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Since the variety of their light curve morphologies, the vast majority of the known heartbeat stars (HBSs) have been discovered by manual inspection. Machine learning, which has already been successfully applied to the classification of…
Eclipsing binaries are crucial astrophysical laboratories for studying stellar parameters and evolutionary processes. In this study, we constructed a machine-learning-based model for systematic phenomenological classification of eclipsing…
In this paper we use electrically detected optical excitation spectroscopy of individual erbium ions in silicon to determine their optical and paramagnetic properties simultaneously. We demonstrate that this high spectral resolution…
We assess the impact of accurate, self-consistent modelling of thermal effects in neutron-star merger remnants in the context of third-generation gravitational-wave detectors. This is done through the usage, in Bayesian model selection…
Analysis of Electrochemical Impedance Spectroscopy (EIS) data for electrochemical systems often consists of defining an Equivalent Circuit Model (ECM) using expert knowledge and then optimizing the model parameters to deconvolute various…
In this work, we test whether gradient-boosting algorithms, trained on broadband photometric data from traditional Lyman-$\alpha$ emitting (LAE) surveys, can efficiently and accurately identify LAE candidates from typical star-forming…
This paper explores using a Long short-term memory (LSTM) based sequence autoencoder to learn interesting features for detecting surveillance aircraft using ADS-B flight data. An aircraft periodically broadcasts ADS-B (Automatic Dependent…
We investigate the relationship between different transients such as blinkers detected in images taken at 304~{\AA}, extreme ultraviolet coronal bright points (ECBPs) at 193~{\AA}, X-ray coronal bright points (XCBPs) at 94~{\AA} on AIA, and…
Epilepsy is a neurological condition such that it affects the brain and the nervous system. It is characterized by recurrent seizures, which are physical reactions to sudden, usually brief, excessive electrical discharges in a group of…
The Atmospheric Imaging Assembly (AIA) onboard the Solar Dynamics Observatory (SDO) returns high-resolution images of the solar atmosphere in seven extreme ultraviolet (EUV) wavelength channels. The images are processed on the ground to…
Solar activity plays a quintessential role in influencing the interplanetary medium and space-weather around the Earth. Remote sensing instruments onboard heliophysics space missions provide a pool of information about the Sun's activity…
We present a new automated algorithm to identify, track, and characterize small-scale brightening associated with solar eruptive phenomena observed in H{\alpha}. The temporal spatially-localized changes in chromospheric intensities can be…
We propose inelastic electron tunneling spectroscopy scanning tunneling microscopy (IETS-STM) as a means of exciting and observing intrinsic localized modes (breathers) in a macromolecule. As a demonstration, inelastic tunneling features of…
The use of highly sensitive pixelated direct detectors has dramatically improved the performance of high energy instrumentation such as transmission electron microscopy. Here, we describe a recently developed monolithic active pixel sensor…
Scientists at the Berkeley SETI Research Center are Searching for Extraterrestrial Intelligence (SETI) by a new signal detection method that converts radio signals into spectrograms through Fourier transforms and classifies signals…
The detection of ultra-high-energy (UHE) neutrinos in the EeV range is the goal of current and future in-ice radio arrays at the South Pole and in Greenland. Here, we present a deep neural network that can reconstruct the main neutrino…
Analyzing the physical and chemical properties of single DNA based molecular machines such as polymerases and helicases often necessitates to track stepping motion on the length scale of base pairs. Although high resolution instruments have…
Gamma-Ray bursts (GRBs) have been traditionally classified based on their duration. The increasing number of extended emission (EE) GRBs, lasting typically more than 2 seconds but with properties similar to those of a short GRBs, challenges…
(Frankle & Carbin, 2019) shows that there exist winning tickets (small but critical subnetworks) for dense, randomly initialized networks, that can be trained alone to achieve comparable accuracies to the latter in a similar number of…
In deep, ground-based imaging, about 15%-30% of object detections are expected to correspond to two or more true objects - these are called ``unrecognized blends''. We use Machine Learning algorithms to detect unrecognized blends in deep…