# Exact dimension estimation of interacting qubit systems assisted by a single quantum probe

## TL;DR

This paper introduces a practical method for exactly estimating the dimension of multiqubit quantum systems by analyzing the system's interaction with a single quantum probe, using graph theory and realization theory.

## Contribution

It presents a novel approach that enables exact dimension estimation through indirect measurement and system modeling, overcoming experimental control limitations.

## Key findings

- Exact dimension estimation is achievable using the proposed method.
- The approach is robust against background noise within certain limits.
- System model order correlates with the Hilbert space dimension.

## Abstract

Estimating the dimension of an Hilbert space is an important component of quantum system identification. In quantum technologies, the dimension of a quantum system (or its corresponding accessible Hilbert space) is an important resource, as larger dimensions determine e.g. the performance of quantum computation protocols or the sensitivity of quantum sensors. Despite being a critical task in quantum system identification, estimating the Hilbert space dimension is experimentally challenging. While there have been proposals for various dimension witnesses capable of putting a lower bound on the dimension from measuring collective observables that encode correlations, in many practical scenarios, especially for multiqubit systems, the experimental control might not be able to engineer the required initialization, dynamics and observables. Here we propose a more practical strategy, that relies not on directly measuring an unknown multiqubit target system, but on the indirect interaction with a local quantum probe under the experimenter's control. Assuming only that the interaction model is given and the evolution correlates all the qubits with the probe, we combine a graph-theoretical approach and realization theory to demonstrate that the dimension of the Hilbert space can be exactly estimated from the model order of the system. We further analyze the robustness in the presence of background noise of the proposed estimation method based on realization theory, finding that despite stringent constrains on the allowed noise level, exact dimension estimation can still be achieved.