Shallow quantum circuit for generating extremely low-entangled approximate state designs

TL;DR

This paper introduces a shallow quantum circuit to generate low-entanglement approximate state designs, enabling efficient quantum state preparation and classical shadow tomography with minimal resources.

Contribution

It presents a novel ensemble of quantum states with minimal entanglement and a shallow, ancilla-free circuit to generate them efficiently, advancing quantum state design methods.

Findings

States reach theoretical lower bounds of entanglement, magic, and coherence.

The circuit depth is optimal among ancilla-free algorithms.

Enables efficient classical shadow tomography with minimal measurements.

Abstract

Random quantum states have various applications in quantum information science. We discover a new ensemble of quantum states that serve as an $\epsilon$-approximate state $t$-design while possessing extremely low entanglement, magic, and coherence. These resources can reach their theoretical lower bounds, $\Omega(\log (t/\epsilon))$, which are also proven in this work. This implies that for fixed $t$ and $\epsilon$, entanglement, magic, and coherence do not scale with the system size, i.e., $O(1)$ with respect to the total number of qubits $n$. Moreover, we explicitly construct an ancilla-free shallow quantum circuit for generating such states by transforming $k$-qubit approximate state designs into $n$-qubit ones without increasing the support size. The depth of such a quantum circuit, $O(t [\log t]^3 \log n \log(1/\epsilon))$, is the most efficient among existing algorithms without ancilla qubits. A class of quantum circuits proposed in our work offers reduced cost for classical simulation of random quantum states, leading to potential applications in quantum information processing. As a concrete example, we propose classical shadow tomography using an estimator with superpositions between only two states, from which almost all quantum states can be efficiently certified by requiring only $O(1)$ measurements and classical post-processing time.