High-performance nonlinear optimization module for quantum control

Precise manipulation of quantum systems via shaped control pulses has emerged as a key area of development for quantum physics and chemistry. In near-term quantum computers, for example, substitution of primitive operations with optimized noise-robust controls can yield improved fidelities for single- and multi-qubit gates without hardware modifications. However, for all but the most basic of systems, identifying ideal control pulses via analytic approaches is intractable, motivating an approach based on numerical optimization. In this talk we introduce a custom GPU-compatible optimization toolkit purpose-built for rapidly creating high-fidelity, noise-robust quantum controls in high-dimensional Hilbert spaces. We describe the design of the toolkit, provide examples of standard and custom workflows, and present benchmarking results that demonstrate the speedup enabled by the GPU-compatible graph architecture.