Optimal purification of a spin ensemble by quantum-algorithmic feedback

• URL: http://arxiv.org/abs/2111.04624v1
• Date: Mon, 8 Nov 2021 16:54:04 GMT
• Title: Optimal purification of a spin ensemble by quantum-algorithmic feedback
• Authors: Daniel M. Jackson, Urs Haeusler, Leon Zaporski, Jonathan H. Bodey, Noah Shofer, Edmund Clarke, Maxime Hugues, Mete Atat\"ure, Claire Le Gall and Dorian A. Gangloff
• Abstract summary: We present a quantum feedback algorithm capable of stabilising the collective state of an ensemble from an infinite-temperature state to the limit of single quanta. We implement this on 50,000 nuclei in a semiconductor quantum dot, and show that the nuclear-spin fluctuations are reduced 83-fold down to 10 spin macrostates.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Purifying a high-temperature ensemble of quantum particles towards a known state is a key requirement to exploit quantum many-body effects. An alternative to passive cooling, which brings a system to its ground state, is based on feedback to stabilise the system actively around a target state. This alternative, if realised, offers additional control capabilities for the design of quantum states. Here we present a quantum feedback algorithm capable of stabilising the collective state of an ensemble from an infinite-temperature state to the limit of single quanta. We implement this on ~50,000 nuclei in a semiconductor quantum dot, and show that the nuclear-spin fluctuations are reduced 83-fold down to 10 spin macrostates. While our algorithm can purify a single macrostate, system-specific inhomogeneities prevent reaching this limit. Our feedback algorithm further engineers classically correlated ensemble states via macrostate tuning, weighted bimodality, and latticed multistability, constituting a pre-cursor towards quantum-correlated macrostates.

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