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Abstract:

Abstract Fast X-ray transients (FXTs) are brief, luminous bursts of soft X-ray emission whose physical origins remain uncertain. The Einstein Probe (EP) mission has recently enabled prompt discovery of these events, providing opportunities for rapid multi-wavelength follow-up. We present a coordinated radio observing campaign targeting 20 FXTs detected by the EP in 2024. The core consists of 59 epochs with the Allen Telescope Array (ATA), sampling post-burst timescales from ~1 to ~65 days and reaching typical 3σ sensitivities of 0.6–1.5 mJy across 1–8 GHz. We additionally incorporate higher-sensitivity observations from MeerKAT, the VLA, ATCA, eMERLIN, and AMI-LA. Two FXTs—EP240315a and EP241021a—have radio counterparts. For EP241021a, AMI-LA monitoring at 15.5 GHz reveals a light curve peaking at ~30 days with Fν ≈ 1.0 mJy; equipartition analysis implies a Newtonian equipartition energy of ~3 × 1049 erg and a mildly relativistic on-axis solution with Γon ≈ 1.3. Multi-frequency modelling of EP240315a, combining new VLA measurements with published MeerKAT, ATCA, and eMERLIN data, indicates highly relativistic early emission (Γ ≳ 3) that decelerates with time, consistent with jetted outflow. The detections and ATA non-detections span luminosities overlapping the brightest GRB and relativistic tidal disruption event (TDE) afterglows, suggesting FXTs comprise a heterogeneous population including both relativistic and non-relativistic explosions. Under a GRB-like redshift prior, our 3σ ATA limits correspond to observer-frame specific-luminosity thresholds of ~1032–1033 erg s−1 Hz−1; for nearby events (z ≲ 0.2), Lν ≲ 1030–31 erg s−1 Hz−1. Planned ATA upgrades and next-generation arrays (SKA, DSA, ngVLA) will enable sensitive, population-level radio studies of the FXT radio sky.

Abstract:

Abstract The structure of dark matter haloes is often described by radial density profiles motivated by cosmological simulations. These are typically assumed to have a fixed functional form (e.g. NFW), with some free parameters. However, relying on simulations has the disadvantage that the resulting profiles depend on the dark matter model and the baryonic physics implementation, which are highly uncertain. Instead, we present a method to constrain halo density profiles directly from observations. This is done using a symbolic regression algorithm called Exhaustive Symbolic Regression (ESR). ESR searches for the optimal analytic expression to fit data, combining both accuracy and simplicity. We apply ESR to a sample of 149 galaxy clusters from the HSC-XXL survey to identify which functional forms perform best across the entire sample of clusters. We identify density profiles that statistically outperform NFW under a minimum-description-length criterion. Within the radial range probed by the weak-lensing data (R ~ 0.3 − 3 h−1 Mpc), the highest-ranked ESR profiles exhibit shallow inner behaviour and a maximum in the density profile. As a practical application, we show how the best-fitting ESR models can be used to obtain enclosed mass estimates. We find masses that are, on average, higher than those derived using NFW, highlighting a source of potential bias when assuming the wrong density profile. These results have important knock-on effects for analyses that utilise clusters, for example cosmological constraints on σ8 and Ωm from cluster abundance and clustering. Beyond the HSC dataset, the method is applicable to any data constraining the dark matter distribution in galaxies and galaxy clusters, such as other weak lensing surveys, galactic rotation curves, or complementary probes.