We present a theoretical framework for calculating the volume filling fraction of galactic outflows in cosmic voids by integrating analytical models for the halo mass function (HMF), the halo occupation fraction, the stellar mass-halo mass relation, and outflow sizes. Using RAMSES, we perform a hydrodynamical zoom-in simulation of the central 25 cMpc/h region of a spherical void, identified as the lowest-density region among 1,000 random spheres in a parent 1 Gpc box simulation. This void has a diameter of 120 cMpc/h and a density contrast of $\delta \simeq -0.8$. We find that the properties of void galaxies remain stable when expanding the zoom-in region to 50 cMpc/h, though our relatively low mass resolution impacts the results. Our higher-resolution simulation aligns with the analytical HMF that accounts for the void's underdensity and size. While higher resolution improves stellar mass estimates for low-mass halos, computational constraints necessitate a theoretical framework that enables extrapolation to infinite resolution. Our analytical model, calibrated to our simulations, enables extrapolation down to the filtering mass of star-forming halos. To compare galaxy properties in this void with those in the field, we conduct a companion field simulation of the same box size. At infinite resolution, we predict wind volume filling fractions of $18.6\%$ in the field and $3.1\%$ in our void, with values dependent on cosmic variance, void size, and underdensity. Dwarf galaxies contribute minimally, and resolving halos to $M_{\rm h}=10^{10} M_\odot$ suffices for robust estimates. Applying our framework to the Local Group void ($\delta \simeq -0.5$, $R=20\ \mathrm{cMpc}$), we predict a wind volume filling fraction of $9.6\%\pm3.3\%$.
The systematic properties are largely unknown for the black hole X-ray binary Swift J151857.0--572147 newly discovered in the 2024 outburst. The nature of a black hole can be completely defined by specifying the mass and dimensionless spin parameter. Therefore, accurate measurement of the two fundamental parameters is important for understanding the nature of black holes. The joint spectral fitting of a reflection component with simultaneous observations from Insight-HXMT, NICER and NuSTAR reveals for the first time a black hole dimensionless spin of $0.84^{+0.17}_{-0.26}$ and an inclination angle of $21.1^{+4.5}_{-3.6}$ degree for this system. Monitoring of the soft state by NICER results in disk flux and temperature following $F_{\rm disk} \propto T_{\rm in}^{3.83\pm 0.17}$. For the standard thin disk, $L_{\rm disk}\approx 4\pi R_{\rm in}^{2}\sigma T_{\rm in}^{4}$, so the relationship between the flux and temperature of the disk we measured indicates that the inner radius of the disk is stable and the disk is in the Innermost Stable Circular Orbit. With an empirical relation built previously between the black hole outburst profile and the intrinsic power output, the source distance is estimated as $5.8\pm 2.5$ kpc according to the outburst profile and peak flux observed by Insight-HXMT and NICER. Finally, a black hole mass of $3.67\pm1.79-8.07\pm 4.20 M_\odot$ can be inferred from a joint diagnostic of the aforementioned parameters measured for this system. This system is also consistent with most black hole X-ray binaries with high spin and a mass in the range of 5--20 $M_\odot$
We study the spectral properties of the black hole X-ray transient binary 4U 1630--472 during the 2022 and 2023 outbursts with Insight-HXMT observations. We find that the outbursts are in peculiar soft states. The effect of the hardening factor on the disk temperature is taken into account by kerrbb, and the flux and temperature of the disk are found to follow $F \propto T_{\rm eff}^{3.92\pm 0.13}$ and $F \propto T_{\rm eff}^{4.91\pm 1.00}$, for the two outbursts respectively. The flux-temperature relation is roughly consistent with holding a standard disk, By fitting with the p-free model, the p-value is found to have anti-correlation with disk temperature. Combined a joint diagnostic in a diagram of the relation between the non-thermal fraction and luminosity, by enclosing as well the previous outbursts, reveals a possible pattern for the disk evolution toward a slim one, and such an evolution may depend on the fraction of the non-thermal emission in the high soft state.
Understanding the ages of stars is crucial for unraveling the formation history and evolution of our Galaxy. Traditional methods for estimating stellar ages from spectroscopic data often struggle with providing appropriate uncertainty estimations and are severely constrained by the parameter space. In this work, we introduce a new approach using normalizing flows, a type of deep generative model, to estimate stellar ages for evolved stars with improved accuracy and robust uncertainty characterization. The model is trained on stellar masses for evolved stars derived from asteroseismology and predicts the relationship between the carbon and nitrogen abundances of a given star and its age. Unlike standard neural network techniques, normalizing flows enable the recovery of full likelihood distributions for individual stellar ages, offering a richer and more informative perspective on uncertainties. Our method yields age estimations for 378,720 evolved stars and achieves a typical absolute age uncertainty of approximately 2 Gyr. By intrinsically accounting for the coverage and density of the training data, our model ensures that the resulting uncertainties reflect both the inherent noise in the data and the completeness of the sampled parameter space. Applying this method to data from the SDSS-V Milky Way Mapper, we have produced the largest stellar age catalog for evolved stars to date.
In the era of time-domain, multi-messenger astronomy, the detection of transient events on the high-energy electromagnetic sky has become more important than ever. The Gravitational wave high-energy Electromagnetic Counterpart All-sky Monitor (GECAM) is a dedicated mission to monitor gamma-ray transients, launched in December, 2020. A real-time on-board trigger and location software, using the traditional signal-to-noise ratio (SNR) method for blind search, is constrained to relatively bright signals due to the limitations in on-board computing resources and the need for real-time search. In this work, we developed a ground-based pipeline for GECAM to search for various transients, especially for weak bursts missed by on-board software. This pipeline includes both automatic and manual mode, offering options for blind search and targeted search. The targeted search is specifically designed to search for interesting weak bursts, such as gravitational wave-associated gamma-ray bursts (GRBs). From the ground search of the data in the first year, GECAM has been triggered by 54 GRBs and other transients, including soft gamma-ray repeaters, X-ray binaries, solar flares, terrestrial gamma-ray flashes. We report the properties of each type of triggers,such as trigger time and light curves. With this search pipeline and assuming a soft Band spectrum, the GRB detection sensitivity of GECAM is increased to about 1.1E-08 erg cm-2 s-1 (10 keV - 1000 keV, burst duration of 20 s). These results demonstrate that the GECAM ground search system (both blind search and targeted search) is a versatile pipeline to recover true astrophysical signals which were too weak to be found in the on-board search.
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