Automated Auxiliary Qubit Allocation in High-Level Quantum Programming

TL;DR

This paper introduces an automated method for auxiliary qubit allocation in high-level quantum programming, significantly reducing CNOT gate counts and optimizing quantum circuit compilation for near-term hardware.

Contribution

It presents a novel automated auxiliary qubit allocation technique integrated into Ket, improving multi-qubit gate decomposition and circuit optimization over existing platforms.

Findings

87% reduction in CNOT gates for Grover's algorithm

CNOT gate count reduced from 2.8×10^7 to 5.7×10^3 in state preparation

Quadratic reduction in CNOT gates with more auxiliary qubits

Abstract

We present a method for optimizing quantum circuit compilation by automating the allocation of auxiliary qubits for multi-qubit gate decompositions. This approach is implemented and evaluated within the high-level quantum programming platform Ket. Our results indicate that the decomposition of multi-qubit gates is more effectively handled by the compiler, which has access to all circuit parameters, rather than through a quantum programming API. To evaluate the approach, we compared our implementation against Qiskit, a widely used quantum programming platform, by analyzing two quantum algorithms. Using a 16-qubit QPU, we observed a reduction of 87% in the number of CNOT gates in Grover's algorithm for 9 qubits. For a state preparation algorithm with 7 qubits, the number of CNOT gates was reduced from $2.8\times10^7$ to $5.7\times10^3$, leveraging additional Ket optimizations for high-level quantum program constructions. Overall, a quadratic reduction in the number of CNOT gates in the final circuit was observed, with greater improvements achieved when more auxiliary qubits were available. These findings underscore the importance of automatic resource management, such as auxiliary qubit allocation, in optimizing quantum applications and improving their suitability for near-term quantum hardware.