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At least 73 records · Page 4

The forward TPC system of the NA61/SHINE experiment at CERN: a tandem TPC concept

This paper presents the Forward Time Projection Chamber (FTPC) system of the NA61/SHINE experiment at the CERN SPS accelerator. This TPC system applies a novel tandem-TPC design to reduce the background originating from particle tracks not synchronous with the event trigger. The FTPC system is composed of three chambers with alternating drift field directions. The chambers were installed directly along the beamline region of the NA61/SHINE detector in a medium- to high-intensity (10-100 kHz) hadron or ion beam. The tandem TPC system has proved to be capable of rejecting out-of-time background tracks not associated with a primary interaction. In addition, the system performs tracking and inclusive dE/dx particle identification for particles at and near the beam momentum. This shows that a tandem-TPC-based chamber design may be used also in other experimental applications with a demand for low material budget, tracking capability, and the need for dE/dx particle identification, all while in the presence of a relatively high particle flux.

47 OTHER INSTRUMENTATION↗

Image segmentation for uranium isotopic analysis by SIMS: Combined adaptive thresholding and marker controlled watershed approach

A novel approach to particle identification and particle isotope ratio determination has been developed for nuclear safeguard applications. This particle search approach combines an adaptive thresholding algorithm and marker-controlled watershed segmentation (MCWS) transform, which improves the secondary ion mass spectrometry (SIMS) isotopic analysis of uranium containing particle populations for nuclear safeguards applications. The Niblack assisted MCWS approach (a.k.a. SEEKER) developed for this work has improved the identification of isotopically unique uranium particles under conditions that have historically presented significant challenges for SIMS image data processing techniques. Particles obtained from five NIST uranium certified reference materials (CRM U129A, U015, U150, U500 and U850) were successfully identified in regions of SIMS image data 1) where a high variability in image intensity existed, 2) where particles were touching or were in close proximity to one another and/or 3) where the magnitude of ion signal for a given region was count limited. Analysis of the isotopic distributions of uranium containing particles identified by SEEKER showed four distinct, accurately identified 235U enrichment distributions, corresponding to the NIST certified 235U/238U isotope ratios for CRM U129A/U015 (not statistically differentiated), U150, U500 and U850. Additionally, comparison of the minor uranium isotope (234U, 235U and 236U) atom percent values verified that, even in the absence of high precision isotope ratio measurements, SEEKER could be used to segment isotopically unique uranium particles from SIMS image data. Although demonstrated specifically for SIMS analysis of uranium containing particles for nuclear safeguards, SEEKER has application in addressing a broad set of image processing challenges.

adaptive thresholding↗

Performance of a Quintuple-GEM Based RICHDetector Prototype

Cerenkov technology is often the optimal choice for particle identification in high energy particle collision applications. Typically, the most challenging regime is at high pseudorapidity (forward) where particle identification must perform well at high laboratory momenta. For the upcoming electron ion collider (EIC), the physics goals require hadron (π, K, p) identification up to ~50 GeV/c. In this region Cerenkov ring-imaging (RICH) is the most viable solution. The speed of light in a radiator medium is inversely proportional to the refractive index. Hence, for particle identification (PID) reaching out to high momenta a small index of refraction is required. Unfortunately, the lowest indices of refraction also result in the lowest light yield ([(dNγ)/dx] ∝ sin2(θC)) driving up the radiator length and thereby the overall detector cost. In this paper we report on a successful test of a compact RICH detector (1 meter radiator) capable of delivering in excess of 10 photoelectrons per ring with a low index radiator gas (CF4). The detector concept is a natural extension of the PHENIX hadron-blind detector (HBD) achieved by adding focusing capability at low wavelength and adequate gain for high efficiency detection of single-electron induced avalanches. Our results indicate that this technology is indeed a viable choice in the forward direction of the EIC. The setup and results are described within.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Using machine learning for particle track identification in the CLAS12 detector

Particle track reconstruction is the most computationally intensive process in nuclear physics experiments. Traditional algorithms use a combinatorial approach that exhaustively tests track measurements ("hits") to identify those that form an actual particle trajectory. In this article, we describe the development of four machine learning (ML) models that assist the tracking algorithm by identifying valid track candidates from the measurements in drift chambers. Several types of machine learning models were tested, including: Convolutional Neural Networks (CNN), Multi-Layer Perceptrons (MLP), Extremely Randomized Trees (ERT) and Recurrent Neural Networks (RNN). As a result of this work, an MLP network classifier was implemented as part of the CLAS12 reconstruction software to provide the tracking code with recommended track candidates. The resulting software achieved accuracy of greater than 99% and resulted in an end-to-end speedup of 35% compared to existing algorithms.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Direct reaction experimental studies with beams of radioactive tin ions

The tin chain of isotopes provides a unique region in which to investigate the evolution of single-particle structure, spreading from N = 50 at {sup 100}Sn, through 10 stable isotopes and the N = 82 shell closure at {sup 132}Sn out into the r-process path. Direct reactions performed on radioactive ion beams are sensitive spectroscopic tools for studying exotic nuclei. Here we present one experiment knocking out neutrons from tin isotopes that are already neutron deficient and two reactions that add a neutron to neutron-rich {sup 130}Sn. Both techniques rely on selective particle identification and the measurement of γ rays in coincidence with charged ions. We present the goals of the two experiments and the particle identification for the channels of interest. The final results will be presented in future publications.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Calorimetric classification of track-like signatures in liquid argon TPCs using MicroBooNE data

The MicroBooNE liquid argon time projection chamber located at Fermilab is a neutrino experiment dedicated to the study of short-baseline oscillations, the measurements of neutrino cross sections in liquid argon, and to the research and development of this novel detector technology. Accurate and precise measurements of calorimetry are essential to the event reconstruction and are achieved by leveraging the TPC to measure deposited energy per unit length along the particle trajectory, with mm resolution. We describe the non-uniform calorimetric reconstruction performance in the detector, showing dependence on the angle of the particle trajectory. Such non-uniform reconstruction directly affects the performance of the particle identification algorithms which infer particle type from calorimetric measurements. This work presents a new particle identification method which accounts for and effectively addresses such non-uniformity. The newly developed method shows improved performance compared to previous algorithms, illustrated by a 93.7% proton selection efficiency and a 10% muon mis-identification rate, with a fairly loose selection of tracks performed on beam data. The performance is further demonstrated by identifying exclusive final states in ν μ CC interactions. While developed using MicroBooNE data and simulation, this method is easily applicable to future LArTPC experiments, such as SBND, ICARUS, and DUNE.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Pileup mitigation at CMS in 13 TeV data

With increasing instantaneous luminosity at the LHC come additional reconstruction challenges. At high luminosity, many collisions occur simultaneously within one proton-proton bunch crossing. The isolation of an interesting collision from the additional “pileup” collisions is needed for effective physics performance. In the CMS Collaboration, several techniques capable of mitigating the impact of these pileup collisions have been developed. Such methods include charged-hadron subtraction, pileup jet identification, isospin-based neutral particle “δβ” correction, and, most recently, pileup per particle identification. This paper surveys the performance of these techniques for jet and missing transverse momentum reconstruction, as well as muon isolation. The analysis makes use of data corresponding to 35.9 fb−1 collected with the CMS experiment in 2016 at a center-of-mass energy of 13 TeV. The performance of each algorithm is discussed for up to 70 simultaneous collisions per bunch crossing. Significant improvements are found in the identification of pileup jets, the jet energy, mass, and angular resolution, missing transverse momentum resolution, and muon isolation when using pileup per particle identification.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Electron/hadron separation with the TRD based on GaAs pixel detectors

Transition Radiation Detectors (TRDs) are widely used for particle identification in both high-energy physics and astroparticle physics. They are typically equipped with gaseous detectors. The main limitation of these types of detectors is that TR photons and ionization losses cannot be decoupled, which significantly reduces the particle separation power. Recent advancements in the development of pixel detectors based on GaAs sensors offer a unique opportunity to effectively detect TR photons and separate them from ionization losses. Such detectors represent novel devices that combine precise tracking capabilities with particle identification (PID) properties. The present work is dedicated to an experimental study of particle identification properties of the TRD prototype based on 500 μ m-thick GaAs sensor bonded to a Timepix3 chip. Studies were performed at the CERN SPS and it was shown that at a particle momentum of 20 GeV/c, the probability of misidentifying a hadron as an electron is below 10 −2 for an electron detection efficiency of 98%–99%, and it is 1 . 6⋅10 −4 for electron detection efficiency of 90%. This performance surpasses the electron/hadron rejection power of all known TRDs by an order of magnitude for the same detector length.

GaAs detectors↗

Identification of long-lived charged particles using time-of-flight systems at the upgraded LHC detectors

We study the impact of picosecond precision timing detection systems on the LHC experiments' long-lived particle search program during the HL-LHC era. We develop algorithms that allow us to reconstruct the mass of such charged particles and perform particle identification using the time-of-flight measurement. We investigate the reach for benchmark scenarios as a function of the timing resolution, and find sensitivity improvement of up to a factor of ten, depending on the new heavy particle mass.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

MO-FG-204-06: A New Algorithm for Gold Nano-Particle Concentration Identification in Dual Energy CT

Purpose: Gold nano-particle (GNP) has recently attracted a lot of attentions due to its potential as an imaging contrast agent and radiotherapy sensitiser. Imaging the GNP at its low contraction is a challenging problem. We propose a new algorithm to improve the identification of GNP based on dual energy CT (DECT). Methods: We consider three base materials: water, bone, and gold. Determining three density images from two images in DECT is an under-determined problem. We propose to solve this problem by exploring image domain sparsity via an optimization approach. The objective function contains four terms. A data-fidelity term ensures the fidelity between the identified material densities and the DECT images, while the other three terms enforces the sparsity in the gradient domain of the three images corresponding to the density of the base materials by using total variation (TV) regularization. A primal-dual algorithm is applied to solve the proposed optimization problem. We have performed simulation studies to test this model. Results: Our digital phantom in the tests contains water, bone regions and gold inserts of different sizes and densities. The gold inserts contain mixed material consisting of water with 1g/cm3 and gold at a certain density. At a low gold density of 0.0008 g/cm3, the insert is hardly visible in DECT images, especially for those with small sizes. Our algorithm is able to decompose the DECT into three density images. Those gold inserts at a low density can be clearly visualized in the density image. Conclusion: We have developed a new algorithm to decompose DECT images into three different material density images, in particular, to retrieve density of gold. Numerical studies showed promising results.

60 APPLIED LIFE SCIENCES↗

Open Specy 1.0: Automated (Hyper)spectroscopy for Microplastics

Microplastic spectral analysis is one of the most time-consuming processes in studying microplastic pollution, often requiring days per sample. Researchers are transitioning to automated batch and hyperspectral image analysis techniques to enhance efficiency. Open Specy, initially aimed at manual single-spectrum analysis, has now integrated automated methods. This updated version, Open Specy 1.0, introduces several new features, including two algorithms for automated processing (smoothing and particle compression), an extensive library containing over 40,000 open-source Raman and FTIR spectra, and two machine learning classifiers (logistic regression and k medoids) developed from this library. Furthermore, it includes a revamped user interface, an R package, and a benchmark data set for testing future advancements in automated techniques. Researchers evaluated various configurations for hyperspectral smoothing, particle identification, compression, and splitting, to achieve combined recovery rates between 50 and 150% particle counts, identities, and sizes with a coefficient of variation (CV) of less than 40% (the accredited standard). Mean absorbance times the standard deviation provided a consistent particle identification. Hyperspectral smoothing led to a 96% combined recovery rate and reduced variability (CV = 38%) compared to the 86% recovery (CV = 83%) of nonsmoothed controls. Additionally, compressing spectra for particles was significantly faster (>3x) and showed similar accuracy but with reduced variability than processing each pixel individually. Key challenges persist in automating spectral analysis, particularly in refining particle splitting algorithms, and improving identification routines to minimize false positives and negatives. In conclusion, new methods in sample preparation for better stabilization and dispersion of particles could overcome some of these issues.

13 HYDRO ENERGY↗

Characterization of Solidification Microstructures in Vacuum Arc Remelted Nickel Alloy 718

Digital image analysis techniques were developed to autonomously characterize dendritic solidification features in microstructures of a nickel alloy 718 ingot produced by vacuum arc remelting (VAR). Automated macrophotography was implemented to image microstructures and produce large image montages of etched ingot cross sections. Two image analysis techniques, particle identification and two-point correlation, were applied to autonomously measure primary dendrite arm orientation and secondary dendrite arm spacing from the image montages. Particle identification measured individual dendritic features. The two-point correlation technique measured averaged feature values over defined image areas. These methods are described and compared. Melt pool profile and solidification time histories were reconstructed from primary dendrite arm orientation and secondary dendrite arm spacing measurements, respectively. These characterization techniques provide two new methods of reconstructing melt pool profiles and solidification times in cast ingots. The information produced is expected to be useful in the validation of computational models for solidification during VAR, similar remelting processes, and general casting processes that produce dendritic solidification features.

36 MATERIALS SCIENCE↗

Design and R&D of RICH detectors for EIC experiments

An Electron-Ion Collider (EIC) has been proposed to further explore the strong force and QCD, focusing on the structure and the interaction of gluon-dominated matter. A generic detector R& D program (EIC PID consortium) for the particle identification in EIC experiments was formed to explore technologically advanced solutions in this scope. In this context two Ring Imaging Cherenkov (RICH) counters have been proposed: a modular RICH detector which consists of an aerogel radiator, a Fresnel lens, a mirrored box, and pixelated photon sensor; a dual-radiator RICH, consisting of an aerogel radiator and C 2 F 6 gas in a mirror-focused configuration. We present the simulations of the two detectors and their estimated performance.

electron-ion collider↗

Fast timing with µRWELL-PICOSEC detector technology

The µWELL-PICOSEC detector, which is based on Resistive Micro-Well (µRWELL) technology, is a novel concept for fast timing gaseous detectors that can provide timing resolution in the tens of picosecond range, making it ideal candidate for time-of-flight (TOF) technology for particle identification (PID) in particle physics experiments as well as for future medical instrumentation. The µRWELL-PICOSEC concept is based on a Cerenkov radiator that produces Cerenkov photons from high energetic charged particles, a photocathode layer that converts the Cerenkov photons into primary electrons, a µRWELL amplification layer that multiply the electrons through amplification in a CF4-based gas mixture and a pad-segmentation anode readout coupled with fast timing electronics to provide fast signal. Beam tests were carried out at the CERN SPS H4 beamline in summer 2023 and 2024. Preliminary results show timing performance of the order of 23 ps achievable with µRWELL-PICOSEC prototype. and position scan of the 100-pads of a multi-channel prototype was also performed to study time response uniformity of large area detector. In this talk, after a brief overview of the PICOSEC technology, we will present recent results with different single channel µRWELL-PICOSEC prototype designs and also the position scan results of the 100-pads large prototype to study timing response uniformity for large area µRWELL-PICOSEC detector. Finally, we will discuss the ongoing R&D effort to further improve the timing resolution and allow good position capabilities through charge sharing for large area.

Gnanvo, Kondo↗

(Multi-)strange hadron and light (anti-)nuclei production with ALICE at the LHC

Thanks to its excellent tracking performance and particle identification capabilities, the ALICE detector allows for the identification of light (anti-)(hyper)nuclei and for the measurement of (multi-)strange particles over a wide range of transverse momentum. Deuterons, {sup 3}He and {sup 4}He and their corresponding anti-nuclei are identified via their specific energy loss in the Time Projection Chamber and the velocity measurement provided by the Time-Of-Flight detector. Strange and multi-strange baryons and mesons as well as (anti-)hypertritons are reconstructed via their topological decays. Detailed measurements of (multi-)strange hadron production in pp, p–Pb and Pb–Pb collision and of light (anti-)nuclei and (anti-)hypertritons in Pb–Pb collisions with ALICE at the LHC are presented. The experimental results will be compared with the predictions of both statistical hadronization and coalescence models.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗