Suchergebnisse

Fermi Research Alliance, LLC ; U.S. Department of Energy, Office of Science, Office of High Energy Physics ; U.S. Department of Energy ; Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) ; Fermilab theory group ; Hong Kong Ph.D. Fellowship Scheme (HKPFS) ; Hong Kong University of Science and Technology ; European Union's Horizon Research and Innovation Programme under Marie Sklodowska-Curie Grant ; National Science Foundation ; Fermi Research Alliance, LLC: DE-AC02-07CH11359 ; U.S. Department of Energy: DE-FG02-13ER41958 ; U.S. Department of Energy: DE-AC02-06CH11357 ; Processo FAPESP: 2012/21627-9 ; European Union's Horizon Research and Innovation Programme under Marie Sklodowska-Curie Grant: 674896 ; European Union's Horizon Research and Innovation Programme under Marie Sklodowska-Curie Grant: 690575 ; National Science Foundation: PHY-1607611 ; We show that, in the presence of bulk masses, sterile neutrinos propagating in large extra dimensions (LED) can induce electron-neutrino appearance effects. This is in contrast to what happens in the standard LED scenario, and hence LED models with explicit bulk masses have the potential to address the MiniBooNE and LSND appearance results as well as the reactor and Gallium anomalies. A special feature in our scenario is that the mixing of the first Kaluza-Klein modes to active neutrinos can be suppressed, making the contribution of heavier sterile neutrinos to oscillations relatively more important. We study the implications of this neutrino mass generation mechanism for current and future neutrino oscillation experiments and show that the Short Baseline Neutrino Program at Fermilab will be able to efficiently probe such a scenario. In addition, this framework leads to massive Dirac neutrinos and thus precludes any signal in neutrinoless double beta decay experiments.

Financial markets are complex systems where information processing occurs at multiple levels. One signature of this information processing is the existence of recurrent sequences. In this paper, we developed a procedure for finding these sequences and a process of statistical significance testing to identify the most meaningful ones. To do so, we downloaded daily closing prices of the Dow Jones Industrial Average component stocks, as well as various assets like stock market indices, United States government bonds, precious metals, commodities, oil and gas, and foreign exchange. We mapped each financial instrument to a letter and their upward movements to words, before testing the frequencies of these words against a null model obtained by reshuffling the empirical time series. We then identify market leaders and followers from the statistically significant words in different cross sections of financial instruments, and interpret actionable trends that can be traded upon. ; Ministry of Education (MOE) ; Published version ; YWL, YYL, JL, JT, and XT thank the Singapore Ministry of Education Science Mentorship Program for the opportunity to participate in this study.