MixedPrecisionAnsätze

MixedPrecisionAnsätze are a concept in quantum computing that describes variational quantum circuit designs which deliberately employ components with different numerical precisions. In this approach, gate parameters or parts of the circuit are represented or processed using multiple precisions, such as combining 16-bit and 32-bit representations, or mixing high- and low-precision computations within the same ansatz.

Rationale and scope: Mixed precision is motivated by the desire to balance computational efficiency with the expressive power of the circuit. By using lower precision where possible, memory usage and compute time can be reduced, while higher precision can be reserved for parts of the circuit that are more sensitive to quantization error or where accurate gradient information is crucial.

Construction: A mixed-precision ansatz may organize layers or subcircuits with distinct precision settings or implement dynamic precision schemes that adjust during optimization. It can also refer to mixed-precision simulation of the circuit, where expectation values or gradient estimates are computed with differing levels of numerical accuracy.

Benefits and challenges: Potential benefits include faster training, lower memory footprints, and improved scalability on hardware that supports mixed precision. Challenges include numerical instability, degraded gradient information due to quantization, and the need for careful calibration to preserve the trainability and expressivity of the ansatz.

Relation to broader methods: MixedPrecisionAnsätze intersect with hardware-efficient and problem-inspired ansätze in variational quantum algorithms and complement approaches such as adaptive depth and error mitigation. Research in this area focuses on identifying regimes where mixed precision preserves performance while delivering computational savings, and on developing guidelines for when and how to apply precision mixing.