Quantum Brain
← Back to papers

An efficient quantum compiler that reduces T count

Luke E Heyfron, E. Campbell·December 5, 2017·DOI: 10.1088/2058-9565/aad604
MathematicsPhysicsComputer Science

AI Breakdown

Get a structured breakdown of this paper — what it's about, the core idea, and key takeaways for the field.

Abstract

Before executing a quantum algorithm, one must first decompose the algorithm into machine-level instructions compatible with the architecture of the quantum computer, a process known as quantum compiling. There are many different quantum circuit decompositions for the same algorithm but it is desirable to compile leaner circuits. A fundamentally important cost metric is the T count—the number of T gates in a circuit. For the single qubit case, optimal compiling is essentially a solved problem. However, multi-qubit compiling is a harder problem with optimal algorithms requiring classical runtime exponential in the number of qubits. Here, we present and compare several efficient quantum compilers for multi-qubit Clifford + T circuits. We implemented our compilers in C++ and benchmarked them on random circuits, from which we determine that our TODD compiler yields the lowest T counts on average. We also benchmarked TODD on a library of reversible logic circuits that appear in quantum algorithms and found that it reduced the T count for 97% of the circuits with an average T-count saving of 20% when compared against the best of all previous circuit decompositions.

Related Research

Quantum Intelligence

Ask about quantum research, companies, or market developments.