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At least 829 records · Page 46

Projected sensitivities of the LUX-ZEPLIN experiment to new physics via low-energy electron recoils

LUX-ZEPLIN is a dark matter detector expected to obtain world-leading sensitivity to weakly-interacting massive particles interacting via nuclear recoils with a ∼7-tonne xenon target mass. This paper presents sensitivity projections to several low-energy signals of the complementary electron recoil signal type: 1) an effective neutrino magnetic moment, and 2) an effective neutrino millicharge, both for 𝑝⁢𝑝-chain solar neutrinos, 3) an axion flux generated by the Sun, 4) axionlike particles forming the Galactic dark matter, 5) hidden photons, 6) mirror dark matter, and 7) leptophilic dark matter. World-leading sensitivities are expected in each case, a result of the large 5.6 t 1000 d exposure and low expected rate of electron-recoil backgrounds in the <100 keV energy regime. A consistent signal generation, background model and profile-likelihood analysis framework is used throughout.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DUAL-PARTICLE DOSEMETER BASED ON ORGANIC SCINTILLATOR

Abstract Traditionally available handheld dosemeters are generally sensitive to only one type of radiation: neutrons or photons. Some dosemeters also rely on very specific attenuation correlations between response and dose, are not scalable in size and multiple dosemeters are required to characterise mixed-particle fields. The research presented here serves as a proof-of-concept for a method to simultaneously measure dose rates from neutrons and photons using a particle discriminating organic scintillation detector without the need for spectral deconvolution. The method was compared with traditional instruments and to simulation. Isotopic photon dose rates measured with this method were within 4% of simulated truth, whereas fission spectrum neutron dose rates were measured within 21%. Measurements of dose rates from both particles agree with simulated truth better than traditional instruments. This new method allows for measurement of dose equivalent from both neutrons and photons with a single instrument and no reliance on spectral deconvolution.

Miller, C. A.↗

CompF2: Theoretical Calculations and Simulation Topical Group Report

This report summarizes the work of the Computational Frontier topical group on theoretical calculations and simulation for Snowmass 2021. We discuss the challenges, potential solutions, and needs facing six diverse but related topical areas that span the subject of theoretical calculations and simulation in high energy physics (HEP): cosmic calculations, particle accelerator modeling, detector simulation, event generators, perturbative calculations, and lattice QCD (quantum chromodynamics). The challenges arise from the next generations of HEP experiments, which will include more complex instruments, provide larger data volumes, and perform more precise measurements. Calculations and simulations will need to keep up with these increased requirements. The other aspect of the challenge is the evolution of computing landscape away from general-purpose computing on CPUs and toward special-purpose accelerators and coprocessors such as GPUs and FPGAs. These newer devices can provide substantial improvements for certain categories of algorithms, at the expense of more specialized programming and memory and data access patterns.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Optimizing observables with machine learning for better unfolding

Most measurements in particle and nuclear physics use matrix-based unfolding algorithms to correct for detector effects. In nearly all cases, the observable is defined analogously at the particle and detector level. We point out that while the particle-level observable needs to be physically motivated to link with theory, the detector-level need not be and can be optimized. We show that using deep learning to define detector-level observables has the capability to improve the measurement when combined with standard unfolding methods.

47 OTHER INSTRUMENTATION↗

Ariel 6 measurements of ultra-heavy cosmic ray fluxes in the region 34 or = Z or = 48

The Ariel VI satellite was launched by NASA on a Scout rocket on 3rd June 1979 from Wallops Island, Virginia, USA, into a near circular 625 km orbit inclined at 55 deg. It carried a spherical cosmic ray detector designed by a group from Bristol University. A spherical aluminum vessel of diameter 75 cm contains a gas scintillation mixture and a thin spherical shell of Pilot 425 plastic, and forms a single optical cavity viewed by 16 photomultipliers. Particle tracks through the detector may be characterized by their impact parameter p and by whether or not they pass through the cup of plastic scintillator placed between the sphere and the spacecraft body (referred to below as the Anti-Coincidence Detector or ACD). Individual particle charges are determined by separately measuring the gas scintillation and the Cerenkov emission from the plastic shell. This is possible because of the quite different distribution in time of these emissions.

Fowler, P. H.↗

Single particle detection system for strong-field QED experiments

Abstract Measuring signatures of strong-field quantum electrodynamics (SF-QED) processes in an intense laser field is an experimental challenge: it requires detectors to be highly sensitive to single electrons and positrons in the presence of the typically very strong x-ray and γ -photon background levels. In this paper, we describe a particle detector capable of diagnosing single leptons from SF-QED interactions and discuss the background level simulations for the upcoming Experiment-320 at FACET-II (SLAC National Accelerator Laboratory). The single particle detection system described here combines pixelated scintillation LYSO screens and a Cherenkov calorimeter. We detail the performance of the system using simulations and a calibration of the Cherenkov detector at the ELBE accelerator. Single 3 GeV leptons are expected to produce approximately 537 detectable photons in a single calorimeter channel. This signal is compared to Monte-Carlo simulations of the experiment. A signal-to-noise ratio of 18 in a single Cherenkov calorimeter detector is expected and a spectral resolution of 2% is achieved using the pixelated LYSO screens.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Picosecond Timing Resolution Measurements of Low Gain Avalanche Detectors with a 120 GeV Proton Beam for the TOPSiDE Detector Concept

This paper presents results that take a critical step toward proving 10 ps timing resolution’s feasibility for particle identification in the TOPSiDE detector concept for the Electron-Ion Collider. Measurements of LGADs with a thickness of 35 μm and 50 μm are evaluated with a 120 GeV proton beam. The performance of the gain and timing response is assessed, including the dependence on the reverse bias voltage and operating temperature. The best timing resolution of UFSDs in a test beam to date is achieved using three combined planes of 35 μm thick LGADs at -30°C with a precision of 14.3 ± 1.5 ps.

Particle tracking detectors↗

Deep learning-based spatiotemporal multi-event reconstruction for delay line detectors

Abstract Accurate observation of two or more particles within a very narrow time window has always been a challenge in modern physics. It creates the possibility of correlation experiments, such as the ground-breaking Hanbury Brown–Twiss experiment, leading to new physical insights. For low-energy electrons, one possibility is to use a Microchannel plate with subsequent delay lines for the readout of the incident particle hits, a setup called a Delay Line Detector. The spatial and temporal coordinates of more than one particle can be fully reconstructed outside a region called the dead radius. For interesting events, where two electrons are close in space and time, the determination of the individual positions of the electrons requires elaborate peak finding algorithms. While classical methods work well with single particle hits, they fail to identify and reconstruct events caused by multiple nearby particles. To address this challenge, we present a new spatiotemporal machine learning model to identify and reconstruct the position and time of such multi-hit particle signals. This model achieves a much better resolution for nearby particle hits compared to the classical approach, removing some of the artifacts and reducing the dead radius a factor of eight. We show that machine learning models can be effective in improving the spatiotemporal performance of delay line detectors.

Computer Science↗

Design of the ECCE detector for the Electron Ion Collider

The EIC Comprehensive Chromodynamics Experiment (ECCE) detector has been designed to address the full scope of the proposed Electron Ion Collider (EIC) physics program as presented by the National Academy of Science and provide a deeper understanding of the quark-gluon structure of matter. To accomplish this, the ECCE detector offers nearly acceptance and energy coverage along with excellent tracking and particle identification. The ECCE detector was designed to be built within the budget envelope set out by the EIC project while simultaneously managing cost and schedule risks. Finally, this detector concept has been selected to be the basis for the EIC project detector.

47 OTHER INSTRUMENTATION↗

Machine learning-based jet and event classification at the Electron-Ion Collider with applications to hadron structure and spin physics

We explore machine learning-based jet and event identification at the future Electron-Ion Collider (EIC). We study the effectiveness of machine learning-based classifiers at relatively low EIC energies, focusing on (i) identifying the flavor of the jet and (ii) identifying the underlying hard process of the event. We propose applications of our machine learning-based jet identification in the key research areas at the future EIC and current Relativistic Heavy Ion Collider program, including enhancing constraints on (transverse momentum dependent) parton distribution functions, improving experimental access to transverse spin asymmetries, studying photon structure, and quantifying the modification of hadrons and jets in the cold nuclear matter environment in electron-nucleus collisions. We establish first benchmarks and contrast the estimated performance of flavor tagging at the EIC with that at the Large Hadron Collider. We perform studies relevant to aspects of detector design including particle identification, charge information, and minimum transverse momentum capabilities. Additionally, we study the impact of using full event information instead of using only information associated with the identified jet. These methods can be deployed either on suitably accurate Monte Carlo event generators, or, for several applications, directly on experimental data. We provide an outlook for ultimately connecting these machine learning-based methods with first principles calculations in quantum chromodynamics.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Dark scalars and heavy neutral leptons at DarkQuest

The proposed DarkQuest beam dump experiment, a modest upgrade to the existing SeaQuest/SpinQuest experiment, has great potential for uncovering new physics within a dark sector. We explore both the near-term and long-term prospects for observing two distinct, highly-motivated hidden sector benchmark models: heavy neutral leptons and Higgs-mixed scalars. We comprehensively examine the particle production and detector acceptance at DarkQuest, including an updated treatment of meson production, and light scalar production through both bremsstrahlung and gluon-gluon fusion. In both benchmark models, DarkQuest will provide an opportunity to probe previously inaccessible interesting regions of parameter space on a fairly short timescale when compared to other proposed experiments.

79 ASTRONOMY AND ASTROPHYSICS↗

First measurements of energetic protons in Mega Amp Spherical Tokamak Upgrade (MAST-U)

First proton production rates from the d(d,p)t reaction in the Mega Amp Spherical Tokamak Upgrade (MAST-U) are measured. The data were taken during the MAST-U experimental campaign with an upgraded version of the proton detector (PD) previously used in MAST. The new detector array consists of three collimated silicon surface barrier detectors with a depletion depth of 300 μm and a collimated 120 μm thick diamond detector, mounted on the MAST-U reciprocating probe arm. This array measures the energies of unconfined energetic 3 MeV protons and 1 MeV tritons mainly produced by beam-thermal DD reactions during neutral beam injection heating. Diamond detectors have the potential to be uniquely suited to detect charged fusion products as they promise to be much more radiation resistant and much less sensitive to temperature variations compared to silicon-based detectors. Using silicon and diamond-based detectors simultaneously allowed us to directly compare the performance of these two detector types. PD particle rates measured during different plasma scenarios are presented and compared to neutron rates measured using the neutron camera upgrade and TRANSP predictions.

Instruments & Instrumentation↗

High performance FPGA embedded system for machine learning based tracking and trigger in sPhenix and EIC

We present a comprehensive end-to-end pipeline to classify triggers versus background events in this paper. This pipeline makes online decisions to select signal data and enables the intelligent trigger system for efficient data collection in the Data Acquisition System (DAQ) of the upcoming sPHENIX and future EIC (Electron-Ion Collider) experiments. Starting from the coordinates of pixel hits that are lightened by passing particles in the detector, the pipeline applies three-stage of event processing (hits clustering, track reconstruction, and trigger detection) and labels all processed events with the binary tag of trigger versus background events. The pipeline consists of deterministic algorithms such as clustering pixels to reduce event size, tracking reconstruction to predict candidate edges, and advanced graph neural network-based models for recognizing the entire jet pattern. In particular, we apply the message-passing graph neural network to predict links between hits and reconstruct tracks and a hierarchical pooling algorithm (DiffPool) to make the graph-level trigger detection. We obtain an impressive performance (≥70% accuracy) for trigger detection with only 3200 neuron weights in the end-to-end pipeline. We deploy the end-to-end pipeline into a field-programmable gate array (FPGA) and accelerate the three stages with speedup factors of 1152, 280, and 21, respectively.

Instruments & Instrumentation↗

New measurement of double- β decays of Mo 100 to excited states of Ru 100 with the CUPID-Mo experiment

The CUPID-Mo experiment, located at Laboratoire Souterrain de Modane (France), was a demonstrator experiment for CUPID. It consisted of an array of 20 Li 2 100 MoO 4 (LMO) calorimeters each equipped with a Ge light detector (LD) for particle identification. In this work, we present the result of a search for two-neutrino and neutrinoless double beta decays of 100 Mo to the first 0 + and 2 + excited states of 100 Ru using the full CUPID-Mo exposure (2.71 kg yr of LMO). We measure the half-life of 2νββ decay to the $0^+_1$ state as $T^{2ν→0^+_1}_{1/2}$ = (7.5 ± 0.8 (stat.) $^{+0.4}_{-0.3}$ (syst.)) × 10 20 yr. The bolometric technique enables measurement of the electron energies as well as the gamma rays from nuclear de-excitation and this allows us to set new limits on the two-neutrino decay to the $2^+_1$ state of $T^{2ν→2^+_1}_{1/2}$ > 4.4×10 21 yr (90% c.i.) and on the neutrinoless modes of $T^{0ν→2^+_1}_{1/2}$ > 2.1×10 23 yr (90% c.i.), $T^{0ν→0^+_1}_{1/2}$ > 1.2 × 10 23 yr (90% c.i.). Information on the electrons spectral shape is obtained which allows us to make the first comparison of the single state (SSD) and higher state (HSD) 2νββ decay models for the $0^+_1$ excited state of 100 Ru.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Measurement of the energy asymmetry in $t\bar{t} j$ production at 13 TeV with the ATLAS experiment and interpretation in the SMEFT framework

A measurement of the energy asymmetry in jet-associated top-quark pair production is presented using 139fb -1 of data collected by the ATLAS detector at the Large Hadron Collider during pp collisions at $\sqrt{s}$ =13TeV. The observable measures the different probability of top and antitop quarks to have the higher energy as a function of the jet scattering angle with respect to the beam axis. The energy asymmetry is measured in the semileptonic $t\bar{t}$ decay channel, and the hadronically decaying top quark must have transverse momentum above 350GeV. The results are corrected for detector effects to particle level in three bins of the scattering angle of the associated jet. The measurement agrees with the SM prediction at next-to-leading-order accuracy in quantum chromodynamics in all three bins. In the bin with the largest expected asymmetry, where the jet is emitted perpendicular to the beam, the energy asymmetry is measured to be -0.043 ± 0.020, in agreement with the SM prediction of -0.037 ± 0.003. Interpreting this result in the framework of the Standard Model effective field theory (SMEFT), it is shown that the energy asymmetry is sensitive to the top-quark chirality in four-quark operators and is therefore a valuable new observable in global SMEFT fits.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

End-to-End Pipeline for Trigger Detection on Hit and Track Graphs

There has been a surge of interest in applying deep learning in particle and nuclear physics to replace labor-intensive offline data analysis with automated online machine learning tasks. This paper details a novel AI-enabled triggering solution for physics experiments in Relativistic Heavy Ion Collider and future Electron-Ion Collider. The triggering system consists of a comprehensive end-to-end pipeline based on Graph Neural Networks that classifies trigger events versus background events, makes online decisions to retain signal data, and enables efficient data acquisition. Here, the triggering system first starts with the coordinates of pixel hits lit up by passing particles in the detector, applies three stages of event processing (hits clustering, track reconstruction, and trigger detection), and labels all processed events with the binary tag of trigger versus background events. By switching among different objective functions, we train the Graph Neural Networks in the pipeline to solve multiple tasks: the edge-level track reconstruction problem, the edge-level track adjacency matrix prediction, and the graph-level trigger detection problem. We propose a novel method to treat the events as track-graphs instead of hit-graphs. This method focuses on intertrack relations and is driven by underlying physics processing. As a result, it attains a solid performance (around 72% accuracy) for trigger detection and outperforms the baseline method using hit-graphs by 2% higher accuracy.

97 MATHEMATICS AND COMPUTING↗

High Intensity Gamma Ray Source Scintillation Attenuation Spectrometer and Filter Stack Monoenergetic Calibration

The Laser-Based X-ray Radiographic Imaging team at Los Alamos National Lab is looking for a monoenergetic MeV X-ray source to both verify our Monte Carlo N-particle simulations of detector performance and calibrate the instruments for future measurements. Funded by the Laboratory Directed Research and Development (LDRD) program, our overall goal is to improve the radiographic quality and reliability of laser-based X-ray sources for deployment at both dynamic and static radiography facilities. Laser-based X-ray sources have demonstrated smaller spot sizes to current electron accelerator based sources. The smaller laser spot size leads to significantly improved resolution.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗