arXiv subjects

M. Dong

Publications and source records attributed to M. Dong.

5 recordsLinked to original sources

arXiv2025

Enhancing Particle Identification in Helium-Based Drift Chambers Using Cluster Counting Insights from Beam Test Studies

Particle identification in gaseous detectors traditionally relies on energy loss measurements (dE/dx); however, uncertainties in total energy deposition limit its resolution. The cluster counting technique (dN/dx) offers an alternative approach by exploiting the Poisson-distributed nature of primary ionization, providing a statistically robust method for mass determination. Simulation studies with Garfield++ and Geant4 indicate that dN/dx can achieve twice the resolution of dE/dx in helium-based drift chambers. However, experimental implementation is challenging due to signal overlap in the time domain, complicating the identification of electron peaks and ionization clusters. This paper presents novel algorithms and modern computational techniques to address these challenges, facilitating accurate cluster recognition in experimental data. The effectiveness of these algorithms is validated through four beam tests conducted at CERN, utilizing various helium gas mixtures, gas gains, and wire orientations relative to ionizing tracks. The experiments employ a muon beam (1 GeV/c to 180 GeV/c) with drift tubes of different sizes and sense wire diameters. The analysis explores the Poisson nature of cluster formation, evaluates the performance of different clustering algorithms, and examines the dependence of counting efficiency on the beam particle impact parameter. Furthermore, a comparative study of the resolution achieved using dN/dx and dE/dx is presented.

physics.ins-det↗

arXiv2018

Non-Intrusive Signature Extraction for Major Residential Loads

The data collected by smart meters contain a lot of useful information. One potential use of the data is to track the energy consumptions and operating statuses of major home appliances.The results will enable homeowners to make sound decisions on how to save energy and how to participate in demand response programs. This paper presents a new method to breakdown the total power demand measured by a smart meter to those used by individual appliances. A unique feature of the proposed method is that it utilizes diverse signatures associated with the entire operating window of an appliance for identification. As a result, appliances with complicated middle process can be tracked. A novel appliance registration device and scheme is also proposed to automate the creation of appliance signature database and to eliminate the need of massive training before identification. The software and system have been developed and deployed to real houses in order to verify the proposed method.

eess.SP↗

arXiv2016

Machine learning applied to single-shot x-ray diagnostics in an XFEL

X-ray free-electron lasers (XFELs) are the only sources currently able to produce bright few-fs pulses with tunable photon energies from 100 eV to more than 10 keV. Due to the stochastic SASE operating principles and other technical issues the output pulses are subject to large fluctuations, making it necessary to characterize the x-ray pulses on every shot for data sorting purposes. We present a technique that applies machine learning tools to predict x-ray pulse properties using simple electron beam and x-ray parameters as input. Using this technique at the Linac Coherent Light Source (LCLS), we report mean errors below 0.3 eV for the prediction of the photon energy at 530 eV and below 1.6 fs for the prediction of the delay between two x-ray pulses. We also demonstrate spectral shape prediction with a mean agreement of 97%. This approach could potentially be used at the next generation of high-repetition-rate XFELs to provide accurate knowledge of complex x-ray pulses at the full repetition rate.

physics.data-an↗

arXiv2001

Monoclinic phase in the relaxor-based piezo-/ ferroelectric Pb(Mg$_{1/3}$Nb$_{2/3})O_3$-PbTiO$_3$ system

A ferroelectric monoclinic phase of space group $Cm$ ($M_A$ type) has been discovered in 0.65Pb(Mg$_{1/3}$Nb$_{2/3})O_3$-0.35PbTiO$_3$ by means of high resolution synchrotron X-ray diffraction. It appears at room temperature in a single crystal previously poled under an electric field of 43 kV/cm applied along the pseudocubic [001] direction, in the region of the phase diagram around the morphotropic phase boundary between the rhombohedral (R3m) and the tetragonal (P4mm) phases. The monoclinic phase has lattice parameters a = 5.692 A, b = 5.679 A, c = 4.050 A and $β$ = $90.15^{\circ}$, with the b$_m$-axis oriented along the pseudo-cubic [110] direction . It is similar to the monoclinic phase observed in PbZr$_{1-x}$Ti$_x$O$_3$, but different from that recently found in Pb(Zn$_{1/3}$Nb$_{2/3})O_3$-PbTiO$_3$, which is of space group $Pm$ ($M_C$ type).

cond-mat.mtrl-sci↗

arXiv1992

Elastic String in a Random Potential

We have studied numerically the dynamics of a directed elastic string in a two-dimensional array of quenched random impurities. The string is driven by a constant transverse force and thermal fluctuations are neglected. There is a transition from pinned to unpinned behavior at a critical value $F_T$ of the driving force. At the transition the average string velocity scales with the driving force. The scaling is equally well described by a power law $v_d\sim (F-F_T)^ζ$, with $ζ=0.24\pm0.1$, or by a logarithm, $v_d\sim1/\ln(F-F_T)$. The divergence of the velocity-velocity correlation length at threshold is characterized by an exponent $ν=1.05\pm0.1$.

cond-mat↗