Efficient Frequency Allocation for Superconducting Quantum Processors Using Improved Optimization Techniques

TL;DR

This paper introduces improved optimization techniques for frequency allocation in superconducting quantum processors, enabling larger, more flexible designs with higher yield and reduced computational costs.

Contribution

The work presents novel constraints and methods that enhance frequency allocation optimization, allowing for larger, more adaptable quantum processors without manual orientation selection.

Findings

Successfully optimized a 1,000+ qubit processor with over 10% yield

Achieved higher dispersion levels at low computational cost

Enhanced flexibility in processor boundary condition selection

Abstract

Building on previous research on frequency allocation optimization for superconducting circuit quantum processors, this work incorporates several new techniques to improve overall solution quality. New features include tightening constraints, imposing edgewise differences, including edge orientation in the optimization, and integrating multimodule designs with various boundary conditions. These enhancements allow for greater flexibility in processor design by eliminating the need for handpicked orientations. We support the efficient assembly of large processors with dense connectivity by choosing the best boundary conditions. Examples demonstrate that, at low computational cost, the new optimization approach finds a frequency configuration for a square chip with over 1,000 qubits and over 10% yield at much larger dispersion levels than required by previous approaches.