Quantum process tomography with unknown single-preparation input states
Yannick Deville, Alain Deville

TL;DR
This paper introduces a novel quantum process tomography method that operates with unknown input states and only a single instance of each, simplifying the characterization of quantum processes.
Contribution
It proposes a blind, single-preparation quantum process tomography approach that removes the need for precise input state control and multiple copies, expanding QPT applicability.
Findings
Numerical validation with random pure states demonstrates effectiveness.
Method successfully characterizes processes with cylindrical-symmetry Heisenberg spin coupling.
Approach is adaptable to various input state properties and broader quantum processes.
Abstract
Quantum Process Tomography (QPT) methods aim at identifying, i.e. estimating, a given quantum process. QPT is a major quantum information processing tool, since it especially allows one to characterize the actual behavior of quantum gates, which are the building blocks of quantum computers. However, usual QPT procedures are complicated, since they set several constraints on the quantum states used as inputs of the process to be characterized. In this paper, we extend QPT so as to avoid two such constraints. On the one hand, usual QPT methods requires one to know, hence to precisely control (i.e. prepare), the specific quantum states used as inputs of the considered quantum process, which is cumbersome. We therefore propose a Blind, or unsupervised, extension of QPT (i.e. BQPT), which means that this approach uses input quantum states whose values are unknown and arbitrary, except that…
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