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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS1979

On the clustering of multidimensional pictorial data

Obvious approaches to reducing the cost (in computer resources) of applying current clustering techniques to the problem of remote sensing are discussed. The use of spatial information in finding fields and in classifying mixture pixels is examined, and the AMOEBA clustering program is described. Internally, a pattern recognition program, from without, AMOEBA appears to be an unsupervised clustering program. It is fast and automatic. No choices (such as arbitrary thresholds to set split/combine sequences) need be made. The problem of finding the number of clusters is solved automatically. At the conclusion of the program, all points in the scene are classified; however, a provision is included for a reject classification of some points which, within the theoretical framework, cannot rationally be assigned to any cluster.

Bryant, J. D.↗
NASA NTRS1993

A possibilistic approach to clustering

Fuzzy clustering has been shown to be advantageous over crisp (or traditional) clustering methods in that total commitment of a vector to a given class is not required at each image pattern recognition iteration. Recently fuzzy clustering methods have shown spectacular ability to detect not only hypervolume clusters, but also clusters which are actually 'thin shells', i.e., curves and surfaces. Most analytic fuzzy clustering approaches are derived from the 'Fuzzy C-Means' (FCM) algorithm. The FCM uses the probabilistic constraint that the memberships of a data point across classes sum to one. This constraint was used to generate the membership update equations for an iterative algorithm. Recently, we cast the clustering problem into the framework of possibility theory using an approach in which the resulting partition of the data can be interpreted as a possibilistic partition, and the membership values may be interpreted as degrees of possibility of the points belonging to the classes. We show the ability of this approach to detect linear and quartic curves in the presence of considerable noise.

Krishnapuram, Raghu↗
DOE OSTI2022

Cosmic ray muon clustering for the MicroBooNE liquid argon time projection chamber using sMask-RCNN

In this article, we describe a modified implementation of Mask Region-based Convolutional Neural Networks (Mask-RCNN) for cosmic ray muon clustering in a liquid argon TPC and applied to MicroBooNE neutrino data. Our implementation of this network, called sMask-RCNN, uses sparse submanifold convolutions to increase processing speed on sparse datasets, and is compared to the original dense version in several metrics. The networks are trained to use wire readout images from the MicroBooNE liquid argon time projection chamber as input and produce individually labeled particle interactions within the image. These outputs are identified as either cosmic ray muon or electron neutrino interactions. We find that sMask-RCNN has an average pixel clustering efficiency of 85.9% compared to the dense network's average pixel clustering efficiency of 89.1%. We demonstrate the ability of sMask-RCNN used in conjunction with MicroBooNE's state-of-the-art Wire-Cell cosmic tagger to veto events containing only cosmic ray muons. The addition of sMask-RCNN to the Wire-Cell cosmic tagger removes 70% of the remaining cosmic ray muon background events at the same electron neutrino event signal efficiency. Furthermore, this event veto can provide 99.7% rejection of cosmic ray-only background events while maintaining an electron neutrino event-level signal efficiency of 80.1%. In addition to cosmic ray muon identification, sMask-RCNN could be used to extract features and identify different particle interaction types in other 3D-tracking detectors.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Stable Rate of Slip Along the Karakax Section of the Altyn Tagh Fault from Observation of Interglacial and Postglacial Offset Morphology and Surface Dating

Digital elevation maps obtained using TanDEM-X and Pleiades data combined with newly obtained surface age estimates using cosmogenic radionuclide (CRN) and optically simulated luminescence (OSL) methods are used to quantify the slip rate along the western section of the Altyn Tagh Fault in southern Xinjiang. The reconstruction of the conical shape of massive alluvial fans inferred to be from the Eemian (115±7 ka) from CRN dating shows consistent left-lateral offsets of 300±20 m, yielding a slip rate of 2.6±0.3 mm/year. Successive episodes of incision have left cut terraces inset in wide canyons, 10–25 m below the fans' surface. The incision was followed by the deposition of a broad terrace of early Holocene age, which is reincised by modern stream channels. Near the village of Shanxili, a 200 m wide valley is partially dammed by a shutter ridge displaced by the fault. A fill terrace deposited upstream from the ridge has an OSL age of 8.8±0.6 ka. The 23±2 m offset of the riser incising the terrace indicates a minimum postdepositional movement on the fault, yielding a Holocene rate of 2.6±0.5 mm/year, consistent with the 115-ka average slip rate. Furthermore, scarp degradation analysis using mass diffusion reveals a nonlinear relationship between fault displacement and degradation coefficient along the progressively exposed fault scarp, a pattern suggesting either seismic clustering or variable diffusion rate since the Eemian. Together with the Gozha Co-Longmu Co fault to the south, the Karakax section of the Altyn Tagh Fault contributes to the eastward movement of the western corner of Tibet.

58 GEOSCIENCES↗
DOE OSTI2020

Imaging plasma formation in isolated nanoparticles with ultrafast resonant scattering

We have recorded the diffraction patterns from individual xenon clusters irradiated with intense extreme ultraviolet pulses to investigate the influence of light-induced electronic changes on the scattering response. The clusters were irradiated with short wavelength pulses in the wavelength regime of different 4d inner-shell resonances of neutral and ionic xenon, resulting in distinctly different optical properties from areas in the clusters with lower or higher charge states. The data show the emergence of a transient structure with a spatial extension of tens of nanometers within the otherwise homogeneous sample. Simulations indicate that ionization and nanoplasma formation result in a light-induced outer shell in the cluster with a strongly altered refractive index. The presented resonant scattering approach enables imaging of ultrafast electron dynamics on their natural timescale.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Parametrizing the detector response with neural networks

In high energy physics, characterizing the response of a detector to radiation is one of the most important and fundamental experimental tasks. In many cases, this task is accomplished by parameterizing summary statistics of the full detector response probability density. The parameterized detector response can then be used for calibration as well as for directly improving physics analysis sensitivity. This paper reports on how to parameterize summary statistics of the detector response using neural networks. Specifically, neural networks are powerful tools for incorporating multidimensional data and the loss function used during training determines which summary statistic is learned. One common summary statistic that has not been combined with deep learning (as far as the authors are aware) is the mode. A neural network-based approach to mode learning is proposed and empirically demonstrated in the context of high energy jet calibrations. Altogether, the neural network-based toolkit for detector response parameterization can enhance the utility of data collected at high energy physics experiments and beyond.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

FPGA-based tracking for the CMS Level-1 trigger using the tracklet algorithm

The high instantaneous luminosities expected following the upgrade of the Large Hadron Collider (LHC) to the High-Luminosity LHC (HL-LHC) pose major experimental challenges for the CMS experiment. A central component to allow efficient operation under these conditions is the reconstruction of charged particle trajectories and their inclusion in the hardware based trigger system. There are many challenges involved in achieving this: a large input data rate of about 20–40 Tb/s; processing a new batch of input data every 25 ns, each consisting of about 15,000 precise position measurements and rough transverse momentum measurements of particles (“stubs”); performing the pattern recognition on these stubs to find the trajectories; and producing the list of trajectory parameters within 4 µs. Here, this paper describes a proposed solution to this problem, specifically, it presents a novel approach to pattern recognition and charged particle trajectory reconstruction using an all-FPGA solution. The results of an end-to-end demonstrator system, based on Xilinx Virtex-7 FPGAs, that meets timing and performance requirements are presented along with a further improved, optimized version of the algorithm together with its corresponding expected performance.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Design, upgrade and characterization of the silicon photomultiplier front-end for the AMIGA detector at the Pierre Auger Observatory

AMIGA (Auger Muons and Infill for the Ground Array) is an upgrade of the Pierre Auger Observatory to complement the study of ultra-high-energy cosmic rays (UHECR) by measuring the muon content of extensive air showers (EAS). It consists of an array of 61 water Cherenkov detectors on a denser spacing in combination with underground scintillation detectors used for muon density measurement. Each detector is composed of three scintillation modules, with 10 m 2 detection area per module, buried at 2.3 m depth, resulting in a total detection area of 30 m 2 . Silicon photomultiplier sensors (SiPM) measure the amount of scintillation light generated by charged particles traversing the modules. In this paper, the design of the front-end electronics to process the signals of those SiPMs and test results from the laboratory and from the Pierre Auger Observatory are described. Compared to our previous prototype, the new electronics shows a higher performance, higher efficiency and lower power consumption, and it has a new acquisition system with increased dynamic range that allows measurements closer to the shower core. The new acquisition system is based on the measurement of the total charge signal that the muonic component of the cosmic ray shower generates in the detector.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

A new calibration method for charm jet identification validated with proton-proton collision events at $\sqrt{s}$ =13 TeV

Many measurements at the LHC require efficient identification of heavy-flavour jets, i.e. jets originating from bottom (b) or charm (c) quarks. An overview of the algorithms used to identify c jets is described and a novel method to calibrate them is presented. This new method adjusts the entire distributions of the outputs obtained when the algorithms are applied to jets of different flavours. It is based on an iterative approach exploiting three distinct control regions that are enriched with either b jets, c jets, or light-flavour and gluon jets. Results are presented in the form of correction factors evaluated using proton-proton collision data with an integrated luminosity of 41.5 fb$^{-1}$ at √s = 13 TeV, collected by the CMS experiment in 2017. The closure of the method is tested by applying the measured correction factors on simulated data sets and checking the agreement between the adjusted simulation and collision data. Furthermore, a validation is performed by testing the method on pseudodata, which emulate various mismodelling conditions. The calibrated results enable the use of the full distributions of heavy-flavour identification algorithm outputs, e.g. as inputs to machine-learning models. Thus, they are expected to increase the sensitivity of future physics analyses.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Centrality determination in heavy-ion collisions with the LHCb detector

The centrality of heavy-ion collisions is directly related to the created medium in these interactions. A procedure to determine the centrality of collisions with the LHCb detector is implemented for lead-lead collisions at √ s NN = 5 TeV and lead-neon fixed-target collisions at √ s NN = 69 GeV. The energy deposits in the electromagnetic calorimeter are used to determine and define the centrality classes. The correspondence between the number of participants and the centrality for the lead-lead collisions is in good agreement with the correspondence found in other experiments, and the centrality measurements for the lead-neon collisions presented here are performed for the first time in fixed-target collisions at the LHC.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Machine learning on FPGA for event selection

Real-time data processing is a frontier field in experimental particle physics. The application of FPGAs at the trigger level is used by many current and planned experiments (CMS, LHCb, Belle2, PANDA). Usually they use conventional processing algorithms. LHCb has implemented Machine Learning (ML) elements for real-time data processing with a triggered readout system that runs most of the ML algorithms on a computer farm. The work described in this article aims to test the ML-FPGA algorithms for streaming data acquisition. Herein, there are many experiments working in this area and they have a lot in common, but there are many specific solutions for detector and accelerator parameters that are worth exploring further. This report describes the purpose of the work and progress in evaluating the ML-FPGA application.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Muon track reconstruction in a segmented bolometric array using multi-objective optimization

Recent advances in segmented solid-state detector arrays for rare-event searches have allowed the technology to approach the ton-scale in detector mass and the scale of meters in size. Often focused around searches for neutrinoless double-beta decay or direct dark matter detection, such experiments also have the capability to search for exotic particles that leave track-like signatures across their volume. However, the segmented nature of such detector arrays often sets the spatial resolution and makes the problem of reconstructing track-like paths non-trivial. Here, in this paper, we present an algorithm that improves reconstruction of track-like events in segmented detectors using multi-objective optimization — a computational technique that optimizes more than one cost function at a time without specifying a quantitative weighting between them. Such a technique allows the reconstruction of tracks through a detector and the determination of path-lengths through individual elements. When combined with the reconstructed energy depositions in each element this allows for a calculation of the stopping power of track-like particles and opens the door to searches for particles with abnormal stopping power like monopoles or lightly-ionizing particles (LIPs). Results are presented which evaluate the precision of the reconstruction tools as they currently stand against Monte Carlo generated data. The algorithm is presented in the context of the CUORE experiment, but has applications to other segmented calorimeter detectors.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Electron and photon energy calibration with the ATLAS detector using LHC Run 2 data

This paper presents the electron and photon energy calibration obtained with the ATLAS detector using 140 fb -1 of LHC proton-proton collision data recorded at $\sqrt{s}$ = 13 TeV between 2015 and 2018. Methods for the measurement of electron and photon energies are outlined, along with the current knowledge of the passive material in front of the ATLAS electromagnetic calorimeter. The energy calibration steps are discussed in detail, with emphasis on the improvements introduced in this paper. The absolute energy scale is set using a large sample of Z-boson decays into electron-positron pairs, and its residual dependence on the electron energy is used for the first time to further constrain systematic uncertainties. The achieved calibration uncertainties are typically 0.05% for electrons from resonant Z-boson decays, 0.4% at E T ~ 10 GeV, and 0.3% at E T ~ 1 TeV; for photons at E T ~ 60 GeV, they are 0.2% on average. This is more than twice as precise as the previous calibration. The new energy calibration is validated using J/ψ → ee and radiative Z-boson decays.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Using graph neural networks to reconstruct charged pion showers in the CMS High Granularity Calorimeter

A novel method to reconstruct the energy of hadronic showersin the CMS High Granularity Calorimeter (HGCAL) is presented. TheHGCAL is a sampling calorimeter with very fine transverse andlongitudinal granularity. The active media are silicon sensors andscintillator tiles readout by SiPMs and the absorbers are acombination of lead and Cu/CuW in the electromagnetic section, andsteel in the hadronic section. The shower reconstruction method isbased on graph neural networks and it makes use of a dynamicreduction network architecture. It is shown that the algorithm isable to capture and mitigate the main effects that normally hinderthe reconstruction of hadronic showers using classicalreconstruction methods, by compensating for fluctuations in themultiplicity, energy, and spatial distributions of the shower'sconstituents. The performance of the algorithm is evaluated usingtest beam data collected in 2018 prototype of the CMS HGCALaccompanied by a section of the CALICE AHCAL prototype. Thecapability of the method to mitigate the impact of energy leakagefrom the calorimeter is also demonstrated.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Expected tracking performance of the ATLAS Inner Tracker at the High-Luminosity LHC

The high-luminosity phase of LHC operations (HL-LHC), will feature a large increase in simultaneous proton-proton interactions per bunch crossing up to 200, compared with a typical leveling target of 64 in Run 3. Such an increase will create a very challenging environment in which to perform charged particle trajectory reconstruction, a task crucial for the success of the ATLAS physics program, and will exceed the capabilities of the current ATLAS Inner Detector (ID). A new all-silicon Inner Tracker (ITk) will replace the current ID in time for the start of the HL-LHC. To ensure successful use of the ITk capabilities in Run 4 and beyond, the ATLAS tracking software has been successfully adapted to achieve state-of-the-art track reconstruction in challenging high-luminosity conditions with the ITk detector. This paper presents the expected tracking performance of the ATLAS ITk based on the latest available developments since the ITk technical design reports.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

Calibration plan for the SBC 10-kg liquid argon detector with 100 eV target threshold

The Scintillating Bubble Chamber (SBC) Collaboration is designing a new generation of low background, noble liquid bubble chamber experiments with sub-keV nuclear recoil threshold. These experiments combine the electronic recoil blindness of a bubble chamber with the energy resolution of noble liquid scintillation, and maintain electron recoil discrimination at higher degrees of superheat (lower nuclear recoil thresholds) than Freon-based bubble chambers. A 10-kg liquid argon bubble chamber has the potential to set world leading limits on the dark matter nucleon cross-section for 𝒪(GeV/c 2 ) masses, and to perform a high statistics coherent elastic neutrino nuclear scattering measurement with reactor neutrinos. This work presents a detailed calibration plan to measure the detector response of these experiments, combining photoneutron scattering with two new techniques to induce sub-keV nuclear recoils: nuclear Thomson scattering and thermal neutron capture.

Dark Matter detectors (WIMPs, axions, etc.)↗
DOE OSTI2021

Dark Energy Camera photometry reveals extra-tidal stars around the Milky Way globular cluster NGC 6864 (M75)

ABSTRACT Globular clusters are prone to lose stars while moving around the Milky Way. These stars escape the clusters and are distributed throughout extended envelopes or tidal tails. However, such extra-tidal structures are not observed in all globular clusters, and yet there are no structural or dynamical parameters that can predict their presence or absence. NGC 6864 is an outer halo globular cluster with reported no observed tidal tails. We used Dark Energy Camera photometry reaching ∼4 mag underneath its main-sequence turnoff to confidently detect an extra-tidal envelope, and stellar debris spread across the cluster outskirts. These features emerged once robust field star filtering techniques were applied to the fainter end of the observed cluster main sequence. NGC 6864 is associated to the Gaia-Enceladus dwarf galaxy, among others 28 globular clusters. Up-to-date, nearly 64${{\ \rm per\,cent}}$ of them have been targeted looking for tidal tails and most of them have been confirmed to exhibit tidal tails. Thus, the present outcomes allow us to speculate on the possibility that Gaia-Enceladus globular clusters share a common pattern of mass loss by tidal disruption.

Piatti, Andrés E. (ORCID:0000000286790589)↗
DOE OSTI2024

Hidden-flavor four-quark states in the charm and bottom region

We discuss the spectrum and the internal composition of ground and excited four-quark states in the charm and bottom energy region. To this end we extend previous calculations within the framework of the relativistic four-body Faddeev-Yakubovsky equation to include quantum numbers with J P C = 0 + + , 0 − + , 1 − − , 1 + − and 1 + + and study their internal composition in terms of heavy-light meson pairs, hadroquarkonia and diquark-antidiquark clusters. We observe similar patterns in the charm and bottom energy region with different compositions of the four-quark states depending on J P C quantum numbers. Most notably, we find that all states with C · P = + 1 are dominated by heavy-light meson contributions, whereas for axial-vector states with J P C = 1 + − including the Z c ( 3900 ) we find a much more complicated picture depending on the flavor content. We systematically compare our results for the spectrum with existing experimental results and provide predictions for future analyses. Published by the American Physical Society 2024

Astronomy & Astrophysics↗