.
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abstract
Modern problems in astronomical Bayesian inference require efficient methods for sampling from complex, high-dimensional, often multi-modal probability distributions. Most popular methods, such as Markov chain Monte Carlo sampling, perform poorly on strongly multi-modal probability distributions, rarely jumping between modes or settling on just one mode without finding others. Parallel tempering addresses this problem by sampling simultaneously with separate Markov chains from tempered versions of the target distribution with reduced contrast levels. Gaps between modes can be traversed at higher temperatures, while individual modes can be efficiently explored at lower temperatures. In this paper, we investigate how one might choose the ladder of temperatures to achieve more efficient sampling, as measured by the autocorrelation time of the sampler. In particular, we present a simple, easily-implemented algorithm for dynamically adapting the temperature configuration of a sampler while sampling. This algorithm dynamically adjusts the temperature spacing to achieve a uniform rate of exchanges between chains at neighbouring temperatures. We compare the algorithm to conventional geometric temperature configurations on a number of test distributions and on an astrophysical inference problem, reporting efficiency gains by a factor of 1.2-2.5 over a well-chosen geometric temperature configuration and by a factor of 1.5-5 over a poorly chosen configuration. On all of these problems a sampler using the dynamical adaptations to achieve uniform acceptance ratios between neighbouring chains outperforms one that does not.
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representative citing papers
Bayesian global fit to Xe-Xe and Pb-Pb LHC data infers nearly maximal triaxiality for the 129Xe ground state and extracts two- and three-particle correlations.
Bayesian data augmentation reintroduces missing LISA data segments as auxiliary variables during posterior sampling to enable consistent parameter estimation for galactic binaries despite gaps.
GEODES characterizes three accelerating nearby stars, finding a stellar companion, a 45-Jupiter-mass brown dwarf at about 18 AU, and a 9.5-Jupiter-mass companion that is more likely a planet than a brown dwarf.
DALI extends the Fisher Matrix to higher orders and approximates MCMC posteriors for GW events at 55 times lower cost, with singlet-DALI offering better accuracy and the GWDALI code providing automatic differentiation and modern waveforms.
A neural spline flow pipeline performs amortized inference on millihertz MBHB signals, delivering ~20 deg² pre-merger sky localizations in ~1 minute while matching PTMCMC sky modes and parameter uncertainties.
Mass of 13.7 Earth masses and density 0.4 g cm^{-3} measured for TOI-1883 b, a super-Neptune in the ridge regime around an early-M dwarf, with implications for disk migration and photoevaporation.
Introduces UQ extension to KLIFF using PTMCMC to quantify uncertainty from parameter variation and IP functional form inadequacy, demonstrated on Stillinger-Weber potential for silicon.
citing papers explorer
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Accelerated Time-domain Analysis for Gravitational Wave Astronomy
Presents a practical fully time-domain end-to-end likelihood for gravitational-wave inference with structured linear algebra and GPU acceleration.
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Yoctosecond imaging of the ground state of $^{129}$Xe at the Large Hadron Collider
Bayesian global fit to Xe-Xe and Pb-Pb LHC data infers nearly maximal triaxiality for the 129Xe ground state and extracts two- and three-particle correlations.
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Gravitational-wave parameter estimation with gaps in LISA: a Bayesian data augmentation method
Bayesian data augmentation reintroduces missing LISA data segments as auxiliary variables during posterior sampling to enable consistent parameter estimation for galactic binaries despite gaps.
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Gaia Exoplanet Orbits, Demographics, and Evolution Survey (GEODES): Characteristics of Three Long-Period Companions Accelerating their Host Stars
GEODES characterizes three accelerating nearby stars, finding a stellar companion, a 45-Jupiter-mass brown dwarf at about 18 AU, and a 9.5-Jupiter-mass companion that is more likely a planet than a brown dwarf.
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On the use of the Derivative Approximation for Likelihoods for Gravitational Wave Inference
DALI extends the Fisher Matrix to higher orders and approximates MCMC posteriors for GW events at 55 times lower cost, with singlet-DALI offering better accuracy and the GWDALI code providing automatic differentiation and modern waveforms.
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Pre-localization of Massive Black Hole Binaries in the Millihertz Band
A neural spline flow pipeline performs amortized inference on millihertz MBHB signals, delivering ~20 deg² pre-merger sky localizations in ~1 minute while matching PTMCMC sky modes and parameter uncertainties.
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The mass of TOI-1883 b: A low density super-Neptune in the ridge regime transiting an early-M dwarf
Mass of 13.7 Earth masses and density 0.4 g cm^{-3} measured for TOI-1883 b, a super-Neptune in the ridge regime around an early-M dwarf, with implications for disk migration and photoevaporation.
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Extending OpenKIM with an Uncertainty Quantification Toolkit for Molecular Modeling
Introduces UQ extension to KLIFF using PTMCMC to quantify uncertainty from parameter variation and IP functional form inadequacy, demonstrated on Stillinger-Weber potential for silicon.