Lower T-count with faster algorithms

TL;DR

This paper introduces faster, more efficient algorithms for reducing the $T$-count in quantum circuits, significantly improving optimization speed and effectiveness, especially for Hadamard-free circuits, with proven upper bounds on $T$-gate counts.

Contribution

It proposes new $T$-count optimization algorithms with lower complexity and better or equal performance compared to existing methods, including proven upper bounds on $T$-gates.

Findings

Improved complexity of the TODD algorithm.

New algorithms achieve lower $T$-counts.

Proven upper bounds on $T$-gates in optimized circuits.

Abstract

Among the cost metrics characterizing a quantum circuit, the $T$-count stands out as one of the most crucial as its minimization is particularly important in various areas of quantum computation such as fault-tolerant quantum computing and quantum circuit simulation. In this work, we contribute to the $T$-count reduction problem by proposing efficient $T$-count optimizers with low execution times. In particular, we greatly improve the complexity of TODD, an algorithm currently providing the best $T$-count reduction on various quantum circuits. We also propose some modifications to the algorithm which are leading to a significantly lower number of $T$ gates. In addition, we propose another algorithm which has an even lower complexity and that achieves a better or equal $T$-count than the state of the art on most quantum circuits evaluated. We also prove that the number of $T$ gates in the circuit obtained after executing our algorithms on a Hadamard-free circuit composed of $n$ qubits is upper bounded by $n(n + 1)/2 + 1$, which improves on the worst-case $T$-count of existing optimization algorithms. From this we derive an upper bound of $(n + 1)(n + 2h)/2 + 1$ for the number of $T$ gates in a Clifford$+T$ circuit where $h$ is the number of internal Hadamard gates in the circuit, i.e. the number of Hadamard gates lying between the first and the last $T$ gate of the circuit.