Nuclear chronometer, which predicts the ages of the oldest stars by comparing the present and initial abundances of long-lived radioactive nuclides, provides an independent dating technique for the cosmos. A new nuclear chronometer called Th-U-X chro
nometer is proposed, which imposes stringent constraints on the astrophysical conditions in the $r$-process simulation by synchronizing the previous Th/X, U/X and Th/U chronometers. The astrophysical uncertainties of nuclear chronometer are significantly reduced from more than $pm2$ billion years to within 0:3 billion years by the Th-U-X chronometer. The proposed chronometer is then applied to estimate the ages of the six metal-poor stars with observed uranium abundances, and the predicted ages are compatible with the cosmic age 13.8 billion years predicted from the cosmic microwave background radiation, but in contradictory with the new cosmic age 11.4 billion years from the gravitational lenses measurement.
The murder of George Floyd by police in May 2020 sparked international protests and renewed attention in the Black Lives Matter movement. Here, we characterize ways in which the online activity following George Floyds death was unparalleled in its vo
lume and intensity, including setting records for activity on Twitter, prompting the saddest day in the platforms history, and causing George Floyds name to appear among the ten most frequently used phrases in a day, where he is the only individual to have ever received that level of attention who was not known to the public earlier that same week. Further, we find this attention extended beyond George Floyd and that more Black victims of fatal police violence received attention following his death than during other past moments in Black Lives Matters history. We place that attention within the context of prior online racial justice activism by showing how the names of Black victims of police violence have been lifted and memorialized over the last 12 years on Twitter. Our results suggest that the 2020 wave of attention to the Black Lives Matter movement centered past instances of police violence in an unprecedented way, demonstrating the impact of the movements rhetorical strategy to say their names.
The kernel ridge regression (KRR) approach is extended to include the odd-even effects in nuclear mass predictions by remodulating the kernel function without introducing new weight parameters and inputs in the training network. By taking the WS4 mas
s model as an example, the mass for each nucleus in the nuclear chart is predicted with the extended KRR network, which is trained with the mass model residuals, i.e., deviations between experimental and calculated masses, of other nuclei with known masses. The resultant root-mean-square mass deviation from the available experimental data for the 2353 nuclei with $Zge8$ and $Nge8$ can be reduced to 128 keV, which provides the most precise mass model from machine learning approaches so far. Moreover, the extended KRR approach can avoid the risk of worsening the mass predictions for nuclei at large extrapolation distances, and meanwhile, it provides a smooth extrapolation behavior with respect to the odd and even extrapolation distances.
Machine learning is employed to build an energy density functional for self-bound nuclear systems for the first time. By learning the kinetic energy as a functional of the nucleon density alone, a robust and accurate orbital-free density functional f
or nuclei is established. Self-consistent calculations that bypass the Kohn-Sham equations provide the ground-state densities, total energies, and root-mean-square radii with a high accuracy in comparison with the Kohn-Sham solutions. No existing orbital-free density functional theory comes close to this performance for nuclei. Therefore, it provides a new promising way for future developments of nuclear energy density functionals for the whole nuclear chart.
We constructed a sample of 13,798 stars with $Trm_{eff}$, log $g$, [Fe/H], radial velocity, proper motions and parallaxes from LAMOST DR5 and Gaia DR2 in the LAMOST Complete Spectroscopic Survey of Pointing Area (LaCoSSPAr) at the Southern Galactic C
ap consisting of areas A and B. Using the distributions in both proper motions and radial velocity, we detected very significant overdensities in these two areas. These substructures most likely are portions of Sagittarius (Sgr) stream. With the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm, 220 candidates stream members were identified. Based upon distance to the Sun and published models, 106 of these stars are likely to be the members of the Sgr stream. The abundance pattern of these members using [$alpha$/Fe] from Xiang et al. were found to be similar to Galactic field stars with [Fe/H] $<$ -1.5 and deficient to Milky Way populations at similar metallicities with [Fe/H] $>$ -1.0. No vertical and only small radial gradients in metallicity along the orbit of Sgr stream were found in our Sgr stream candidates.
The nuclear Chirality-Parity (ChP) violation, a simultaneous breaking of chiral and reflection symmetries in the intrinsic frame, is investigated with a reflection-asymmetric triaxial particle rotor model. A new symmetry for an ideal ChP violation sy
stem is found and the corresponding selection rules of the electromagnetic transitions are derived. The fingerprints for the ChP violation including the nearly degenerate quartet bands and the selection rules of the electromagnetic transitions are provided. These fingerprints are examined for ChP quartet bands by taking a two-$j$ shell $h_{11/2}$ and $d_{5/2}$ with typical energy spacing for $A=$ 130 nuclei.
A promising short term precursor of major earthquakes (EQ) is very crucial in saving people and preventing huge losses. Ez, atmospheric electrostatic field vertical component, under fair air conditions, is generally oriented downwards (positive). Ano
malous negative Ez signals could be used as an indicator of a great number of radioactive gases which are released from great number of rock clefts just before major earthquakes. Enhanced emission of radon radioactive decay will produce an anomalously large number of ion pairs. The positive particles will be transported downward by the fair weather electrostatic field and pile up near the surface. Finally, obviously and abnormally, an oriented upward atmospheric electric field Ez near the ground could be formed. Therefore, monitoring this Ez may be applied effectively in earthquake warning.
We study bottom-up grown semiconductor indium antimonide nanowires that are coated with shells of tin. The shells are uniform in thickness. The interface between Sn and InSb is abrupt and without interdiffusion. Devices for transport are prepared by
in-situ shadowing of nanowires using nearby nanowires as well as flakes, resulting in etch-free junctions. Tin is found to induce a hard superconducting gap in the range 600-700 micro-eV. Superconductivity persists up to 4 T in magnetic field. A tin island exhibits the coveted two-electron charging effect, a hallmark of charge parity stability. The findings open avenues for superconducting and topological quantum circuits based on new superconductor-semiconductor combinations.
To study the disc central surface brightness ($mu_0$) distribution in optical and near-infrared bands, we select 708 disc-dominated galaxies within a fixed distance of 57 Mpc from SDSS DR7 and UKIDSS DR10. Then we fit $mu_0$ distribution by using sin
gle and double Gaussian profiles with an optimal bin size for the final sample of 538 galaxies in optical $griz$ bands and near-infrared $YJHK$ bands. Among the 8 bands, we find that $mu_{0}$ distribution in optical bands can not be much better fitted with double Gaussian profiles. However, for all the near-infrared bands, the evidence of being better fitted by using double Gaussian profiles is positive. Especially for $K$ band, the evidence of a double Gaussian profile being better than a single Gaussian profile for $mu_{0}$ distribution is very strong, the reliability of which can be approved by 1000 times test for our sample. No dust extinction correction is applied. The difference of $mu_{0}$ distribution between optical and near-infrared bands could be caused by the effect of dust extinction in optical bands. Due to the sample selection criteria, our sample is not absolutely complete. However, the sample incompleteness does not change the double Gaussian distribution of $mu_{0}$ in $K$ band. Furthermore, we discuss some possible reasons for the fitting results of $mu_{0}$ distribution in $K$ band. Conclusively, the double Gaussian distribution of $mu_{0}$ in $K$ band for our sample may depend on bulge-to-disk ratio, color and disk scalelength, rather than the inclination of sample galaxies, bin size and statistical fluctuations.
In our previous work [Chen el al., J. Comput. Phys., 373(2018)], the quadratic Wasserstein metric is successfully applied to the earthquake location problem. The actual earthquake hypocenter can be accurately recovered starting from initial values ve
ry far from the true ones. However, the seismic wave signals need to be normalized since the quadratic Wasserstein metric requires mass conservation. This brings a critical difficulty. Since the amplitude of a seismogram at a receiver is a good representation of the distance between the source and the receiver, simply normalizing the signals will cause the objective function in optimization process to be insensitive to the distance between the source and the receiver. When the data is contaminated with strong noise, the minimum point of the objective function will deviate and lead to a low accurate location result. To overcome the difficulty mentioned above, we apply the Wasserstein-Fisher-Rao (WFR) metric [Chizat et al., Found. Comput. Math., 18(2018)] to the earthquake location problem. The WFR metric is one of the newly developed metric in the unbalanced Optimal Transport theory. It does not require the normalization of the seismic signals. Thus, the amplitude of seismograms can be considered as a new constraint, which can substantially improve the sensitivity of the objective function to the distance between the source and the receiver. As a result, we can expect more accurate location results from the WFR metric based method compare to those based on quadratic Wasserstein metric under high-intensity noise. The numerical examples also demonstrate this.
