Parallel quantum trajectories via forking for sampling without redundancy

Daniel K. Park, Ilya Sinayskiy, Mark Fingerhuth, Francesco Petruccione, June Koo Kevin Rhee

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)

Abstract

The computational cost of preparing a quantum state can be substantial depending on the structure of data to be encoded. Many quantum algorithms require repeated sampling to find the answer, mandating reconstruction of the same input state for every execution of an algorithm. Thus, the advantage of quantum computation can diminish due to redundant state initialization. We present a framework based on quantum forking that bypasses this fundamental issue and expedites a family of tasks that require sampling from independent quantum processes. Quantum forking propagates an input state to multiple quantum trajectories in superposition, and a weighted power sum of individual results from each trajectories is obtained in one measurement via quantum interference. The significance of our work is demonstrated via applications to implementing non-unitary quantum channels, studying entanglement and benchmarking quantum control. A proof-of-principle experiment is implemented on the IBM and Rigetti quantum cloud platforms.

Original languageEnglish
Article number083024
JournalNew Journal of Physics
Volume21
Issue number8
DOIs
Publication statusPublished - 2019 Aug 12

Bibliographical note

Publisher Copyright:
© 2019 The Author(s). Published by IOP Publishing Ltd on behalf of the Institute of Physics and Deutsche Physikalische Gesellschaft.

All Science Journal Classification (ASJC) codes

  • Physics and Astronomy(all)

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