arXiv subjects

Allison Lin

Publications and source records attributed to Allison Lin.

3 recordsLinked to original sources

arXiv2026

Illuminating M82: Simulating X-ray Emission from Galactic Winds in a Starburst Galaxy

We generate mock X-ray observations from a suite of idealized high-resolution ($\sim 4$ pc), tall-box ($\sim 2 \times 2 \times 8$ kpc$^3$) simulations of star formation driven galactic winds in an M82-like system, varying the spatial resolution as well as the strength and distribution of supernova (SN) energy injection. We compare our mock X-ray observations with deep Chandra observations of the hot plasma around M82. While the simulated total X-ray luminosity, $L_X$, increases with resolution and when SNe feedback is spatially distributed, even in the best case scenario, our simulated $L_X$ is a factor of $\sim 50-100$ lower than observed and the surface brightness profiles of X-ray emission, $S_X(z)$, fall off too quickly with distance from the galaxy. Past results were able to reproduce these observables and we discuss potential simulation differences that could explain this discrepancy. We make the first comparison of the X-ray spectrum of our simulations to observations and find that our simulated spectrum is too soft, with a deficit of hard X-ray photons at $\gtrsim 1$ keV. We discuss how physical processes missing from our simulations and prior work (e.g., thermal conduction and cosmic rays) could help resolve this discrepancy.

astro-ph.GA↗

arXiv2025

Lomb-Scargle periodograms struggle with non-sinusoidal supermassive BH binary signatures in quasar lightcurves

Supermassive black hole binary (SMBHB) systems are expected to form as a consequence of galaxy mergers. At sub-parsec separations, SMBHBs can be identified as quasars with periodic variability with previous periodicity searches uncovering significant candidates. However, these searches focused primarily on sinusoidal signals, while theoretical models and hydrodynamical simulations predict that binaries produce more complex non-sinusoidal pulse shapes. Here we examine the efficacy of the Lomb-Scargle periodogram (LSP; one of the most popular tools for periodicity searches in unevenly sampled lightcurves) to detect periodicities with a sawtooth shape mimicking results of hydrodynamical simulations. We simulate idealised well-sampled lightcurves, lightcurves that mimic the data in the Palomar Transient Factory (PTF) analyzed in Charisi et al., 2016, and lightcurves that resemble our expectations for single-band data in the upcoming Legacy Survey of Space and Time (LSST) of the Rubin Observatory. We approximate quasar variability with a damped random walk (DRW) model, inject sinusoidal and sawtooth pulse shapes and assess their statistical significance. We find that in the presence of red noise the LSP detects a relatively low fraction of the sinusoidal signals (~45%, ~24% and ~23%, in the PTF-like, idealised, and LSST-like lightcurves, respectively). The fraction is significantly reduced for sawtooth periodicity (with only ~9% in PTF-like and ~1% in idealised and LSST-like lightcurves). These low recovery rates imply that previous searches have missed the large majority of binaries. They also have significant implications for the detection of SMBHBs in upcoming LSST necessitating the developement of advanced tools that go beyond the simple LSP.

astro-ph.HE↗

arXiv2024

Periodicity significance testing with null-signal templates: reassessment of PTF's SMBH binary candidates

Periodograms are widely employed for identifying periodicity in time series data, yet they often struggle to accurately quantify the statistical significance of detected periodic signals when the data complexity precludes reliable simulations. We develop a data-driven approach to address this challenge by introducing a null-signal template (NST). The NST is created by carefully randomizing the period of each cycle in the periodogram template, rendering it non-periodic. It has the same frequentist properties as a periodic signal template regardless of the noise probability distribution, and we show with simulations that the distribution of false positives is the same as with the original periodic template, regardless of the underlying data. Thus, performing a periodicity search with the NST acts as an effective simulation of the null (no-signal) hypothesis, without having to simulate the noise properties of the data. We apply the NST method to the supermassive black hole binaries (SMBHB) search in the Palomar Transient Factory (PTF), where Charisi et al. had previously proposed 33 high signal to (white) noise candidates utilizing simulations to quantify their significance. Our approach reveals that these simulations do not capture the complexity of the real data. There are no statistically significant periodic signal detections above the non-periodic background. To improve the search sensitivity we introduce a Gaussian quadrature based algorithm for the Bayes Factor with correlated noise as a test statistic, in contrast to the standard signal to white noise. We show with simulations that this improves sensitivity to true signals by more than an order of magnitude. However, using the Bayes Factor approach also results in no statistically significant detections in the PTF data.

astro-ph.GA↗