In this paper we show that electron-positron pairs can be pumped inexhaustibly with a constant production rate from the one dimensional potential well with oscillating depth or width. Bound states embedded in the the Dirac sea can be pulled out and p
ushed to the positive continuum, and become scattering states. Pauli block, which dominant the saturation of pair creation in the static super-critical potential well, can be broken by the ejection of electrons. We find that the width oscillating mode is more efficient that the depth oscillating mode. In the adiabatic limit, pair number as a function of upper boundary of the oscillating, will reveal the diving of the bound states.
We probe the local detection efficiency in a nanowire superconducting single-photon detector along the cross-section of the wire with a spatial resolution of 10 nm. We experimentally find a strong variation in the local detection efficiency of the de
vice. We demonstrate that this effect explains previously observed variations in NbN detector efficiency as function of device geometry.
New imaging techniques are in great demand for investigating underground plant roots systems which play an important role in crop production. Compared with other non-destructive imaging modalities, PET can image plant roots in natural soil and produc
e dynamic 3D functional images which reveal the temporal dynamics of plant-environment interactions. In this study, we combined PET with optical projection tomography (OPT) to evaluate its potential for plant root phenotyping. We used a dedicated high resolution plant PET imager that has a 14 cm transaxial and 10 cm axial field of views, and multi-bed imaging capability. The image resolution is around 1.25 mm using ML-EM reconstruction algorithm. B73 inbred maize seeds were germinated and then grown in a sealed jar with transparent gel-based media. PET scanning started on the day when the first green leaf appeared, and was carried out once a day for 5 days. Each morning, around 10 mCi of 11CO2 was administrated into a custom built plant labeling chamber. After 10 minutes, residual activity was flushed out with fresh air before a 2-h PET scan started. For the OPT imaging, the jar was placed inside an acrylic cubic container filled with water, illuminated with a uniform surface light source, and imaged by a DSLR camera from 72 angles to acquire optical images for OPT reconstruction. The same plant was imaged 3 times a day by the OPT system. Plant roots growth is measured from the optical images. Co-registered PET and optical images indicate that most of the hot spots appeared in later time points of the PET images correspond to the most actively growing root tips. The strong linear correlation between 11C allocation at root tips measured by PET and eventual root growth measured by OPT suggests that we can use PET as a phenotyping tool to measure how a plant makes subterranean carbon allocation decisions in different environmental scenarios.
We construct a Josephson junction in non-relativistic case with a Lifshitz geometry as the dual gravity. We investigate the effect of the Lifshitz scaling in comparison with its relativistic counterpart. The standard sinusoidal relation between the c
urrent and the phase difference is found for various Lifshitz scalings characterised by the dynamical critical exponent. We also find the exponential decreasing relation between the condensate of the scalar operator within the barrier at zero current and the width of the weak link, as well as the relation between the critical current and the width. Nevertheless, the coherence lengths obtained from two exponential decreasing relations generically have discrepancies for non-relativistic dual.
For the study of information propagation, one fundamental problem is uncovering universal laws governing the dynamics of information propagation. This problem, from the microscopic perspective, is formulated as estimating the propagation probability
that a piece of information propagates from one individual to another. Such a propagation probability generally depends on two major classes of factors: the intrinsic attractiveness of information and the interactions between individuals. Despite the fact that the temporal effect of attractiveness is widely studied, temporal laws underlying individual interactions remain unclear, causing inaccurate prediction of information propagation on evolving social networks. In this report, we empirically study the dynamics of information propagation, using the dataset from a population-scale social media website. We discover a temporal scaling in information propagation: the probability a message propagates between two individuals decays with the length of time latency since their latest interaction, obeying a power-law rule. Leveraging the scaling law, we further propose a temporal model to estimate future propagation probabilities between individuals, reducing the error rate of information propagation prediction from 6.7% to 2.6% and improving viral marketing with 9.7% incremental customers.
We investigate theoretically the effects of intrinsic spin-relaxation on the spin-dependent transport through a single-molecule magnet (SMM), which is weakly coupled to ferromagnetic leads. The tunnel magnetoresistance (TMR) is obtained by means of t
he rate-equation approach including not only the sequential but also the cotunneling processes. It is shown that the TMR is strongly suppressed by the fast spin-relaxation in the sequential region and can vary from a large positive to slight negative value in the cotunneling region. Moreover, with an external magnetic field along the easy-axis of SMM, a large negative TMR is found when the relaxation strength increases. Finally, in the high bias voltage limit the TMR for the negative bias is slightly larger than its characteristic value of the sequential region, however it can become negative for the positive bias caused by the fast spin-relaxation.
We theoretically investigate quantum transport through single-molecule magnet (SMM) junctions with ferromagnetic and normal-metal leads in the sequential regime. The current obtained by means of the rate-equation gives rise to the tunneling anisotrop
ic magnetoresistance (TAMR), which varies with the angle between the magnetization direction of ferromagnetic lead and the easy axis of SMM. The angular dependence of TAMR can serve as a probe to determine experimentally the easy axis of SMM. Moreover, it is demonstrated that both the magnitude and sign of TAMR are tunable by the bias voltage, suggesting a promising TAMR based spintronic molecule-device.
We study thermoelectric transport through double quantum dots system with spin-dependent interdot coupling and ferromagnetic electrodes by means of the non-equilibrium Green function in the linear response regime. It is found that the thermoelectric
coefficients are strongly dependent on the splitting of interdot coupling, the relative magnetic configurations and the spin polarization of leads. In particular, the thermoelectric efficiency can achieve considerable value in parallel configuration when the effective interdot coupling and tunnel coupling between QDs and the leads for spin-down electrons are small. Moreover, the thermoelectric efficiency increases with the intradot Coulomb interactions increasing and can reach very high value at an appropriate temperature. In the presence of the magnetic field, the spin accumulation in leads strongly suppresses the thermoelectric efficiency and a pure spin thermopower can be obtained.
We theoretically study the spin-polarized transport through a single-molecule magnet, which is weakly coupled to ferromagnetic leads, by means of the rate-equation approach. We consider both the ferromagnetic and antiferromagnetic exchange-couplings
between the molecular magnet and transported electron-spin in the nonlinear tunneling regime. For the ferromagnetic exchangecoupling, spin current exhibits step- and basin-like behaviors in the parallel and antiparallel configurations respectively. An interesting observation is that the polarization reversal of spin-current can be realized and manipulated by the variation of bias voltage in the case of antiferromagnetic exchange-coupling with antiparallel lead-configuration, which may be useful in the development of spintronic devices, while the bias voltage can only affect the magnitude of spin-polarization in the ferromagnetic coupling.
Uncovering factors underlying the network formation is a long-standing challenge for data mining and network analysis. In particular, the microscopic organizing principles of directed networks are less understood than those of undirected networks. Th
is article proposes a hypothesis named potential theory, which assumes that every directed link corresponds to a decrease of a unit potential and subgraphs with definable potential values for all nodes are preferred. Combining the potential theory with the clustering and homophily mechanisms, it is deduced that the Bi-fan structure consisting of 4 nodes and 4 directed links is the most favored local structure in directed networks. Our hypothesis receives strongly positive supports from extensive experiments on 15 directed networks drawn from disparate fields, as indicated by the most accurate and robust performance of Bi-fan predictor within the link prediction framework. In summary, our main contribution is twofold: (i) We propose a new mechanism for the local organization of directed networks; (ii) We design the corresponding link prediction algorithm, which can not only testify our hypothesis, but also find out direct applications in missing link prediction and friendship recommendation.
