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At least 235 records · Page 13

Implications of HARP Results for the Energy of the Proton Driver for a Neutrino Factory and Muon Collider

Cross-section data from the HARP experiment for pion production by protons from a tantalum target have been convoluted with the acceptance of the front-end channel for the proposed neutrino factory or muon collider and integrated over the full phase space measured by HARP, to determine the beam-energy dependence of the muon yield. This permits a determination of the optimal beam energy for the proton driver for these projects. The cross-section data are corrected for the beam-energy dependent 'amplification' due to the development of hadronic showers in a thick target. The conclusion is that, for constant beam power, the yield is maximum for a beam energy of about 7 GeV, but it is within 10% of this maximum for 4 < T{sub beam} < 11 GeV, and within 20% of the maximum for T{sub beam} as low as 2 GeV. This result is insensitive to which of the two HARP groups results are used, and to which pion generator is used to compute the thick target effects.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Experimental and computational kinetics study of the liquid-phase hydrogenation of C=C and C=O bonds

Solvent effects on adsorption equilibrium and reaction kinetics are evaluated for hydrogenation reactions catalyzed by Pd/alumina in a series of different solvents. Three reactants – cyclohexene, benzene and benzaldehyde – and three solvents – n-heptane (HEP), methylcyclohexane (MCHA), decalin (DL) – have been investigated. Kinetic analysis of hydrogenation of cyclohexene reveals that hydrogen adsorbs on different sites from those where cyclohexene and the solvents adsorb; however, the presence of hydrogen on these separate sites affects the heats of adsorption of the hydrocarbons. When the solvent is a weakly interacting linear alkane (HEP), the rate determining step of the reaction is the first hydrogenation of adsorbed cyclohexene. Furthermore, this conclusion is supported by DFT calculations that show a higher enthalpy barrier for the first hydrogenation than for the second, while statistical thermodynamics analysis validates the physical significance of the entropy of adsorption parameters derived from the kinetic fitting of experimental data. By contrast, with solvents such as MCHA and DL, which interact more strongly with the metal surface and compete for active sites with the reactant and the surface intermediate, the rate limiting step seems to shift to the second hydrogenation step.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Software Aspects of IEEE Floating-Point Computations for Numerical Applications in High Energy Physics

Floating-point computations are at the heart of much of the computing done in high energy physics. The correctness, speed and accuracy of these computations are of paramount importance. The lack of any of these characteristics can mean the difference between new, exciting physics and an embarrassing correction. This talk will examine practical aspects of IEEE 754-2008 floating-point arithmetic as encountered in HEP applications. After describing the basic features of IEEE floating-point arithmetic, the presentation will cover: common hardware implementations (SSE, x87) techniques for improving the accuracy of summation, multiplication and data interchange compiler options for gcc and icc affecting floating-point operations hazards to be avoided. About the speaker: Jeffrey M Arnold is a Senior Software Engineer in the Intel Compiler and Languages group at Intel Corporation. He has been part of the Digital->Compaq->Intel compiler organization for nearly 20 years; part of that time, he worked on both low- and high-level math libraries. Prior to that, he was in the VMS Engineering organization at Digital Equipment Corporation. In the late 1980s, Jeff spent 2½ years at CERN as part of the CERN/Digital Joint Project. In 2008, he returned to CERN to spent 10 weeks working with CERN/openlab. Since that time, he has returned to CERN multiple times to teach at openlab workshops and consult with various LHC experiments. Jeff received his Ph.D. in physics from Case Western Reserve University.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Sloan Digital Sky Survey Photometric Calibration Revisited

The Sloan Digital Sky Survey calibration is revisited to obtain the most accurate photometric calibration. A small but significant error is found in the flat-fielding of the Photometric telescope used for calibration. Two SDSS star catalogs are compared and the average difference in magnitude as a function of right ascension and declination exhibits small systematic errors in relative calibration. The photometric transformation from the SDSS Photometric Telescope to the 2.5 m telescope is recomputed and compared to synthetic magnitudes computed from measured filter bandpasses.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Uncertainty Propagation within Chained Models for Machine Learning Reconstruction of Neutrino-LAr Interactions

Sequential or chained models are increasingly prevalent in machine learning for scientific applications, due to their flexibility and ease of development. Chained models are particularly useful when a task is separable into distinct steps with a hierarchy of meaningful intermediate representations. In reliability-critical tasks, it is important to quantify the confidence of model inferences. However, chained models pose an additional challenge for uncertainty quantification, especially when input uncertainties need to be propagated. In such cases, a fully uncertainty-aware chain of models is required, where each step accepts a probability distribution over the input space, and produces a probability distribution over the output space. In this work, we present a case study for adapting a single model within an existing chain, designed for reconstruction within neutrino-Argon interactions, developed for neutrino oscillation experiments such as MicroBooNE, ICARUS, and the future DUNE experiment. We test the performance of an input uncertainty-enabled model against an uncertainty-blinded model using a method for generating synthetic noise. By comparing these two, we assess the increase in inference quality achieved by exposing models to upstream uncertainty estimates.

97 MATHEMATICS AND COMPUTING↗

Top Quark Amplitudes with an Anomolous Magnetic Moment

The anomalous magnetic moment of the top quark may be measured during the first run of the LHC at 7 TeV. For these measurements, it will be useful to have available tree amplitudes with t{bar t} and arbitrarily many photons and gluons, including both QED and color anomalous magnetic moments. In this paper, we present a method for computing these amplitudes using the Britto-Cachazo-Feng-Witten recursion formula. Because we deal with an effective theory with higher-dimension couplings, there are roadblocks to a direct computation with the Britto-Cachazo-Feng-Witten method. We evade these by using an auxiliary scalar theory to compute a subset of the amplitudes.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Reliability Assessment of Safety-Critical Network Communication in a Digitalized Nuclear Power Plant

In analog instrumentation and control (I and C) systems for nuclear power plants (NPPs), most connections are comprised of hardwired point-to-point types. Since they are based on analog technologies, they are fragile to noise and require analog-to-digital conversion time. Therefore, many NPPs have adopted communication network for the exchange of safety-critical data between programmable logic controllers (PLCs) in digital I and C systems to effectively accommodate a huge number of field controllers. However, the primary issue of digital network communication in a safety-critical system involves potential hazards, such as partial or total loss of communication between PLCs, which may result in a failure of safety critical signal generation when it is needed. Therefore, the probability that a safety-critical system in digitalized NPP becomes unsafe due to a network failure must be evaluated to quantify the risk of digital I and C system. In Korea, the Engineered Safety Feature-Component Control System (ESF-CCS) was developed as one of the digital safety-critical system in Advanced Power Reactor- 1400 (APR-1400). The function of a digital engineered safety feature (ESF) actuation system and field actuator controllers of conventional NPPs are performed by the ESF-CCS. In this system, safety-critical network, High Reliable- Safety Data Network (HR-SDN), was employed for the safety-critical data transmission from group controllers (GCs) to loop controllers (LCs). In this study, a framework for assessing the reliability of a HR-SDN network communication between GCs and LCs in the ESF-CCS in addition to a fault-tree model for ESF components considering network failure between GCs and LCs were developed to assess the plant risk effect of a newly developed digitalized ESF-CCS. Based on the case studies and cut set analysis, the risk effect of network failure on plant risk and the important risk contributors of network failure were quantitatively addressed. A framework for identifying the potential hazardous states of network communication in the ESFCCS was proposed. In addition, a fault-tree model for network communication failure was developed to estimate the risk effects of network failure between the GCs and LCs on ESF-CCS signal failure. The developed fault-tree model was then applied to several case studies. The fault-tree model of ESF-CCS signal failure for ESF components required for various mitigation actions regarding NPP DBAs was designed by considering the identified hazardous states of network failure that would result in a failure to provide input signals to the corresponding LC. As a sensitivity study, three case studies were performed based on the periodic test methods for hardware components in HR-SDN module and their test intervals in this study. The quantitative results for three case studies demonstrated that the probability of overall network communication failure, which was calculated as the sum of the failure probability associated with each failure cause, contributed up to 1.58% on the Small-LOCA CD frequency. The results also revealed the important basic events related to network failure in the case studies which included CCF of hardware and software in HR-SDN module. This study is expected to provide insight into the development of the fault-tree model for the network failure in digital I and C system and into the quantification of the risk effect of network failure for safety-critical data transmission in NPPs. As a further study, the risk effects of network failure in the ESF-CCS on the plant risk can be estimated in a more detailed manner by analyzing the failure modes and causes in a sub-component level and the fault detection coverage of the fault tolerance techniques for network failure implemented in ESF-CCS after the detailed configuration of ESF-CCS is decided. In terms of the failure of manual ESF actuation, the relationship among the human action failures must be investigated to consider multiple human error condition since ESF-CCS provides multiple manual actuation to assure the diversity of the system. Since the conventional HEP method cannot accommodate the multiple conditions in a fault tree, condition-based human reliability assessment (CBHRA) method or the dynamic human reliability modeling approach can be applied to include a complex relationship among the automated safety signal generation and the human operator's manual actuation, avoiding the optimistic estimation of HEP of the human action failure.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

High Energy Physics Network Requirements Review: Two-Year Update

The Energy Sciences Network (ESnet) is the high-performance network user facility for the US Department of Energy (DOE) Office of Science (SC) and delivers highly reliable data transport capabilities optimized for the requirements of data-intensive science. In essence, ESnet is the circulatory system that enables the DOE science mission by connecting all its laboratories and facilities in the US and abroad. ESnet is funded and stewarded by the Advanced Scientific Computing Research (ASCR) program and managed and operated by the Scientific Networking Division at Lawrence Berkeley National Laboratory (LBNL). ESnet is widely regarded as a global leader in the research and education networking community. ESnet interconnects DOE national laboratories, user facilities, and major experiments so that scientists can use remote instruments and computing resources as well as share data with collaborators, transfer large datasets, and access distributed data repositories. ESnet is specifically built to provide a range of network services tailored to meet the unique requirements of the DOE’s data-intensive science. In July 2023, the Energy Sciences Network (ESnet) and the High Energy Physics program (HEP) of the DOE SC organized an interim ESnet requirements review of HEP-supported activities, to follow up on the work started during the 2020 HEP Network Requirements Review. Preparation for these events included checking back with the key stakeholders: program and facility management, research groups, and technology providers. Each stakeholder group was asked to prepare updates to their previously submitted case study documents, so that ESnet could update the understanding of any changes to the current, near-term, and long-term status, expectations, and processes that will support the science activities of the program.

97 MATHEMATICS AND COMPUTING↗

GQLink: an implementation of Quantized State Systems (QSS) methods in Geant4

Simulations in high energy physics (HEP) often require the numerical solution of ordinary differential equations (ODE) to determine the trajectories of charged particles in a magnetic field when particles move throughout detector volumes. Each crossing of a volume interrupts the underlying numerical method that solves the equations of motion, triggering iterative algorithms to estimate the intersection point within a given accuracy. The computational cost of this procedure can grow significantly depending on the application at hand. Quantized State System (QSS) is a recent family of discrete-event driven numerical methods exhibiting attractive features for this type of problems, such as native dense output (sequences of polynomial segments updated only by accuracy-driven events) and lightweight detection and handling of volume crossings. In this work we present GQLink, a proof-of-concept integration of QSS with the Geant4 simulation toolkit which stands as an interface for co-simulation that orchestrates robustly and transparently the interaction between the QSS simulation engine and aspects such as geometry definition and physics processes controlled by Geant4. In conclusion, we validate the accuracy and study the performance of the method in simple geometries (subject to intense volume crossing activity) and then in a realistic HEP application using a full CMS detector configuration.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Celeritas: Accelerating Geant4 with GPUs

Celeritas [1] is a new Monte Carlo (MC) detector simulation code designed for computationally intensive applications (specifically, High Lumi- nosity Large Hadron Collider (HL-LHC) simulation) on high-performance heterogeneous architectures. In the past two years Celeritas has advanced from prototyping a GPU-based single physics model in infinite medium to implementing a full set of electromagnetic (EM) physics processes in complex geometries. The current release of Celeritas, version 0.3, has incorporated full device-based navigation, an event loop in the presence of magnetic fields, and detector hit scoring. New functionality incorporates a scheduler to offload electromagnetic physics to the GPU within a Geant4-driven simulation, enabling integration of Celeritas into high energy physics (HEP) experimental frameworks such as CMSSW. On the Summit supercomputer, Celeritas performs EM physics between 6 and 32 faster using the machine’s Nvidia GPUs compared to using only CPUs. When running a multithreaded Geant4 ATLAS test beam application with full hadronic physics, using Celeritas to accelerate the EM physics results in an overall simulation speedup of 1.8–2.3× on GPU and 1.2× on CPU.

Johnson, Seth R.↗

Production Operations Management System (POMS) for Fermilab Experiments

The Production Operations Management System (POMS) software allows production teams and analysis groups across multiple Fermilab experiments to launch, modify and monitor large scale campaigns of related Monte Carlo or data processing jobs, and currently manages the majority of production computing of experiments at Fermilab.POMS provides a web service interface that enables automated job submission on distributed resources according to customers’ requests, as well as subsequent monitoring of those submissions as well as recovery of failed submissions, debugging and record keeping.POMS interfaces with existing HEP data access, processing, movement and monitoring tools at Fermilab, including Jobsub (for job submission), SAM (for data management), and Landscape (for monitoring), and in combination with them handles the creation of intermediate datasets of files for multistage campaigns.POMS visualizes these campaigns with an interactive GUI interface. An important feature of POMS is a one-to-one connection between the GUI campaign visualizer and a text based representation of the complete campaign configuration. An extensible library of template campaign configurations is available. The templates are user modifiable and map cleanly to and from the GUI description of the campaign.This paper will discuss the current usage, history, and some technical details of POMS, as well as planned future extensions, particularly interfacing with Rucio as well as SAM for file movement.

Mengel, Marc↗

2020 High Energy Physics Network Requirements Review (Final Report)

The Energy Sciences Network (ESnet) is the high-performance network user facility for the US Department of Energy (DOE) Office of Science (SC) and delivers highly reliable data transport capabilities optimized for the requirements of data-intensive science. In essence, ESnet is the circulatory system that enables the DOE science mission by connecting all of its laboratories and facilities in the United States and abroad. ESnet is funded and stewarded by the Advanced Scientific Computing Research (ASCR) program and managed and operated by the Scientific Networking Division at Lawrence Berkeley National Laboratory (LBNL). ESnet is widely regarded as a global leader in the research and education networking community. Throughout 2020,ESnet and the Office of High Energy Physics (HEP) of the DOE SC organized an ESnet requirements review of HEP-supported activities. Preparation for this event included identification of key stakeholders: program and facility management, research groups, technology providers, and a number of external observers. These individuals were asked to prepare formal case study documents about their relationship to the HEP program to build a complete understanding of the current, near-term, and long-term status, expectations, and processes that will support the science going forward. A series of pre-planning meetings better prepared case study authors for this task, along with guidance on how the review would proceed in a virtual fashion. ESnet and ASCR use requirements reviews to discuss and analyze current and planned science use cases and anticipated data output of a particular program, user facility, or project to inform ESnet’s strategic planning, including network operations, capacity upgrades, and other service investments. A requirements review comprehensively surveys major science stakeholders’ plans and processes in order to investigate data management requirements over the next 5–10 years.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Deep Learning Methods for Symbolic Calculations in HEP

This project develops machine learning methods to accelerate symbolic calculations in high-energy physics. Using sequence-to-sequence transformer models, we construct frameworks to predict squared amplitudes and related quantities for Standard Model processes, including quantum electrodynamics, quantum chromodynamics, and electroweak interactions. The results demonstrate that deep learning can successfully learn complex symbolic relationships and provide a scalable approach to symbolic computation with potential applications in precision calculations and collider phenomenology.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Measurement of the E+ E- to Pi+ Pi- (Gamma) Cross Section with the ISR Method with BaBar

A precision measurement of the cross section for the process e{sup +}e{sup -} {yields} {pi}{sup +}{pi}{sup -}({gamma}) is presented with the radiative return method with the high statistics data accumulated by BaBar at the {Upsilon}(4S). The luminosity is determined from the study of the corresponding leptonic process e{sup +}e{sup -} {yields} {mu}{sup +}{mu}{sup -}({gamma}), thus cancelling several factors and reducing the overall systematic uncertainty. Trigger, tracking, particle identification, and kinematic-fit {chi}{sup 2} efficiencies are evaluated from data in the same environment. Additional radiation from the initial and the final states is studied in both processes. The analysis covers the mass range between threshold and 5 GeV. Preliminary results are presented here between 0.5 and 3 GeV, with data samples of 513183 pion events and 445631 muon events. The systematic uncertainty in the main {rho} resonance region is 5.6 x 10{sup -3}. The measured mass dependent pion-pair cross section is compared with measurements from earlier experiments and used to compute the hadronic vacuum polarization contribution from the dominant {pi}{pi} channel to the muon magnetic anomaly.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

HEP Software Foundation Community White Paper Working Group – Conditions Data

To produce the best physics results, high energy physics experiments require access to calibration and other non-event data during event data processing. These conditions data are typically stored in databases that provide versioning functionality, allowing physicists to make improvements while simultaneously guaranteeing the reproducibility of their results. With the increased complexity of modern experiments, and the evolution of computing models that demand large scale access to conditions data, the solutions for managing this access have evolved over time. In this white paper we give an overview of the conditions data access problem, present convergence on a common solution and present some considerations for the future.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Quantum Algorithms for Collider Physics (Final Report)

The goal of this project was to unite powerful analysis techniques in high-energy physics (HEP) with cutting-edge advances in quantum information science (QIS). Almost every event at the Large Hadron Collider (LHC) involves jets, collimated sprays of particles that are copiously produced in proton-proton collisions. Current LHC algorithms to identify and classify jets are constrained by the limits of classical computation. Quantum algorithms could fundamentally change how collider data is analyzed, by speeding up existing classical algorithms and by enabling new quantum jet representations. By exploiting the capabilities of quantum computation, this research confronted the challenge of data analysis in collider physics.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Virtual machine provisioning, code management, and data movement design for the Fermilab HEPCloud Facility

The Fermilab HEPCloud Facility Project has as its goal to extend the current Fermilab facility interface to provide transparent access to disparate resources including commercial and community clouds, grid federations, and HPC centers. This facility enables experiments to perform the full spectrum of computing tasks, including data-intensive simulation and reconstruction. We have evaluated the use of the commercial cloud to provide elasticity to respond to peaks of demand without overprovisioning local resources. Full scale data-intensive workflows have been successfully completed on Amazon Web Services for two High Energy Physics Experiments, CMS and NOνA, at the scale of 58000 simultaneous cores. This paper describes the significant improvements that were made to the virtual machine provisioning system, code caching system, and data movement system to accomplish this work. The virtual image provisioning and contextualization service was extended to multiple AWS regions, and to support experiment-specific data configurations. A prototype Decision Engine was written to determine the optimal availability zone and instance type to run on, minimizing cost and job interruptions. We have deployed a scalable on-demand caching service to deliver code and database information to jobs running on the commercial cloud. It uses the frontiersquid server and CERN VM File System (CVMFS) clients on EC2 instances and utilizes various services provided by AWS to build the infrastructure (stack). We discuss the architecture and load testing benchmarks on the squid servers. We also describe various approaches that were evaluated to transport experimental data to and from the cloud, and the optimal solutions that were used for the bulk of the data transport. Finally, we summarize lessons learned from this scale test, and our future plans to expand and improve the Fermilab HEP Cloud Facility.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

The Simplicity of Perfect Atoms: Degeneracies in Supersymmetric Hydrogen

Supersymmetric QED hydrogen-like bound states are remarkably similar to non-supersymmetric hydrogen, including an accidental degeneracy of the fine structure and which is broken by the Lamb shift. This article classifies the states, calculates the leading order spectrum, and illustrates the results in several limits. The relation to other non-relativistic bound states is explored. Supersymmetric bound states provide a laboratory for studying dynamics in supersymmetric theories. Bound states like hydrogen provide a framework for understanding the qualitative dynamics of QCD mesons, a supersymmetric version of QED can provide a qualitative picture for the symmetries and states of superQCD mesons. Furthermore, recent interest in dark matter as a composite state, leads to asking how supersymmetry acts upon these composite states [4-7]. This article calculates the leading order corrections to a hydrogen-like atoms in an exactly supersymmetric version of QED. Much of the degeneracy is broken by the fine structure and a seminal calculation was performed in [1] for positronium, see [2] for an N = 2 version of positronium. Supersymmetric hydrogen is a similar except for the absence of annihilation diagrams, see [3] for an independent calculation. In the heavy proton mass limit, the supersymmetric interactions of the theory become irrelevant operators, suppressed by powers of the proton mass like the magnetic moment operator in QED and the fine structure is identical to the non-supersymmetric theory. This article finds that fine structure spectrum of supersymmetric spectrum of hydrogen has an accidental degeneracy which is exactly analogous to the accidental degeneracy of the l = 0 and l = 1 levels of the n = 2; j = 1/2 state of hydrogen. The supersymmetric version of the Lamb shift lifts the residual degeneracy and this article computes the logarithmically enhanced breaking.

08 HYDROGEN↗