Evidence map›Paper›PMID 39064422›Full record

ArticleMicromachines2024

Suppressing Thermal Noise to Sub-Millikelvin Level in a Single-Spin Quantum System Using Realtime Frequency Tracking.

Zhiyi Hu, Jingyan He, Runchuan Ye, Xue Lin, Feifei Zhou, Nanyang Xu

Abstract read
In one paragraph

Article in Micromachines, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Zhiyi HuSchool of Microelectronics, Hefei University of Technology, Hefei 230009, China.
Jingyan HeInstitute of Quantum Sensing and College of Optical Science and Engineering, Zhejiang University, Hangzhou 310027, China.
Runchuan YeInstitute of Quantum Sensing and College of Optical Science and Engineering, Zhejiang University, Hangzhou 310027, China.
Xue LinInstitute of Quantum Sensing and College of Optical Science and Engineering, Zhejiang University, Hangzhou 310027, China.
Feifei ZhouCollege of Metrology Measurement and Instrument, China Jiliang University, Hangzhou 310018, China.
Nanyang XuInstitute of Quantum Sensing and College of Optical Science and Engineering, Zhejiang University, Hangzhou 310027, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A single nitrogen-vacancy (NV) center in a diamond can be used as a nanoscale sensor for magnetic field, electric field or nuclear spins. Due to its low photon detection efficiency, such sensing processes often take a long time, suffering from an electron spin resonance (ESR) frequency fluctuation induced by the time-varying thermal perturbations noise. Thus, suppressing the thermal noise is the fundamental way to enhance single-sensor performance, which is typically achieved by utilizing a thermal control protocol with a complicated and highly costly apparatus if a millikelvin-level stabilization is required. Here, we analyze the real-time thermal drift and utilize an active way to alternately track the single-spin ESR frequency drift in the experiment. Using this method, we achieve a temperature stabilization effect equivalent to sub-millikelvin (0.8 mK) level with no extra environmental thermal control, and the spin-state readout contrast is significantly improved in long-lasting experiments. This method holds broad applicability for NV-based single-spin experiments and harbors the potential for prospective expansion into diverse nanoscale quantum sensing domains.

Indexed as

feedback controlNV centerrealtime frequency trackingspin manipulationthermal noise suppression

Identifiers

PMID39064422
PMCPMC11278624

What OpenQuestion holds

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.