Adaptive circuits with unary encoding prepare sparse states, Slater determinant sums, and Bethe wavefunctions in logarithmic or constant depth, trading circuit depth for extra width.
Resource-compact time-optimal quantum computation
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abstract
Fault-tolerant quantum computation enables reliable quantum computation but incurs a significant overhead from both time and resource perspectives. To reduce computation time, Austin G. Fowler proposed time-optimal quantum computation by constructing a quantum circuit for a fault-tolerant $T$ gate without probabilistic $S$ gate correction. In this work, we introduce a resource-compact quantum circuit that significantly reduces resource requirements by more than 60% for a fault-tolerant $T$ gate without probabilistic $S$ gate correction. Consequently, we present a quantum circuit that minimizes resource utilization for time-optimal quantum computation, demonstrating efficient time-optimal quantum computation. Additionally, we describe an efficient form involving initialization, CNOTs, and measurements, laying the foundation for the development of an efficient compiler for fault-tolerant quantum computation.
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Reducing Circuit Depth in Quantum State Preparation for Quantum Simulation Using Measurements and Feedforward
Adaptive circuits with unary encoding prepare sparse states, Slater determinant sums, and Bethe wavefunctions in logarithmic or constant depth, trading circuit depth for extra width.