83 resultados para TSALLIS ENTROPY


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Measurements of explosive nucleosynthesis yields in core-collapse supernovae provide tests for explosion models. We investigate constraints on explosive conditions derivable from measured amounts of nickel and iron after radioactive decays using nucleosynthesis networks with parameterized thermodynamic trajectories. The Ni/Fe ratio is for most regimes dominated by the production ratio of Ni-58/(Fe-54 + Ni-56), which tends to grow with higher neutron excess and with higher entropy. For SN 2012ec, a supernova (SN) that produced a Ni/Fe ratio of 3.4 +/- 1.2 times solar, we find that burning of a fuel with neutron excess eta approximate to 6 x 10(-3) is required. Unless the progenitor metallicity is over five times solar, the only layer in the progenitor with such a neutron excess is the silicon shell. SNe producing large amounts of stable nickel thus suggest that this deep-lying layer can be, at least partially, ejected in the explosion. We find that common spherically symmetric models of M-ZAMS less than or similar to 13 M-circle dot stars exploding with a delay time of less than one second (M-cut < 1.5 M-circle dot) are able to achieve such silicon-shell ejection. SNe that produce solar or subsolar Ni/Fe ratios, such as SN 1987A, must instead have burnt and ejected only oxygen-shell material, which allows a lower limit to the mass cut to be set. Finally, we find that the extreme Ni/Fe value of 60-75 times solar derived for the Crab cannot be reproduced by any realistic entropy burning outside the iron core, and neutrino-neutronization obtained in electron capture models remains the only viable explanation.

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Purpose Previously, it has been reported that molecular mobility determines the rate of molecular approach to crystal surfaces, while entropy relates to the probability of that approaching molecule having the desirable configuration for further growth of the existing crystal; and the free energy dictates the probability of that molecule not returning to the liquid phase1. If we plot the crystal growth rate and viscosity of a supercooled liquid in a log-log format, the relationship between the two is linear, indicating the influence viscosity has upon crystal growth rate. However, such approximation has been derived from pure drug compounds and it is apparent that further understanding of crystallization from drug-polymer solid dispersion is required in order to stabilise drugs embedded within amorphous polymeric solid dispersions. Methods Mixtures of felodipine and polymer (HPMCAS-HF, PVPK15 and Soluplus®) at specified compositions were prepared using a Restch MM200 ball mill. To examine crystal growth within amorphous solid dispersions, samples were prepared by melting 5-10 mg of ball milled mixture at 150°C for 3-5 minutes on a glass slip pre-cleaned with methanol and acetone. All prepared samples were confirmed to be crystal free by visual observation using a polarised light microscope (Olympus BX50). Prepared samples were stored at 0% RH (P2O5), inside desiccators, maintained in ovens at 80°C. For the dynamic viscosity measurement, approximately 100-200mg ball milled mixture was heated on the base plate of a rotational rheometer at 150°C for 5 minutes and the top plate was lowered to a defined gap to form a good contact with the material. The sandwiched amorphous material was heated to 80°C and the viscosity was measured. Results The equation was used to probe the correlation of viscosity to crystal growth rate. In comparison to the value of xi in log-log equation reported from pure drug compound, a value of 1.63 was obtained for FD-polymer solid dispersions irrespective of the polymer involved. &#8733 Conclusion The high xi value suggests stronger viscosity dependence may exist for amorphous FD once incorporated with amorphous polymer.

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Irreversibility is one of the most intriguing concepts in physics. While microscopic physical laws are perfectly reversible, macroscopic average behavior has a preferred direction of time. According to the second law of thermodynamics, this arrow of time is associated with a positive mean entropy production. Using a nuclear magnetic resonance setup, we measure the nonequilibrium entropy produced in an isolated spin-1/2 system following fast quenches of an external magnetic field and experimentally demonstrate that it is equal to the entropic distance, expressed by the Kullback-Leibler divergence, between a microscopic process and its time-reverse. Our result addresses the concept of irreversibility from a microscopic quantum standpoint.

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We investigate the link between information and thermodynamics embodied by Landauer’s principle in the open dynamics of a multipartite quantum system. Such irreversible dynamics is described in terms of a collisional model with a finite temperature reservoir. We demonstrate that Landauer’s principle holds, for such a configuration, in a form that involves the flow of heat dissipated into the environment and the rate of change of the entropy of the system. Quite remarkably, such a principle for heat and entropy power can be explicitly linked to the rate of creation of correlations among the elements of the multipartite system and, in turn, the non-Markovian nature of their reduced evolution. Such features are illustrated in two exemplary cases.

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A Physical Unclonable Function (PUF) can be used to provide authentication of devices by producing die-unique responses. In PUFs based on ring oscillators (ROs), the responses are derived from the oscillation frequencies of the ROs. However, RO PUFs can be vulnerable to attack due to the frequency distribution characteristics of the RO arrays. In this paper, in order to improve the design of RO PUFs for FPGA devices, the frequencies of RO arrays implemented on a large number of FPGA chips are statistically analyzed. Three RO frequency distribution (ROFD) characteristics are observed and discussed. Based on these ROFD characteristics, two RO comparison strategies are proposed that can be used to improve the design of RO PUFs. It is found that the symmetrical RO comparison strategy has the highest entropy density.

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A periodic monitoring of the pavement condition facilitates a cost-effective distribution of the resources available for maintenance of the road infrastructure network. The task can be accurately carried out using profilometers, but such an approach is generally expensive. This paper presents a method to collect information on the road profile via accelerometers mounted in a fleet of non-specialist vehicles, such as police cars, that are in use for other purposes. It proposes an optimisation algorithm, based on Cross Entropy theory, to predict road irregularities. The Cross Entropy algorithm estimates the height of the road irregularities from vehicle accelerations at each point in time. To test the algorithm, the crossing of a half-car roll model is simulated over a range of road profiles to obtain accelerations of the vehicle sprung and unsprung masses. Then, the simulated vehicle accelerations are used as input in an iterative procedure that searches for the best solution to the inverse problem of finding road irregularities. In each iteration, a sample of road profiles is generated and an objective function defined as the sum of squares of differences between the ‘measured’ and predicted accelerations is minimized until convergence is reached. The reconstructed profile is classified according to ISO and IRI recommendations and compared to its original class. Results demonstrate that the approach is feasible and that a good estimate of the short-wavelength features of the road profile can be detected, despite the variability between the vehicles used to collect the data.

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This work presents a new general purpose classifier named Averaged Extended Tree Augmented Naive Bayes (AETAN), which is based on combining the advantageous characteristics of Extended Tree Augmented Naive Bayes (ETAN) and Averaged One-Dependence Estimator (AODE) classifiers. We describe the main properties of the approach and algorithms for learning it, along with an analysis of its computational time complexity. Empirical results with numerous data sets indicate that the new approach is superior to ETAN and AODE in terms of both zero-one classification accuracy and log loss. It also compares favourably against weighted AODE and hidden Naive Bayes. The learning phase of the new approach is slower than that of its competitors, while the time complexity for the testing phase is similar. Such characteristics suggest that the new classifier is ideal in scenarios where online learning is not required.

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We present a quantum simulation method that follows the dynamics of out-of-equilibrium many-body systems of electrons and oscillators in real time. Its cost is linear in the number of oscillators and it can probe time scales from attoseconds to hundreds of picoseconds. Contrary to Ehrenfest dynamics, it can thermalize starting from a variety of initial conditions, including electronic population inversion. While an electronic temperature can be defined in terms of a nonequilibrium entropy, a Fermi-Dirac distribution in general emerges only after thermalization. These results can be used to construct a kinetic model of electron-phonon equilibration based on the explicit quantum dynamics.