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On the need for large Quantum depth

Published: 22 June 2020 Publication History

Abstract

Near-term quantum computers are likely to have small depths due to short coherence time and noisy gates. A natural approach to leverage these quantum computers is interleaving them with classical computers. Understanding the capabilities and limits of this hybrid approach is an essential topic in quantum computation. Most notably, the quantum Fourier transform can be implemented by a hybrid of logarithmic-depth quantum circuits and a classical polynomial-time algorithm. Therefore, it seems possible that quantum polylogarithmic depth is as powerful as quantum polynomial depth in the presence of classical computation.
Indeed, Jozsa conjectured that “Any quantum polynomial-time algorithm can be implemented with only O(logn) quantum depth interspersed with polynomial-time classical computations.” This can be formalized as asserting the equivalence of BQP and “BQNC BPP ”. On the other hand, Aaronson conjectured that “there exists an oracle separation between BQP and BPP BQNC .BQNC BPP and BPP BQNC are two natural and seeming incomparable ways of hybrid classical-quantum computation.
In this work, we manage to prove Aaronson’s conjecture and disproves Jozsa’s conjecture relative to an oracle. In fact, we prove a stronger statement that for any depth parameter d, there exists an oracle that separates quantum depth d and 2d+1 in the presence of classical computation. Thus, our results show that relative to oracles, doubling the quantum circuit depth indeed gives the hybrid model more power, and this cannot be traded by classical computation.

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cover image ACM Conferences
STOC 2020: Proceedings of the 52nd Annual ACM SIGACT Symposium on Theory of Computing
June 2020
1429 pages
ISBN:9781450369794
DOI:10.1145/3357713
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Publication History

Published: 22 June 2020

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Author Tags

  1. d-shuffling Simon's problem
  2. hybrid quantum-classical computer
  3. near-term quantum computer
  4. oracle separation
  5. small-depth quantum circuit

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  • Research-article

Funding Sources

  • Academia Sinica Career Development Award,
  • YoungScholar Fellowship Program by Ministry of Science and Tech-nology in Taiwan,
  • MOST QC project,

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STOC '20
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Overall Acceptance Rate 1,469 of 4,586 submissions, 32%

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  • (2024)Resource Optimization for Quantum Dynamics with Tensor Networks: Quantum and Classical AlgorithmsThe Journal of Physical Chemistry A10.1021/acs.jpca.4c03407128:32(6774-6797)Online publication date: 5-Aug-2024
  • (2024)Quantum Algorithms for the Study of Electronic Structure and Molecular Dynamics: Novel Computational ProtocolsComprehensive Computational Chemistry10.1016/B978-0-12-821978-2.00139-2(228-251)Online publication date: 2024
  • (2024)Syndrome decoding by quantum approximate optimizationQuantum Information Processing10.1007/s11128-024-04568-723:11Online publication date: 1-Nov-2024
  • (2024)Exact distributed quantum algorithm for generalized Simon’s problemActa Informatica10.1007/s00236-024-00455-x61:2(131-159)Online publication date: 1-Jun-2024
  • (2023)Gate-based quantum computing for protein designPLOS Computational Biology10.1371/journal.pcbi.101103319:4(e1011033)Online publication date: 12-Apr-2023
  • (2023)Quantum Depth in the Random Oracle ModelProceedings of the 55th Annual ACM Symposium on Theory of Computing10.1145/3564246.3585153(1111-1124)Online publication date: 2-Jun-2023
  • (2023)Quantum Computing with DartboardsThe Journal of Physical Chemistry A10.1021/acs.jpca.3c04262127:37(7853-7857)Online publication date: 7-Sep-2023
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  • (2022)Quantum advantage in learning from experimentsScience10.1126/science.abn7293376:6598(1182-1186)Online publication date: 10-Jun-2022
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