arXiv subjects

Peter W. Hatfield

Publications and source records attributed to Peter W. Hatfield.

4 recordsLinked to original sources

arXiv2023

MIGHTEE-HI: The HI mass-stellar mass relation over the last billion years

We study the $M_{\rm HI}-M_{\star}$ relation over the last billion years using the MIGHTEE-HI sample. We first model the upper envelope of the $M_{\rm HI}-M_{\star}$ relation with a Bayesian technique applied to a total number of 249 HI-selected galaxies, without binning the datasets, while taking account of the intrinsic scatter. We fit the envelope with both linear and non-linear models, and find that the non-linear model is preferred over the linear one with a measured transition stellar mass of $\log_{10}(M_\star$/$M_{\odot})$ = $9.15\pm0.87$, beyond which the slope flattens. This finding supports the view that the lack of HI gas is ultimately responsible for the decreasing star formation rate observed in the massive main-sequence galaxies. For spirals alone, which are biased towards the massive galaxies in our sample, the slope beyond the transition mass is shallower than for the full sample, indicative of distinct gas processes ongoing for the spirals/high-mass galaxies from other types with lower stellar masses. We then create mock catalogues for the MIGHTEE-HI detections and non-detections with two main galaxy populations of late- and early-type galaxies to measure the underlying $M_{\rm HI}-M_{\star}$ relation. We find that the turnover in this relation persists whether considering the two galaxy populations as a whole or separately. We note that an underlying linear relation could mimic this turnover in the observed scaling relation, but a model with a turnover is strongly preferred. Measurements on the logarithmic average of HI masses against the stellar mass are provided as a benchmark for future studies.

astro-ph.GA↗

arXiv2023

Spectral age distribution for radio-loud active galaxies in the XMM-LSS field

Jets of energetic particles, as seen in FR type-I and FR type-II sources, ejected from the center of Radio-Loud AGN affect the sources surrounding intracluster medium/intergalactic medium. Placing constraints on the age of such sources is important in order to measure the jet powers and determine the effects on feedback. To evaluate the age of these sources using spectral age models, we require high-resolution multi-wavelength data. The new sensitive and high-resolution MIGHTEE survey of the XMM-LSS field along with data from the Low Frequency Array (LOFAR) and the Giant Metrewave Radio Telescope (GMRT) provide data taken at different frequencies with similar resolution, which enables us to determine the spectral age distribution for radio loud AGN in the survey field. In this study we present a sample of 28 radio galaxies with their best fitting spectral age distribution analyzed using the Jaffe-Perola (JP) model on a pixel-by-pixel basis. Fits are generally good and objects in our sample show maximum ages within the range of 2.8 Myr to 115 Myr with a median of 8.71 Myr. High-resolution maps over a range of frequencies are required to observe detailed age distributions for small sources and high-sensitivity maps will be needed in order to observe fainter extended emission. We do not observe any correlation between the total physical size of the sources and their age and we speculate both dynamical models and the approach to spectral age analysis may need some modification to account for our observations.

astro-ph.GA↗

arXiv2021

The data-driven future of high energy density physics

The study of plasma physics under conditions of extreme temperatures, densities and electromagnetic field strengths is significant for our understanding of astrophysics, nuclear fusion and fundamental physics. These extreme physical systems are strongly non-linear and very difficult to understand theoretically or optimize experimentally. Here, we argue that machine learning models and data-driven methods are in the process of reshaping our exploration of these extreme systems that have hitherto proven far too non-linear for human researchers. From a fundamental perspective, our understanding can be helped by the way in which machine learning models can rapidly discover complex interactions in large data sets. From a practical point of view, the newest generation of extreme physics facilities can perform experiments multiple times a second (as opposed to ~daily), moving away from human-based control towards automatic control based on real-time interpretation of diagnostic data and updates of the physics model. To make the most of these emerging opportunities, we advance proposals for the community in terms of research design, training, best practices, and support for synthetic diagnostics and data analysis.

physics.plasm-ph↗

arXiv2021

MIGHTEE-HI: The baryonic Tully-Fisher relation over the last billion years

Using a sample of 67 galaxies from the MIGHTEE Survey Early Science data we study the HI-based baryonic Tully-Fisher relation (bTFr), covering a period of $\sim$one billion years ($0 \leq z \leq 0.081 $). We consider the bTFr based on two different rotational velocity measures: the width of the global HI profile and $\rm V_{out}$, measured as the outermost rotational velocity from the resolved HI rotation curves. Both relations exhibit very low intrinsic scatter orthogonal to the best-fit relation ($σ_{\perp}=0.07\pm0.01$), comparable to the SPARC sample at $z \simeq 0$. The slopes of the relations are similar and consistent with the $ z \simeq 0$ studies ($3.66^{+0.35}_{-0.29}$ for $\rm W_{50}$ and $3.47^{+0.37}_{-0.30}$ for $\rm V_{out}$). We find no evidence that the bTFr has evolved over the last billion years, and all galaxies in our sample are consistent with the same relation independent of redshift and the rotational velocity measure. Our results set up a reference for all future studies of the HI-based bTFr as a function of redshift that will be conducted with the ongoing deep SKA pathfinders surveys.

astro-ph.GA↗