arXiv subjects

R. Hausen

Publications and source records attributed to R. Hausen.

5 recordsLinked to original sources

arXiv2026

Teglon: A Pixel-Level Pipeline for Galaxy-Informed Gravitational-Wave Follow-up Planning and Efficiency Analysis

We describe Teglon, an open-source database and analysis pipeline engineered to optimize the search for electromagnetic (EM) counterparts to gravitational wave (GW) sources. Teglon constructs a 3D galaxy completeness metric from an input galaxy catalog and convolves it with the 3D localization volume of a GW event, producing an updated posterior map informed by known galaxy distributions. Using Teglon, users can ingest arbitrary instrument footprints --- or download them directly from the Treasure Map --- to generate dynamic observation plans that seamlessly interpolate between targeted galaxy pointing and region tiling. By focusing efforts on high-probability volumes, Teglon significantly reduces the predicted search area to find EM counterparts and increases observational efficiency, especially for small field-of-view (<= 1 deg^2) instruments like the Nancy Grace Roman Space Telescope. Furthermore, Teglon integrates with Redback to calculate pixel-level model detection efficiencies, enabling custom, event-specific observing strategies or retrospective detection efficiencies on an arbitrary grid of EM transient models. Teglon also supports custom science cases, such as prioritizing Active Galactic Nuclei searches for EM counterparts to binary black hole mergers. Having supported Gravity Collective and related programs from the LIGO-Virgo-KAGRA third observing run (O3) through O4, Teglon is being continuously developed to support O5 and beyond. We document the public repository lineage and packaging, and provide Version 2.0 as an open-source tool for the community.

astro-ph.HE↗

arXiv2024

The Gravity Collective: A Comprehensive Analysis of the Electromagnetic Search for the Binary Neutron Star Merger GW190425

We present an ultraviolet-to-infrared search for the electromagnetic (EM) counterpart to GW190425, the second-ever binary neutron star (BNS) merger discovered by the LIGO-Virgo-KAGRA Collaboration (LVK). GW190425 was more distant and had a larger localization area than GW170817, therefore we use a new tool teglon to redistribute the GW190425 localization probability in the context of galaxy catalogs within the final localization volume. We derive a 90th percentile area of 6,688 deg$^{2}$, a $\sim$1.5$\times$ improvement relative to the LIGO/Virgo map, and show how teglon provides an order of magnitude boost to the search efficiency of small ($\leq$1 deg$^{2}$) field-of-view instruments. We combine our data with all publicly reported imaging data, covering 9,078.59 deg$^2$ of unique area and 48.13% of the LIGO/Virgo-assigned localization probability, to calculate the most comprehensive kilonova, short gamma-ray burst (sGRB) afterglow, and model-independent constraints on the EM emission from a hypothetical counterpart to GW190425 to date under the assumption that no counterpart was found in these data. If the counterpart were similar to AT 2017gfo, there was a 28.4% chance that it would have been detected in the combined dataset. We are relatively insensitive to an on-axis sGRB, and rule out a generic transient with a similar peak luminosity and decline rate as AT 2017gfo to 30% confidence. Finally, across our new imaging and all publicly-reported data, we find 28 candidate optical counterparts that we cannot rule out as being associated with GW190425, finding that 4 such counterparts discovered within the localization volume and within 5 days of merger exhibit luminosities consistent with a kilonova.

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arXiv2023

Low-mass bursty galaxies in JADES efficiently produce ionising photons and could represent the main drivers of reionisation

We study galaxies in JADES Deep to study the evolution of the ionising photon production efficiency, $ξ_{\rm{ion}}$, observed to increase with redshift. We estimate $ξ_{\rm{ion}}$ for a sample of 677 galaxies at $z \sim 4 - 9$ using NIRCam photometry. Specifically, combinations of the medium and wide bands F335M-F356W and F410M-F444W to constrain emission lines that trace $ξ_{\rm{ion}}$: H$α$ and [OIII]. Additionally, we use the spectral energy distribution fitting code \texttt{Prospector} to fit all available photometry and infer galaxy properties. The flux measurements obtained via photometry are consistent with FRESCO and NIRSpec-derived fluxes. Moreover, the emission-line-inferred measurements are in tight agreement with the \texttt{Prospector} estimates. We also confirm the observed $ξ_{\rm{ion}}$ trend with redshift and M$_{\rm{UV}}$, and find: $\log ξ_{\rm{ion}} (z,\text{M}_{\rm{UV}}) = (0.05 \pm 0.02)z + (0.11 \pm 0.02) \text{M}_{\rm{UV}} + (27.33 \pm 0.37)$. We use \texttt{Prospector} to investigate correlations of $ξ_{\rm{ion}}$ with other galaxy properties. We see a clear correlation between $ξ_{\rm{ion}}$ and burstiness in the star formation history of galaxies, given by the ratio of recent to older star formation, where burstiness is more prevalent at lower stellar masses. We also convolve our $ξ_{\rm{ion}}$ relations with luminosity functions from the literature, and constant escape fractions of 10 and 20\%, to place constraints on the cosmic ionising photon budget. By combining our results, we find that if our sample is representative of the faint low-mass galaxy population, galaxies with bursty star formation are efficient enough in producing ionising photons and could be responsible for the reionisation of the Universe.

astro-ph.GA↗

arXiv2023

Identification and properties of intense star-forming galaxies at redshifts z>10

Surveys with James Webb Space Telescope (JWST) have discovered candidate galaxies in the first 400 Myr of cosmic time. Preliminary indications have suggested these candidate galaxies may be more massive and abundant than previously thought. However, without confirmed distances, their inferred properties remain uncertain. Here we identify four galaxies located in the JWST Advanced Deep Extragalactic Survey (JADES) Near-Infrared Camera (NIRCam) imaging with photometric redshifts z~10-13. These galaxies include the first redshift z>12 systems discovered with distances spectroscopically confirmed by JWST in a companion paper. Using stellar population modelling, we find the galaxies typically contain a hundred million solar masses in stars, in stellar populations that are less than one hundred million years old. The moderate star formation rates and compact sizes suggest elevated star formation rate surface densities, a key indicator of their formation pathways. Taken together, these measurements show that the first galaxies contributing to cosmic reionisation formed rapidly and with intense internal radiation fields.

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arXiv2023

Identification of tidal features in deep optical galaxy images with Convolutional Neural Networks

Interactions between galaxies leave distinguishable imprints in the form of tidal features which hold important clues about their mass assembly. Unfortunately, these structures are difficult to detect because they are low surface brightness features so deep observations are needed. Upcoming surveys promise several orders of magnitude increase in depth and sky coverage, for which automated methods for tidal feature detection will become mandatory. We test the ability of a convolutional neural network to reproduce human visual classifications for tidal detections. We use as training $\sim$6000 simulated images classified by professional astronomers. The mock Hyper Suprime Cam Subaru (HSC) images include variations with redshift, projection angle and surface brightness ($μ_{lim}$ =26-35 mag arcsec$^{-2}$). We obtain satisfactory results with accuracy, precision and recall values of Acc=0.84, P=0.72 and R=0.85, respectively, for the test sample. While the accuracy and precision values are roughly constant for all surface brightness, the recall (completeness) is significantly affected by image depth. The recovery rate shows strong dependence on the type of tidal features: we recover all the images showing shell features and 87% of the tidal streams; these fractions are below 75% for mergers, tidal tails and bridges. When applied to real HSC images, the performance of the model worsens significantly. We speculate that this is due to the lack of realism of the simulations and take it as a warning on applying deep learning models to different data domains without prior testing on the actual data.

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