Tuning the Dzyaloshinskii-Moriya Interaction in Pt/Co/MgO heterostructures through MgO thickness

The interfacial Dzyaloshinskii-Moriya interaction (DMI) in the ferromagnetic/heavy metal ultra-thin film structures , has attracted a lot of attention thanks to its capability to stabilize Neel-type domain walls (DWs) and magnetic skyrmions for the realization of non-volatile memory and logic devices. In this study, we demonstrate that magnetic properties in perpendicularly magnetized Ta/Pt/Co/MgO/Pt heterostructures, such as magnetization and DMI, can be significantly influenced through both the MgO and the Co ultrathin film thickness. By using a field-driven creep regime domain expansion technique, we find that non-monotonic tendencies of DMI field appear when changing the thickness of MgO and the MgO thickness corresponding to the largest DMI field varies as a function of the Co thicknesses. We interpret this efficient control of DMI as subtle changes of both Pt/Co and Co/MgO interfaces, which provide a method to investigate ultra-thin structures design to achieve skyrmion electronics.Comment: 18 pages, 11 figure

Role of sea quarks in the nucleon transverse spin

We present a phenomenological extraction of transversity distribution functions and Collins fragmentation functions by simultaneously fitting to semi-inclusive deep inelastic scattering and electron-positron annihilation data. The analysis is performed within the transverse momentum dependent factorization formalism, and sea quark transversity distributions are taken into account for the first time. We find the $\bar u$ quark favors a negative transversity distribution while that of the $\bar d$ quark is consistent with zero according to the current accuracy. In addition, based on a combined analysis of world data and simulated data, we quantitatively demonstrate the impact of the proposed Electron-ion Collider in China on precise determinations of the transversity distributions, especially for sea quarks, and the Collins fragmentation functions

Bio-inspired small target motion detector with a new lateral inhibition mechanism

In nature, it is an important task for animals to detect small targets which move within cluttered background. In recent years, biologists have found that a class of neurons in the lobula complex, called STMDs (small target motion detectors) which have extreme selectivity for small targets moving within visual clutter. At the same time, some researchers assert that lateral inhibition plays an important role in discriminating the motion of the target from the motion of the background , even account for many features of the tuning of higher order visual neurons. Inspired by the finding that complete lateral inhibition can only be seen when the motion of the central region is identical to the motion of the peripheral region, we propose a new lateral inhibition mechanism combined with motion velocity and direction to improve the performance of ESTMD model (elementary small target motion detector). In this paper, we will elaborate on the biological plausibility and functionality of this new lateral inhibition mechanism in small target motion detection

An Improved LPTC Neural Model for Background Motion Direction Estimation

A class of specialized neurons, called lobula plate tangential cells (LPTCs) has been shown to respond strongly to wide-field motion. The classic model, elementary motion detector (EMD) and its improved model, two-quadrant detector (TQD) have been proposed to simulate LPTCs. Although EMD and TQD can percept background motion, their outputs are so cluttered that it is difficult to discriminate actual motion direction of the background. In this paper, we propose a max operation mechanism to model a newly-found transmedullary neuron Tm9 whose physiological properties do not map onto EMD and TQD. This proposed max operation mechanism is able to improve the detection performance of TQD in cluttered background by filtering out irrelevant motion signals. We will demonstrate the functionality of this proposed mechanism in wide-field motion perception

A Directionally Selective Small Target Motion Detecting Visual Neural Network in Cluttered Backgrounds

Discriminating targets moving against a cluttered background is a huge challenge, let alone detecting a target as small as one or a few pixels and tracking it in flight. In the insect's visual system, a class of specific neurons, called small target motion detectors (STMDs), have been identified as showing exquisite selectivity for small target motion. Some of the STMDs have also demonstrated direction selectivity which means these STMDs respond strongly only to their preferred motion direction. Direction selectivity is an important property of these STMD neurons which could contribute to tracking small targets such as mates in flight. However, little has been done on systematically modeling these directionally selective STMD neurons. In this paper, we propose a directionally selective STMD-based neural network for small target detection in a cluttered background. In the proposed neural network, a new correlation mechanism is introduced for direction selectivity via correlating signals relayed from two pixels. Then, a lateral inhibition mechanism is implemented on the spatial field for size selectivity of the STMD neurons. Finally, a population vector algorithm is used to encode motion direction of small targets. Extensive experiments showed that the proposed neural network not only is in accord with current biological findings, i.e., showing directional preferences, but also worked reliably in detecting small targets against cluttered backgrounds