85,430 research outputs found

    Portfolio selection using neural networks

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    In this paper we apply a heuristic method based on artificial neural networks in order to trace out the efficient frontier associated to the portfolio selection problem. We consider a generalization of the standard Markowitz mean-variance model which includes cardinality and bounding constraints. These constraints ensure the investment in a given number of different assets and limit the amount of capital to be invested in each asset. We present some experimental results obtained with the neural network heuristic and we compare them to those obtained with three previous heuristic methods.Comment: 12 pages; submitted to "Computers & Operations Research

    Simulations on High-z Long Gamma-Ray Burst Rate

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    Since the launch of Swift satellite, the detections of high-z (z>4) long gamma-ray bursts (LGRBs) have been rapidly growing, even approaching the very early Universe (the record holder currently is z=8.3). The observed high-z LGRB rate shows significant excess over that estimated from the star formation history. We investigate what may be responsible for this high productivity of GRBs at high-z through Monte Carlo simulations, with effective Swif/BAT trigger and redshift detection probabilities based on current Swift/BAT sample and CGRO/BATSE LGRB sample. We compare our simulations to the Swift observations via log N-log P, peak luminosity (L) and redshift distributions. In the case that LGRB rate is purely proportional to the star formation rate (SFR), our simulations poorly reproduce the LGRB rate at z>4, although the simulated log N-log P distribution is in good agreement with the observed one. Assuming that the excess of high-z GRB rate is due to the cosmic metallicity evolution or unknown LGRB rate increase parameterized as (1+z)^delta, we find that although the two scenarios alone can improve the consistency between our simulations and observations, incorporation of them gives much better consistency. We get 0.2<epsilon<0.6 and delta<0.6, where epsilon is the metallicity threshold for the production of LGRBs. The best consistency is obtained with a parameter set (epsilon, delta)=(~0.4, ~0.4), and BAT might trigger a few LGRBs at z~14. With increasing detections of GRBs at z>4 (~15% of GRBs in current Swift LGRB sample based on our simulations), a window for very early Universe is opening by Swift and up-coming SVOM missions.Comment: 9 pages, including 8 figures and 1 table, one more figure added. Accepted for publication in MNRA

    Recent progress on intrinsic charm

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    Over the past  ⁣ ⁣10\sim\!\! 10 years, the topic of the nucleon's nonperturbative or intrinsic\textit{intrinsic} charm (IC) content has enjoyed something of a renaissance, largely motivated by theoretical developments involving quark modelers and PDF fitters. In this talk I will briefly describe the importance of intrinsic charm to various issues in high-energy phenomenology, and survey recent progress in constraining its overall normalization and contribution to the momentum sum rule of the nucleon. I end with the conclusion that progress on the side of calculation has now placed the onus on experiment to unambiguously resolve the proton's intrinsic charm component.Comment: Invited talk at the Conference "XIIth Quark Confinement and the Hadron Spectrum" (Thessaloniki, Greece; 29th August - 3rd September 2016). 9 pages, 4 figures; reference added in version
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