High Energy Physics Community Research Articles

Quantum Computing for High-Energy Physics: State of the Art and Challenges

Quantum computers offer an intriguing path for a paradigmatic change of computing in the natural sciences and beyond, with the potential for achieving a so-called quantum advantage—namely, a significant (in some cases exponential) speedup of numerical simulations. The rapid development of hardware devices with various realizations of qubits enables the execution of small-scale but representative applications on quantum computers. In particular, the high-energy physics community plays a pivotal role in accessing the power of quantum computing, since the field is a driving source for challenging computational problems. This concerns, on the theoretical side, the exploration of models that are very hard or even impossible to address with classical techniques and, on the experimental side, the enormous data challenge of newly emerging experiments, such as the upgrade of the Large Hadron Collider. In this Roadmap paper, led by CERN, DESY, and IBM, we provide the status of high-energy physics quantum computations and give examples of theoretical and experimental target benchmark applications, which can be addressed in the near future. Having in mind hardware with about 100 qubits capable of executing several thousand two-qubit gates, where possible, we also provide resource estimates for the examples given using error-mitigated quantum computing. The ultimate declared goal of this task force is therefore to trigger further research in the high-energy physics community to develop interesting use cases for demonstrations on near-term quantum computers. Published by the American Physical Society 2024

Review Paper- “Detail Evolution of RTE Food”

Biospark-healthcare Private Limited is a Private incorporated on 05 July 2021. It is classified as Non-govt companyand is registered at Registrar of Companies, Mumbai. Its authorized share capital is Rs. 150,000 and its paid up capital is Rs. 150,000. It is inolved in Manufacture of other food products Biospark-healthcare Private Limited's Annual General Meeting (AGM) was last held on N/A and as per records fromMinistry of Corporate Affairs (MCA), its balance sheet was last filed on 31 March 2022. Directors of Biospark-healthcare Private Limited are Jaiprakash Khanchand Vasdani, Neelkumar Rewachand Sujan,Vijay Jeevan Sujan and Prashant Kothari. Biospark-healthcare Private Limited's Corporate Identification Number is (CIN) U24290MH2021PTC363325 and its registration number is 363325.Its Email address is vijay.sujan@jnvgroup.co and its registered address is 4-A, 4TH FLOOR, 898 NOTAN PLAZA TURNER ROAD, BANDRA (WEST) MUMBAI Mumbai City MH 400050 IN. Current status of Biospark-healthcare Private Limited is - Active. The initial project proposal outlined a simple system of using a concept called “networked hypertext” to transmit documents and to communicate among staff in the high-energy physics community. Keywords – SUPPLY, SUPPLY CHAIN, SUPPLY CHAIN MANAGMENT, INDIRECT SUPPLY, TAX TRANSPORT COMPLIANCE, TRANSPORTATION

Review Paper- “E-COMMERCE GROWTH IN INTERNATIONAL MARKET IMPACT ON SUPPLY CHAIN MANAGEMENT”

This research paper provides a comprehensive review of logistic and supply chain models, aiming to enhance the understanding of the intricate frameworks that govern the movement of goods and information within global business networks. The logistics and supply chain management (SCM) landscape has evolved significantly in recent years, driven by technological advancements, globalization, and the increasing complexity of business operations. This paper explores various models employed in logistics and supply chain management, focusing on their theoretical foundations, practical applications, and the impact of emerging trends on their effectiveness. The initial project proposal outlined a simple system of using a concept called “networked hypertext” to transmit documents and to communicate among staff in the high-energy physics community. Keywords – SUPPLY, SUPPLY CHAIN, SUPPLY CHAIN MANAGMENT, INDIRECT SUPPLY, TAX TRANSPORT COMPLIANCE, TRANSPORTATION

Symbolic Regression on FPGAs for Fast Machine Learning Inference

The high-energy physics community is investigating the potential of deploying machine-learning-based solutions on Field-Programmable Gate Arrays (FPGAs) to enhance physics sensitivity while still meeting data processing time constraints. In this contribution, we introduce a novel end-to-end procedure that utilizes a machine learning technique called symbolic regression (SR). It searches the equation space to discover algebraic relations approximating a dataset. We use PySR (a software to uncover these expressions based on an evolutionary algorithm) and extend the functionality of hls4ml (a package for machine learning inference in FPGAs) to support PySR-generated expressions for resource-constrained production environments. Deep learning models often optimize the top metric by pinning the network size because the vast hyperparameter space prevents an extensive search for neural architecture. Conversely, SR selects a set of models on the Pareto front, which allows for optimizing the performance-resource trade-off directly. By embedding symbolic forms, our implementation can dramatically reduce the computational resources needed to perform critical tasks. We validate our method on a physics benchmark: the multiclass classification of jets produced in simulated proton-proton collisions at the CERN Large Hadron Collider. We show that our approach can approximate a 3-layer neural network using an inference model that achieves up to a 13-fold decrease in execution time, down to 5 ns, while still preserving more than 90% approximation accuracy.

Advances in the TCAD modelling of non-irradiated and irradiated Low-Gain Avalanche Diode sensors

The recently developed Low-Gain Avalanche Diode (LGAD) technology has gained growing interest within the high-energy physics (HEP) community, thanks to its capability of internal signal amplification that improves the particle detection. Since the next generation of HEP experiments will require tracking detectors able to efficiently operate in environments where expected fluences will exceed 1 × 1017 1 MeV n eq/cm2, the design of radiation-resistant particle detectors becomes of utmost importance. To this purpose, Technology Computer-Aided Design (TCAD) simulations are a relevant part of the current detector R&D, not only to support the sensor design and optimization, but also for a better understanding and modelling of radiation damage. In this contribution, the recent advances in the TCAD modelling of non-irradiated and irradiated LGAD sensors are presented, whose validation relies on the agreement between the simulated and experimental data — in terms of current-voltage (I-V), capacitance-voltage (C-V), and gain-voltage (G-V) characteristics, coming from devices manufactured by Hamamatsu Photonics (HPK), and accounting for different irradiation levels and temperatures.

Electron scattering and neutrino physics

A thorough understanding of neutrino–nucleus scattering physics is crucial for the successful execution of the entire US neutrino physics program. Neutrino–nucleus interaction constitutes one of the biggest systematic uncertainties in neutrino experiments—both at intermediate energies affecting long-baseline deep underground neutrino experiment, as well as at low energies affecting coherent scattering neutrino program—and could well be the difference between achieving or missing discovery level precision. To this end, electron–nucleus scattering experiments provide vital information to test, assess and validate different nuclear models and event generators intended to test, assess and validate different nuclear models and event generators intended to be used in neutrino experiments. Similarly, for the low-energy neutrino program revolving around the coherent elastic neutrino–nucleus scattering (CEvNS) physics at stopped pion sources, such as at ORNL, the main source of uncertainty in the evaluation of the CEvNS cross section is driven by the underlying nuclear structure, embedded in the weak form factor, of the target nucleus. To this end, parity-violating electron scattering (PVES) experiments, utilizing polarized electron beams, provide vital model-independent information in determining weak form factors. This information is vital in achieving a percent level precision needed to disentangle new physics signals from the standard model expected CEvNS rate. In this white paper, we highlight connections between electron- and neutrino–nucleus scattering physics at energies ranging from 10 s of MeV to a few GeV, review the status of ongoing and planned electron scattering experiments, identify gaps, and lay out a path forward that benefits the neutrino community. We also highlight the systemic challenges with respect to the divide between the nuclear and high-energy physics communities and funding that presents additional hurdles in mobilizing these connections to the benefit of neutrino programs.

Potential of the Julia Programming Language for High Energy Physics Computing

Research in high energy physics (HEP) requires huge amounts of computing and storage, putting strong constraints on the code speed and resource usage. To meet these requirements, a compiled high-performance language is typically used; while for physicists, who focus on the application when developing the code, better research productivity pleads for a high-level programming language. A popular approach consists of combining Python, used for the high-level interface, and C++, used for the computing intensive part of the code. A more convenient and efficient approach would be to use a language that provides both high-level programming and high-performance. The Julia programming language, developed at MIT especially to allow the use of a single language in research activities, has followed this path. In this paper the applicability of using the Julia language for HEP research is explored, covering the different aspects that are important for HEP code development: runtime performance, handling of large projects, interface with legacy code, distributed computing, training, and ease of programming. The study shows that the HEP community would benefit from a large scale adoption of this programming language. The HEP-specific foundation libraries that would need to be consolidated are identified.

Status of the High Field Cable Test Facility at Fermilab

Fermi National Accelerator Laboratory (FNAL) and Lawrence Berkeley National Laboratory (LBNL) are building a new High Field Vertical Magnet Test Facility (HFVMTF) for testing superconducting cables in high magnetic field. The background magnetic field of 15 T in the HFVMTF will be produced by a magnet provided by LBNL. The HFVMTF is jointly funded by the US DOE Offices of Science, High Energy Physics (HEP), and Fusion Energy Sciences (FES), and will serve as a superconducting cable test facility in high magnetic fields and a wide range of temperatures for HEP and FES communities. This facility will also be used to test high-field superconducting magnet models and demonstrators, including hybrid magnets, produced by the US Magnet Development Program (MDP). The paper describes the status of the facility, including construction, cryostat designs, top and lambda plates, and systems for powering, and quench protection and monitoring.

Making digital objects FAIR in high energy physics: An implementation for Universal FeynRules Output (UFO) models

Research in the data-intensive discipline of high energy physics (HEP) often relies on domain-specific digital contents. Reproducibility of research relies on proper preservation of these digital objects. This paper reflects on the interpretation of principles of Findability, Accessibility, Interoperability, and Reusability (FAIR) in such context and demonstrates its implementation by describing the development of an end-to-end support infrastructure for preserving and accessing Universal FeynRules Output (UFO) models guided by the FAIR principles. UFO models are custom-made python libraries used by the HEP community for Monte Carlo simulation of collider physics events. Our framework provides simple but robust tools to preserve and access the UFO models and corresponding metadata in accordance with the FAIR principles.

Codebase release 2.0 for UFOManager

Research in the data-intensive discipline of high energy physics (HEP) often relies on domain-specific digital contents. Reproducibility of research relies on proper preservation of these digital objects. This paper reflects on the interpretation of principles of Findability, Accessibility, Interoperability, and Reusability (FAIR) in such context and demonstrates its implementation by describing the development of an end-to-end support infrastructure for preserving and accessing Universal FeynRules Output (UFO) models guided by the FAIR principles. UFO models are custom-made python libraries used by the HEP community for Monte Carlo simulation of collider physics events. Our framework provides simple but robust tools to preserve and access the UFO models and corresponding metadata in accordance with the FAIR principles.

Domain-adversarial graph neural networks for Λ hyperon identification with CLAS12

Machine learning methods and in particular Graph Neural Networks (GNNs) have revolutionized many tasks within the high energy physics community. Particularly in the realm of jet tagging, GNNs and domain adaptation have been especially successful. However, applications with lower energy events have not received as much attention. We report on the novel use of GNNs and a domain-adversarial training method to identify Λ hyperon events with the CLAS12 experiment at Jefferson Lab. The GNN method we have developed increases the purity of the Λ yield by a factor of 1.95 and by 1.82 using the domain-adversarial training. This work also provides a good benchmark for developing event tagging machine learning methods for the Λ and other channels at CLAS12 and other experiments, such as the planned Electron Ion Collider.

High efficiency, low cost, RF sources for accelerators and colliders

Accelerators for High Energy Physics (HEP) are large users of energy, much of it in the form of radiofrequency (RF) power to accelerate particles to very high energies. Proposed HEP projects will require even larger amounts of RF energy. Increasing concerns of the cost and availability of energy will require the HEP community to use energy as efficeintly as possible. Successful transfer of HEP technology to the public and private sectors will be most effective if it is highly efficient. Historically, the HEP community has utilized available RF power sources, mainly in the form of vacuum tube technology, much of which was developed during the cold war or is otherwized used in the private sector. The private sector is moving to solid-state RF sources which do not exibit the electrical efficiency that is needed for future HEP projects. Here, we summarize the state of the development of a number of RF sources that promise efficeincies of 80% and above. We also outline future efforts that are needed to fully realize the potential of these sources.

On the feasibility of future colliders: report of the Snowmass'21 Implementation Task Force

Colliders are essential research tools for particle physics. Numerous future collider proposal were discussed in the course of the US high energy physics community strategic planning exercise Snowmass'21. The Implementation Task Force (ITF) has been established to evaluate the proposed future accelerator projects for performance, technology readiness, schedule, cost, and environmental impact. Corresponding metrics has been developed for uniform comparison of the proposals ranging from Higgs/EW factories to multi-TeV lepton, hadron and ep collider facilities, based on traditional and advanced acceleration technologies. This article describes the metrics and approaches, and presents evaluations of future colliders performed by the ITF.

Sub-10 ps time tagging of electromagnetic showers with scintillating glasses and SiPMs

The high energy physics community has recently identified an e+e− Higgs factory as one of the next-generation collider experiments, following the completion of the High Luminosity LHC program at CERN. The moderate radiation levels expected at such colliders compared to hadron colliders, enable the use of less radiation tolerant but cheaper technologies for the construction of the particle detectors. This opportunity has triggered a renewed interest in the development of scintillating glasses for the instrumentation of large detector volumes such as homogeneous calorimeters. While the performance of such scintillators remains typically inferior in terms of light yield and radiation tolerance compared to that of many scintillating crystals, substantial progress has been made over the recent years. In this paper we discuss the time resolution of cerium-doped Alkali Free Fluorophosphate scintillating glasses, read-out with silicon photo-multipliers in detecting single charged tracks and at different positions along the longitudinal development of an electromagnetic shower, using respectively 150 GeV pions and 100 GeV electron beams at the CERN SPS H2 beam line. A single sensor time resolution of 14.4 ps and 5–7 ps was measured respectively in the two cases. With such a performance the present technology has the potential to address an emerging requirement of future detectors at collider experiments: measuring the time-of-flight of single charged particles as well as that of neutral particles showering inside the calorimeter and the time development of showers.

Data and Analysis Preservation in the PHENIX Experiment at RHIC

The PHENIX experiment (the Pioneering High Energy Nuclear Interaction eXperiment) is the largest of the four experiments that have operated at the Relativistic Heavy Ion Collider (RHIC), taking data in 2000-2016. PHENIX has made fundamental contributions to the discovery and study of the Quark-Gluon Plasma, advancement of spin physics and other areas. Currently, the PHENIX Collaboration is analyzing large data samples previously collected, while facing challenges in the area of Data and Analysis Preservation. We describe the strategy and practices employed by the PHENIX Collaboration to meet these challenges by leveraging state-of-the-art platforms and tools created and maintained by the High Energy and Nuclear Physics communities, including Zenodo, HEPData, OpenData, REANA and others.

Excited muon production in muon colliders via contact interaction

In recent years, with the enlightenment of some issues encountered in muon colliders, muon colliders have become more feasible for the high-energy physics community. For this reason, we studied the single production of an excited muon in muon colliders via contact interactions. In addition, we assumed that the excited muon decayed into a photon and muon through gauge interactions. Then, signal and background analyses were performed in muon–antimuon collider options with center-of-mass energies of 6, 14, and 100 TeV. The attainable mass and compositeness scale limits were calculated for the excited muon in these collider options. Based on the calculations, it was concluded that muon–antimuon colliders would be a perfect collider option for excited muon investigations.

Particle physics facing a pandemic

Background: Ordinary life as we knew it changed in March of 2020 due to the global COVID-19 pandemic. While springtime in general was well awaited and regarded as a synonym for rejuvenation, March of 2020 on the other hand brought lock-down, curfews, home working and digital education to the lives of many. The particle physics community was not an exception: research institutes and universities introduced remote working and digital lecturing and all workshops, conferences and summer schools were cancelled, got postponed or took place online. Methods: Using publicly available data from the INSPIRE and arXiv databases we investigate the effects of this dramatic change of life to the publishing trends of the high-energy physics community with an emphasis on particle phenomenology, theory and CERN’s two major LHC experiments, ATLAS and CMS. To get insights, we gather information about publishing trends in the last 20 years, ending by December 2021, and analyse it in detail. Results: Our analysis revealed that the publishing trend in particle physics was only been affected in a minor way. Conclusions: Publication data show that difficult times were successfully overcome and that the community even increased scientific output.

Hog (HDL on Git): An easy system to handle HDL on a git-based repository

Coordinating firmware development among many international collaborators is becoming a very widespread problem in high-energy physics. Guaranteeing firmware synthesis reproducibility and assuring traceability of binary files is paramount.We devised Hog - HDL on git (cern.ch/hog), a set of Tcl and Shell scripts that tackles these issues and is deeply integrated with HDL IDEs, such as Xilinx Vivado Design Suite and ISE PlanAhead or Intel Quartus Prime, and all major simulation tools, like Siemens ModelSim or Aldec Riviera Pro.Git is a very powerful tool and has been chosen as standard by several research institutions, including CERN. Hog perfectly integrates with git to assure an absolute control of HDL source files, constraint files, IDE and simulation settings. It guarantees traceability by automatically embedding the git commit SHA and a numeric version into the binary file, also automatically renamed.Hog does not rely on any external tool apart from the HDL IDE and git, so it is extremely compatible and does not require any installation. Developers can get quickly up to speed: clone the repository, run the Hog script, work normally with the IDE.The learning curve to use Hog for the users is minimal. Once the HDL project is created, developers can work on it either using the IDE graphical interface, or with the provided Shell scripts to run the workflow.Hog works on Windows and Linux, supports IPbus, Sigasi and provides pre-made YAML files to set up a working Continuous Integration on GitLab (Hog-CI) with no additional effort, which runs the HDL implementation for the desired projects. Other features of Hog-CI are the automatic creation of tags and GitLab releases with timing and utilisation reports.Currently, Hog is successfully used by several firmware projects within the High-Energy Physics community, e.g. in the ATLAS and CMS Phase-II upgrades.

Analog IP blocks in 28 nm CMOS for the high energy physics community: SLVS transmitter and receiver

A Scalable Low Voltage Signaling (SLVS) transmitter and receiver have been developed as IP blocks in a 28 nm standard CMOS technology for the future upgrades for the high luminosity LHC. At the target data rate of 1.28 Gbps, the transmitter consumes 6 mW and the receiver consumes 2 mW. The transmitter’s output is powered with 1.2 V to provide compatibility with previous designs, while the core logic can be powered with 0.8 V to reduce power consumption. This work summarizes the design approach at the schematic and layout level. Practical aspects of the novel technology for the design of ASICs in High Energy Physics will be discussed along with characterization results. Other IP blocks are being designed (ADC, DAC, PLL) and they will be presented.

ASIC survival in the radiation environment of the LHC experiments: 30 years of struggle and still tantalizing

The radiation environment at the CERN Large Hadron Collider (LHC) poses an unprecedented challenge to the reliable functionality of the electronics components composing the detector systems. Starting from the beginning of the 90s, a large effort has been dedicated at CERN and in the collaborating institutes to develop, produce and deploy Application-Specific Integrated Circuits (ASICs) tolerant to all types of radiation effects: Total Ionizing Dose (TID), Single Event Effects (SEE) and Displacement Damage (DD). This article briefly describes the approaches and methodologies that the High Energy Physics community developed or adopted for that purpose over the last 30 years.