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Predicting rogue behavior

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On the afternoon of Nov. 9, 1975, the sturdy and storied freighter SS Edmund Fitzgerald, well known in the Great Lakes region for its record-breaking hauls of iron ore, set out across eastern Lake Superior, carrying a full cargo destined for a Detroit steel mill.

En route, it joined a second freighter, the SS Arthur M. Anderson, and by late afternoon of the following day, the two ships were caught in a frightening storm, encountering sustained winds of over 50 knots and waves as high as 35 ft. Shortly after 7:10 p.m., the Fitzgerald sank suddenly in Canadian waters about 15 nautical miles from Whitefish Bay.

Studies in laser physics are now examining the analogous behavior of light and water waves. Researchers are finding a probability distribution for the appearance of optical rogue waves, which could have great implications for predicting, and avoiding, rogues at sea. Courtesy of Pixabay/NeuPaddy.


Studies in laser physics are now examining the analogous behavior of light and water waves. Researchers are finding a probability distribution for the appearance of optical rogue waves, which could have great implications for predicting, and avoiding, rogues at sea. Courtesy of Pixabay/NeuPaddy.


Captained by Ernest M. McSorley, who was known to be an excellent heavy-weather seaman, the Fitzergald was nevertheless quickly overcome. No distress signals were sent before it sank. McSorley’s last communication was, “We are holding our own.” The ship’s crew of 29 all perished and no bodies were recovered. Though it has been much examined, the cause of the sinking remains unknown.

One prominent theory, however, is that the Fitzgerald was struck by a succession of rogue waves — typically associated with open ocean, but also possible in large bodies of fresh water — known in the Great Lakes region as the “three sisters.” The phenomenon involves a three-punch combination of waves. The first punch slams a ship with a wall of water, and before that can drain away, second and third blows quickly follow, overwhelming the vessel with the accumulated backwash.

Such occurrences of giant waves with great destructive power that rise up seemingly out of nowhere have always been tinged with a veneer of myth, but in recent decades, scientists have been able to prove through direct observations that they indeed exist. Still, researchers have found it impossible to predict the conditions that may lead to rogue-wave formation, and they have found it difficult to fully measure the wave characteristics.

Using a trained neural network from numerical simulations, researchers are able to predict the intensity of extreme waves of light emerging at the output of an optical fiber from unstable nonlinear propagation governed by the nonlinear Schrödinger equation. Courtesy of Goëry Genty/Tampere University of Technology.


Using a trained neural network from numerical simulations, researchers are able to predict the intensity of extreme waves of light emerging at the output of an optical fiber from unstable nonlinear propagation governed by the nonlinear Schrödinger equation. Courtesy of Goëry Genty/Tampere University of Technology.


More recently, however, studies in laser physics examining the analogous behavior of light and water waves have begun to provide clues about the instabilities that drive extreme events. Five years ago, University of Auckland physicist Miro Erkintalo told Nature Photonics, “Rogue waves are so rare that examining them at sea is next to impossible. Optical systems offer a convenient test bed that permits ultrafast measurements in controlled conditions. The dream is that experiments in optics could eventually provide sufficient insights into the mechanisms of rogue waves, so that we would be able to predict them.”

In a significant step, a team of researchers from Finland’s Tampere University of Technology (TUT) and France’s Institut FEMTO-ST at the Université Bourgogne-Franche-Comté, recently published a study (also in Nature Photonics) in which they used artificial intelligence to determine a probability distribution of extreme light waves.

The researchers injected laser pulses into an optical fiber system designed to reproduce wave propagation described by a nonlinear Schrödinger equation. They then compiled a data set of thousands of spectral signals, which, although easy to measure, did not show the presence of rogue waves directly. However, by using numerical simulations to train a neural network, it was possible to develop an algorithm that could accurately pick out features in the spectra to predict the emergence of a rogue wave.

The results yielded a probability distribution for the appearance of the optical rogue waves, which could have great implications for the practical matter of predicting — and hopefully avoiding — rogues at sea.

Professor John M. Dudley, who headed the team at the Université Bourgogne-Franche-Comté, went a step further: “As well as suggesting that similar techniques can be used to analyze real-time measurements on oceanographic wave data, the results open new perspectives in all fields of research where direct time-domain observations are difficult, but where spectral data is available.”


BioPhotonics
Jan 2019
SS Edmund FitzgeraldSS Arthur M. AndersonGreat Lakeswavesrogue-wavelasersTampere University of TechnologyInstitut FEMTO-STUniversité Bourgogne-Franche ComtéPost Scripts

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