Galaxies in LCDM with Halo Abundance Matching: luminosity-velocity relation, baryonic mass-velocity relation, velocity function and clustering

It has long been regarded as difficult for a cosmological model to account simultaneously for the galaxy luminosity, mass, and velocity distributions. We revisit this issue using a modern compilation of observational data along with the best available large-scale cosmological simulation of dark matter. We find that the standard cosmological model, used in conjunction with halo abundance matching (HAM) and simple dynamical corrections, fits all basic statistics of galaxies with circular velocities Vcirc > 80 km/s. Our observational constraint is the luminosity-velocity relation which allows all types of galaxies to be included. We have compiled data for a variety of galaxies ranging from dwarf irregulars to giant ellipticals. The data present a clear monotonic luminosity-velocity relation from 50 km/s to 500 km/s, with a bend below 80 km/s and a systematic offset between late- and early-type galaxies. For comparison to theory, we employ our LCDM "Bolshoi" simulation of dark matter, which has unprecedented mass and force resolution. We use halo abundance matching to assign rank-ordered galaxy luminosities to the dark matter halos. The resulting predictions for the luminosity-velocity relation are in excellent agreement with the available data on both early-type and late-type galaxies for the luminosity range from Mr = -14-22. We also compare our predictions for the "cold" baryon mass (i.e., stars and cold gas) of galaxies as a function of circular velocity with the available observations, again finding a very good agreement. The predicted circular velocity function is in agreement with the galaxy velocity function for 80-400 km/s. However, we find that the dark matter halos with Vcirc < 80 km/s are much more abundant than observed galaxies with the same Vcirc . We find that the two-point correlation function of galaxies in our model matches very well the results from the SDSS.Comment: 40 pages, 18 figures, published in Ap

Crowd counting using density maps

Law enforcement agents have to care about the number of people in public areas to ensure security. The problem they have is that they do not have tools to measure the number of people in a fast and precise way. This need has been especially important since 2020 COVID pandemic arrived to our society and the control of people is relevant to avoid spread of COVID. This Master Thesis is complementing other previous Master Thesis presented in 2021 where via an Android app connected to a drone the system was able to count people from the images captured in real time. This solution was only able to count individual people, as crowds of people are complex to measure following standard object detection algorithms as YOLO technology. In our Master Thesis we are adding a new functionality by being able not only to count individuals but also counting crowds of people. With this new functionality the app could provide to the police a more accurate tool to be able to count people in different scenarios as prides, sports events, demonstrations, concerts¿ where crowd is a normal situation. As main technology driver we are working with CNN (Convolutional Neural Networks). First, we have been implementing a CNN density map using the CSRNet technology that is able to count people by measuring the concentration of people. Therefore, an important part of this Master Thesis is to create a process to split the input images in 2 (segmentation process), one for YOLO (individual persons) and other for CSRNET (crowds of people). This process has been implemented using a second CNN called Region-based CNN (R-CNN), that we found it was the most suitable tool to train a model to detect a crowd. The solution has been developed in Google Colab platform and using Python as programming language. We have been working with images taken from drones from Castelldefels Police and UPC but also public datasets. The final solution has been able to detect crowds and calculate the number of people in that crowd with a maximum error of 20% considering Mean Average Percentage Error (MAPE) and 89 considering Mean Absolute Error (MAE).Objectius de Desenvolupament Sostenible::3 - Salut i BenestarObjectius de Desenvolupament Sostenible::11 - Ciutats i Comunitats Sostenible

Hints against the cold and collisionless nature of dark matter from the galaxy velocity function

The observed number of dwarf galaxies as a function of rotation velocity is significantly smaller than predicted by the standard model of cosmology. This discrepancy cannot be simply solved by assuming strong baryonic feedback processes, since they would violate the observed relation between maximum circular velocity ($v_{\rm max}$) and baryon mass of galaxies. A speculative but tantalising possibility is that the mismatch between observation and theory points towards the existence of non-cold or non-collisionless dark matter (DM). In this paper, we investigate the effects of warm, mixed (i.e warm plus cold), and self-interacting DM scenarios on the abundance of dwarf galaxies and the relation between observed HI line-width and maximum circular velocity. Both effects have the potential to alleviate the apparent mismatch between the observed and theoretical abundance of galaxies as a function of $v_{\rm max}$. For the case of warm and mixed DM, we show that the discrepancy disappears, even for luke-warm models that evade stringent bounds from the Lyman-$\alpha$ forest. Self-interacting DM scenarios can also provide a solution as long as they lead to extended ($\gtrsim 1.5$ kpc) dark matter cores in the density profiles of dwarf galaxies. Only models with velocity-dependent cross sections can yield such cores without violating other observational constraints at larger scales.Comment: Matches published versio

Low-mass galaxy assembly in simulations: regulation of early star formation by radiation from massive stars

Despite recent success in forming realistic present-day galaxies, simulations still form the bulk of their stars earlier than observations indicate. We investigate the process of stellar mass assembly in low-mass field galaxies, a dwarf and a typical spiral, focusing on the effects of radiation from young stellar clusters on the star formation (SF) histories. We implement a novel model of SF with a deterministic low efficiency per free-fall time, as observed in molecular clouds. Stellar feedback is based on observations of star-forming regions, and includes radiation pressure from massive stars, photoheating in H II regions, supernovae and stellar winds. We find that stellar radiation has a strong effect on the formation of low-mass galaxies, especially at z > 1, where it efficiently suppresses SF by dispersing cold and dense gas, preventing runaway growth of the stellar component. This behaviour is evident in a variety of observations but had so far eluded analytical and numerical models without radiation feedback. Compared to supernovae alone, radiation feedback reduces the SF rate by a factor of ~100 at z < 2, yielding rising SF histories which reproduce recent observations of Local Group dwarfs. Stellar radiation also produces bulgeless spiral galaxies and may be responsible for excess thickening of the stellar disc. The galaxies also feature rotation curves and baryon fractions in excellent agreement with current data. Lastly, the dwarf galaxy shows a very slow reduction of the central dark matter density caused by radiation feedback over the last ~7 Gyr of cosmic evolution

Another baryon miracle? Testing solutions to the 'missing dwarfs' problem

The dearth of dwarf galaxies in the local universe is hard to reconcile with the large number of low mass haloes expected within the concordance $\Lambda$CDM paradigm. In this paper we perform a systematic evaluation of the uncertainties affecting the measurement of DM halo abundance using galaxy kinematics. Using a large sample of dwarf galaxies with spatially resolved kinematic data we derive a correction to obtain the observed abundance of galaxies as a function of their halo maximum circular velocity from the line-of-sight velocity function in the Local Volume. This estimate provides a direct means of comparing the predictions of theoretical models and simulations (including nonstandard cosmologies and novel galaxy formation physics) to the observational constraints. The new "galactic $V_{max}$" function is steeper than the line-of-sight velocity function but still shallower than the theoretical CDM expectation, showing that some unaccounted physical process is necessary to reduce the abundance of galaxies and/or drastically modify their density profiles compared to CDM haloes. Using this new galactic $V_{max}$ function, we investigate the viability of baryonic solutions such as feedback-powered outflows and photoevaporation of gas from an ionising radiation background. At the 3-$\sigma$ confidence level neither energetic feedback nor photoevaporation are effective enough to reconcile the disagreement. In the case of maximum baryonic effects, the theoretical estimate still deviates significantly from the observations for $V_{max} < 60$ km/s. CDM predicts at least 1.8 times more galaxies with $V_{max} = 50$ km/s and 2.5 times more than observed at $30$ km/s. Recent hydrodynamic simulations seem to resolve the discrepancy but disagree with the properties of observed galaxies with resolved kinematics. (abridged)Comment: 17 pages, 22 figures; major revisions include clarification of the method, expanded comparison with simulations with a new figure, analysis of uncertainties in model as well as pressure support corrections, and a new table with nomenclatur