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At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Rapid Inference of Logic Gate Neural Networks for Anomaly Detection in High Energy Physics

The increasing data rates and complexity of detectors at the Large Hadron Collider (LHC) necessitate fast and efficient machine learning models, particularly for rapid selection of what data to store, known as triggering. Building on recent work in differentiable logic gates, we present a public implementation of a Convolutional Differentiable Logic Gate Neural Network (CLGN). We apply this to detecting anomalies at the Level-1 Trigger at CMS using public data from the CICADA project. We demonstrate that the CLGN achieves physics performance on par with or superior to conventional quantized neural networks. We also synthesize an LGN for a Field-Programmable Gate Array (FPGA) and show highly promising FPGA characteristics, notably zero Digital Signal Processor (DSP) resource usage. This work highlights the potential of logic gate networks for high-speed, on-detector inference in High Energy Physics and beyond.

FOS: Physical sciences↗
DOE OSTI2025

Long-lived particles: theory and experimental probes

Long-lived particles (LLPs) are particles that are stable or that live long enough for their decays to be experimentally distinguishable in time or position from their production point. We provide an overview of the phenomenology and experimental signatures of LLPs, focusing on LLPs at the Large Hadron Collider (LHC). We explain what determines a particle's lifetime and we show that LLPs are ubiquitous both within the Standard Model and beyond. We survey the methods used to experimentally detect and characterize particles at collider-based experiments, and discuss how searches for LLPs present both experimental challenges and exciting new possibilities for detection. Finally, we situate LHC searches for LLPs within the broader experimental landscape with a brief overview of searches for LLPs at lower-energy experiments and a discussion of astrophysical and cosmological probes offering complementary insight into the physics of LLPs beyond the Standard Model.

Jeanty, Laura [University of Oregon]↗
NASA NTRS2007

Challenges in 21st Century Physics

We are truly fortunate to live in one of the great epochs of human discovery, a time when science is providing new visions and understanding about ourselves and the world in which we live. At last, we are beginning to explore the Universe itself. One particularly exciting area of advancement is high-energy physics where several existing concepts will be put to the test. A brief survey will be given of accomplishments in 20th Century physics. These include relativity and quantum physics which have produced breakthroughs in cosmology, astrophysics, and high-energy particle physics. The current situation is then assessed, combining the last 100 years of progress with new 21st Century challenges about unification and where to go next. Finally, the future is upon us. The next frontier in experimental high-energy physics, the Large Hadron Collider (LHC) at CERN in Geneva, is scheduled to begin coming online this year (2007). The potential for the LHC to address several of the significant problems in physics today will be discussed, as this great accelerator examines the predictions of the Standard Model of particle physics and even cosmology. New physics and new science will surely emerge and a better vision of the world will unfold.

Wilson, Thomas L.↗
NASA NTRS2007

The Ultimate Monte Carlo: Studying Cross-Sections With Cosmic Rays

The high-energy physics community has been discussing for years the need to bring together the three principal disciplines that study hadron cross-section physics - ground-based accelerators, cosmic-ray experiments in space, and air shower research. Only recently have NASA investigators begun discussing the use of space-borne cosmic-ray payloads to bridge the gap between accelerator physics and air shower work using cosmic-ray measurements. The common tool used in these three realms of high-energy hadron physics is the Monte Carlo (MC). Yet the obvious has not been considered - using a single MC for simulating the entire relativistic energy range (GeV to EeV). The task is daunting due to large uncertainties in accelerator, space, and atmospheric cascade measurements. These include inclusive versus exclusive cross-section measurements, primary composition, interaction dynamics, and possible new physics beyond the standard model. However, the discussion of a common tool or ultimate MC might be the very thing that could begin to unify these independent groups into a common purpose. The Offline ALICE concept of a Virtual MC at CERN s Large Hadron Collider (LHC) will be discussed as a rudimentary beginning of this idea, and as a possible forum for carrying it forward in the future as LHC data emerges.

Wilson, Thomas L.↗
NASA NTRS2008

The Cosmic Ray Electron Excess

This slide presentation reviews the possible sources for the apparent excess of Cosmic Ray Electrons. The presentation reviews the Advanced Thin Ionization Calorimeter (ATIC) instrument, the various parts, how cosmic ray electrons are measured, and shows graphs that review the results of the ATIC instrument measurement. A review of Cosmic Ray Electrons models is explored, along with the source candidates. Scenarios for the excess are reviewed: Supernova remnants (SNR) Pulsar Wind nebulae, or Microquasars. Each of these has some problem that mitigates the argument. The last possibility discussed is Dark Matter. The Anti-Matter Exploration and Light-nuclei Astrophysics (PAMELA) mission is to search for evidence of annihilations of dark matter particles, to search for anti-nuclei, to test cosmic-ray propagation models, and to measure electron and positron spectra. There are slides explaining the results of Pamela and how to compare these with those of the ATIC experiment. Dark matter annihilation is then reviewed, which represent two types of dark matter: Neutralinos, and kaluza-Kline (KK) particles, which are next explained. The future astrophysical measurements, those from GLAST LAT, the Alpha Magnetic Spectrometer (AMS), and HEPCAT are reviewed, in light of assisting in finding an explanation for the observed excess. Also the Compact Muon Solenoid (CMS) experiment at the Large Hadron Collider (LHC) could help by revealing if there are extra dimensions.

Chang, J.↗
NASA NTRS2007

Science Objectives of the JEM EUSO Mission on International Space Station

JEM-EUSO space observatory is planned with a very large exposure factor which will exceed the critical exposure factor required for observing the most of the sources within the propagational horizon of about one hundred Mpc. The main science objective of JEM-EUSO is the source-identifying astronomy in particle channel with extremey-high-energy particles. Quasi-linear tracking of the source objects through galactic magnetic field should become feasible at energy > 10(exp 20) eV for all-sky. The individual GZK profile in high statistics experiments should differ from source to source due to different distance unless Lorentz invariance is somehow limited. hi addition, JEM-EUSO has three exploratory test observations: (i), extremely high energy neutrinos beginning at E > 10(exp 19) eV: neutrinos as being expected to have a slowly increasing cross section in the Standard Model, and in particular, hundreds of times more in the extra-dimension models. (ii). fundamental physics at extreme Super LHC (Large Hadronic Collider) energies with the hierarchical unified energy much below the GUT scale, and (iii). global atmospheric observation, including large-scale and local plasma discharges, night-glow, meteorites, and others..

Takahashi, Yoshiyuki↗
NASA NTRS2024

COLUTA: Custom 8-Channel 15-bit 40-MSPS ADC for the ATLAS Liquid Argon Calorimeter Readout

The stringent radiation-tolerance, quantization requirements, and the need for seamless integration of the on-detector readout electronics chain require the design of a full-custom analog-to-digital converter (ADC) for the 182,468 channels in the ATLAS Liquid Argon (LAr) calorimeter at the Large Hadron Collider (LHC) at CERN, as part of the High-Luminosity LHC (HL-LHC) upgrade. Each of the 8 channels in the prototype 65 nm CMOS ADC with 15-bit resolution and >68 dB signal-to-noise-and-distortion ratio (SNDR), or equivalently >11 effective number of bits (ENOB), consists of a Multiplying-DAC (MDAC) and a successive-approximation (SAR) ADC. A digital data processing unit (DDPU) calibrates and serially transmits the quantized data. Initial lab characterization of 18 chips shows a minimum SNDR of 69.5 dB at full-scale at about 5 MHz and a maximum power consumption of 1.17 W; differential non-linearity (DNL) measurements show no missing codes. Additional validation of the ADC is ongoing before approximately 70k chips can be mass-produced for the upgrade.

Rui Xu↗
DOE OSTI2021

Finalizing Construction of a New Data Center at BNL

Computational science, data management and analysis have been key factors in the success of Brookhaven National Laboratory's scientific programs at the Relativistic Heavy Ion Collider (RHIC), the National Synchrotron Light Source II (NSLS-II), the Center for Functional Nanomaterials (CFN), and in biological, atmospheric, and energy systems science, Lattice Quantum Chromodynamics (LQCD) and Materials Science, as well as our participation in international research collaborations, such as the ATLAS experiment at Europe's Large Hadron Collider (LHC) at CERN (Switzerland) and the Belle II experiment at KEK (Japan). The construction of a new data center is an acknowledgement of the increasing demand for computing and storage services at BNL in the near term and enable the Lab to address the needs of the future experiments at the High-Luminosity LHC at CERN and the Electron-Ion Collider (EIC) at BNL in the long term.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2021

The Tracking Machine Learning challenge : Throughput phase

This paper reports on the second "Throughput" phase of the Tracking Machine Learning (TrackML) challenge on the Codalab platform. As in the first "Accuracy" phase, the participants had to solve a difficult experimental problem linked to tracking accurately the trajectory of particles as e.g. created at the Large Hadron Collider (LHC): given O($10^5$) points, the participants had to connect them into O($10^4$) individual groups that represent the particle trajectories which are approximated helical. While in the first phase only the accuracy mattered, the goal of this second phase was a compromise between the accuracy and the speed of inference. Both were measured on the Codalab platform where the participants had to upload their software. The best three participants had solutions with good accuracy and speed an order of magnitude faster than the state of the art when the challenge was designed. Although the core algorithms were less diverse than in the first phase, a diversity of techniques have been used and are described in this paper. The performance of the algorithms are analysed in depth and lessons derived.

Amrouche, Sabrina↗
DOE OSTI2021

Review of opportunities for new long-lived particle triggers in Run 3 of the Large Hadron Collider

Long-lived particles (LLPs) are highly motivated signals of physics Beyond the Standard Model (BSM) with great discovery potential and unique experimental challenges. The LLP search programme made great advances during Run 2 of the Large Hadron Collider (LHC), but many important regions of signal space remain unexplored. Dedicated triggers are crucial to improve the potential of LLP searches, and their development and expansion is necessary for the full exploitation of the new data. The public discussion of triggers has therefore been a relevant theme in the recent LLP literature, in the meetings of the LLP@LHC Community workshop and in the respective experiments. This paper documents the ideas collected during talks and discussions at these Workshops, benefiting as well from the ideas under development by the trigger community within the experimental collaborations. We summarise the theoretical motivations of various LLP scenarios leading to highly elusive signals, reviewing concrete ideas for triggers that could greatly extend the reach of the LHC experiments. We thus expect this document to encourage further thinking for both the phenomenological and experimental communities, as a stepping stone to further develop the LLP@LHC physics programme.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Autoencoders on FPGAs for real-time, unsupervised new physics detection at 40 MHz at the Large Hadron Collider

In this paper, we show how to adapt and deploy anomaly detection algorithms based on deep autoencoders, for the unsupervised detection of new physics signatures in the extremely challenging environment of a real-time event selection system at the Large Hadron Collider (LHC). We demonstrate that new physics signatures can be enhanced by three orders of magnitude, while staying within the strict latency and resource constraints of a typical LHC event filtering system. This would allow for collecting datasets potentially enriched with high-purity contributions from new physics processes. Through per-layer, highly parallel implementations of network layers, support for autoencoder-specific losses on FPGAs and latent space based inference, we demonstrate that anomaly detection can be performed in as little as $80\,$ns using less than 3% of the logic resources in the Xilinx Virtex VU9P FPGA. Opening the way to real-life applications of this idea during the next data-taking campaign of the LHC.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Optical Transmission Characterization of Fused Silica Materials Irradiated at the CERN Large Hadron Collider

The Target Absorbers for Neutrals (TANs) represent one of the most radioactive regions in the Large Hadron Collider (LHC). Seven 40 cm long fused silica rods with different dopant specifications, manufactured by Heraeus, were irradiated in one of the TANs located around the ATLAS experiment by the Beam RAte of Neutrals (BRAN) detector group. This campaign took place during the Run 2 p+p data taking, which occurred between 2016 and 2018. This paper reports a complete characterization of optical transmission per unit length of irradiated fused silica materials as a function of wavelength (240 nm - 1500 nm), dose (up to 18 MGy), and level of OH and H$_2$ dopants introduced in the manufacturing process. The dose delivered to the rods was estimated using Monte Carlo simulations performed by the CERN FLUKA team.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

US ATLAS and US CMS HPC and Cloud Blueprint

The Large Hadron Collider (LHC) at CERN houses two general purpose detectors - ATLAS and CMS - which conduct physics programs over multi-year runs to generate increasingly precise and extensive datasets. The efforts of the CMS and ATLAS collaborations lead to the discovery of the Higgs boson, a fundamental particle that gives mass to other particles, representing a monumental achievement in the field of particle physics that was recognized with the awarding of the Nobel Prize in Physics in 2013 to François Englert and Peter Higgs. These collaborations continue to analyze data from the LHC and are preparing for the high luminosity data taking phase at the end of the decade. The computing models of these detectors rely on a distributed processing grid hosted by more than 150 associated universities and laboratories worldwide. However, such new data will require a significant expansion of the existing computing infrastructure. To address this, both collaborations have been working for years on integrating High Performance Computers (HPC) and commercial cloud resources into their infrastructure and continue to assess the potential role of such resources in order to cope with the demands of the new high luminosity era. US ATLAS and US CMS computing management have charged the authors to provide a blueprint document looking at current and possibly future use of HPC and Cloud resources, outlining integration models, possibilities, challenges and costs. The document will address key questions such as the optimal use of resources for the experiments and funding agencies, the main obstacles that need to be overcome for resource adoption, and areas that require more attention.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Exclusive QCD Factorization and Single Transverse Polarization Phenomena at High-Energy Colliders

This Ph.D. thesis is divided into two distinct parts. The first part focuses on hard exclusive scattering processes in Quantum Chromodynamics (QCD) at high energies, while the second part delves into spin phenomena at the Large Hadron Collider (LHC). Hard exclusive scattering processes play a crucial role in QCD at high energies, providing unique insights into the confined partonic dynamics within hadrons, complementing inclusive processes. Studying these processes within the QCD factorization approach yields the generalized parton distribution (GPD), a nonperturbative parton correlation function that offers a three-dimensional tomographic parton image within a hadron. However, the experimental measurement of these processes poses significant challenges. This thesis will review the factorization formalism for related processes, examine the limitations of some widely used processes, and introduce two novel processes that enhance the sensitivity to GPD, particularly its dependence on the parton momentum fraction x. The second part of the thesis centers on spin phenomena, specifically single spin production, at the LHC. Noting that a single transverse polarization can be generated even in an unpolarized collision, this research proposes two new jet substructure observables: one for boosted top quark jets and another for high-energy gluon jets. The observation of these phenomena paves the way for innovative tools in LHC phenomenology, enabling both precision measurements and the search for new physics.

Yu, Zhite↗
DOE OSTI2023

Induced Generative Adversarial Particle Transformers

In high energy physics (HEP), machine learning methods have emerged as an effective way to accurately simulate particle collisions at the Large Hadron Collider (LHC). The message-passing generative adversarial network (MPGAN) was the first model to simulate collisions as point, or ``particle'', clouds, with state-of-the-art results, but suffered from quadratic time complexity. Recently, generative adversarial particle transformers (GAPTs) were introduced to address this drawback; however, results did not surpass MPGAN. We introduce induced GAPT (iGAPT) which, by integrating ``induced particle-attention blocks'' and conditioning on global jet attributes, not only offers linear time complexity but is also able to capture intricate jet substructure, surpassing MPGAN in many metrics. Our experiments demonstrate the potential of iGAPT to simulate complex HEP data accurately and efficiently.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Smart Pixels: In-pixel AI for on-sensor data filtering

We present a smart pixel prototype readout integrated circuit (ROIC) designed in CMOS 28 nm bulk process, with in-pixel implementation of an artificial intelligence (AI) / machine learning (ML) based data filtering algorithm designed as proof-of-principle for a Phase III upgrade at the Large Hadron Collider (LHC) pixel detector. The first version of the ROIC consists of two matrices of 256 smart pixels, each 25$\times$25 $\mu$m$^2$ in size. Each pixel consists of a charge-sensitive preamplifier with leakage current compensation and three auto-zero comparators for a 2-bit flash-type ADC. The frontend is capable of synchronously digitizing the sensor charge within 25 ns. Measurement results show an equivalent noise charge (ENC) of $\sim$30e$^-$ and a total dispersion of $\sim$100e$^-$ The second version of the ROIC uses a fully connected two-layer neural network (NN) to process information from a cluster of 256 pixels to determine if the pattern corresponds to highly desirable high-momentum particle tracks for selection and readout. The digital NN is embedded in-between analog signal processing regions of the 256 pixels without increasing the pixel size and is implemented as fully combinatorial digital logic to minimize power consumption and eliminate clock distribution, and is active only in the presence of an input signal. The total power consumption of the neural network is $\sim$ 300 $\mu$W. The NN performs momentum classification based on the generated cluster patterns and even with a modest momentum threshold, it is capable of 54.4% - 75.4% total data rejection, opening the possibility of using the pixel information at 40MHz for the trigger. The total power consumption of analog and digital functions per pixel is $\sim$ 6 $\mu$W per pixel, which corresponds to $\sim$ 1 W/cm$^2$ staying within the experimental constraints.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Large Neutrino "Collider"

We propose using current and future large-volume neutrino telescopes as ``Large Neutrino Colliders" (L$ν$Cs) to explore TeV-scale physics beyond the Standard Model. Cosmic neutrinos with energies above 100 PeV colliding with nucleons in the detector reach center-of-mass energies beyond the 14 TeV limit of the Large Hadron Collider (LHC). Using recently predicted and measured high-energy and ultra-high-energy neutrino fluxes from IceCube and KM3NeT, we estimate mass-scale sensitivities for representative new physics scenarios at 1--30 km$^3$ L$ν$Cs. Our results demonstrate that L$ν$Cs provide a novel avenue to probe multi-TeV particles with sensitivities comparable to, or even surpassing, those of the LHC.

Bai, Yang [Wisconsin U., Madison; Argonne]↗
DOE OSTI2025

Why Is Attention Sparse In Particle Transformer?

Transformer-based models have achieved state-of-the-art performance in jet tagging at the CERN Large Hadron Collider (LHC), with the Particle Transformer (ParT) representing a leading example of such models. A striking feature of ParT is its sparse, nearly binary, attention structure, raising questions about the origin of this behavior and whether it encodes physically meaningful correlations. In this work, we investigate the source of ParT's sparse attention by comparing models trained on multiple benchmark datasets and examine the relative contributions of the attention term and the physics-inspired interaction matrix before softmax. We find that binary sparsity arises primarily from the attention mechanism itself, with the interaction matrix playing a secondary role. Moreove, we show that ParT is able to identify key jet substructure elements, such as leptons in semileptonic top decays, even without explicit particle identification inputs. These results provide new insight into the interpretability of transformer-based jet taggers and clarify the conditions under which sparse attention patterns emerge in ParT.

Legge, Timothy [UC, San Diego]↗