1,259 research outputs found

### Majorana Neutrino Masses from Neutrinoless Double-Beta Decays and Lepton-Number-Violating Meson Decays

The Schechter-Valle theorem states that a positive observation of
neutrinoless double-beta ($0\nu \beta \beta$) decays implies a finite Majorana
mass term for neutrinos when any unlikely fine-tuning or cancellation is
absent. In this note, we reexamine the quantitative impact of the
Schechter-Valle theorem, and find that current experimental lower limits on the
half-lives of $0\nu \beta \beta$-decaying nuclei have placed a restrictive
upper bound on the Majorana neutrino mass $|\delta m^{ee}_\nu| < 7.43 \times
10^{-29}~{\rm eV}$ radiatively generated at the four-loop level. Furthermore,
we generalize this quantitative analysis of $0\nu \beta \beta$ decays to that
of the lepton-number-violating (LNV) meson decays $M^- \to {M^\prime}^+ +
\ell^-_\alpha + \ell^-_\beta$ (for $\alpha$, $\beta$ = $e$ or $\mu$). Given the
present upper limits on these rare LNV decays, we have derived the loop-induced
Majorana neutrino masses $|\delta m^{ee}_\nu| < 9.7 \times 10^{-18}~{\rm eV}$,
$|\delta m^{e\mu}_\nu| < 1.6 \times 10^{-15}~{\rm eV}$ and $|\delta m^{\mu
\mu}_\nu| < 1.0 \times 10^{-12}~{\rm eV}$ from $K^- \to \pi^+ + e^- + e^-$,
$K^- \to \pi^+ + e^- + \mu^-$ and $K^- \to \pi^+ + \mu^- + \mu^-$,
respectively. A partial list of radiative neutrino masses from the LNV decays
of $D$, $D_s^{}$ and $B$ mesons is also given.Comment: 10 pages, 1 figure, clarification added and references updated, Phys.
Lett. B in pres

### Combining Enterprise Knowledge Graph and News Sentiment Analysis for Stock Price Prediction

Many state of the art methods analyze sentiments in news to predict stock price. When predicting stock price movement, the correlation between stocks is a factor that can’t be ignored because correlated stocks could cause co-movement. Traditional methods of measuring the correlation between stocks are mostly based on the similarity between corresponding stock price data, while ignoring the business relationships between companies, such as shareholding, cooperation and supply-customer relationships. To solve this problem, this paper proposes a new method to calculate the correlation by using the enterprise knowledge graph embedding that systematically considers various types of relationships between listed stocks. Further, we employ Gated Recurrent Unit (GRU) model to combine the correlated stocks’ news sentiment, the focal stock’s news sentiment and the focal stock’s quantitative features to predict the focal stock’s price movement. Results show that our method has an improvement of 8.1% compared with the traditional method

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