Published December 22, 2022
| Version v1
Journal article
Open
Preparation of metrological states in dipolar-interacting spin systems
Creators
- 1. University of Chicago
Description
Spin systems are an attractive candidate for quantum-enhanced metrology. Here we develop a variational method to generate metrological states in small dipolar-interacting spin ensembles with limited qubit control. For both regular and disordered spatial spin configurations the generated states enable sensing beyond the standard quantum limit (SQL) and, for small spin numbers, approach the Heisenberg limit (HL). Depending on the circuit depth and the level of readout noise, the resulting states resemble Greenberger-Horne-Zeilinger (GHZ) states or Spin Squeezed States (SSS). Sensing beyond the SQL holds in the presence of finite spin polarization and a non-Markovian noise environment. The developed black-box optimization techniques for small spin numbers (N ≤ 10) are directly applicable to diamond-based nanoscale field sensing, where the sensor size limits N and conventional squeezing approaches fail.
Data availability
All relevant data supporting the main conclusions and figures of the document are available from the corresponding author on reasonable request.
All relevant code is available from the corresponding author upon reasonable request.
Files
Preparation-of-metrological-states-in-dipolar-interacting-spin-systems.pdf
Additional details
Identifiers
- DOI
- 10.1038/s41534-022-00667-4
- Other
- oai:uchicago.tind.io:11721
Related works
- Is supplement to
- https://doi.org/10.1038/s41534-024-00843-8 (URL)
Funding
- National Science Foundation
- OMA-1936118
- National Science Foundation
- OIA-2040520
- National Science Foundation
- QuBBE QLCI
- National Science Foundation
- Institute for Quantum Information and Matter
- National Science Foundation
- EPiQC
- National Science Foundation
- EPiQC
- National Science Foundation
- STAQ
- U.S. Department of Energy
- Office of Advanced Scientific Computing Research, Accelerated Research for Quantum Computing Program
- National Science Foundation
- OMA-2016136