IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v693y2026ics037843712600275x.html

Hybrid real-imaginary time evolution for low-depth Hamiltonian simulation in quantum optimization

Author

Listed:
  • Li, Fei
  • Li, Xiao-Wei

Abstract

Counterdiabatic (CD) driving is a powerful technique for accelerating adiabatic quantum computing. However, it becomes self-limiting in complex optimizations like the Sherrington–Kirkpatrick model: long evolution times T needed to traverse crossings force the CD strength to scale as 1/T, causing it to vanish before convergence and wasting the quantum resources invested in its implementation. We break this trade-off with a Hybrid adaptive variational quantum dynamics simulation (HAVQDS). HAVQDS combines adaptive real-time evolution for circuit compression with imaginary-time steps that suppress excitations at no extra gate cost. For the SK model (6–14 qubits), HAVQDS achieves higher approximation ratios than adiabatic or CD approaches, while reducing CNOT counts by 1–2 orders of magnitude, and avoids barren plateaus, ensuring non-vanishing parameter updates for scalable quantum optimization.

Suggested Citation

  • Li, Fei & Li, Xiao-Wei, 2026. "Hybrid real-imaginary time evolution for low-depth Hamiltonian simulation in quantum optimization," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 693(C).
    • Handle: RePEc:eee:phsmap:v:693:y:2026:i:c:s037843712600275x
    DOI: 10.1016/j.physa.2026.131539
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S037843712600275X
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2026.131539?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    More about this item

    Keywords

    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:693:y:2026:i:c:s037843712600275x. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.