Vectorizing Quantum Control: A RISC-V Vector Extension Architecture for Scalable Qubit Systems

2026-07-08

AI Summary

This work proposes a RISC-V Vector Extension (RVV)-based quantum control processor architecture that overcomes the high toolchain costs and limited scalability of existing custom-instruction-set approaches. By introducing quantum-oriented instruction extensions, parameterized rotation gate encoding, dynamic tuning mechanisms, and a nanosecond-scale hardware pause-resume protocol, the design enables single-instruction parallel control of up to 128 qubits and supports mid-circuit measurement feedback. FPGA prototyping demonstrates up to 2.52× speedup in program execution time compared to baseline designs, with pipeline recovery within 80 nanoseconds after measurement, significantly enhancing both scalability and programming flexibility.

Abstract

The Quantum Control Processor (QCP) bridges the gap between compiler toolchains and control electronics, and is responsible for translating compiled quantum circuits into executable instructions that directly manipulate qubits and handle measurement feedback. However, existing designs rely primarily on customized instruction sets, limiting design reuse and requiring significant effort to build supporting toolchains. Furthermore, efficiently addressing qubits and scheduling operations in highly scalable scenarios remains a critical challenge. In this work, we present a vectorized quantum control approach built upon the RISC-V Vector (RVV) engine with a quantum-oriented extension. Leveraging the high parallelism of RVV, our approach can address up to 128 qubits in a single instruction. We also embed parameterized rotation information into the instruction set, enabling dynamic tuning of gate rotations in hybrid quantum-classical programs. To support mid-circuit measurements, we design a hardware-based halt-resume protocol that resumes pipeline execution within 80 $ns$ of receiving the measurement result. Comprehensive evaluation using both RISC-V toolchains and FPGA prototypes demonstrates that our design achieves up to 2.52$\times$ speedup over the baseline in program execution time, with excellent scalability.

Problem

• Quantum Control Processor
• RISC-V Vector Extension
• Scalable Qubit Systems
• Custom Instruction Sets
• Qubit Addressing

Innovation

• RISC-V Vector Extension
• Quantum Control Processor
• Vectorized Qubit Addressing
• Parameterized Quantum Gates
• Mid-Circuit Measurement