Quantum rotations: a case study in static and dynamic machine-code generation for quantum computers

Abstract

Work in quantum computer architecture has focused on communication, layout and fault tolerance, largely driven by Shor's factorization algorithm. For the first time, we study a larger range of benchmarks and find that another critical issue is the generation of code sequences for quantum rotation operations. Specifically, quantum algorithms require arbitrary rotation angles, while quantum technologies and error correction codes provide only for discrete angles and operators. A sequence of quantum machine instructions must be generated to approximate the arbitrary rotation to the required precision. While previous work has focused exclusively on static compilation, we find that some applications require dynamic code generation and explore the advantages and disadvantages of static and dynamic approaches. We find that static code generation can, in some cases, lead to a terabyte of machine code to support required rotations. We also find that some rotation angles are unknown until run time, requiring dynamic code generation. Dynamic code generation, however, exhibits significant trade-offs in terms of time overhead versus code size. Furthermore, dynamic code generation will be performed on classical (non-quantum) computing resources, which may or may not have a clock speed advantage over the target quantum technology. For example, operations on trapped ions run at kilohertz speeds, but superconducting qubits run at gigahertz speeds. We introduce a new method for compiling arbitrary rotations dynamically, designed to minimize compilation time. The new method reduces compilation time by up to five orders of magnitude while increasing code size by one order of magnitude. We explore the design space formed by these trade-offs of dynamic versus static code generation, code quality, and quantum technology. We introduce several techniques to provide smoother trade-offs for dynamic code generation and evaluate the viability of options in the design space.