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Register a new userSupernova neutrino oscillations: what do we understand?
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Amol Dighe
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We summarize our current understanding of the neutrino flavor
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This document will review the most prominent proposals using multilayer convolutional architectures. Importantly, the various components of a typical convolutional network will be discussed through a review of different approaches that base their design decisions on biological findings and/or sound theoretical bases. In addition, the different attempts at understanding ConvNets via visualizations and empirical studies will be reviewed. The ultimate goal is to shed light on the role of each layer of processing involved in a ConvNet architecture, distill what we currently understand about ConvNets and highlight critical open problems.
We investigate the precision with which the supernova neutrino spectra can be reconstructed in water Cherenkov detectors, in particular the large scale Hyper-Kamiokande and Super-Kamiokande. To this aim, we consider quasi-thermal neutrino spectra modified by the Mikheev-Smirnov-Wolfenstein effect for the case of normal ordering. We perform three 9 degrees of freedom likelihood analyses including first inverse-beta decay only, then the combination of inverse beta decay and elastic scattering on electrons and finally a third analysis that also includes neutral scattering neutrino-oxygen events. A tenth parameter is added in the analyses to account for the theoretical uncertainty on the neutral current neutrino-oxygen cross section. By assuming a 100% efficiency in Hyper-Kamiokande, we show that one can reconstruct the electron antineutrino average energy and pinching parameter with an accuracy of $sim2%$ and $sim7%$ percent respectively, while the antineutrino integrated luminosity can be pinned down at $sim3%$ percent level. As for the muon and tau neutrinos, the average energy and the integrated luminosity can be measured with $sim7%$ precision. These results represent a significant improvement with respect Super-Kamiokande, particularly for the pinching parameter defining the electron antineutrino spectra. As for electron neutrinos, the determination of the emission parameters requires the addition of supplementary detection channels.
Temperature, the central concept of thermal physics, is one of the most frequently employed physical quantities in common practice. Even though the operative methods of the temperature measurement are described in detail in various practical instructions and textbooks, the rigorous treatment of this concept is almost lacking in the current literature. As a result, the answer to a simple question of what the temperature is is by no means trivial and unambiguous. There is especially an appreciable gap between the temperature as introduced in the frame of statistical theory and the only experimentally observable quantity related to this concept, phenomenological temperature. Just the logical and epistemological analysis of the present concept of phenomenological temperature is the kernel of the contribution.
In the present paper, we investigate the cosmographic problem using the bias-variance trade-off. We find that both the z-redshift and the $y=z/(1+z)$-redshift can present a small bias estimation. It means that the cosmography can describe the supernova data more accurately. Minimizing risk, it suggests that cosmography up to the second order is the best approximation. Forecasting the constraint from future measurements, we find that future supernova and redshift drift can significantly improve the constraint, thus having the potential to solve the cosmographic problem. We also exploit the values of cosmography on the deceleration parameter and equation of state of dark energy $w(z)$. We find that supernova cosmography cannot give stable estimations on them. However, much useful information was obtained, such as that the cosmography favors a complicated dark energy with varying $w(z)$, and the derivative $dw/dz<0$ for low redshift. The cosmography is helpful to model the dark energy.
The DNA molecule, apart from carrying the genetic information, plays a crucial role in a variety of biological processes and find applications in drug design, nanotechnology and nanoelectronics. The molecule undergoes significant structural transitions under the influence of forces due to physiological and non-physiological environments. Here, we summarize the insights gained from simulations and single-molecule experiments on the structural transitions and mechanics of DNA under force, as well as its elastic properties, in various environmental conditions, and discuss appealing future directions.
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