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Multi-view multi-human association and tracking (MvMHAT), is a new but important problem for multi-person scene video surveillance, aiming to track a group of people over time in each view, as well as to identify the same person across different views at the same time, which is different from previous MOT and multi-camera MOT tasks only considering the over-time human tracking. This way, the videos for MvMHAT require more complex annotations while containing more information for self learning. In this work, we tackle this problem with a self-supervised learning aware end-to-end network. Specifically, we propose to take advantage of the spatial-temporal self-consistency rationale by considering three properties of reflexivity, symmetry and transitivity. Besides the reflexivity property that naturally holds, we design the self-supervised learning losses based on the properties of symmetry and transitivity, for both appearance feature learning and assignment matrix optimization, to associate the multiple humans over time and across views. Furthermore, to promote the research on MvMHAT, we build two new large-scale benchmarks for the network training and testing of different algorithms. Extensive experiments on the proposed benchmarks verify the effectiveness of our method. We have released the benchmark and code to the public.

Grating couplers that interconnect photonic chips to off-chip components are of essential importance for various optoelectronics applications. Despite numerous efforts in past decades, existing grating couplers still suffer from poor energy efficiency and thus hinder photonic integration toward a larger scale. Here, we theoretically propose and experimentally demonstrate a method to achieve ultra-low-loss grating coupler by employing topological unidirectional guided resonances (UGRs). Leveraging the unidirectional emitting nature of UGRs, the useless downward radiation is greatly suppressed with no mirror placed on the bottom. By engineering the dispersion and apodizing the geometry of grating, we realize a grating coupler on 340 nm silicon-on-insulator platform with a record-low-loss of 0.34 dB and bandwidth exceeding 30 nm at the telecom wavelength of 1550 nm. We further show a pair of grating couplers works as optic via that interconnects two stacked photonic chips with a loss of only 0.94 dB. Our work sheds light on the feasibility of energy-efficient optical interconnect for silicon photonics, and paving the way to large-scale photonic integration for applications from optical communication to photonic computing., Comment: 21 pages, 5 figures

Two-dimensional materials with unique physicochemical properties promote photocatalytic activities. As the 2D material composites research studies the statistical average of complex catalytic behaviors, an integrated photonic platform allows clean and single flake level photo-catalytic investigations with precisely quantified photocatalytic activities. In this paper, we track fluence-dependent photo-oxidation in two-dimensional Tellurene (2D Te) by the evanescently coupled micro-resonator. Nearly 32 perent of oxidation is achieved in 10 nm 2D Te flake, compared to only 4.5% oxidation in 30 nm sample, probed by the resonance shift in silicon microring resonators (MRRs) substrate. The wider bandgap in the few layers of 2D Te allows faster charge transfer to adsorbed oxygen for a more efficient photocatalytic redox reaction. The photo-oxidation in hybrid 2D Te results in an invariant lineshapes of optical transmission resonance for wavelength trimming (more than 3 times resonance bandwidth). The low threshold power, near-infrared, and in-waveguide resonance trimming scheme is compatible with most integrated photonic setups for easy fixing the nanofabrication-induced random resonance deviation for integrated photonic circuit applications in wavelength-division-multiplexing systems and spin qubits quantum computing.

Non-Hermitian systems with their spectral degeneracies known as exceptional points (EPs) have been explored for lasing, controlling light transport, and enhancing a sensor s response. A ring resonator can be brought to an EP by controlling the coupling between its frequency degenerate clockwise and counterclockwise traveling modes. This has been typically achieved by introducing two or more nanotips into the resonator s mode volume. While this method provides a route to study EP physics, the basic understanding of how the nanotips shape and size symmetry impact the system s non-Hermicity is missing, along with additional loss from both in-plane and out-of-plane scattering. The limited resonance stability poses a challenge for leveraging EP effects for switches or modulators, which requires stable cavity resonance and fixed laser-cavity detuning. Here we use lithographically defined asymmetric and symmetric Mie scatterers, which enable subwavelength control of wave transmission and reflections without deflecting to additional radiation channels. We show that those pre-defined Mie scatterers can bring the system to an EP without post tuning, as well as enable chiral light transport within the resonator. Counterintuitively, the Mie scatterer results in enhanced quality factor measured on the transmission port, through coherently suppressing the backscattering from the waveguide surface roughness. The proposed device platform enables pre-defined chiral light propagation and backscattering-free resonances, needed for various applications such as frequency combs, solitons, sensing, and other nonlinear optical processes such as photon blockade, and regenerative oscillators.

Periodic or gradient subwavelength structures are basic configurations of photonic crystals and metamaterials. The measured linear losses of those nanophotonic devices are well-beyond theoretical predictions. Nanofabrication related geometric inhomogeneity is considered as the primary cause of the deleterious performance. The deep-UV photolithography in CMOS foundry is a large-scale parallel processing, which can significantly suppress the random offsets and thus the optical linear loss. Here we demonstrate ultra-low loss photonic crystal waveguides with a multi-project wafer run through AIM photonics and post-processing. For sub-millimeter long photonic crystal waveguides, 2 dB total loss and 40 dB extinction ratio are observed across dies., Comment: 10 pages 4 figures. arXiv admin note: substantial text overlap with arXiv:2104.09293

Silicon modulators are key components in silicon photonics to support the dense integration of electro-optic (EO) functional elements on a compact chip for various applications including high-speed data transmission, signal processing, and photonic computing. Despite numerous advances in promoting the operation speed of silicon modulators, a bandwidth ceiling of 67 GHz emerges in practices and becomes an obstacle to paving silicon photonics toward Tbps level data throughput on a single chip. Here, we theoretically propose and experimentally demonstrate a design strategy for silicon modulators by employing the slow light effect, which shatters the present bandwidth ceiling of silicon modulators and pushes its limit beyond 110 GHz in a small footprint. The proposed silicon modulator is built on a coupled-resonator optical waveguide (CROW) architecture, in which a set of Bragg gratings are appropriately cascaded to give rise to a slow light effect. By comprehensively balancing a series of merits including the group index, photon lifetime, electrical bandwidth, and losses, we found the modulators can benefit from the slow light for better modulation efficiency and compact size while remaining their bandwidth sufficiently high to support ultra-high-speed data transmission. Consequently, we realize a modulator with an EO bandwidth of 110 GHz in a length of 124 {\mu}m, and demonstrate a data rate beyond 110 Gbps by applying simple on-off keying modulation for a DSP-free operation. Our work proves that silicon modulators beyond 110 GHz are feasible, thus shedding light on the potentials of silicon photonics in ultra-high-bandwidth applications such as data communication, optical interconnection, and photonic machine learning.

Lead halide perovskites (LHPs) have emerged as an excellent class of semiconductors for next-generation solar cells and optoelectronic devices. Tailoring physical properties by fine-tuning the lattice structures has been explored in these materials by chemical composition or morphology. Nevertheless, its dynamic counterpart, phonon-driven ultrafast material control, as contemporarily harnessed for oxide perovskites, has not been established yet. Here we employ intense THz electric fields to obtain direct lattice control via nonlinear excitation of coherent octahedral twist modes in hybrid CH3NH3PbBr3 and all-inorganic CsPbBr3 perovskites. These Raman-active phonons at 0.9 - 1.3 THz are found to govern the ultrafast THz-induced Kerr effect in the low-temperature orthorhombic phase and thus dominate the phonon-modulated polarizability with potential implications for dynamic charge carrier screening beyond the Froehlich polaron. Our work opens the door to selective control of LHP's vibrational degrees of freedom governing phase transitions and dynamic disorder., Comment: 11 pages, 5 figures

We tackle a new problem of multi-view camera and subject registration in the bird's eye view (BEV) without pre-given camera calibration. This is a very challenging problem since its only input is several RGB images from different first-person views (FPVs) for a multi-person scene, without the BEV image and the calibration of the FPVs, while the output is a unified plane with the localization and orientation of both the subjects and cameras in a BEV. We propose an end-to-end framework solving this problem, whose main idea can be divided into following parts: i) creating a view-transform subject detection module to transform the FPV to a virtual BEV including localization and orientation of each pedestrian, ii) deriving a geometric transformation based method to estimate camera localization and view direction, i.e., the camera registration in a unified BEV, iii) making use of spatial and appearance information to aggregate the subjects into the unified BEV. We collect a new large-scale synthetic dataset with rich annotations for evaluation. The experimental results show the remarkable effectiveness of our proposed method.

Many crystalline solids possess strongly anharmonic soft phonon modes characterized by diminishing frequency as temperature approaches a critical point associated with a symmetry breaking phase transition. While electron-soft phonon coupling can introduce unique scattering channels for charge carriers in ferroelectrics, recent studies on the non-ferroelectric lead halide perovskites have also suggested the central role of anharmonic phonons bearing resemblance to soft modes in charge carrier screening. Here we apply coherent phonon spectroscopy to directly study electron coupling to the soft transverse optical (TO) phonon mode in a ferroelectric semiconductor SbSI. Photo-generated charge carriers in SbSI are found to be exceptionally long lived and are associated with a transient electro-optical effect that can be explained by interactions between charge carriers and thermally stimulated soft-phonon excitations. These results provide strong evidence for the role of electron-soft phonon coupling in the efficient screening of charge carriers and in reducing charge recombination rates, both desirable properties for optoelectronics., Comment: 15 pages, 4 figures, 6 pages SI

Recent years have witnessed the advancement of deep learning vision technologies and applications in the medical industry. Intelligent devices for special medication management are in great need of, which requires more precise detection algorithms to identify the specifications and locations. In this work, YOLO (You only look once) based object detectors are tailored for toxic and narcotic medications detection tasks. Specifically, a more flexible annotation with rotated degree ranging from $0^\circ$ to $90^\circ$ and a mask-mapping-based non-maximum suppression method are proposed to achieve a feasible and efficient medication detector aiming at arbitrarily oriented bounding boxes. Extensive experiments demonstrate that the rotated YOLO detectors are more suitable for identifying densely arranged drugs. The best shot mean average precision of the proposed network reaches 0.811 while the inference time is less than 300ms.

Periodic or gradient subwavelength structures are basic configurations of photonic crystals and metamaterials. While the numerical simulations predict trivial loss, but the fabricated photonic crystal waveguides by E-beam lithography and standard dry etching shows unacceptable loss beyond 10 dB. Nanofabrication variation introduced geometric inhomogeneity is considered as the primary cause of the deleterious performance. The deep UV photolithography in CMOS foundry is a large-scale parallel processing, which can significantly suppress the fabrication-related inhomogeneous offsets and thus the optical linear loss. Here we demonstrate ultra-low loss photonic crystal waveguides with a 300 mm multi-project wafer run. For sub-millimetre long photonic crystal W1 waveguides, consistent performance of 2 dB total loss and 40 dB extinction ratio are observed across different dies.

We designed an on-chip transformative optic system of a metalens-photonic crystal resonator metasystem on a foundry compatible silicon photonic platform. By adjusting the on-chip metalens' focusing length and mode dimension, the insertion loss between the metalens and the photonic crystal resonator and waveguide structures are minimized through mode-matching. The micro-system does not involve any single mode silicon nanowire waveguide, and thus mechanically robust without any oxide claddings. The proposed microsystem is ideal for miniaturized chemical and biosensors operating in air or solution environment.

Light trapping is a constant pursuit in photonics because of its importance in science and technology. Many mechanisms have been explored, including the use of mirrors made of materials or structures that forbid outgoing waves, and bound states in the continuum that are mirror-less but based on topology. Here we report a compound method, combing mirrors and bound states in the continuum in an optimized way, to achieve a class of on-chip optical cavities that have high quality factors and small modal volumes. Specifically, light is trapped in the transverse direction by the photonic band gap of the lateral hetero-structure and confined in the vertical direction by the constellation of multiple bound states in the continuum. As a result, unlike most bound states in the continuum found in photonic crystal slabs that are de-localized Bloch modes, we achieve light-trapping in all three dimensions and experimentally demonstrate quality factors as high as $Q = 1.09 \times 10^6$ and modal volumes as low as $V = 3.56~ \mu m^3$ in the telecommunication regime. We further prove the robustness of our method through the statistical study of multiple fabricated devices. Our work provides a new method of light trapping, which can find potential applications in photonic integration, nonlinear optics and quantum computing., Comment: 16 pages, 5 figures

The ultrafast optical Kerr effect (OKE) is widely used to investigate the structural dynamics and interactions of liquids, solutions and solids by observing their intrinsic nonlinear temporal responses through nearly-collinear four-wave mixing (FWM). Non-degenerate mixing schemes allow for background free detection and can provide information on the interplay between a material's internal degrees of freedom. Here we show a source of temporal dynamics in the OKE signal that is not reflective of the intrinsic nonlinear response but arises from group index and momentum mismatch. It is observed in two-color experiments on condensed media with sizable spectral dispersion, a common property near an optical resonance. In particular birefringence in crystalline solids is able to entirely change the character of the OKE signal via the off-diagonal tensor elements of the nonlinear susceptibility. We develop a detailed description of the phase-mismatched ultrafast OKE and show how to extract quantitative information on the spectrally resolved birefringence and group index from time-resolved experiments in one and two dimensions., Comment: 12 pages, 6 figures

The ultrafast polarization response to incident light and ensuing exciton/carrier generation are essential to outstanding optoelectronic properties of lead halide perovskites (LHPs). A large number of mechanistic studies in the LHP field to date have focused on contributions to polarizability from organic cations and the highly polarizable inorganic lattice. For a comprehensive understanding of the ultrafast polarization response, we must additionally account for the nearly instantaneous hyperpolarizability response to the propagating light field itself. While light propagation is pivotal to optoelectronics and photonics, little is known about this in LHPs in the vicinity of the bandgap where stimulated emission, polariton condensation, superfluorescence, and photon recycling may take place. Here we develop two-dimensional optical Kerr effect (2D-OKE) spectroscopy to energetically dissect broadband light propagation and dispersive nonlinear polarization responses in LHPs. In contrast to earlier interpretations, the below-bandgap OKE responses in both hybrid CH3NH3PbBr3 and all-inorganic CsPbBr3 perovskites are found to originate from strong hyperpolarizability and highly anisotropic dispersions. In both materials, the nonlinear mixing of anisotropically propagating light fields result in convoluted oscillatory polarization dynamics. Based on a four-wave mixing model, we quantitatively derive dispersion anisotropies, reproduce 2D-OKE frequency correlations, and establish polarization dressed light propagation in single crystal LHPs. Moreover, our findings highlight the importance of distinguishing the often-neglected anisotropic light propagation from underlying coherent quasi-particle responses in various forms of ultrafast spectroscopy., Comment: 22 pages, 5 figures, 32 pages SI

Past few years have witnessed the artificial intelligence inspired evolution in various medical fields. The diagnosis and treatment of gliomas -- one of the most commonly seen brain tumors with low survival rate -- rely heavily on the computer assisted segmentation process undertaken on the magnetic resonance imaging (MRI) scans. Although the encoder-decoder shaped deep learning networks have been the de facto standard style for semantic segmentation tasks in medical imaging analysis, enormous effort is still required to be spent on designing the detailed architecture of the down-sampling and up-sampling blocks. In this work, we propose a neural architecture search (NAS) based solution to brain tumor segmentation tasks on multimodal volumetric MRI scans. Three sets of candidate operations are composed respectively for three kinds of basic building blocks in which each operation is assigned with a specific probabilistic parameter to be learned. Through alternately updating the weights of operations and the other parameters in the network, the searching mechanism ends up with two optimal structures for the upward and downward blocks. Moreover, the developed solution also integrates normalization and patching strategies tailored for brain MRI processing. Extensive comparative experiments on the BraTS 2019 dataset demonstrate that the proposed algorithm not only could relieve the pressure of fabricating block architectures but also possesses competitive feasibility and scalability.

Subwavelength periodic confinement can collectively and selectively enhance local light intensity and enable control over the photo-induced phase transformations at the nanometer scale. Standard nanofabrication process can result in geometrical and compositional inhomogeneities in optical phase change materials, especially chalcogenides, as those materials exhibit poor chemical and thermal stability. Here we demonstrate the self-assembled planar chalcogenide nanostructured array with resonance enhanced light emission to create an all-dielectric optical metasurface, by taking advantage of the fluid properties associated with solution processed films. A patterned silicon membrane serves as a template for shaping the chalcogenide metasurface structure. Solution-processed arsenic sulfide metasurface structures are self-assembled in the suspended 250 nm silicon membrane templates. The periodic nanostructure dramatically manifests the local light-matter interaction such as absorption of incident photons, Raman emission, and photoluminescence. Also, the thermal distribution is modified by the boundaries and thus the photo-thermal crystallization process, leading to the formation of anisotropic nano-emitters within the field enhancement area. This hybrid structure shows wavelength selective anisotropic photoluminescence, which is a characteristic behavior of the collective response of the resonant guided modes in a periodic nanostructure. The resonance enhanced Purcell effect could manifest the quantum efficiency of localized light emission.

Past few years have witnessed the prevalence of deep learning in many application scenarios, among which is medical image processing. Diagnosis and treatment of brain tumors requires an accurate and reliable segmentation of brain tumors as a prerequisite. However, such work conventionally requires brain surgeons significant amount of time. Computer vision techniques could provide surgeons a relief from the tedious marking procedure. In this paper, a 3D U-net based deep learning model has been trained with the help of brain-wise normalization and patching strategies for the brain tumor segmentation task in the BraTS 2019 competition. Dice coefficients for enhancing tumor, tumor core, and the whole tumor are 0.737, 0.807 and 0.894 respectively on the validation dataset. These three values on the test dataset are 0.778, 0.798 and 0.852. Furthermore, numerical features including ratio of tumor size to brain size and the area of tumor surface as well as age of subjects are extracted from predicted tumor labels and have been used for the overall survival days prediction task. The accuracy could be 0.448 on the validation dataset, and 0.551 on the final test dataset., Comment: Third place award of the 2019 MICCAI BraTS challenge survival task [BraTS 2019](https://www.med.upenn.edu/cbica/brats2019.html)