a-fast-template-periodogram-for-finding-periodic-non-sinusoidal-waveforms-in-noisy-irregularly-samp.json

{
  "copyright_text": "Standard YouTube License",
  "description": "Astronomers are often interested in detecting periodic signals in noisy time-series data. The Lomb-Scargle periodogram was designed for this purpose, and can efficiently handle complications like irregular sampling and heteroskedastic measurement errors. However, many signals in astronomy are non-sinusoidal, and while extensions to the Lomb-Scargle periodogram are able to handle a variety of waveform shapes, this comes at the cost of decreased sensitivity. Template fitting algorithms provide better sensitivity by explicitly fitting a fixed-shape waveform to the data, but this is too computationally demanding to be practical for large surveys. We present a new algorithm, the Fast Template Periodogram, that combines the speed advantage of Lomb-Scargle with the sensitivity of template fitting. The Fast Template Periodogram provides up to 4 orders of magnitude of speedup over more naive template fitting methods for large surveys with greater than 1,000 datapoints per object.",
  "duration": 1433,
  "language": "eng",
  "recorded": "2017-07-16",
  "related_urls": [
    {
      "label": "schedule",
      "url": "https://scipy2017.scipy.org/ehome/220975/493422/"
    }
  ],
  "speakers": [
    "John Hoffman"
  ],
  "tags": [],
  "thumbnail_url": "https://i.ytimg.com/vi/7STeeVnfYFM/maxresdefault.jpg",
  "title": "A Fast Template Periodogram for Finding Periodic (Non-Sinusoidal) Waveforms in Noisy, Irregularly-Sampled Time Series Data",
  "videos": [
    {
      "type": "youtube",
      "url": "https://www.youtube.com/watch?v=7STeeVnfYFM"
    }
  ]
}