2024 RHIC/AGS Annual Users' Meeting

Anders Knospe (Lehigh University), Marzia Rosati (Iowa State University (mrosati@iastate.edu)), Zhenyu Ye (University of Illinois at Chicago)

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The Annual RHIC & AGS Users' Meeting will be held on June 11-14, 2024. The meeting will highlight the latest results from the PHENIX, STAR and sPHENIX experiments and provide an outlook with the future programs at RHIC and the EIC.

Workshops that will be held on Tuesday, June 11 and Wednesday, June 12 will enable more in-depth discussions of the following topics:

 * Beam Energy Scan
 * Computing, Machine Learning, & AI
 * Heavy Flavor & Quarkonia
 * Jets
 * Spin Physics, Cold QCD, & UPCs
 * Flow & Vorticity
 * Diversity, Equity, & Inclusion and Career Development

There will be an in-person poster session on Thursday, June 13. Plenary sessions will be held on Thursday, June 13 and Friday, June 14. Reports on operation status from the sPHENIX and STAR experiments and highlights from PHENIX, sPHENIX and STAR experiments, EIC detectors, reports from representatives from the funding agencies, and award ceremonies will be held during the plenary sessions.

Event ID: E000005813

Note: This meeting falls under Exemption E. Meetings such as Advisory Committee and Federal Advisory Committee meetings. Solicitation/Funding Opportunity Announcement Review Board meetings, peer review/objective review panel meetings, evaluation panel/board meetings, and program kick-off and review meetings (including those for grants and contracts) are open to the public.

    • Computing, Machine Learning, & AI - Building 463, John Dunn Seminar Room 463 (Bldg)



      John Dunn Seminar Room
      Conveners: Jakub Kvapil (Los Alamos National Laboratory), Tanner Mengel (University of Tennessee (UTK))
      • 1
        Overview of Artificial Intelligence at RHIC and Beyond

        This talk will provide an overview of applications of artificial intelligence at RHIC for a variety of purposes ranging from data-taking to physics analysis. Applications ongoing and envisioned for the upcoming EIC will also be discussed.

        Speaker: Hannah Bossi (Massachusetts Institute of Technology (MIT))
      • 2
        Generative AI for full-detector, whole-event simulation of heavy ion collisions

        Artificial intelligence (AI) generative models, such as generative adversarial networks (GANs), have been explored as alternatives to traditional simulations but face challenges with training instability and sparse data coverage. This study investigates the effectiveness of denoising diffusion probabilistic models (DDPMs) for full-detector, whole-event heavy-ion collision simulations as a surrogate model for the traditional Geant4 simulation method. DDPM performance in sPHENIX calorimeter simulation data is compared with GANs. DDPMs outperform GANs and exhibit superior stability and consistency across central and peripheral heavy-ion collision events. Additionally, DDPMs offer a substantial speedup, being approximately 100 times faster than the traditional Geant4 simulation method.

        Speaker: Yeonju Go (Brookhaven National Laboratory )
      • 3
        Interpretable Machine Learning applications to Jet Background Subtraction

        Reconstructing jets in heavy collisions has always required dealing with the challenges of a high background environment. Traditional techniques, such as the area based method, suffered from poor resolution at low momenta due to the large fluctuating background there. In recent years, the resolution has been improved by using machine learning to estimate the background. While machine learning tends to lead to improvements in general (wherever it is applied), care must be taken to ensure these improvements do not come at the cost of interpretability or bias from models used for training. We demonstrate a middle path – using machine learning techniques to translate “black-box” models (such as neural nets) into human interpretable formulas. We present a novel application of symbolic regression to extract a functional representation of a deep neural network trained to subtract background for measurements of jets in heavy ion collisions. With this functional representation we show that the relationship learned by a neural network is approximately the same as a new background subtraction method using the particle multiplicity in a jet. We compare the multiplicity method to the deep neural network method alone, showing its increased interpretability and comparable performance. We also discuss the application of these techniques to background subtraction for jets measured at the EIC.

        Speaker: Charles Hughes (Iowa State University)
      • 10:30 AM
        Coffee break
      • 4
        Real-Time Information Distillation with Deep Neural Network-based Compression Algorithms

        Real-time data collection and analysis in large experimental facilities pose significant challenges across multiple domains, including high-energy physics, nuclear physics, and cosmology. Machine learning (ML)-based methods for real-time data compression have garnered substantial attention as a solution. In this talk, we will explore the use of deep neural networks in designing fast compression algorithms for 3D tensor data from the Time-Projection Chamber (TPC) at the sPHENIX experiment. Specifically, we will delve into the application of Bicephalous Convolutional Neural Networks designed to handle the sparsity and discontinuity of data from the tracking detector. Additionally, we will present our recent development in utilizing sparse convolution techniques to better exploit the data's inherent sparsity. Finally, we will briefly discuss several AI hardware accelerators that we have tested to achieve high-throughput inference.

        Speaker: Yi Huang (Brookhaven National Laboratory)
      • 5
        FastML triggering in sPHENIX (Autonomous selection of physics events)

        A demonstrator for separating events with a heavy flavor decay from background events in proton-proton collisions with the sPHENIX detector is presented. Due to data volume limitations, sPHENIX is capable of recording 10% of the minimum-bias collisions at RHIC using streaming readout in addition to its 15 kHz hardware trigger of rare events. This demonstrator will use machine-learning algorithms on FPGAs to sample the remaining 90% of the collisions.

        Speaker: Cameron Dean (Massachusetts Institute of Technology (MIT))
      • 6
        Machine Learning Application in Jet Quenching Analysis

        Measurements of jet substructure in ultra-relativistic heavy ion collisions suggest that the jet showering process is modified by interaction with the quark gluon plasma. Modifications of the hard substructure of jets can be explored using modern data-driven techniques. In this study, we use a machine learning approach to identify jet quenching amounts. Jet showering processes, both with and without the quenching effect, are simulated using the JEWEL Monte-Carlo event generator and embedded with uncorrelated backgrounds simulated using the ANGANTYR module within the PYTHIA event generator. Sequential substructure variables are extracted from the jet clustering history in an angular-ordered sequence and are used in the training of a neural network based on a long short-term memory network. To understand the detector effects on the efficacy of machine learning, we employed DELPHES-3.5.0 for rapid simulation of CMS detectors, providing reconstructed tracks and neutral particles similar to the particle flow candidates in CMS data. We measured the jet shape and jet fragmentation functions for jets classified by the neural network outputs and quantified their in-medium modifications. We validated that, even with detector effects and a large uncorrelated background of soft particles created in heavy ion collisions, the neural network is still able to learn from the desired features of jet quenching physics

        Speaker: Yilun Wu (Vanderbilt University)
      • 12:30 PM
        No Host Lunch Break
      • 7
        AI/ML applications for the EIC (Virtual)

        The Electron-Ion Collider, a state-of-the-art facility for studying the strong force, is expected to begin commissioning its first experiments in early 2030. Artificial intelligence and machine learning are being incorporated from the beginning at this facility and will continue to be used throughout all phases leading up to the experiments. In this talk, I will highlight a few examples of AI/ML activities that may impact the science of the future EIC.

        Speaker: Cristiano Fanelli (College of William & Mary)
      • 8
        Towards ML Calibration with the ePIC Barrel Hadronic Calorimeter

        Measurement of jets and their substructure will provide valuable information about the underlying dynamics of hard-scattered quarks and gluons in Deep-Inelastic Scattering events. The ePIC Barrel Hadronic Calorimeter (BHCal) will be a critical tool for such measurements at the Electron-Ion Collider. By enabling the measurement of the neutral hadronic component of jets, the BHCal will complement the Barrel Imaging Calorimeter (BIC) and the ePIC tracking system to improve our knowledge of the jet energy scale. However, to obtain a physically meaningful measurement, the response of the combined BIC + BHCal system must be properly calibrated using information from both. We present a potential Machine Learning (ML) based algorithm for the calibration of the combined system. With ML, this calibration can be done in such a way that is both computationally efficient and easy to deploy in a production environment, making such an approach ideal for quasi-real time calibrations needed in a streaming readout environment. We will discuss progress towards its implementation as well as the role it might play in a broader ML-based Particle Flow Algorithm.

        Speaker: Derek Anderson (Iowa State University)
      • 9
        Machine Learning Applications for EBIS Beam Intensity and RHIC Luminosity Maximization

        In this talk, we present some results about EBIS beam intensity and RHIC luminosity online and offline optimization, using the machine learning packages GPTune and XGBoost.

        Speaker: Xiaofeng Gu (Collider Accelerator Department, BNL)
      • 3:00 PM
        Coffee break
      • 10
        Machine learning applications in particle accelerators

        Discussion and examples of Bayesian optimization, Reinforcement learning, and future planning for particle accelerators.

        Speaker: Yuan Gao (Collider Accelerator Department, BNL)
      • 11

        MultiFold is a machine-learning based technique that can correct for detector effects for multiple observables in an unbinned manner. In this talk, we discuss how MultiFold works, highlight its applications in several experiments, and introduce resources available to get started on using it.

        Speaker: Youqi Song (Yale University)
      • 12
        Adventures in OmniFold: Multivariable Unfolding of Jet-Level Observables with STAR Data (Virtual)

        OmniFold, the full phase space application of MultiFold, is an unbinned way of correcting multiple observables for detector effects simultaneously using machine learning. As these dependencies are typically addressed in a binned, observable-by-observable fashion, OmniFold presents a novel alternative. In this talk, we present the OmniFold method and a direct application of it to jet-level STAR data.

        Speaker: Hannah Harrison (University of Kentucky)
    • Flow & Vorticity - Bldg. 510, Physics Large Seminar Room and Bldg 490, Medical Large Conference Room 510/490 (Bldg.)



      Physics Large Seminar Room/Medical Large Conference Room
      Conveners: Niseem (Magdy) Abdelrahman (University of Tennessee, Knoxville), Yu Hu (Lawrence Berkeley National Laboratory)
      • 13
        Vorticity measurements from the STAR experiment at RHIC
        Speaker: Xingrui Gou (Shandong University)
      • 14
        Experimental Overview of the Spin Alignment and Electromagnetic Field Effect Observations at RHIC
        Speaker: Diyu Shen (Fudan University)
      • 15
        "Spin puzzle" spins back
        Speaker: Dr Yi Yin (Institute of modern physics chinese academy of sciences)
      • 10:15 AM
        Coffee break
      • 16
        Highlights from the STAR experiment on flow measurements
        Speaker: Priyanshi Sinha (IISER Tirupati)
      • 17
        Highlights from the PHENIX experiment on flow measurements
        Speaker: Yuri Mitrankov (Stony Brook University)
      • 18
        Highlights from the sPHENIX experiment on flow measurements
        Speaker: Ejiro Umaka (Brookhaven National Laboratory)
      • 12:00 PM
        No Host Lunch Break - Workshop moving to Bldg 490, Large Conference Room at 2:00 PM
      • 19
        The small system flow measurements from the STAR experiment at RHIC
        Speaker: Zhengxi Yan (Stony Brook University)
      • 20
        The small system flow measurements from the PHENIX experiment at RHIC
        Speaker: Sanghoon Lim (Pusan University)
      • 2:50 PM
        Coffee break
      • 21
        Theoretical progress in small systems calculations
        Speaker: Wenbin Zhao (Brookhaven National Laboratory)
      • 22
        Theoretical highlights on anisotropic flow calculations
        Speaker: Dr Xiang-Yu Wu (McGill University)
      • 23
        New flow observables from BSQ charge fluctuations
        Speaker: Jordi Salinas San Martin (University of Illinois at Urbana-Champaign)
      • 24
        Open dissection on flow and collectively in small collision systems
        Speakers: Dr Niseem (Magdy) Abdelrahman (University of Tennessee, Knoxville), Yu Hu (Lawrence Berkeley National Laboratory)
    • Cold QCD, Spin Physics, & UPCs from RHIC to the EIC - Bldg. 488, Berkner Hall Room B 488 (Bldg.)



      Berkner Hall, Room B
      Conveners: Daniel Brandenburg (Ohio State University), Jae Nam (Temple University), Sookhyun Lee (University of Michigan, Ann Arbor)
      • 25
        STAR Foward Systems and Related Topics
        Speaker: Xilin Liang (University of California, Riverside)
      • 26
        Highlights from the PHENIX
        Speaker: Devon Loomis (University of Michigan, Ann Arbor)
      • 27
        Propects with the sPHENIX
        Speaker: Genki Nukazuka (RIKEN BNL Research Center)
      • 2:30 PM
        Coffee Break
      • 28
        Entanglement in UPC Collisions
        Speaker: Haowu Duan (North Carolina State University)
      • 29
        UPC Flow and Baryon Junction
        Speaker: Prithwish Tribedy (Brookhaven National Laboratory)
      • 30
        UPC Photoproduction at RHIC
        Speaker: Ashik Ikbal Sheikh (Kent State University )
      • 31
        Midrapidity Measurements Highlighting Lambda (Virtual)
        Speaker: Jan Vanek (Brookhaven National Laboratory )
      • 32
        Helicity Correlation of Lambda Hyperons at UPC and EIC
        Speaker: Shu-yi Wei
      • 33
        Spin/Cold-QCD Theory Towards EIC
        Speaker: Yiyu Zhou (South China Normal University)
    • Jets - Bldg 488 Berkner Hall Room B 488 (Bldg.)



      Bekner Hall Room B
      Conveners: Anthony Hodges (University of Illinois), Jussi Viinikainen (University of Illinois at Chicago), Tristan Protzman (Lehigh University)
    • Beam Energy Scan - Bldg. 510 Physics Large Conference Room 510 (Bldg.)



      Physics Large Seminar Room
      Conveners: Yevheniia Khyzhniak (Ohio State University), Zachary Sweger (University of California, Davis), Zhiwan Xu (University of California, Los Angeles)
    • Heavy Flavor - Bldg. 490 Medical Conference Room 490 (Bldg)



      Medical Large Conference Room
      Conveners: Anthony Frawley (Florida State University), Antonio Carlos Oliveira da Silva (Iowa State University)
    • Diversity, Equity, & Inclusion + Career Dual Session - Bldg,488 Berkner Hall Room B 488 (Bldg.)



      Berkner Hall, Room B
      Convener: Justin Frantz (Ohio University)
      • 63
        Speaker: Justin Frantz (Ohio University)
      • 64
        DEI Updates at the Lab
        Speaker: Noel Blackburn (Brookhaven National Laboratory)
      • 65
        APS-IDEA: Facilitating Community Transformation.
        Speaker: Dessie Lee Clark (University of Wisconsin)
      • 66
        Discussion about DEI Strategies in RHI for the Future
      • 4:05 PM
        Coffee Break
      • 67
        Career Directions: From heavy ion physics to quant trading

        advice from a PHENIX 2006-10 alumn and Hedge Fund co-founder

        Speaker: Rui Wei (Scientech LLC)
      • 68
        Career Directions

        advice from a Data Scientist

        Speaker: Jonathan Runchey (Home Depot)
      • 69
        Career Directions

        advice from a PET detector scientist

        Speaker: Shiv Kumar Subedi (Canon Medical Research)
      • 70
        Dinner at Painters' Restaurant at 6:00 p.m. Reservations Required
    • Plenary Session I - Bldg. 488 Berkner Hall Auditorium 488 (Bldg)



      Berkner Hall Auditorium
      Conveners: Prof. Anders (UEC Chair- Elect) Knospe (Lehigh University), Marzia Rosati (UEC Chair) (Iowa State University), Zhenyu Ye (UEC Past-Chair) (University of Illinois at Chicago)
    • Plenary Session I - Bldg. 488 Berkner Hall Auditorium: Part A
      Conveners: Prof. Anders Knospe (Lehigh University), Virginia Bailey (Georgia State University)
      • 71
        Welcome Remarks
        Speaker: JoAnne Hewett (Director of Brookhaven National Laboratory)
      • 72
        Opening Remarks
        Speaker: Haiyan Gao (BNL, Associate Laboratory Director, Nuclear and Particle Physics)
      • 73
        Report from the DOE
        Speaker: Dr. Sharon Stephenson (Physics Research Division Director, Office of Nuclear Physics, Department of Energy)
      • 74
        Report from the NSF
        Speaker: Dr. Senta Victoria Greene (Program Director, U.S. National Science Foundation)
    • 10:35 AM
      Coffee Break & Poster Session
    • Plenary Session I - Bldg. 488 Berkner Hall Auditorium: Part B
      Conveners: Daniel Brandenburg (Ohio State University), Raghav Kunnawalkam Elayavalli (Vanderbilt University)
    • 12:20 PM
      No Host Lunch Break & Poster Session
    • Plenary Session I - Bldg. 488 Berkner Hall Auditorium: Part C
      Conveners: Marzia Rosati (Iowa State University), Youqi Song (Yale University)
    • 2:55 PM
      Coffee Break & Poster Session
    • Plenary Session I - Bldg. 488 Berkner Hall Auditorium: Part D
      Conveners: Cameron Dean (MIT), Megan Connors (Georgia State University)
    • 5:30 PM
      Poster Session & Cocktail Hour
    • Plenary Session II - Bldg. 488 Berkner Hall Auditorium 488 (Bldg.)



      Berkner Hall Auditorium
      Conveners: Prof. Anders Knospe (Lehigh University), Marzia Rosati (Iowa State University), Zhenyu Ye (University of Illinois at Chicago)
    • Plenary Session II - Bldg. 488 Berkner Hall Auditorium: Part A
      Conveners: Emilie Duckworth (Kent State University), Hannah Bossi (MIT)
      • 89
        Workshop Report: Flow & Vorticity
        Speaker: Niseem (Magdy) Abdelrahman (University of Tennessee, Knoxville)
      • 90
        Workshop Report: Beam Energy Scan
        Speaker: Yevheniia Khyzhniak (Ohio State University )
      • 91
        Workshop Report: Cold QCD, Spin Physics, & UPCs from RHIC to the EIC
        Speakers: Daniel Brandenburg (Ohio State University), Jae Nam (Temple University)
      • 92
        EIC Project Status
        Speaker: James Fast (Jefferson Laboratory )
    • 10:30 AM
      Coffee Break
    • Plenary Session II - Bldg. 488 Berkner Hall Auditorium: Part B
      Conveners: Prof. Anders Knospe (Lehigh University), Yeonju Go (University of Colorado, Boulder)
    • 1:00 PM
      End of Meeting Luncheon Compliments of BSA