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Robert Campion

Publications and source records attributed to Robert Campion.

Anti-Glitches in the Ultraluminous Accreting Pulsar NGC 300 ULX-1 Observed with NICER

We present evidence for three spin-down glitches (or “anti-glitches”) in the ultraluminous accreting X-ray pulsar NGC 300 ULX-1, in timing observations made with the Neutron Star Interior Composition Explorer. Our timing analysis reveals three sudden spin-down events of magnitudes Δν=−23, −30, and −43 μHz (fractional amplitudes Δν/ν=−4.4, −5.5, and −7.7×10−4). We determined fully phase-coherent timing solutions through the first two glitches, giving us high confidence in their detection, while the third candidate glitch is somewhat less secure. These are larger in magnitude (and opposite in sign) than any known radio pulsar glitch. This may be caused by the prolonged rapid spin up of the pulsar, causing a sudden transfer of angular momentum between the superfluid and non-superfluid components of the star. We find no evidence for profile or spectral changes at the epochs of the glitches, supporting the conclusion that these are due to the same process as in normal pulsar glitches, but in reverse.

Paul S Ray↗

Machine Learning Algorithms for Alignment Verification of the Roman Space Telescope

The Nancy Grace Roman Telescope is a NASA observatory designed to unravel the secrets of dark energy and dark matter, search for and image exoplanets, and explore many topics in infrared optics. Scheduled to launch no earlier than October 2026, this 2.4 meter aperture telescope has a field of view 100 times greater than the Hubble Space Telescope. The mission is currently in its construction phase, where the telescope and its two instruments will soon be aligned together to ensure proper pupil matching. To help verify this alignment, multiple point sources above the entrance pupil of the telescope will illuminate the optical path through the telescope-instrument system, and shadows of various obstructions in the system will be analyzed using machine learning algorithms to determine the pupil matching error. This presentation discusses the test approach and the machine learning algorithms employed, as well as our uncertainty predictions based on a modeled Monte-Carlo analysis of the test.

Telescope↗