APS Logo

Massively Multiplexed Nanoscale Magnetometry with Diamond Quantum Sensors

ORAL

Abstract

Single nitrogen vacancy (NV) centers in diamond have been used extensively for high-sensitivity nanoscale sensing, but conventional approaches use confocal microscopy to measure individual centers sequentially, limiting throughput and access to non-local physical properties. Here we design and implement a multiplexed NV sensing platform that allows us to read out many single NV centers simultaneously using a low-noise camera. We coherently manipulate and read out the spin states of hundreds of individual NV centers in parallel and implement a parallelized version of spin-to-charge-conversion readout for low spin state readout noise to demonstrate multiplexed covariance magnetometry, in which we measure six two-point magnetic field correlators from four NV centers simultaneously. In contrast to scanning probes for imaging spatially varying magnetic fields, our approach measures the temporal dynamics of the magnetic field at many precisely defined positions simultaneously, from which the local noise spectrum and non-local properties such as correlation functions can be computed. This will find immediate applications in studying condensed matter phenomena characterized by the noise spectrum or correlation functions, including quantum phase transitions, dynamics far from equilibrium, magnetic order, and correlated electron phenomena. In this presentation, I will describe our recent progress in studying correlated phenomena in thin-film superconductors with this multiplexing platform.

Publication: "Massively multiplexed nanoscale magnetometry with diamond quantum sensors", arXiv:2408.11666 [quant-ph]

Presenters

  • Kai-Hung Cheng

    Princeton University

Authors

  • Kai-Hung Cheng

    Princeton University

  • Zeeshawn Kazi

    Princeton University

  • Jared D Rovny

    Princeton University

  • Bichen Zhang

    Princeton University

  • Lila S Nassar

    Princeton University, Georgia Institute of Technology

  • Faranak Bahrami

    Princeton University

  • Yifan Zhang

    Princeton University

  • Rhine Samajdar

    Princeton University

  • Sarang Gopalakrishnan

    Princeton University, Department of Electrical and Computer Engineering, Princeton University, Princeton, NJ 08544, Princeton University Princeton

  • Jeff D Thompson

    Princeton University

  • Nathalie P de Leon

    Princeton University