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Modern microelectronic processors have migrated towards parallel computing architectures with many-core processors. However, such expansion comes with diminishing returns exacted by the high cost of data movement between individual processors. The use of optical interconnects has burgeoned as a promising technology that can address the limits of this data transfer. While recent pushes to enhance optical communication have focused on developing wavelength-division multiplexing technology, this approach will eventually saturate the usable bandwidth, and new dimensions of data transfer will be paramount to fulfill the ever-growing need for speed. Here we demonstrate an integrated intra- and inter-chip multi-dimensional communication scheme enabled by photonic inverse design. Using inverse-designed mode-division multiplexers, we combine wavelength- and mode- multiplexing and send massively parallel data through nano-photonic waveguides and optical fibres. Crucially, as we take advantage of an orthogonal optical basis, our approach is inherently scalable to a multiplicative enhancement over the current state of the art., Comment: Fig.2-4 present new experimental results -- (i) demonstration of a broadband, low cross-talk multiplexer, (ii) a silicon photonic mode-division multiplexing with a chip-scale soliton microcomb source, and (iii) a chip-to-chip optical interconnect using a multimode-matched fibre and inverse-designed beam couplers

Atmospheric turbulence generally limits free-space optical (FSO) communications, and this problem is severely exacerbated when implementing highly sensitive and spectrally efficient coherent detection. Specifically, turbulence induces power coupling from the transmitted Gaussian mode to higher-order Laguerre-Gaussian (LG) modes, resulting in a significant decrease of the power that mixes with a single-mode local oscillator (LO). Instead, we transmit a frequency-offset Gaussian pilot tone along with the data signal, such that both experience similar turbulence and modal power coupling. Subsequently, the photodetector (PD) optoelectronically mixes all corresponding pairs of the beams' modes. During mixing, a conjugate of the turbulence experienced by the pilot tone is automatically generated and compensates the turbulence experienced by the data, and nearly all orders of the same corresponding modes efficiently mix. We demonstrate a 12-Gbit/s 16-quadrature-amplitude-modulation (16-QAM) polarization-multiplexed (PolM) FSO link that exhibits resilience to emulated turbulence. Experimental results for turbulence D/r_0~5.5 show up to ~20 dB reduction in the mixing power loss over a conventional coherent receiver. Therefore, our approach automatically recovers nearly all the captured data power to enable high-performance coherent FSO systems.

Lanthanum (La), the first member of the rare-earth elements, recently aroused strong interest due to its unique superhydride with superconducting properties. Although there is much theoretical and experimental work about phase transitions and superconductivity in metallic La, we got a new body-centred tetragonal ($bct$) phase in metallic La with space group $I4/mmm$ at $190$ GPa exchanging from face-centered cubic ($fcc$) phase in previous work, which expanded the phase transition sequence. The $bct$ phase shows an abnormal packing way that turned to non-closed packing at high pressure. And more detailed properties of the new phase are discussed.

Lanthanum hydrides, containing hydrogen framework structures under compression, display a superconducting state with a high observed critical temperature. However, this phenomenon has so far only been observed at very high pressures. Here, we computationally search for superconductors with very high critical temperatures, but at much lower pressures. We uncover two such sodalite-type clathrate hydrides, YbH6 and LuH6 (Tc =145 K at P=70 GPa for YbH6 and, especially, Tc =273 K at P=100 GPa for LuH6). These striking properties are a consequence of the strong interrelationship between the f states present at the Fermi surface, structural stability and Tc value. For example, TmH6, with unfilled 4f orbitals, is stable at 50 GPa, while it has a relatively low value of Tc of 25 K. As for the YbH6 and LuH6 compounds, they have filled f-shells and the decrease of the f-energy below the Fermi level leads to formation of the nesting regions on the Fermi surface and, as a result, to phonon "softening" and an increase in Tc., Comment: 14 pages ,4 figures

Common optical metasurfaces are 2-dimensional functional devices composed of periodically arranged subwavelength constituents. Here, we achieved the positional-disorder-immune metasurfaces composed of core-shell cylinders which successively exhibit the magnetic dipole (MD) resonant, non-radiating anapole, and electric dipole (ED) resonant modes when their outer radii are fixed and the inner radii changes continuously in a range. The performances of the metasurfaces under a periodically structural design are not degraded even when the positions of the cylinders are subjected to random and considerable displacements. The positional-disorder-immunity is due to the weak non-local effect of the metasurfaces. Because the multiple scattering among cylinders is weak and insensitive to the spacing among the cylinders around the ED and MD resonant modes and vanishing irrespective of the spacing at the non-radiating anapole mode, the reflection properties including the reflection phase and reflectivity of the metasurfaces are insensitive to the spacing between neighboring cylinders for this entire variation range of the inner radius. The positional-disorder-immunity make the metasurface to be adapted to some unstable and harsh environments., Comment: 20 pages, 8 figures

The high critical temperature phase of lanthanum hydrides deserves special attention because this phase displays the highest observed critical temperature. We focus on the evaluation of the critical temperature, isotope coefficient, and their pressure dependence of this phase (Fm3m phase of the LaH10 compound). By combining the method of two coupling constants, describing the interaction with the optical and acoustic modes, and two characteristic frequencies with first-principle calculations we are able to analyze the role of the light hydrogen in the amplitude of the critical temperature in this unique compound. Specifically, the critical temperature of 254 K and the isotope coefficient of 0.45 are evaluated at high pressure, and the results are in good agreement with the experimental data. The peculiar decrease in the value of the critical temperature upon further increase in pressure is explained by the presence of a flat region on the Fermi surface and the appearance of a two-gap structure, which should be experimentally observable by tunneling spectroscopy., Comment: 21 pages, 6 figures,2 tables

Following the discovery of high-temperature superconductivity in the La-H system, where for the recently discovered fcc-LaH10 a record critical temperature Tc = 250 K was achieved [Drozdov et al., Nature, 569, 528 (2019) and Somayazulu et al., Phys. Rev. Lett. 122, 027001 (2019)], we studied the formation of new chemical compounds in the barium-hydrogen system at pressures up to 173 GPa. Using in situ generation of hydrogen from NH3BH3, we synthesized previously unknown superhydride BaH12 with a pseudocubic (fcc) Ba sublattice, which was observed in a wide range of pressures from 75 to 173 GPa in four independent experiments. DFT calculations indicate a close agreement between the theoretical and experimental equations of state. In addition to BaH12, we identified previously known P6/mmm BaH2 and possibly BaH10 and BaH6 as impurities in the samples. Ab initio calculations show that newly discovered semimetallic BaH12 contains H2, H3 molecular units and detached H12 chains. Barium dodecahydride is a unique molecular hydride with metallic conductivity which demonstrates a superconducting transition around 20 K at 140 GPa in agreement with calculations (19-32 K). The interpretation of the multiphase XRD data was possible thanks to the development of new Python scripts for postprocessing the results of evolutionary searches. These scripts help quickly identify the theoretical structures that explain the experimental data in the best way, among thousands of candidates., Comment: Due to file size restrictions the supporting information file was uploaded to the Researchgate website

The recent discovery of H3S and LaH10 superconductors with record high superconducting transition temperatures, Tc, at high pressure, has fueled the search for room-temperature superconductivity in the compressed superhydrides. Here we predict the existence of an unprecedented hexagonal HfH10, with an extraordinarily high Tc of around 213-234 K at 250 GPa. In HfH10, the H atoms are arranged in clusters to form a planar "penta-graphene-like" sublattice, in contrast to the covalent sixfold cubic structure in H3S and clathrate-like structure in LaH10. The Hf atom acts as a "precompressor" and electron donor to the hydrogen sublattice. This "penta-graphene-like" H10 structure is also found in ZrH10, ScH10 and LuH10 at high pressure, each material showing a high Tc ranging from 134 to 220 kelvin. Our study of dense superhydrides with "penta-graphene-like" layered structures opens the door to the exploration and exploitation of a new class of high Tc superconductors.

Chinese keyword spotting is a challenging task as there is no visual blank for Chinese words. Different from English words which are split naturally by visual blanks, Chinese words are generally split only by semantic information. In this paper, we propose a new Chinese keyword spotter for natural images, which is inspired by Mask R-CNN. We propose to predict the keyword masks guided by text line detection. Firstly, proposals of text lines are generated by Faster R-CNN;Then, text line masks and keyword masks are predicted by segmentation in the proposals. In this way, the text lines and keywords are predicted in parallel. We create two Chinese keyword datasets based on RCTW-17 and ICPR MTWI2018 to verify the effectiveness of our method., Comment: Accepted by ICDAR2019

Class probabilities predicted by most multiclass classifiers are uncalibrated, often tending towards over-confidence. With neural networks, calibration can be improved by temperature scaling, a method to learn a single corrective multiplicative factor for inputs to the last softmax layer. On non-neural models the existing methods apply binary calibration in a pairwise or one-vs-rest fashion. We propose a natively multiclass calibration method applicable to classifiers from any model class, derived from Dirichlet distributions and generalising the beta calibration method from binary classification. It is easily implemented with neural nets since it is equivalent to log-transforming the uncalibrated probabilities, followed by one linear layer and softmax. Experiments demonstrate improved probabilistic predictions according to multiple measures (confidence-ECE, classwise-ECE, log-loss, Brier score) across a wide range of datasets and classifiers. Parameters of the learned Dirichlet calibration map provide insights to the biases in the uncalibrated model., Comment: Accepted for presentation at NeurIPS 2019