Related papers: Enhancing Particle Identification in Helium-Based …
An efficient neutron detection system with good energy resolution is required to correctly characterize decays of neutron-rich nuclei where $\beta-$delayed neutron emission is a dominant decay mode. The Neutron dEtector with Xn Tracking…
In this paper we show that 1-electron properties such as Compton profiles and structure factors of crystals can be asymptotically retrieved through cluster-based calculations, followed by an appropriate partition of the 1-electron reduced…
CR-39 solid-state nuclear track detectors are widely used in fusion research for detecting charged particles produced in fusion reactions. However, analyzing increasingly complex and large-scale CR-39 track images to extract meaningful…
Conductance-based graph clustering has been recognized as a fundamental operator in numerous graph analysis applications. Despite the significant success of conductance-based graph clustering, existing algorithms are either hard to obtain…
Accurate measuring the location and orientation of individual particles in a beam monitoring system is of particular interest to researchers in multiple disciplines. Among feasible methods, gaseous drift chambers with hybrid pixel sensors…
A gas electron multiplier (GEM) detector with a gadolinium cathode has been developed to explore its potential application as a neutron detector. It consists of three standard-sized ($10\times 10$ cm${}^{2}$) GEM foils and a thin gadolinium…
We show that a general purpose clusterization algorithm, Deterministic Annealing, can be adapted to the problem of jet identification in particle production by high energy collisions. In particular we consider the problem of jet searching…
The mission of the Compressed Baryonic Matter (CBM) experiment at the future Facility for Antiproton and Ion Research (FAIR) in Darmstadt is to explore the QCD phase diagram at high net baryon densities likely to exist in the core of…
The conventional way to search for long-lived CHArged Massive Particles (CHAMPs) is to identify slow (small $\beta$) tracks using delayed time of flight and high ionization energy loss. But at the 7-14 TeV center of mass energy of the LHC,…
This paper addresses a detection problem where several spatially distributed sensors independently observe a time-inhomogeneous stochastic process. The task is to decide between two hypotheses regarding the statistics of the observed…
Density-based spatial clustering of applications with noise (DBSCAN) is a data clustering algorithm which has the high-performance rate for dataset where clusters have the constant density of data points. One of the significant attributes…
Martian terrain recognition is pivotal for advancing our understanding of topography, geomorphology, paleoclimate, and habitability. While deep clustering methods have shown promise in learning semantically homogeneous feature embeddings…
Particle identification in large high-energy physics experiments typically relies on classifiers obtained by combining many experimental observables. Predicting the probability density function (pdf) of such classifiers in the multivariate…
This article proposes a new method to measure the proton detector efficiency for use in "beam" determinations of the free neutron lifetime. There is currently a 4{\sigma} disagreement between the "beam" and "storage" methods of measuring…
Most density-based clustering methods largely rely on how well the underlying density is estimated. However, density estimation itself is also a challenging problem, especially the determination of the kernel bandwidth. A large bandwidth…
This much revised and shortened PhD thesis contains many ideas that I could not follow up on, like self destructing beams in scattering cells, the depletion enhancing Wittig tube, ionic seeding via beta-decay foil or Langmuir-Taylor…
Clustering is a cornerstone of modern data analysis. Detecting clusters in exploratory data analyses (EDA) requires algorithms that make few assumptions about the data. Density-based clustering algorithms are particularly well-suited for…
High precision experiments with muons and pions often require tracking charged particles with $O(100~\mu\mathrm{m})$ single-hit resolution, possibly with particle identification capabilities, down to very low momenta ($p \lesssim…
We present studies of electron identification (eID) in the MPD experiment at NICA using machine learning techniques. The goal is to improve electron identification efficiency while preserving high purity, which is crucial for dielectron…
Deuterium fractionation in molecular ions, in particular HCO+, has been extensively used to estimate the degree of ionization in molecular clouds. This paper reviews recent work on ionization degree in homogeneous clouds. We will show that…