Data validation through anomaly detection for Gaia DR4

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• Sireesha Chamarthi (IoA / CASU)
• Monday 25 November 2024, 16:00-17:00
• Martin Ryle Seminar Room, KICC.

If you have a question about this talk, please contact km723.

A crucial step in a data release is performing data validation to distinguish true scientific anomalies from those caused by instrument or calibration errors. Gaia Data Release 4 (DR4) presents significant computational and methodological challenges due to its vast, high-dimensional datasets. One of the aspects of validation process is anomaly detection within the photometry data, which involves identifying deviations from expected patterns in time series data. In this talk, I will first address the broader data validation problem for epoch photometry in Gaia DR4 . I will then introduce a proposed anomaly detection pipeline, highlighting various techniques for detecting anomalies in time series data, including both statistical approaches and machine learning-based methods. By combining domain expertise with data-driven methodologies, this work aims to enhance the validation of Gaia’s photometric time series data.

This talk is part of the Astro Data Science Discussion Group series.

This talk is included in these lists:

• Astro Data Science Discussion Group
• Cambridge Astronomy Talks
• Combined External Astrophysics Talks DAMTP
• Cosmology, Astrophysics and General Relativity
• Institute of Astronomy Extra Talks
• Institute of Astronomy Talk Lists
• Martin Ryle Seminar Room, KICC

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