Stefan Seritan

Quantum Information Science

Author profile picture

Quantum Information Science


I have a background in making quantum chemistry run fast on classical computers; since joining Sandia National Laboratories in 2020, I’ve pivoted to trying to solve this problem with quantum computers instead. I split my time between working on characterization and benchmarking protocols with the Quantum Performance Laboratory (QPL) as one of the developers of PyGSTi, as well as on developing quantum simulation algorithms for chemistry and physics with the Quantum Applications and Algorithms Collaboratory (QuAAC). One of my current research interests is building systematic, scalable application-inspired benchmarks for quantum computers.


Ph.D.Physical ChemistryStanford University2020
B.S.Chemistry & BiochemistryUC Santa Barbara2015

Research Interests

  • Quantum Characterization, Validation, and Verification
  • Fault-Tolerant Quantum Simulation Algorithms
  • Application-inspired Benchmarking

Organization & Leadership Roles

Lead Developer of PyGSTi
CSRI CA Intern Coordinator(2022-2023)
QuAAC Seminar Coordinator(2022-present)


  1. Two-Qubit Gate Set Tomography with Fewer Circuits. K.M. Rudinger, C.I. Ostrove, S.K. Seritan, M.D. Grace, E. Nielsen, R.J. Blume-Kohout, K.C. Young. arXiv (2023). DOI: 10.48550/arXiv.2307.15767
  2. Quantifying T-gate-count improvements for ground-state-energy estimation with near-optimal state preparation. S. Pathak, A. Russo, S. Seritan, A. Baczewski. Phys. Rev. A 107, L040601 (2023). DOI: 10.1103/PhysRevA.107.L040601
  3. Scalable Randomized Benchmarking of Quantum Computers Using Mirror Circuits. T. Proctor, S. Seritan, K. Rudinger, E. Nielsen, R. Blume-Kohout, K. Young. Phys. Rev. Lett. 129, 150502 (2022). DOI: 10.1103/PhysRevLett.129.150502