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At least 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Tau-Jet Matching and Tag-and-Probe Tau Tagging Efficiencies for HH→bbτ+τ− Searches Using Run 3 CMS Scouting Data

We are studying tau-jet matching efficiency and tau tagging efficiency for the search for Higgs boson pair production in the HH→bbτ+τ− decay channel using Run 3 CMS scouting data. Collision events in the CMS detector produce many particle candidates, so jets are clustered using the anti-kT algorithm to identify possible tau signatures. In Monte Carlo simulation, tau-jet matching efficiency can be measured by comparing generated taus to reconstructed jets. In actual collision data, however, generated taus are not available, so we use a tag-and-probe method with Z→τ+τ− candidate events. In this method, one tau candidate is used as the tag and the other as the probe. The invariant mass of the tau-pair candidates is plotted and fitted with signal and background functions to estimate the number of real tau events and determine the tagging efficiency. By comparing efficiencies in data and Monte Carlo simulation, this work helps evaluate the performance of scouting-based tau reconstruction and tau tagging for future HH→bbτ+τ− searches.

Bellot, Annella [North Central Coll.; Fermilab]↗
DOE OSTI2022

The role of ProtoDUNE-SP in future oscillation physics

Long-baseline oscillation experiments are entering a new phase where neutrino beams can provide ultra-high fuxes over long distances. These beams will lead to an era of high statistics in large neutrino detectors, creating new systematic uncertainty-limited analyses. The Deep Underground Neutrino Experiment (DUNE) plans a high fux beam to travel 1300 km to 10-kT liquid argon detector modules. While neither the near detector nor the far detector has been constructed, prototypes of the DUNE Far Detector have been built and operated at CERN. One prototype, ProtoDUNE Single-Phase, is a full-scale mockup of the first 10-kT DUNE Far Detector module and can inform DUNE on detector performance and particle passage in argon. The proceedings discuss some published and in-progress results from ProtoDUNE-SP and how these results can impact current sensitivity studies and future analyses.

Diurba, Richard↗
DOE OSTI2024

hls4ml

hls4ml (high level synthesis for machine learning) Is a Python package used to translate commonly used open-source machine learning models into HLS. This is useful in machine learning applications on FPGAs. Machine learning algorithms are only as fast as the hardware that they are used on, and some applications require high speed without sacrificing accuracy. In these situations, an FPGA is a good choice since it is faster than a CPU or a GPU, but programming an FPGA is difficult. This is where hls4ml can be used to simplify the process, as a well-known learning model can be converted to HLS and more easily deployed onto an FPGA. There are many use cases for a machine learning algorithm running on an FPGA. For example, detectors in a particle accelerator cannot keep every event that they detect, and so a computer must decide which events to keep and which to discard. Using an FPGA with a machine learning algorithm would be a good way to keep as many events as possible.

Swanson, Caiden↗
DOE OSTI2023

Search for heavy long-lived multi-charged particles in the full LHC Run 2 pp collision data at s = 13 TeV using the ATLAS detector

A search for heavy long-lived multi-charged particles is performed using the ATLAS detector at the LHC. Data collected in 2015-2018 at $\sqrt{s}$ = 13 TeV from pp collisions corresponding to an integrated luminosity of 139 fb -1 are examined. Particles producing anomalously high ionization, consistent with long-lived spin-$\frac{1}{2}$ massive particles with electric charges from |q|=2e to |q|=7e are searched for. No statistically significant evidence of such particles is observed, and 95% confidence level cross-section upper limits are calculated and interpreted as the lower mass limits for a Drell-Yan plus photon-fusion production mode. The least stringent limit, 1060 GeV, is obtained for |q|=2e particles, and the most stringent one, 1600 GeV, is for |q|=6e particles.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Reconstruction of Six-Dimensional Phase Space

A phase space is a mathematical representation of all possible physical states of a system. Particle beams at Fermilab exist within a six-dimensional (6D) phase space defined by three positional components, (x, y, z) and three momentum components, (px, py, pz). To reconstruct this space implies taking measurement data from detectors and mapping out particle behavior using computational methods. The beam detectors, however, are only able to detect spatial distribution among the events of the beam, therefore being limited to positional data. Also, due to the vast number of events in a particle beam, it is extremely difficult to analyze and differentiate every single one’s behavior. However, with Machine Learning (ML), which can distinguish between patterns and map out particle behavior more efficiently. We first used the particle beam software, G4beamline, to simulate a 10,000-event muon beam, adjusting parameters such as initial momentum magnitude (p¬0) and virtual detector position. Using ten virtual detectors, we analyzed p0 values such that minimum 9,990 events were analyzed by every detector. We then input the data from these beam simulations to a C++ program, that randomly selects 100 events, and creates a 2D histogram based on spatial distribution, detector position, and event intensity. This process is repeated 100 times to create 100 histograms per p0 value. These images were then input to a modified ResNet18 Convolutional Neural Network (CNN) for training, and to predict p0 from some unseen set of histograms. The model was accurate when trained on momentum increments of 5 MeV/c and provided with denser training samples around highly variable test values. These results displayed machine learning being able to accurately predict p0 from being trained on different particle behaviors.

Shirlee, Jermain [Fermilab]↗
DOE OSTI2020

Performance of position-sensitive resistive silicon detectors in the Forward Array Using Silicon Technology (FAUST)

The silicon telescopes of the Forward Array Using Silicon Technology (FAUST) have been recently upgraded with silicon detectors which use resistive charge-splitting to measure the position of charged particles. This is in addition to the measurement of the total energy that these charged particles deposit in the detector. The upgrade results in increased angular resolution with a much smaller number of signals than silicon strip detectors with similar resolution. Here, a novel method of calibration has been used to demonstrate the efficacy of these position-sensitive detectors, and the detectors have been used in a commissioning experiment.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Mu2e: Modeling Drift of Ionized Particles with ML

The Mu2e experiment searches for charged lepton flavor violation through muon-to-electron conversion in the field of a nucleus. The signal is a monoenergetic electron with an energy of 104.97 MeV. Its momentum is reconstructed using information from drifting ionized particles in a straw tracker detector. This project analyzes the drift of ionized particles with a deep neural network to help improve the momentum reconstruction process. The model yields a 20% improvement in resolution from a reference linear model.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Mu2e: Modeling Drift of Ionized Particles with ML

The Mu2e experiment searches for charged lepton flavor violation through muon-to-electron conversion in the field of a nucleus. The signal is a monoenergetic electron with an energy of 104.97 MeV. Its momentum is reconstructed using information from drifting ionized particles in a straw tracker detector. This project analyzes the drift of ionized particles with a deep neural network to help improve the momentum reconstruction process. The model yields a 20% improvement in resolution from a reference linear model.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Search for Higgs boson decays into a pair of pseudoscalar particles in the $bbμμ$ final state with the ATLAS detector in pp collisions at $\sqrt{s} =$ 13 TeV

This paper presents a search for decays of the Higgs boson with a mass of 125 GeV into a pair of new pseudoscalar particles, $H→aa$, where one a-boson decays into a b-quark pair and the other into a muon pair. The search uses 139 fb -1 of proton-proton collision data at a center-of-mass energy of $\sqrt{s} =$ 13 TeV recorded between 2015 and 2018 by the ATLAS experiment at the LHC. A narrow dimuon resonance is searched for in the invariant mass spectrum between 16 GeV and 62 GeV. The largest excess of events above the Standard Model backgrounds is observed at a dimuon invariant mass of 52 GeV and corresponds to a local (global) significance of 3.3σ (1.7σ). Upper limits at 95% confidence level are placed on the branching ratio of the Higgs boson to the $bbμμ$ final state, $B(H→aa→bbμμ)$, and are in the range 0.2-4.0×10 -4 , depending on the signal mass hypothesis.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Critical problems of energy frontier Muon Colliders: optics, magnets and radiation

This White Paper brings together our previous studies on a Muon Collider (MC) and presents a design concept of the 6 TeV MC optics, the superconducting (SC) magnets, and a preliminary analysis of the protection system to reduce magnet radiation loads as well as particle backgrounds in the detector. The SC magnets and detector protection considerations impose strict limitations on the lattice choice, hence the design of the collider optics, magnets and Machine Detector Interface (MDI) are closely intertwined. As a first approximation we use the Interaction Region (IR) design with beta-star=3 mm, whereas for the arcs we re-scale the arc cell design of the 3 TeV MC. Traditional cos-theta coil geometry and Nb3Sn superconductor were used to provide field maps for the analysis and optimization of the arc lattice and IR design, as well as for studies of beam dynamics and magnet protection against radiation. The stress management in the coil will be needed to avoid large degradation or even damage of the brittle SC coils. In the assumed IR designs, the dipoles close to the Interaction Point (IP) and tungsten masks in each IR (to protect magnets) help reducing background particle fluxes in the detector by a substantial factor. The tungsten nozzles in the 6 to 600 cm region from the IP, assisted by the detector solenoid field, trap most of the decay electrons created close to the IP as well as most of the incoherent electron-positron pairs generated in the IP. With sophisticated tungsten, iron, concrete and borated polyethylene shielding in the MDI region, the total reduction of background loads by more than three orders of magnitude can be achieved.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

Measurement of the central exclusive production of charged particle pairs in proton-proton collisions at $\sqrt{s}$ = 200 GeV with the STAR detector at RHIC

We report on the measurement of the Central Exclusive Production of charged particle pairs h+h- (h = π, K, p) with the STAR detector at RHIC in proton-proton collisions at $\sqrt{s}$ = 200 GeV. The charged particle pairs produced in the reaction pp → p' + h + h - + p' are reconstructed from the tracks in the central detector and identified using the specific energy loss and the time of flight method, while the forward-scattered protons are measured in the Roman Pot system. Exclusivity of the event is guaranteed by requiring the transverse momentum balance of all four final-state particles. Differential cross sections are measured as functions of observables related to the central hadronic final state and to the forward-scattered protons. They are measured in a fiducial region corresponding to the acceptance of the STAR detector and determined by the central particles’ transverse momenta and pseudorapidities as well as by the forward-scattered protons’ momenta. This fiducial region roughly corresponds to the square of the four-momentum transfers at the proton vertices in the range 0.04 GeV 2 < -t 1 , -t 2 < 0.2 GeV 2 , invariant masses of the charged particle pairs up to a few GeV and pseudorapidities of the centrally-produced hadrons in the range |η| < 0.7. The measured cross sections are compared to phenomenological predictions based on the Double Pomeron Exchange (DPE) model. Structures observed in the mass spectra of π + π - and K + K - pairs are consistent with the DPE model, while angular distributions of pions suggest a dominant spin-0 contribution to π + π - production. For π + π - production, the fiducial cross section is extrapolated to the Lorentz-invariant region, which allows decomposition of the invariant mass spectrum into continuum and resonant contributions. The extrapolated cross section is well described by the continuum production and at least three resonances, the f 0 (980), f 2 (1270) and f 0 (1500), with a possible small contribution from the f 0 (1370). Fits to the extrapolated differential cross section as a function of t 1 and t 2 enable extraction of the exponential slope parameters in several bins of the invariant mass of π + π - pairs. These parameters are sensitive to the size of the interaction region.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Designing observables for measurements with deep learning

Many analyses in particle and nuclear physics use simulations to infer fundamental, effective, or phenomenological parameters of the underlying physics models. When the inference is performed with unfolded cross sections, the observables are designed using physics intuition and heuristics. We propose to design targeted observables with machine learning. Unfolded, differential cross sections in a neural network output contain the most information about parameters of interest and can be well-measured by construction. The networks are trained using a custom loss function that rewards outputs that are sensitive to the parameter(s) of interest while simultaneously penalizing outputs that are different between particle-level and detector-level (to minimize detector distortions). We demonstrate this idea in simulation using two physics models for inclusive measurements in deep inelastic scattering. We find that the new approach is more sensitive than classical observables at distinguishing the two models and also has a reduced unfolding uncertainty due to the reduced detector distortions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Heavy Flavor Physics at the EIC with the ECCE detector

The proposed Electron-Ion Collider (EIC) will operate high-energy high-luminosity electron+proton and electron+nucleus collisions to solve several unresolved fundamental questions. Due to their large masses (mc,b > ΛQCD), heavy quarks and their hadron products are ideal probes to study the nucleon/nuclear parton distribution functions in the high Bjorken-x (xBJ > 0.1) region and explore the hadronization process within the unconstrained kinematic region. Recently, the Electron-Ion Collider Comprehensive Chromodynamics Experiment (ECCE) consortium detector conceptual design has been selected as the reference design for the EIC project detector. The precise momentum and spatial resolutions provided by the ECCE tracking detector enable a series of open heavy flavor and quarkonia measurements. The physics projections of these proposed heavy flavor measurements in simulation studies using the ECCE detector design will be presented.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

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↗