We utilize a new framework, CUJET3.0, to deduce the energy and temperature dependence of the jet trans- port parameter, q （E 〉 10 GeV, T）, from a combined analysis of available data on nudear modification factor an...We utilize a new framework, CUJET3.0, to deduce the energy and temperature dependence of the jet trans- port parameter, q （E 〉 10 GeV, T）, from a combined analysis of available data on nudear modification factor and azimuthal asymmetries from high energy nuclear collisions at RHIC/BNL and LHC/CERN. Extending a previous perturbative-QCD based jet energy loss model （known as CUJET2.0） with （2＋1）D viscous hydrody- namic bulk evolution, this new framework includes three novel features of nonperturbative physics origin; （i） the Polyakov loop suppression of color-electric scattering （aka ＇semi-QGP＇ of Pisarski et al.）, （ii） the enhancement of jet scattering due to emergent magnetic monopoles near Tc （aka ＇magnetic scenario＇ of Liao and Shuryak）, and Oii） thermodynamic properties constrained by lattice QCD data. CUJET3.0 reduces to v2.0 at high tem- peratures T 〉400 MeV, while greatly enhances ~ near the QCD deconfinement transition temperature range. This enhancement accounts well for the observed elliptic harmonics of jets with pT 〉10 GeV. Extrapolating our data-constrained q down to thermal energy scales, E-2 GeV, we find for the first time a remarkable consistency between high energy jet quenching and bulk perfect fluidity with η/s^T3/q^0.1 near To.展开更多
A new search for two-neutrino double-beta(2νββ)decay of^(136)Xe to the 0+1 excited state of 136Ba is performed with the full EXO-200 dataset.A deep learning-based convolutional neural network is used to discriminat...A new search for two-neutrino double-beta(2νββ)decay of^(136)Xe to the 0+1 excited state of 136Ba is performed with the full EXO-200 dataset.A deep learning-based convolutional neural network is used to discriminate signal from background events.Signal detection efficiency is increased relative to previous searches by EXO-200 by more than a factor of two.With the addition of the Phase II dataset taken with an upgraded detector,the median 90%confidence level half-life sensitivity of 2νββdecay to the 0+1 state of 136Ba is 2.9×10^(24)yr using a total^(136)Xe exposure of 234.1 kg yr.No statistically significant evidence for 2νββdecay to the 0^(+)_(1)state is observed,leading to a lower limit of T2ν1/2(0^(+)→0^(+)_(1))>1.4×10^(24)yr at 90%confidence level,improved by 70%relative to the current world's best constraint.展开更多
基金Supported by the USA DOE Nuclear Science under Grant No DE-FG02-93ER40764the National Science Foundation under Grant No PHY-1352368the RIKEN BNL Research Center
文摘We utilize a new framework, CUJET3.0, to deduce the energy and temperature dependence of the jet trans- port parameter, q （E 〉 10 GeV, T）, from a combined analysis of available data on nudear modification factor and azimuthal asymmetries from high energy nuclear collisions at RHIC/BNL and LHC/CERN. Extending a previous perturbative-QCD based jet energy loss model （known as CUJET2.0） with （2＋1）D viscous hydrody- namic bulk evolution, this new framework includes three novel features of nonperturbative physics origin; （i） the Polyakov loop suppression of color-electric scattering （aka ＇semi-QGP＇ of Pisarski et al.）, （ii） the enhancement of jet scattering due to emergent magnetic monopoles near Tc （aka ＇magnetic scenario＇ of Liao and Shuryak）, and Oii） thermodynamic properties constrained by lattice QCD data. CUJET3.0 reduces to v2.0 at high tem- peratures T 〉400 MeV, while greatly enhances ~ near the QCD deconfinement transition temperature range. This enhancement accounts well for the observed elliptic harmonics of jets with pT 〉10 GeV. Extrapolating our data-constrained q down to thermal energy scales, E-2 GeV, we find for the first time a remarkable consistency between high energy jet quenching and bulk perfect fluidity with η/s^T3/q^0.1 near To.
文摘A new search for two-neutrino double-beta(2νββ)decay of^(136)Xe to the 0+1 excited state of 136Ba is performed with the full EXO-200 dataset.A deep learning-based convolutional neural network is used to discriminate signal from background events.Signal detection efficiency is increased relative to previous searches by EXO-200 by more than a factor of two.With the addition of the Phase II dataset taken with an upgraded detector,the median 90%confidence level half-life sensitivity of 2νββdecay to the 0+1 state of 136Ba is 2.9×10^(24)yr using a total^(136)Xe exposure of 234.1 kg yr.No statistically significant evidence for 2νββdecay to the 0^(+)_(1)state is observed,leading to a lower limit of T2ν1/2(0^(+)→0^(+)_(1))>1.4×10^(24)yr at 90%confidence level,improved by 70%relative to the current world's best constraint.
