Differentiable master equation solver for quantum device characterization
Differentiable models of physical systems provide a powerful platform for gradient-based algorithms, with particular impact on parameter estimation and optimal control. Quantum systems present a particular challenge for such characterization and control, owing to their inherently stochastic nature a...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
American Physical Society
2024-11-01
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| Series: | Physical Review Research |
| Online Access: | http://doi.org/10.1103/PhysRevResearch.6.043175 |
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| _version_ | 1846162239434784768 |
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| author | D. L. Craig N. Ares E. M. Gauger |
| author_facet | D. L. Craig N. Ares E. M. Gauger |
| author_sort | D. L. Craig |
| collection | DOAJ |
| description | Differentiable models of physical systems provide a powerful platform for gradient-based algorithms, with particular impact on parameter estimation and optimal control. Quantum systems present a particular challenge for such characterization and control, owing to their inherently stochastic nature and sensitivity to environmental parameters. To address this challenge, we present a versatile differentiable quantum master equation solver facilitating direct computation of steady-state solutions, and incorporate this solver into a framework for device characterization capable of dealing with additional nondifferentiable parameters. Our approach utilizes gradient-based optimization and Bayesian inference to provide estimates and uncertainties in quantum device parameters. To showcase our approach, we consider steady-state charge transport through electrostatically defined quantum dots. Using simulated data, we demonstrate efficient estimation of parameters for a single quantum dot, and model selection as well as the capability of our solver to compute time evolution for a double quantum dot system. Our differentiable solver stands to widen the impact of physics-aware machine learning algorithms on quantum devices for characterization and control. |
| format | Article |
| id | doaj-art-661b5b178a924dabbb1c9d825997e2d3 |
| institution | Kabale University |
| issn | 2643-1564 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | American Physical Society |
| record_format | Article |
| series | Physical Review Research |
| spelling | doaj-art-661b5b178a924dabbb1c9d825997e2d32024-11-20T15:12:09ZengAmerican Physical SocietyPhysical Review Research2643-15642024-11-016404317510.1103/PhysRevResearch.6.043175Differentiable master equation solver for quantum device characterizationD. L. CraigN. AresE. M. GaugerDifferentiable models of physical systems provide a powerful platform for gradient-based algorithms, with particular impact on parameter estimation and optimal control. Quantum systems present a particular challenge for such characterization and control, owing to their inherently stochastic nature and sensitivity to environmental parameters. To address this challenge, we present a versatile differentiable quantum master equation solver facilitating direct computation of steady-state solutions, and incorporate this solver into a framework for device characterization capable of dealing with additional nondifferentiable parameters. Our approach utilizes gradient-based optimization and Bayesian inference to provide estimates and uncertainties in quantum device parameters. To showcase our approach, we consider steady-state charge transport through electrostatically defined quantum dots. Using simulated data, we demonstrate efficient estimation of parameters for a single quantum dot, and model selection as well as the capability of our solver to compute time evolution for a double quantum dot system. Our differentiable solver stands to widen the impact of physics-aware machine learning algorithms on quantum devices for characterization and control.http://doi.org/10.1103/PhysRevResearch.6.043175 |
| spellingShingle | D. L. Craig N. Ares E. M. Gauger Differentiable master equation solver for quantum device characterization Physical Review Research |
| title | Differentiable master equation solver for quantum device characterization |
| title_full | Differentiable master equation solver for quantum device characterization |
| title_fullStr | Differentiable master equation solver for quantum device characterization |
| title_full_unstemmed | Differentiable master equation solver for quantum device characterization |
| title_short | Differentiable master equation solver for quantum device characterization |
| title_sort | differentiable master equation solver for quantum device characterization |
| url | http://doi.org/10.1103/PhysRevResearch.6.043175 |
| work_keys_str_mv | AT dlcraig differentiablemasterequationsolverforquantumdevicecharacterization AT nares differentiablemasterequationsolverforquantumdevicecharacterization AT emgauger differentiablemasterequationsolverforquantumdevicecharacterization |