REVIEW 7 cited by
JAXNS: a high-performance nested sampling package based on JAX
Not yet reviewed by Pith; the record is open.
This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.
SPECIMEN: schema-true, not a live event
T0 review · schema-true
One-sentence machine reading of the paper's core claim.
pith:XXXXXXXX · record.json · timestamp
JAXNS: a high-performance nested sampling package based on JAX
read the original abstract
Since its debut by John Skilling in 2004, nested sampling has proven a valuable tool to the scientist, providing hypothesis evidence calculations and parameter inference for complicated posterior distributions, particularly in the field of astronomy. Due to its computational complexity and long-running nature, in the past, nested sampling has been reserved for offline-type Bayesian inference, leaving tools such as variational inference and MCMC for online-type, time-constrained, Bayesian computations. These tools do not easily handle complicated multi-modal posteriors, discrete random variables, and posteriors lacking gradients, nor do they enable practical calculations of the Bayesian evidence. An opening thus remains for a high-performance out-of-the-box nested sampling package that can close the gap in computational time, and let nested sampling become common place in the data science toolbox. We present JAX-based nested sampling (JAXNS), a high-performance nested sampling package written in XLA-primitives using JAX, and show that it is several orders of magnitude faster than the currently available nested sampling implementations of PolyChord, MultiNEST, and dynesty, while maintaining the same accuracy of evidence calculation. The JAXNS package is publically available at \url{https://github.com/joshuaalbert/jaxns}.
Forward citations
Cited by 7 Pith papers
-
\chisao{}: A GPU-Native Parallel Optimizer for Multimodal Black-Box Functions via Convergence-Anticonvergence Oscillation
CHISAO recovers all modes on the full SFU benchmark suite up to dimension 64 with 100% success using GPU parallelism and a convergence-anticonvergence oscillation, where CPU baselines fail at d >= 8.
-
Precise Determination of the Metallicity and C/O of WASP-39~b From a Single JWST Instrument Mode with Phase-Resolved Cross-Correlation Retrievals
Phase-resolved cross-correlation retrieval on a single JWST G395H transit of WASP-39 b detects CO and yields bounded C/O (0.68) and metallicity (1.2 dex), previously requiring multi-instrument coverage.
-
A search for periodic AGN variability in $\textit{Gaia}$ Data Release 3
Systematic search of 377k Gaia DR3 AGN light curves finds no reliable periodic SMBHB candidates after red-noise modeling and empirical false-alarm testing; all survivors lie in the few-cycle regime.
-
Impact of sky localization uncertainty on ringdown inference
Properly accounting for sky localization uncertainty in ringdown inference widens mode-amplitude posteriors, avoids bias from fixed point estimates, and leaves amplitude ratios robust for Kerr spectroscopy.
-
Plato's view on supermassive black hole binaries: Exploring the faint limit of ESA's Plato space mission
Simulations show Plato can recover relativistic photometric signatures of supermassive black hole binaries in bright quasars (G≤18) via Bayesian inference on mock light curves.
-
LITMUS: Bayesian Lag Recovery in Reverberation Mapping with Fast Differentiable Models
LITMUS introduces a differentiable Bayesian lag recovery framework that outperforms JAVELIN on OzDES-like mock data by reducing false positives from seasonal aliasing.
-
A decade of monitoring the HIP 41378's planetary system
Decade-long RV data from multiple instruments confirms Pd=278 days for planet d, refines Pe=393 days for e, measures Mf=25 Earth masses confirming low density of 0.166 g cm^-3, and identifies candidate planet h at ~2600 days.
discussion (0)
Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.