Related papers: Machine Learning Optimization of BEGe Detector Eve…
A method for correcting smearing effects using machine learning technique is presented. Compared to the standard deconvolution approaches in high energy particle physics, the method can use more than one reconstructed variable to predict…
In the search for new particles in high-energy physics, it is crucial to select the Signal Region (SR) in such a way that it is enriched with signal events if they are present. While most existing search methods set the region relying on…
Over the last years, machine learning tools have been successfully applied to a wealth of problems in high-energy physics. A typical example is the classification of physics objects. Supervised machine learning methods allow for significant…
The Pauli Exclusion Principle (PEP) was introduced by the austrian physicist Wolfgang Pauli in 1925. Since then, several experiments have checked its validity. From 2006 until 2010, the VIP (VIolation of the Pauli Principle) experiment took…
Using 58 million $J/\psi$ and 14 million $\psi(2S)$ events collected by the BESII detector at the BEPC, branching fractions or upper limits for the decays $J/\psi$ and $\psi(2S) \to \Lambda \bar{\Lambda} \pi^0$ and $\Lambda \bar{\Lambda}…
We have developed MICROMEGAS (MICRO MEsh GASeous) detectors for detecting {\alpha} particles emitted from an 241-Am standard source. The voltage applied to the ionization region of the detector is optimized for stable operation at room…
The p-type point-contact germanium detectors have been adopted for light dark matter WIMP searches and the studies of low energy neutrino physics. These detectors exhibit anomalous behavior to events located at the surface layer. The…
This paper proposes new methods for analyzing dynamic images registered by multichannel, highly sensitive detectors with low spatial but high temporal resolution. The principal characteristic of the approach is the absence of factorization…
AMEGO-X, the All-sky Medium Energy Gamma-Ray Observatory eXplorer, is a proposed instrument designed to bridge the so-called "MeV gap" by surveying the sky with unprecedented sensitivity from ~100 keV to about one GeV. This energy band is…
The experimental study of nuclear reactions of astrophysical interest is greatly facilitated by a low-background, high-luminosity setup. The Laboratory for Underground Nuclear Astrophysics (LUNA) 400 kV accelerator offers ultra-low…
Single- and multi-photon events with missing energy are selected in 619/pb of data collected by the L3 detector at LEP at centre-of-mass energies between 189GeV and 209GeV. The cross sections of the process e^+e^- -> nu nu gamma (gamma) are…
We construct a Bayesian inference deep learning machine for parameter estimation of gravitational wave events of binaries of black hole coalescence. The structure of our deep Bayesian machine adopts the conditional variational autoencoder…
In order to leverage the full power of quantum noise squeezing with unavoidable decoherence, a complete understanding of the degradation in the purity of squeezed light is demanded. By implementing machine learning architecture with a…
A p-type HPGe detector has been segmented by cutting, with a diamond saw, and etching six circumferential grooves through the Li-diffused dead layer. The degree of segmentation was tested with the 88 keV gamma rays from a well-collimated…
The photon flux resulting from high-energy electron beam interactions with high field systems, such as in the upcoming FACET-II experiments at SLAC National Accelerator Laboratory, may give deep insight into the electron beam's underlying…
The LUXE experiment, currently in design and planning, aims to perform analyses of strong-field quantum electrodynamics interactions by colliding the high-quality high-energy EU.XFEL electron beam with a powerful laser. With the ability to…
Machine-designed control of complex devices or experiments can discover strategies superior to those developed via simplified models. We describe an online optimization algorithm based on Gaussian processes and apply it to optimization of…
The Deep Underground Neutrino Experiment is a next-generation neutrino oscillation experiment that aims to measure $CP$-violation in the neutrino sector as part of a wider physics program. A deep learning approach based on a convolutional…
Here we propose the Reweighted Autoencoded Variational Bayes for Enhanced Sampling (RAVE) method, a new iterative scheme that uses the deep learning framework of variational autoencoders to enhance sampling in molecular simulations. RAVE…
BESIII is the particle detector of the Beijing Electron-Positron Collider, which is a {\tau} -charm factory working at energies around 4 GeV. The first part of the detector, around the collision site, is called the Main Drift Chamber, MDC.…