Award Abstract # 2230111
CyberTraining: Implementation: Small: Interactive and Integrated Training for Quantum Application Developers across Platforms

NSF Org: OAC
Office of Advanced Cyberinfrastructure (OAC)
Recipient: KENT STATE UNIVERSITY
Initial Amendment Date: August 18, 2022
Latest Amendment Date: July 24, 2024
Award Number: 2230111
Award Instrument: Standard Grant
Program Manager: Juan Li
jjli@nsf.gov
 (703)292-2625
OAC
 Office of Advanced Cyberinfrastructure (OAC)
CSE
 Directorate for Computer and Information Science and Engineering
Start Date: November 1, 2022
End Date: October 31, 2025 (Estimated)
Total Intended Award Amount: $500,000.00
Total Awarded Amount to Date: $510,000.00
Funds Obligated to Date: FY 2022 = $500,000.00
FY 2023 = $10,000.00
History of Investigator:
  • Qiang Guan (Principal Investigator)
    qguan@kent.edu
  • Barry Dunietz (Co-Principal Investigator)
  • Ran Li (Co-Principal Investigator)
  • Michael Strickland (Former Co-Principal Investigator)
Recipient Sponsored Research Office: Kent State University
1500 HORNING RD
KENT
OH  US  44242-0001
(330)672-2070
Sponsor Congressional District: 14
Primary Place of Performance: Kent State University
1500 HORNING RD
KENT
OH  US  44242-0001
Primary Place of Performance
Congressional District:
14
Unique Entity Identifier (UEI): KXNVA7JCC5K6
Parent UEI:
NSF Program(s): CyberTraining - Training-based,
FET-Fndtns of Emerging Tech,
Special Initiatives,
PROJECTS,
PHYSICS AT THE INFO FRONTIER
Primary Program Source: 01002223DB NSF RESEARCH & RELATED ACTIVIT
01002324DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s): 7203, 7569, 7928, 9251
Program Element Code(s): 044Y00, 089Y00, 164200, 197800, 755300
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.041, 47.049, 47.070

ABSTRACT

Along with the evolution of actual quantum computers from industry, like IBM, IonQ, Rigetti, and D-Wave, quantum computing research has rapidly grown in the past few years. However, the industry and academia lack mature and effective workforce training plans for cutting across multiple disciplines, the most relevant being physics, computer and information science, and electrical engineering. The project aims to deliver a project-oriented training program that can assist the scientific research workforce development for quantum computing cyberinfrastructure and help foster broad adoption of quantum computing cyberinfrastructure to advance fundamental research. The proposed training program targets students and early-stage researchers, e.g., undergraduates, graduate students, and postdocs, who are interested in quantum computing systems, quantum applications, cyber-physical systems, Quantum Physics, Quantum Chemistry, and quantum machine learning. A long-term collaboration with DoE national laboratories will ensure broad adoption of quantum computing infrastructure by the research community to catalyze significant research advances and train professional cyberinfrastructure contributors to optimize the current hardware and software stack. The proposed cyber training programs will accommodate 80+ trainees participating in cutting-edge research projects each year. These programs will expedite adopters and users to understand how to use the quantum computing cyberinfrastructure and enable them to advance research in CISE, BIO, ENG, and MPS' core areas.

This project builds upon existing knowledge, data, and tools to create tailored, high-impact, engaging, collaborative, and integrated training modules for quantum computing cyberinfrastructure research workforce Development. Three training projects are built upon the PI and co-PI's innovative research on quantum error characterization and modeling, visual analytics of the quality of the quantum hardware system and quantum compiler optimizations, and reliability assessment of the quantum applications. Each training module will focus on one mini-project. With the aim to enhance the trainee's design and implementation capability, problem-solving skills, and critical thinking ability, the training modules will be delivered with multiple lessons on the background of the problem, literature study, data collection and processing, methodology, evaluations of the solutions, and hands-on experiments. The deliveries of the proposed training program will include: 1) a new course on "ST: Fundamentals of Quantum Computing Systems"; 2) a project-based short course plus its long-term maintenance and support; 3) hands-on tutorials based on the training projects; and 4) multiple research topics for undergraduate and graduate capstone projects. The long-term goal of this project is to boost the adoption of new quantum computing cyberinfrastructure to multidisciplinary students and researchers from different STEM domains.

This award by the Office of Advanced Cyberinfrastructure is jointly supported by the Physics at the Information Frontier program in the Division of Physics within the Directorate for Mathematical and Physical Sciences, the Division of Chemistry in the Directorate for Mathematical and Physical Sciences, the Division of Computing and Communication Foundations in the Computer and Information Science and Engineering Directorate, and the Division of Chemical, Bioengineering, Environmental, and Transport Systems in the Directorate for Engineering.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH

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Giusto, Edoardo and Dri, Emanuele and Montrucchio, Bartolomeo and Baheri, Betis and Guan, Qiang and Tiwari, Devesh and Rech, Paolo "Quantum Computing Reliability: Problems, Tools, and Potential Solutions" DSN , 2023 https://doi.org/10.1109/DSN-S58398.2023.00015 Citation Details
Senapati, Priyabrata and Athawale, Tushar M. and Pugmire, David and Guan, Qiang "Advancing Comprehension of Quantum Application Outputs: A Visualization Technique" Proceedings of the 2023 International Workshop on Quantum Classical Cooperative , 2023 https://doi.org/10.1145/3588983.3596689 Citation Details

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