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Shupe, David L.

Publications and source records attributed to Shupe, David L..

Discovery of Highly Blueshifted Broad Balmer and Metastable Helium Absorption Lines in a Tidal Disruption Event

We report the discovery of nonstellar hydrogen Balmer and metastable helium absorption lines accompanying a transient, high-velocity (0.05c) broad absorption line (BAL) system in the optical spectra of the tidal disruption event (TDE) AT2018zr (z = 0.071). In the Hubble Space Telescope UV spectra, absorption of high- and low-ionization lines is also present at this velocity, making AT2018zr resemble a low-ionization BALQSO. We conclude that these transient absorption features are more likely to arise in fast outflows produced by the TDE than absorbed by the unbound debris. In accordance with the outflow picture, we are able to reproduce the flat-topped Hα emission in a spherically expanding medium without invoking the typical prescription of an elliptical disk. We also report the appearance of narrow (~1000 kms(exp −1)) N III λ4640, He II λ4686, Hα, and Hβ emission in the late-time optical spectra of AT2018zr, which may be a result of UV continuum hardening at late times, as observed by Swift. Including AT2018zr, we find a high association rate (three out of four) of BALs in the UV spectra of TDEs. This suggests that outflows may be ubiquitous among TDEs and less sensitive to viewing angle effects compared to QSO outflows.

Hung, T.

The IPAC Image Subtraction and Discovery Pipeline for the Intermediate Palomar Transient Factory

We describe the near real-time transient-source discovery engine for the intermediate Palomar Transient Factory (iPTF), currently in operations at the Infrared Processing and Analysis Center (IPAC), Caltech. We coin this system the IPAC/iPTF Discovery Engine (or IDE). We review the algorithms used for PSF-matching, image subtraction, detection, photometry, and machine-learned (ML) vetting of extracted transient candidates. We also review the performance of our ML classifier. For a limiting signal-to-noise ratio of 4 in relatively unconfused regions, bogus candidates from processing artifacts and imperfect image subtractions outnumber real transients by approximately equal to 10:1. This can be considerably higher for image data with inaccurate astrometric and/or PSF-matching solutions. Despite this occasionally high contamination rate, the ML classifier is able to identify real transients with an efficiency (or completeness) of approximately equal to 97% for a maximum tolerable false-positive rate of 1% when classifying raw candidates. All subtraction-image metrics, source features, ML probability-based real-bogus scores, contextual metadata from other surveys, and possible associations with known Solar System objects are stored in a relational database for retrieval by the various science working groups. We review our efforts in mitigating false-positives and our experience in optimizing the overall system in response to the multitude of science projects underway with iPTF.

methods: analytical – methods: data analysis –

The WIRE Image Simulator

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WIRE starburst galaxies BIB detector arrays source