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The sample of time-delay gravitational lenses appropriate for studying the geometry of the Universe continues to grow as dedicated campaigns, such as the Dark Energy Survey, the (Very Large Telescope) VLT Survey Telescope (VST) ATLAS survey, and the Large Synoptic Survey Telescope, complete their census of high-redshift sources. This catalogue now includes hundreds of strong lensing systems, at least 31 of which have reasonably accurate time-delay measurements. In this paper, we use them to compare the predictions of two competing Friedmann–Lemaître–Robertson–Walker models: flat Lambda cold dark matter (ΛCDM), characterized by two adjustable parameters (H 0 and Ωm), and the R h = ct universe (with H 0 as the single free variable). Over the past decade, the latter has accounted for the data better than the standard model, most recently the emergence of well-formed galaxies discovered by JWST at cosmic dawn. Here, we show that the current sample of time-delay lenses favours R h = ct with a likelihood of ∼ |$84{{\ \rm per\ cent}}$| versus ∼ |$16{{\ \rm per\ cent}}$| for the standard model. This level of accuracy will greatly improve as the ongoing surveys uncover many thousands of additional lens systems over the next several years. [ABSTRACT FROM AUTHOR]

The accurate estimation of photometric redshifts plays a crucial role in accomplishing science objectives of the large survey projects. Template-fitting and machine learning are the two main types of methods applied currently. Based on the training set obtained by cross-correlating the DESI Legacy Imaging Surveys DR9 galaxy catalogue and the SDSS DR16 galaxy catalogue, the two kinds of methods are used and optimized, such as eazy for template-fitting approach and catboost for machine learning. Then, the created models are tested by the cross-matched samples of the DESI Legacy Imaging Surveys DR9 galaxy catalogue with LAMOST DR7, GAMA DR3, and WiggleZ galaxy catalogues. Moreover, three machine learning methods (catboost , Multi-Layer Perceptron, and Random Forest) are compared; catboost shows its superiority for our case. By feature selection and optimization of model parameters, catboost can obtain higher accuracy with optical and infrared photometric information, the best performance (⁠|$\rm MSE=0.0032$|⁠ , σNMAD = 0.0156, and |$O=0.88{{\ \rm per\ cent}}$|⁠) with g ≤ 24.0, r ≤ 23.4, and z ≤ 22.5 is achieved. But eazy can provide more accurate photometric redshift estimation for high redshift galaxies, especially beyond the redshift range of training sample. Finally, we finish the redshift estimation of all DESI Legacy Imaging Surveys DR9 galaxies with catboost and eazy , which will contribute to the further study of galaxies and their properties. [ABSTRACT FROM AUTHOR]

We extend the standard model of forward–reverse shock (FS–RS) for gamma-ray burst (GRB) afterglow to more general cases. On one hand, we derive the analytical solution to the hydrodynamics of the shocks in two limiting cases, i.e. an ultrarelativistic reverse shock case and a Newtonian reverse shock case. Based on the asymptotic solutions in these two limiting cases, we constitute a semi-analytical solution for the hydrodynamics of the shocks in the generic case, covering the mildly relativistic reverse shock case. On the other hand, we derive the evolution of the system taking into account the condition of energy conservation which is not satisfied in the standard FS–RS model. A generic solution of semi-analytical expressions is also given. In both the extended standard FS–RS model (satisfying pressure balance condition) and the model satisfying energy conservation, we find that the results in the ultrarelativistic reverse shock case and in the early stage of the Newtonian reverse shock case are different from those in the standard FS–RS model by only a factor that close to one while the same initial conditions adopted. However, the asymptotic solutions in the limiting cases are not good approximations to those in the intermediate case. Our semi-analytical results agree well with the numerical results for a large range of model parameters, and hence can be easily employed to diagnose the physical quantities of the GRB shell and circumburst environment. [ABSTRACT FROM AUTHOR]