Related papers: FLAME: Fitting Ly$\alpha$ Absorption lines using M…
We extend our super-resolution and emulation framework for cosmological dark matter simulations to include hydrodynamics. We present a two-stage deep learning model to emulate high-resolution (HR-HydroSim) baryonic fields from…
We have performed high-resolution hydrodynamic simulations of the Lyman-alpha forest in a variety of popular cold dark matter dominated cosmologies, including a low density and a vacuum-dominated model. The fluctuation amplitude of these…
A purely data-driven approach using deep convolutional neural networks is discussed in the context of Large Eddy Simulation (LES) of turbulent premixed flames. The assessment of the method is conducted a priori using direct numerical…
In this paper we show how to use data on Lyman-limit and Damped Lyman-alpha absorption systems to derive the hydrogen ionization fractions and the distribution of the face-on total gas column density. We consider axially symmetric, randomly…
Rapid and accurate wildfire detection is crucial for emergency response and environmental management. In airborne and spaceborne missions, real-time algorithms must distinguish between no fire, active fire, and post-fire conditions, and…
We present two new tools for studying and modelling metal absorption lines in the circumgalactic medium. The first tool, dubbed ``NMF Profile Maker'' (NMF$-$PM), uses a non-negative matrix factorization (NMF) method and provides a robust…
Visual food recognition in real-world dietary logging scenarios naturally exhibits severe data imbalance, where a small number of food categories appear frequently while many others occur rarely, resulting in long-tailed class…
Federated Learning (FL) has emerged as a new paradigm for training machine learning models distributively without sacrificing data security and privacy. Learning models on edge devices such as mobile phones is one of the most common use…
Convolutional networks require extensive image annotation, which can be costly and time-consuming. Feature Learning from Image Markers (FLIM) tackles this challenge by estimating encoder filters (i.e., kernel weights) from user-drawn…
Successful visual navigation depends upon capturing images that contain sufficient useful information. In this letter, we explore a data-driven approach to account for environmental lighting changes, improving the quality of images for use…
In the present work, accurate determination of single-particle ignition is focused on using high-speed optical diagnostics combined with machine learning approaches. Ignition of individual particles in a laminar flow reactor are visualized…
This paper proposes a novel calibration-free wavelength modulated spectroscopy (WMS) spectral fitting technique based on the firefly algorithm. The technique by simulating the information interaction behavior between fireflies to achieve…
We explore the use of Deep Learning to infer physical quantities from the observable transmitted flux in the Lyman-alpha forest. We train a Neural Network using redshift z=3 outputs from cosmological hydrodynamic simulations and mock…
Absorption-line systems detected in high resolution quasar spectra can be used to compare the value of dimensionless fundamental constants such as the fine-structure constant, alpha, and the proton-to-electron mass ratio, mu = m_p/m_e, as…
Recently, vision transformers were shown to be capable of outperforming convolutional neural networks when pretrained on sufficiently large datasets. Vision transformer models show good accuracy on large scale datasets, with features of…
Unintended radiated emissions arise during the use of electronic devices. Identifying and mitigating the effects of these emissions is a key element of modern power engineering and associated control systems. Signal processing of the…
We present a new high-resolution N-body algorithm for cosmological simulations. The algorithm employs a traditional particle-mesh technique on a cubic grid and successive multilevel relaxations on the finer meshes, introduced recursively in…
Damped Lyman-$\alpha$ Absorber(DLA) of HI 21cm system is an ideal probe to directly measure cosmic acceleration in real-time cosmology via Sandage-Loeb(SL) test. During short observations toward two DLAs in the commissioning progress of…
In this article, we explore the challenges and evolution of two key technologies in the current field of AI: Vision Transformer model and Large Language Model (LLM). Vision Transformer captures global information by splitting images into…
In chemistry tabulations and Flamelet combustion models, the Flamelet Generated Manifold (FGM) is recognized for its precision and physical representation. The practical implementation of FGM requires a significant allocation of memory…