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.
By Ludvig Doeser, Jens Jasche
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.
By Bo Liang, Hanlin Song, Chang Liu, Tianyu Zhao, Yuxiang Xu, Zihao Xiao, Manjia Liang, Minghui Du, Wei-Liang Qian, Li-e Qiang, Peng Xu, Ziren Luo
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...
By Yichen Zang, Song Liu, Jiun-Yi Lin
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.
By Ibrahim Elsharkawy, David Curtin, Yonatan Kahn, Neal Weiner
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.
By Harini Venkatesan, Christian Shelton, Ming-Feng Ho, Simeon Bird, Mengxuan Wu
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.
By Hubert Leterme, Andreas Tersenov, Jalal Fadili, Jean-Luc Starck