Approximations in transmon simulation
- URL: http://arxiv.org/abs/2102.09721v2
- Date: Fri, 19 Nov 2021 23:06:05 GMT
- Title: Approximations in transmon simulation
- Authors: Tyler Jones, Kaiah Steven, Xavier Poncini, Matthew Rose, Arkady
Fedorov
- Abstract summary: We present a series of models, ordered in a hierarchy of progressive approximation, which appear in quantum control literature.
The validity of each model is characterised experimentally by designing and benchmarking control protocols for an IBMQ cloud quantum device.
An evaluation of simulated control dynamics reveals that despite the substantial variance in numerical predictions, the complexity of discovering local optimal control protocols appears invariant in the simple control scheme setting.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Classical simulations of time-dependent quantum systems are widely used in
quantum control research. In particular, these simulations are commonly used to
host iterative optimal control algorithms. This is convenient for algorithms
that are too onerous to run in the loop with current-day quantum hardware, as
well as for researchers without consistent access to hardware. However, if the
model used to represent the system is not selected carefully, an optimised
control protocol may be rendered futile when applied to hardware. We present a
series of models, ordered in a hierarchy of progressive approximation, which
appear in quantum control literature. The validity of each model is
characterised experimentally by designing and benchmarking control protocols
for an IBMQ cloud quantum device. This result demonstrates error amplification
induced by the application of a first-order perturbative approximation.
Furthermore, the emergence of errors that cannot be corrected by simple
amplitude scaling of control pulses is demonstrated in simulation, due to an
underlying mistreatment of noncomputational dynamics. Finally, an evaluation of
simulated control dynamics reveals that despite the substantial variance in
numerical predictions across the proposed models, the complexity of discovering
local optimal control protocols appears invariant in the simple control scheme
setting.
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