Publications

My work spans quantum algorithms, numerical analysis, scientific machine learning, and mathematical physics. Peer-reviewed articles and preprints are listed separately from my dissertation, reports, and early research. Links point to stable publisher or repository records. You can also view my Google Scholar profile.

Journal peer reviewed Preprint manuscript Record thesis or report

Preprints

4 works
  1. 2026
    Preprint

    Logical Resource Estimation for Quantum State Preparation with Compilation

    Diyi Liu, Hanyu Wang, Shuchen Zhu, Jason Cong, Wibe A. de Jong, Di Fang, Zhen Huang, Costin Iancu, and Chao Yang

    arXiv:2605.18877 [quant-ph]

    arXivPDFDOI
  2. 2025
    Preprint

    Magic State Distillation using Asymptotically Good Codes on Qudits

    Michael J. Cervia, Henry Lamm, Diyi Liu, Edison M. Murairi, and Shuchen Zhu

    arXiv:2512.21874 [quant-ph]

    arXivPDF
  3. 2025
    Preprint

    Block encoding with low gate count for second-quantized Hamiltonians

    Diyi Liu, Shuchen Zhu, Guang Hao Low, Lin Lin, and Chao Yang

    arXiv:2510.08644 [quant-ph]

    arXivPDF
  4. 2025
    Preprint

    High-order Magnus Expansion for Hamiltonian Simulation

    Di Fang, Diyi Liu, and Shuchen Zhu

    arXiv:2509.06054 [quant-ph]

    arXivPDF

Peer-reviewed articles

7 works
  1. 2025
    Journal

    Synthesis of single-qutrit circuits from Clifford+R gates

    Erik J. Gustafson, Henry Lamm, Diyi Liu, Edison M. Murairi, and Shuchen Zhu

    Physical Review A 112(6), 062414

    DOIarXiv
  2. 2025
    Journal

    Time-Dependent Hamiltonian Simulation via Magnus Expansion: Algorithm and Superconvergence

    Di Fang, Diyi Liu, and Rahul Sarkar

    Communications in Mathematical Physics 406, article 128

    DOIarXiv
  3. 2025
    Journal

    An efficient quantum circuit for block encoding a pairing Hamiltonian

    Diyi Liu, Weijie Du, Lin Lin, James P. Vary, and Chao Yang

    Journal of Computational Science 85, 102480

    DOIarXiv
  4. 2025
    Journal

    Learning the Local Density of States of a Bilayer Moire Material

    Diyi Liu, Alexander B. Watson, Michael Hott, Stephen Carr, and Mitchell Luskin

    Multiscale Modeling & Simulation 23(4), 1481–1514

    DOIarXiv
  5. 2024
    Journal

    Modeling of Electronic Dynamics in Twisted Bilayer Graphene

    Tianyu Kong, Diyi Liu, Mitchell Luskin, and Alexander B. Watson

    SIAM Journal on Applied Mathematics 84(3), 1011–1038

    DOIarXivCode
  6. 2022
    Journal

    Seeing moiré: convolutional network learning applied to twistronics

    Diyi Liu, Mitchell Luskin, and Stephen Carr

    Physical Review Research 4(4), 043224

    DOIarXiv
  7. 2022
    Journal

    Computing Free Energies with Fluctuation Relations on Quantum Computers

    Lindsay Bassman Oftelie, Katherine Klymko, Diyi Liu, Norm M. Tubman, and Wibe A. de Jong

    Physical Review Letters 129(13), 130603

    DOIarXiv

Dissertation, reports & earlier research

4 works
  1. 2025
    Dissertation

    Data-driven Approach and Analysis for Electronic Structure in Moiré Materials

    Diyi Liu

    Ph.D. dissertation, University of Minnesota, Mathematics · Advisor: Mitchell Luskin

    Permanent recordRepositoryPDF
  2. 2024
    White paper

    Mathematical and Computational Challenges in Quantum Computing

    Ahmad M. Alkadri, Abhinav Anand, Andrew Baczewski, et al., including Diyi Liu

    Institute for Pure and Applied Mathematics · Long Program white paper

    Official recordPDF
  3. 2019
    Early research

    Image Segmentation with Kernel Flow Algorithm

    Diyi Liu, Houman Owhadi, and Lei Zhang

    Undergraduate thesis presentation

    Presentation
  4. 2018
    Technical report

    Classification of Large-Scale Lyme Disease Data

    Ada Wang, Eric Chen, Rong Huang, Catherine Wahlenmayer, Diyi Liu, Denali Molitor, Jamie Haddock, and Deanna Needell

    Unpublished technical report

    DOIReport

In progress

Current projects

  • Continuum models for transition-metal dichalcogenides, with Alexander B. Watson and Mitchell Luskin.
  • Ground-state preparation with open quantum systems, with Marius Junge and Paul Cazeaux.