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Research

Overview #

I study quantum algorithms for many-body state preparation, simulation, and optimization, trying to understand how physical structure can be used to guide algorithm and circuit design. My current work focuses on:

  • Gibbs-state preparation

    • Spectral core-tail architecture. Combines a structured thermal core with a unitary tail, yielding local-error bounds under explicit locality and thermal-response assumptions. Moreover, we provide a systematic Hamiltonian-residual reduction procedure for treating weak deformations around an exactly solvable Hamiltonian.
    • Matrix-product-state-assisted variational preparation. Uses matrix product states to optimize thermal purification circuits without full-statevector storage. Our benchmarks reveal trade-offs between thermal accuracy, circuit entropy capacity, and the classical costs of MPS assisted optimization.

  • Quantum optimization for protein structure prediction

    • Face-centered cubic lattice encoding. Represents protein conformations on an FCC lattice and optimizes them using polynomial-fitting or constrained variational methods. Experiments on noisy IBM processors recovered minimum-energy lattice conformations for a six-residue peptide sequence.
    • Problem-agnostic quantum circuits. Combines quantum sampling with classical energy evaluation, avoiding explicit Hamiltonian construction and ancillary qubits. Benchmarks sequences of up to 26 residues across three different lattice models (tetrahedral, BCC, and FCC), including both first- and second-nearest-neighbor interactions.

My earlier theoretical-physics research examined how symmetry and band topology govern transport in Weyl and Dirac semimetals, including chiral-anomaly-induced nonlinear Hall response and tunable spin-charge conversion. I also studied anomaly-free and leptophobic dark matter models.

I welcome collaborations and discussions. Please feel free to contact me through the links on my homepage.

Publications #

† Equal contribution among the marked authors. * All authors contributed equally and are listed alphabetically.

  1. R.-H. Li, Spectral Core-Tail Architecture for Locally Certified Gibbs-State Preparation, arXiv:2609.09291 (2026), under review.
  2. K. Zheng, Y. Zhou, R.-H. Li, Z. Ding, Z. Liang, and S. Li, Q-Score: A Quantum-Native Scoring Function for Molecular Docking, arXiv:2607.09737 (2026).
  3. F. Cumbo, R.-H. Li, B. Raubenolt, J. Joshi, A. K. M. Masum, S. Aygun, and D. Blankenberg, Quantum hyperdimensional computing: a foundational paradigm for quantum neuromorphic architectures, npj Unconventional Computing 3, 21 (2026).
  4. R.-H. Li, S. Valgushev, and K. Najafi, Matrix-product-state-assisted variational Gibbs-state preparation, arXiv:2510.23546 (2025), under review.
  5. H. Linn†, R.-H. Li†, A. Holden, A. A. Saki, F. DiFilippo, T. Radivoyevitch, D. Blankenberg, L. García-Álvarez, and G. Johansson, Efficient Quantum Protein Structure Prediction with Problem-Agnostic Ansatzes, arXiv:2509.18263 (2025), under review.
  6. R.-H. Li†, H. Doga†, B. Raubenolt†, S. Mostame, N. DiSanto, F. Cumbo, J. Joshi, H. Linn, M. Gaffney, A. Holden, V. Kulkarni, V. Chaudhary, K. M. Merz Jr, A. A. Saki, T. Radivoyevitch, F. DiFilippo, J. Qin, O. Shehab, and D. Blankenberg, Quantum Algorithm for Protein Structure Prediction Using the Face-Centered Cubic Lattice, arXiv:2507.08955 (2025), under review.
  7. X. Li, V. R. Kulkarni, J. Nana, S. Pu, N. Xie, Q. Guan, R.-H. Li, S. Zhang, S. Xu, D. Blankenberg, and V. Chaudhary, Quantum Circuit Optimization for Protein Structure Prediction, 2025 55th Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshops (DSN-W), pp. 220–223 (2025).
  8. K. Blekos*, D. Brand*, A. Ceschini*, C.-H. Chou*, R.-H. Li*, K. Pandya*, and A. Summer*, A review on Quantum Approximate Optimization Algorithm and its variants, Physics Reports 1068, 1–66 (2024).
  9. R.-H. Li†, P. Shen†, and S. S.-L. Zhang, Tunable spin-charge conversion in class-I topological Dirac semimetals, APL Materials 10, 041108 (2022).
  10. R.-H. Li, O. G. Heinonen, A. A. Burkov, and S. S.-L. Zhang, Nonlinear Hall effect in Weyl semimetals induced by chiral anomaly, Physical Review B 103, 045105 (2021).
  11. P. Fileviez Pérez*, E. Golias*, R.-H. Li*, C. Murgui*, and A. D. Plascencia*, Anomaly-free dark matter models, Physical Review D 100, 015017 (2019).
  12. P. Fileviez Pérez*, E. Golias*, R.-H. Li*, and C. Murgui*, Leptophobic dark matter and the baryon number violation scale, Physical Review D 99, 035009 (2019).

Talks and panels #

Invited talks and panels #

Selected talks and tutorials #

Conference talks #

Outreach and other talks #

  • Introduction to (Qiskit) Quantum Machine Learning — Qiskit Fall Fest, CWRU, 2022 (co-organizer). Slides · Demo.
  • Introduction to Quantum Approximate Optimization Algorithm — QOSF Mentorship Program meeting, 2022. Slides.
  • Majorana Zero Modes in a Kitaev Chain — CMP Journal Club, CWRU, Spring 2022. Slides.
  • Fantastic Dark Matter and Where to Find Them: Indirect Detection — CERCA Weekly Seminar, Spring 2019. Slides.
  • Baryon Number Violation and Leptophobic Dark Matter — CERCA Weekly Seminar, Fall 2018. Slides.
  • Quantum Corrections in Left-Right Symmetric Seesaw Mechanisms — Honours final presentation, October 2016. Slides.

Miscellaneous Notes #