State-Based Classical Shadows

TL;DR

This paper introduces a novel state-based approach to classical shadow tomography, leveraging pseudorandom states and simple measurements, enhancing efficiency and computational feasibility for predicting quantum observables.

Contribution

It proposes a new state-based method for classical shadows using pseudorandom states, diverging from unitary-based approaches, and introduces computationally efficient techniques for quantum state prediction.

Findings

Uses entanglement with auxiliary states for classical shadow creation.

Shows pseudorandom states suffice for efficient observable prediction.

Achieves constant-depth measurement implementation.

Abstract

Classical Shadow Tomography (Huang, Kueng and Preskill, Nature Physics 2020) is a method for creating a classical snapshot of an unknown quantum state, which can later be used to predict the value of an a-priori unknown observable on that state. In the short time since their introduction, classical shadows received a lot of attention from the physics, quantum information, and quantum computing (including cryptography) communities. In particular there has been a major effort focused on improving the efficiency, and in particular depth, of generating the classical snapshot. Existing constructions rely on a distribution of unitaries as a central building block, and research is devoted to simplifying this family as much as possible. We diverge from this paradigm and show that suitable distributions over \emph{states} can be used as the building block instead. Concretely, we create the snapshot by entangling the unknown input state with an independently prepared auxiliary state, and measuring the resulting entangled state. This state-based approach allows us to consider a building block with arguably weaker properties that has not been studied so far in the context of classical shadows. Notably, our cryptographically-inspired analysis shows that for \emph{efficiently computable} observables, it suffices to use \emph{pseudorandom} families of states. To the best of our knowledge, \emph{computational} classical shadow tomography was not considered in the literature prior to our work. Finally, in terms of efficiency, the online part of our method (i.e.\ the part that depends on the input) is simply performing a measurement in the Bell basis, which can be done in constant depth using elementary gates.