Astrophysical measurements regarding compact stars are just ahead of a big evolution jump, since the NICER experiment deployed on ISS on 14 th June 2017. This will provide soon data that would enable the determination of compact star radius with less than 10 % error. This can be further constrained by the new observation of gravitational waves originated from merging neutron stars, GW170817. This poses new challenges to nuclear models aiming to explain the structure of super dense nuclear matter found in neutron stars.A detailed studies of the QCD phase diagram shows the importance of bosonic quantum fluctuations in the cold dense matter equation of state. Here we used a demonstrative model with one bosonic and one fermionic degree of freedom coupled by Yukawa coupling we show the effect of bosonic quantum fluctuations on compact star observables such as mass, radius and compactness.We have also calculated the difference in the value of compressibility which is caused by quantum fluctuations. The above mentioned quantities are calculated in mean field, one-loop and in high order many loop approximation. The results show that the magnitude of these effects is in the range of 4-5 %, which place it into the region where modern measurements may detect it. This forms a base for further investigations that how these results carry over to more complicated models.
The functional equation governing the renormalization flow of fermionic field theories is investigated in d dimensions without introducing auxiliary Bose fields on the example of the Gross-Neveu and the Nambu-JonaLasinio model. The UV-safe fixed points and the eigenvectors of the renormalization group equations linearized around them are found in the local potential approximation. The results are compared carefully with those obtained with partial bosonization. The results do not receive any correction in the next-to-leading order approximation of the gradient expansion of the effective action.
This paper is about the meaning of understanding in scientific and in artificial intelligent systems. We give a mathematical definition of the understanding, where, contrary to the common wisdom, we define the probability space on the input set, and we treat the transformation made by an intelligent actor not as a loss of information, but instead a reorganization of the information in the framework of a new coordinate system. We introduce, following the ideas of physical renormalization group, the notions of relevant and irrelevant parameters, and discuss, how the different AI tasks can be interpreted along these concepts, and how the process of learning can be described. We show, how scientific understanding fits into this framework, and demonstrate, what is the difference between a scientific task and pattern recognition. We also introduce a measure of relevance, which is useful for performing lossy compression.
Recent multi-channel astrophysics observations and the soon-to-be published new measured electromagnetic and gravitation data provide information on the inner structure of the compact stars. These macroscopic observations can significantly increase our knowledge on the neutron star enteriors, providing constraints on the microscopic physical properties. On the other hand, due to the masquarade problem, there are still uncertainties on the various nuclear-matter models and their parameters as well. Calculating the properties of the dense nuclear matter, effective field theories are the most widely-used tools. However the values of the microscopical parameters need to be set consistently to the nuclear and astrophysical measurements. In this work we investigate how uncertainties are induced by the variation of the microscopical parameters. We use a symmetric nuclear matter in an extended σ-ω model. We calculate the dense matter equation of state and give the mass-radius diagram. We present that the Landau mass and compressibility modulus of the nuclear matter have definite linear relation to the maximum mass of a Schwarzschild neutron star.
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