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Nachman Group
Nachman Group News
2024
4/24/2024
- Vinicius's OmniLearn: A Method to Simultaneously Facilitate All Jet Physics Tasks is now on arXiv!
3/25/2024
- We had a great group picnic at Ohlone Park!
4/11/2024
- Sascha's and Vinicius's paper Improving generative model-based unfolding with Schrodinger bridges
- Kehang's and Radha's paper Non-resonant anomaly detection with background extrapolation
3/25/2024
- Press release from the LBNL Physical Science Area on Ben's APS GDS election:
3/20/2024
- Vinicius gave a great talk about generative AI for particle physics at GTC!
3/12/2024
- Vinicius's paper Full phase space resonant anomaly detection
3/08/2024
- Radha's paper The interplay of machine learning-based resonant anomaly detection methods
2/20/2024
- Shahzar and Mariel's paper Learning likelihood ratios with neural network classifiers
- Ben was quoted in an MIT Tech. Review article on the search for new physics .
2/15/2024
- Dennis gave the UC Berkeley BIDMaP Seminar: From Particle to Paper: Machine Learning for High-Energy Physics .
2/1/2024
- Mariel gave the LBNL Physics Division Seminar: Towards a Foundation Model for Fundamental Physics .
- Vinny's paper on single-shot calorimeter shower simulation
with diffusion models
1/31/2023
- Group lunch!
1/16/2024
- Ben has been elected as Vice-Chair of the Group on Data Science at the American Physical Society!
2023
11/29/2023
- Ben gave a talk at the AI4EIC workshop on High Dimensional Unfolding using Machine Learning (and Vinicius chaired the session on AI/ML for Data Analysis and Theory ).
11/27/2023
- Our paper on Weakly supervised anomaly detection in the Milky Way
11/18/2023
- Our paper on Anomaly detection with flow-based fast calorimeter simulators is now on arXiv!
11/21/2023
- Our paper on Non-resonant Anomaly Detection with Background Extrapolation led by Kehang and Radha is now on arXiv!
- Our paper on Morphing one dataset into another with maximum likelihood estimation
11/13/2023
- Our paper on Integrating Particle Flavor into Deep Learning Models for Hadronization is now on arXiv!
- Our paper on Safe but Incalculable: Energy-weighting is not all you need is now on arXiv!
- Berkeley Lab's Physical Science Area features a press release about Polymathic AI:
11/12/2023
- Berkeley Lab's Physical Science Area features a press release about Data Physicsts:
11/6-10/2023
- Many talks at ml4jets!
11/3/2023
- Ben gave the Argonne National Laboratory Physics Colloquium on Re-Imagining the Search for Fundamental Interactions with Machine Learning .
11/2/2023
- Radha was selected as a Templeton TEX fellow!
11/1/2023
- Many papers accepted at the Machine Learning and Physical Sciences Workshop at NeurIPS! Congratulations to Elham, Fernando, Mariel, Shahzar, and Vinicius! Camera-ready versions will be posted soon.
10/23/2023
- Ben gave a talk at the CERN CMS Machine Learning Innovation group on Spectrum Morphing with Machine Learning .
10/13/2023
- Ben wrote an opinion piece for APS News on the intersection of data science and physics:
10/12/2023
- Our paper on Designing Observables for Measurements with Deep Learning in collaboration with Owen Long at UC Riverside is now on arXiv!
10/10/2023
- Our paper on Full Phase Space Resonant Anomaly Detection led by Vinicius is now on arXiv!
- Ben gave the colloquium at the US ATLAS physic analysis tutorial at SLAC on Reimagining Physics Analysis in ATLAS .
10/9/2023
- Mariel is part of a team (called Polymath ) to study large language models for science and they have made their debut today! Here is a blog post about it written by Mariel:
10/2/2023
- Our paper on The Optimal use of Segmentation for Sampling Calorimeters led by Fernando is now on arXiv!
9/29/2023
- Ben gave the UC Berkeley BIDMaP seminar on Re-imagining the search for fundamental interactions with machine learning .
9/22/2023
- Our paper on Enhanced latent spaces for improved collider simulations
9/13/2023
- Our paper on Flow for Flows led by Radha in collaboration with folks from the University of Geneva is now on arXiv!
- Our paper on Fitting a Deep Generative Hadronization Model
9/11/2023
- Our paper on geometry optimization for long-lived particle detectors is now published in JINST!:
9/1/2023
- A brief press release about the BOOST Conference that we co-organized:
8/30/2023
- Ben gave a talk on Using unbinned measurements for new physics
8/29/2023
- Our paper on Enhanced latent spaces for improved collider simulations
8/28/2023
- Our paper on Fast Point Cloud Generation with Diffusion Models in High Energy Physics
8/23/2023
- Our paper on Schrodinger Bridges for Unfolding led by Vinicius and Sascha is now on arXiv!
- Our paper on Schrodinger Bridges for Simulation Refinement led by Sascha and Vinicius is now on arXiv!
8/21/2023
- Ben gave a talk on ML-assisted measurements of lepton-jet asymmetries in DIS @ H1
8/20/2023
- Our paper on optimizing long-lived particle detectors with Tom Gorordo, Simon Knapen, Dean Robinson, and Adi Suresh is has been accepted for publication in JINST!
8/13/2023
- Ben is now a member of the PhyStat Committee .
8/8/2023
- Ben gave a lecture at the SLAC Summer Institute on Challenges in AI/ML at the Energy Frontier
- Our paper on Fast Point Cloud Generation with Diffusion Models in High Energy Physics
8/7/2023
- Our NSF Proposal Enabling Particle and Nuclear Physics Discoveries with Neural Deconvolution has been funded!
- Our paper on Fitting a Deep Generative Hadronization Model
- Our paper on CaloScore v2: Single-shot Calorimeter Shower Simulation with Diffusion Models led by Vinicius is now on arXiv!
8/4/2023
- The BOOST conference was a big success! The conference photo below is a link to the agenda with many interesting presentations! See also this summary from ATLAS.
8/1/2023
-The ml4jets conference poster is now online!
7/28/2023
-The US ATLAS ML Training Event was a big success! There were a number of talks by group members (indico linked below).
7/28/2023
- We went for a hike at The Dish to celebrate Ben's promotion to career staff scientist!
7/25/2022
- Vinicius's H1 analysis
Unbinned Deep Learning Jet Substructure Measurement has been accepted for publication in PLB!
- Our paper on Resonant Anomaly Detection with Multiple Reference Datasets with Mayee Chen (Stanford) and Fred Sala (U. Wisconsin) is has been published in JHEP!
7/20/2023
- Our paper on The Interplay of Machine Learning--based Resonant Anomaly Detection Methods led by Radha is now on arXiv!
7/18/2022
- Ben was quoted in a Symmetry article about AI/ML and Simulation:
7/17/2023
- Fast Point Cloud Generation with Diffusion Models in High Energy Physics led by Vinicius and Mariel is now on arXiv!
7/15/2023
- Our paper on Parton Labeling without Matching is has been published in EPJC!
7/11/2023
- Our paper on Resonant Anomaly Detection with Multiple Reference Datasets with Mayee Chen (Stanford) and Fred Sala (U. Wisconsin) is has been accepted for publication in JHEP!
7/10/2023
- Comparison of Point Cloud and Image-based Models for Calorimeter Fast Simulation led by Fernando and Vinicius is now on arXiv!
7/7/2023
- Our paper on Unbinned Profiled Unfolding
7/5/2023
- The Machine Learning and Physical Sciences Workshop has been accepted for another iteration at NeurIPS!
- Our paper on Parton Labeling without Matching is has been accepted for publication in EPJC!
6/27/2023
- Ben gave a talk about Machine Learning for Precision Physics at the LHC at LoopFest .
- Our paper on Learning to Isolate Muons in Data with Ed Witkowski and Daniel Whiteson now on arXiv!
- Ben wrote an article published in the CERN EP Newsletter
6/22/2023
- Our paper on covariant particle transformers is now published in PRD!:
6/20/2023
- Our paper on modeling theory uncertainties is now published in SciPost!:
6/19/2023
- Our paper on Unbinned Profiled Unfolding
6/16/2023
- Our joint grant with Anja Butter's group at LPNHE in Paris on unfolding has been funded through the France-Berkeley Fund !
6/12/2023
- Our paper on Unbinned Profiled Unfolding
6/6/2023
- Our paper on High-dimensional and Permutation Invariant Anomaly Detection led by Vinicius is now on arXiv!
6/1/2023
- Ben gave a talk about the Range of Machine Learning methods in Particle Physics at the PhyStat-2sample workshop.
5/26/2023
- Our paper on Fitting a Deep Generative Hadronization Model led by Jay is now on arXiv!
5/22/2023
- Paper on Statistical Patterns of Theory Uncertainties with Aishik Ghosh, Tilman Plehn, Lily Shire, Tim Tait, and Daniel Whiteson has been accepted for publication at SciPost!
5/17/2023
- Our paper on Learning Likelihood Ratios with Neural Network Classifiers led by Mariel and Shahzar is now on arXiv!
5/12/2023
- Our paper on Enhanced latent spaces for improved collider simulations is now on arXiv!
5/11/2023
- Our paper on Covariant Particle Transformers has been accepted for publication in PRD!
5/5/2023
- Our paper on Weakly-Supervised Anomaly Detection in the Milky Way led by Mariel and Sowmya is now on arXiv!
5/2/2023
- Our paper on Flow-Enhanced Transportation for Anomaly Detection led by Radha has been accepted for publication in PRD!
4/19/2023
- Congratlations to Krish for passing his qualifying exam! Here is a picture from our celebration:
4/18/2023
- Our paper on Parton Labeling without Matching is now on arXiv!
3/23/2023
- Fernando's H1 analysis
Machine learning-assisted measurement of azimuthal angular asymmetries is now public!
- Vinicius's H1 analysis
Unbinned Deep Learning Jet Substructure Measurement has been posted to arXiv!
3/9/2023
- Ben was presented an Outstanding Reviewer Award from IOP for MLST.
3/8/2023
- Ben gave the PHYSTAT seminar on Unbinned and High-dimensional Unfolding with Machine Learning .
3/7/2023
- Congratlations to Radha for passing her qualifying exam! Here is a picture from our (rainy!) celebration:
2/22/2023
- Ben gave a ML overview talk at the P5 Town Hall at LBNL.
- Our paper on quantum anomaly detection in JHEP!:
2/17/2023
-Congratulations to Radha for being awarded an APS GDS Impact Award!:
2/15/2023
- Our paper on maching-learning for topic modeling in JHEP!:
2/10/2023
- Our paper on Unbinned Profiled Unfolding led by Jay is now on arXiv!
1/13/2023
- Our paper on simulation-based AD is now published in JHEP!:
1/9/2023
- Our paper on the coordinate dependence of anomaly detection is now published in PRD!:
2022
Group gathering in the fall of 2022
12/24/2022
- Our paper on anomaly detection with multileptons with Kasia has been accepted for publication in JHEP!
12/22/2022
- Our hadronization universality paper is now published in EPJC!:
12/21/2022
- Our paper on Flow-Enhanced Transportation for Anomaly Detection led by Radha is now on arXiv!
12/20/2022
- Our paper on Resonant Anomaly Detection with Multiple Reference Datasets with Mayee Chen (Stanford) and Fred Sala (U. Wisconsin) is now on arXiv!
12/19/2022
- Our paper on the coordinate dependence of unsupervised learning has been accepted for publication in PRD!
12/12/2022
- Our paper on Efficiently Moving Instead of Reweighting Collider Events with Machine Learning led by Radha is now on arXiv!
12/5/2022
- Our paper on systematically improvable quark/gluon likelihood ratios is now published in JHEP!:
11/29/2022
- Our jet tagger universality project with Kingman Cheung, Alan Chung, and Shih-Chieh Hsu has been accepted for publication in EPJC!
11/28/2022
- Our ML hadronization project has now been published in Phys. Rev D!:
- Our CaloScore project has now been published in Phys. Rev D!:
11/22/2022
- Our CaloScore project has now been published in Phys. Rev D!:
- Ben was recognized at the Director's Award Ceremony for his DOE Early Career Award:
11/20/2022
- We have many papers accepted at he Machine Learning and Physical Sciences workshop at NeurIPS2022!
M. Chen, B. Nachman, and F. Sala, Anomaly Detection with Multiple Reference Datasets in High Energy Physics
K. Desai, B. Nachman, and J. Thaler, Deconvolving Detector Effects for Distribution Moments
R. Mastandrea and B. Nachman, Efficiently Moving Instead of Reweighting Collider Events with Machine Learning
G., Rikab, J. Thaler, B. Nachman, Learning Uncertainties the Frequentist Way: Calibration and Correlation in High Energy Physic
N. Karr, B. Nachman, and D. Shih, One-Class Dense Networks for Anomaly Detection
Y. Huang, J. Collins, B. Nachman, S. Knapen, and D. Whiteson, Particle-level Compression for New Physics Searches
11/18/2022
- Our paper on implementing 2+1 Abelian lattice gauge theories on a quantum computer with Chris Kane, Dorota Grabowska, and Christian Bauer is now on arXiv!
11/15/2022
- Our paper on optimizing long-lived particle detectors with Tom Gorordo, Simon Knapen, Dean Robinson, and Adi Suresh is now on arXiv!
11/7/2022
- Our Fair Universe Project led by Wahid Bhimji has been highlighted in a Berkeley Lab press release:
11/4/2022
- Paper on a deep generative model for hadronization with Aishik Ghosh, Xiangyang Ju, and Andrzej Siodmok has now been accepted for publication in Phys. Rev. D!
11/1-4/2022
- Many people in the group gave talks at ml4jets!
10/31/2022
- Ben gave the Physics Department Colloquium at Yale on Machine Learning for Fundamental Physics .
10/28/2022
- Our project with Rikab that used open simulation from CMS recieved an honrable mention in the MIT Prize for Open Data!:
10/27/2022
- Paper on Statistical Patterns of Theory Uncertainties with Aishik Ghosh, Tilman Plehn, Lily Shire, Tim Tait, and Daniel Whiteson is now on arXiv!
10/26/2022
- Ben gave a talk on Modern jet physics with AI at the LHeC/FCCeh and PERLE Workshop at Orsay.
10/25/2022
- Our recent H1 results have been highlighted in a Berkeley Lab press release:
10/20/2022
- Many papers from the group were accepted to the Machine Learning and Physical Sciences Workshop at NeurIPS2022!
R. Gambhir, J. Thaler, B. Nachman, Learning Uncertainties the Frequentist Way: Calibration and Correlation in High Energy Physics
R. Mastandrea and B. Nachman, Efficiently Moving Instead of Reweighting Collider Events with Machine Learning
K. Desai, B. Nachman, J. Thaler, Deconvolving Detector Effects for Distribution Moments
M. Chen, B. Nachman, F. Sala, Anomaly Detection with Multiple Reference Datasets in High Energy Physics
Y. Huang, J. Collins. B. Nachman, S. Knapen. D. Whiteson, Particle-level Compression for New Physics Searches
N. Karr, B. Nachman. D. Shih, One-Class Dense Networks for Anomaly Detection
- Paper on Machine-Learning Compression for Particle Physics Discoveries with Jack Collins, Yifeng (Eric) Huang, Simon Knapen, and Daniel Whiteson is now on arXiv!
10/14/2022
- Ben gave a seminar at CMU's STAtistical Methods for the Physical Sciences Research Group (STAMPS).
10/11/2022
- After a two year process, the Computational Frontier report for Snowmass is now on arXiv!
- Ben co-organized a session and gave a talk about Differentiable Simulations at the AI4EIC workshop.
10/10/2022
- Ben gave a talk about AI-driven detector design for the EIC at the AI4EIC workshop.
10/7/2022
- Our Ephemeral Learning paper has been accepted for publication in SciPost Physics!
10/6/2022
- Our DOE CompHEP project A Fair Universe: Unbiased Data Benchmark Ecosystem for Physics postdoc opening for someone to study inference-aware machine learning methods.
10/1/2022
- Our NNSA NA-22 project Deep Learning Based Particle Identification Methods for Silicon CCDs (led by Ren Cooper) was funded! We have a postdoc opening for someone to apply machine learning for particle identification.
9/22/2022
- Ben gave the Physics and Astronomy Department Colloquium at the University of San Francisco.
- Our Calomplification paper has been accepted for publication in JINST!
9/13/2022
- Paper perspective on coordinate dependence of anomaly detection with Gregor, Radha, Vinicius, Mariel, and David is now on arXiv!
9/8/2022
- Our AQCEL quantum complier is now published in Quantum!
9/6/2022
- Our CATHODE method is now published in PRD!
8/26/2022
- Our ATLAS PUB Note about Point Cloud Deep Learning Methods for Pion Reconstruction is now public!
8/25/2022
- Our ATLAS PUB Note about Constituent-Based Top-Quark Tagging is now public!
8/19/2022
- We have a job posting for a postdoc to join our group and work on anomaly detection .
8/16/2022
- White paper perspective on Open Data for Snowmass is now on arXiv!
- Our Ephemeral Learning paper was accepted for publication in SciPost.
8/15/2022
- Our pair of papers on prior-independent calibration with Rikab and Jesse have been published in PRL and PRD!
8/10/2022
- Our paper on remeasurement for our quantum parton shower has been published in PRD!
8/8/2022
- Ben gave the monthly A3D3 seminar on Towards Online Anomaly Detection for Particle Physics .
8/5/2022
- Paper on a quantum simulations for U(1) lattice gauge theory with Dorota Grabowska, Christopher Kane, and Christian Bauer is now on arXiv!
- Paper on self-supervised anomaly detection with Radha Mastandrea and Barry Dillon (Heidelberg)has been accepted by PRD!
8/4/2022
- Ben gave a talk at Google's Core Science Seminar series on Building Robust Deep Learning Methods for High Energy Physics .
8/3/2022
- Paper on a differentiable parton shower with Stefan Prestel is now on arXiv!
7/27/2022
- Elham and Aishik (with help from many others from our group!) organized a successful ML training event, sponsored by US ATLAS and with help from NERSC! Ben gave an Overview of Machine Learning for HEP .
7/26/2022
- Ben is now an associate editor at EPJC.
7/25/2022
- Paper on systematically improvable likelihoods with Sam Bright-Thonney, Ian Moult, and Stefan Prestel is now on arXiv!
- Paper on maximum likelihood calibration with Rikab Gambhir and Jesse Thaler (MIT) has been accepted for publication in PRL!
7/20/2022
- Paper on the bias and priors of machine learning calibrations with Rikab Gambhir and Jesse Thaler (MIT) has been acceped for publication in PRD!
- Ben was scheduled to give a talk on AI-driven detector design for the EIC , but it was postponed last minute (see the website for the slides).
7/19/2022
- Our paper describing the CATHODE technique, a a density-based anomaly detection method has been accepted for publication in PRD!
- Ben gave a talk on silicon sensor simulation in an instrumentation parallel session at the Snowmass Community Summer Study.
7/17/2022
- The Snowmass Community Summer Study began today! We are involved in many parts of this event, mostly in the context of the Computational Frontier. I won't list all of the Computational Frontier events (there are many) - see the website for details!
- A first version of the Computational Frontier report is now public - feedback is most welcome!
7/10/2022
- Ben gave a colloquium at the QUC Summer School at KIAS .
7/9/2022
- Yao gave a great talk at ICHEP!
7/6/2022
- The ML for Physical Sciences workshop that we are co-organizing has been accepted for NeurIPS 2022!
7/7/2022
- Our paper on using ML-tailored observables for unfolding has been published in JINST!
7/4/2022
- Yao's differential electron-jet correlation measurement with H1 data is now public in time for his talk at ICHEP!
6/27/2022
- Many abstracts related to work in our group have been accepted for talks at BOOST 2022 ! In particular, Matt LeBlanc (CERN) will talk about topic modeling for the strong coupling, Sascha Diefenbacher (Hamburg) will talk about online density estimation, Sebastian Bieringer (Hamburg) will talk about statistical amplification of generative models, Tobias Quadfasel (Hamburg) will talk about anomaly detection with CATHODE, Dilia Quintero (TRIUMF) will talk about ml4pions, and Christine McLean (ANL) will talk about the future of jet substructure.
6/26/2022
- Paper on diffusion models for calorimeter simulation with Vinny is now on arXiv!
- Ben gave a lecture about Machine Learning for Instrumentation at the HEPCAT Summer school .
6/22/2022
- Ben gave a talk about uncertainty quantification for machine learning-based data analysis at an EIC Software Meeting:
6/21/2022
- Paper on topic modeling to extract the strong coupling constant with Matt LeBlanc and Christof Sauer is now on arXiv!
- Ben gave a talk about jet measurements for the proposed high-luminosity Electron Ion Collider.
6/16/2022
- Paper on anomaly detection with quantum machine learning with Sulaiman Alvi and Christian Bauer is now on arXiv!
6/13/2022
- Our first H1 analysis was featured in the DESY Lab Annual Report on Particle Physics!
- Ben was interviewed on the podcast My Journey as a Physicist .
6/7/2022
- Ben has recieved a DOE Early Career Award!
6/4/2022
- Our paper on anomaly detection with symmetry violation in collaboration with M. Birman and S. Bressler has been published in EPJC!
6/1/2022
- Ben and Sulaiman gave talks at the BNL (virtual) workshop on Quantum Machine Learning for HEP .
5/29/2022
- Our paper on Optimizing Observables with Machine Learning for Better Unfolding with Miguel Arratia, Daniel Britzger, and Owen Long has been accepted for publication in JINST!
5/26/2022
- Our paper on symmetry discovery with Krish Desai and Jesse Thaler has been published in PRD!
5/24/2022
- Ben organized and gave the overview talk at the PHYSTAT-Anomalies workshop .
- Today and tomorrow, Ben will give lectures on QCD, jets and substructure at a HEP Graduate Student Workshop (virtually) in Algeria.
5/20/2022
- Paper on self-supervised anomaly detection with Radha Mastandrea and Barry Dillon (Heidelberg) is now on arXiv!
- Our paper on anomaly detection with symmetry violation in collaboration with M. Birman and S. Bressler has been accepted for publication in EPJC!
- Ben gave a talk on quantum error mitigation at the The Fifth Annual Southeast Quantum Computing Workshop .
5/19/2022
- Ben gave a talk about anomaly detection at LHCP.
- Our review on searches with machine learning with Georgia Karagiorgi, Gregor Kasieczka, Scott Kravitz, and David Shih has been published in Nature Reviews Physics!
5/10/2022
- Paper on the bias and priors of machine learning calibrations with Rikab Gambhir and Jesse Thaler (MIT) is now on arXiv!
- Preliminary plots for the point cloud studies on ml4pions are now public!
5/9/2022
- Paper on maximum likelihood calibration with Rikab Gambhir and Jesse Thaler (MIT) is now on arXiv!
- A number of results from our group will be presented this week at the 5th CERN IML workshop .
5/4/2022
- Ben gave a keynote talk about Machine Learning for Fundamental Physics to the Cray User Group (CUG).
5/3/2022
- Vinny presented our latest H1 measurement that uses graph neural networks to process high-dimensional inputs for jet substrcture at DIS 2022 !
4/29/2022
- Ben's upcoming talk at the Cray User Group (CUG) Conference was featured in HPC Wire .
4/26/2022
- Our paper on anomaly detection for electron-positron collisions is now published in JHEP!
4/22/2022
- Our paper on neural conditional reweighting is now published in Phys. Rev. D!
4/13/2022
- Oak Ridge National Lab wrote a press release about our work on simulating effective field theories on a quantum computer:
4/9/2022
- Ben gave a talk Discovering Unanticipated New Physics with Machine Learning at the APS April meeting.
4/8/2022
- Paper on the universality of jet classification with Kingman Cheung, Yi-Lun (Alan) Chung and Shih-Chieh Hsu is now on arXiv!
4/7/2022
- Ben gave the TRIUMF lab colloquium on anomaly detection .
- Snowmass white paper on Quantum Simulation for HEP is now on arXiv!
4/6/2022
- Our application of weakly-supervised anomaly detection to e+ e- data with Julia Gonski, Jerry Lai, and Ines Ochoa has been accepted for publication in JHEP!
- Ben gave a talk at the University of Bern on Deep Generative Models for High Energy Physics .
4/5/2022
- Our paper on new random identity insertion is now published in Phys. Rev. A!
4/4/2022
- Our paper on symmetry discovery with Krish Desai and Jesse Thaler has been accepted for publication in PRD!
3/31/2022
- Our paper on Optimizing Observables with Machine Learning for Better Unfolding with Miguel Arratia, Daniel Britzger, and Owen Long is now on arXiv!
- Registration is now open for a workshop Ben is organizing on Quantum Error Mitigation for Particle and Nuclear Physics at the University of Washington:
3/28/2022
- We contributed to a couple of chapers in a book about artificial intelligence for high energy physics .
3/24/2022
- Welcome to Matan Grinberg who is a UCB physics graduate student and working with us this semester on machine learning methods!
3/23/2022
- Our paper on machine learning for hadronization with Aishik, Xiangyang, and Andrzej is now on arXiv!
3/21/2022
- Ben gave the opening talk at the Simons Center workshop Flowing into the future: Particle Jets in Quantum Field Theory and Phenomenology .
3/18/2022
- Our paper on quantum parton showers with gate remeasurement with Plato, James, Diana, Zoe, and Christian is now on arXiv!
3/17/2022
- Our paper on anomaly detection with multileptons with Kasia is now on arXiv!
3/16/2022
- Snowmass White paper on demonstrator plasma accelerators is now on arXiv!
- Ben gave the Berkeley Theory Seminar on Discovering Unanticipated New Physics with Machine Learning .
3/15/2022
- Snowmass white paper deadline is today! A few white papers came out early (see below) and some will be late (see above), but two came out right on time:
3/14/2022
- Our paper on Lorentz covarient transformers in collaboration with S. Qiu, S. Han, X. Ju, and H. Wang is now on arXiv!
- Our paper on anomaly detection with symmetry violation in collaboration with M. Birman and S. Bressler is now on arXiv!
- Mariel's Snowmass White paper on covariant neural networks is now on arXiv!
3/11/2022
- Snowmass White paper on silicon simulation is now on arXiv!
3/10/2022
- Our paper building on Neural Conditional Reweighting with Jesse Thaler has been accepted for publication in Phys. Rev. D!
3/8/2022
- Our paper on decorrelated autoencoders is now published in Phys. Rev. D!
which was also featured as the Editors' suggestion:
3/7/2022
- Our paper on decorrelated theory uncertainties is featured as an EPJC highlight:
and in Springer Research News:
3/4/2022
- Our paper about the dangers of decorrelating theory uncertainties with Aishik Ghosh has been selected for the cover of EPJC's January edition!
3/3/2022
- Our paper building on the Random Identity Insertion Method for quantum gate error mitigation with Vince Pascuzzi, Andre He, Christian Bauer, and Bert de Jong has been accepted for publication in Phys. Rev. A!
2/28/2022
- Our review on searches with machine learning with Georgia Karagiorgi, Gregor Kasieczka, Scott Kravitz, and David Shih has been accepted for publication in Nature Reviews Physics!
2/25/2022
- The H1 Collaboration paper applying OmniFold for electron-jet correlations has been accepted for publication in Phys. Rev. Letters!
2/23/2022
- Radha has been selected as a Data Science Education Community of Practice Fellow !
- Ben gave a lecture on Machine Learning in Particle Physics in UC Berkeley Physics 290E.
- Our recent work on quantum error mitigation in collaboration with quantum chemistry colleagues was featured in a Berkeley Lab press release:
- A new community challenge that we are co-organizing centered around machine learning methods for calorimeter simulation is now live!
2/22/2022
- Ben is now an affiliated faculty member of the Designated Emphasis graduate program in Computational Data Science and Engineering .
2/21/2022
- Ben, Krish, Mariel, Radha, and Sowmya are giving talks at the APS April Meeting !
2/18/2022
- Our paper on online normalizing flows for triggerless learning is now on arXiv!
- Ben gave a talk about Machine Learning for hadronic final state reconstruction at the STAR Collaboration Week.
2/15/2022
- Our paper on statistical amplification from deep generative models applied to calorimeter simulation is now on arXiv!
2/7/2022
- Our paper on decorrelated autoencoders with Vinicius Mikuni and David Shih is has been accepted by PRD and also selected as a highlight as an Editor's Suggestion!
1/28/2022
- Our paper on decorrelating theory uncertainties is now published in Eur. Phys. J. C!
1/27/2022
- Ben gave an invited talk at the ATLAS ML forum about less-than-supervised learning in collider physics .
1/24/2022
- Our paper on active readout error mitigation is now published in Phys. Rev. A!
1/19/2022
- Our paper on unbinned cross section measurements is now published in JINST!
1/14/2022
- Ben gave a talk about Application of Machine Learning to Event Reconstruction and Analysis at the 2022 IAS Program on High Energy Physics.
1/12/2022
- Ben gave a talk about H1 lepton-jet correlations and ML unfolding at the Lepton Photon Conference.
- We are happy to welcome Fernando Torales-Acosta as a postdoc in the group! Fernando will start on February 1.
1/10/2022
- Our paper about the dangers of decorrelating theory uncertainties with Aishik Ghosh has been accepted for publiation by EPJC!
1/6/2022
- Welcome to Haoxing Du who is a UCB physics graduate student and working with us this semester on particle property inference with normalizing flows!
2021
Group gathering in the fall of 2021
12/22/2021
- Les Houches proposal for presening unbinned differential cross section results is now on accepted at JINST!
12/20/2021
- Our readout error correction protocol paper with Rebecca Hicks, Bryce Kobrin, and Christian Bauer is now accepted at Phys. Rev. A!
12/14/2021
- Our EIC grant was featured in a news article at BIDS:
12/13/2021
- Today was the Machine Learning and Physical Sciences workshop ! Many people from our group presented posters (click to enlarge):
- Our paper on symmetry discovery with Krish Desai and Jesse Thaler is now on arXiv!
- Paper on reconstructing the kinematics of deep inelastic scattering using deep learning with Miguel Arratia, Daniel Britzger, and Owen Long, is now published in NIMA!
12/07/2021
- Our review on searches with machine learning with Georgia Karagiorgi, Gregor Kasieczka, Scott Kravits, and David Shih is now on arXiv!
- The LHC Olympics paper has been published in Reports on Progress in Physics!
12/04/2021
- Paper on reconstructing the kinematics of deep inelastic scattering using deep learning has been accepted for publication in NIMA!
12/03/2021
- Krish, Radha, and Vinny presented excellent posters at a poster session at the Berkeley Institue for Data Science:
12/02/2021
- Our group has been awarded a grant from the DOE, office of Nuclear Physics to optimize the detectors of the Electron Ion Collider with machine learning! The press release from the DOE is here and the article in Elements is below:
- Ben is co-organizing a virtual seminar series on anomaly detection , which had its first talk today by Jie Ren at Google Brain.
12/01/2021
- Yao presented a great poster at the virtual SULI poster session:
11/18/2021
- The depolarizing noise mitiagion paper has been accepted for publication in Phys. Rev. Letters!
- Our paper on simulating effective field theories on a quantum computer has been published in Phys. Rev. Letters!
11/11/2021
- Ben prepared a talk about Machine Learning for Collider Event Reconstruction and Analysis for the CEPPC workshop
- Ben gave a talk about silicon simulations for the silicon instrumentation Snowmass meeting
- Our paper on decorrelated autoencoders with Vinicius Mikuni and David Shih is now on arXiv!
11/4/2021
- The LHC Olympics paper is now published in Reports on Progress in Physics!
11/2/2021
- Ben gave a talk on Deep Learning, Quantum Information, and the LHC as a Gluon Factory at the weekly Harvard LPPC seminar.
10/29/2021
- The LHC Olympics paper has been accepted for publication in Reports on Progress in Physics!
10/27/2021
- Our paper building on the Random Identity Insertion Method for quantum gate error mitigation with Vince Pascuzzi, Andre He, Christian Bauer, and Bert de Jong is now on arXiv!
- The combination of OmniFold with BSM searches paper was published today in Phys. Rev. D!
10/22/2021
- Four papers from our group have been accepted for poster presentations a NeurIPS workshops this year!
A. Hallin, et al., Classifying Anomalies THrough Outer Density Estimation (CATHODE), ML4PS2021
A. Ghosh, B. Nachman, D. Whiteson, Uncertainty Aware Learning for High Energy Physics With A Cautionary Tale, ML4PS2021
K. Desai, B. Nachman, J. Thaler, Symmetry Discovery with Deep Learning, ML4PS2021
R. Winterhalder, M. Bellegente, B. Nachman, Latent Space Refinement for Deep Generative Models, DGMs2021
10/20/2021
Aishik and Krish gave talks at the Perceive 2021 conference organized by Clarifai.
The Physics Division Machine Learning group has opened up two postdoc searches:
Developing Surrogate Models for Particle Physics and Cosmology: AJO
Machine Learning Detector Design and Data Analysis for Hadronic Physics: AJO
10/16/2021
- Ben gave a lecture about Quantum Error Mitigation to the Quantum Computing at Berkeley group.
10/15/2021
- Ben was awarded the 2022 Henry Primakoff Award for Early-Career Particle Physics by the American Physical Society:
10/14/2021
- Ben gave a talk about the H1 ML-based unfolding measurement in the Physics Division ML Group Meeting (slides are only visible to the Berkeley community).
10/12/2021
- Our paper Simulating collider physics on quantum computers using effective field theories was accepted for publicaiton in PRL!
- Paper on reconstructing the kinematics of deep inelastic scattering using deep learning with Miguel Arratia, Daniel Britzger, and Owen Long, is now on arXiv!
10/11/2021
- Ben gave a talk about the H1 electron-jet correlation measurement at the MPI@LHC workshop.
- Today we had our first hybrid group meeting! Aside from some minor technical struggles in the beginning, it worked fairly well.
10/5/2021
- Ben gave a talk about the H1 electron-jet correlation measurement at the QCD Structure of the Nucleon workshop.
9/30/2021
- Aishik gave a talk about our uncertainty-aware paper at the AMLD EPFL workshop .
- Paper with Patrick McCormack and Patrick Komiske on preserving new physics from unfolding was accepted for publication in PRD!
9/28/2021
- Ben gave a talk at the ATLAS Exotic Physics Workshop on New anomaly detection techniques .
- At the 2nd workshop on jets for 3D imaging at the EIC , Ben spoke about the H1 lepton-jet correlation measurement.
- Ben gave a talk at the Low-x Conference on both the H1 and ZEUS lepton-jet correlation measurements.
- The uncertainty-aware learning paper was published today in Phys. Rev. D!
9/27/2021
- Ben gave a talk about anomaly detection in electron-positron collisions at an FCC Physics meeting .
- In an EF05 Snowmass topical group meeting , Ben spoke about Experimental studies of energy correlators and spin effects at the LHC .
- Mariel gave a great talk as the second speaker of the semester in the BIDS Machine Learning and Science Forum !
- Les Houches proposal for presening unbinned differential cross section results is now on arXiv!
9/24/2021
- Ben represented the Computational Frontier at Snowmass Day
9/22/2021
- Our paper about Gaussian state preparation on a quantum computer with Christian Bauer, Plato Deliyannis, and Marrat Freytsis is now on arXiv!
9/19/2021
- Our paper about the dangers of decorrelating theory uncertainties with Aishik Ghosh is now on arXiv!
9/18/2021
- We had a group get-together at Ben's place!
9/16/2021
- The first Physics Division ML Group meeting of the semester!
9/15/2021
- Ben gave an overview of the Quantum Computing group's activities at the 2021 QuantISED Collaboration Meeting .
9/13/2021
- Vinny gave a great talk as the first speaker of the semester in the BIDS Machine Learning and Science Forum !
9/9/2021
- We received a grant (as a co-I; PI is Uros Seljak) from DOE ASCR to combine machine learning with simulations for high energy physics and cosmology!
- Ben co-organized a session on Accelerator and Detector Control at the AI4EIC workshop this week.
9/7/2021
- At this week's AI4EIC workshop , Ben will co-organize a session on Accelerator and Detector Control (Thursday) and give talks about simulation (Tuesday) and reconstruction (Wednesday).
9/2/2021
- Ben spoke about Quantum Computing for Modeling High Energy Scattering at the Berkeley Lab Thursday Science Forum on Quantum Information Science.
9/1/2021
- Welcome to Mariel Pettee who is a new Chamberlain Fellow and Vinicius Mikuni who is a new NESAP Fellow!
- A joint venture of many collaborators has now produced CATHODE, a density-based anomaly detection method that outperforms many other approaches on the LHC Olympics. The manuscript is now on arXiv!
- The paper we contributed to on memory confidence in rats has now been published in Current Biology!
- Ben presented a machine learning overview at the Snowmass Energy Frontier restart workshop .
8/31/2021
- Ben co-wrote an article about machine learning-based anomaly detection for high energy physics in the CERN Courier :
8/30/2021
- Our application of weakly-supervised anomaly detection to e+ e- data with Julia Gonski, Jerry Lai, and Ines Ochoa is now on arXiv!
8/27/2021
- The H1 Collaboration paper applying OmniFold for electron-jet correlations is now on arXiv!
- Our new readout error correction protocol paper with Rebecca Hicks, Bryce Kobrin, and Christian Bauer is now on arXiv!
8/23/2021
- Welcome to Yao Xu who is a SULI intern working with us on OmniFold R&D!
8/22/2021
- Structure Functions and Parton Densities DIS 2021 Conference Proceedings are now on arXiv .
8/16/2021
- The Machine Learning and the Physical Sciences NeurIPS workshop website is now live!
8/12/2021
- The ATLAS leakage current paper is now published in JINST!
8/5/2021
- The SA-CWoLa anomaly detection paper was published today in Phys. Rev. D!
8/3/2021
- The URAP posting for this fall is now online - UC Berkeley undergraduates are invited to apply!
7/28/2021
- Ben gave a seminar on Quantum Algorithms for High Energy Physics Simulations at the IISc Quantum Technologies Initiative (IQTI)
7/27/2021
- Aishik, Adi, and Ben gave talks during the public session of the the CMS Machine Learning Town Hall:
Adi: Scaffolding Simulations with Deep Learning for High-dimensional Deconvolution [slides ]
Aishik: Uncertainty Aware Learning For High Energy Physics [slides ]
Ben: Learning from Many Collider Events at Once [slides ]
7/26/2021
- Ben gave three talks today at the EPS-HEP conference:
Acceptance talk for the Young Experimental Particle Physics prize [slides ]
Summary of exotic Higgs boson searches in ATLAS [slides ]
H1 Collaboration OmniFold measurement [slides ]
7/25/2021
- The ATLAS note on digluon tagging with deep sets and DCTR reweighting with Murtaza Safdari is now public!
7/23/2021
- The NeurlPS workshop on Machine Learning for the Physical Sciences was accepted for a 2021 edition!
7/19/2021
- The neural conditional reweighting paper with Jesse Thaler is now on arXiv!
7/15/2021
- Ben gave a talk about Modern techniques for jet reconstruction at the ILC Working Group 3 Open Physics Meeting.
7/14/2021
- Ben gave his first talk as a member of the H1 Collaboration at the ISMD workshop on Jet-based TMD measurements with H1 data .
7/12/2021
- Adi and Kees gave great talks at the APS DPF conference about their work in progress on the ATLAS OmniFold analysis and the ATLAS weakly supervised bump hunt analysis .
7/8/2021
- Ben gave a talk about New Physics from Precision at High Energy at the LISHEP workshop.
7/6/2021
- ML4Jets2021 started today! Over the next three days, we will hear 96 talks covering many exciting topics! Talks from our group:
Additionally, there were many talks from collaborators on joint projects (in order of the talks):
- The ANDEA workshop paper on the LHC Olympics dataset is on arXiv!
- Ben was featured in the CERN Courier for the Altarelli award:
7/5/2021
- After a long saga, the HEPData for the track-based fragmentation function measurement has been updated to include covariance matrices!
- Welcome to Radha Mastandrea who is an incoming UCB physics graduate student and working with us this summer on anomaly detection!
7/3/2021
- Our paper on combining the SALAD and CWoLa anomaly detection methods with Kees and Luc has been accepted for publication in PRD!
7/2/2021
- Paper with Yi-Lun (Alan) Chung and Shih-Chieh Hsu on disentangling boosted Higgs Boson production modes with machine learning is now published in JINST!
6/30/2021
- Our paper Comparing Weak- and Unsupervised Methods for Resonant Anomaly Detection led by Pablo Martin and in collaboration with Jack Collins and David Shih has been accepted for publication in EPJC!
- Ben gave a talk about Extracting the Most from Collider Data with Deep Learning at the Jefferson Lab AI Lunch series:
6/28/2021
- Ben gave a talk about Quantum Algorithm for High Energy Physics Simulations at the KIAS QUC-AIHEP seminar series.
6/24/2021
- Ben gave a talk about Simulating collider physics on quantum computers using effective field theories at the All Things EFT seminar series.
6/23/2021
- Ben spoke to Berkeley Lab interns about his research and career trajectory into quantum computing for high energy physics .
- The ATLAS pixel leakage current measurement paper is now accepted for publication in JINST!
6/21/2021
- The Mainz Institute for Theoretical Physics 2 week program on Machine Learning for Particle Physics started today with interesting talks about optimal transport!
6/20/2021
- An ML-oriented paper about the LHC Olympics dataset was accepted into the ANDEA workshop at KDD 2021 !
6/18/2021
- The ML4Jets program is now public! We had 100 abstract submissions and for the first time, we have to have parallel sessions to fit in all of the exciting talks.
6/17/2021
- Ben gave a talk about Recent progress in ML applications for LHC phenomenology at the virtual Les Houches workshop as well as leading a discussion about unbinned differential cross section measurements .
- The ATLAS pixel leakage current measurement paper is finally on arXiv!
6/14/2021
- Paper with Jesse Thaler on Learning from Many Collider Events at Once was published in Phys. Rev. D!
- Welcome Kasia Krzyzanska (Princeton undergraduate) who will be joining our group for the summer as part of the (virtual) CERN REU!
6/10/2021
- The paper on the statistics of generative adversarial networks with Anja Butter, Sascha Diefenbacher, Gregor Kasieczka, and Tilman Plehn has been published in SciPost Physics!
6/7/2021
- Ben gave a talk at the AICamp about Group Anomaly Detection
6/3/2021
- Brief article in Nature Reviews Physics about OmniFold is now published!
6/1/2021
- Paper on Latent Space Refinement for Deep Generative Models with Ramon Winterhalder and Marco Bellegente is now on arXiv!
- Ben was interviewed by Berkeley Lab's Elements . 5/31/2021
- Together with Andreas Hinzmann (U. Hamburg), Ben covered Jet Substructure measurements by ATLAS and CMS at the recent CERN Jets and Theory workshop.
- Ben was awarded the 2021 HEP Young Experimental Physicst Prize from the European Physical Society!
5/27/2021
- The paper on the statistics of generative adversarial networks with Anja Butter, Sascha Diefenbacher, Gregor Kasieczka, and Tilman Plehn has been accepted to SciPost Physics!
- Ben gave the IFIC Colloquium on What can Deep Learning Teach Us About Particle Physics?
5/25/2021
- Ben gave the HEP seminar at UCSD on Extracting the Most from Collider Data with Deep Learning
5/20/2021
- Paper with Patrick McCormack and Patrick Komiske on preserving new physics from unfolding was posted to arXiv!
5/18/2021
- Paper with Jesse Thaler on Learning from Many Collider Events at Once was accepted for publication in Phys. Rev. D!
- Paper with Aishik Ghosh and Daniel Whiteson on uncertainty-aware learning was posted to arXiv!
5/17/2021
- Welcome Ashia Lewish (NERSC summer intern) to the group!
- Ben gave a talk at UC Irvine to the Machine Learning and Physical Sciences NSF graduate training program about our work and what it is like working at a national laboratory.
5/10/2021
- Paper with Jakub Filipek, Shih-Chieh Hsu, John Kruper (U. Washington) and Kirtimaan Mohan (Michigan State) on Identifying the Quantum Properties of Hadronic Resonances using Machine Learning is now on arXiv!
- Our ICLR paper with Anders Andreassen (Google), Patrick Komiske, Eric Metodiev, Jesse Thaler (MIT), and Adi Suresh (UC Berkeley) on Scaffolding Simulations with Deep Learning for High-dimensional Deconvolution is now on arXiv!
- Ben presented at the AICamp:
5/7/2021
- Adi presented a poster on OmniFold and Sascha Diefenbacher presented a poster on GANplifying at the simDL ICLR workshop.
5/5/2021
- Ben gave the LBNL Brown Bag Instrumentation Seminar on Radiation effects in the LHC experiments: Impact on detector performance and operation .
5/3/2021
- The beyond 4D tracking paper is now published in JINST!
4/27/2021
- Congratulations to Luc Le Pottier for winning the University of Michigan's William L. Williams Thesis Award!
4/26/2021
- Our paper on CNNs for Higgs final state identification has been accepted for publication at JINST!
4/22/2021
- Krish gave an excellent talk in today's Physics Division Machine Learning Group meeting on his Symmetry Discovery project.
4/21/2021
- Ben is the Physical Science Area's representative to the lab committe Future Berkeley Lab Computing Working Group . This committee was highlighted in today's lab research update article .
4/19/2021
- Murtaza gave a great talk at today's APS April meeting!
- Berkeley Lab's daily newsletter, Elements, featured Ben's Altarelli Award as did the Berkeley Institute for Data Science , and he was also featured in a tweet by the ATLAS Collaboration:
.
4/18/2021
- Adi, Aishik, Krish, and Patrick gave excellent talks today at the APS April meeting!
- Ben also started off the Data Science parallels today with an overview of the LHC Olympics .
4/16/2021
- Ben was awarded the 2021 Guido Altarelli prize at the DIS Conference!
4/15/2021
- Congratulations to Kees for accepting an offer for physics graduate school at Harvard and to Luc for accepting an offer for physics graduate school at UC Berkeley!
Miguel Arratia presented our OmniFold H1 analysis at DIS !
4/14/2021
- Ben was a panelist in the ML Club debate on anomaly detection for discoveries:
4/13/2021
- CERN Yellow Report on radiation damage at the LHC is now published! This has been a multi-year effort, resulting from multple workshops and coordination across all four LHC experiments and including RD50. Ben was the co-editor of the sensor measurements section and contributed to the simulation section.
- Ben is co-organizing the Parton Densities and Structure Functions session at DIS this week with Katarzyna Wichmann (DESY) and Pia Zurita (Regensburg).
4/12/2021
- Paper with Mike Geller (U. Georgia) on Categorizing Readout Error Correlations on Near Term Quantum Computers is now on arXiv!
4/9/2021
- Ben gave a talk about Discovering Unanticipated New Physics with Machine Learning at the PIT PACC workshop LHC physics for Run 3 .
4/6/2021
- Our first result as a member of the H1 Collaboration with Miguel Arratia is now public: using OmniFold applied to deep inelastic scattering data to probe the strong force in new ways! Here is an event display from the measurement:
4/5/2021
- Our paper Comparing Weak- and Unsupervised Methods for Resonant Anomaly Detection led by Pablo Martin and in collaboration with Jack Collins and David Shih is now on arXiv!
- The video and slides from the deep generative models for fundamental physics workshop are now online.
4/2/2021
- Our papers on extending (1) OmniFold to include background and acceptance effects and (2) the statistical power of deep generative models were accepted at the simDL workshop at ICLR 2021 !
3/31/2021
- Congratulations to Jason Huang for accepting an offer for physics graduate school at UIUC!
3/30/2021
- Today we heard interesting talks about machine learning for jet physics at the KITP workshop from Jesse Thaler and Frederic Dreyer .
3/26/2021
- Ben gave a talk in the University of San Francisco Seminar Series in Data Science :
3/25/2021
- Ben presented a seminar on Building Robust AI/ML Methods for High Energy Physics at the Berkeley Lab Thursday Morning Science Forum.
3/19/2021
- We have produced new summary plots for exotic Higgs boson decays for Moriond 2021, including model indendent results for the first time.
- Luc has created a pip-installable python package called anomaly-detection-models for the SALAD and SA-CWoLa anomaly detection codes!
3/18/2021
- Today we heard interesting talks about anomaly detection at the KITP workshop from Gregor Kasieczka and Anja Butter .
3/17/2021
- Ben gave a talk at the T2K General Cross Section Meeting about OmniFold.
- Today's Deep Generative Modeling for Fundamental Physics co-hosted by BIDS was a great success! Many of the slides are online and the video will be posted later this week.
- Ben gave a lecture to the ATLAS undergradates on the strong force.
3/16/2021
- Ben gave a talk on quantum computing at the University of Geneva.
3/15/2021
- Congratulations to Sulaiman Alvi who has been selected as a 2021 SURF L&S Fellow!
- The Mitigating depolarizing noise on quantum computers with noise-estimation circuits paper with Miro Urbanek, Vince Pascuzzi, Andre He, Christian Bauer, and Bert de Jong was posted to arXiv!
- Welcome Diana Chamaki (Berkeley Undergraduate) to the group!
3/11/2021
- The ninth meeting of the Physics Division ML group in 2021 took place today! Aishik Ghosh spoke about our project that incorporates uncertainty into deep learning inference.
3/4/2021
- The eigth meeting of the Physics Division ML group in 2021 took place today! David Shih spoke about anomaly detection applied to steller streams.
3/1/2021
- Ben gave the University of Michigan HEP-Astro on Extracting the Most From Collider Data With Deep Learning .
2/28/2021
- The MoDE paper was accepted for publication in JHEP!
2/25/2021
- Ben gave the first lecture of the LBNL ATLAS lecture series on high energy physics , geared towards the ATLAS group's undergraduate students.
- The seventh meeting of the Physics Division ML group in 2021 took place today! Ben spoke about the LHC Olympics.
2/24/2021
- Our quantum parton shower paper was featured in a Physics World!
2/23/2021
- Ben gave the Michigan State University High Energy Physics Seminar on Disentangling Boosted higgs boson Production Modes with Machine Learning .
2/22/2021
- The Double DisCo shower paper was published today in Phys. Rev. D!
- Matt Buckley and David Shih (Rutgers) showed how our ANODE method can be applied to astrophysical data at the Streams21 workshop .
2/19/2021
- Our ATLAS weakly supervised anomaly detection search was featured in a press release by Berkeley Lab.
- Registration is now open for the Deep Generative Models for Fundamental Physics workshop we are co-organizing with BIDS and the ML Group at Berkeley Lab.
- The Quantum Gate Pattern Recognition and Circuit Optimization for Scientific Applications paper with Koji Terashi, Wonho Jang, Christian Bauer and others was posted to arXiv!
2/18/2021
- Ben gave a talk about the LHC Olympics at the CERN Reinterpretation Workshop (here is the recording ).
- The sixth meeting of the Physics Division ML group in 2021 took place today! Ryan Roberts spoke about graph neural networks for top quark physics.
2/17/2021
- The beyond 4D tracking paper was accepted for publication in JINST!
2/16/2021
- Yi-Lun (Alan) Chung gave a talk at the CERN IML on our work about disentangling Higgs production modes at high momentum . Here are the slides and the recording .
2/15/2021
- Welcome Norman Karr (Berkeley Undergraduates) to the group!
2/12/2021
- Our quantum parton shower paper was featured in a press release by Berkeley Lab.
2/11/2021
- The fifth meeting of the Physics Division ML group in 2021 took place today! Xiangyang Ju spoke about various applications of graph neural networks.
- Talks from our group were accepted at the APS April Meeting:
B. Nachman, G. Kasieczka, D. Shih, The LHC Olympics: A Community Challenge for Anomaly Detection in High Energy Physics
A. Suresh, A. Andreassen, S. Hsu, B. Nachman, N. Suaysom, Parameter Estimation using Neural Networks in the Presence of Detector Effects
A. Ghosh, B. Nachman, D. Whiteson, Uncertainty Aware Learning for High Energy Physics
W. McCormack, B. Nachman, P. Komiske, Unfolding New Physics with the OmniFold Method
K. Desai, B. Nachman, J. Thaler, Symmetry Discovery using Machine Learning
M. Safdari, B. Nachman, A. Schwartzman, Investigating the Unexplored H to 4g Decay Mode With Machine Learning Analysis Techniques in pp Collisions at sqrt(s) = 13 TeV With the ATLAS Detector
2/10/2021
- The quantum parton shower paper was published today in Phys. Rev. Letters!
2/9/2021
- Ben gave a seminar to the Relativistic Heavy Ion Physics group at the University of Tennessee on OmniFold and jet measurements.
- The Simulating collider physics on quantum computers using effective field theories paper with Christian Bauer and Marat Freytsis was posted to arXiv!
2/8/2021
- Ben gave the Physics Department Seminar at SMU on High dimensional jet measurements in pp and ep collisions . A recording of the talk is on YouTube .
- Ben was elected as the secretary of the American Physical Society's Group on Data Science:
2/5/2021
- The readout rebalancing paper was published today in Phys. Rev. A!
2/4/2021
- The fourth meeting of the Physics Division ML group in 2021 took place today! Daniel Murname spoke about metric learning and graph neural networks for particle tracking.
2/3/2021
- The ABCDisCo paper was accepted for publication in Phys. Rev. D!
2/2/2021
- A brief paper highlighting the Living Review of Machine Learning for Particle Physics co-authored with Matthew Feickert is now on arXiv!
2/1/2021
- The SRGN paper was published today in Phys. Rev. D!
1/29/2021
- Our paper on quantum parton showers was featured in Nature Reviews Physics :
1/28/2021
- The third meeting of the Physics Division ML group in 2021 took place today! Vanessa Boehm spoke about differentiable simulations for weak cosmic lensing.
1/27/2021
- Ben gave a talk High dimensional jet measurements (at the EIC) at the (virutal) EIC opportunities for Snowmass workshop.
1/26/2021
- The LHC Olympics was featured on the Berkeley Institute for Data Science website !
1/22/2021
- The The LHC Olympics 2020: A Community Challenge for Anomaly Detection in High Energy Physics paper co-edited by Gregor Kasieczka and David Shih was posted to arXiv!
1/21/2021
- Ben is now a member of the H1 Collaboration at DESY , working on a multi-differential cross section measurement with Miguel Arratia probing azimuthal decorrelations.
- The second meeting of the Physics Division ML group in 2021 took place today! Jack Newsom and Ethan Lu spoke about the application of machine learning to neutrino event reconstruction.
1/20/2021
- Paper with Jesse Thaler on Learning from Many Collider Events at Once was posted to arXiv!
1/15/2021
- The readout rebalancing paper was accepted for publication in Phys. Rev. A!
- Ben gave a talk Discovering Unanticipated New Physics with Machine Learning at the (virutal) Hong Kong IAS Program on High Energy Physics.
1/14/2021
- Ben gave the talk A Neural Resampler for Monte Carlo Reweighting with Preserved Uncertainties at the CMS Machine Learning forum (unfortunately, the meeting agenda was private).
- The first meeting of the Physics Division ML group in 2021 took place today! George Stein spoke about Self-Supervised Representation Learning for Astronomical Images.
1/12/2021
- UC IrvineYvonne Ng won an US ATLAS Center grant to visit Berkeley Lab last fall to work on ML-based anomaly detection. That was and is still not possible, but we are happy to welcome her as a "virtual" visitor this spring!
- Welcome Ming Fong (Berkeley Undergraduates) to the group!
2020
12/18/2020
- The quantum parton shower paper has been accepted for publication in PRL!
12/16/2020
- Our new GPU cluster ml4hep is now alive! RTX6000's are super fast!
12/15/2020
- We now have a presence on bioRxiv! Ben contributed to the paper Total recall: episodic memory retrieval, choice, and memory confidence in the rat , led by Dr. Hannah Joo at UCSF.
- Ben wrote an article Machine learning ushers in a new paradigm for particle searches at the LHC for the CERN EP department newsletter.
12/11/2020
- Many people from our group and collaborators are presenting posters at the Machine Learning for Physical Sciences workshop at NeurIPS today. In particular:
12/10/2020
- The fourth regular meeting of the Physics Division ML group took place today! Giuseppe Puglisi spoke about deep generative models for the Cosmic Microwave Background (CMS).
12/9/2020
- The SRGN paper has been accepted for publication in PRD!
- The Chamberlain Fellowship interviews have begun! As candidates cannot travel to Berkeley this year, the Physics Division has prepared a virtual tour. Towards the end, you can see a brief highlight of the Division's exciting work in quantum information and machine learning:
12/8/2020
- Paper with Patty Fox, Jason Huang, Josh Isaacson, and Xiangyang Ju on using silicon pixel cluster shapes for track seeding was posted to arXiv!
12/7/2020
- Today we had a first Nachman ML Group meeting! Was great to see everyone in the same (virtual) room!
12/3/2020
- The third regular meeting of the Physics Division ML group took place today! Our very own Adi Suresh gave a very intersting and engaging talk about Parameter Estimation using Neural Networks in the Presence of Detector Effects
11/25/2020
- The CODEX-b Expression of Interest paper has been accepted for publication in EPJC!
11/23/2020
- We have released the LHC Olympics solutions on Zenodo .
- Ben gave a seminar Extracting the most from collider data with deep learning virtually in China.
11/20/2020
- Ben gave a talk on the Neural Positive Resampler at the HEP Software Foundation workshop .
11/19/2020
- The second regular meeting of the Physics Division ML group took place today! We had interesting discussions about machine learning prospects for LZ and DESI.
11/11/2020
- Ben gave the HEP seminar at the University of Liverpool (virtually) on Anomaly detection with machine learning at the LHC .
11/5/2020
- The first regular meeting of the Physics Division ML group took place today! We had about 45 people in attendence from all areas of fundamental physics and across the lab and wider Berkelely community.
- BIDS advertises the Berkeley Lab Physics Division ML group meetings.
- Our unfolding paper for quantum computer readout error mitigation was featured in a press release by Berkeley Lab.
11/2/2020
- The DCTRGAN paper was published today in JINST!
10/27/2020
- Review on Anomaly Detection for Physics Analysis and Less than Supervised Learning was posted to arXiv!
- Ben gave the Nuclear Science Division HIT seminar on Simulation-based and label-free deep learning for fundamental physics.
10/21/2020
- Ben gave a talk at Clarifai's Perceive 2020 workshop on Less than Supervised Learning for Fundamental Physics Discoveries .
10/20/2020
- Ben is now an affiliate at the Berkeley Institute for Data Science .
10/19/2020
- First part of a 3-part mini-workshop on jet substructure hosted by the LHC EW Working Group on Jets and EW Bosons and co-organized by Ben and James Mulligan .
- Ben gave a talk at the 2020 Accelerated AI for Big-Data Experiments Conference on The Computational Challenge of Anomaly Detection .
- Paper with Ouail Kitouni, Constantin Weisser, and Mike Williams (MIT) on Enhancing searches for resonances with machine learning and moment decomposition was posted to arXiv!
10/18/2020
- Many people from our group and collaborators are speaking at the CERN Inter-experiment ML workshop this week. In particular:
10/15/2020
- Paper with Rebecca Hicks and Christian Bauer on readout rebalancing for quantum computers was posted to arXiv!
- Ben gave a seminar at the University of Washington on quantum computing for high energy physics (slides and recording are public).
10/14/2020
- Ben gave a talk at the MATHUSLA weekly collaboration meeting about the background estimation strategy used by CODEX-b.
10/13/2020
- Both the supervised clustering and neural resampler papers were published today in Phys. Rev. D!
10/9/2020
- Ben represented the LHC Electroweak Working Group Jets and Bosons Subgroup in the biannual general meeting.
10/7/2020
- Ben spoke at the annual ATLAS Higgs + Top quark Workshop ML: gains & pitfalls for ttH (unfortunately, the website is ATLAS internal).
10/6/2020
- This week is the Snowmass Community Planning Meeting. Ben kicked off the Computational Frontier acivities
10/1/2020
- Welcome Vince Pascuzzi (LBNL postdoc)! Vince will join the group with a part of his time to work on quantum algorithms.
9/25/2020
- The quantum computing unfolding paper is now published in npj Quantum Information!
9/24/2020
- Ben spoke at the LBNL ATLAS-theory lunch about jet substructure and anomaly detection plans for Snowmass .
9/21/2020
- Ben spoke at the EF05 Snowmass Topical Group Meeting about Jets and Jet Substructure at Future Colliders .
- The weakly supervised anomaly search paper is now published in Physical Review Letters!
9/23/2020
- The paper on graph nets for supervised jet clustering with Xiangyang Ju has been accepted for publication in Phys. Rev. D!
9/22/2020
- Welcome Sulaiman Alvi (Berkeley Undergraduates) to the group!
- Kees gave a talk on SA-CWoLa at the Pacific NW Theory Workshop
9/18/2020
- The DCTRGAN paper was accepted for publication in JINST!
9/17/2020
- The Neural Resampler paper was accepted for publication in PRD!
- Ben gave a talk at the IF03 Solid State Detectors and Tracking Snowmass topical group meeting about the challenges for radiation damage simulation tools.
- Ben gave a talk about classification for top quarks at the Top2020 workshop. The last time I gave a talk at a Top Quark conference was in 2012, when I was presenting our (CMS Collaboration at the time!) measurement of the top quark mass :
9/14/2020
- Lab affiliate and former collaborator Michela Paganini gave the first Machine Learning and Science Forum talk of the year at BIDS today!
- Paper with Yi-Lun (Alan) Chung and Shih-Chieh Hsu on disentangling boosted Higgs Boson production modes with machine learning is now on arXiv!
- Welcome Sowmya Thanvantri and Jerry Lai (Berkeley Undergraduates) to the group!
9/8/2020
- Together with Sascha Diefenbacher, Engin Eren, Gregor Kasieczka, Anatolii Korol, and David Shih, we posted our paper combining neural reweighting with deep generative models
9/6/2020
- Kees, Luc, and Ben posted the paper on combining the SALAD and CWoLa anomaly detection methods
9/4/2020
- Ben gave a talk in Norm Yao's group at UCB. Lots of interesting questions!
9/2/2020
- Ben and Matthew Feickert chaired the machine learning session at the ATLAS Higgs and Diboson Resonances searches workshop today.
- High Energy Nuclear Physics in China seminar: slides .
8/27/2020
- The paper on charge calibration with Compton scattering lead by Patrick McCormack has been posted to arXiv!
- Ben officially accepted a new position as Staff Scientist in the physics division at LBNL!
- The Chamberlain Fellowship advertisement for FY2021 can be found here . We are looking for multiple postdocs to join our group!
8/17/2020
- The paper on the statistics of generative adversarial networks with Anja Butter, Sascha Diefenbacher, Gregor Kasieczka, and Tilman Plehn has been posted to arXiv!
- Ben gave a talk on error mitigation for quantum computers at the QuantISED Quest collaboration meeting.
8/16/2020
- The paper on graph nets for supervised jet clustering with Xiangyang Ju has been posted to arXiv!
8/13/2020
- Ben was part of a panel about Snowmass at the annual Fermilab users meeting.
8/12/2020
- Kees gave an excellent (virtual) final REU presentation!
- Our URAP project is now available and advertised at BIDS - thank you Marsha Fenner and Maryam Vareth for your help!
8/10/2020
- First day of the computational frontier workshop for the HEP community planning meeting. Ben gave the opening talk :
8/7/2020
- Ben gave a talk at the DANCE workshop on ML for dark matter and neutrino physics. Title: Measurements using all available information with OmniFold :
8/6/2020
- The agenda for the Snowmass Computational Frontier workshop next week is finalized: August 10-11 . There are many interesting talks, especially in the machine learning and quantum computing parallel sessions!
8/5/2020
- The ATLAS CWoLa hunting paper was accepted for publication in PRL!
- Luc gave a great (virtual!) presentation of his summer work at the LBNL interns poster session today:
8/4/2020
- The error corrected quantum chemistry paper was accepted for publication in PRA!
