Embedding memory-efficient stochastic simulators as quantum trajectories
By exploiting the complexity intrinsic to quantum dynamics, quantum technologies promise a whole host of computational advantages. One such advantage lies in the field of stochastic modelling, where it has been shown that quantum stochastic simulators can operate with a lower memory overhead tha...
| Main Authors: | , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
2024
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| Online Access: | https://hdl.handle.net/10356/178324 |
| _version_ | 1826120381150265344 |
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| author | Elliott, Thomas J. Gu, Mile |
| author2 | School of Physical and Mathematical Sciences |
| author_facet | School of Physical and Mathematical Sciences Elliott, Thomas J. Gu, Mile |
| author_sort | Elliott, Thomas J. |
| collection | NTU |
| description | By exploiting the complexity intrinsic to quantum dynamics, quantum
technologies promise a whole host of computational advantages. One such
advantage lies in the field of stochastic modelling, where it has been shown
that quantum stochastic simulators can operate with a lower memory overhead
than their best classical counterparts. This advantage is particularly
pronounced for continuous-time stochastic processes; however, the corresponding
quantum stochastic simulators heretofore prescribed operate only on a
quasi-continuous-time basis, and suffer an ever-increasing circuit complexity
with increasing temporal resolution. Here, by establishing a correspondence
with quantum trajectories -- a method for modelling open quantum systems -- we
show how truly continuous-time quantum stochastic simulators can be embedded in
such open quantum systems, bridging this gap and obviating previous
constraints. We further show how such an embedding can be made for
discrete-time stochastic processes, which manifest as jump-only trajectories,
and discuss how viewing the correspondence in the reverse direction provides
new means of studying structural complexity in quantum systems themselves. |
| first_indexed | 2024-10-01T05:15:33Z |
| format | Journal Article |
| id | ntu-10356/178324 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T05:15:33Z |
| publishDate | 2024 |
| record_format | dspace |
| spelling | ntu-10356/1783242024-06-17T15:34:21Z Embedding memory-efficient stochastic simulators as quantum trajectories Elliott, Thomas J. Gu, Mile School of Physical and Mathematical Sciences Complexity Institute Nanyang Quantum Hub MajuLab, CNRS-UNS-NUS-NTU International Joint Research Unit, UMI No. 3654 Physics Computational advantages Continous time By exploiting the complexity intrinsic to quantum dynamics, quantum technologies promise a whole host of computational advantages. One such advantage lies in the field of stochastic modelling, where it has been shown that quantum stochastic simulators can operate with a lower memory overhead than their best classical counterparts. This advantage is particularly pronounced for continuous-time stochastic processes; however, the corresponding quantum stochastic simulators heretofore prescribed operate only on a quasi-continuous-time basis, and suffer an ever-increasing circuit complexity with increasing temporal resolution. Here, by establishing a correspondence with quantum trajectories -- a method for modelling open quantum systems -- we show how truly continuous-time quantum stochastic simulators can be embedded in such open quantum systems, bridging this gap and obviating previous constraints. We further show how such an embedding can be made for discrete-time stochastic processes, which manifest as jump-only trajectories, and discuss how viewing the correspondence in the reverse direction provides new means of studying structural complexity in quantum systems themselves. Agency for Science, Technology and Research (A*STAR) Ministry of Education (MOE) National Research Foundation (NRF) Published version This work was funded by the University of Manchester Dame Kathleen Ollerenshaw Fellowship; the Imperial College Borland Fellowship in Mathematics; the Lee Kuan Yew Endowment Fund (Postdoctoral Fellowship); Grants No. FQXi-RFP-1809 and No. FQXi-RFP-IPW-1903 from the Foundational Questions Institute and Fetzer Franklin Fund (a donor advised fund of Silicon Valley Community Foundation); the National Research Foundation, Singapore, and Agency for Science, Technology and Research under its QEP2.0 program (Grant No. NRF2021-QEP2-02-P06); and the Singapore Ministry of Education Tier 1 Grants No. RG190/17 and No. RG77/22 and Tier 2 Grant No. MOET2EP50221-0005. 2024-06-12T01:07:15Z 2024-06-12T01:07:15Z 2024 Journal Article Elliott, T. J. & Gu, M. (2024). Embedding memory-efficient stochastic simulators as quantum trajectories. Physical Review A, 109(2), 022434-. https://dx.doi.org/10.1103/PhysRevA.109.022434 2469-9926 https://hdl.handle.net/10356/178324 10.1103/PhysRevA.109.022434 2-s2.0-85186267100 2 109 022434 en NRF2021-QEP2-02-P06 RG190/17 RG77/22 MOET2EP50221-0005 Physical Review A © 2024 The Authors. Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article’s title, journal citation, and DOI. application/pdf |
| spellingShingle | Physics Computational advantages Continous time Elliott, Thomas J. Gu, Mile Embedding memory-efficient stochastic simulators as quantum trajectories |
| title | Embedding memory-efficient stochastic simulators as quantum trajectories |
| title_full | Embedding memory-efficient stochastic simulators as quantum trajectories |
| title_fullStr | Embedding memory-efficient stochastic simulators as quantum trajectories |
| title_full_unstemmed | Embedding memory-efficient stochastic simulators as quantum trajectories |
| title_short | Embedding memory-efficient stochastic simulators as quantum trajectories |
| title_sort | embedding memory efficient stochastic simulators as quantum trajectories |
| topic | Physics Computational advantages Continous time |
| url | https://hdl.handle.net/10356/178324 |
| work_keys_str_mv | AT elliottthomasj embeddingmemoryefficientstochasticsimulatorsasquantumtrajectories AT gumile embeddingmemoryefficientstochasticsimulatorsasquantumtrajectories |