Generalized fast quasi-adiabatic population transfer for improved qubit
readout, shuttling, and noise mitigation
- URL: http://arxiv.org/abs/2203.07517v2
- Date: Mon, 26 Jun 2023 16:52:33 GMT
- Title: Generalized fast quasi-adiabatic population transfer for improved qubit
readout, shuttling, and noise mitigation
- Authors: F. Fehse, M. David, M. Pioro-Ladri\`ere, W. A. Coish
- Abstract summary: Population-transfer schemes are commonly used to convert information robustly stored in some quantum system.
We give explicit fast quasiadiabatic (fast-QUAD) conversion strategies (pulse shapes) beyond the adiabatic approximation.
- Score: 0.0
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Population-transfer schemes are commonly used to convert information robustly
stored in some quantum system for manipulation and memory into more macroscopic
degrees of freedom for measurement. These schemes may include, e.g.,
spin-to-charge conversion for spins in quantum dots, detuning of charge qubits
between a noise-insensitive operating point and a measurement point, spatial
shuttling of qubits encoded in spins or ions, and parity-to-charge conversion
schemes for qubits based on Majorana zero modes. A common strategy is to use a
slow (adiabatic) conversion. However, in an adiabatic scheme, the adiabaticity
conditions, on the one hand, and accumulation of errors through dephasing,
leakage, and energy relaxation processes on the other hand, limit the fidelity
that can be achieved. Here, we give explicit fast quasiadiabatic (fast-QUAD)
conversion strategies (pulse shapes) beyond the adiabatic approximation that
allow for optimal state conversion. In contrast with many other approaches,
here we account for noise in combination with pulse shaping. Although we
restrict to noise sources that can be modeled by a classical fluctuating
parameter, we allow generally for anisotropic nonGaussian noise that is
nevertheless sufficiently weak to lead to a small error. Inspired by analytic
methods that have been developed for dynamical decoupling theory, we provide a
general framework for unique noise mitigation strategies that can be tailored
to the system and environment of interest.
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