Generation and annihilation time of magnetic droplet solitons

Magnetic droplet solitons were first predicted to occur in materials with uniaxial magnetic anisotropy due to a long-range attractive interaction between elementary magnetic excitations, magnons. A non-equilibrium magnon population provided by a spin-polarized current in nanocontacts enables their creation and there is now clear experimental evidence for their formation, including direct images obtained with scanning x-ray transmission microscopy. Interest in magnetic droplets is associated with their unique magnetic dynamics that can lead to new types of high frequency nanometer scale oscillators of interest for information processing, including in neuromorphic computing. However, there are no direct measurements of the time required to nucleate droplet solitons or their lifetime-experiments to date only probe their steady-state characteristics, their response to dc spin-currents. Here we determine the timescales for droplet annihilation and generation using current pulses. Annihilation occurs in a few nanoseconds while generation can take several nanoseconds to a microsecond depending on the pulse amplitude. Micromagnetic simulations show that there is an incubation time for droplet generation that depends sensitively on the initial magnetic state of the nanocontact. An understanding of these processes is essential to utilizing the unique characteristics of magnetic droplet solitons oscillators, including their high frequency, tunable and hysteretic response

Effect of temperature on magnetic solitons induced by spin-transfer torque

Spin-transfer torques in a nanocontact to an extended magnetic film can create spin waves that condense to form dissipative droplet solitons. Here we report an experimental study of the temperature dependence of the current and applied field thresholds for droplet soliton formation, as well as the nanocontact's electrical characteristics associated with droplet dynamics. Nucleation requires lower current densities at lower temperatures, in contrast to typical spin-transfer-torque-induced switching between static magnetic states. Magnetoresistance and electrical noise measurements (10 MHz-1 GHz) show that droplet solitons become more stable at lower temperature. These results are of fundamental interest in understanding the influence of thermal noise on droplet solitons and have implications for the design of devices using the spin-transfer-torque effects to create and control collective spin excitations

Effect of Temperature on Magnetic Solitons Induced by Spin-Transfer Torque

This paper was accepted for publication in the journal Physical Review Applied and is available at http://dx.doi.org/10.1103/PhysRevApplied.7.054027.Spin-transfer torques in a nanocontact to an extended magnetic film can create spin waves that condense to form dissipative droplet solitons. Here we report an experimental study of the temperature dependence of the current and applied field thresholds for droplet soliton formation, as well as the nanocontact's electrical characteristics associated with droplet dynamics. Nucleation requires lower current densities at lower temperatures, in contrast to typical spin-transfer-torque-induced switching between static magnetic states. Magnetoresistance and electrical noise measurements (10 MHz-1 GHz) show that droplet solitons become more stable at lower temperature. These results are of fundamental interest in understanding the influence of thermal noise on droplet solitons and have implications for the design of devices using the spin-transfer-torque effects to create and control collective spin excitations

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Co‐occurrence matching of local binary patterns for improving visual adaption and its application to smoke recognition

It is challenging to recognize smoke from visual scenes due to large variations of smoke colors, textures and shapes. To improve robustness, we propose a novel feature extraction method based on similarity and dissimilarity matching measures of Local Binary Patterns (LBP). Given two bit-sequences of an LBP code pair, the similarity and dissimilarity matching measures are defined as the ratios of the 1-1 bitwise matching number to the 0-0 bitwise matching number and the 1-0 number to the 0-1 number, respectively. To capture local code variations, we calculate the measures between LBP codes of a center pixel and its neighbors. Then we compare each measure with its global mean to propose Similarity Matching based Local Binary Patterns (SMLBP) and Dissimilarity Matching based Local Binary Patterns (DMLBP). Since SMLBP and DMLBP extract spatial variations of the 1st order LBP codes, they actually represent the 2nd order variations of pixel values. Furthermore, we adopt different mapping modes and multi-scale neighborhoods to obtain rotation and scale invariances. Finally, we concatenate the histograms of LBP, SMLBP and DMLBP to generate a feature vector containing 1st and 2nd order information. Experiments show that our method obviously outperforms existing methods.</p