Quadratic improvement on accuracy of approximating pure quantum states and unitary gates by probabilistic implementation

TL;DR

This paper demonstrates a quadratic improvement in the accuracy of approximating pure quantum states and unitary gates using probabilistic encoding, significantly reducing resource requirements for quantum state and circuit approximation.

Contribution

It establishes tight bounds on classical bit length for probabilistic quantum state encoding and shows quadratic accuracy improvements over deterministic methods.

Findings

Probabilistic encoding halves the bit length needed compared to deterministic encoding.

Quadratic increase in approximation accuracy using ensembles of pure states.

Improved reduction rate in circuit size for probabilistic circuit synthesis.

Abstract

Pure quantum states are often approximately encoded as classical bit strings such as those representing probability amplitudes and those describing circuits that generate the quantum states. The crucial quantity is the minimum length of classical bit strings from which the original pure states are approximately reconstructible. We derive asymptotically tight bounds on the minimum bit length required for probabilistic encodings with which one can approximately reconstruct the original pure state as an ensemble of the quantum states encoded in classical strings. We also show that such a probabilistic encoding asymptotically halves the bit length required for "deterministic" ones. This is based on the fact that the accuracy of approximating pure states by using a given subset of pure states can be increased quadratically if we use ensembles of pure states in the subset. Moreover, we show that a similar fact holds when we consider the approximation of unitary gates by using a given subset of unitary gates. This improves the reduction rate of the circuit size by using probabilistic circuit synthesis compared to previous results. This also demonstrates that the reduction is possible even for low-accuracy circuit synthesis, which might improve the accuracy of various NISQ algorithms.