The paper "Nested Sampling: A Critical and Comprehensive Theoretical Guide" offers an in‑depth derivation of the nested sampling (NS) technique, clarifying its theoretical foundations and practical challenges. It explains how NS efficiently explores high‑likelihood regions, discusses its connections to importance sampling and vertical Monte Carlo, and highlights both strengths and limitations. The work serves as both a tutorial for newcomers and a critical review for experienced practitioners, aiming to inspire future enhancements and more efficient implementations across scientific fields.
arXiv:2606. 10023v1 Announce Type: cross Abstract: Accurate posterior estimation is central to scientific inference, as uncertainties determine what can be reliably learned from observational data.
arXiv:2510. 17459v3 Announce Type: replace-cross Abstract: In this work, we propose a flow-matching Markov chain Monte Carlo (FM-MCMC) algorithm for estimating the orbital parameters of exoplanetary systems, especially for those only one exoplanet is involved.
arXiv:2608.21729v1 Announce Type: new Abstract: Simulation-Based Inference (SBI) serves as a vital framework for parameter inference in scientific fields where simulators involve intractable likeliho...
ASTROLABE is a flow‑matching generative emulator that operates directly on the 6N phase‑space coordinates of individual particles, avoiding voxel grids and allowing any observable to be measured from inference. It uses a field‑particle hybrid transformer so that compute and memory scale linearly with the number of particles, and incorporates physical flow matching by basing the prior on COLA‑derived coordinates with momentum and mass conservation enforced throughout the flow. In Lambda‑CDM tests, ASTROLABE reproduces realistic fields, accurate power spectra, halo mass functions, velocity profiles, and halo density profiles, and it generalizes to out‑of‑distribution dark‑acoustic oscillation initial conditions while also being fine‑tuned to emulate large‑scale simulations such as TNG50‑3‑dark at a fraction of the cost.
arXiv:2608. 13774v1 Announce Type: new Abstract: Markov chain Monte Carlo (MCMC) requires only the ability to evaluate the likelihood, making it a common technique for inference in complex models.
arXiv:2603. 22006v2 Announce Type: replace-cross Abstract: Upcoming stage-IV surveys such as Euclid and Rubin will deliver vast amounts of high-precision data, opening new opportunities to constrain cosmological models with unprecedented accuracy.
arXiv:2608. 07648v1 Announce Type: cross Abstract: Sampling high-dimensional probability distributions is a central task in scientific computing, with applications ranging from Bayesian inference to statistical physics and molecular simulation.
arXiv:2606. 00803v1 Announce Type: cross Abstract: Reconstructing the three-dimensional distribution of dark matter from weak-lensing observations is a central but highly ill-posed inverse problem in cosmology.
The paper presents a fully automated method for reconstructing the surface mass density of galaxy clusters using photometry and gravitational lensing data. It introduces DarkClusters-15k, a benchmark dataset of 15,000 simulated clusters with paired mass and photometry maps across multiple redshifts and simulation frameworks. By training a diffusion prior on this dataset, the authors generate posterior samples constrained by weak- and strong-lensing observables, achieving accurate, physics‑guided reconstructions with well‑calibrated uncertainties in minutes.
arXiv:2606. 00219v1 Announce Type: cross Abstract: We are witnessing a surge in observations of the cosmic dawn (CD) and epoch of reionisation (EoR), driving an increasing demand for fast and robust theoretical interpretation frameworks.
arXiv:2604. 08648v2 Announce Type: replace-cross Abstract: We motivate the use of differentiable probabilistic programming techniques in order to account for the large model-space inherent to astrophysical $\gamma$-ray analyses.
arXiv:2606. 11295v1 Announce Type: cross Abstract: Recovering cosmological information beyond the power spectrum is a central goal for upcoming cosmological surveys, since late-time non-Gaussian signal in the matter density cannot be accessed through two-point statistics alone.