Cryogenic thermo-optic thin-film lithium niobate modulator with an NbN superconducting heater

We propose and demonstrate a cryogenic thermo-optic(TO)modulator in x-cut thin-film lithium niobate(TFLN)with an NbN superconducting heater.Compared to a conventional metal heating electrode,a fast and energy-efficient modulation is obtained by placing an NbN superconducting heating electrode above the TFLN waveguide.The transition of the NbN superconducting electrode between superconducting and normal states turns the heating and cooling processes from continuous to discontinuous change.Thus,the energy consumption during the modulation process is reduced proportionally.The rise/fall time of the proposed device is 22μs/15μs,which has been the fastest response time reported in TFLN thermo-optic modulators so far.The presented TO modulator can easily be used at cryogenic temperatures and has great potential for applications in cryogenic optoelectronics.

PINK1-mediated Drp1^(S616) phosphorylation modulates synaptic development and plasticity via promoting mitochondrial fission

Dynamic change of mitochondrial morphology and distribution along neuronal branches are essential for neural circuitry formation and synaptic efficacy.However,the underlying mechanism remains elusive.We show here that Pink1 knockout(KO)mice display defective dendritic spine maturation,reduced axonal synaptic vesicles,abnormal synaptic connection,and attenuated long-term synaptic potentiation(LTP).Drp1 activation via ^(S616) phosphorylation rescues deficits of spine maturation in Pink1 KO neurons.

Fabrication and characterization of on-chip silicon spherical-like microcavities with high Q-factors

An effective way to fabricate high-quality(Q)silicon microcavities on-chip is proposed and studied.Our fabrication technique consists of two significant steps:(1)patterning a special silicon micro-pillar by Bosch processes and(2)subsequent reflow of the pillar into a spherical-like microcavity using a laser pulse at 532 nm.Its shape and surface roughness are characterized using a scanning electron microscope and an atomic force microscope.The root-mean-square roughness of the surface is about 0.6 nm.A representative value for the loaded Q-factors of our silicon spherical-like microcavities is on the order of 10^(5).

Analyzing OAM mode purity in optical fibers with CNN-based deep learning

Inspired by recent rapid deep learning development,we present a convolutional-neural-network(CNN)-based algorithm to predict orbital angular momentum(OAM)mode purity in optical fibers using far-field patterns.It is found that this image-processing-based technique has an excellent ability in predicting the OAM mode purity,potentially eliminating the need of using bulk optic devices to project light into different polarization states in traditional methods.The excellent performance of our algorithm can be characterized by a prediction accuracy of 99.8%and correlation coefficient of 0.99994.Furthermore,the robustness of this technique against different sizes of testing sets and different phases between different fiber modes is also verified.Hence,such a technique has a great potential in simplifying the measuring process of OAM purity.