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Preserving a qubit during adjacent measurements at a few micrometers distance

Quantum Physics 2023-06-06 v1

Abstract

Protecting a quantum object against irreversible accidental measurements from its surroundings is necessary for controlled quantum operations. This becomes especially challenging or unfeasible if one must simultaneously measure or reset a nearby object's quantum state, such as in quantum error correction. In atomic systems - among the most established quantum information processing platforms - current attempts to preserve qubits against resonant laser-driven adjacent measurements waste valuable experimental resources such as coherence time or extra qubits and introduce additional errors. Here, we demonstrate high-fidelity preservation of an `asset' ion qubit while a neighboring `process' qubit is reset or measured at a few microns distance. We achieve <1×103< 1\times 10^{-3} probability of accidental measurement of the asset qubit while the process qubit is reset, and <4×103< 4\times 10^{-3} probability while applying a detection beam on the same neighbor for experimentally demonstrated fast detection times, at a distance of 6 μm6\ \rm{\mu m} or four times the addressing Gaussian beam waist. These low probabilities correspond to the preservation of the quantum state of the asset qubit with fidelities above 99.9%99.9\% (state reset) and 99.6%99.6\% (state measurement). Our results are enabled by precise wavefront control of the addressing optical beams while utilizing a single ion as a quantum sensor of optical aberrations. Our work demonstrates the feasibility of in-situ state reset and measurement operations, building towards enhancements in the speed and capabilities of quantum processors, such as in simulating measurement-driven quantum phases and realizing quantum error correction.

Keywords

Cite

@article{arxiv.2306.03075,
  title  = {Preserving a qubit during adjacent measurements at a few micrometers distance},
  author = {Sainath Motlakunta and Nikhil Kotibhaskar and Chung-You Shih and Anthony Vogliano and Darian Mclaren and Lewis Hahn and Jingwen Zhu and Roland Hablützel and Rajibul Islam},
  journal= {arXiv preprint arXiv:2306.03075},
  year   = {2023}
}