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  <title><![CDATA[Special CRA SEMINAR| Jake Lange | RIT Alumni | Host: Dr. Meg Millhouse]]></title>
  <body><![CDATA[<p><strong>Speaker:</strong> Jake Lange</p><p><strong>Host: </strong>Dr. Meg Millhouse</p><p><strong>Title: </strong>Growing the RIFT: an update on features and applications for the gravitational wave inference code RIFT</p><p><strong>Abstract:</strong><br>As the sensitivity of the gravitational wave (GW) detectors improve, the number of detections for future observing runs are expected to dramatically increase. Due to this, the need for fast, accurate, and increasingly automated parameter inference code becomes ever more relevant. The GW parameter inference code RIFT is a grid-based code that takes advantage of the parameter-dependencies of terms within the likelihood to efficiently marginalize the extrinsic parameters. This piecewise approach to the construction of the likelihood allows for highly parallelizable calculations and computational speed compared to standard Markov-Chain Monte Carlo methods. In this talk, I will present some recent improvements to RIFT as well as some recent applications where RIFT was used to produce novel results. This includes analyses with initially unbound, eccentric-precessing, and eccentric-matter waveforms. Fast and accurate inference of these more exotic sources will be essential as we approach design sensitivity of LIGO/Virgo and look forward to 3G detectors.</p>]]></body>
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      <value><![CDATA[<p><strong>Abstract:</strong><br>As the sensitivity of the gravitational wave (GW) detectors improve, the number of detections for future observing runs are expected to dramatically increase. Due to this, the need for fast, accurate, and increasingly automated parameter inference code becomes ever more relevant. The GW parameter inference code RIFT is a grid-based code that takes advantage of the parameter-dependencies of terms within the likelihood to efficiently marginalize the extrinsic parameters. This piecewise approach to the construction of the likelihood allows for highly parallelizable calculations and computational speed compared to standard Markov-Chain Monte Carlo methods. In this talk, I will present some recent improvements to RIFT as well as some recent applications where RIFT was used to produce novel results. This includes analyses with initially unbound, eccentric-precessing, and eccentric-matter waveforms. Fast and accurate inference of these more exotic sources will be essential as we approach design sensitivity of LIGO/Virgo and look forward to 3G detectors.</p>]]></value>
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