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The nature of the minute-to-hour long Fast X-ray Transients (FXTs) localised by telescopes such as Chandra, Swift, and XMM-Newton remains mysterious, with numerous models suggested for the events. Here, we report multi-wavelength observations of EP240315a, a 1600 s long transient detected by the Einstein Probe, showing it to have a redshift of z=4.859. We measure a low column density of neutral hydrogen, indicating that the event is embedded in a low-density environment, further supported by direct detection of leaking ionising Lyman-continuum. The observed properties are consistent with EP240315a being a long-duration gamma-ray burst, and these observations support an interpretation in which a significant fraction of the FXT population are lower-luminosity examples of similar events. Such transients are detectable at high redshifts by the Einstein Probe and, in the (near) future, out to even larger distances by SVOM, THESEUS, and Athena, providing samples of events into the epoch of reionisation., Comment: 41 pages, 7 figures, submitted

GW170817 is a binary neutron star merger that exhibited a gravitational wave (GW) and a gamma-ray burst, followed by an afterglow. In this work, we estimate the Hubble constant ($H_0$) using broad-band afterglow emission and relativistic jet motion from the Very Long Baseline Interferometry and Hubble Space Telescope images of GW170817. Compared to previous attempts, we combine these messengers with GW in a simultaneous Bayesian fit. We probe the $H_0$ measurement robustness depending on the data set used, the assumed jet model, the possible presence of a late time flux excess. Using the sole GW leads to a $20\%$ error ($77^{+21}_{-10}$ km/s/Mpc, medians, 16th-84th percentiles), because of the degeneracy between viewing angle ($\theta_v$) and luminosity distance ($d_L$). The latter is reduced by the inclusion in the fit of the afterglow light curve, leading to $H_0=96^{+13}_{-10}$ km/s/Mpc, a large value, caused by the fit preference for high viewing angles due to the possible presence of a late-time excess in the afterglow flux. Accounting for the latter by including a constant flux component at late times brings $H_0=78.5^{+7.9}_{-6.4}$ km/s/Mpc. Adding the centroid motion in the analysis efficiently breaks the $d_L-\theta_v$ degeneracy and overcome the late-time deviations, giving $H_0 = 69.0^{+4.4}_{-4.3}$ km/s/Mpc (in agreement with Planck and SH0ES measurements) and $\theta_v = 18.2^{+1.2}_{-1.5}$ deg. This is valid regardless of the jet structure assumption. Our simulations show that for next GW runs radio observations are expected to provide at most few other similar events., Comment: 14 pages, 10 figures. Accepted for publication in MNRAS

On August 17, 2017, Advanced LIGO and Virgo observed GW170817, the first gravitational-wave (GW) signal from a binary neutron star merger. It was followed by a short-duration gamma-ray burst, GRB 170817A, and by a non-thermal afterglow emission. In this work, a combined simultaneous fit of the electromagnetic (EM, specifically, afterglow) and GW domains is implemented, both using the posterior distribution of a GW standalone analysis as prior distribution to separately process the EM data, and fitting the EM and GW domains simultaneously. These approaches coincide mathematically, as long as the actual posterior of the GW analysis, and not an approximation, is used as prior for the EM analysis. We treat the viewing angle, $\theta_v$, as shared parameter across the two domains. In the afterglow modelling with a Gaussian structured jet this parameter and the jet core angle, $\theta_c$, are correlated, leading to high uncertainties on their values. The joint EM+GW analysis relaxes this degeneracy, reducing the uncertainty compared to an EM-only fit. We also apply our methodology to hypothetical GW170817-like events occurring in the next GW observing run at $\sim$140 and 70 Mpc. At 70 Mpc the existing EM degeneracy is broken, thanks to the inclusion of the GW domain in the analysis. At 140 Mpc, the EM-only fit cannot constrain $\theta_v$ nor $\theta_c$ because of the lack of detections in the afterglow rising phase. Folding the GW data into the analysis leads to tighter constraints on $\theta_v$, still leaving $\theta_c$ unconstrained, requiring instruments with higher sensitivities, such as Athena., Comment: 15 pages, 10 figures. Accepted for publication in MNRAS

We use a set of about 300 simulated clusters from The Three Hundred Project to calculate their hydrostatic masses and evaluate the associated bias by comparing them with the true cluster mass. Over a redshift range from 0.07 to 1.3, we study the dependence of the hydrostatic bias on redshift, concentration, mass growth, dynamical state, mass, and halo shapes. We find almost no correlation between the bias and any of these parameters. However, there is a clear evidence that the scatter of the mass-bias distribution is larger for low-concentrated objects, high mass growth, and more generically for disturbed systems. Moreover, we carefully study the evolution of the bias of twelve clusters throughout a major-merger event. We find that the hydrostatic-mass bias follows a particular evolution track along the merger process: to an initial significant increase of the bias recorded at the begin of merger, a constant plateaus follows until the end of merge, when there is a dramatic decrease in the bias before the cluster finally become relaxed again. This large variation of the bias is in agreement with the large scatter of the hydrostatic bias for dynamical disturbed clusters. These objects should be avoided in cosmological studies because their exact relaxation phase is difficult to predict, hence their mass bias cannot be trivially accounted for., Comment: 11 pages, 8 figures. Accepted for publication in MNRAS

Galaxy clusters are useful laboratories to investigate the evolution of the Universe, and accurately measuring their total masses allows us to constrain important cosmological parameters. However, estimating mass from observations that use different methods and spectral bands introduces various systematic errors. This paper evaluates the use of a Convolutional Neural Network (CNN) to reliably and accurately infer the masses of galaxy clusters from the Compton-y parameter maps provided by the Planck satellite. The CNN is trained with mock images generated from hydrodynamic simulations of galaxy clusters, with Planck's observational limitations taken into account. We observe that the CNN approach is not subject to the usual observational assumptions, and so is not affected by the same biases. By applying the trained CNNs to the real Planck maps, we find cluster masses compatible with Planck measurements within a 15% bias. Finally, we show that this mass bias can be explained by the well known hydrostatic equilibrium assumption in Planck masses, and the different parameters in the Y500-M500 scaling laws. This work highlights that CNNs, supported by hydrodynamic simulations, are a promising and independent tool for estimating cluster masses with high accuracy, which can be extended to other surveys as well as to observations in other bands., Comment: 17 pages, 3 Figures and Supplementary material (+11 figures). Published in Nature Astronomy

We introduce \textsc{Gizmo-Simba}, a new suite of galaxy cluster simulations within \textsc{The Three Hundred} project. \textsc{The Three Hundred} consists of zoom re-simulations of 324 clusters with $M_{200}\gtrsim 10^{14.8}M_\odot$ drawn from the MultiDark-Planck $N$-body simulation, run using several hydrodynamic and semi-analytic codes. The \textsc{Gizmo-Simba} suite adds a state-of-the-art galaxy formation model based on the highly successful {\sc Simba} simulation, mildly re-calibrated to match $z=0$ cluster stellar properties. Comparing to \textsc{The Three Hundred} zooms run with \textsc{Gadget-X}, we find intrinsic differences in the evolution of the stellar and gas mass fractions, BCG ages, and galaxy colour-magnitude diagrams, with \textsc{Gizmo-Simba} generally providing a good match to available data at $z \approx 0$. \textsc{Gizmo-Simba}'s unique black hole growth and feedback model yields agreement with the observed BH scaling relations at the intermediate-mass range and predicts a slightly different slope at high masses where few observations currently lie. \textsc{Gizmo-Simba} provides a new and novel platform to elucidate the co-evolution of galaxies, gas, and black holes within the densest cosmic environments., Comment: 20 pages, 12 figures, matched to published version in MNRAS

Hydrostatic equilibrium (HE) is often used in observations to estimate galaxy clusters masses. We use a set of almost 300 simulated clusters from The Three Hundred Project, to estimate the cluster HE mass and the bias deriving from it. We study the dependence of the bias on several dynamical state indicators across a redshift range from 0.07 to 1.3, finding no dependence between them. Moreover, we focus our attention on the evolution of the HE bias during the merger phase, where the bias even reaches negative values due to an overestimation of the mass with HE., Comment: To appear in the Proceedings of the International Conference entitled "mm Universe @ NIKA2", Rome (Italy), June 2021, EPJ Web of conferences

Clusters of galaxies are useful tools to constrain cosmological parameters, only if their masses can be correctly inferred from observations. In particular, X-ray and Sunyaev-Zeldovich (SZ) effect observations can be used to derive masses within the framework of the hydrostatic equilibrium. Therefore, it is crucial to have a good control of the possible mass biases that can be introduced when this hypothesis is not valid. In this work, we analyzed a set of 260 synthetic clusters from the MUSIC simulation project, at redshifts $0 \leq z \leq 0.82$. We estimate the hydrostatic mass of the MUSIC clusters from X-ray only (temperature and density) and from X-ray and SZ (density and pressure). Then, we compare them with the true 3D dynamical mass. The biases are of the order of 20%. We find that using the temperature instead of the pressure leads to a smaller bias, although the two values are compatible within 1$\sigma$. Non-thermal contributions to the total pressure support, arising from bulk motion and turbulence of the gas, are also computed and show that they are sufficient to account for this bias. We also present a study of the correlation between the mass bias and the dynamical state of the clusters. A clear correlation is shown between the relaxation state of the clusters and the bias factor. We applied the same analysis on a subsample of 32 objects, already selected for supporting the NIKA2 SZ Large Program., Comment: 19 pages, 16 figures. Accepted for publication in MNRAS