Context. Recent years have given rise to numerous methods of detecting the cosmic web elements in the large-scale structure of the Universe. All of these methods describe more or less the same features, but each with its nuance. The Bisous filament finder is a stochastic tool for identifying the spines of filaments using galaxy positions. Aims. This work provides an analysis of how the galaxy number density of the input data affects the filaments detected with the Bisous model and gives estimates of the reliability of the method itself to assess the robustness of the results. Methods. We applied the Bisous filament finder to MultiDark-Galaxies data, using various magnitude cuts from the catalogue to study the effects of different galaxy number densities on the results and different parameters of the model. We compared the structures by the fraction of galaxies in filaments and the volume filled by filaments, and we analysed the similarities between the results from different cuts based on the overlap between detected filamentary structures. The filament finder was also applied to the exact same data 200 times with the same parameters to study the stochasticity of the results and the correlation between different runs was calculated. Results. Multiple samples show that galaxies in filaments have preferentially higher luminosity. We found that when a galaxy is in a filament there is a 97% chance that the same galaxy would be in a filament with even more complete input data and about 85% of filaments are persistent when detecting the filamentary network with higher-density input data. Lower galaxy number density inputs mean the Bisous model finds fewer filaments, but the filaments found are persistent even if we use more complete input data for the detection. We calculated the correlation coefficient between 200 Bisous runs on the exact same input, which is 0.98. Conclusions. This study confirms that increased number density of galaxies is important to obtain a more complete picture of the cosmic web. To overcome the limitation of the spectroscopic surveys, we will develop the Bisous model further to apply this tool to combined spectroscopic and narrow-band photometric redshift surveys, such as the J-PAS.

Large multi-object spectroscopic surveys require automated algorithms to optimise their observing strategy. One of the most ambitious upcoming spectroscopic surveys is the 4MOST survey. The 4MOST survey facility is a fibre-fed spectroscopic instrument on the VISTA telescope with a large enough field of view to survey a large fraction of the southern sky within a few years. Several Galactic and extragalactic surveys will be carried out simultaneously, so the combined target density will strongly vary. In this paper, we describe a new tiling algorithm that can naturally deal with the large target density variations on the sky and which automatically handles the different exposure times of targets. The tiling pattern is modelled as a marked point process, which is characterised by a probability density that integrates the requirements imposed by the 4MOST survey. The optimal tilling pattern with respect to the defined model is estimated by the tiles configuration that maximises the proposed probability density. In order to achieve this maximisation a simulated annealing algorithm is implemented. The algorithm automatically finds an optimal tiling pattern and assigns a tentative sky brightness condition and exposure time for each tile, while minimising the total execution time that is needed to observe the list of targets in the combined input catalogue of all surveys. Hence, the algorithm maximises the long-term observing efficiency and provides an optimal tiling solution for the survey. While designed for the 4MOST survey, the algorithm is flexible and can with simple modifications be applied to any other multi-object spectroscopic survey.

Context. The importance of photometric galaxy redshift estimation is rapidly increasing with the development of specialised powerful observational facilities. Aims. We develop a new photometric redshift estimation workflow TOPz to provide reliable and efficient redshift estimations for the upcoming large-scale survey J-PAS which will observe 8500 deg 2 of the northern sky through 54 narrow-band filters. Methods. TOPz relies on template-based photo-z estimation with some added J-PAS specific features and possibilities. We present TOPz performance on data from the miniJPAS survey, a precursor to the J-PAS survey with an identical filter system. First, we generated spectral templates based on the miniJPAS sources using the synthetic galaxy spectrum generation software CIGALE. Then we applied corrections to the input photometry by minimising systematic offsets from the template flux in each filter. To assess the accuracy of the redshift estimation, we used spectroscopic redshifts from the DEEP2, DEEP3, and SDSS surveys, available for 1989 miniJPAS galaxies with r < 22 mag AB . We also tested how the choice and number of input templates, photo-z priors, and photometric corrections affect the TOPz redshift accuracy. Results. The general performance of the combination of miniJPAS data and the TOPz workflow fulfills the expectations for J-PAS redshift accuracy. Similarly to previous estimates, we find that 38.6% of galaxies with r < 22 mag reach the J-PAS redshift accuracy goal of dz/(1 + z) < 0.003. Limiting the number of spectra in the template set improves the redshift accuracy up to 5%, especially for fainter, noise-dominated sources. Further improvements will be possible once the actual J-PAS data become available.