Evidence map›Paper›PMID 42513049›Full record

ReviewMicromachines2026

Advances in FPGA-Based Laser Frequency Stabilization Techniques.

Zhilin Yan, Wenqiang Fan, Longjie Zhang, Wanxiao Gao, Cunwei Zhang, Jiaming Zhang, Tie Li, Yancheng Guo, Yulei Wang, Zhiwei Lu and 2 more

Abstract readReview
In one paragraph

Review in Micromachines, 2026. 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

12 authors.

Zhilin YanCenter for Advanced Laser Technology, Hebei University of Technology, Tianjin 300401, China.
Wenqiang FanCenter for Advanced Laser Technology, Hebei University of Technology, Tianjin 300401, China.
Longjie ZhangCenter for Advanced Laser Technology, Hebei University of Technology, Tianjin 300401, China.
Wanxiao GaoCenter for Advanced Laser Technology, Hebei University of Technology, Tianjin 300401, China.
Cunwei ZhangCenter for Advanced Laser Technology, Hebei University of Technology, Tianjin 300401, China.
Jiaming ZhangCenter for Advanced Laser Technology, Hebei University of Technology, Tianjin 300401, China.
Tie LiCenter for Advanced Laser Technology, Hebei University of Technology, Tianjin 300401, China.
Yancheng GuoScience and Technology on Particle Transport and Separation Laboratory, China National Nuclear Corporation, Tianjin 300180, China.
Yulei WangCenter for Advanced Laser Technology, Hebei University of Technology, Tianjin 300401, China.
Zhiwei LuCenter for Advanced Laser Technology, Hebei University of Technology, Tianjin 300401, China.
Qiunan YangScience and Technology on Particle Transport and Separation Laboratory, China National Nuclear Corporation, Tianjin 300180, China.
Zhenxu BaiCenter for Advanced Laser Technology, Hebei University of Technology, Tianjin 300401, China.ORCID 0000-0003-2040-833X

Funding

Hebei Provincial Department of Education JCZX2025003Key Research and Development Program of China 2024YFE0206000National Key Laboratory of Particle-Transport and Separation Technology WZKF-2025-05National Natural Science Foundation of China 62375076Science and Technology Cooperation Special Project of Shijiazhuang SJZZXC24006
6 · The paper itself

Abstract

Laser frequency stabilization underpins precision metrology, optical atomic clocks, quantum optics, and laser spectroscopy. In recent years, field-programmable gate arrays (FPGAs) have become attractive for this task because signal generation, phase-sensitive detection, digital filtering, feedback control, lock monitoring, and automatic re-locking can be integrated on compact and reconfigurable platforms. This review examines recent progress in FPGA-based laser frequency stabilization from four linked perspectives: stabilization principles, digital implementation, system architecture, and intelligent control. We first summarize representative error-signal generation methods, including Pound-Drever-Hall locking, saturation absorption spectroscopy, frequency modulation spectroscopy, and modulation transfer spectroscopy. We then discuss the FPGA functions that determine practical performance, such as data acquisition, direct digital synthesis, digital demodulation, proportional-integral-derivative (PID)/infinite impulse response (IIR) filtering, latency management, and lock-state monitoring. Mixed-signal, all-digital, distributed, and machine-learning-assisted systems are compared to show how bandwidth, latency, stability, integration, cost, and automation are balanced in different designs. This review closes by identifying remaining challenges in analog-to-digital converter/digital-to-analog converter (ADC/DAC) resolution, converter noise, loop latency, actuator bandwidth, long-term robustness, and algorithm portability, and by outlining future directions toward low-latency, software-defined, and intelligent stabilization platforms.

Indexed as

digital feedback controlFPGAlaser frequency stabilizationPound–Drever–Hall technique

Identifiers

PMID42513049
PMCPMC13414417

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

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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.