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Register a new userWhat can be learned from a future supernova neutrino detection?
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This year marks the thirtieth anniversary of the only supernova from which we have detected neutrinos - SN 1987A. The twenty or so neutrinos that were detected were mined to great depth in order to determine the events that occurred in the explosion and to place limits upon all manner of neutrino properties. Since 1987 the scale and sensitivity of the detectors capable of identifying neutrinos from a Galactic supernova have grown considerably so that current generation detectors are capable of detecting of order ten thousand neutrinos for a supernova at the Galactic Center. Next generation detectors will increase that yield by another order of magnitude. Simultaneous with the growth of neutrino detection capability, our understanding of how massive stars explode and how the neutrino interacts with hot and dense matter has also increased by a tremendous degree. The neutrino signal will contain much information on all manner of physics of interest to a wide community. In this review we describe the expected features of the neutrino signal, the detectors which will detect it, and the signatures one might try to look for in order to get at these physics.
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We make extensive numerical studies of masses and radii of proto-neutron stars during the first second after their birth in core-collapse supernova events. We use a quasi-static approach for the computation of proto-neutron star structure, built on parameterized entropy and electron fraction profiles, that are then evolved with neutrino cooling processes. We vary the equation of state of nuclear matter, the proto-neutron star mass and the parameters of the initial profiles, to take into account our ignorance of the supernova progenitor properties. We show that if masses and radii of a proto-neutron star can be determined in the first second after the birth, e.g. from gravitational wave emission, no information could be obtained on the corresponding cold neutron star and therefore on the cold nuclear equation of state. Similarly, it seems unlikely that any property of the proto-neutron star equation of state (hot and not beta-equilibrated) could be determined either, mostly due to the lack of information on the entropy, or equivalently temperature, distribution in such objects.
We present an analysis of the recent measurement of $eta$-meson production by two virtual photons made by BaBar collaboration. It is the first measurement of a transition form factor which is entirely within the kinematic regime of the collinear factorization approach and thus provides a clean test of QCD factorization theorem for distribution amplitudes (DAs). We demonstrate that the data is in agreement with the perturbative QCD. Also, we show that it is sensitive to power corrections to the factorization theorem and to the decay constants. We discuss features of the meson production cross-section and point out the kinematic regions that are sensitive to interesting physics. We also provide an estimation of uncertainties on the extraction of DA parameters.
Fine structure of giant resonances (GR) has been established in recent years as a global phenomenon across the nuclear chart and for different types of resonances. A quantitative description of the fine structure in terms of characteristic scales derived by wavelet techniques is discussed. By comparison with microscpic calculations of GR strength distributions one can extract information on the role of different decay mechanisms contributing to the width of GRs. The observed cross-section fluctuations contain information on the level density (LD) of states with a given spin and parity defined by the multipolarity of the GR.
Measuring precise all-flavor neutrino information from a supernova is crucial for understanding the core-collapse process as well as neutrino properties. We apply a chi-squared analysis for different detector setups to explore determination of $ u_{e}$ spectral parameters. Using a long-term two-dimensional core-collapse simulation with three time varying spectral parameters, we generate mock data to examine the capabilities of the current Super-Kamiokande detector and compare the relative improvements that gadolinium, Hyper-Kamiokande, and DUNE would have. We show that in a realistic three spectral parameter framework, the addition of gadolinium to Super-Kamiokande allows for a qualitative improvement in $ u_e$ determination. Significant improvements will be made by Hyper-Kamiokande and DUNE, allowing for much more precise determination of $ u_e$ spectral parameters.
Numerous models for grounded language understanding have been recently proposed, including (i) generic models that can be easily adapted to any given task and (ii) intuitively appealing modular models that require background knowledge to be instantiated. We compare both types of models in how much they lend themselves to a particular form of systematic generalization. Using a synthetic VQA test, we evaluate which models are capable of reasoning about all possible object pairs after training on only a small subset of them. Our findings show that the generalization of modular models is much more systematic and that it is highly sensitive to the module layout, i.e. to how exactly the modules are connected. We furthermore investigate if modular models that generalize well could be made more end-to-end by learning their layout and parametrization. We find that end-to-end methods from prior work often learn inappropriate layouts or parametrizations that do not facilitate systematic generalization. Our results suggest that, in addition to modularity, systematic generalization in language understanding may require explicit regularizers or priors.
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