AI/ML for Particle Accelerator, X-Ray Beamlines and Electron Microscopy

Name: AI/ML for Particle Accelerator, X-Ray Beamlines and Electron Microscopy
Start: 2021-11-01T10:00:00-05:00
End: 2021-11-03T16:00:00-05:00
Location: Virtual

1 Nov 2021, 10:00 → 3 Nov 2021, 16:00 US/Central

Virtual

Description

AI for Particle Accelerators, X-ray Beamlines, and Electron Microscopy Workshop @ ANL

Advances in instrumentation have dramatically increased the complexities associated with experimental facilities. This includes enhanced facility capabilities as well as a substantial increase in the data generated. Consequently, the control and diagnostics of these experimental facilities are becoming increasingly complex, and the large output data streams necessitate smarter and more automated management and analyses of the data. Artificial Intelligence (AI) methods hold the promise of substantially improved management, control, and data analyses with the potential to dramatically increase experimental efficiencies as well as expanding and accelerating scientific discoveries.

Argonne is the home to world-leading facilities such as the Advanced Photon Source (APS), the Argonne Tandem Linear Accelerator (ATLAS), the Argonne Wakefield Accelerator (AWA), and the Electron Microscopy Center at the Center for Nanoscale Materials (CNM). In order to highlight AI opportunities in these facilities, Argonne is hosting a workshop on AI for with participants drawn from 3 communities: particle accelerators, X-ray beamlines and electron microscopy. The goals of the workshop are:

review problems in control, diagnostics, and data management that can be remedied by AI tools
explore commonalities in problems and potential AI solutions across the 3 communities: particle accelerators, X-ray beamlines, and electron microscopy
stimulate interactions across the communities to better leverage expertise and resources.

The workshop will be held virtually Nov. 1 – 3, 2021. The topics covered will be:

Tuning and Control
Data Analytics
Imaging and Data Management
Failure Detection, Virtual Diagnostics, and Digital Twins
Autonomous Discovery
Data, Computing, and Modeling

Each topic will open with invited presentations that give an overview of the current state, and set the stage for discussions – the discussions are the central part of the workshop and we will encourage broad and lively participation in the discussions.

The workshop is open to all of ANL. Registration information will be announced shortly.

WORKSHOP ORGANIZERS FROM EACH OF THE THREE COMMUNITIES

Particle Accelerators

X-ray Beamlines

Electron Microscopy

Michael Borland (APS)

Brahim Mustapha (PHY)

John Power (HEP)

Olle Heinonen (PSE)

Nicholas Schwarz (APS)

Martin Holt (NST)

Jianguo Wen (NST)

Charudatta Phatak (MSD)

Participants

Alec Sandy
Alex Lumpkin
Alexander Hexemer
Alexander Scheinker
Allison Mis
alvaro mayagoitia
Aniket Tekawade
Anthony Avarca
Anthony Tran
Arun Bommannavar
Athula Wickremasinghe
Auralee Edelen
Barry Lai
Benjamin Blaiszik
Brahim Mustapha
Brendan Chandler
Buduka Ogonor
Calem Hoffman
Charudatta Phatak
Chengiun Sun
Chi Young Moon
Chia-Hao Lee
Chris Benmore
Chris Tennant
Chunguang Jing
Clayton Dickerson
Colin Ophus
Curt preissner
Daniel Haskel
Daniel Ratner
David Potterveld
Davis Unruh
Denis Keane
Dillon Merenich
Doga Gursoy
Elaine Chandler
Elina Kasman
Eric Stach
Erik Gottschalk
Fanzhi Su
Ganesh Sivaraman
ganesh tiwari
Gary Navrotski
Guobao Shen
Gwanghui Ha
Hairong Shang
Hannah Parraga
Henry Cuzco
Henry Smith
Howard Yanxon
Hua Zhou
Huihuo Zheng
Ian Sugrue
Ignacia Guerra
Ihar Lobach
Jan Strube
Jason St. John
Jayden Plumb
Jeffrey Huang
Jeffrey Larson
Jianguo Wen
Jicheng Guo
Jie Xu
Joe Sullivan
John Byrd
John Carwardine
John Power
Jonathan Edelen
Jonathan Jarvis
Jonathan Schwartz
Jose L. Martinez-Marin
Joydeep Munshi
Jun-Sang Park
Kamlesh Suthar
Kent Wootton
Kevin Yager
Kibaek Kim
Kishansingh Rajput
Kiyomi Seiya
Krzysztof Lazarski
Kyle Hazelwood
Louis Emery
Luca Rebuffi
Malachi Schram
Malcolm Capel
Marcus Noack
Maria Chan
Martin Holt
Mathew Cherukara
Matt Amthor
Max Wyman
MEIMEI LI
Michael Borland
Michael Caple
Michael Carpenter
Nestor Zaluzec
Nicholas Schwarz
Nikita Kuklev
Nina Andrejevic
Noor Mahmud
Olga Antipova
Olivier Grasdijk
Olle Heinonen
Patric Den Hartog
Paul Voyles
Pinshane Huang
Pooja Swamy
Rama Vasudevan
Ryan Roussel
Seongyeol Kim
Sergey Antipov
Shefali Saxena
Sheikh Mashrafi
Sinisa Veseli
Stefan Wild
Steve Heald
Subramanian Sankaranarayanan
tao zhou
Tekin Bicer
Tia Miceli
Tianzhe Xu
Venkatram Vishwanath
Vinay Amatya
Volker Rose
Wanming Liu
WEI HOU TAN
Willem Blokland
William Pellico
Xiaowei Wu
Xingfu Wu
Xueying Lu
Xuli Wu
Yi Jiang
Yigit Yucesan
Yine Sun
Yipeng Sun
Yong Choi
Yudong Yao
Yuming Xiao
Yuzi Liu
Zhan Zhang
Zhi Qiao
Zou Finfrock
Zunping Liu

Janet Bergman

jbergman@anl.gov

brahim@anl.gov

Monday, 1 November
- 10:00 → 12:15
  Opening Session: Tuning and Control
  
  Convener: Michael Borland (Argonne National Laboratory)
  - 10:00
    
    Opening Remarks 5m
    
    Speakers: Brahim Mustapha (Argonne National Laboratory), Olle Heinonen (Argonne National Laboratory)
    
    AI-ML-Workshop-Opening-Remarks.pdf
  - 10:05
    
    Online tuning of particle accelerators with reinforcement learning and comprehensive surrogate models 25m
    
    Speaker: Auralee Edelen (SLAC)
    
    20211101_AIML_ANL_Edelen.pdf
    
    A.Edelen_AIML@ANL.pdf
  - 10:30
    
    Automated Experiments, Machine Learning and Reinforcement Learning for tuning and control applications in microscopy 25m
    
    Speaker: Rama Vasudevan (Oak Ridge National Laboratory)
    
    rkv_argonne.pdf
    
    R.Vasudevan_AIML@ANL.pdf
  - 10:55
    
    Bayesian Techniques for Accelerator Characterization and Control 25m
    
    Speaker: Ryan Roussel (University of California Los Angeles)
    
    Roussel_AWA_AI_ML_workshop.pdf
    
    R.Roussel_AIML@ANL.pdf
  - 11:20
    
    Simultaneous online optimization of dynamic acceptance and lifetime for APS 20m
    
    Speaker: Yipeng Sun (Argonne National Laboratory)
    
    YipengSun-2021Nov.pdf
  - 11:40
    
    Open / Speaker Panel Discussion 35m
- 12:15 → 13:30
  
  Lunch Break 1h 15m
- 13:30 → 15:45
  Session II: Data Analytics
  
  Convener: Martin Holt (ANL)
  - 13:30
    
    Accelerating atomic-scale characterization by combining theory and AI/ML 25m
    
    Speaker: Maria Chan (Argonne National Laboratory)
    
    M.Chan_AIML@ANL.pdf
  - 13:55
    
    Solving X-ray and Cryo-EM Inverse Problems with Deep Learning 25m
    
    Speaker: Daniel Ratner (SLAC)
    
    Argonne_InverseProblems_Nov2021.pptx
    
    D.Ratner_AIML@ANL.pdf
  - 14:20
    
    Supervised and Unsupervised Machine Learning for Large, Noisy STEM Data 25m
    
    Speaker: Paul Voyles (University of Wisconsin - Madison )
    
    ML for STEM ANL AI Workshop 2021.pdf
    
    P.Voyles_AIML@ANL.pdf
  - 14:45
    
    Automated x-ray PDF analysis and ML modeling 25m
    
    Speaker: Chris Benmore (Argonne National Laboratory)
    
    Benmore_ML_X-ray_Oct2021.pdf
    
    C.Benmore_AIML@ANL.pdf
  - 15:10
    
    Open / Speaker Panel Discussion 35m
Tuesday, 2 November
- 10:00 → 12:30
  Session III: Failure Detection, Virtual Diagnostics & Digital Twin
  
  Convener: John Power (Argonne National Lab)
  - 10:00
    
    Applications of Neural Networks for Anomaly Detection in Particle Accelerators 25m
    
    Speaker: Jonathan Edelen (RadiaSoft LLC)
    
    J.Edelen_AIML@ANL.pdf
    
    J.Edelen_AIML@ANL_Talk.pdf
  - 10:25
    
    Data-Driven Detection, Isolation, Identification, and Prediction of Accelerator Fault Events 25m
    
    Speaker: Chris Tennant (Jefferson Lab)
    
    ANL_TENNANT_11022021.pdf
    
    C.Tennant_AIML@ANL.pdf
  - 10:50
    
    Adaptive Machine Learning for Control and Virtual Diagnostics of Time-Varying Particle Accelerator Systems and Beams 25m
    
    Speaker: Alexander Scheinker (Los Alamos National Laboratory)
    
    A.Scheinker_AIML@ANL.pdf
    
    Scheinker_ANL_2021_vFinal.pdf
  - 11:15
    
    A Digital Twin for Spatiotemporal Experiments 25m
    
    Speaker: Subramanian Sankaranarayanan (Argonne National Laboratory)
    
    S.Sankara_AIML@ANL.pdf
  - 11:40
    
    Uncertainty aware anomaly detection to predict errant beam pulses in the SNS accelerator 15m
    
    Speaker: Malachi Schram (Thomas Jefferson National Accelerator Facility)
    
    M.Schram_AIML@ANL.pdf
    
    M.Schram_AIML@ANL_Talk_v4.pdf
  - 11:55
    
    Open / Speaker Panel Discussion 35m
- 12:30 → 13:30
  
  Lunch Break 1h
- 13:30 → 15:45
  Session IV: Imaging and Data Processing
  
  Convener: Charudatta Phatak (ANL)
  - 13:30
    
    Using automated image analysis to understand nanoparticle coarsening, ripening and evaporation at the nanoscale 25m
    
    Speaker: Eric Stach (University of Pennsylvania)
  - 13:55
    
    Phase retrieval with deep learning network and automatic differentiation 25m
    
    Speaker: Tao Zhou (Argonne National Laboratory)
    
    T.Zhou_AIML@ANL.pdf
  - 14:20
    
    Overview of AI/ML@APS beamlines 25m
    
    Speaker: Mathew Cherukara (Argonne National Laboratory)
  - 14:45
    
    Accelerated Data Analysis Workflows for Ptychography using Remote Leadership Computing Resources 25m
    
    Speaker: Tekin Bicer (Argonne National Laboratory)
    
    T.Bicer_AIML@ANL.pdf
  - 15:10
    
    Open / Speaker Panel Discussion 35m
Wednesday, 3 November
- 10:00 → 12:15
  Session V: Autonomous Discovery
  
  Convener: Jianguo Wen (ANL)
  - 10:00
    
    Imaging 2D materials, atom by atom, on the million-atom scale 25m
    
    Speaker: Pinshane Huang (University of Illinois Urbana-Champaign)
    
    P.Huang_AIML@ANL.pdf
  - 10:25
    
    Recent Progress in Autonomous X-ray Scattering 25m
    
    Speaker: Kevin Yager (Brookhaven National Laboratory)
    
    K.Yager_AIML@ANL.pdf
  - 10:50
    
    Domain-Aware Gaussian Processes and High-Performance Mathematical Optimization for Stochastic Function Approximation and Autonomous Data Acquisition 25m
    
    Speaker: Marcus Noack (Lawrence Berkeley National Laboratory)
    
    M.Noack_AIML@ANL.pdf
  - 11:15
    
    Advanced Robotics and Software Defined Automation to Speed Materials Discovery 25m
    
    Speaker: Ben Blaiszik (University of Chicago)
  - 11:40
    
    Open / Speaker Panel Discussion 35m
- 12:15 → 13:30
  
  Lunch Break 1h 15m
- 13:30 → 15:45
  Closing Session: Data, Computing and Modeling
  
  Convener: Nicholas Schwarz (APS / ANL)
  - 13:30
    
    Programmatic and Deep Learning Analysis Pipelines for 4D-STEM Materials Science Experiments 25m
    
    Speaker: Colin Ophus (Lawrence Berkeley National Laboratory)
    
    C.Ophus_AIML@ANL.pdf
  - 13:55
    
    MLExchange, bringing machine learning to the beamline 25m
    
    Speaker: Alexander Hexemer (Lawrence Berkeley National Laboratory)
    
    A.Hexemer_AIML@ANL.pdf
  - 14:20
    
    The FNAL accelerator complex initial ML efforts and a conceptual AI roadmap for operations 25m
    
    Speaker: Tia Miceli (NMSU)
    
    FNAL_for_Argonne_workshop.pdf
    
    T.Miceli_AIML@ANL.pdf
  - 14:45
    
    Surrogate Models for Beam Transport and Particle Tracking 20m
    
    Speaker: Jose Martinez (Argonne National Laboratory)
    
    J.Martinez_AIML@ANL.pdf
  - 15:05
    
    Open / Speaker Panel Discussion 35m
  - 15:40
    
    Closing Remarks 5m
    
    Speakers: Brahim Mustapha (Argonne National Laboratory), Olle Heinonen (Argonne National Laboratory)