# Adaptive compressive tomography with no a priori information

## TL;DR

This paper introduces an adaptive compressive tomography method that efficiently reconstructs quantum states with minimal measurement configurations, requiring no prior assumptions beyond the system dimension.

## Contribution

It presents a novel adaptive tomography scheme inspired by compressed sensing, eliminating the need for prior information about the quantum state.

## Key findings

- Significantly reduces measurement configurations needed for quantum state reconstruction
- Successfully implemented and tested experimentally
- Achieves accurate reconstruction without prior state assumptions

## Abstract

Quantum state tomography is both a crucial component in the field of quantum information and computation, and a formidable task that requires an incogitably large number of measurement configurations as the system dimension grows. We propose and experimentally carry out an intuitive adaptive compressive tomography scheme, inspired by the traditional compressed-sensing protocol in signal recovery, that tremendously reduces the number of configurations needed to uniquely reconstruct any given quantum state without any additional a priori assumption whatsoever (such as rank information, purity, etc) about the state, apart from its dimension.