Conveners: Steven Gottlieb, V. Daniel Elvira, Benjamin Nachman

Frontier Summary Report arXiv:2210.05822

Topical Group Reports:

        Experimental Algorithm Parallelization arXiv:2209.07356
                Conveners: Giuseppe Cerati, Katrin Heitmann, Walter Hopkins
        Theoretical Calculations and Simulations arXiv:2209.08177
                Conveners: Peter Boyle, Kevin Pedro, Ji Qiang
        Machine Learning arXiv:2209.07559
                Conveners: Phiala Shanahan, Kazuhiro Terao, Daniel Whiteson
        Storage and Processing Resource Access arXiv:2209.08868
                Conveners: Wahid Bhimji, Meifeng Line, Frank Wurthwein
        End User Analysis arXiv:2209.14984
                Conveners: Gavin S. Davies, Peter Onyisi, Amy Roberts
        Quantum Computing arXiv:2209.06786
                Conveners: Travis S. Humble, Gabriel N. Perdue,
                      Martin J. Savage
        Reinterpretation and Long-Term Preservation of Data and Code arXiv:2209.08054
                Conveners: Stephen Bailey, Kyle S. Cranmer

Contributed Papers:

General - centered on this frontier:

T. Aarrestad et al. HL-LHC Computing Review: Common Tools and Community Software arXiv:2008.13636
S. Campana et al. HEP Computing Collaborations for the Challenges of the Next Decade arXiv:2203.07237
D. Casper et al. Software and Computing for Small HEP Experiments arXiv:2203.07645
Y. Kahn et al. Modeling, Statistics, Simulations, and Computing Needs for Direct Dark Matter Detection arXiv:2203.07700
A. Roberts et al. Dark-matter And Neutrino Computation Explored (DANCE) Community Input to Snowmass arXiv:2203.08338
C. D. Jones et al. Evolution of HEP Processing Frameworks arXiv:2203.14345

General - cross-listed:

J. Heise. The Sanford Underground Research Facility arXiv:2203.08293
E. Barzi et al. In Search of Excellence and Equity in Physics arXiv:2203.10393
E. Barzi et al. How Community Agreements Can Improve Workplace Culture in Physics arXiv:2209.06755

Experimental Algorithm Parallelization

B. Fleming et al. DUNE Software and High Performance Computing arXiv:2203.06104
M. Bhattacharya et al. Portability: A Necessary Approach for Future Scientific Software arXiv:2203.09945

Theoretical Calculations and Simulations

A. Valassi et al. Challenges in Monte Carlo Event Generator Software for High-Luminosity LHC arXiv:2004.13687
A. Costantini et al. Vector Boson Fusion at Multi-TeV Muon Colliders arXiv:2005.10289
E. Yazgan et al. (HSF Physics Event Generator Working Group) HL-LHC Computing Review Stage-2, Common Software Projects: Event Generators arXiv:2109.14938
R. Ruiz et al. The Effective Vector Boson Approximation in High-Energy Muon Collisions arXiv:2111.02442
M. Constantinou et al. Lattice QCD Calculations of Parton Physics arXiv:2202.07193
S. Banerjee et al. Detector and Beamline Simulation for Next-Generation High Energy Physics Experiments arXiv:2203.07614
D. Poland et al. The Numerical Conformal Bootstrap arXiv:2203.08117
F. Foucart et al. Numerical Relativity for Next-Generation Gravitational-Wave Probes of Fundamental Physics arXiv:2203.08139
S. Biedron et al. Accelerator Modeling Community White Paper arXiv:2203.08335
L. Alvarez Ruso et al. Theoretical Tools for Neutrino Scattering: Interplay between Lattice QCD, EFTs, Nuclear Physics, Phenomenology, and Neutrino Event Generators arXiv:2203.09030
S. C. Tognini et al. Celeritas: GPU-Accelerated Particle Transport for Detector Simulation in High Energy Physics Experiments arXiv:2203.09467
T. Blum et al. Discovering New Physics in Rare Kaon Decays arXiv:2203.10998
J. M. Campbell et al. Event Generators for High-Energy Physics Experiments arXiv:2203.11110
A. A. Sahai et al. PetaVolts per Meter Plasmonics arXiv:2203.11623
P. Boyle et al. Lattice QCD and the Computational Frontier arXiv:2204.00039
F. Febres Cordero et al. Computational Challenges for Multi-Loop Collider Phenomenology arXiv:2204.04200
T.-J. Hou et al. Impact of Lattice s(x)−sbar(x) Data in the CTEQ-TEA Global Analysis arXiv:2204.07944
P. Boyle et al. A Lattice QCD Perspective on /weak //decays of b and c Quarks arXiv:2205.15373
A. S. Kronfeld et al. Lattice QCD and Particle Physics arXiv:2207.07641

Machine Learning

G. Kasieczka et al. The LHC Olympics 2020: A Community Challenge for Anomaly Detection in High Energy Physics arXiv:2101.08320
S. V. Chekanov et al. Event-Based Anomaly Detection for New Physics Searches at the LHC using Machine Learning arXiv:2111.12119
D. Boyda et al. Applications of Machine Learning to Lattice Quantum Field Theory arXiv:2202.05838
A. Scheinker, S. Gessner. Adaptive Machine Learning for Time-Varying Systems: Towards 6D Phase Space Diagnostics of Short Intense Charged Particle Beams arXiv:2203.04391
B. Viren et al. Solving Simulation Systematics in and with AI/ML arXiv:2203.06112
A. Bogatskiy et al. Symmetry Group Equivariant Architectures for Physics arXiv:2203.06153
D. Diaz et al. Improving Di-Higgs Sensitivity at Future Colliders in Hadronic Final States with Machine Learning arXiv:2203.07353
R. Bartoldus et al. Innovations in Trigger and Data Acquisition Systems for Next-Generation Physics Facilities arXiv:2203.07620
C. Dvorkin et al. Machine Learning and Cosmology arXiv:2203.08056
A. Adelmann et al. New Directions for Surrogate Models and Differentiable Programming for High Energy Physics Detector Simulation arXiv:2203.08806
N. Akchurin et al. Deep learning applications for quality control in particle detector construction arXiv:2203.08969
S. Thais et al. Graph Neural Networks in Particle Physics: Implementations, Innovations, and Challenges arXiv:2203.12852
P. Harris et al. Physics Community Needs, Tools, and Resources for Machine Learning arXiv:2203.16255
M. S. Neubauer et al. Explainable AI for High Energy Physics arXiv:2206.06632
G. Benelli et al. Data Science and Machine Learning in Education arXiv:2207.09060
T. Y. Chen et al. Interpretable Uncertainty Quantification in AI for HEP arXiv:2208.03284

Storage and Processing Resource Access

A. Sim et al. Deploying In-Network Caches in Support of Distributed Scientific Data Sharing arXiv:2203.06843
A. Bashyal et al. Data Storage for HEP Experiments in the Era of High-Performance Computing arXiv:2203.07885
D. Benjamin et al. Analysis Facilities for HL-LHC arXiv:2203.08010
T. Lehman et al. Data Transfer and Network Services Management for Domain Science Workflows arXiv:2203.08280
K. Herner et al. Towards an HPC Complementary Computing Facility arXiv:2203.08861
K. Lannon et al. Analysis Cyberinfrastructure: Challenges and Opportunities arXiv:2203.08811
M. Acosta Flechas et al. Collaborative Computing Support for Analysis Facilities Exploiting Software as Infrastructure Techniques arXiv:2203.10161

End User Analysis

S. V. Chekanov et al. Jas4pp - a Data-Analysis Framework for Physics and Detector Studies arXiv:2011.05329
J. Pivarski et al. HL-LHC Computing Review Stage 2, Common Software Projects: Data Science Tools for Analysis arXiv:2202.02194
J. V. Bennett et al. Belle II Grid-Based User Analysis arXiv:2203.07564
H. B. Prosper et al. Analysis Description Language: A DSL for HEP Analysis arXiv:2203.09886
C. Backhouse et al. The CAFAna Framework for Neutrino Analysis arXiv:2203.13768

Quantum Computing

Y. Meurice et al. Tensor Networks for High Energy Physics arXiv:2203.04902
S. Brooks et al. Ion Coulomb Crystals in Storage Rings for Quantum Information Science arXiv:2203.06809
T. S. Humble et al. Quantum Computing Systems and Software for High-energy Physics Research arXiv:2203.07091
A. Delgado et al. Quantum Computing for Data Analysis in High-Energy Physics arXiv:2203.08805
J. B. Kowalkowski, A. L. Lyon. Simulations for the Development of Quantum Computational Devices for HEP arXiv:2203.09740
A. Berlin et al. Searches for New Particles, Dark Matter, and Gravitational Waves with SRF Cavities arXiv:2203.12714
A. Derevianko et al. Quantum Networks for High Energy Physics arXiv:2203.16979
C. W. Bauer et al. Quantum Simulation for High Energy Physics arXiv:2204.03381
M. S. Alam et al. Quantum Computing Hardware for HEP Algorithms and Sensing arXiv:2204.08605

Reinterpretation and Long-Term Preservation of Data and Code

M. Alvarez et al. Data Preservation for Cosmology arXiv:2203.08113
S. Bailey et al. Data and Analysis Preservation, Recasting, and Reinterpretation arXiv:2203.10057
B. Nachman. When, Where, and How to Open Data: A Personal Perspective arXiv:2208.07910