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Estimating forest height from Synthetic Aperture Radar (SAR) images often relies on traditional physical models, which, while interpretable and data-efficient, can struggle with generalization. In contrast, Deep Learning (DL) approaches…

Computer Vision and Pattern Recognition · Computer Science 2025-04-15 Ragini Bal Mahesh , Ronny Hänsch

We present Neural Random Forest Imitation - a novel approach for transforming random forests into neural networks. Existing methods propose a direct mapping and produce very inefficient architectures. In this work, we introduce an imitation…

Machine Learning · Computer Science 2024-04-05 Christoph Reinders , Bodo Rosenhahn

Neutral hydrogen (HI) serves as a crucial probe for the Cosmic Dawn and the Epoch of Reionization (EoR). Actual observations of the 21-cm signal often encounter challenges such as thermal noise and various systematic effects. To overcome…

Galaxy cluster mass functions are a function of cosmology, but mass is not a direct observable, and systematic errors abound in all its observable proxies. Mass-free inference can bypass this challenge, but it requires large suites of…

Cosmology and Nongalactic Astrophysics · Physics 2023-10-19 Urmila Chadayammuri , Michelle Ntampaka , John ZuHone , Àkos Bogdàn , Ralph Kraft

We outline the physical picture of the high-redshift Ly-alpha forest that has emerged from cosmological simulations, describe statistical characteristics of the forest that can be used to test theories of structure formation, present a…

Long-term climate projections require running global Earth system models on timescales of hundreds of years and have relatively coarse resolution (from 40 to 160 km in the horizontal) due to their high computational costs. Unresolved…

Quantum Physics · Physics 2025-02-17 Lorenzo Pastori , Arthur Grundner , Veronika Eyring , Mierk Schwabe

Simulation of fluid flow in porous media has many applications, from the micro-scale (cell membranes, filters, rocks) to macro-scale (groundwater, hydrocarbon reservoirs, and geothermal) and beyond. Direct simulation of flow in porous media…

Fluid Dynamics · Physics 2020-04-27 Ying Da Wang , Traiwit Chung , Ryan T. Armstrong , Peyman Mostaghimi

We present a comprehensive analysis of high resolution hydrodynamic simulations in terms of Lyman-alpha and Lyman-beta one dimensional flux power spectra ($P_{\alpha\alpha}$ and $P_{\beta\beta}$). In particular, we focus on the behaviour…

Cosmology and Nongalactic Astrophysics · Physics 2014-12-15 Vid Iršič , Matteo Viel

The observed Lyman-Alpha (Lya) line profile is a convolution of the complex Lya radiative transfer taking place in the interstellar, circumgalactic and intergalactic medium (ISM, CGM, and IGM, respectively). Discerning the different…

We examine the statistics of the low-redshift Lyman-alpha forest from smoothed particle hydrodynamic simulations in light of recent improvements in the estimated evolution of the cosmic ultraviolet background (UVB) and recent observations…

We compare cosmological hydrodynamical simulations combined with the homogeneous metagalactic UV background (UVB) of Haardt & Madau (2012) (HM2012) to observations of the Lyman-alpha forest that are sensitive to the thermal and ionization…

Cosmology and Nongalactic Astrophysics · Physics 2015-09-30 Ewald Puchwein , James S. Bolton , Martin G. Haehnelt , Piero Madau , George D. Becker , Francesco Haardt

Most environmental phenomena, such as wind profiles, ozone concentration and sunlight distribution under a forest canopy, exhibit nonstationary dynamics i.e. phenomenon variation change depending on the location and time of occurrence.…

Machine Learning · Computer Science 2018-04-30 Sahil Garg , Amarjeet Singh , Fabio Ramos

A novel approach is presented for the solution of instantaneous chemical equilibrium problems. The chemical equilibrium can be considered, due to its intrinsically local character, as a mapping of the three-dimensional parameter space…

Astrophysics · Physics 2009-11-11 A. Asensio Ramos , H. Socas-Navarro

We advocate for a new paradigm of cosmological likelihood-based inference, leveraging recent developments in machine learning and its underlying technology, to accelerate Bayesian inference in high-dimensional settings. Specifically, we…

Cosmology and Nongalactic Astrophysics · Physics 2024-09-06 Davide Piras , Alicja Polanska , Alessio Spurio Mancini , Matthew A. Price , Jason D. McEwen

Lyman-alpha forest data probing the post-reionization Universe shows surprisingly large opacity fluctuations over rather large ($\ge$50 comoving Mpc/h) spatial scales. We model these fluctuations using a hybrid approach utilizing the large…

Cosmology and Nongalactic Astrophysics · Physics 2017-03-21 Jonathan Chardin , Ewald Puchwein , Martin G. Haehnelt

We combine the Ly-alpha forest power spectrum (LYA) from the Sloan Digital Sky Survey (SDSS) and high resolution spectra with cosmic microwave background (CMB) including 3-year WMAP, and supernovae (SN) and galaxy clustering constraints to…

Astrophysics · Physics 2009-11-11 Uros Seljak , Anze Slosar , Patrick McDonald

Visualizing the high-redshift Universe is difficult due to the dearth of available data; however, the Lyman-alpha forest provides a means to map the intergalactic medium at redshifts not accessible to large galaxy surveys. Large-scale…

Instrumentation and Methods for Astrophysics · Physics 2015-06-18 Jessi Cisewski , Rupert A. C. Croft , Peter E. Freeman , Christopher R. Genovese , Nishikanta Khandai , Melih Ozbek , Larry Wasserman

Mapping the intergalactic medium (IGM) in Lyman-$\alpha$ emission would yield unprecedented tomographic information on the large-scale distribution of baryons and potentially provide new constraints on the UV background and various feedback…

Astrophysics of Galaxies · Physics 2021-06-22 Joris Witstok , Ewald Puchwein , Girish Kulkarni , Renske Smit , Martin G. Haehnelt

The full-shape correlations of the Lyman alpha (Ly$\alpha$) forest contain a wealth of cosmological information through the Alcock-Paczy\'{n}ski effect. However, these measurements are challenging to model without robustly testing and…

Accurate estimation of forest biomass is crucial for monitoring carbon sequestration and informing climate change mitigation strategies. Existing methods often rely on allometric models, which estimate individual tree biomass by relating it…

Machine Learning · Computer Science 2026-03-06 Habib Pourdelan , Zhengkang Xiang , Hugh Stewart , Cam Nicholson , Martin Tomko , Kourosh Khoshelham
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