Quantum Science and Technology · 2018 · 97 citations · 30 references
ComputingComputer EngineeringComputer ScienceCompilersComputer ArchitectureQuantum ComputingQuantum AlgorithmsQuantum CircuitsQuantum CompilationQuantum ComputationQuantum GatesQuantum Hardware ArchitecturesDigital Logic CircuitsMulti-qubit GatesQuantum Algorithm Complexity AnalysisQuantum Architecture-aware CompilationQuantum Circuit BenchmarkingQuantum Circuit CompilationQuantum Compilation BenchmarksSingle-qubit Gates
Quantum compiling transforms high‑level algorithms into machine‑level instructions, and the T count—the number of T gates—is a key cost metric, especially challenging for multi‑qubit circuits where optimal solutions require exponential classical time. This work presents and compares several efficient quantum compilers for multi‑qubit Clifford + T circuits. Implemented in C++ and benchmarked on random circuits, the TODD compiler consistently achieves the lowest average T counts. On a library of reversible logic circuits used in quantum algorithms, TODD reduced the T count in 97 % of cases, saving an average of 20 % compared to the best previous decompositions.
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.
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