Skip to content
DraconiticResearch
Search Sources API
184,937 studies31 sourcesUpdated 34 min ago
PreprintarXiv licencearXiv

Fast Cliffords When Your Quantum Memory Is Full

  • Marten Folkertsma
  • Ian Mertz
  • Sergii Strelchuk
  • Sathyawageeswar Subramanian
Open at sourcePDFDOICite

Abstract

Additional qubits can reduce the depth of a quantum circuit by providing workspace for parallel computation, but standard constructions assume that this workspace is initialized in a known state. In this work we study catalytic implementations, i.e. asking whether dirty qubits can instead be used provided that their joint state including any entanglement with other registers is restored exactly at the end of the computation. We show that every n-qubit Clifford circuit has a catalytic implementation of depth O(log n) using O(n2/log2 n) catalytic qubits and no clean qubits, matching the asymptotic depth achievable when clean workspace is available. We extend this approach to diagonal elements of any fixed level Ck of the Clifford hierarchy, which admit catalytic implementations of depth O(log(n+1)) with O(nk/log(n)) gates and O(nk/log2(n)) catalytic qubits, as well as to semi-Clifford Gates.

Related

  1. Violating a Bell Inequality: What to Do When You Lose Your Quantum System
    Xinyu Xu, Yuqing Li, Mingze Xu +1
    arXivPreprintarXiv licenceFull textQuantum physics & quantum informationarXiv
  2. Is Your AI Fast Enough to Run a Fusion Reactor?
    Nathaniel Chen, Andrew Rothstein, Ricardo Shousha +4
    arXivPreprintCC BY 4.0Full textPlasma physicsarXiv
  3. Know Your Qubits, Know Your Users: Personas for Quantum Software
    Lukas Schmidbauer, Joshua Ammermann, Laura Schulz +5
    arXivPreprintCC BY 4.0Full textQuantum physics & quantum informationarXiv
  4. Does Your Self-Consistent Field Program Know How Wrong It Is? Introducing Quantum Chemistry Uncertainty Propagation.
    Anna Diaz Farias, Shalith C Jayasekara, Jonathan M Waldrop +3
    The journal of physical chemistry lettersPeer-reviewedCC BY-NC-NDFull textAtomic, molecular & optical physicsEurope PMC
  5. Fast Neural Noise Stabilizes Associative Memory against Slow Synaptic Noise
    Tomoki Kurikawa, Kunihiko Kaneko
    arXivPreprintCC BY-NC-SA 4.0Full textBiological & medical physicsCondensed matterarXiv

Cite

BibTeXRIS
BibTeX
@misc{folkertsma2026fast,
  title = {{Fast Cliffords When Your Quantum Memory Is Full}},
  author = {Marten Folkertsma and Ian Mertz and Sergii Strelchuk and Sathyawageeswar Subramanian},
  howpublished = {arXiv},
  year = {2026},
  month = sep,
  doi = {10.48550/arxiv.2609.40144},
  eprint = {2609.40144},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2609.40144},
}
RIS
TY  - UNPB
TI  - Fast Cliffords When Your Quantum Memory Is Full
AU  - Marten Folkertsma
AU  - Ian Mertz
AU  - Sergii Strelchuk
AU  - Sathyawageeswar Subramanian
PY  - 2026
DA  - 2026/09/30
PB  - arXiv
DO  - 10.48550/arxiv.2609.40144
UR  - https://arxiv.org/abs/2609.40144
AB  - Additional qubits can reduce the depth of a quantum circuit by providing workspace for parallel computation, but standard constructions assume that this workspace is initialized in a known state. In this work we study catalytic implementations, i.e. asking whether dirty qubits can instead be used provided that their joint state including any entanglement with other registers is restored exactly at the end of the computation. We show that every n-qubit Clifford circuit has a catalytic implementation of depth O(log n) using O(n^2/log^2 n) catalytic qubits and no clean qubits, matching the asymptotic depth achievable when clean workspace is available. We extend this approach to diagonal elements of any fixed level C_k of the Clifford hierarchy, which admit catalytic implementations of depth O(log(n+1)) with O(n^k/log(n)) gates and O(n^k/log^2(n)) catalytic qubits, as well as to semi-Clifford Gates.
ER  -