English
Related papers

Related papers: Ly$\alpha$NNA: A Deep Learning Field-level Inferen…

200 papers

The hydrogen Ly$\alpha$ forest is an important probe of the $z>2$ Universe that is otherwise challenging to observe with galaxy redshift surveys, but this technique has traditionally been limited to 1D studies in front of bright quasars.…

Cosmology and Nongalactic Astrophysics · Physics 2017-03-22 Khee-Gan Lee

This paper introduces a modular processing chain to derive global high-resolution maps of leaf traits. In particular, we present global maps at 500 m resolution of specific leaf area, leaf dry matter content, leaf nitrogen and phosphorus…

Bayesian posterior inference of modern multi-probe cosmological analyses incurs massive computational costs. For instance, depending on the combinations of probes, a single posterior inference for the Dark Energy Survey (DES) data had a…

Cosmology and Nongalactic Astrophysics · Physics 2023-01-25 Chun-Hao To , Eduardo Rozo , Elisabeth Krause , Hao-Yi Wu , Risa H. Wechsler , Andrés N. Salcedo

We describe techniques for comparing spectra extracted from cosmological simulations and observational data, using the same methodology to link Lyman-alpha properties derived from the simulations with properties derived from observational…

Astrophysics · Physics 2009-11-07 C. E. Petry , C. D. Impey , N. Katz , D. H. Weinberg , L. E. Hernquist

We present a theory-first framework that interprets inference-time adaptation in large language models (LLMs) as online Bayesian state estimation. Rather than modeling rapid adaptation as implicit optimization or meta-learning, we formulate…

Machine Learning · Computer Science 2026-01-13 Andrew Kiruluta

We compare the observed probability distribution function of the transmission in the \HI\ Lyman-alpha forest, measured from the UVES 'Large Programme' sample at redshifts z=[2,2.5,3], to results from the GIMIC cosmological simulations. Our…

Cosmology and Nongalactic Astrophysics · Physics 2015-06-11 Emmanuel Rollinde , Tom Theuns , Joop Schaye , Isabelle Pâris , Patrick Petitjean

Lyman-$\alpha$ (Ly$\alpha$) spectra provide insights into the small-scale structure and kinematics of neutral hydrogen (HI) within galaxies as well as the ionization state of the intergalactic medium (IGM). The former defines the intrinsic…

Astrophysics of Galaxies · Physics 2020-10-21 Chris Byrohl , Max Gronke

Wood increment is critical information in forestry management. Previous studies used mathematics models to describe complex growing pattern of forest stand, in order to determine the dynamic status of growing forest stand in multiple…

Computational Engineering, Finance, and Science · Computer Science 2014-05-21 Xiaohui Huang , Xing Hu , Weichang Jiang , Zhi Yang , Hao Li

Recently, NIRSpec PRISM/CLEAR observations by JWST have begun providing rest-frame UV continuum measurements of galaxies at $z\gtrsim7$, revealing signatures of Ly$\alpha$ damping-wing (DW) absorption by the intergalactic medium (IGM). We…

The Lyman $\alpha$ (Ly$\alpha$) line from high-redshift galaxies is a powerful probe of the Epoch of Reionization (EoR). Neutral hydrogen in the intergalactic medium (IGM) can significantly attenuate the emergent Ly$\alpha$ line, even in…

Astrophysics of Galaxies · Physics 2026-02-17 Samuel Gagnon-Hartman , Andrei Mesinger , Ivan Nikolić , Eleonora Parlanti , Giacomo Venturi

We present the one-dimensional Lyman-$\alpha$ forest power spectrum measurement using the first data provided by the Dark Energy Spectroscopic Instrument (DESI). The data sample comprises $26,330$ quasar spectra, at redshift $z > 2.1$,…

We propose a novel inverse-modelling approach which estimates the parameters of a simple land-surface model (LSM) by assimilating data into a differentiable physics-based forward model. The governing equations are expressed within a…

Atmospheric and Oceanic Physics · Physics 2026-04-17 Ruiyue Huang , Claire E. Heaney , Maarten van Reeuwijk

We present moderate resolution data for 39 QSOs at z $\approx$ 2 obtained at the Multiple Mirror Telescope. These data are combined with spectra of comparable resolution of 60 QSOs with redshifts greater than 1.7 found in the literature to…

Astrophysics · Physics 2009-10-31 J. Scott , J. Bechtold , A. Dobrzycki

It has been recently shown that the astrophysics of reionization can be extracted from the Ly$\alpha$ forest power spectrum by marginalizing the memory of reionization over cosmological information. This impact of cosmic reionization on the…

Cosmology and Nongalactic Astrophysics · Physics 2023-03-07 Paulo Montero-Camacho , Yuchen Liu , Yi Mao

High resolution N-body simulations of cold dark matter (CDM) models predict that galaxies and clusters have cuspy halos with excessive substructure. Observations reveal smooth halos with central density cores. One possible resolution of…

Astrophysics · Physics 2015-09-23 Vijay K. Narayanan , David N. Spergel , Romeel Davé , Chung-Pei Ma

The Lyman-alpha forest provides strong constraints on both cosmological parameters and intergalactic medium astrophysics, which are forecast to improve further with the next generation of surveys including eBOSS and DESI. As is generic in…

Cosmology and Nongalactic Astrophysics · Physics 2019-02-19 Keir K. Rogers , Hiranya V. Peiris , Andrew Pontzen , Simeon Bird , Licia Verde , Andreu Font-Ribera

We investigate the relationship between the Lyman-alpha (Lya) forest transmission in the intergalactic medium (IGM) and the environmental density of galaxies, focusing on its implications for the measurement of ionizing radiation escape…

Astrophysics of Galaxies · Physics 2025-04-24 C. Scarlata , W. Hu , M. J. Hayes , S. Taamoli , A. A. Khostovan , C. M. Casey , A. L. Faisst , J. S. Kartaltepe , Y. Lin , M. Salvato , M. Rafelski

The purpose of this study was to investigate the use of deep learning for coniferous/deciduous classification of individual trees from airborne LiDAR data. To enable efficient processing by a deep convolutional neural network (CNN), we…

Machine Learning · Computer Science 2018-02-27 Hamid Hamraz , Nathan B. Jacobs , Marco A. Contreras , Chase H. Clark

Bayesian Neural Networks provide a principled framework for uncertainty quantification by modeling the posterior distribution of network parameters. However, exact posterior inference is computationally intractable, and widely used…

Machine Learning · Computer Science 2025-12-02 Alfredo Reichlin , Miguel Vasco , Danica Kragic
‹ Prev 1 8 9 10 Next ›