Optimal Quantum Control of Time-Correlated Semiclassical Control Noise
ORAL
Abstract
Precise control of quantum systems is required for most proposed quantum technologies. The major roadblock in precise quantum control of quantum systems is noise due to unwanted environmental interactions. Provably optimal control sequences for select system-bath interactions exist while numerical optimization methods have traditionally been applied to mitigate errors in the control. In this work, we provide an analytical framework for constructing optimal control for systems under the influence of temporally-correlated semiclassical control noise. This framework is built from Autoregressive-moving-average models (ARMA) from time series analysis for representing signals with arbitrary noise spectra. With this framework, we have constructed provably optimal quantum control sequences for single-axis quantum control under the influence of temporally-correlated semiclassical control noise with select noise spectra. In this talk, I will discuss the framework, optimality of the solutions for select noise spectra, and extensions to signals with arbitrary spectra.
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Presenters
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Colin Trout
Johns Hopkins University Applied Physics Lab, Johns Hopkins University Applied Physics Laboratory
Authors
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Colin Trout
Johns Hopkins University Applied Physics Lab, Johns Hopkins University Applied Physics Laboratory
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Kevin Schultz
Johns Hopkins University Applied Physics Lab, Applied Phys Lab/JHU, Johns Hopkins University Applied Physics Laboratory
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Greg Quiroz
Johns Hopkins University Applied Physics Lab, Johns Hopkins University Applied Physics Laboratory
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Robert Barr
Johns Hopkins University Applied Physics Lab
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David Clader
Johns Hopkins University Applied Physics Lab, Johns Hopkins University Applied Physics Laboratory, Applied Phys Lab/JHU