Microresonator soliton dual-comb spectroscopy

By Myoung-Gyun Suh, Qifan Yang, Ki Youl Yang, Xu Yi, Kerry J. Vahala. Science, 2016

788 citations recorded by the source corpus.

Shrinking spectrometers Dual-comb spectroscopy is a powerful technique that uses the interference of two closely related combs to map spectroscopic features directly into a frequency domain that can be read by electronics. Suh et al. developed a dual-comb spectroscopy approach using combs produced by silica microresonators fabricated on a silicon chip. Perhaps high-resolution spectroscopy will soon be shrunk to the chip scale, doing away with the need for bulky spectrometers. Science, this issue p. 600 Dual-comb spectroscopy is demonstrated using a pair of silica microresonators. Measurement of optical and vibrational spectra with high resolution provides a way to identify chemical species in cluttered environments and is of general importance in many fields. Dual-comb spectroscopy has emerged as a powerful approach for acquiring nearly instantaneous Raman and optical spectra with unprecedented resolution. Spectra are generated directly in the electrical domain, without the need for bulky mechanical spectrometers. We demonstrate a miniature soliton-based dual-comb system that can potentially transfer the approach to a chip platform. These devices achieve high-coherence pulsed mode locking. They also feature broad, reproducible spectral envelopes, an essential feature for dual-comb spectroscopy. Our work shows the potential for integrated spectroscopy with high signal-to-noise ratios and fast acquisition rates.

Subfields: Atomic and Molecular Physics, and Optics, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/161010485832b87cd152fd067830f4942a942851

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In Atomic and Molecular Physics, and Optics

  1. David J. Moss
  2. Roberto Morandotti
  3. Xingyuan Xu
  4. Arnan Mitchell
  5. Jiayang Wu
  6. Mengxi Tan
  7. Brent E. Little
  8. Sai T. Chu

In Electrical and Electronic Engineering

  1. David J. Moss
  2. Roberto Morandotti
  3. Xingyuan Xu
  4. Arnan Mitchell
  5. Jiayang Wu
  6. Mengxi Tan
  7. Brent E. Little
  8. Sai T. Chu

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