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Spin-orbit coupling in solids is typically a single-body effect arising from relativity. In this work, we propose a spontaneous generation of spin-orbit coupling from symmetry breaking. A spin-dependent electron-phonon coupling model is investigated on a half-filled square lattice, which is solved by sign-problem-free quantum Monte Carlo simulations. The phase diagram as function of phonon frequency $\omega$ and coupling constant $\lambda$ is fully investigated. The spin-orbit coupling emerges as an order in the ground state for any $\lambda$ in the adiabatic limit, accompanied by a breathing mode of lattice distortion and a staggered loop spin-current. This phase dominates in the entire range of $\omega$ with $\lambda< \lambda_{\infty}$, a critical value in the $\omega \to \infty$ limit. With increasing $\omega$ and $\lambda > \lambda_{\infty}$, the emergent spin-orbit coupling is suppressed and a phase transition occurs leading to charge-density-wave degenerate with superconductivity order. Our work opens up the possibility of hidden spin-orbit coupling in materials where it is otherwise forbidden by lattice symmetry and paves the way to explore new usable materials or devices in spintronics., Comment: 5 pages, 7 figures

Holography is an essential technique of generating three-dimensional images. Recently, quantum holography with undetected photons (QHUP) has emerged as a groundbreaking method capable of capturing complex amplitude images. Despite its potential, the practical application of QHUP has been limited by susceptibility to phase disturbances, low interference visibility, and limited spatial resolution. Deep learning, recognized for its ability in processing complex data, holds significant promise in addressing these challenges. In this report, we present an ample advancement in QHUP achieved by harnessing the power of deep learning to extract images from single-shot holograms, resulting in vastly reduced noise and distortion, alongside a notable enhancement in spatial resolution. The proposed and demonstrated deep learning QHUP (DL-QHUP) methodology offers a transformative solution by delivering high-speed imaging, improved spatial resolution, and superior noise resilience, making it suitable for diverse applications across an array of research fields stretching from biomedical imaging to remote sensing. DL-QHUP signifies a crucial leap forward in the realm of holography, demonstrating its immense potential to revolutionize imaging capabilities and pave the way for advancements in various scientific disciplines. The integration of DL-QHUP promises to unlock new possibilities in imaging applications, transcending existing limitations and offering unparalleled performance in challenging environments.

Scattering obscures information carried by wave by producing a speckle pattern, posing a common challenge across various fields, including microscopy and astronomy. Traditional methods for extracting information from speckles often rely on significant physical assumptions, complex devices, or intricate algorithms. Recently, machine learning has emerged as a scalable and widely adopted tool for interpreting speckle patterns. However, most current machine learning techniques depend heavily on supervised training with extensive labeled datasets, which is problematic when labels are unavailable. To address this, we propose a strategy based on unsupervised learning for speckle recognition and evaluation, enabling to capture high-level information, such as object classes, directly from speckles without labeled data. By deriving invariant features from speckles, this method allows for the classification of speckles and facilitates diverse applications in image sensing. We experimentally validated our strategy through two significant applications: a noninvasive glucose monitoring system capable of differentiating time-lapse glucose concentrations, and a high-throughput communication system utilizing multimode fibers in dynamic environments. The versatility of this method holds promise for a broad range of far-reaching applications, including biomedical diagnostics, quantum network decoupling, and remote sensing.

Topological physics provides novel insights for designing functional photonic devices, such as magnetic-free optical diodes, which are important in optical engineering and quantum information processing. Past efforts mostly focus on the topological edge modes in two-dimensional (2D) photonic Chern lattices, which, however, require delicate fabrication and temporal modulation. In particular, the 1D nonreciprocal edge mode needs to be embedded in a 2D lattice, contradicting with the compactness of integrated photonics. To address these challenges, we investigate the optical nonreciprocity of the 1D Su-Schrieffer-Heeger (SSH) superradiance lattices in room-temperature atoms. The probe fields propagating in two opposite directions perceive two different SSH topological phases, which have different absorption spectra due to the interplay between the Zak phase and the thermal motion of atoms, resulting in optical nonreciprocity. Our findings reveal the relationship between 1D topological matter and optical nonreciprocity, simplifying the design of topologically resilient nonreciprocal devices., Comment: 4 figures

Landau levels (LLs) are of great importance for understanding the quantum Hall effect and associated many-body physics. Recently, their three-dimensional (3D) counterparts, i.e., dispersionless 3D LLs with well-defined quantum numbers, have attracted significant attention but have not yet been reported. Here we theoretically propose and experimentally observe 3D LLs with a sharply quantized spectrum in a diamond acoustic lattice, where the eigenstates are characterized by SU(3) quantum numbers. The engineered inhomogeneous hopping strengths not only introduce pseudomagnetic fields that quantize the nodal lines into LLs but also provide three bosonic degrees of freedom, embedding a generic SU(3) symmetry into the LLs. Using a phased array of acoustic sources, we selectively excite distinct eigenstates within the degenerate LL multiplets and visualize their 3D eigenmodes. Importantly, our approach enables the precise reconstruction of SU(3) quantum numbers directly from eigenmode correlations. Our results establish SU(3) LLs as a tractable model in artificial platforms, and pave the way for synthesizing LLs with zero dispersion and countable quantum numbers in arbitrary dimensions., Comment: 6 pages, 4 figures

Uncovering the fundamental neural correlates of biological intelligence, developing mathematical models, and conducting computational simulations are critical for advancing new paradigms in artificial intelligence (AI). In this study, we implemented a comprehensive visual decision-making model that spans from visual input to behavioral output, using a neural dynamics modeling approach. Drawing inspiration from the key components of the dorsal visual pathway in primates, our model not only aligns closely with human behavior but also reflects neural activities in primates, and achieving accuracy comparable to convolutional neural networks (CNNs). Moreover, magnetic resonance imaging (MRI) identified key neuroimaging features such as structural connections and functional connectivity that are associated with performance in perceptual decision-making tasks. A neuroimaging-informed fine-tuning approach was introduced and applied to the model, leading to performance improvements that paralleled the behavioral variations observed among subjects. Compared to classical deep learning models, our model more accurately replicates the behavioral performance of biological intelligence, relying on the structural characteristics of biological neural networks rather than extensive training data, and demonstrating enhanced resilience to perturbation.

Computational imaging is crucial in many disciplines from autonomous driving to life sciences. However, traditional model-driven and iterative methods consume large computational power and lack scalability for imaging. Deep learning (DL) is effective in processing local-to-local patterns, but it struggles with handling universal global-to-local (nonlocal) patterns under current frameworks. To bridge this gap, we propose a novel DL framework that employs a progressive denoising strategy, named the deterministic diffusion model (DDM), to facilitate general computational imaging at a low cost. We experimentally demonstrate the efficient and faithful image reconstruction capabilities of DDM from nonlocal patterns, such as speckles from multimode fiber and intensity patterns of second harmonic generation, surpassing the capability of previous state-of-the-art DL algorithms. By embedding Bayesian inference into DDM, we establish a theoretical framework and provide experimental proof of its uncertainty quantification. This advancement ensures the predictive reliability of DDM, avoiding misjudgment in high-stakes scenarios. This versatile and integrable DDM framework can readily extend and improve the efficacy of existing DL-based imaging applications.

Pair density wave (PDW) is an intriguing quantum matter proposed in the frontier of condensed matter physics. However, the existence of PDW in microscopic models has been rare. In this work, we obtain, by Ginzburg-Landau arguments and self-consistent mean field theory, novel $2a_0\times2a_0$ PDW on the kagome lattice arising from attractive on-bond pairing interactions and the distinct Bloch wave functions near the p-type van Hove singularity. The PDW state carrying three independent wave-vectors, the so-called 3Q PDW, is nodeless and falls into two topological classes characterized by the Chern number $C = 0$ or $C = \pm2$. The chiral ($C=\pm2$) PDW state presents a rare case of interaction driven topological quantum state without the requirement of spin-orbit coupling. Finally, we analyze the stabilities and properties of these PDWs intertwining with charge orders, and discuss the relevance of our minimal model to recent experimental observations in kagome superconductors. Our theory not only elucidates the driving force of the chiral PDW, but also predicts strongly anisotropic superconducting gap structure in the momentum space and quantized transverse thermal conductivity that can be tested in future experiments., Comment: 7 pages, 4 figures

Soliton pulsations are ubiquitous feature of non-stationary soliton dynamics in mode-locked lasers and many other physical systems. To overcome difficulties related to huge amount of necessary computations and low efficiency of traditional numerical methods in modeling the evolution of non-stationary solitons, we propose a two-parallel bidirectional long short-term memory recurrent neural network, with the main objective to predict dynamics of vector-soliton pulsations in various complex states, whose real-time dynamics is verified by experiments. Besides, the scheme of coded information storage based on the TP-Bi_LSTM RNN, instead of actual pulse signals, is realized too. The findings offer new applications of deep learning to ultrafast optics and information storage., Comment: To be published in Laser & Photonics Reviews;https://doi.org/10.1002/lpor.202400097

Vortex is a topological defect in the superconducting condensate when a magnetic field is applied to a type-II superconductor, as elucidated by the Ginzburg-Landau theory. Due to the confinement of the quasiparticles by a vortex, it exhibits a circular shaped pattern of bound states with discrete energy levels, as predicted by the Caroli-de Gennes-Matricon theory in 1964. Here, however, we report a completely new type of vortex pattern which is necklace-like in an iron-based superconductor KCa2Fe4As4F2. Our theoretical analysis shows that this necklace-like vortex pattern arises from selective off-shell interference between vortex bound states of opposite angular momenta in the presence of rotational symmetry breaking due to disorders. This fascinating effect can be observed in a system with a small Fermi energy and wave vector, conditions fortuitously met in our samples. Our results not only disclose a novel vortex structure but also provide insights into comprehending the physics of the superconducting condensate., Comment: 29 pages total; 16 pages of main text with 5 figures, 13 pages of supplementary materials with 10 figures

Quantum simulation offers an analog approach for exploring exotic quantum phenomena using controllable platforms, typically necessitating ultracold temperatures to maintain the quantum coherence. Superradiance lattices (SLs) have been harnessed to simulate coherent topological physics at room temperature, but the thermal motion of atoms remains a notable challenge in accurately measuring the physical quantities. To overcome this obstacle, we invent and validate a velocity scanning tomography technique to discern the responses of atoms with different velocities, allowing cold-atom spectroscopic resolution within room-temperature SLs. By comparing absorption spectra with and without atoms moving at specific velocities, we can derive the Wannier-Stark ladders of the SL across various effective static electric fields, their strengths being proportional to the atomic velocities. We extract the Zak phase of the SL by monitoring the ladder frequency shift as a function of the atomic velocity, effectively demonstrating the topological winding of the energy bands. Our research signifies the feasibility of room-temperature quantum simulation and facilitates their applications in quantum information processing., Comment: 6 pages, 4 figures

Isotope effect with a large coefficient $\alpha=-\partial \ln T_c/\partial \ln M$ is usually taken as an evidence of phonon mediated superconductors in the Bardeen-Cooper-Schrieffer (BCS) theory. However, in cuprates which are now widely believed to be strong correlation induced d-wave superconductors, $\alpha$ is experimentally observed to be quite small at optimal doping, but keeps growing up with decreasing $T_c$ upon doping, even after exceeding the BCS value $1/2$. Such an anomalous isotope effect seems to challenge the non-phonon picture and still leave room for the phonon-dominated mechanism. In this work, we show that the anomalous dependence of $\alpha$ on $T_c$ can actually be obtained in spin fluctuation induced d-wave superconductors, by studying the Hubbard model on square lattices with functional renormalization group. We have considered two types of electron-phonon couplings (EPCs). The first type couples to electron densities, including the Holstein, breathing and buckling phonons, called Holstein-like. For all these EPCs, $\alpha$ is negative and drops down towards $-\infty$ with decreasing $T_c$ upon doping. On the opposite, for the other type of Peierls-like EPC coupling to electron hoppings on the nearest bonds, also called Su-Schrieffer-Heeger phonon, $\alpha$ is positive, grows up with decreasing $T_c$ and tends to diverge as $T_c\to0$, in qualitative agreement with the experiments. The difference between these two types of EPCs can be understood by their isotope effects on spin fluctuations. From this study, we conclude that the SSH phonon can explain the anomalous isotope effect in cuprates, although it is not the leading pairing mechanism.

The bound states around a vortex in anisotropic superconductors is a longstanding yet important issue. In this work, we develop a variational theory on the basis of the Andreev approximation to obtain the energy levels and wave functions of the low-energy quantized bound states in superconductors with anisotropic pairing on arbitrary Fermi surface. In the case of circular Fermi surface, the effective Schr\"odinger equation yielding the bound state energies gets back to the theory proposed by Volovik and Kopnin many years ago. Our generalization here enables us to prove the equidistant energy spectrum inside a vortex in a broader class of superconductors. More importantly, we are now able to obtain the wave functions of these bound states by projecting the quasiclassical wave function on the eigenmodes of the effective Schr\"odinger equation, going beyond the quasiclassical Eilenberger results, which, as we find, are sensitive to the scattering rate. For the case of isotropic Fermi surface, the spatial profile of the low-energy local density of states is dominated near the vortex center and elongates along the gap antinode directions, in addition to the ubiquitous Friedel oscillation arising from the quantum inteference neglected in the Eilenberger theory. Moreover, as a consequence of the pairing anisotropy, the quantized wave functions develop a peculiar distribution of winding number, which reduces stepwise towards the vortex center. Our work provides a flexible way to study the vortex bound states in the future.

Complete quantum control of a stationary quantum bit embedded in a quantum emitter is crucial for photonic quantum information technologies. Recently, the orbital degree of freedom in optically active quantum dots has emerged as a promising candidate. However, the essential ability to perform arbitrary rotations on orbital qubits remains elusive. Here, we demonstrate arbitrary rotation of a hole orbital qubit with direct phase control using picosecond optical pulses. This is achieved by successfully inducing stimulated Raman transitions within $\Lambda$ systems coupled via radiative Auger processes. The new capability enables direct control of polar and azimuth angles of the Bloch vector without requiring timed precession. Our results establish orbital states in solid-state quantum emitters as a viable resource for applications in high-speed quantum information processing., Comment: Manuscript with 7 pages and 4 figures plus Supplementary Material comprising 9 pages and 10 figures

Quantum speed limits (QSLs) impose fundamental constraints on the evolution speed of quantum systems. Traditionally, the Mandelstam-Tamm (MT) and Margolus-Levitin (ML) bounds have been widely employed, relying on the standard deviation and mean of energy distribution to define the QSLs. However, these universal bounds only offer loose restrictions on the quantum evolution. Here we introduce the generalized ML bounds, which prove to be more stringent in constraining dynamic evolution, by utilizing moments of energy spectra of arbitrary orders, even noninteger orders. To validate our findings, we conduct experiments in a superconducting circuit, where we have the capability to prepare a wide range of quantum photonic states and rigorously test these bounds by measuring the evolution of the system and its photon statistics using quantum state tomography. While, in general, the MT bound is effective for short-time evolution, we identify specific parameter regimes where either the MT or the generalized ML bounds suffice to constrain the entire evolution. Our findings not only establish new criteria for estimating QSLs but also substantially enhance our comprehension of the dynamic evolution of quantum systems.

The effects of optical bond phonons coupled to electrons in two-dimensional lattices have attracted much interest recently, with the hope to explore unconventional superconducting mechanism and pairing symmetries. Here we conduct a systematic investigation of such phonon modes in the kagome lattice at and around the upper van Hove filling, in order to unravel new effects of the bond phonons in the presence of the unique sublattice frustration. We combine the singular-mode functional renormalization group and the projector determinant quantum Monte Carlo methods. At the upper van Hove filling and in the absence of the Hubbard interaction $U$, we find there exists an s-wave superconducting state at weaker electron-phonon coupling constant $\lambda$ and higher phonon frequency $\omega$, and a charge bond order (or the valence bond solid) state at larger $\lambda$ and lower $\omega$. The Hubbard interaction $U$ suppresses drastically the s-wave pairing, so that only the charge bond order survives. On the other hand, upon slight doping away from the van Hove filling, we observe that the charge bond order is suppressed due to the breakdown of the perfect Fermi surface nesting, while the superconductivity persists. The s-wave superconductivity and charge bond order may be relevant in the layered kagome superconductors AV$_3$Sb$_5$ (A=K, Rb, Cs).

We study the electronic orders at the lower van Hove filling in the kagome lattice. In the weak limit of the Hubbard interaction $U$ versus the hopping parameter $t$, we find that the system develops itinerant ferromagnetism; In the intermediate range of $U$, we find the system develops noncollinear magnetic order with orthogonal spin moments on nearest-neighbor bonds. This is in fact a Chern insulator supporting quantized anomalous Hall conductance; In the strong $U$ limit, we map the Hubbard model to the $t$-$J$ model with $J = 4t^2/U$. For moderate values of $J$ we recover the noncollinear magnetic order obtained in the Hubbard model. However, in the limit of $J\to 0$ (or $U\to \infty$) we find the ferromagnetic order revives. The results are obtained by combination of the random-phase approximation and functional renormalization group in the weak to moderate limit of $U$, and the variational quantum Monte Carlo for the $t$-$J$ model in the strong coupling limit. The phase diagram is distinctly different to that at the higher van Hove filling studied earlier, and the difference can be attributed to the lack of particle-hole symmetry in the band structure with respect to the Dirac point.

The recent discovery of bulk superconductivity in trilayer nickelate La$_4$Ni$_3$O$_{10}$ with the critical temperature $T_c$ near $30$K under high pressure is attracting a new wave of research interest, after the breakthrough of bilayer La$_3$Ni$_2$O$_7$ with $T_c$ near $80$K. The similarities and differences of electronic structure and superconducting mechanism in these two systems are urgent theoretical issues. In this Letter, we study the electronic band structure and construct a minimal trilayer tight-binding model for the high-pressure phase of La$_4$Ni$_3$O$_{10}$ in terms of the nickel $3d_{x^2-y^2}$ and $3d_{3z^2-r^2}$ orbitals, and study the superconducting mechanism due to local Coulomb interactions by the unbiased functional renormalization group. We find antiferromagnetic correlations between the outer layers instead of neighboring ones, apart from the inplane correlations. The effective interaction induces Cooper pairing with the $s_\pm$-wave symmetry, which changes sign across the Fermi pockets. We find $T_c$ in La$_4$Ni$_3$O$_{10}$ is systematically lower than that in La$_3$Ni$_2$O$_7$, and electron doping can enhance $T_c$., Comment: 4 pages, 4 figures, 1 table

Visible-infrared person re-identification (VI-ReID) aims to retrieve images of the same persons captured by visible (VIS) and infrared (IR) cameras. Existing VI-ReID methods ignore high-order structure information of features while being relatively difficult to learn a reasonable common feature space due to the large modality discrepancy between VIS and IR images. To address the above problems, we propose a novel high-order structure based middle-feature learning network (HOS-Net) for effective VI-ReID. Specifically, we first leverage a short- and long-range feature extraction (SLE) module to effectively exploit both short-range and long-range features. Then, we propose a high-order structure learning (HSL) module to successfully model the high-order relationship across different local features of each person image based on a whitened hypergraph network.This greatly alleviates model collapse and enhances feature representations. Finally, we develop a common feature space learning (CFL) module to learn a discriminative and reasonable common feature space based on middle features generated by aligning features from different modalities and ranges. In particular, a modality-range identity-center contrastive (MRIC) loss is proposed to reduce the distances between the VIS, IR, and middle features, smoothing the training process. Extensive experiments on the SYSU-MM01, RegDB, and LLCM datasets show that our HOS-Net achieves superior state-of-the-art performance. Our code is available at \url{https://github.com/Jaulaucoeng/HOS-Net}., Comment: Accepted by AAAI-2024