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Non-Hermitian systems, going beyond conventional Hermitian systems, have brought in intriguing concepts such as exceptional points and complex spectral topology as well as exotic phenomena such as non-Hermitian skin effects (NHSEs). However, previous studies on non-Hermitian systems predominantly focus on the properties of eigenstates, with rather limited discussions on non-Hermitian dynamic phenomena. Here, inspired by the celebrated success of the parity-time symmetry in non-Hermitian physics, we theoretically study a one-dimensional non-Hermitian system with glide-time reversal (GT) symmetry. We discover that the GT symmetry leads to unique physical properties and enables rich dynamic phenomena in non-Hermitian systems. Remarkably, we reveal the dynamic NHSEs that exhibit diverse behaviors across distinct dynamic phases, elucidating the richness of non-Hermitian dynamics. We establish the theoretical frameworks for understanding the rich non-Hermitian dynamic phenomena. We further show that the rich dynamic phases in the GT-symmetric systems enable the remarkable tuning of the dynamics in the bulk as well as at the edge boundaries. These include the directional wave propagation and amplification in the bulk, as well as the wave trapping and the dynamic patterns at the edge boundaries. With both the development in the theoretical framework and the study of the rich non-Hermitian dynamic phases, this work serves as a stepstone for future studies on non-Hermitian dynamics with a special emphasize on the pivotal role of the lattice symmetry.

In spatiotemporally modulated systems, topological states exist not only in energy gaps but also in momentum gaps. Such unconventional topological states impose challenges on topological physics. The underlying models also make the conventional Hamiltonian descriptions complicated. Here, we propose to describe such systems with space- and time-direction transfer matrices which substantially simplify the underlying theory and give direct information on the topological properties of the quasienergy and quasimomentum gaps. In particular, we find that the space- and time-direction reflection phases can serve as signatures for distinguishing various topological phases of the quasienergy and quasimomentum gaps. This approach directly reveals the topological properties of the band gap, avoiding the complexity in calculating bulk band topology in hybrid energy-moment space. By investigating two concrete models, we show that the method works well for both Hermitian and non-Hermitian systems. Furthermore, we uncover an unconventional topological state, called the anomalous Floquet quasimomentum gap, whose topological properties are invariant for different choices of the unit-cell center. This work advances the study of topological phenomena in hybrid space-time (energy-momentum) dimension that are attracting much interest due to the development of spatiotemporally modulated materials., Comment: 11 pages, 15 figures

Thermal transport is a fundamental mechanism of energy transfer process quite distinct from wave propagation phenomena. It can be manipulated well beyond the possibilities offered by natural materials with a new generation of artificial metamaterials: thermal metamaterials. Topological physics, a focal point in contemporary condensed matter physics, is closely intertwined with thermal metamaterials in recent years. Inspired by topological photonics and topological acoustics in wave metamaterials, a new research field emerged recently, which we dub `topological thermotics', which encompasses three primary branches: topological thermal conduction, convection, and radiation. For topological thermal conduction, we discuss recent advances in both 1D and higher-dimensional thermal topological phases. For topological thermal convection, we discuss the implementation of thermal exceptional points with their unique properties and non-Hermitian thermal topological states. Finally, we review the most recent demonstration of topological effects in the near-field and far-field radiation. Anticipating future developments, we conclude by discussing potential directions of topological thermotics, including the expansion into other diffusion processes such as particle dynamics and plasma physics, and the integration with machine learning techniques., Comment: This perpective summarizes the topological physics in thermal metamaterials and proposes a new research field, "topological thermotics"

High-brightness coherent light source is at the heart of optical technology and yet challenging to achieve. Here, we propose an unconventional approach that utilizes the "forbidden chemical" in optical thermodynamics to convert any incoming light beam into a high-brightness, high-spatial-coherence light beam in multimode nonlinear optical waveguide systems, in contrast to evaporative cooling in cold atoms where the brightness is instead reduced. This approach is powered by the fact that light in nonlinear multimode structures undergoes an irreversible thermalization process triggered by its own photon-photon interactions. Moreover, the key characteristics in statistical mechanics, the optical temperature and chemical potential can be widely tuned in photonic systems. As such, when the chemical potential of an optical reservoir is designed to locate at the forbidden band of the probe bosonic system, it can never reach thermal equilibrium with the probe hence endlessly pumping the probe system towards an enhanced brightness and spatial coherence. This amplified cooling of light beam is revealed via both Onsager's irreversible thermodynamics theory and numerical simulations. Akin to this effect, the inverse photonic transport currents emerge due to the negative off-diagonal Onsager coefficients. We demonstrate the feasibility of the amplified beam cooling using a coupled multimode optical waveguide system and show that after 800 rounds of amplified cooling, the optical power of an incoming beam is enhanced by 16 times, meanwhile the fundamental mode occupancy is increased to 90%. These findings unveil an anomalous optical phenomenon and a new route toward high-quality light sources.

The accuracy and efficiency of a coarse-grained (CG) force field are pivotal for high-precision molecular simulations of large systems with complex molecules. We present an automated mapping and optimization framework for molecular simulation (AMOFMS), which is designed to streamline and improve the force field optimization process. It features a neural-network-based mapping function, DSGPM-TP (Deep Supervised Graph Partitioning Model with Type Prediction). This model can accurately and efficiently convert atomistic structures to CG mappings, reducing the need for manual intervention. By integrating bottom-up and top-down methodologies, AMOFMS allows users to freely combine these approaches or use them independently as optimization targets. Moreover, users can select and combine different optimizers to meet their specific mission. With its parallel optimizer, AMOFMS significantly accelerates the optimization process, reducing the time required to achieve optimal results. Successful applications of AMOFMS include parameter optimizations for systems such as POPC and PEO, demonstrating its robustness and effectiveness. Overall, AMOFMS provides a general and flexible framework for the automated development of high-precision CG force fields., Comment: 22 pages, 5 figures, A flexible and accurate framework for the development of CG force field

Integrated nanophotonic biosensors offer a promising route toward future biomedical detection applications that may enable inexpensive, portable, and sensitive diagnosis of diseases with a small amount of biological samples for convenient early-stage screening of fatal diseases. However, the current photonic biosensor designs are not suitable for highly integrated and multiplexing device architectures that can achieve the detection of complex combinations of many biomarkers. Here, we propose a topological scheme for the integration of miniature biosensors in photonic crystal chips that can meet the above requirement. Using photonic topological edge states as robust one-dimensional waveguides that connect many photonic biosensors, we propose here the topologically integrated photonic biosensor circuits. We demonstrate that the performance of the topologically integrated photonic biosensors is much more robust against disorders than that of the photonic biosensors connected by the normal photonic waveguides, due to the robust transport of photons along the edge channel. Since disorders arising from the fabrication imperfection and the random distribution of the biomarkers are inevitable in genuine devices, resilience against disorders is a necessity for on-chip integration of biosensors. The topological scheme proposed here thus opens a promising path toward reliable integration of photonic biosensors for next-generation biomedical applications.

We propose a conceptual device for multiplexed biosensor in a photonic crystal chip based on the Su-Schrieffer-Heeger mechanism. Remarkably, the proposed biosensor can identify three distinct disease markers through a single-shot photon transmission measurement, due to the couplings among the three Su-Schrieffer-Heeger boundary modes in the photonic crystal. Our biosensor design is more robust against defects and disorders inevitable in real-life device applications than previous designs. Such robustness is invaluable for achieving efficient, reliable, and integrated biosensing based on nanophotonic systems. We further demonstrate that various combinations of disease markers can be recognized via the photon transmission spectrum, unveiling a promising route toward high performance advanced biosensing for future biomedical technology.

Robotic grasping in clutters is a fundamental task in robotic manipulation. In this work, we propose an economic framework for 6-DoF grasp detection, aiming to economize the resource cost in training and meanwhile maintain effective grasp performance. To begin with, we discover that the dense supervision is the bottleneck of current SOTA methods that severely encumbers the entire training overload, meanwhile making the training difficult to converge. To solve the above problem, we first propose an economic supervision paradigm for efficient and effective grasping. This paradigm includes a well-designed supervision selection strategy, selecting key labels basically without ambiguity, and an economic pipeline to enable the training after selection. Furthermore, benefit from the economic supervision, we can focus on a specific grasp, and thus we devise a focal representation module, which comprises an interactive grasp head and a composite score estimation to generate the specific grasp more accurately. Combining all together, the EconomicGrasp framework is proposed. Our extensive experiments show that EconomicGrasp surpasses the SOTA grasp method by about 3AP on average, and with extremely low resource cost, for about 1/4 training time cost, 1/8 memory cost and 1/30 storage cost. Our code is available at https://github.com/iSEE-Laboratory/EconomicGrasp., Comment: 19 pages, 7 figures. Accepted in ECCV 2024!

Going beyond the conventional theory, non-Abelian band topology uncovers the global quantum geometry of Bloch bands with multiple gaps and thus unveil a new paradigm for topological physics. However, to date, all non-Abelian topological materials are restricted to systems with time-reversal symmetry (T). Here, starting from a Kagome lattice inspired by Haldane model and designer gyromagnetic photonic crystals (PhCs), we show that T breaking can lead to rich non-Abelian topological physics, particularly the emergence of multigap antichiral edge states. Simply changing the magnetic flux of the Kagome lattice, or in-situ tuning the local magnetic field of the gyromagnetic PhCs, can lead to the unconventional creation, braiding, merging, and splitting of non-Abelian charged band nodes, alongside with the direct manipulation of the multigap antichiral edge states. Particularly, the quadratic point can be split into four Dirac points, a phenomenon unique in T-broken systems. Our theoretical and experimental findings will inspire a new direction in the study of non-Abelian physics in T-broken systems and open an unprecedent pathway for topological manipulation of electromagnetic waves.

Quantumkey distribution (QKD) promises unconditional security for communication. However, the random choices of the measurement basis in QKD usually result in low key creation efficiency. This drawback is overcome in the differential-phase-shift QKD, provided that each photon can be prepared in a large number of time bins with a proper waveform. In this work we develop a miniature 1550-nm single-photon source to generate narrowband single photon in 50 time bins with a nearly optimal waveform for achieving unity key creation efficiency. By utilizing these single photons in the field test, we demonstrate the differential-phase-shift QKD with a key creation efficiency of 97%. Our work shows that the practical QKD can benefit from the narrowband single photons with controllable waveforms., Comment: 9pages, 4figures

This paper explores a novel task ""Dexterous Grasp as You Say"" (DexGYS), enabling robots to perform dexterous grasping based on human commands expressed in natural language. However, the development of this field is hindered by the lack of datasets with natural human guidance; thus, we propose a language-guided dexterous grasp dataset, named DexGYSNet, offering high-quality dexterous grasp annotations along with flexible and fine-grained human language guidance. Our dataset construction is cost-efficient, with the carefully-design hand-object interaction retargeting strategy, and the LLM-assisted language guidance annotation system. Equipped with this dataset, we introduce the DexGYSGrasp framework for generating dexterous grasps based on human language instructions, with the capability of producing grasps that are intent-aligned, high quality and diversity. To achieve this capability, our framework decomposes the complex learning process into two manageable progressive objectives and introduce two components to realize them. The first component learns the grasp distribution focusing on intention alignment and generation diversity. And the second component refines the grasp quality while maintaining intention consistency. Extensive experiments are conducted on DexGYSNet and real world environment for validation., Comment: 9 pages, 7 figures

Nonlinear multimode optical systems have attracted substantial attention due to their rich physical properties. Complex interplay between the nonlinear effects and mode couplings makes it difficult to understand the collective dynamics of photons. Recent studies show that such collective phenomena can be effectively described by a Rayleigh-Jeans thermodynamics theory which is a powerful tool for the study of nonlinear multimode photonic systems. These systems, in turn, offer a compelling platform for investigating fundamental issues in statistical physics, attributed to their tunability and the ability to access negative temperature regimes. However, to date, a theory for the nonequilibrium transport and fluctuations is yet to be established. Here, we employ the full counting statistics theory to study the nonequilibrium transport of particle and energy in nonlinear multimode photonic systems in both positive and negative temperature regimes. Furthermore, we discover that in situations involving two reservoirs of opposite temperatures and chemical potentials, an intriguing phenomenon known as the loop current effect can arise, wherein the current in the positive energy sector runs counter to that in the negative energy sector. In addition, we numerically confirm that the fluctuation theorem remains applicable in optical thermodynamics systems across all regimes, from positive temperature to negative ones. Our findings closely align with numerical simulations based on first-principles nonlinear wave equations. Our work seeks to deepen the understanding of irreversible non-equilibrium processes and statistical fluctuations in nonlinear many-body photonic systems which will enhance our grasp of collective phenomena of photons and foster a fruitful intersection between optics and statistical physics., Comment: All comments are welcome

The puckered lattice geometry, along with $p$-orbitals is often overlooked in the study of topological physics. Here, we investigate the higher-order topology of the $p_{x,y}$-orbital bands in acoustic metamaterials using a simplified two-dimensional phosphorene lattice which possesses a puckered structure. Notably, unlike the $s$-orbital bands in planar lattices, the unique higher-order topology observed here is specific to $p$-orbitals and the puckered geometry due to the unusual hopping patterns induced by them. {Using acoustic pump-probe measurements in metamaterials}, we confirm the emergence of the edge and corner states arising due to the unconventional higher-order topology. We reveal the uniqueness of the higher-order topological physics here via complimentary tight-binding calculations, finite-element simulations, and acoustic experiments. We analyze the underlying physics of the special properties of the edge and corner states in the puckered lattice acoustic metamaterials from the picture of Wannier orbitals. Our work sheds light on the intriguing physics of $p$-orbital topological physics in puckered lattices and acoustic metamaterials which lead to unconventional topological boundary states. \end{abstract}, Comment: Accepted by Phys. Rev. B

Non-Hermitian physics has added new ingredients to topological physics, leading to the rising frontier of non-Hermitian topological phases. In this study, we investigate Chern insulator phases emerging from non-Hermitian kagome models with non-reciprocal and pure imaginary next-nearest neighbor hoppings. In the presence or absence of $C_3$ rotation symmetry, hybrid topological-skin effects are explored through the identification of distinct corner skin modes in different energy regions within two band gaps. By employing the dynamical analysis, the underlying physics is revealed from the non-Hermitian skin effects associated with the chiral edge states, leading to diverse non-Hermitian bulk-boundary responses. The simplicity of these kagome models and their rich emergent topological phenomena suggest that they are appealing candidates for studying non-Hermitian topological phases. We further discuss the possible realizations of these models in non-Hermitian metamaterials.

Fragile topology, akin to twisted bilayer graphene and the exotic phases therein, is a notable topological class with intriguing properties. However, due to its unique nature and the lack of bulk-edge correspondence, the experimental signature of fragile topology has been under debated since its birth. Here, we demonstrate experimentally that fragile topological phases with filling anomaly can be probed via screw dislocations, despite that they do not support gapless edge states. Using a designer hexagonal phononic crystal with a fragile topological band gap, we find that 1D gapless bound modes can emerge at a screw dislocation due to the bulk fragile topology. We then establish a connection between our system and the twisted boundary condition via the gauge invariance principle and illustrate that such an emergent phenomenon is an intrinsic property of fragile topological phases with filling anomaly. We observe experimentally the 1D topological bound states using the pump-probe measurements of their dispersion and wavefunctions, which unveils a novel bulk-defect correspondence of fragile topology and a powerful tool for probing fragile topological phases and materials., Comment: Submitted to Science Bulletin

The machine learning force field has achieved significant strides in accurately reproducing the potential energy surface with quantum chemical accuracy. However, it still faces significant challenges, e.g., extrapolating to uncharted chemical spaces, interpreting long-range electrostatics, and mapping complex macroscopic properties. To address these issues, we advocate for a synergistic integration of physical principles and machine learning techniques within the framework of a physically informed neural network (PINN). This innovative approach involves the incorporation of physical constraints directly into the parameters of the neural network, coupled with the implementation of a global optimization strategy. We choose the AMOEBA+ force field as the physics-based model for embedding, and then train and test it using the diethylene glycol dimethyl ether (DEGDME) dataset as a case study. The results reveal a significant breakthrough in constructing a precise and noise-robust machine learning force field. Utilizing two training sets with hundreds of samples, our model exhibits remarkable generalization and DFT accuracy in describing molecular interactions and enables a precise prediction of the macroscopic properties such as diffusion coefficient with minimal cost. This work provides a crucial insight into establishing a fundamental framework of PINN., Comment: 21 pages; 5 figures

Non-Hermitian physics has greatly enriched our understanding of nonequilibrium phenomena and uncovered novel effects such as the non-Hermitian skin effect (NHSE) that has profoundly revolutionized the field. NHSE is typically predicted in systems with nonreciprocal couplings which, however, are difficult to realize in experiments. Without nonreciprocal couplings, the NHSE can also emerge in systems with coexisting gauge fields and loss or gain (e.g., in Floquet non-Hermitian systems). However, such Floquet NHSE remains largely unexplored in experiments. Here, we realize the Floquet NHSEs in periodically modulated optical waveguides integrated on a silicon photonics platform. By engineering the artificial gauge fields induced by the periodical modulation, we observe various Floquet NHSEs and unveil their rich topological transitions. Remarkably, we discover the transitions between the normal unipolar NHSEs and an unconventional bipolar NHSE which is accompanied by the directional reversal of the NHSEs. The underlying physics is revealed by the band winding in complex quasienergy space which undergoes a topology change from isolated loops with the same winding to linked loops with opposite windings. Our work unfolds a new route toward Floquet NHSEs originating from the interplay between gauge fields and dissipation effects and offers fundamentally new ways for steering light and other waves., Comment: 12 pages, 3 figures

Text prompts are crucial for generalizing pre-trained open-set object detection models to new categories. However, current methods for text prompts are limited as they require manual feedback when generalizing to new categories, which restricts their ability to model complex scenes, often leading to incorrect detection results. To address this limitation, we propose a novel visual prompt method that learns new category knowledge from a few labeled images, which generalizes the pre-trained detection model to the new category. To allow visual prompts to represent new categories adequately, we propose a statistical-based prompt construction module that is not limited by predefined vocabulary lengths, thus allowing more vectors to be used when representing categories. We further utilize the category dictionaries in the pre-training dataset to design task-specific similarity dictionaries, which make visual prompts more discriminative. We evaluate the method on the ODinW dataset and show that it outperforms existing prompt learning methods and performs more consistently in combinatorial inference., Comment: Accepted at ICASSP 2024

To address the computational challenges of ab initio molecular dynamics and the accuracy limitations of empirical force fields, the introduction of machine learning force fields has proven effective in various systems including metals and inorganic materials. However, in large-scale organic systems, the application of machine learning force fields is often hindered by impediments such as the complexity of long-range intermolecular interactions and molecular conformations, as well as the instability in long-time molecular simulations. Therefore, we propose a universal multiscale higher-order equivariant model combined with active learning techniques, efficiently capturing the complex long-range intermolecular interactions and molecular conformations. Compared to existing equivariant models, our model achieves the highest predictive accuracy, and magnitude-level improvements in computational speed and memory efficiency. In addition, a bond length stretching method is designed to improve the stability of long-time molecular simulations. Utilizing only 901 samples from a dataset with 120 atoms, our model successfully extends high precision to systems with hundreds of thousands of atoms. These achievements guarantee high predictive accuracy, fast simulation speed, minimal memory consumption, and robust simulation stability, satisfying the requirements for high-precision and long-time molecular simulations in large-scale organic systems., Comment: 20 pages, 7 figures, Machine learning force field model

Entanglement entropy is a fundamental concept with rising importance in different fields ranging from quantum information science, black holes to materials science. In complex materials and systems, entanglement entropy provides insight into the collective degrees of freedom that underlie the systems' complex behaviours. As well-known predictions, the entanglement entropy exhibits area laws for systems with gapped excitations, whereas it follows the Gioev-Klich-Widom scaling law in gapless fermion systems. Furthermore, the entanglement spectrum provides salient characterizations of topological phases and phase transitions beyond the conventional paradigms. However, many of these fundamental predictions have not yet been confirmed in experiments due to the difficulties in measuring entanglement entropy in physical systems. Here, we report the experimental verification of the above predictions by probing the nonlocal correlations in phononic systems. From the pump-probe responses in phononic crystals, we obtain the entanglement entropy and entanglement spectrum for phononic systems with the fermion filling analog. With these measurements, we verify the Gioev-Klich-Widom scaling law of entanglement entropy for various quasiparticle dispersions in one- and two-dimensions. Moreover, we observe the salient signatures of topological phases in the entanglement spectrum and entanglement entropy which unveil an unprecedented probe of topological phases without relying on the bulk-boundary correspondence. The progress here opens a frontier where entanglement entropy serves as an important experimental tool in the study of emergent phases and phase transitions which can be generalized to non-Hermitian and other unconventional regimes.

Non-Hermitian effects have emerged as a new paradigm for the manipulation of phases of matter that profoundly changes our understanding of non-equilibrium systems, introducing novel concepts such as exceptional points and spectral topology, as well as exotic phenomena such as non-Hermitian skin effects (NHSEs). Most existing studies, however, focus on non-Hermitian eigenstates, whereas dynamic properties of non-Hermitian systems have been discussed only very recently, predicting unexpected phenomena such as wave self-healing, chiral Zener tunneling, and the dynamic NHSEs that are not yet confirmed in experiments. Here, we report the first experimental observation of rich non-Hermitian skin dynamics using tunable one-dimensional nonreciprocal double-chain mechanical systems with glide-time symmetry. Remarkably, dynamic NHSEs are observed with various dynamic behaviors in different dynamic phases, revealing the intriguing nature of these phases that can be understood via the generalized Brillouin zone and the related concepts. Moreover, the observed tunable non-Hermitian skin dynamics and amplifications, the bulk unidirectional wave propagation, and the boundary wave trapping provide promising ways to guide, trap, and amplify waves in a controllable and robust way. Our findings unveil the fundamental aspects and open a new pathway toward non-Hermitian dynamics, which will fertilize the study of non-equilibrium phases of matter and give rise to novel applications in information processing.

Quantum thermodynamics with microscopic inelastic scattering processes has been intensively investigated in recent years. Here, we apply quantum master equation combined with full counting statistics approach to investigate the role of quantum coherence on the periodically-driven inelastic heat engine. We demonstrate that the inelastic quantum heat engine exhibits dramatic advantage of thermodynamic performance compared to their elastic counterpart. Moreover, it is found that inelastic currents, {output work}, and the efficiency can be enhanced by quantum coherence. In particular, the geometric effect proves crucial in achieving maximal values of generated output work and energy conversion efficiency. The Berry curvature boosted by quantum coherence unveils the underlying mechanism of periodically-driven inelastic heat engine. Our findings may provide some insights for further understanding and optimizing periodically-driven heat engines via quantum coherence resource and inelastic scattering processes., Comment: 13 pages, 7 figures

Photonic crystals (PCs) are periodic dielectric structures that severed as an excellent platform to manipulate light. A conventional way to guide/trap light via PCs is to introduce a line or point defect by removing or modifying several unit cells. Here we show that the light can be effectively guided and trapped in the glided photonic crystal interfaces (GPCIs). The projected band gap of GPCIs, which depends on the glide parameter, is characterized by a Dirac mass. Interestingly, the GPCIs with zero Dirac mass is a glide-symmetric waveguide featured with excellent transmission performance even in the presence of sharp corners and disorders. Moreover, placing two GPCIs with opposite Dirac mass together results in a photonic bound state due to the Jackiw-Rebbi theory. Our work provides an alternative way towards the design of ultracompact photonic devices such as GPCIs-induced coupled cavity-waveguide system and waveguide splitter.

Diffusion driven by temperature or concentration gradients is a fundamental mechanism of energy and mass transport, which inherently differs from wave propagation in both physical foundations and application prospects. Compared with conventional schemes, metamaterials provide an unprecedented potential for governing diffusion processes, based on emerging theories like the transformation and the scattering cancellation theory, which enormously expanded the original concepts and suggest innovative metamaterial-based devices. We hereby use the term "diffusionics" to generalize these remarkable achievements in various energy (e.g., heat) and mass (e.g., particles and plasmas) diffusion systems. For clarity, we categorize the numerous studies appeared during the last decade by diffusion field (i.e., heat, particles, and plasmas) and discuss them from three different perspectives: the theoretical perspective, to detail how the transformation principle is applied to each diffusion field; the application perspective, to introduce various intriguing metamaterial-based devices, such as cloaks and radiative coolers; and the physics perspective, to connect with concepts of recent concern, such as non-Hermitian topology, nonreciprocal transport, and spatiotemporal modulation. We also discuss the possibility of controlling diffusion processes beyond metamaterials. Finally, we point out several future directions for diffusion metamaterial research, including the integration with artificial intelligence and topology concepts., Comment: This review article has been published in Reviews of Modern Physics, volume 96, 015002 (2024)

Pain is a significant global health issue, and the current treatment options for pain management have limitations in terms of effectiveness, side effects, and potential for addiction. There is a pressing need for improved pain treatments and the development of new drugs. Voltage-gated sodium channels, particularly Nav1.3, Nav1.7, Nav1.8, and Nav1.9, play a crucial role in neuronal excitability and are predominantly expressed in the peripheral nervous system. Targeting these channels may provide a means to treat pain while minimizing central and cardiac adverse effects. In this study, we construct protein-protein interaction (PPI) networks based on pain-related sodium channels and develop a corresponding drug-target interaction (DTI) network to identify potential lead compounds for pain management. To ensure reliable machine learning predictions, we carefully select 111 inhibitor datasets from a pool of over 1,000 targets in the PPI network. We employ three distinct machine learning algorithms combined with advanced natural language processing (NLP)-based embeddings, specifically pre-trained transformer and autoencoder representations. Through a systematic screening process, we evaluate the side effects and repurposing potential of over 150,000 drug candidates targeting Nav1.7 and Nav1.8 sodium channels. Additionally, we assess the ADMET (absorption, distribution, metabolism, excretion, and toxicity) properties of these candidates to identify leads with near-optimal characteristics. Our strategy provides an innovative platform for the pharmacological development of pain treatments, offering the potential for improved efficacy and reduced side effects.

Interfacial interactions are crucial in a variety of fields and can greatly affect the electric, magnetic, and chemical properties of materials. Among them, interface orbital hybridization plays a fundamental role in the properties of surface electrons such as dispersion, interaction, and ground states. Conventional measurements of electronic states at interfaces such as scanning tunneling microscopes are all based on electric interactions which, however, suffer from strong perturbation on these electrons. Here we unveil a new experimental detection of interface electrons based on the weak magnetic interactions between them and the nitrogen-vacancy (NV) center in diamond. With negligible perturbation on the interface electrons, their physical properties can be revealed by the NV spin coherence time. In our system, the interface interaction leads to significant decreases in both the density and coherence time of the electron spins at the diamond-graphene interface. Furthermore, together with electron spin resonance spectra and first-principle calculations, we can retrieve the effect of interface electron orbital hybridization. Our study opens a new pathway toward the microscopic probing of interfacial electronic states with weak magnetic interactions and provides a new avenue for future research on material interfaces.

Based on the spectral decomposition through a code of PrepSpec, the light curves (spanning 6.5 years in the observed frame) of the broad-line Balmer decrement, i.e., the flux ratio of the broad \ha to the broad \hb line, are calculated for a sample of 44 Sloan Digital Sky Survey reverberation-mapped quasars ($z<0.53$). It is found that the logarithm of the mean broad-line Balmer decrement is 0.62 with a standard deviation of 0.15 dex. The relations between the mean Balmer decrement and the SMBH accretion properties (the luminosity, black hole mass, Eddington ratio, accretion rate) are investigated and no obvious correlations are found. It is found that there are 27 quasars ($61\%$) showing strong negative correlations between the Balmer decrement variance and the continuum variance, i.e., the Balmer decrement would be smaller with larger continuum flux. Assuming that the dust obscuration leads to the variance in the Balmer decrement and the continuum, an expected slope is $-1/3$, which is not consistent with most of measured slopes. Using the interpolated cross-correlation function, the time delays between the inverse Balmer decrement and the continuum are measured for 14 quasars with the maximum correlation coefficient larger the 0.6. It suggests that the size corresponding to the Balmer decrement lag extends from the BLR size to the torus size., Comment: 10 pages, 10 figures, Accepted for publication in MNRAS