Ferromagnetic barrier induced negative differential conductance on the surface of a topological insulator

We theoretically investigate the effect of the negative differential conductance of a ferromagnetic barrier on the surface of a topological insulator. Due to the changes of the shape and position of the Fermi surfaces in the ferromagnetic barrier, the transport processes can be divided into three kinds: the total, partial and blockade transmission mechanisms. The bias voltage can give rise to the transition of the transport processes from partial to blockade transmission mechanisms, which results in a giant effect of negative differential conductance. With appropriate structural parameters, the current-voltage characteristics show that the minimum value of the current can reach to zero in a wide range of the bias voltage, and a large peak-to-valley current ratio can be obtained.Comment: 4 figure

Searching for Low Mass Dark Portal at the LHC

Light dark matter with mass smaller than about 10 GeV is difficult to probe from direct detection experiments. In order to have the correct thermal relic abundance, the mediator of the interaction between dark matter and the Standard Model (SM) should also be relatively light, $\sim 10^2$ GeV. If such a light mediator couples to charged leptons, it would already be strongly constrained by direct searches at colliders. In this work, we consider the scenario of a leptophobic light $Z'$ vector boson as the mediator, and study the the prospect of searching for it at the 8 TeV Large Hadron Collider (LHC). To improve the reach in the low mass region, we perform a detailed study of the processes that the $Z'$ is produced in association with jet, photon, $W^\pm$ and $Z^0$. We show that in the region where the mass of $Z'$ is between 80 and 400 GeV, the constraint from associated production can be comparable or even stronger than the known monojet and dijet constraints. Searches in these channels can be complementary to the monojet search, in particular if the $Z'$ couplings to quarks ($g_{Z'}$) and dark matter ($g_D$) are different. For $g_D < g_{Z'}$, we show that there is a larger region of parameter space which has correct thermal relic abundance and a light $Z'$, $M_{Z'} \sim 100$ GeV. This region, which cannot be covered by the mono-jet search, can be covered by the resonance searches described in this paper.Comment: 16 pages, 5 figure

EVN detection of a compact radio source as a counterpart to Fermi J1418+3541

Fermi J1418+3541 is a suspected blazar recently detected as a flaring gamma-ray point source, identified with likely radio, optical and infrared counterparts within the Fermi LAT error circle. We detected the proposed radio counterpart of Fermi J1418+3541 with the European VLBI Network (EVN), in real-time e-VLBI mode at 5 GHz on 2013 Jan 16 (project code RSF07). The source is dominated by a compact radio core, practically unresolved on intercontinental baselines from Europe to South Africa

Unsupervised Spoken Term Detection with Spoken Queries by Multi-level Acoustic Patterns with Varying Model Granularity

This paper presents a new approach for unsupervised Spoken Term Detection with spoken queries using multiple sets of acoustic patterns automatically discovered from the target corpus. The different pattern HMM configurations(number of states per model, number of distinct models, number of Gaussians per state)form a three-dimensional model granularity space. Different sets of acoustic patterns automatically discovered on different points properly distributed over this three-dimensional space are complementary to one another, thus can jointly capture the characteristics of the spoken terms. By representing the spoken content and spoken query as sequences of acoustic patterns, a series of approaches for matching the pattern index sequences while considering the signal variations are developed. In this way, not only the on-line computation load can be reduced, but the signal distributions caused by different speakers and acoustic conditions can be reasonably taken care of. The results indicate that this approach significantly outperformed the unsupervised feature-based DTW baseline by 16.16\% in mean average precision on the TIMIT corpus.Comment: Accepted by ICASSP 201