Reinforcement learning-enhanced protocols for coherent population-transfer in three-level quantum systems

Jonathon Brown; Pierpaolo Sgroi; Luigi Giannelli; Gheorghe Sorin Paraoanu; Elisabetta Paladino; Giuseppe Falci; Mauro Paternostro; Alessandro Ferraro

doi:10.1088/1367-2630/ac2393

Reinforcement learning-enhanced protocols for coherent population-transfer in three-level quantum systems

Jonathon Brown^*, Pierpaolo Sgroi, Luigi Giannelli, Gheorghe Sorin Paraoanu, Elisabetta Paladino, Giuseppe Falci, Mauro Paternostro, Alessandro Ferraro

^*Corresponding author for this work

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Abstract

We deploy a combination of reinforcement learning-based approaches and more traditional optimization techniques to identify optimal protocols for population transfer in a multi-level system. We constrain our strategy to the case of fixed coupling rates but time-varying detunings, a situation that would simplify considerably the implementation of population transfer in relevant experimental platforms, such as semiconducting and superconducting ones. Our approach is able to explore the space of possible control protocols to reveal the existence of efficient protocols that, remarkably, differ from (and can be superior to) standard Raman, stimulated Raman adiabatic passage or other adiabatic schemes. The new protocols that we identify are robust against both energy losses and dephasing.

Original language	English
Article number	093035
Number of pages	15
Journal	New Journal of Physics
Volume	23
Issue number	9
DOIs	https://doi.org/10.1088/1367-2630/ac2393
Publication status	Published - Sept 2021
MoE publication type	A1 Journal article-refereed

Funding

Original content from this work may be used under the terms of the . Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI. EU H2020 framework through Collaborative Projects TEQ 766900 COST Action CA15220 International Mobility Programme DfE-SFI Investigator Programme 15/IA/2864 Royal Society Wolfson Research Fellowship scheme RSWF\R3\183013 Engineering and Physical Sciences Research Council https://doi.org/10.13039/501100000266 EP/T028106/1 Academy of Finland https://doi.org/10.13039/501100002341 QuantERA grant SiUCs 731473 QuantERA Leverhulme Trust Research Project Grant UltraQute RGP-2018-266 Foundational Questions Institute Fund(“Exploring the fundamental limits set by thermodynamics in the quantum regime”) FQXi-IAF19-06 yes � 2021 The Author(s). Published by IOP Publishing Ltd on behalf of the Institute of Physics and Deutsche Physikalische Gesellschaft Creative Commons Attribution 4.0 licence

Keywords

condensed matter physics
quantum control
reinforcement learning

Access to Document

10.1088/1367-2630/ac2393

Brown_Reinforcement learning-enhanced protocols for coherent population-transfer in three-level quantum systemsFinal published version, 3.04 MBLicence: CC BY

Cite this

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title = "Reinforcement learning-enhanced protocols for coherent population-transfer in three-level quantum systems",

abstract = "We deploy a combination of reinforcement learning-based approaches and more traditional optimization techniques to identify optimal protocols for population transfer in a multi-level system. We constrain our strategy to the case of fixed coupling rates but time-varying detunings, a situation that would simplify considerably the implementation of population transfer in relevant experimental platforms, such as semiconducting and superconducting ones. Our approach is able to explore the space of possible control protocols to reveal the existence of efficient protocols that, remarkably, differ from (and can be superior to) standard Raman, stimulated Raman adiabatic passage or other adiabatic schemes. The new protocols that we identify are robust against both energy losses and dephasing.",

keywords = "condensed matter physics, quantum control, reinforcement learning",

author = "Jonathon Brown and Pierpaolo Sgroi and Luigi Giannelli and Paraoanu, \{Gheorghe Sorin\} and Elisabetta Paladino and Giuseppe Falci and Mauro Paternostro and Alessandro Ferraro",

note = "| openaire: EC/H2020/766900/EU//TEQ Funding Information: Original content from this work may be used under the terms of the . Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI. EU H2020 framework through Collaborative Projects TEQ 766900 COST Action CA15220 International Mobility Programme DfE-SFI Investigator Programme 15/IA/2864 Royal Society Wolfson Research Fellowship scheme RSWF\textbackslash{}R3\textbackslash{}183013 Engineering and Physical Sciences Research Council https://doi.org/10.13039/501100000266 EP/T028106/1 Academy of Finland https://doi.org/10.13039/501100002341 QuantERA grant SiUCs 731473 QuantERA Leverhulme Trust Research Project Grant UltraQute RGP-2018-266 Foundational Questions Institute Fund(“Exploring the fundamental limits set by thermodynamics in the quantum regime”) FQXi-IAF19-06 yes � 2021 The Author(s). Published by IOP Publishing Ltd on behalf of the Institute of Physics and Deutsche Physikalische Gesellschaft Creative Commons Attribution 4.0 licence Publisher Copyright: {\textcopyright} 2021 The Author(s). Published by IOP Publishing Ltd on behalf of the Institute of Physics and Deutsche Physikalische Gesellschaft.",

year = "2021",

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doi = "10.1088/1367-2630/ac2393",

language = "English",

volume = "23",

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AU - Brown, Jonathon

AU - Sgroi, Pierpaolo

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AU - Paraoanu, Gheorghe Sorin

AU - Paladino, Elisabetta

AU - Falci, Giuseppe

AU - Paternostro, Mauro

AU - Ferraro, Alessandro

N1 - | openaire: EC/H2020/766900/EU//TEQ Funding Information: Original content from this work may be used under the terms of the . Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI. EU H2020 framework through Collaborative Projects TEQ 766900 COST Action CA15220 International Mobility Programme DfE-SFI Investigator Programme 15/IA/2864 Royal Society Wolfson Research Fellowship scheme RSWF\R3\183013 Engineering and Physical Sciences Research Council https://doi.org/10.13039/501100000266 EP/T028106/1 Academy of Finland https://doi.org/10.13039/501100002341 QuantERA grant SiUCs 731473 QuantERA Leverhulme Trust Research Project Grant UltraQute RGP-2018-266 Foundational Questions Institute Fund(“Exploring the fundamental limits set by thermodynamics in the quantum regime”) FQXi-IAF19-06 yes � 2021 The Author(s). Published by IOP Publishing Ltd on behalf of the Institute of Physics and Deutsche Physikalische Gesellschaft Creative Commons Attribution 4.0 licence Publisher Copyright: © 2021 The Author(s). Published by IOP Publishing Ltd on behalf of the Institute of Physics and Deutsche Physikalische Gesellschaft.

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Y1 - 2021/9

N2 - We deploy a combination of reinforcement learning-based approaches and more traditional optimization techniques to identify optimal protocols for population transfer in a multi-level system. We constrain our strategy to the case of fixed coupling rates but time-varying detunings, a situation that would simplify considerably the implementation of population transfer in relevant experimental platforms, such as semiconducting and superconducting ones. Our approach is able to explore the space of possible control protocols to reveal the existence of efficient protocols that, remarkably, differ from (and can be superior to) standard Raman, stimulated Raman adiabatic passage or other adiabatic schemes. The new protocols that we identify are robust against both energy losses and dephasing.

AB - We deploy a combination of reinforcement learning-based approaches and more traditional optimization techniques to identify optimal protocols for population transfer in a multi-level system. We constrain our strategy to the case of fixed coupling rates but time-varying detunings, a situation that would simplify considerably the implementation of population transfer in relevant experimental platforms, such as semiconducting and superconducting ones. Our approach is able to explore the space of possible control protocols to reveal the existence of efficient protocols that, remarkably, differ from (and can be superior to) standard Raman, stimulated Raman adiabatic passage or other adiabatic schemes. The new protocols that we identify are robust against both energy losses and dephasing.

KW - condensed matter physics

KW - quantum control

KW - reinforcement learning

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Reinforcement learning-enhanced protocols for coherent population-transfer in three-level quantum systems

Abstract

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Keywords

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