Integrating High-Performance Computing with Electron Microscopy for Scientific Insights
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Ghosh, Ayana↗
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Strategies for simulating the time evolution of Hamiltonian lattice field theories
Simulating the time evolution of quantum field theories given some Hamiltonian H requires developing algorithms for implementing the unitary operator e -iHt . A variety of techniques exist that accomplish this task, with the most common technique used so far being Trotterization, which is a special case of the application of a product formula. However, other techniques exist that promise better asymptotic scaling in certain parameters of the theory being simulated, the most efficient of which are based on the concept of block encoding. In this work we study the performance of such algorithms in simulating lattice field theories. We derive and compare the asymptotic gate complexities of several commonly used simulation techniques in application to Hamiltonian lattice field theories. Using the scalar $\hat{φ}$ 4 theory as a test, we also perform numerical studies and compare the gate costs required by product formulas and signal-processing-based techniques to simulate time evolution. For the latter, we use the linear combination of unitaries (LCU) construction augmented with the quantum Fourier transform circuit to switch between the field and momentum eigenbases, which leads to immediate order-of-magnitude improvement in the cost of preparing the block encoding. Further, this paper also includes a pedagogical review of the techniques used, in particular product formulas, LCU, qubitization, quantum signal processing, as well as the technique for simulating geometrically-local Hamiltonians developed by Haah, Hastings, Kothari, and Low.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Method to simultaneously facilitate all jet physics tasks
Machine learning has become an essential tool in jet physics. Due to their complex, high-dimensional nature, jets can be explored holistically by neural networks in ways that are not possible manually. However, innovations in all areas of jet physics are proceeding in parallel. We show that specially constructed machine learning models trained for a specific jet classification task can improve the accuracy, precision, or speed of all other jet physics tasks. This is demonstrated by training on a particular multiclass generation and classification task and then using the learned representation for different generation and classification tasks, for datasets with a different (full) detector simulation, for jets from a different collision system ($pp$ versus $ep$), for generative models, for likelihood ratio estimation, and for anomaly detection. We consider our omnilearn approach thus as a jet-physics foundation model. It is made publicly available for use in any area where state-of-the-art precision is required for analyses involving jets and their substructure.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
State of the Art of Molecular Visualization in Immersive Virtual Environments
Abstract Visualization plays a crucial role in molecular and structural biology. It has been successfully applied to a variety of tasks, including structural analysis and interactive drug design. While some of the challenges in this area can be overcome with more advanced visualization and interaction techniques, others are challenging primarily due to the limitations of the hardware devices used to interact with the visualized content. Consequently, visualization researchers are increasingly trying to take advantage of new technologies to facilitate the work of domain scientists. Some typical problems associated with classic 2D interfaces, such as regular desktop computers, are a lack of natural spatial understanding and interaction, and a limited field of view. These problems could be solved by immersive virtual environments and corresponding hardware, such as virtual reality head‐mounted displays. Thus, researchers are investigating the potential of immersive virtual environments in the field of molecular visualization. There is already a body of work ranging from educational approaches to protein visualization to applications for collaborative drug design. This review focuses on molecular visualization in immersive virtual environments as a whole, aiming to cover this area comprehensively. We divide the existing papers into different groups based on their application areas, and types of tasks performed. Furthermore, we also include a list of available software tools. We conclude the report with a discussion of potential future research on molecular visualization in immersive environments.
97 MATHEMATICS AND COMPUTING↗
Multiscale Neural Networks for Approximating Green’s Functions
Neural networks (NNs) have been widely used to solve partial differential equations (PDEs) in the applications of physics, biology, and engineering. One effective approach for solving PDEs with a fixed differential operator is learning Green’s functions. However, Green’s functions are notoriously difficult to learn due to their poor regularity, which typically requires larger NNs and longer training times. In this work, we address these challenges by leveraging multiscale NNs to learn Green’s functions. Through theoretical analysis using multiscale Barron space methods and experimental validation, we show that the multiscale approach significantly reduces the necessary NN size and accelerates training.
97 MATHEMATICS AND COMPUTING↗
ALDX Mission Assurance Plan and Quality Plan
This document describes how ALDX assures successful mission delivery, via nurturing essential scientific and computational capabilities in our staff, negotiating and delivering upon milestones, and ensuring a safe, secure, and productive work environment. The document also describes how we manage and minimize different types of risks, ranging from risks associated with completing essential mission tasks, to risks in safety and security in our organization, as discussed in the Risk Register/Heat Map. It also describes how ALDX assures Quality in its work.
99 GENERAL AND MISCELLANEOUS↗
Summary of Responses to the Request for Information (RFI) on Partnerships for Transformational Artificial Intelligence Models
The Department of Energy (DOE) issued a Request for Information (RFI) in December 2025 inviting public comments regarding partnerships for transformational Artificial Intelligence (AI) models for the Genesis Mission Consortium, a public-private partnership platform. This RFI solicited feedback from industry, nonprofit organizations, universities, independent research organizations and other stakeholders. Specifically, the RFI asked three questions on (1) mobilizing DOE National Laboratories to curate the scientific data in a responsible and privacy-preserving manner, (2) the extent to which existing general-purpose AI models can be leveraged and which scientific disciplines are priorities for such model development, and (3) mechanisms by which these AI models can be provided to scientific communities. This document summarizes the input from 194 unique nonproprietary responses from businesses, universities, nonprofit organizations, research institutes and laboratories as well as a variety of other contributors, including individual contributions.
97 MATHEMATICS AND COMPUTING↗
Training and onboarding initiatives in high energy physics experiments
In this article we document the current analysis software training and onboarding activities in several High Energy Physics (HEP) experiments: ATLAS, CMS, LHCb, Belle II and DUNE. Fast and efficient onboarding of new collaboration members is increasingly important for HEP experiments. With rapidly increasing data volumes and larger collaborations the analyses and consequently, the related software, become ever more complex. This necessitates structured onboarding and training. Recognizing this, a meeting series was held by the HEP Software Foundation (HSF) in 2022 for experiments to showcase their initiatives. Here we document and analyze these in an attempt to determine a set of key considerations for future HEP experiments.
analysis software↗
Recorder trace files of 91 built-in tests from three widely-used I/O libraries (Dec 24, 2024)
This dataset contains the Recorder trace files of 91 built-in tests from three widely-used I/O libraries. It was utilized in our IPDPS'25 paper, "VerifyIO: Verifying Adherence to Parallel I/O Consistency Semantics". The dataset can be used to reproduce the results presented in the paper and to conduct additional analyses
Wang, Chen [Lawrence Livermore National Laboratory↗
DMTN-221: Periodicity Analysis in Alert Production
The baselined timeseries features to be computed in Alert Production include a Lomb-Scargle periodogram ran on two classes of variable systems: RR Lyrae and Eclipsing Binaries. Based on a simulated LSST-like cadence light curves taken from the Extended LSST Astronomical Time-series Classification Challenge (ELAsTiCC) we perform an end-to-end test to characterize the periodicity recovery on the Alert Production multi-band light curves. In both variable classes, we found that a single-band Lomb-Scargle implementation yields to a low fraction of recovered periods, with a significant preference on the simple periodic phenomena such as RR Lyrae. We also investigated the results from a multi-band Lomb-Scargle and found an increased fraction of recovered periodicities above 15% for the eclipsing binaries, and over 80$\%$ for the RR Lyrae stars. Our findings suggest that a multi-band Lomb-Scargle should be implemented for searching periodic phenomena through AP. We also asses the computational and scientific performance of several configurations on simulated alert data and find that our current configuration scales linearly with the number of detections while assuming an heuristic frequency grid.
79 ASTRONOMY AND ASTROPHYSICS↗
New Scientific Data Systems /SDS/ digital computer programs
Digital computer programs including external display testing, symbolic paper tape editing, and real time star tracking
DIGITAL COMPUTER↗
CDC to CRAY FORTRAN conversion manual
Documentation describing software differences between two general purpose computers for scientific applications is presented. Descriptions of the use of the FORTRAN and FORTRAN 77 high level programming language on a CDC 7600 under SCOPE and a CRAY XMP under COS are offered. Itemized differences of the FORTRAN language sets of the two machines are also included. The material is accompanied by numerous examples of preferred programming techniques for the two machines.
Mcgary, C.↗
Faraday Cage Protects Against Lightning
Faraday cage protects electronic and electronically actuated equipment from lightning. Follows standard lightning-protection principles. Whether lightning strikes cage or cables running to equipment, current canceled or minimized in equipment and discharged into ground. Applicable to protection of scientific instruments, computers, radio transmitters and receivers, and power-switching equipment.
Jafferis, W.↗
WetNet: Using SSM/I data interactively for global distribution of tropical rainfall and precipitable water
The research objectives were the following: (1) to use SSM/I to categorize, measure, and parameterize effects of rainfall systems around the globe, especially mesoscale convective systems; (2) to use SSM/I to monitor key components of the global hydrologic cycle, including tropical rainfall and precipitable water, and links to increasing sea surface temperatures; and (3) to assist in the development of efficient methods of exchange of massive satellite data bases and of analysis techniques, especially their use at a university. Numerous tasks have been initiated. First and foremost has been the integration and startup of the WetNet computer system into the TAMU computer network. Scientific activity was infeasible before completion of this activity. Final hardware delivery was not completed until October 1991, after which followed a period of identification and solution of several hardware and software and software problems. Accomplishments representing approximately four months work with the WetNEt system are presented.
Zipser, Edward J.↗
Feature isolation and quantification of evolving datasets
Identifying and isolating features is an important part of visualization and a crucial step for the analysis and understanding of large time-dependent data sets (either from observation or simulation). In this proposal, we address these concerns, namely the investigation and implementation of basic 2D and 3D feature based methods to enhance current visualization techniques and provide the building blocks for automatic feature recognition, tracking, and correlation. These methods incorporate ideas from scientific visualization, computer vision, image processing, and mathematical morphology. Our focus is in the area of fluid dynamics, and we show the applicability of these methods to the quantification and tracking of three-dimensional vortex and turbulence bursts.
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The Automatic Parallelisation of Scientific Application Codes Using a Computer Aided Parallelisation Toolkit
The shared-memory programming model is a very effective way to achieve parallelism on shared memory parallel computers. Historically, the lack of a programming standard for using directives and the rather limited performance due to scalability have affected the take-up of this programming model approach. Significant progress has been made in hardware and software technologies, as a result the performance of parallel programs with compiler directives has also made improvements. The introduction of an industrial standard for shared-memory programming with directives, OpenMP, has also addressed the issue of portability. In this study, we have extended the computer aided parallelization toolkit (developed at the University of Greenwich), to automatically generate OpenMP based parallel programs with nominal user assistance. We outline the way in which loop types are categorized and how efficient OpenMP directives can be defined and placed using the in-depth interprocedural analysis that is carried out by the toolkit. We also discuss the application of the toolkit on the NAS Parallel Benchmarks and a number of real-world application codes. This work not only demonstrates the great potential of using the toolkit to quickly parallelize serial programs but also the good performance achievable on up to 300 processors for hybrid message passing and directive-based parallelizations.
Ierotheou, C.↗
JSD: Parallel Job Accounting on the IBM SP2
The IBM SP2 is one of the most promising parallel computers for scientific supercomputing - it is fast and usually reliable. One of its biggest problems is a lack of robust and comprehensive system software. Among other things, this software allows a collection of Unix processes to be treated as a single parallel application. It does not, however, provide accounting for parallel jobs other than what is provided by AIX for the individual process components. Without parallel job accounting, it is not possible to monitor system use, measure the effectiveness of system administration strategies, or identify system bottlenecks. To address this problem, we have written jsd, a daemon that collects accounting data for parallel jobs. jsd records information in a format that is easily machine- and human-readable, allowing us to extract the most important accounting information with very little effort. jsd also notifies system administrators in certain cases of system failure.
Saphir, William↗
Easy and Accessible Imaging Software
DATASTAR, Inc., of Picayune, Mississippi, has taken NASA s award-winning Earth Resources Laboratory Applications Software (ELAS) program and evolved it into a user-friendly desktop application and Internet service to perform processing, analysis, and manipulation of remotely sensed imagery data. NASA s Stennis Space Center developed ELAS in the early 1980s to process satellite and airborne sensor imagery data of the Earth s surface into readable and accessible information. Since then, ELAS information has been applied worldwide to determine soil content, rainfall levels, and numerous other variances of topographical information. However, end-users customarily had to depend on scientific or computer experts to provide the results, because the imaging processing system was intricate and labor intensive.
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