Related papers: Deep Forest: Neural Network reconstruction of inte…
We derive new constraints on models of decaying and annihilating dark matter (DM) by requiring that the energy injected into the intergalactic medium (IGM) not overheat it at late times, when measurements of the Lyman-$\alpha$ forest…
Proton resonance frequency (PRF) based MR thermometry is essential for focused ultrasound (FUS) thermal ablation therapies. This work aims to enhance temporal resolution in dynamic MR temperature map reconstruction using an improved deep…
We investigate the thermal and ionization history of Lyman alpha clouds photoionized by a time--dependent UV background, including non equilibrium effects. The results show that it is possible to obtain temperatures as low as T~15000 K (or,…
At $z \lesssim 1$, shock heating caused by large-scale velocity flows and possibly violent feedback from galaxy formation, converts a significant fraction of the cool gas ($T\sim 10^4$ K) in the intergalactic medium (IGM) into warm-hot…
Observations of the intergalactic medium (IGM) suggest that quasars reionize HeII in the IGM at z ~ 3. We have run a set of 190 and 430 comoving Mpc simulations of HeII being reionized by quasars to develop an understanding of the nature of…
We analyse the formation of broad absorption troughs in the spectra of high-redshift sources in the redshift range $5 \le z \le 15$ for two observationally motivated reionization histories inferred from distant galaxy spectra and CMB…
The mid-infrared spectra of galaxies are rich in features such as the Polycyclic Aromatic Hydrocarbon (PAH) and silicate dust features which give valuable information about the physics of galaxies and their evolution. For example they can…
Changing climate conditions threaten the natural permafrost thaw-freeze cycle, leading to year-round soil temperatures above 0{\deg}C. In Alaska, the warming of the topmost permafrost layer, known as the active layer, signals elevated…
The epoch of hydrogen reionization is complete by $z=5$, but its progression at higher redshifts is uncertain. Measurements of Ly$\alpha$ forest opacity show large scatter at $z<6$, suggestive of spatial fluctuations in neutral fraction…
We introduce an efficient and accurate alternative to full hydrodynamic simulations, Hydro-PM (HPM), for the study of the low column density Lyman-alpha forest. It consists of a Particle-Mesh solver, modified to compute, in addition to the…
During reionization, the intergalactic medium is heated impulsively by supersonic ionization fronts (I-fronts). The peak gas temperatures behind the I-fronts, $T_\mathrm{reion}$, are a key uncertainty in models of the thermal history after…
In this work, ML models were used to predict the plasma temperature using the dataset obtained by implementing the CR-model for Na-like Krypton. The models included in the study are: Linear Regression, Lasso Regression, Support Vector…
We present a random forest framework for predicting circumgalactic medium (CGM) physical conditions from quasar absorption line observables, trained on a sample of Voigt profile-fit synthetic absorbers from the Simba cosmological…
In this work, deep neural networks made up of multiple hidden Long Short-Term Memory (LSTM) and Feedforward layers are trained to predict the thermal behavior of the joint motors of robot manipulators. A model-free and scalable approach is…
Simulations of high-energy density physics often need non-local thermodynamic equilibrium (NLTE) opacity data. This data, however, is expensive to produce at relatively low-fidelity. It is even more so at high-fidelity such that the opacity…
Heat management is crucial for state-of-the-art applications such as passive radiative cooling, thermally adjustable wearables, and camouflage systems. Their adaptive versions, to cater to varied requirements, lean on the potential of…
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…
Traditionally, 1D models based on scaling laws have been used to parameterized convective heat transfer rocks in the interior of terrestrial planets like Earth, Mars, Mercury and Venus to tackle the computational bottleneck of high-fidelity…
A key challenge for computationally intensive state-of-the-art Earth System models is to distinguish global warming signals from interannual variability. Here we introduce DLESyM, a parsimonious deep learning model that accurately simulates…
We introduce a novel method for reconstructing surface temperatures through occluding forest vegetation by combining signal processing and machine learning. Our goal is to enable fully automated aerial wildfire monitoring using autonomous…