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These lectures give a pedagogical discussion of the computation of QCD tree amplitudes for collider physics. The tools reviewed are spinor products, color ordering, MHV amplitudes, and the Britto-Cachazo-Feng-Witten recursion formula.
Abstract Not Provided
Future particle physics experiments looking for rare processes will have no choice but to address the demanding challenges of fast pattern recognition in triggering as detector hit density becomes significantly higher due to the high luminosity required to produce the rare process. The authors propose to develop a 3D Vertically Integrated Pattern Recognition Associative Memory (VIPRAM) chip for HEP applications, to advance the state-of-the-art for pattern recognition and track reconstruction for fast triggering.
Theories of dark matter that support bound states are an intriguing possibility for the identity of the missing mass of the Universe. This article proposes a class of models of supersymmetric composite dark matter where the interactions with the Standard Model communicate supersymmetry breaking to the dark sector. In these models supersymmetry breaking can be treated as a perturbation on the spectrum of bound states. Using a general formalism, the spectrum with leading supersymmetry effects is computed without specifying the details of the binding dynamics. The interactions of the composite states with the Standard Model are computed and several benchmark models are described. General features of non-relativistic supersymmetric bound states are emphasized.
About dCache: A distributed petabyte-scale storage system for scientific data. Joint effort between DESY(2000), FNAL(2001) and NDGF(2006). Supports standard and HEP specific access protocols and authentication mechanisms. Developed for HERA and Tevatron, used for LHC and others: Belle II, LOFAR, CTA, IceCUBE, EU-XFEL, Petra3, DUNE, and many more.
Celeritas is a new Monte Carlo (MC) detector simulation code designed for computationally intensive applications on high-performance heterogeneous architectures. In the past two years Celeritas has advanced from prototyping a Graphics Processing Unit (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 0.4, 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 straightforward integration of Celeritas into the high energy physics (HEP) experimental frameworks CMSSW and ATLAS FullSimLight. On the Perlmutter supercomputer, Celeritas performs EM physics between 3× and 18× faster using the machine’s Nvidia GPUs compared to using only CPUs, corresponding to an electrical power efficiency up to a factor of 5. 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 1.7–2.2× on GPU and 1.2× on CPU. In a CMS test application using tt¯ events and the prototype Run 4 configuration, compared to Geant4 CPU, Celeritas with a Nvidia A100 improves overall throughput up to a factor of 2.7× but cannot be efficiently shared with more than 8 cores.
This year the University of Puerto Rico at Mayaguez (UPRM) High Energy Physics (HEP) group continued with the ongoing research program outlined in the grant proposal. The program is centered on the Compact Muon Solenoid (CMS) experiment at the proton-proton (pp) collisions at the Large Hadron Collider (LHC) at CERN in Geneva, Switzerland. The main research focus is on data analysis and on the preparation for the High Luminosity (HL) LHC or experiment detector upgrade. The physics data analysis included Higgs Doublet Search and measurement of the (1) Λ 0 b branching fraction, (2) B meson mass, and (3) hyperon θ - b lifetime. The detector upgrade included work on the preparations for the Forward Pixel (FPIX) detector Silicon Sensor Testing in a production run at Fermilab. In addition, the group has taken responsibilities on the Software Release through our former research associate Dr. Eric Brownson who acted until last December as a Level Two Offline Manager for the CMS Upgrade. In support of the CMS data analysis activities carried out locally, the UPRM group has built and maintains an excellent Tier3 analysis center in Mayaguez. This allowed us to analyze large data samples and to continue the development of algorithms for the upgrade tracking robustness we started several years ago, and we plan to resume in the near future. This project involves computer simulation of the radiation damage to be suffered at the higher luminosities of the upgraded LHC. This year we continued to serve as a source of outstanding students for the field of high energy physics. Three of our graduate students finished their MS work in May, 2014, Their theses research were on data analysis of heavy quark b-physics. All of them are currently enrolled at Ph.D. physics program across the nation. One of them (Hector Moreno) at New Mexico University (Hector Moreno), one at University of New Hampshire (Sandra Santiesteban) and one at University of Puerto Rico-Rio Piedras (Carlos Malca). The students H. Moreno and C. Malca has been directly supervised by Dr. Mendez and S. Santiesteban supervised by Dr. Ramirez. During the last 13 years, our group have graduated 23 MS students on experimental High Energy Physics data analysis and applied hardware techniques. Most of the students have been supported by DOE grants, included this grant. Since 2001, Dr. Mendez have directly supervised eleven students, Dr. Ramirez three students and the former PI (Dr. Lopez) nine students. These theses work are fully documented in the group web page (http://charma.uprm.edu). The High Energy Physics group at Mayaguez is small and presently consists of three Physics faculty members, the Senior Investigators Dr. Hector Mendez (Professor) and Dr. Juan Eduardo Ramirez (Professor), and Dr. Sudhir Malik who was just hired in July 2014. Dr. Ramirez is in charge of the UPRM Tier-3 computing and will be building the network bandwidth infrastructure for the campus, while Dr. Mendez will continues his effort in finishing the heavy quark physics data analysis and moving to work on SUSY analysis for the 2015 data. Our last grant application in 2012 was awarded only for 2013-2014. As a result our postdoc position was lost last month of March. Since then, we have hired Dr. Malik as a new faculty in order to reinforce the group and to continue our efforts with the CMS experiment. Our plan is to hire another junior faculty in the next two years to strengthen the HEP group even further. Dr. Mendez continues with QuarkNet activities involving an ever larger group of high school physics teachers from all around Puerto Rico.
As of 2012, a number of US Department of Energy (DOE) National Laboratories have access to a 100 Gb/s wide-area network backbone. The ESnet Advanced Networking Initiative (ANI) project is intended to develop a prototype network, based on emerging 100 Gb/s Ethernet technology. The ANI network will support DOE's science research programs. A 100 Gb/s network test bed is a key component of the ANI project. The test bed offers the opportunity for early evaluation of 100Gb/s network infrastructure for supporting the high impact data movement typical of science collaborations and experiments. In order to make effective use of this advanced infrastructure, the applications and middleware currently used by the distributed computing systems of large-scale science need to be adapted and tested within the new environment, with gaps in functionality identified and corrected. As a user of the ANI test bed, Fermilab aims to study the issues related to end-to-end integration and use of 100 Gb/s networks for the event simulation and analysis applications of physics experiments. In this paper we discuss our findings from evaluating existing HEP Physics middleware and application components, including GridFTP, Globus Online, etc. in the high-speed environment. These will include possible recommendations to the system administrators, application and middleware developers on changes that would make production use of the 100 Gb/s networks, including data storage, caching and wide area access.
The ATLAS Event Streaming Service (ESS) at the LHC is an approach to preprocess and deliver data for Event Service (ES) that has implemented a fine-grained approach for ATLAS event processing. The ESS allows one to asynchronously deliver only the input events required by ES processing, with the aim to decrease data traffic over WAN and improve overall data processing throughput. A prototype of ESS was developed to deliver streaming events to fine-grained ES jobs. Based on it, an intelligent Data Delivery Service (iDDS) is under development to decouple the "cold format" and the processing format of the data, which also opens the opportunity to include the production systems of other HEP experiments. Here we will at first present the ESS model view and its motivations for iDDS system. Then we will also present the iDDS schema, architecture and the applications of iDDS.
This document provides, for those not closely associated with the experimental High Energy Physics (HEP) community, an introduction to data input and output requirements for a variety of data processing tasks. Examples in it are drawn from the art event processing framework, and from experiments and projects using art, most notably the LArSoft and NuTools projects.
In the fall 2016, GeantV went through a thorough community evaluation of the project status and of its strategy for sharing the R&D results with the LHC experiments and with the HEP simulation community in general. Following this discussion, GeantV has engaged onto an ambitious 2-year road-path aiming to deliver a beta version that has most of the final design and several performance features of the final product, partially integrated with some of the experiment’s frameworks. The initial GeantV prototype has been updated to a vector-aware concurrent framework, which is able to deliver high-density floating-point computations for most of the performance-critical components such as propagation in field and physics models. Electromagnetic physics models were adapted for the specific GeantV requirements, aiming for the full demonstration of shower physics performance in the alpha release at the end of 2017. We have revisited and formalized GeantV user interfaces and helper protocols, allowing to: connect to user code, provide recipes to access efficiently MC truth and generate user data in a concurrent environment.
We show how the Geant4 Simulation Toolkit, originally developed for High Energy Physics, has been applied to a wide variety of challenging applications in medical physics. As the authors are mainly responsible for providing assistance to Geant4 users in North America, they draw on examples from the North American experience, but the conclusions can be generalized to the Geant4 medical user community worldwide. Geant4 is already heavily used in all areas of medical physics, from external beam therapy to brachytherapy to interventional nuclear medicine and medical imaging. As the complexity of medical physics studies continues to increase, requiring greater accuracy of modeling, and an increase in 4D capabilities (component motion and time-varying electric and magnetic fields), Geant4 use will only expand. The openness of the HEP community (keeping Geant4 well supported, open and free) is greatly appreciated by the medical and aerospace communities. The democratic nature of Geant4's governance (that decision-making rests with a technical steering board elected by the collaborators) has given outside communities the confidence to invest their energies in Geant4 (shown them that it is worth the time investment to become expert users). Geant4's latest key area of focus, moving to multithreaded operation, is seen as a huge boon to the medical users (where precision simulations often require billions of primary particles). Another recent key area of Geant4, increasing automated systems for unit and end-to-end testing, is also seen as extremely valuable to these non-HEP communities. Innovations from HEP and aerospace will benefit medical applications, and vice versa. Geant4 can expect increasing resources to be provided by the medical physics community, pooling resources to the benefit of all users. (authors)
In this report, the first attempt for an alternative approach for the simulation of the non-abelian group BT has been done. First, we analysed why SNAP and Displacement decomposition is not feasible for this problem with the current technology, and then we explored a new approach for the optimisation of the pulses. In particular, we studied how the expansion of the pulses in Chebyshev Polynomials could affect the optimisation process. Even if the study is not conclusive, we believe that it might be worth continuing to study this approach in the future, in order to be able to efficiently implement quantum circuits on computers.
Monitoring services play a crucial role in the day-to-day operation of distributed computing systems. The ATLAS Experiment at LHC uses the Production and Distributed Analysis workload management system (PanDA WMS), which allows a million computational jobs to run daily at over 170 computing centers of the WLCG and opportunistic resources, utilizing 600k cores simultaneously on average. The BigPanDA monitor is an essential part of the monitoring infrastructure for the ATLAS Experiment that provides a wide range of views, from top-level summaries to a single computational job and its logs. Over the past few years of the PanDA WMS advancement in the ATLAS Experiment, several new components were developed, such as Harvester, iDDS, Data Carousel, and Global Shares. Due to its modular architecture, the BigPanDA monitor naturally grew into a platform where the relevant data from all PanDA WMS components and accompanying services are accumulated and displayed in the form of interactive charts and tables. Moreover the system has been adopted by other experiments beyond HEP. In this paper we describe the evolution of the BigPanDA monitor system, the development of new modules, and the integration process into other experiments.
Many workflows in high-energy-physics (HEP) stand to benefit from recent advances in transformer-based large language models (LLMs). While early applications of LLMs focused on text generation and code completion, modern LLMs now support orchestrated agency: the coordinated execution of complex, multi-step tasks through tool use, structured context, and iterative reasoning. We introduce the HEP Toolkit for Agentic Planning, Orchestration, and Deployment (HEPTAPOD), an orchestration framework designed to bring this emerging paradigm to HEP pipelines. The framework enables LLMs to interface with domain-specific tools, construct and manage simulation workflows, and assist in common utility and data analysis tasks through schema-validated operations and run-card-driven configuration. To demonstrate these capabilities, we consider a representative Beyond the Standard Model (BSM) Monte Carlo validation pipeline that spans model generation, event simulation, and downstream analysis within a unified, reproducible workflow. HEPTAPOD provides a structured and auditable layer between human researchers, LLMs, and computational infrastructure, establishing a foundation for transparent, human-in-the-loop systems.
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AdS/QCD, the correspondence between theories in a dilaton-modified five-dimensional anti-de Sitter space and confining field theories in physical space-time, provides a remarkable semiclassical model for hadron physics. Light-front holography allows hadronic amplitudes in the AdS fifth dimension to be mapped to frame-independent light-front wavefunctions of hadrons in physical space-time. The result is a single-variable light-front Schroedinger equation which determines the eigenspectrum and the light-front wavefunctions of hadrons for general spin and orbital angular momentum. The coordinate z in AdS space is uniquely identified with a Lorentz-invariant coordinate {zeta} which measures the separation of the constituents within a hadron at equal light-front time and determines the off-shell dynamics of the bound state wavefunctions as a function of the invariant mass of the constituents. The hadron eigenstates generally have components with different orbital angular momentum; e.g., the proton eigenstate in AdS/QCD with massless quarks has L = 0 and L = 1 light-front Fock components with equal probability. Higher Fock states with extra quark-anti quark pairs also arise. The soft-wall model also predicts the form of the nonperturbative effective coupling and its {beta}-function. The AdS/QCD model can be systematically improved by using its complete orthonormal solutions to diagonalize the full QCD light-front Hamiltonian or by applying the Lippmann-Schwinger method to systematically include QCD interaction terms. Some novel features of QCD are discussed, including the consequences of confinement for quark and gluon condensates. A method for computing the hadronization of quark and gluon jets at the amplitude level is outlined.
High Energy Physics (HEP) experiments generally employ sophisticated statistical methods to present results in searches of new physics. In the problem of searching for sterile neutrinos, likelihood ratio tests are applied to short-baseline neutrino oscillation experiments to construct confidence intervals for the parameters of interest. The test statistics of the form Δχ2 is often used to form the confidence intervals, however, this approach can lead to statistical inaccuracies due to the small signal rate in the region-of-interest. In this paper, we present a computational model for the computationally expensive Feldman-Cousins corrections to construct a statistically accurate confidence interval for neutrino oscillation analysis. The program performs a grid-based minimization over oscillation parameters and is written in C++. Our algorithms make use of vectorization through Eigen3, yielding a single-core speed-up of 350 compared to the original implementation, and achieve MPI data parallelism by employing DIY. We demonstrate the strong scaling of the application at High-Performance Computing (HPC) sites. We utilize HDF5 along with HighFive to write the results of the calculation to file.