Related papers: Deep Forest: Neural Network reconstruction of inte…
The reionization of the second electron of helium shapes the physical state of intergalactic gas at redshifts between 2 < z < 5. Because performing full in situ radiative transfer in hydrodynamic simulations is computationally expensive for…
Multimode fiber (MMF) imaging aided by machine learning holds promise for numerous applications, including medical endoscopy. A key challenge for this technology is the sensitivity of modal transmission characteristics to environmental…
We use machine learning models to predict ion density and electron temperature from visible emission spectra, in a high energy density pulsed-power-driven aluminum plasma, generated by an exploding wire array. Radiation transport…
Sea Surface Temperature (SST) reconstructions from satellite images affected by cloud gaps have been extensively documented in the past three decades. Here we describe several Machine Learning models to fill the cloud-occluded areas…
We use a convolutional neural network to retrieve the internuclear distance in the two-dimensional H$_2^{+}$ molecule ionized by a strong few-cycle laser pulse based on the photoelectron momentum distribution. We show that a neural network…
The 21-cm forest, comprising narrow absorption features imprinted on the radio spectra of high-redshift radio-loud quasars by intervening neutral hydrogen, offers a uniquely sensitive probe of the thermal state of the neutral intergalactic…
We present a new suite of over 1,500 cosmological N-body simulations with varied Warm Dark Matter (WDM) models ranging from 2.5 to 30 keV. We use these simulations to train Convolutional Neural Networks (CNNs) to infer WDM particle masses…
Land surface temperature (LST) retrieval from remote sensing data is pivotal for analyzing climate processes and surface energy budgets. However, LST retrieval is an ill-posed inverse problem, which becomes particularly severe when only a…
We present two measurements of the temperature-density relationship (TDR) of the intergalactic medium (IGM) in the redshift range $2.55 < z < 2.95$ using a sample of 13 high-quality quasar spectra and high resolution numerical simulations…
We propose a deep learning analyzing technique with convolutional neural network (CNN) to predict the evolutionary track of the Epoch of Reionization (EoR) from the 21-cm differential brightness temperature tomography images. We use…
We have constructed a Bayesian neural network able of retrieving tropospheric temperature profiles from rotational Raman-scatter measurements of nitrogen and oxygen and applied it to measurements taken by the RAman Lidar for Meteorological…
Several different methods are regularly used to infer the properties of the neutral interstellar medium (ISM) using atomic hydrogen (H I) 21cm absorption and emission spectra. In this work, we study various techniques used for inferring ISM…
Observations of resolved HeII Lyman alpha absorption in spectra of two QSO's suggest that the epoch of helium ionization occurred at z~3. Proximity zones in the spectra of the quasars (z=3.18, 3.285) at 304 A resemble Stromgren spheres,…
Estimates of the metagalactic hydrogen ionization rate from the Lyman-alpha forest opacity in QSO absorption spectra depend on the complex density distribution of neutral hydrogen along the line-of-sight. We use a large suite of high…
Reionization leads to large spatial fluctuations in the intergalactic temperature that can persist well after its completion. We study the imprints of such fluctuations on the $z\sim5$ Ly$\alpha$ forest flux power spectrum using a set of…
The thermal history and structure of the intergalactic medium (IGM) at $z \geq 4$ is an important boundary condition for reionization, and a key input for studies using the Ly$\alpha$ forest to constrain the masses of alternative dark…
The remarkable efficiency of the UVES spectrograph at the VLT has made it possible to push high-resolution, high-S/N ground observations of the Ly-a forest down to z~1.5, gaining new insight into the physical conditions of the intergalactic…
Many models of early structure formation predict a period of heating immediately preceding reionization, when X-rays raise the gas temperature above that of the cosmic microwave background. These X-rays are often assumed to heat the…
We demonstrate a deep-learning-based fibre imaging system which can transfer real-time artifact-free cell images through a meter-long Anderson localizing optical fibre. The cell samples are illuminated by an incoherent LED light source. A…
Deep learning is having a tremendous impact in many areas of computer science and engineering. Motivated by this success, deep neural networks are attracting an increasing attention in many other disciplines, including physical sciences. In…