Quantum control with noisy fields: computational complexity vs. sensitivity to noise
S. Kallush, M. Khasin, R. Kosloff

TL;DR
This paper explores how the complexity of quantum control tasks affects their sensitivity to noise, revealing that larger systems are more vulnerable, especially for hard control tasks, which challenges the feasibility of noise-resistant quantum control.
Contribution
It establishes a connection between control complexity and noise sensitivity in quantum systems, classifying tasks as easy or hard based on variance and scaling behavior.
Findings
Easy tasks are less sensitive to noise and easier to control.
Hard tasks exhibit high variance and are more noise-sensitive.
Noise effects dominate in large systems, undermining controllability.
Abstract
A closed quantum system is defined as completely controllable if an arbitrary unitary transformation can be executed using the available controls. In practice, control fields are a source of unavoidable noise, which has to be suppressed to retain controllability. Can one design control fields such that the effect of noise is negligible on the time-scale of the transformation? This question is intimately related to the fundamental problem of a connection between the computational complexity of the control problem and the sensitivity of the controlled system to noise. The present study considers a paradigm of control, where the Lie-algebraic structure of the control Hamiltonian is fixed, while the size of the system increases with the dimension of the Hilbert space representation of the algebra. We find two types of control tasks, easy and hard. Easy tasks are characterized by a small…
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