Long distance spin shuttling enabled by few-parameter velocity optimization

TL;DR

This paper demonstrates that spin qubit shuttling errors in silicon quantum dots can be significantly reduced below fault-tolerance thresholds by using simple trajectory shaping with minimal parameters, despite inherent disorder and noise.

Contribution

It introduces a minimal-parameter velocity optimization method for spin shuttling that effectively mitigates errors caused by disorder and valley effects in silicon quantum dots.

Findings

Errors for 10 μm shuttling at constant speed are around 100%.

Trajectory shaping with 4 Fourier components reduces errors below fault-tolerance thresholds.

Simple parametrization enables experimental implementation without detailed disorder knowledge.

Abstract

Spin qubit shuttling via moving conveyor-mode quantum dots in Si/SiGe offers a promising route to scalable miniaturized quantum computing. Recent modeling of dephasing via valley degrees of freedom and well disorder dictate a slow shutting speed which seems to limit errors to above correction thresholds if not mitigated. We increase the precision of this prediction, showing that typical errors for 10 $\mu$m shuttling at constant speed results in O(1) error, using fast, automatically differentiable numerics and including improved disorder modeling and potential noise ranges. However, remarkably, we show that these errors can be brought to well below fault-tolerant thresholds using trajectory shaping with very simple parametrization with as few as 4 Fourier components, well within the means for experimental in-situ realization, and without the need for targeting or knowing the location of valley near degeneracies.