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We study the applications of non-extensive Tsallis statistics to high energy and hadron physics. These applications include studies of $pp$ collisions, equation of state of QCD, as well as Bose-Einstein condensation. We also analyze the connections of Tsallis statistics with thermofractals, and address some of the conceptual aspects of the fractal approach, which are expressed in terms of the renormalization group equation and the self-energy corrections to the parton mass. We associate these well-known concepts with the origins of the fractal structure in the quantum field theory., Comment: 16 pages, 8 figures. Talk given by E.Megias at the 10th International Conference on New Frontiers in Physics (ICNFP 2021), 23 Aug - 7 Oct 2021, Kolymbari, Crete, Greece

Using multiple ion beam analysis measurements, or techniques, combined with self-consistent data processing, generally allows extracting more (or more accurate) information from the measurements than processing separately data from single measurements. Solving ambiguities, improving the final depth resolution, defining constraints and extending applicability are the main strengths of the data-fusion approach. It basically consists in formulating a multi-objective minimization problem that can be tackled by the adoption of the weighted-sum method. A simulation study is reported in order to evaluate the systematic error inserted in the analysis by the choice of a specific objective function, or even by the weights or normalization adopted in the weighted-sum method. We demonstrate that the bias of the analyzed objective functions asymptotically converges to the true value for better statistics. We also demonstrate that the joint analysis inherits the accuracy of the most accurate measurement, establishing a rank of information content, where some combinations of measurements are more valuable than others, i.e. when processed together they provide more information by means of a better constraint for the multi-objective optimization., Comment: 9 pages and 8 figures

Ion Beam Analysis (IBA) comprises a set of analytical techniques suited for material analysis, many of which are rather closely related. Self-consistent analysis of several IBA techniques takes advantage of this close relationship to combine different Ion Beam measurements in a unique model to obtain an improved characterization of the sample. This approach provides a powerful tool to obtain an unequivocal and reliable model of the sample, increasing confidence and reducing ambiguities. Taking advantage of the recognized reliability and quality of the simulations provided by SIMNRA, we developed a multi-process program for a self-consistent analysis based on SIMNRA calculations. MultiSIMNRA uses computational algorithms to minimize an objective function running multiple instances of SIMNRA. With four different optimization algorithms, the code can handle sample and setup parameters (including correlations and constraints), to find the set of parameters that best fits simultaneously all experimental data., Comment: 27 pages, 5 figures, research paper

In 2020, Brazil was the leading country in COVID-19 cases in Latin America, and capital cities were the most severely affected by the outbreak. Climates vary in Brazil due to the territorial extension of the country, its relief, geography, and other factors. Since the most common COVID-19 symptoms are related to the respiratory system, many researchers have studied the correlation between the number of COVID-19 cases with meteorological variables like temperature, humidity, rainfall, etc. Also, due to its high transmission rate, some researchers have analyzed the impact of human mobility on the dynamics of COVID-19 transmission. There is a dearth of literature that considers these two variables when predicting the spread of COVID-19 cases. In this paper, we analyzed the correlation between the number of COVID-19 cases and human mobility, and meteorological data in Brazilian capitals. We found that the correlation between such variables depends on the regions where the cities are located. We employed the variables with a significant correlation with COVID-19 cases to predict the number of COVID-19 infections in all Brazilian capitals and proposed a prediction method combining the Ensemble Empirical Mode Decomposition (EEMD) method with the Autoregressive Integrated Moving Average Exogenous inputs (ARIMAX) method, which we called EEMD-ARIMAX. After analyzing the results poor predictions were further investigated using a signal processing-based anomaly detection method. Computational tests showed that EEMD-ARIMAX achieved a forecast 26.73% better than ARIMAX. Moreover, an improvement of 30.69% in the average root mean squared error (RMSE) was noticed when applying the EEMD-ARIMAX method to the data normalized after the anomaly detection.

The connection between initial-state geometry and anisotropic flow can be quantified through a well-established mapping between $p_T$-integrated flow harmonics and cumulants of the initial transverse energy distribution. In this paper we successfully extend this mapping to also include $p_T$-differential flow. In doing so, we find that subleading principal components of anisotropic flow can reveal previously unobserved details of the hydrodynamic response, in both the linear and the nonlinear regimes. Most importantly, we show that they provide novel information on the small-scale structures present in the initial stage of relativistic heavy-ion collisions., Comment: 18 pages, 12 figures. Published version

We investigate the effects of pre-hydrodynamic evolution on final-state observables in heavy-ion collisions using state-of-the art event simulations coupled to different pre-hydrodynamic scenarios, which include the recently-developed effective kinetic transport theory evolution model KoMPoST. Flow observables are found to be insensitive to the details of pre-hydrodynamic evolution. The main effect we observe is in the $p_T$ spectra, particularly the mean transverse momentum. However, at least part of this effect is a consequence of the underlying conformal invariance assumption currently present in such approaches, which is known to be violated in the temperature regime probed in heavy-ion collisions. This assumption of early time conformal invariance leads to an artificially large out-of-equilibrium bulk pressure when switching from (conformal) pre-hydrodynamic evolution to hydrodynamics (using the non-conformal QCD equation of state), which in turn increases the transverse momentum. Our study indicates that a consistent treatment of pre-hydrodynamic evolution in heavy-ion collisions requires the use of non-conformal models of early time dynamics., Comment: 17 pages, 15 figures, 1 appendix

We propose a redefinition of the principal component analysis (PCA) of anisotropic flow that makes it more directly connected to fluctuations of the initial geometry of the system. Then, using state-of-the-art hydrodynamic simulations, we make an explicit connection between flow fluctuations and a cumulant expansion of the initial transverse geometry. In particular, we show that the second principal component of elliptic flow is generated by higher-order cumulants, and therefore probes smaller length scales of the initial state. With this information, it will be possible to put new constraints on properties of the early-time dynamics of a heavy-ion collision, including small-scale structure, as well as properties of the quark-gluon plasma., Comment: 4 pages, 2 figures, contribution to the proceedings of XXVIIIth International Conference on Ultrarelativistic Nucleus-Nucleus Collisions (Quark Matter 2019)

In this work, we have investigated anisotropic neutron stars in the framework of Rastall-Rainbow gravity. All our calculations were computed using the IU-FSU realistic equation of state (EoS), in which was considered two cases: standard nucleonic composition and the one with the eight lightest baryons. From the neutron star masses and radii obtained we conclude that anisotropic pressure has significant consequences on the structure of stellar objects. In particular, when anisotropy is considered within the general relativity framework, it significantly modifies the maximum stellar mass. On the other hand, when Rastall-Rainbow gravity and anisotropy are simultaneously considered, they provide the best results for mass and radius values, including important astrophysical objects such as the LMXB NGC 6397 and the extremely massive pulsar millisecond MSP J0740 + 6620. Although the expected inclusion of hyperons in the nuclear model reproduces stellar masses smaller than those produced by standard nucleonic matter, we shown that the hyperon puzzle problem can be solved by including anisotropic effects on compact stars in the context of the Rastall-Rainbow gravity.