Quantum state preparation with optimal T-count
David Gosset, Robin Kothari, Kewen Wu
TL;DR
This work establishes the optimal asymptotic T-count for quantum state preparation and diagonal unitary synthesis under Clifford+$T$ gates with ancillas. The authors derive a tight upper bound of $O\left(\sqrt{2^n\log(1/\varepsilon)}+\log(1/\varepsilon)\right)$ T gates and ancillas for arbitrary $n$-qubit states, and prove a matching adaptive Clifford+$T$ lower bound, thereby closing a long-standing gap from previous results. They generalize to diagonal unitaries, and provide practical corollaries such as batched synthesis of multiple single-qubit unitaries and mass production of $U^{\otimes m}$ with near-linear T-cost in $m$. The paper introduces a coarse-to-fine state-approximation strategy combining diagonal-unitary synthesis, LCU, and amplitude amplification, and refines diagonal synthesis via a boolean-oracle-based construction. Overall, the results offer near-optimal resource estimates and enable parallelized and scalable quantum state and diagonal-unitary synthesis, with implications for magic-state costs and decompositions of quantum operations.
Abstract
How many T gates are needed to approximate an arbitrary $n$-qubit quantum state to within error $\varepsilon$? Improving prior work of Low, Kliuchnikov, and Schaeffer, we show that the optimal asymptotic scaling is $Θ\left(\sqrt{2^n\log(1/\varepsilon)}+\log(1/\varepsilon)\right)$ if we allow ancilla qubits. We also show that this is the optimal T-count for implementing an arbitrary diagonal $n$-qubit unitary to within error $\varepsilon$. We describe applications in which a tensor product of many single-qubit unitaries can be synthesized in parallel for the price of one.
