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Chaotic microcomb-based parallel ranging

Nature Photonics volume 17, pages 814–821 (2023)Cite this article

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Abstract

The transition to chaos is ubiquitous in nonlinear systems ranging from fluid dynamics and superconducting circuits to biological organisms. Optical systems driven out of equilibrium such as lasers and supercontinuum generation exhibit chaotic states of light with fluctuations in both amplitude and phase and can give rise to Levy statistics, turbulence and rogue waves. Spatiotemporal chaos also occurs in continuous-wave-driven photonic-chip-based Kerr microresonators, where it is referred to as chaotic modulation instability. Such modulation instability states have generally been considered impractical for applications, in contrast to their coherent-light-state counterparts, which include soliton or dark-pulse states. Here we demonstrate that incoherent and chaotic states of light in an optical microresonator can be harnessed to implement unambiguous and interference-immune massively parallel coherent laser ranging by using the intrinsic random amplitude and phase modulation of the chaotic comb lines. We utilize 40 distinct lines of a microresonator frequency comb operated in the modulation instability regime. Each line carries >1 GHz noise bandwidth, which greatly surpasses the cavity linewidth, and enables to retrieve the distance of objects with centimetre-scale resolution. Our approach utilizes one of the most widely accessible microcomb states, and offers—in contrast to dissipative Kerr soliton states—high conversion efficiency, as well as flat optical spectra, and alleviates the need for complex laser initiation routines. Moreover the approach generates wideband signal modulation without requiring any electro-optical modulator or microwave synthesizer. Viewed more broadly, similar optical systems capable of chaotic dynamics could be applied to random-modulation optical ranging as well as spread-spectrum communication, optical cryptography and random number generation.

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Fig. 1: Concept of chaotic microcomb coherent LiDAR.
Fig. 2: Chaotic MI noise properties.
Fig. 3: Chaotic MI microcomb-based 3D imaging.
Fig. 4: Chaotic MI microcomb-based 3D velocimetry.

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Data availability

The data used to produce the plots within this paper are available via Zenodo at https://doi.org/10.5281/zenodo.7843656 (ref. 68).

Code availability

The code used to produce the plots within this paper is available via Zenodo at https://doi.org/10.5281/zenodo.7843656 (ref. 68).

References

  1. Horton, B. M. Noise-modulated distance measuring systems. In Proc. IRE 47, 821–828 (IEEE, 1959).

  2. Guosui, L., Hong, G. & Weimin, S. Development of random signal radars. IEEE Trans. Aerosp. Electron. Syst. 35, 770–777 (1999).

    Article  Google Scholar 

  3. Scholtz, R. The spread spectrum concept. IEEE Trans. Commun. 25, 748–755 (1977).

    Article  MATH  Google Scholar 

  4. Takeuchi, N., Sugimoto, N., Baba, H. & Sakurai, K. Random modulation cw lidar. Appl. Opt. 22, 1382–1386 (1983).

    Article  ADS  Google Scholar 

  5. Craig, S., Fishbein, W. & Rittenbach, O. Continuous-wave radar with high range resolution and unambiguous velocity determination. In IRE Transactions on Military Electronics MIL-6, 153–161 (IEEE, 1962).

  6. Narayanan, R. M., Xu, Y., Hoffmeyer, P. D. & Curtis, J. O. Design, performance, and applications of a coherent ultra-wideband random noise radar. Opt. Eng. 37, 1855–1869 (1998).

    Article  ADS  Google Scholar 

  7. Carter, G. Coherence and time delay estimation. Proc. IEEE 75, 236–255 (1987).

    Article  Google Scholar 

  8. Behroozpour, B., Sandborn, P. A., Wu, M. C. & Boser, B. E. Lidar system architectures and circuits. IEEE Commun. Magazine 55, 135–142 (2017).

    Article  Google Scholar 

  9. Pierrottet, D. et al. Linear FMCW laser radar for precision range and vector velocity measurements. MRS Online Proceedings Library Archive 1076, 10760406 (2008).

  10. Amann, M.-C. Phase noise limited resolution of coherent LIDAR using widely tunable laser diodes. Electron. Lett. 28, 1694–1696 (1992).

    Article  ADS  Google Scholar 

  11. Ahn, T.-J. & Kim, D. Y. Analysis of nonlinear frequency sweep in high-speed tunable laser sources using a self-homodyne measurement and hilbert transformation. Appl. Opt. 46, 2394–2400 (2007).

    Article  ADS  Google Scholar 

  12. Axelsson, S. Noise radar using random phase and frequency modulation. IEEE Trans. Geosci. Remote Sens. 42, 2370–2384 (2004).

    Article  ADS  Google Scholar 

  13. Hwang, I.-P. & Lee, C.-H. Mutual interferences of a true-random LiDAR with other LiDAR signals. IEEE Access 8, 124123–124133 (2020).

    Article  Google Scholar 

  14. Yang, Z., Li, C., Yu, M., Chen, F. & Wu, T. Compact 405-nm random-modulation continuous wave lidar for standoff biological warfare detection. J. Appl. Remote Sens. 9, 096042 (2015).

    Article  Google Scholar 

  15. Matthey, R. & Mitev, V. Pseudo-random noise-continuous-wave laser radar for surface and cloud measurements. Optics Lasers Eng. 43, 557–571 (2005).

    Article  ADS  Google Scholar 

  16. Quatrevalet, M. et al. Atmospheric CO2 sensing with a random modulation continuous wave integrated path differential absorption Lidar. IEEE J. Sel. Topics Quantum Electron. 23, 157–167 (2016).

    Article  ADS  Google Scholar 

  17. Wang, Y., Wang, B. & Wang, A. Chaotic correlation optical time domain reflectometer utilizing laser diode. IEEE Photon. Technol. Lett. 20, 1636–1638 (2008).

    Article  ADS  Google Scholar 

  18. Wang, A. et al. Precise fault location in WDM-PON by utilizing wavelength tunable chaotic laser. J. Lightwave Technol. 30, 3420–3426 (2012).

    Article  ADS  Google Scholar 

  19. Pulikkaseril, C. & Langdale-Smith, N. Next Generation LiDAR for a Fully Autonomous Future. White Paper (Baraja, 2020).

  20. Crouch, S. C., Reibel, R. R., Curry, J., Milvich, M. & Rupavatharam, K. Method and system for LIDAR detection and Doppler correction of optical phase-encoded range detection. US patent 10,422,880 (2019).

  21. Bashkansky, M., Burris, H. R., Funk, E. E., Mahon, R. & Moore, C. I. RF phase-coded random-modulation LIDAR. Opt. Commun. 231, 93–98 (2004).

    Article  ADS  Google Scholar 

  22. Ai, X., Nock, R., Rarity, J. G. & Dahnoun, N. High-resolution random-modulation cw lidar. Appl. Opt. 50, 4478–4488 (2011).

    Article  ADS  Google Scholar 

  23. Myneni, K., Barr, T. A., Reed, B. R., Pethel, S. D. & Corron, N. J. High-precision ranging using a chaotic laser pulse train. Appl. Phys. Lett. 78, 1496–1498 (2001).

    Article  ADS  Google Scholar 

  24. Lin, F.-Y. & Liu, J.-M. Chaotic lidar. IEEE J. Sel. Topics Quantum Electron. 10, 991–997 (2004).

    Article  ADS  Google Scholar 

  25. Liao, Y.-H. & Lin, F.-Y. Dynamical characteristics and their applications of semiconductor lasers subject to both optical injection and optical feedback. Opt. Express 21, 23568–23578 (2013).

    Article  ADS  Google Scholar 

  26. Cheng, C.-H. et al. 3D pulsed chaos lidar system. Opt. Express 26, 12230–12241 (2018).

    Article  ADS  Google Scholar 

  27. Ho, H.-L. et al. High-speed 3D imaging using a chaos lidar system. Eur. Phys. J. Spec. Top. 231, 435–441 (2022).

  28. Matsko, A. B., Liang, W., Savchenkov, A. A. & Maleki, L. Chaotic dynamics of frequency combs generated with continuously pumped nonlinear microresonators. Opt. Lett. 38, 525–527 (2013).

    Article  ADS  Google Scholar 

  29. Godey, C., Balakireva, I. V., Coillet, A. & Chembo, Y. K. Stability analysis of the spatiotemporal Lugiato-Lefever model for Kerr optical frequency combs in the anomalous and normal dispersion regimes. Phys. Rev. A 89, 063814 (2014).

    Article  ADS  Google Scholar 

  30. Herr, T. et al. Temporal solitons in optical microresonators. Nat. Photon. 8, 145–152 (2014).

    Article  ADS  Google Scholar 

  31. Kippenberg, T. J., Gaeta, A. L., Lipson, M. & Gorodetsky, M. L. Dissipative Kerr solitons in optical microresonators. Science 361, eaan8083 (2018).

    Article  Google Scholar 

  32. Trocha, P. et al. Ultrafast optical ranging using microresonator soliton frequency combs. Science 359, 887–891 (2018).

    Article  ADS  Google Scholar 

  33. Suh, M. G. & Vahala, K. J. Soliton microcomb range measurement. Science 359, 884–887 (2018).

    Article  ADS  Google Scholar 

  34. Suh, M.-G., Yang, Q.-F., Yang, K. Y., Yi, X. & Vahala, K. J. Microresonator soliton dual-comb spectroscopy. Science 354, 600–603 (2016).

    Article  ADS  Google Scholar 

  35. Marin-Palomo, P. et al. Microresonator-based solitons for massively parallel coherent optical communications. Nature 546, 274–279 (2017).

    Article  ADS  Google Scholar 

  36. Ji, X. et al. Chip-based frequency comb sources for optical coherence tomography. Opt. Express 27, 19896–19905 (2019).

    Article  ADS  Google Scholar 

  37. Marchand, P. J. et al. Soliton microcomb based spectral domain optical coherence tomography. Nat. Commun. 12, 427 (2021).

  38. Riemensberger, J. et al. Massively parallel coherent laser ranging using a soliton microcomb. Nature 581, 164–170 (2020).

    Article  ADS  Google Scholar 

  39. Liu, J. et al. Ultralow-power chip-based soliton microcombs for photonic integration. Optica 5, 1347–1353 (2018).

    Article  Google Scholar 

  40. Isono, H. Latest standardization trend for leading edge high-speed optical transceivers. In Metro and Data Center Optical Networks and Short-Reach Links IV 11712, 1171209 (International Society for Optics and Photonics, 2021).

  41. Timurdogan, E. et al. 400G silicon photonics integrated circuit transceiver chipsets for CPO, OBO, and pluggable modules. In Optical Fiber Communication Conference (OFC) 2020 T3H-2 (Optical Society of America, 2020).

  42. Coddington, I., Newbury, N. & Swann, W. Dual-comb spectroscopy. Optica 3, 414–426 (2016).

    Article  ADS  Google Scholar 

  43. Lukashchuk, A., Riemensberger, J., Karpov, M., Liu, J. & Kippenberg, T. J. Dual chirped microcomb based parallel ranging at megapixel-line rates. Nat. Commun. 13, 3280 (2022).

    Article  ADS  Google Scholar 

  44. Guo, H. et al. Universal dynamics and deterministic switching of dissipative Kerr solitons in optical microresonators. Nat. Phys. 13, 94–102 (2017).

    Article  Google Scholar 

  45. Wang, P.-H. et al. Intracavity characterization of micro-comb generation in the single-soliton regime. Opt. Express 24, 10890–10897 (2016).

    Article  ADS  Google Scholar 

  46. Bao, C. et al. Nonlinear conversion efficiency in Kerr frequency comb generation. Opt. Lett. 39, 6126–6129 (2014).

    Article  ADS  Google Scholar 

  47. Herr, T. et al. Universal formation dynamics and noise of Kerr-frequency combs in microresonators. Nat. Photon. 6, 480–487 (2012).

    Article  ADS  Google Scholar 

  48. Coulibaly, S. et al. Turbulence-induced rogue waves in Kerr resonators. Phys. Rev. X 9, 011054 (2019).

    Google Scholar 

  49. Boashash, B. Estimating and interpreting the instantaneous frequency of a signal. I. Fundamentals. Proc. IEEE 80, 520–538 (1992).

    Article  ADS  Google Scholar 

  50. Lin, F.-Y., Chao, Y.-K. & Wu, T.-C. Effective bandwidths of broadband chaotic signals. IEEE J. Quantum Electron. 48, 1010–1014 (2012).

    Article  ADS  Google Scholar 

  51. Akhmediev, N., Soto-Crespo, J. M. & Ankiewicz, A. Extreme waves that appear from nowhere: on the nature of rogue waves. Phys. Lett. A 373, 2137–2145 (2009).

    Article  ADS  MathSciNet  MATH  Google Scholar 

  52. Dudley, J. M., Dias, F., Erkintalo, M. & Genty, G. Instabilities, breathers and rogue waves in optics. Nat. Photon. 8, 755–764 (2014).

    Article  ADS  Google Scholar 

  53. Rice, S. O. Mathematical analysis of random noise. Bell Syst. Techn. J. 24, 46–156 (1945).

    Article  ADS  MathSciNet  MATH  Google Scholar 

  54. Corning SMF-28 (2019); https://www.corning.com/media/worldwide/coc/documents/Fiber/PI-1424-AEN.pdf

  55. Jiang, Y., Karpf, S. & Jalali, B. Time-stretch lidar as a spectrally scanned time-of-flight ranging camera. Nat. Photon. 14, 14–18 (2020).

    Article  Google Scholar 

  56. Xiang, C. et al. Laser soliton microcombs heterogeneously integrated on silicon. Science 373, 99–103 (2021).

    Article  ADS  Google Scholar 

  57. Liu, Y. et al. A photonic integrated circuit-based erbium-doped amplifier. Science 376, 1309–1313 (2022).

    Article  ADS  Google Scholar 

  58. de Beeck, C. O. et al. Heterogeneous III-V on silicon nitride amplifiers and lasers via microtransfer printing. Optica 7, 386–393 (2020).

    Article  ADS  Google Scholar 

  59. Vallaitis, T. et al. Quantum dot SOA input power dynamic range improvement for differential-phase encoded signals. Opt. Express 18, 6270–6276 (2010).

    Article  ADS  Google Scholar 

  60. Rogers, C. et al. A universal 3D imaging sensor on a silicon photonics platform. Nature 590, 256–261 (2021).

    Article  ADS  Google Scholar 

  61. Esman, D., Ataie, V., Kuo, B. P.-P., Alic, N. & Radic, S. Subnoise signal detection and communication. J. Lightwave Technol. 34, 5214–5219 (2016).

    Article  ADS  Google Scholar 

  62. Pecora, L. M. & Carroll, T. L. Synchronization in chaotic systems. Phys. Rev. Lett. 64, 821–824 (1990).

    Article  ADS  MathSciNet  MATH  Google Scholar 

  63. Hu, G., Xiao, J., Yang, J., Xie, F. & Qu, Z. Synchronization of spatiotemporal chaos and its applications. Phys. Rev. E 56, 2738–2746 (1997).

    Article  ADS  Google Scholar 

  64. Kocarev, L. Chaos-based cryptography: a brief overview. IEEE Circuits Syst. Magazine 1, 6–21 (2001).

    Article  Google Scholar 

  65. Chen, G., Mao, Y. & Chui, C. K. A symmetric image encryption scheme based on 3D chaotic cat maps. Chaos Solit. Fractals 21, 749–761 (2004).

    Article  ADS  MathSciNet  MATH  Google Scholar 

  66. Lukashchuk, A., Riemensberger, J., Tusnin, A., Liu, J. & Kippenberg, T. Chaotic micro-comb based parallel ranging. Preprint at arXiv https://arxiv.org/abs/2112.10241 (2021).

  67. Chen, R. et al. Breaking the temporal and frequency congestion of LiDAR by parallel chaos. Nat. Photon. 17, 306–314 (2023).

    Article  ADS  Google Scholar 

  68. Lukashchuk, A. et al. ‘Chaotic micro-comb based parallel ranging’ dataset and code. Zenodo https://doi.org/10.5281/zenodo.7843656 (2023).

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Acknowledgements

We thank A. Tikan for valuable comments and discussions. This Article is based upon work supported by the Air Force Office of Scientific Research under award no. FA8655-21-1-7064. The work was also supported by the Swiss National Science Foundation (SNF) under contract no. 192293. A.L. acknowledges support from the European Space Technology Centre with ESA contract no. 4000133568/20/NL/MH/hm. J.R. acknowledges support from the Swiss National Science Foundation under grant no. 201923 (Ambizione). A.T. acknowledges support from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement no. 812818 (MICROCOMB). The Si3N4 samples were fabricated in the EPFL Center of MicroNanoTechnology (CMi).

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  1. Institute of Physics, Swiss Federal Institute of Technology Lausanne (EPFL), Lausanne, Switzerland

    Anton Lukashchuk, Johann Riemensberger, Aleksandr Tusnin, Junqiu Liu & Tobias J. Kippenberg

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Contributions

A.L. and J.R. conceived and developed the idea. A.L. conducted the various experiments and analysed the data. A.L. designed the samples. J.L. fabricated the samples. J.R. characterized the samples. A.T. performed the numerical simulations. T.J.K. supervised the work. A.L., A.T., J.R. and T.J.K wrote the manuscript.

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Correspondence to Tobias J. Kippenberg.

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T.J.K. is a co-founder and shareholder of LiGenTec SA, a start-up company that is engaged in making Si3N4 nonlinear photonic chips available via foundry service. The other authors declare no competing interests.

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Lukashchuk, A., Riemensberger, J., Tusnin, A. et al. Chaotic microcomb-based parallel ranging. Nat. Photon. 17, 814–821 (2023). https://doi.org/10.1038/s41566-023-01246-5

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