Compressed optimization of device architectures

TL;DR

This paper introduces CODA, a computationally efficient protocol inspired by compressed sensing, for benchmarking and optimizing complex quantum device architectures, enabling automated control and reduced complexity in large-scale quantum systems.

Contribution

It presents a novel, scalable method for designing and controlling complex quantum devices using compressed sensing principles, improving automation and efficiency.

Findings

Demonstrated CODA's effectiveness through simulations of up to eight quantum dots.

Showed CODA can automate control and optimize device performance.

Validated CODA's scalability for large quantum systems.

Abstract

Note: This preprint has been superseded by arXiv:1806.04318. Recent advances in nanotechnology have enabled researchers to control individual quantum mechanical objects with unprecedented accuracy, opening the door for both quantum and extreme-scale conventional computing applications. As these devices become larger and more complex, the ability to design them such that they can be simply controlled becomes a daunting and computationally infeasible task. Here, motivated by ideas from compressed sensing, we introduce a protocol for the Compressed Optimization of Device Architectures (CODA). It leads naturally to a metric for benchmarking device performance and optimizing device designs, and provides a scheme for automating the control of gate operations and reducing their complexity. Because CODA is computationally efficient, it is readily extensible to large systems. We demonstrate the CODA benchmarking and optimization protocols through simulations of up to eight quantum dots in devices that are currently being developed experimentally for quantum computation.