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Caterina Doglioni (The University of Manchester (GB))25/05/2026, 13:45Track 8 - Analysis infrastructure, outreach and educationOral Presentation
The International Committee for Future Accelerators (ICFA) has mandated a panel to address various aspects of the data lifecycle with a focus on open science and FAIR practices - FAIR standing for Findability, Accessibility, Interoperability and Reusability of digital assets. A key indicator of success in this context is the long-term usability of research data by members of experimental...
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Hugo Gonzalez Labrador (CERN)25/05/2026, 14:03Track 8 - Analysis infrastructure, outreach and educationOral Presentation
The open-sharing and re-use of scientific data is ever more important, either to meet the demands of transparency and reproducibility, or to maximize the scientific return of large and small experiments. The FAIR principles (Findable, Accessible, Interoperable, Re-usable) require efficient data publication, discovery, and long-term preservation that often means costly duplication of data...
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Pablo Saiz (CERN)25/05/2026, 14:21Track 8 - Analysis infrastructure, outreach and educationOral Presentation
The CERN Open Data portal provides open access to high-energy physics data collected by CERN experiments for research, education, and outreach. At present, more than 5 PB of data are accessible through it. To ensure the long-term preservation and sustainable management of large datasets, a cold storage system has been introduced. Cold storage enables the archiving of data that is rarely...
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Giovanni Guerrieri (CERN)25/05/2026, 14:39Track 8 - Analysis infrastructure, outreach and educationOral Presentation
The ATLAS Collaboration has for the first time released a large volume of event generator output in HepMC format for the benefit of the research community, allowing theorists and other experimentalists to profit from the efforts and resources of the collaboration. This release complements the existing proton and heavy ion collision data and MC simulation that were released for research use in...
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Piet Nogga (University of Bonn (DE))25/05/2026, 14:57Track 8 - Analysis infrastructure, outreach and educationOral Presentation
The LHCb collaboration is very excited to announce the official public release of the LHCb Ntupling Service: an application for on-demand production and publishing of custom LHCb open data, providing users access to both Run 1, and for the first time, Run 2 pp data collected by the LHCb experiment, amounting to roughly 7 fbโ1. A key feature of this implementation is that no knowledge of the...
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Eric Lancon (Brookhaven National Laboratory (US))25/05/2026, 16:15Track 8 - Analysis infrastructure, outreach and educationOral Presentation
The RHIC experiments at Brookhaven National Laboratory have developed a comprehensive Data and Analysis Preservation (DAP) plan, covering PHENIX, STAR, and sPHENIX. This multi-faceted effort addresses the critical challenge of ensuring long-term accessibility of large volumes of nuclear physics data and reproducibility of analyses developed over 25 years of the RHIC program as the community...
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Dr Mindaugas Sarpis (Vilnius University (LT))25/05/2026, 16:33Track 8 - Analysis infrastructure, outreach and educationOral Presentation
Reproducibility has become a cornerstone of modern particle physics analysis, ensuring that scientific results can be validated, extended, and reinterpreted by the broader community. Building on previous work on analysis modularization and workflow management, this contribution presents practical experiences in achieving full reproducibility for physics analyses at the LHCb experiment. We...
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Mingrui Zhao (Peking University (CN))25/05/2026, 16:51Track 8 - Analysis infrastructure, outreach and educationOral Presentation
Reproducibility and transparency are increasingly critical in high-energy physics, where analyses rely on complex, evolving workflows and heterogeneous software environments. While existing initiatives such as the CERN Analysis Preservation portal and REANA provide essential infrastructure, the day-to-day management and long-term maintainability of individual analyses remain fragmented and...
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Tommaso Diotalevi (Universita e INFN, Bologna (IT))25/05/2026, 17:09Track 8 - Analysis infrastructure, outreach and educationOral Presentation
We present the development of a Virtual Research Environment (VRE) for the Einstein Telescope (ET) project, implemented within the Bologna research unit to support collaborative, high-performance, and reproducible research across the ET community. The Einstein Telescope is a next-generation underground gravitational-wave observatory designed to explore the Universe throughout its cosmic...
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Qingbao Hu (IHEP)25/05/2026, 17:27Track 8 - Analysis infrastructure, outreach and educationOral Presentation
The High Energy Photon Source (HEPS), located in Beijing, is an advanced public research facility designed to support multidisciplinary scientific innovation and high-technology development. HEPS is scheduled to complete construction and enter operation in 2026. It will deliver synchrotron radiation with high energy, high brilliance, and high coherence, achieving spatial, temporal, and energy...
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Dr Marcus Ebert (University of Victoria)25/05/2026, 17:45Track 8 - Analysis infrastructure, outreach and educationOral Presentation
BaBar stopped data taking in 2008, but its data is still analyzed by the collaboration. In 2021 a new computing system outside of the SLAC National Accelerator Laboratory was developed and major changes were needed to keep the ability to analyze the data by the collaboration, while the user facing front ends all needed to stay the same. While the new computing system has worked well since...
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Hannes Jakob Hansen, Paulo Guilherme Pinheiro Pereira (Universidade de Sao Paulo (USP) (BR))26/05/2026, 13:45Track 8 - Analysis infrastructure, outreach and educationOral Presentation
Machine learning challenges have proven to be powerful tools for collaboration, benchmarking and algorithmic innovation in scientific communities. Global platforms such as Kaggle enable researchers to publish datasets, submit solutions and compare performance through structured competitions. However, they assume that participants can use public datasets and external computing resources, which...
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Francesca Lizzi26/05/2026, 14:03Track 8 - Analysis infrastructure, outreach and educationOral Presentation
We summarize five years of experience organizing educational Hackathons within the Italian research landscape of Artificial Intelligence (AI) and High Energy Physics (HEP). These events were part of the INFN AI and ML projects, which aimed to provision GPU and other hardware accelerators via an interactive JupyterLab-based platform providing an easy and highly customizable development...
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Liv Helen Vage (Princeton University (US))26/05/2026, 14:21Track 8 - Analysis infrastructure, outreach and educationOral Presentation
The rapid growth of machine learning has left an overwhelming abundance of teaching resources in its wake that often makes it hard for students to know where to start, how to progress, or what sources to trust. Simultaneously, LLM-based coding assistants enable students to produce working models almost immediately โ often before they understand the underlying principles or common pitfalls....
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Andrew Malone Melo (Vanderbilt University (US))26/05/2026, 14:39Track 8 - Analysis infrastructure, outreach and educationOral Presentation
MLTF (Machine Learning Training Facility) is hardware and software deployed at Vanderbilt University with a focus on portability, reproducibility and ease of exploiting hardware features like RDMA. The software integrates MLflow as an end-to-end ML solution for its capabilities as a user-friendly job submission interface; as a custom-built tracking server for model and run details, arbitrary...
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Jay Ajitbhai Sandesara (University of Wisconsin Madison (US))26/05/2026, 14:57Track 8 - Analysis infrastructure, outreach and educationOral Presentation
The development of Neural Simulation-Based Inference (NSBI) algorithm requires training a large ensemble of neural networks, on the order of one thousand, which makes a serial single-node approach impractical. To address this, we are developing a scalable high-throughput training workflow built around Snakemake[1] and deployed on an HTCondor-based GPU facility. Each neural network training...
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Giovanni Guerrieri (CERN)26/05/2026, 16:15Track 8 - Analysis infrastructure, outreach and educationOral Presentation
CERN IT started providing the capability of an Analysis Facility (AF) in late 2023, initially as a pilot. The AF supports columnar workloads through RDataFrame and Coffea within SWAN, CERNโs web-based analysis environment. Dask provides the computing backend, managing concurrent resources from the CERN batch farm.
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Since then, the AF has evolved beyond the pilot phase. The latest developments... -
Oksana Shadura (University of Nebraska Lincoln (US))26/05/2026, 16:33Track 8 - Analysis infrastructure, outreach and educationOral Presentation
As part of the IRIS-HEP software institute effort and U.S. CMS activities, the Coffea-Casa analysis facility team has executed an Integration Challenge. One goal of this challenge was to demonstrate a full CMS analysis running on the facility and to integrate the IRIS-HEP software stack into a production environment. We describe the solutions deployed at the facility to support and execute the...
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Norbert Neumeister (Purdue University (US))26/05/2026, 16:51Track 8 - Analysis infrastructure, outreach and educationOral Presentation
The Purdue Analysis Facility (Purdue AF) is an interactive, Kubernetes-based computational platform that provides CMS researchers with a comprehensive set of tools and services for end-to-end development and execution of physics analyses. It serves both as a primary development environment for ongoing CMS Run 3 analyses and as a sandbox for testing novel software and data infrastructure...
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88. Offloading CMS detector performance analysis with RNTuple and RDataFrame on an Analysis FacilityCMS Collaboration26/05/2026, 17:09Track 8 - Analysis infrastructure, outreach and educationOral Presentation
The upcoming High-Luminosity phase of the LHC will significantly increase the computational demands of CMS detector performance studies, particularly for workflows that process multi-year datasets and explore high pile-up conditions. In this context, modern data formats and scalable analysis paradigms are essential. This contribution presents an upgrade of a representative CMS detector...
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Benjamin Galewsky (Univ. Illinois at Urbana Champaign (US))26/05/2026, 17:27Track 8 - Analysis infrastructure, outreach and educationOral Presentation
ServiceX is an experiment-agnostic service that extracts columnar data from HEP datasets at scale. Its Python SDK enables researchers to efficiently access complex experimental data by implementing best practices for large-scale dataset processing. Users submit requests using high-level query languages, which generate code that executes within experiment-approved container images, with...
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James Connaughton (University of Warwick (GB))26/05/2026, 17:45Track 8 - Analysis infrastructure, outreach and educationOral Presentation
Modern HEP analysis workflows are becoming increasingly complex and challanging. For LHCb, with its expanded Run 3 data volumes and growing analysis user base, reducing these barriers has become essential for efficient physics output. More recently, LHCb has moved to a declarative system for allowing analysts to filter datasets on WLCG resources for further analysis, known as "Analysis...
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Richa Sharma (University of Puerto Rico (US))28/05/2026, 13:45Track 8 - Analysis infrastructure, outreach and educationOral Presentation
The IRIS-HEP training program and the HEP Software Foundation (HSF), collaborate and co-organize software training events for the high-energy physics community. These activities include hands-on workshops and schools that focus on modern software, computing, and analysis tools. The program addresses the need for both general computational skills and domain-specific knowledge required to...
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Kenneth Rioja (CERN)28/05/2026, 14:03Track 8 - Analysis infrastructure, outreach and educationOral Presentation
The HEP Training platform is a new online registry designed to facilitate the discovery and dissemination of HEP-related training materials and events across high energy physics experiments, labs and universities. Students, researchers, and educators can have access to a list of curated resources โ such as tutorials, guidelines, workshops and training events. These resources are links...
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Danilo Piparo (CERN)28/05/2026, 14:21Track 8 - Analysis infrastructure, outreach and educationOral Presentation
Since 2024, the ROOT team has started a modernisation campaign of the ROOT software trainings as well as of dedicated ROOT tutorials available online on our website. Collectively, we have trained more than 700 people, including newcomers and experienced users wanting to dive into the newest features. We taught in person at CERN and at the Users Workshop in Valencia, and online during the...
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Alexandr Prozorov28/05/2026, 14:39Track 8 - Analysis infrastructure, outreach and educationOral Presentation
The ePIC experiment at the future Electron-Ion Collider relies on a rapidly evolving software ecosystem for simulation, reconstruction, physics analysis and detector support. As the collaboration grows, enabling users to efficiently discover, learn, and develop software tools has become increasingly important. The ePIC User Learning working group addresses this challenge by developing training...
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Fengping Hu (University of Chicago (US))28/05/2026, 14:57Track 8 - Analysis infrastructure, outreach and educationOral Presentation
We present the development and user experience of a hosted BinderHub service that delivers a scalable, uniform, and reproducible computing environment for training sessions and workshops. The IRIS-HEP Scalable Systems Laboratory operates an enhanced, Kubernetes-based BinderHub platform for HEP training and analysis, extending the upstream project with GPU support, guaranteed CPU and memory...
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Dr Eirik Gramstad (University of Oslo (NO))28/05/2026, 16:15Track 8 - Analysis infrastructure, outreach and educationOral Presentation
The ATLAS Open Data for Outreach and Education were transformed in 2025, with an entirely new release featuring new (public) ntuple-making infrastructure, and myriad new notebook examples demonstrating everything from fundamental HEP concepts to complex analyses. The focus of the overhaul has been on simplifying the user experience: with just a few clicks, anyone can make a plot from the Open...
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Suyog Shrestha (Washington College (US))28/05/2026, 16:33Track 8 - Analysis infrastructure, outreach and educationOral Presentation
This contribution presents a scalable and replicable model to engage high-school and undergraduate students with real-world high energy physics (HEP) computing and analysis. At Washington College, we have integrated hands-on analysis of LHC data into both curricular and co-curricular settings. With support from the NSF LEAPS-MPS program, we organize annual workshops for high school students...
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Anuj Raghav (University of Delhi (IN))28/05/2026, 16:51Track 8 - Analysis infrastructure, outreach and educationOral Presentation
The discovery of the Higgs boson by the ATLAS & CMS collaborations at the Large Hadron Collider (LHC) stands as a monumental achievement in particle physics. While the theoretical underpinnings of the Higgs mechanism are widely taught at the university level and substantial data sets have been made publically available, the practical complexities of experimental data analysis, ranging from...
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Lukasz Graczykowski (Warsaw University of Technology (PL))28/05/2026, 17:09Track 8 - Analysis infrastructure, outreach and educationOral Presentation
Title: ALICE Event Display - lessons learned and future enhancements
Authors: Julian Myrcha on behalf of the ALICE collaboration
Affiliations: Warsaw University of TechnologyAfter two years of continuous development and operation, several lessons have been learned that have led to substantial improvements in the ALICE event visualization system. The current solution allows...
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Yuxiao Wang (Tsinghua University (CN))28/05/2026, 17:27Track 8 - Analysis infrastructure, outreach and educationOral Presentation
FireworksWeb is a web-based event display utilizing a C++ ROOT/EVE backend with SAPUI5 frontend for interactive 3D visualization of particle physics events directly in the browser. Building upon ROOT/EVE7 and RenderCore, it eliminates local software installation while maintaining professional-grade event display capabilities. FireworksWeb is currently deployed for live event monitoring in the...
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้็ซ็ weilc (IHEP)28/05/2026, 17:45Track 8 - Analysis infrastructure, outreach and educationOral Presentation
Analyzing ROOT files stored in remote Data Lakes (S3) presents a significant bottleneck: traditional workflows requiring full file downloads incur high latency, while pure client-side solutions (e.g., JSROOT) frequently cause browser memory exhaustion (OOM) when parsing gigabyte-scale binaries.
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To resolve this, we developed a lightweight, hybrid visualization microservice that decouples data...
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