Solitons

Solitons are waves with just a single crest. They result when a wave’s natural tendency to spread as it propagates is cancelled out by an inherently nonlinear phenomenon known as self-focusing. This means that solitons can travel a long distance whilst maintaining their same shape.

Latest Research and Reviews

  • Research |

    Temporal dissipative soliton formation in a free-space femtosecond enhancement cavity with a thin Kerr medium is reported. Locking a 350-fs, 1,035-nm pulse train with a repetition rate of 100 MHz to this cavity-soliton state generates a 37-fs sech2-shaped pulse with a peak-power enhancement of 3,200.

    • N. Lilienfein
    • , C. Hofer
    • , M. Högner
    • , T. Saule
    • , M. Trubetskov
    • , V. Pervak
    • , E. Fill
    • , C. Riek
    • , A. Leitenstorfer
    • , J. Limpert
    • , F. Krausz
    •  & I. Pupeza
  • Research |

    A microphotonic astrocomb is demonstrated via temporal dissipative Kerr solitons in photonic-chip-based silicon nitride microresonators with a precision of 25 cm s–1 (radial velocity equivalent), useful for Earth-like planet detection and cosmological research.

    • Ewelina Obrzud
    • , Monica Rainer
    • , Avet Harutyunyan
    • , Miles H. Anderson
    • , Junqiu Liu
    • , Michael Geiselmann
    • , Bruno Chazelas
    • , Stefan Kundermann
    • , Steve Lecomte
    • , Massimo Cecconi
    • , Adriano Ghedina
    • , Emilio Molinari
    • , Francesco Pepe
    • , François Wildi
    • , François Bouchy
    • , Tobias J. Kippenberg
    •  & Tobias Herr
    Nature Photonics 13, 31-35
  • Research |

    A soliton microcomb as an astronomical spectrograph calibrator is presented. It can ultimately have a footprint of a few cubic centimetres, and reduced weight and power consumption, attractive for precision radial velocity measurement.

    • Myoung-Gyun Suh
    • , Xu Yi
    • , Yu-Hung Lai
    • , S. Leifer
    • , Ivan S. Grudinin
    • , G. Vasisht
    • , Emily C. Martin
    • , Michael P. Fitzgerald
    • , G. Doppmann
    • , J. Wang
    • , D. Mawet
    • , Scott B. Papp
    • , Scott A. Diddams
    • , C. Beichman
    •  & Kerry Vahala
    Nature Photonics 13, 25-30
  • Research | | open

    Real-time characterisation of nonlinear processes in the time domain is challenging. Here, Närhi et al. show that machine learning techniques can help overcome this limitation and use them to infer time-domain properties of optical fibre modulation instability from spectral intensity measurements.

    • Mikko Närhi
    • , Lauri Salmela
    • , Juha Toivonen
    • , Cyril Billet
    • , John M. Dudley
    •  & Goëry Genty

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