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Yu Tian

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preprint2026arXiv

Skills-Coach: A Self-Evolving Skill Optimizer via Training-Free GRPO

We introduce Skills-Coach, a novel automated framework designed to significantly enhance the self-evolution of skills within Large Language Model (LLM)-based agents. Addressing the current fragmentation of the skill ecosystem, Skills-Coach explores the boundaries of skill capabilities, thereby facilitating the comprehensive competency coverage essential for intelligent applications. The framework comprises four core modules: a Diverse Task Generation Module that systematically creates a comprehensive test suite for various skills; a Lightweight Optimization Module dedicated to optimizing skill prompts and their corresponding code; a Comparative Execution Module facilitating the execution and evaluation of both original and optimized skills; and a Traceable Evaluation Module, which rigorously evaluates performance against specified criteria. Skills-Coach offers flexible execution options through its virtual and real modes. To validate its efficacy, we introduce Skill-X, a comprehensive benchmark dataset consisting of 48 diverse skills. Experimental results demonstrate that Skills-Coach achieves significant performance improvements in skill capability across a wide range of categories, highlighting its potential to advance the development of more robust and adaptable LLM-based agents.

preprint2024arXiv

Quench Dynamics in Holographic First-Order Phase Transition

In this work, we investigate the real-time dynamics of quenching a state from phase separation in a holographic model of first-order phase transition. In addition to the typical phase-separated and high-energy final states, we have discovered a novel dynamical process that drives the system to a low-temperature supercooled final state within a narrow range of quench parameters. The critical behavior is also revealed during the fully non-linear dynamics. Following a sudden quench with critical parameters, the phase separation can be attracted to a critical nucleus. Specifically, the critical nucleus will subsequently shrink in size and eventually disappear for super-critical parameters, where the system is actually supercooled with a temperature lower than the initial one. While for sub-critical parameters, the nucleus will grow in size and finally reform a phase separation, where the absorbed quenching energy is reflected in the increment of the latent heat.

preprint2024arXiv

Spreading and Structural Balance on Signed Networks

Two competing types of interactions often play an important part in shaping system behavior, such as activatory or inhibitory functions in biological systems. Hence, signed networks, where each connection can be either positive or negative, have become popular models over recent years. However, the primary focus of the literature is on the unweighted and structurally unbalanced ones, where all cycles have an even number of negative edges. Hence here, we first introduce a classification of signed networks into balanced, antibalanced or strictly unbalanced ones, and then characterize each type of signed networks in terms of the spectral properties of the signed weighted adjacency matrix. In particular, we show that the spectral radius of the matrix with signs is smaller than that without if and only if the signed network is strictly unbalanced. These properties are important to understand the dynamics on signed networks, both linear and nonlinear ones. Specifically, we find consistent patterns in a linear and a nonlinear dynamics theoretically, depending on their type of balance. We also propose two measures to further characterize strictly unbalanced networks, motivated by perturbation theory. Finally, we numerically verify these properties through experiments on both synthetic and real networks.

preprint2023arXiv

Extended black hole thermodynamics from extended Iyer-Wald formalism

In recent years, there has been significant interest in the field of extended black hole thermodynamics, where the cosmological constant and/or other coupling parameters are treated as thermodynamic variables. Drawing inspiration from the Iyer-Wald formalism, which reveals the intrinsic and universal structure of conventional black hole thermodynamics, we illustrate that a proper extension of this formalism also unveils the underlying theoretical structure of extended black hole thermodynamics. As a remarkable consequence, for any gravitational theory described by a diffeomorphism invariant action, it is always possible to construct a consistent extended thermodynamics using this extended formalism.

preprint2023arXiv

Knowledge Distillation to Ensemble Global and Interpretable Prototype-Based Mammogram Classification Models

State-of-the-art (SOTA) deep learning mammogram classifiers, trained with weakly-labelled images, often rely on global models that produce predictions with limited interpretability, which is a key barrier to their successful translation into clinical practice. On the other hand, prototype-based models improve interpretability by associating predictions with training image prototypes, but they are less accurate than global models and their prototypes tend to have poor diversity. We address these two issues with the proposal of BRAIxProtoPNet++, which adds interpretability to a global model by ensembling it with a prototype-based model. BRAIxProtoPNet++ distills the knowledge of the global model when training the prototype-based model with the goal of increasing the classification accuracy of the ensemble. Moreover, we propose an approach to increase prototype diversity by guaranteeing that all prototypes are associated with different training images. Experiments on weakly-labelled private and public datasets show that BRAIxProtoPNet++ has higher classification accuracy than SOTA global and prototype-based models. Using lesion localisation to assess model interpretability, we show BRAIxProtoPNet++ is more effective than other prototype-based models and post-hoc explanation of global models. Finally, we show that the diversity of the prototypes learned by BRAIxProtoPNet++ is superior to SOTA prototype-based approaches.

preprint2023arXiv

Protected Transverse Electric Waves in Topological Dielectric Waveguides

Waveguides are fundamental components in communication systems. However, they suffer from reflection and scattering losses at sharp routes or defects. The breakthrough in developing topological photonic crystals (PhCs) provides promising solutions to robust signal transmission. In this work, we propose a new mechanism for protecting wave-guiding modes by decorating the boundaries of a conventional waveguide with valley-Hall PhCs. This special layout enables the robust propagation of conventional transverse electric waves against defects and bends. Moreover, the proposed waveguide is compatible with the substrate integrated waveguide (SIW). High efficient mode conversion from the SIW to the proposed waveguide is achievable. By leveraging the idea of topology to conventional waveguides, we provide a powerful and practical tool that can largely improve the performance of microwave and millimeter-wave integrated circuits while reserving the features of wave-guiding modes.

preprint2022arXiv

ACPL: Anti-curriculum Pseudo-labelling for Semi-supervised Medical Image Classification

Effective semi-supervised learning (SSL) in medical image analysis (MIA) must address two challenges: 1) work effectively on both multi-class (e.g., lesion classification) and multi-label (e.g., multiple-disease diagnosis) problems, and 2) handle imbalanced learning (because of the high variance in disease prevalence). One strategy to explore in SSL MIA is based on the pseudo labelling strategy, but it has a few shortcomings. Pseudo-labelling has in general lower accuracy than consistency learning, it is not specifically designed for both multi-class and multi-label problems, and it can be challenged by imbalanced learning. In this paper, unlike traditional methods that select confident pseudo label by threshold, we propose a new SSL algorithm, called anti-curriculum pseudo-labelling (ACPL), which introduces novel techniques to select informative unlabelled samples, improving training balance and allowing the model to work for both multi-label and multi-class problems, and to estimate pseudo labels by an accurate ensemble of classifiers (improving pseudo label accuracy). We run extensive experiments to evaluate ACPL on two public medical image classification benchmarks: Chest X-Ray14 for thorax disease multi-label classification and ISIC2018 for skin lesion multi-class classification. Our method outperforms previous SOTA SSL methods on both datasets

preprint2022arXiv

Artifact-Tolerant Clustering-Guided Contrastive Embedding Learning for Ophthalmic Images

Ophthalmic images and derivatives such as the retinal nerve fiber layer (RNFL) thickness map are crucial for detecting and monitoring ophthalmic diseases (e.g., glaucoma). For computer-aided diagnosis of eye diseases, the key technique is to automatically extract meaningful features from ophthalmic images that can reveal the biomarkers (e.g., RNFL thinning patterns) linked to functional vision loss. However, representation learning from ophthalmic images that links structural retinal damage with human vision loss is non-trivial mostly due to large anatomical variations between patients. The task becomes even more challenging in the presence of image artifacts, which are common due to issues with image acquisition and automated segmentation. In this paper, we propose an artifact-tolerant unsupervised learning framework termed EyeLearn for learning representations of ophthalmic images. EyeLearn has an artifact correction module to learn representations that can best predict artifact-free ophthalmic images. In addition, EyeLearn adopts a clustering-guided contrastive learning strategy to explicitly capture the intra- and inter-image affinities. During training, images are dynamically organized in clusters to form contrastive samples in which images in the same or different clusters are encouraged to learn similar or dissimilar representations, respectively. To evaluate EyeLearn, we use the learned representations for visual field prediction and glaucoma detection using a real-world ophthalmic image dataset of glaucoma patients. Extensive experiments and comparisons with state-of-the-art methods verified the effectiveness of EyeLearn for learning optimal feature representations from ophthalmic images.

preprint2022arXiv

Coarse-to-Fine: Hierarchical Multi-task Learning for Natural Language Understanding

Generalized text representations are the foundation of many natural language understanding tasks. To fully utilize the different corpus, it is inevitable that models need to understand the relevance among them. However, many methods ignore the relevance and adopt a single-channel model (a coarse paradigm) directly for all tasks, which lacks enough rationality and interpretation. In addition, some existing works learn downstream tasks by stitches skill block(a fine paradigm), which might cause irrationalresults due to its redundancy and noise. Inthis work, we first analyze the task correlation through three different perspectives, i.e., data property, manual design, and model-based relevance, based on which the similar tasks are grouped together. Then, we propose a hierarchical framework with a coarse-to-fine paradigm, with the bottom level shared to all the tasks, the mid-level divided to different groups, and the top-level assigned to each of the tasks. This allows our model to learn basic language properties from all tasks, boost performance on relevant tasks, and reduce the negative impact from irrelevant tasks. Our experiments on 13 benchmark datasets across five natural language understanding tasks demonstrate the superiority of our method.

preprint2022arXiv

Collapsing dust thin shells in Einstein-Gauss-Bonnet gravity

We investigate gravitational collapse of a spherically symmetric thin shell in the Einstein-Gauss-Bonnet (EGB) gravity. Under the recently proposed 4D limit, we find that the collapsing shell will be bounced back at a small radius, without forming a singularity. This bouncing behavior is similar to those of a test particle and a homogeneous spherical dust star, in accordance with the expectation that the Gauss-Bonnet term will modify the small scale behavior of the Einstein gravity. We analyze the causal structure of the dynamic spacetime that represents the bouncing process, finding that the thin shell has an oscillation behavior on the Penrose diagram, which means that the thin shell results in a novel type of black hole with respect to observers outside the event horizon that the collapse forms. We also find that the weak cosmic censorship conjecture holds in this model. Further implications of such a regular gravitational collapse are discussed.

preprint2022arXiv

Contrastive Transformer-based Multiple Instance Learning for Weakly Supervised Polyp Frame Detection

Current polyp detection methods from colonoscopy videos use exclusively normal (i.e., healthy) training images, which i) ignore the importance of temporal information in consecutive video frames, and ii) lack knowledge about the polyps. Consequently, they often have high detection errors, especially on challenging polyp cases (e.g., small, flat, or partially visible polyps). In this work, we formulate polyp detection as a weakly-supervised anomaly detection task that uses video-level labelled training data to detect frame-level polyps. In particular, we propose a novel convolutional transformer-based multiple instance learning method designed to identify abnormal frames (i.e., frames with polyps) from anomalous videos (i.e., videos containing at least one frame with polyp). In our method, local and global temporal dependencies are seamlessly captured while we simultaneously optimise video and snippet-level anomaly scores. A contrastive snippet mining method is also proposed to enable an effective modelling of the challenging polyp cases. The resulting method achieves a detection accuracy that is substantially better than current state-of-the-art approaches on a new large-scale colonoscopy video dataset introduced in this work.

preprint2022arXiv

Critical phenomena in dynamical scalarization of charged black hole

We report a new black hole scalarization mechanism and disclose novel dynamical critical phenomena in the process of the nonlinear accretion of the scalar field into black holes. The accretion process can transform a seed black hole into a final scalarized or bald black hole, depending on the initial parameter of the scalar field $p$. There is a critical parameter $p_{\ast}$ and near it all intermediate solutions are attracted to a critical solution and stay there for a time scaling as $T\propto-γ\ln|p-p_{\ast}|$. At late times, the solutions evolve into scalarized black holes if $p>p_{\ast}$, or bald black holes if $p<p_{\ast}$. The final masses of the resulting scalarized/bald black holes satisfy power-laws $M_{p}-M_{\pm}\propto|p-p_{\ast}|^{γ_{\pm}}$ where $M_{\pm}$ are the masses of the scalarized/bald black holes when $p\to p_\ast$ from above/below, and $γ_{\pm}$ the corresponding exponents.

preprint2022arXiv

Deep One-Class Classification via Interpolated Gaussian Descriptor

One-class classification (OCC) aims to learn an effective data description to enclose all normal training samples and detect anomalies based on the deviation from the data description. Current state-of-the-art OCC models learn a compact normality description by hyper-sphere minimisation, but they often suffer from overfitting the training data, especially when the training set is small or contaminated with anomalous samples. To address this issue, we introduce the interpolated Gaussian descriptor (IGD) method, a novel OCC model that learns a one-class Gaussian anomaly classifier trained with adversarially interpolated training samples. The Gaussian anomaly classifier differentiates the training samples based on their distance to the Gaussian centre and the standard deviation of these distances, offering the model a discriminability w.r.t. the given samples during training. The adversarial interpolation is enforced to consistently learn a smooth Gaussian descriptor, even when the training data is small or contaminated with anomalous samples. This enables our model to learn the data description based on the representative normal samples rather than fringe or anomalous samples, resulting in significantly improved normality description. In extensive experiments on diverse popular benchmarks, including MNIST, Fashion MNIST, CIFAR10, MVTec AD and two medical datasets, IGD achieves better detection accuracy than current state-of-the-art models. IGD also shows better robustness in problems with small or contaminated training sets. Code is available at https://github.com/tianyu0207/IGD.

preprint2022arXiv

Design of a Biomimetic Tactile Sensor for Material Classification

Tactile sensing typically involves active exploration of unknown surfaces and objects, making it especially effective at processing the characteristics of materials and textures. A key property extracted by human tactile perception is surface roughness, which relies on measuring vibratory signals using the multi-layered fingertip structure. Existing robotic systems lack tactile sensors that are able to provide high dynamic sensing ranges, perceive material properties, and maintain a low hardware cost. In this work, we introduce the reference design and fabrication procedure of a miniature and low-cost tactile sensor consisting of a biomimetic cutaneous structure, including the artificial fingerprint, dermis, epidermis, and an embedded magnet-sensor structure which serves as a mechanoreceptor for converting mechanical information to digital signals. The presented sensor is capable of detecting high-resolution magnetic field data through the Hall effect and creating high-dimensional time-frequency domain features for material texture classification. Additionally, we investigate the effects of different superficial sensor fingerprint patterns for classifying materials through both simulation and physical experimentation. After extracting time series and frequency domain features, we assess a k-nearest neighbors classifier for distinguishing between different materials. The results from our experiments show that our biomimetic tactile sensors with fingerprint ridges can classify materials with more than 8% higher accuracy and lower variability than ridge-less sensors. These results, along with the low cost and customizability of our sensor, demonstrate high potential for lowering the barrier to entry for a wide array of robotic applications, including model-less tactile sensing for texture classification, material inspection, and object recognition.

preprint2022arXiv

Experimental Realization of a Quantum Refrigerator Driven by Indefinite Causal Orders

Indefinite causal order (ICO) is playing a key role in recent quantum technologies. Here, we experimentally study quantum thermodynamics driven by ICO on nuclear spins using the nuclear magnetic resonance system. We realize the ICO of two thermalizing channels to exhibit how the mechanism works, and show that the working substance can be cooled or heated albeit it undergoes thermal contacts with reservoirs of the same temperature. Moreover, we construct a single cycle of the ICO refrigerator based on the Maxwell's demon mechanism, and evaluate its performance by measuring the work consumption and the heat energy extracted from the low-temperature reservoir. Unlike classical refrigerators in which the coefficient of performance (COP) is perversely higher the closer the temperature of the high-temperature and low-temperature reservoirs are to each other, the ICO refrigerator's COP is always bounded to small values due to the non-unit success probability in projecting the ancillary qubit to the preferable subspace. To enhance the COP, we propose and experimentally demonstrate a general framework based on the density matrix exponentiation (DME) approach, as an extension to the ICO refrigeration. The COP is observed to be enhanced by more than three times with the DME approach. Our work demonstrates a new way for non-classical heat exchange, and paves the way towards construction of quantum refrigerators on a quantum system.

preprint2022arXiv

Face Anti-Spoofing by Learning Polarization Cues in a Real-World Scenario

Face anti-spoofing is the key to preventing security breaches in biometric recognition applications. Existing software-based and hardware-based face liveness detection methods are effective in constrained environments or designated datasets only. Deep learning method using RGB and infrared images demands a large amount of training data for new attacks. In this paper, we present a face anti-spoofing method in a real-world scenario by automatic learning the physical characteristics in polarization images of a real face compared to a deceptive attack. A computational framework is developed to extract and classify the unique face features using convolutional neural networks and SVM together. Our real-time polarized face anti-spoofing (PAAS) detection method uses a on-chip integrated polarization imaging sensor with optimized processing algorithms. Extensive experiments demonstrate the advantages of the PAAS technique to counter diverse face spoofing attacks (print, replay, mask) in uncontrolled indoor and outdoor conditions by learning polarized face images of 33 people. A four-directional polarized face image dataset is released to inspire future applications within biometric anti-spoofing field.

preprint2022arXiv

Generalized Visual Quality Assessment of GAN-Generated Face Images

Recent years have witnessed the dramatically increased interest in face generation with generative adversarial networks (GANs). A number of successful GAN algorithms have been developed to produce vivid face images towards different application scenarios. However, little work has been dedicated to automatic quality assessment of such GAN-generated face images (GFIs), even less have been devoted to generalized and robust quality assessment of GFIs generated with unseen GAN model. Herein, we make the first attempt to study the subjective and objective quality towards generalized quality assessment of GFIs. More specifically, we establish a large-scale database consisting of GFIs from four GAN algorithms, the pseudo labels from image quality assessment (IQA) measures, as well as the human opinion scores via subjective testing. Subsequently, we develop a quality assessment model that is able to deliver accurate quality predictions for GFIs from both available and unseen GAN algorithms based on meta-learning. In particular, to learn shared knowledge from GFIs pairs that are born of limited GAN algorithms, we develop the convolutional block attention (CBA) and facial attributes-based analysis (ABA) modules, ensuring that the learned knowledge tends to be consistent with human visual perception. Extensive experiments exhibit that the proposed model achieves better performance compared with the state-of-the-art IQA models, and is capable of retaining the effectiveness when evaluating GFIs from the unseen GAN algorithms.

preprint2022arXiv

Logarithmic correction to black hole entropy from the nonlocality of quantum gravity

It has been known for many years that the leading correction to the black hole entropy is a logarithmic term, which is universal and closely related to conformal anomaly. A fully consistent analysis of this issue has to take quantum backreactions to the black hole geometry into account. However, it was always unclear how to naturally derive the modified black hole metric especially from an effective action, because the problem refers to the elusive non-locality of quantum gravity. In this paper, we show that this problem can be resolved within an effective field theory (EFT) framework of quantum gravity. Our work suggests that the EFT approach provides a powerful and self-consistent tool for studying the quantum gravitational corrections to black hole geometries and thermodynamics.

preprint2022arXiv

NVUM: Non-Volatile Unbiased Memory for Robust Medical Image Classification

Real-world large-scale medical image analysis (MIA) datasets have three challenges: 1) they contain noisy-labelled samples that affect training convergence and generalisation, 2) they usually have an imbalanced distribution of samples per class, and 3) they normally comprise a multi-label problem, where samples can have multiple diagnoses. Current approaches are commonly trained to solve a subset of those problems, but we are unaware of methods that address the three problems simultaneously. In this paper, we propose a new training module called Non-Volatile Unbiased Memory (NVUM), which non-volatility stores running average of model logits for a new regularization loss on noisy multi-label problem. We further unbias the classification prediction in NVUM update for imbalanced learning problem. We run extensive experiments to evaluate NVUM on new benchmarks proposed by this paper, where training is performed on noisy multi-label imbalanced chest X-ray (CXR) training sets, formed by Chest-Xray14 and CheXpert, and the testing is performed on the clean multi-label CXR datasets OpenI and PadChest. Our method outperforms previous state-of-the-art CXR classifiers and previous methods that can deal with noisy labels on all evaluations. Our code is available at https://github.com/FBLADL/NVUM.

preprint2022arXiv

Perturbed and Strict Mean Teachers for Semi-supervised Semantic Segmentation

Consistency learning using input image, feature, or network perturbations has shown remarkable results in semi-supervised semantic segmentation, but this approach can be seriously affected by inaccurate predictions of unlabelled training images. There are two consequences of these inaccurate predictions: 1) the training based on the "strict" cross-entropy (CE) loss can easily overfit prediction mistakes, leading to confirmation bias; and 2) the perturbations applied to these inaccurate predictions will use potentially erroneous predictions as training signals, degrading consistency learning. In this paper, we address the prediction accuracy problem of consistency learning methods with novel extensions of the mean-teacher (MT) model, which include a new auxiliary teacher, and the replacement of MT's mean square error (MSE) by a stricter confidence-weighted cross-entropy (Conf-CE) loss. The accurate prediction by this model allows us to use a challenging combination of network, input data and feature perturbations to improve the consistency learning generalisation, where the feature perturbations consist of a new adversarial perturbation. Results on public benchmarks show that our approach achieves remarkable improvements over the previous SOTA methods in the field. Our code is available at https://github.com/yyliu01/PS-MT.

preprint2022arXiv

Pixel-wise Energy-biased Abstention Learning for Anomaly Segmentation on Complex Urban Driving Scenes

State-of-the-art (SOTA) anomaly segmentation approaches on complex urban driving scenes explore pixel-wise classification uncertainty learned from outlier exposure, or external reconstruction models. However, previous uncertainty approaches that directly associate high uncertainty to anomaly may sometimes lead to incorrect anomaly predictions, and external reconstruction models tend to be too inefficient for real-time self-driving embedded systems. In this paper, we propose a new anomaly segmentation method, named pixel-wise energy-biased abstention learning (PEBAL), that explores pixel-wise abstention learning (AL) with a model that learns an adaptive pixel-level anomaly class, and an energy-based model (EBM) that learns inlier pixel distribution. More specifically, PEBAL is based on a non-trivial joint training of EBM and AL, where EBM is trained to output high-energy for anomaly pixels (from outlier exposure) and AL is trained such that these high-energy pixels receive adaptive low penalty for being included to the anomaly class. We extensively evaluate PEBAL against the SOTA and show that it achieves the best performance across four benchmarks. Code is available at https://github.com/tianyu0207/PEBAL.

preprint2022arXiv

The topological RN-AdS black holes cannot be overcharged by the new version of gedanken experiment

In this paper, we test the weak cosmic censorship conjecture (WCCC) for n >= 4 dimensional nearly extremal RN-AdS black holes with non-trivial topologies, namely plane and hyperbola, using the new version of gedanken experiment proposed by Sorce and Wald. Provided that the non-electromagnetic part of the stress tensor of matter fields satisfies the null energy condition and the linear stability condition holds, we find that the black holes cannot be overcharged under the second-order perturbation approximation, which includes the self-force and finite-size effects. As a result, we conclude that the violation of Hubeny type never occurs and the WCCC holds for the topological RN-AdS black hole.

preprint2022arXiv

Thermodynamic equilibrium condition and the first law of thermodynamics for charged perfect fluids in electromagnetic and gravitational fields

We provide a proof of the necessary and sufficient condition on the profile of the temperature, chemical potential, and angular velocity for a charged perfect fluid in dynamic equilibrium to be in thermodynamic equilibrium not only in fixed but also in dynamical electromagnetic and gravitational fields. In passing, we also present the corresponding expression for the first law of thermodynamics for such a charged star.

preprint2021arXiv

Detecting, Localising and Classifying Polyps from Colonoscopy Videos using Deep Learning

In this paper, we propose and analyse a system that can automatically detect, localise and classify polyps from colonoscopy videos. The detection of frames with polyps is formulated as a few-shot anomaly classification problem, where the training set is highly imbalanced with the large majority of frames consisting of normal images and a small minority comprising frames with polyps. Colonoscopy videos may contain blurry images and frames displaying feces and water jet sprays to clean the colon -- such frames can mistakenly be detected as anomalies, so we have implemented a classifier to reject these two types of frames before polyp detection takes place. Next, given a frame containing a polyp, our method localises (with a bounding box around the polyp) and classifies it into five different classes. Furthermore, we study a method to improve the reliability and interpretability of the classification result using uncertainty estimation and classification calibration. Classification uncertainty and calibration not only help improve classification accuracy by rejecting low-confidence and high-uncertain results, but can be used by doctors to decide how to decide on the classification of a polyp. All the proposed detection, localisation and classification methods are tested using large data sets and compared with relevant baseline approaches.

preprint2021arXiv

Holographic Abrikosov lattice: vortex matter from black hole

The AdS/CFT correspondence provides a unique way to study the vortex matter phases in superconductors. We solved the nonlinear equations of motion for the Abelain-Higgs theory living on the AdS$_4$ black hole boundary that is dual to a two dimensional strongly coupled type II superconductor at temperature $T$ with a perpendicular external uniform magnetic field $B_0$. We found the associated two critical magnetic fields, $B_{c1}(T)$ and $B_{c2}(T)$. For $B_0 < B_{c1}(T)$ the magnetic field will be expelled out by the superconductor resembling the Meissner effect and the superconductivity will be destroyed when $B_0 > B_{c2}(T)$. The Abrikosov lattice appears in the range $B_{c1}(T) < B_0 < B_{c2}(T)$ including, due to the finite size and boundary effect, several kinds of configurations such as hexagonal, square and slightly irregular square lattices, when the magnetic field is increased. The upper and lower critical fields behave as inverse squares of coherence length and magnetic penetration depth respectively which matches the well known consensus.

preprint2021arXiv

Unsupervised Dual Adversarial Learning for Anomaly Detection in Colonoscopy Video Frames

The automatic detection of frames containing polyps from a colonoscopy video sequence is an important first step for a fully automated colonoscopy analysis tool. Typically, such detection system is built using a large annotated data set of frames with and without polyps, which is expensive to be obtained. In this paper, we introduce a new system that detects frames containing polyps as anomalies from a distribution of frames from exams that do not contain any polyps. The system is trained using a one-class training set consisting of colonoscopy frames without polyps -- such training set is considerably less expensive to obtain, compared to the 2-class data set mentioned above. During inference, the system is only able to reconstruct frames without polyps, and when it tries to reconstruct a frame with polyp, it automatically removes (i.e., photoshop) it from the frame -- the difference between the input and reconstructed frames is used to detect frames with polyps. We name our proposed model as anomaly detection generative adversarial network (ADGAN), comprising a dual GAN with two generators and two discriminators. We show that our proposed approach achieves the state-of-the-art result on this data set, compared with recently proposed anomaly detection systems.

preprint2020arXiv

Dynamical Phase Transition from Nonequilibrium Dynamics of Dark Solitons

By holographic duality, we identify a novel dynamical phase transition which results from the temperature dependence of non-equilibrium dynamics of dark solitons in a superfluid.For a non-equilibrium superfluid system with an initial density of dark solitons, there exists a critical temperature $T_d$,above which the system relaxes to equilibrium by producing sound waves, while below which it goes through an intermediate phase with a finite density of vortex-antivortex pairs. In particular, as $T_d$ is approached from below, the density of vortex pairs scales as $(T_d - T)^γ$ with the critical exponent $γ= 1/2$.

preprint2020arXiv

Few-Shot Anomaly Detection for Polyp Frames from Colonoscopy

Anomaly detection methods generally target the learning of a normal image distribution (i.e., inliers showing healthy cases) and during testing, samples relatively far from the learned distribution are classified as anomalies (i.e., outliers showing disease cases). These approaches tend to be sensitive to outliers that lie relatively close to inliers (e.g., a colonoscopy image with a small polyp). In this paper, we address the inappropriate sensitivity to outliers by also learning from inliers. We propose a new few-shot anomaly detection method based on an encoder trained to maximise the mutual information between feature embeddings and normal images, followed by a few-shot score inference network, trained with a large set of inliers and a substantially smaller set of outliers. We evaluate our proposed method on the clinical problem of detecting frames containing polyps from colonoscopy video sequences, where the training set has 13350 normal images (i.e., without polyps) and less than 100 abnormal images (i.e., with polyps). The results of our proposed model on this data set reveal a state-of-the-art detection result, while the performance based on different number of anomaly samples is relatively stable after approximately 40 abnormal training images.

preprint2020arXiv

Holographic boiling and generalized thermodynamic description beyond local equilibrium

Tuning a very simple two-component holographic superfluid model, we can have a first order phase transition between two superfluid phases in the probe limit. Inspired by the potential landscape discussion, an intuitive physical picture for systems with first order phase transitions is provided. We stress that holography perfectly offers a generalized thermodynamic description of certain strongly coupled systems even out of local equilibrium, which enables us to carefully study domain wall structures of the system under first order phase transitions, either static or in real time dynamics. We numerically construct the 1D domain wall configuration and compute the surface tension of the domain wall from its generalized grand potential. We also numerically simulate the real time dynamics of a 2D bubble nucleation process (holographic boiling). The surface tension of the 1D domain wall nicely matches the final state of the 2D bubble nucleation process when the bubble radius is large enough.

preprint2020arXiv

Holographic Superfluid Solitons with Backreaction

Solitons are important nonperturbative excitations in superfluids. For holographic superfluids, we numerically construct dark solitons that have the symmetry-restored phase at their core. A central point is that we include the gravitational back-reaction of the matter fields, which becomes important at low temperatures. We study in detail the properties of these solitons under variation of the back-reaction strength via tuning the gravitational constant. In particular, the depletion fraction of the particle number density at the core of the solitons is carefully investigated. In agreement with the probe-limit analysis, the depletion fraction shows the same qualitative behavior as in Bogoliubov-de Gennes (BdG) theory, even if the back-reaction is included. We find that the depletion decreases with increasing back-reaction strength. Moreover, the inclusion of back-reaction enables us to obtain the effective energy density of solitons within holography, which together with an evaluation of the surface tension leads to a simple physical explanation for the snake instability of dark solitons.

preprint2020arXiv

Hybrid Multiple Attention Network for Semantic Segmentation in Aerial Images

Semantic segmentation in very high resolution (VHR) aerial images is one of the most challenging tasks in remote sensing image understanding. Most of the current approaches are based on deep convolutional neural networks (DCNNs). However, standard convolution with local receptive fields fails in modeling global dependencies. Prior researches have indicated that attention-based methods can capture long-range dependencies and further reconstruct the feature maps for better representation. Nevertheless, limited by the mere perspective of spacial and channel attention and huge computation complexity of self-attention mechanism, it is unlikely to model the effective semantic interdependencies between each pixel-pair of remote sensing data of complex spectra. In this work, we propose a novel attention-based framework named Hybrid Multiple Attention Network (HMANet) to adaptively capture global correlations from the perspective of space, channel and category in a more effective and efficient manner. Concretely, a class augmented attention (CAA) module embedded with a class channel attention (CCA) module can be used to compute category-based correlation and recalibrate the class-level information. Additionally, we introduce a simple yet effective region shuffle attention (RSA) module to reduce feature redundant and improve the efficiency of self-attention mechanism via region-wise representations. Extensive experimental results on the ISPRS Vaihingen and Potsdam benchmark demonstrate the effectiveness and efficiency of our HMANet over other state-of-the-art methods.

preprint2020arXiv

Large-area printing of ferroelectric surface and super-domains for efficient solar water splitting

Surface electronic structures of the photoelectrodes determine the activity and efficiency of the photoelectrochemical water splitting, but the controls of their surface structures and interfacial chemical reactions remain challenging. Here, we use ferroelectric BiFeO3 as a model system to demonstrate an efficient and controllable water splitting reaction by large-area constructing the hydroxyls-bonded surface. The up-shift of band edge positions at this surface enables and enhances the interfacial holes and electrons transfer through the hydroxyl-active-sites, leading to simultaneously enhanced oxygen and hydrogen evolutions. Furthermore, printing of ferroelectric super-domains with microscale checkboard up/down electric fields separates the distribution of reduction/oxidation catalytic sites, enhancing the charge separation and giving rise to an order of magnitude increase of the photocurrent. This large-area printable ferroelectric surface and super-domains offer an alternative platform for controllable and high-efficient photocatalysis.

preprint2020arXiv

On NOMA-Based mmWave Communications

Non-orthogonal multiple access (NOMA) and millimeter-wave (mmWave) communication are two promising techniques to increase the system capacity in the fifth-generation (5G) mobile network. The former can achieve high spectral efficiency by modulating the information in power domain and the latter can provide extremely large spectrum resources. Fluctuating two-ray (FTR) channel model has already been proved to accurately agree with the small-scale fading effects in mmWave communications in experiments. In this paper, the performance of NOMA-based communications over FTR channels in mmWave communication systems is investigated in terms of outage probability (OP) and ergodic capacity (EC). Specifically, we consider the scenario that one base station (BS) transmits signals to two users simultaneously under NOMA scheme. The BS and users are all equipped with a single antenna. Two power allocation strategies are considered: the first one is a general (fixed) power allocation scheme under which we derive the OP and EC of NOMA users in closed form; the other one is an optimal power allocation scheme that can achieve the maximum sum rate for the whole system. Under the second scheme, not only the closed-form OP and EC but also the upper and lower bounds of EC are derived. Furthermore, we also derive the asymptotic expression for the OP in high average SNR region to investigate the diversity order under these two schemes. Finally, we show the correctness and accuracy of our derived expressions by Monte-Carlo simulation.

preprint2020arXiv

Semantic Graph Convolutional Networks for 3D Human Pose Regression

In this paper, we study the problem of learning Graph Convolutional Networks (GCNs) for regression. Current architectures of GCNs are limited to the small receptive field of convolution filters and shared transformation matrix for each node. To address these limitations, we propose Semantic Graph Convolutional Networks (SemGCN), a novel neural network architecture that operates on regression tasks with graph-structured data. SemGCN learns to capture semantic information such as local and global node relationships, which is not explicitly represented in the graph. These semantic relationships can be learned through end-to-end training from the ground truth without additional supervision or hand-crafted rules. We further investigate applying SemGCN to 3D human pose regression. Our formulation is intuitive and sufficient since both 2D and 3D human poses can be represented as a structured graph encoding the relationships between joints in the skeleton of a human body. We carry out comprehensive studies to validate our method. The results prove that SemGCN outperforms state of the art while using 90% fewer parameters.

preprint2019arXiv

Experimental Observation of Equilibrium and Dynamical Quantum Phase Transitions via Out-of-Time-Ordered Correlators

The out-of-time-ordered correlators (OTOC) have been established as a fundamental concept for quantifying quantum information scrambling and diagnosing quantum chaotic behavior. Recently, it was theoretically proposed that the OTOC can be used as an order parameter to dynamically detect both equilibrium quantum phase transitions (EQPTs) and dynamical quantum phase transitions (DQPTs) in one-dimensional many-body systems. Here we report the first experimental observation of EQPTs and DQPTs in a quantum spin chain via quench dynamics of OTOC on a nuclear magnetic resonance quantum simulator. We observe that the quench dynamics of both the order parameter and the two-body correlation function cannot detect the DQPTs, but the OTOC can unambiguously detect the DQPTs. Moreover, we demonstrate that the long-time average value of the OTOC in quantum quench signals the equilibrium quantum critical point and ordered quantum phases, thus one can measure the EQPTs from the non-equilibrium quantum quench dynamics. Our experiment paves a way for experimentally investigating DQPTs through OTOCs and for studying the EQPTs through the non-equilibrium quantum quench dynamics with quantum simulators.

preprint2016arXiv

Dynamical stability of the Holographic System with Two Competing Orders

We investigate the dynamical stability of the holographic system with two order parameters, which exhibits competition and coexistence of condensations. In the linear regime, we have developed the gauge dependent formalism to calculate the quasi-normal modes by gauge fixing, which turns out be considerably convenient. Furthermore, by giving different Gaussian wave packets as perturbations at the initial time, we numerically evolve the full nonlinear system until it arrives at the final equilibrium state. Our results show that the dynamical stability is consistent with the thermodynamical stability. Interestingly, the dynamical evolution, as well as the quasi-normal modes, shows that the relaxation time of this model is generically much longer than the simplest holographic system. We also find that the late time behavior can be well captured by the lowest lying quasi-normal modes except for the non-vanishing order towards the single ordered phase. To our knowledge, this exception is the first counter example to the general belief that the late time behavior towards a final stable state can be captured by the lowest lying quasi-normal modes. In particular, a double relation is found for this exception in certain cases.

preprint2016arXiv

Hadronic production of $D(2550)$, $D^(2600)$, $D(2750)$, $D^_1(2760)$ and $D^*_3(2760)$

Hadronic decays of radially excited $2D$ $D(2^3D_1)$, $D(2^3D_3)$, $D(2D_2)$ and $D(2D^\prime_2)$ have been studied in a $^3P_0$ model. All OZI-allowed decay channels of these $2D$ $D$ resonances have been given, and relevant decay widths have been calculated. $D(2550)$, $D^*(2600)$, $D(2750)$, $D^*_1(2760)$ and $D^*_3(2760)$ can be produced in hadronic decays of $D(2^3D_1)$, $D(2^3D_3)$, $D(2D_2)$ and $D(2D^\prime_2)$. In different assignments, hadronic decay widths and some relevant ratios from the $2D$ $D$ resonances to $D(2550)$, $D^*(2600)$, $D(2750)$, $D^*_1(2760)$ or $D^*_3(2760)$ final states have been predicted, which may provide some more information to identify these resonances in forthcoming experiments.

preprint2016arXiv

In Situ Simultaneous Measuring Forces Acted on Individual Legs of Water Striders According to Archimedes' Principle

The supporting forces of all the legs have been simultaneously measured through a natural phenomenon inspired shadow method, by capturing water strider leg shadows to calculate the expelled water volume and the equivalent floating forces according to Archimedes' principle, with a sensitivity up to nN~pN/pixel. The method was verified by comparing to electronic balance to weight water striders. The supporting force acted on legs was found to linearly proportional to its shadow area, which geometry clearly indicated the hydrophobicity of legs. The pressed depth of legs, vertical weight focus position change and body pitch angle during leg refreshing, sculling and jumping forward of water striders have been achieved with resolutions of 5um/pixel, 2 um/pixel, and 0.02 degree, respectively, which is difficult for general imaging technologies. The shadow method was also developed into a force measuring device and characterized the adhesion force of a hair/polymer surface contact in a few uN with a 0.3 nN/pixel resolution.

preprint2016arXiv

Linear and quadratic in temperature resistivity from holography

We present a new black hole solution in the asymptotic Lifshitz spacetime with a hyperscaling violating factor. A novel computational method is introduced to compute the DC thermoelectric conductivities analytically. We find that both the linear-T and quadratic-T contributions to the resistivity can be realized, indicating that a more detailed comparison with experimental phenomenology can be performed in this scenario.

preprint2016arXiv

Modave Lectures on Applied AdS/CFT with Numerics

These lecture notes are intended to serve as an introduction to applied AdS/CFT with numerics for an audience of graduate students and others with little background in the subject. The presentation begins with a poor man's review of current status of quantum gravity, where AdS/CFT correspondence is believed to be the well formulated quantum gravity in the anti-de Sitter space. Then we present the basic ingredients in applied AdS/CFT and introduce the relevant numerics for solving differential equations into which the bulk dynamics collapses. To demonstrate how to apply AdS/CFT with numerics, we take the zero temperature holographic superfluid as a concrete example for case study. In passing, we also present some new results, which include the numerical evidence as well as an elegant analytic proof for the equality between the superfluid density and particle density, namely $ρ_s=ρ$, and the saturation to the predicted value $\frac{1}{\sqrt{2}}$ by conformal field theory for the sound speed in the large chemical potential limit.

preprint2016arXiv

Nonlinear Transport in a Two Dimensional Holographic Superconductor

The problem of nonlinear transport in a two dimensional superconductor with an applied oscillating electric field is solved by the holographic method. The complex conductivity can be computed from the dynamics of the current for both near- and non-equilibrium regimes. The limit of weak electric field corresponds to the near equilibrium superconducting regime, where the charge response is linear and the conductivity develops a gap determined by the condensate. A larger electric field drives the system into a superconducting non-equilibrium steady state, where the nonlinear conductivity is quadratic with respect to the electric field. Keeping increasing the amplitude of applied electric field results in a far-from-equilibrium non-superconducting steady state with a universal linear conductivity of one. In lower temperature regime we also find chaotic behavior of superconducting gap, which results in a non-monotonic field dependent nonlinear conductivity.

preprint2016arXiv

Note on Zero Temperature Holographic Superfluids

In this note, we have addressed various issues on zero temperature holographic superfluids. First, inspired by our numerical evidence for the equality between the superfluid density and particle density, we provide an elegant analytic proof for this equality by a boost trick. Second, using not only the frequency domain analysis but also the time domain analysis from numerical relativity, we identify the hydrodynamic normal modes and calculate out the sound speed, which is shown to increase with the chemical potential and saturate to the value predicted by the conformal field theory in the large chemical potential limit. Third, the generic non-thermalization is demonstrated by the fully non-linear time evolution from a non-equilibrium state for our zero temperature holographic superfluid. Furthermore, a conserved Noether charge is proposed in support of this behavior.

preprint2016arXiv

Towards Quantum Turbulence in Finite Temperature Bose-Einstein Condensates

Motivated by the various indications that holographic superfluid is BCS like at the standard quantization but BEC like at the alternative quantization, we have implemented the alternative quantization in the dynamical holographic superfluid for the first time. With this accomplishment, we further initiate the detailed investigation of quantum turbulence in finite temperature BEC by a long time stable numerical simulation of bulk dynamics, which includes the two body decay of vortex number caused by vortex pair annihilation, the onset of superfluid turbulence signaled by Kolmogorov scaling law, and a direct energy cascade demonstrated by injecting energy to the turbulent superfluid. All of these results share the same patterns as the holographic superfluid at the standard quantization, thus suggest that these should be universal features for quantum turbulence at temperatures order of the critical temperature.

preprint2016arXiv

Zero Temperature Holographic Superfluids with Two Competing Orders

We initiate the investigation of the zero temperature holographic superfluids with two competing orders, where besides the vacuum phase, two one band superfluid phases, the coexistent superfluid phase has also been found in the AdS soliton background for the first time. We construct the complete phase diagram in the $e-μ$ plane by numerics, which is consistent with our qualitative analysis. Furthermore, we calculate the corresponding optical conductivity and sound speed by the linear response theory. The onset of pole of optical conductivity at $ω=0$ indicates that the spontaneous breaking phase always represents the superfluid phase, and the residue of pole is increased with the chemical potential, which is consistent with the fact that the particle density is essentially the superfluid density for zero temperature superfluids. In addition, the resulting sound speed demonstrates the non-smoothness at the critical points as the order parameter of condensate, which indicates that the phase transitions can also be identified by the behavior of sound speed. Moreover, as expected from the boundary conformal field theory, the sound speed saturates to $\frac{1}{\sqrt{2}}$ at the large chemical potential limit for our two band holographic superfluid model.

preprint2015arXiv

From Petrov-Einstein-Dilaton-Axion to Navier-Stokes equation in anisotropic model

In this paper we generalize the previous works to the case that the near-horizon dynamics of the Einstein-Dilaton-Axion theory can be governed by the incompressible Navier-Stokes equation via imposing the Petrov-like boundary condition on hypersurfaces in the non-relativistic and near-horizon limit. The dynamical shear viscosity $η$ of such dual horizon fluid in our scenario, which isotropically saturates the Kovtun-Son-Starinet (KSS) bound, is independent of both the dilaton field and axion field in that limit.

preprint2015arXiv

Holographic Interpretation of Acoustic Black Holes

With the attempt to find the holographic description of usual acoustic black holes in fluid, we construct an acoustic black hole formed in the $d$-dimensional fluid located at the timelike cutoff surface of a neutral black brane in asymptotically AdS$_{d+1}$ spacetime, the bulk gravitational dual of the acoustic black hole is presented at first order of the hydrodynamic fluctuation. Moreover, the Hawking-like temperature of the acoustic black hole horizon is showed to be connected to the Hawking temperature of the real AdS black brane in the bulk, and the duality between the phonon scattering in the acoustic black hole and the sound channel quasinormal mode propagating in the bulk perturbed AdS black brane is extracted. We thus point out that, the acoustic black hole appeared in fluid, which was originally proposed as an analogous model to simulate Hawking radiation of the real black hole, is not merely an analogy, it can indeed be used to describe specific properties of the real AdS black holes, in the spirits of the fluid/gravity duality.

preprint2015arXiv

Holographic Thermal Relaxation in Superfluid Turbulence

Holographic duality provides a first-principles approach to investigate real time processes in quantum many-body systems, in particular at finite temperature and far-from-equilibrium. We use this approach to study the dynamical evolution of vortex number in a two-dimensional (2D) turbulent superfluid through numerically solving its gravity dual. We find that the temporal evolution of the vortex number can be well fit statistically by two-body decay due to the vortex pair annihilation featured relaxation process, thus confirm the previous suspicion based on the experimental data for turbulent superfluid in highly oblate Bose-Einstein condensates. Furthermore, the decay rate near the critical temperature is in good agreement with the recently developed effective theory of 2D superfluid turbulence.

preprint2015arXiv

The Quasi-normal Modes of Charged Scalar Fields in Kerr-Newman black hole and Its Geometric Interpretation

It is well-known that there is a geometric correspondence between high-frequency quasi-normal modes (QNMs) and null geodesics (spherical photon orbits). In this paper, we generalize such correspondence to charged scalar field in Kerr-Newman space-time. In our case, the particle and black hole are all charged, so one should consider non-geodesic orbits. Using the WKB approximation, we find that the real part of quasi-normal frequency corresponds to the orbits frequency, the imaginary part of the frequency corresponds to the Lyapunov exponent of these orbits and the eigenvalue of angular equation corresponds to carter constant. From the properties of the imaginary part of quasi-normal frequency of charged massless scalar field, we can still find that the QNMs of charged massless scalar field possess the zero damping modes in extreme Kerr-Newman spacetime under certain condition which has been fixed in this paper.

preprint2015arXiv

Time domain analysis of superradiant instability for the charged stringy black hole-mirror system

It has been proved that the charged stringy black holes are stable under the perturbations of massive charged scalar fields. However, superradiant instability can be generated by adding the mirror-like boundary condition to the composed system of charged stringy black hole and scalar field. The unstable boxed quasinormal modes have been calculated by using both analytical and numerical method. In this paper, we further provide a time domain analysis by performing a long time evolution of charged scalar field configuration in the background of the charged stringy black hole with the mirror-like boundary condition imposed. We have used the ingoing Eddington-Finkelstein coordinates to derive the evolution equation, and adopted Pseudo-spectral method and the forth-order Runge-Kutta method to evolve the scalar field with the initial Gaussian wave packet. It is shown by our numerical scheme that Fourier transforming the evolution data coincides well with the unstable modes computed from frequency domain analysis. The existence of the rapid growth mode makes the charged stringy black hole a good test ground to study the nonlinear development of superradiant instability.

preprint2015arXiv

Wavelet-based fast time-resolved magnetic sensing with electronic spins in diamond

Time-resolved magnetic sensing is of great importance from fundamental studies to applications in physical and biological sciences. Recently the nitrogen-vacancy (NV) defect center in diamond has been developed as a promising sensor of magnetic field under ambient conditions. However the methods to reconstruct time-resolved magnetic field with high sensitivity are not yet fully developed. Here, we propose and demonstrate a novel sensing method based on spin echo, and Haar wavelet transform. Our method is exponentially faster in reconstructing time-resolved magnetic field with comparable sensitivity over existing methods. Further, the wavelet's unique features enable our method to extract information from the whole signal with only part of the measuring sequences. We then explore this feature for a fast detection of simulated nerve impulses. These results will be useful to time-resolved magnetic sensing with quantum probes at nano-scales.

preprint2014arXiv

Bulk Viscosity of dual Fluid at Finite Cutoff Surface via Gravity/Fluid correspondence in Einstein-Maxwell Gravity

Based on the previous paper arXiv:1207.5309, we investigate the possibility to find out the bulk viscosity of dual fluid at the finite cutoff surface via gravity/fluid correspondence in Einstein-Maxwell gravity. We find that if we adopt new conditions to fix the undetermined parameters contained in the stress tensor and charged current of the dual fluid, two new terms appear in the stress tensor of the dual fluid. One new term is related to the bulk viscosity term, while the other can be related to the perturbation of energy density. In addition, since the parameters contained in the charged current are the same, the charged current is not changed.

preprint2014arXiv

Doubled Conformal Compactification

We use Weyl transformations between the Minkowski spacetime and dS/AdS spacetime to show that one cannot well define the electrodynamics globally on the ordinary conformal compactification of the Minkowski spacetime (or dS/AdS spacetime), where the electromagnetic field has a sign factor (and thus is discountinuous) at the light cone. This problem is intuitively and clearly shown by the Penrose diagrams, from which one may find the remedy without too much difficulty. We use the Minkowski and dS spacetimes together to cover the compactified space, which in fact leads to the doubled conformal compactification. On this doubled conformal compactification, we obtain the globally well-defined electrodynamics.

preprint2014arXiv

Entropy of isolated horizon from surface term of gravitational action

Starting from the surface term of gravitational action, one can construct a Virasoro algebra with central extension, with which the horizon entropy can be derived by using Cardy formula. This approach gives a new routine to calculate and interpret the horizon entropy. In this paper, we generalize this approach to a more general case, the isolated horizon, which contains non-stationary spacetimes beyond stationary ones. By imposing appropriate boundary conditions near the horizon, the full set of diffeomorphism is restricted to a subset where the corresponding Noether charges form a Virasoro algebra with central extension. Then by using the Cardy formula, we can derive the entropy of the isolated horizon.

preprint2014arXiv

Holographic Entropy Production

The suspicion that gravity is holographic has been supported mainly by a variety of specific examples from string theory. In this paper, we propose that such a holography can actually be observed in the context of Einstein's gravity and at least a class of generalized gravitational theories, based on a definite holographic principle where neither is the bulk space-time required to be asymptotically AdS nor the boundary to be located at conformal infinity, echoing Wilson's formulation of quantum field theory. After showing the general equilibrium thermodynamics from the corresponding holographic dictionary, in particular, we provide a rather general proof of the equality between the entropy production on the boundary and the increase of black hole entropy in the bulk, which can be regarded as strong support to this holographic principle. The entropy production in the familiar holographic superconductors/superfluids is investigated as an important example, where the role played by the holographic renormalization is explained.

preprint2014arXiv

The Petrov-like boundary condition at finite cutoff surface in Gravity/Fluid duality

Previously it has been shown that imposing a Petrov-like boundary condition on a hypersurface may reduce the Einstein equation to the incompressible Navier-Stokes equation, but all these correspondences are established in the near horizon limit. In this note, we remark that this strategy can be extended to an arbitrary finite cutoff surface which is spatially flat, and the Navier-Stokes equation is obtained by employing a non-relativistic long-wavelength limit.

preprint2014arXiv

The Universal Property of the Entropy Sum of Black Holes in All Dimensions

It is proposed by Cvetic et al [Phys. Rev. Lett. 106 (2011) 121301] that the product of all horizon areas for general rotating multi-change black holes has universal expressions independent of the mass. When we consider the product of all horizon entropies, however, the mass will be present in some cases, while another new universal property [JHEP 1401 (2014) 031] is preserved, which is more general and says that the sum of all horizon entropies depends only on the coupling constants of the theory and the topology of the black hole. The property has been studied in limited dimensions and the generalization in arbitrary dimensions is not straight-forward. In this Letter, we prove a useful formula, which makes it possible to investigate this conjectured universality in arbitrary dimensions for the maximally symmetric black holes in general Lovelock gravity and $f(R)$ gravity. We also propose an approach to compute the entropy sum of general Kerr-(anti-)de-Sitter black holes in arbitrary dimensions. In all these cases, we prove that the entropy sum only depends on the coupling constants and the topology of the black hole.

preprint2013arXiv

Fluid/Gravity Correspondence For General Non-rotating Black Holes

In this paper, we investigate the fluid/gravity correspondence in spacetime with general non-rotating weakly isolated horizon. With the help of Petrov-like boundary condition and large mean curvature limit, we show that the dual hydrodynamical system is described by a generalized forced incompressible Navier-Stocks equation. Specially, for stationary black holes or those spacetime with some asymptotically stationary conditions, such a system reduces to a standard forced Navier-Stocks system.

preprint2013arXiv

Generalized Kerr/CFT correspondence with electromagnetic field

The electrovac axisymmetric extreme isolated horizon/CFT correspondence is considered. By expansion techniques under the Bondi-like coordinates, it is proved that the near horizon geometry of electrovac axisymmetric extreme isolated horizon is unique. Furthermore, explicit coordinate transformation between the Bondi-like coordinates and the Poincare-type coordinates for the near horizon metric of the extreme Kerr-Newmann spacetime is found. Based on these analyses and the thermodynamics of the isolated horizon, then, the Kerr/CFT correspondence is generalized to nonstationary extreme black holes with electromagnetic fields.

preprint2013arXiv

Periodically Driven Holographic Superconductor

As a first step towards our holographic investigation of the far-from-equilibrium physics of periodically driven systems at strong coupling, we explore the real time dynamics of holographic superconductor driven by a monochromatically alternating electric field with various frequencies. As a result, our holographic superconductor is driven to the final oscillating state, where the condensate is suppressed and the oscillation frequency is controlled by twice of the driving frequency. In particular, in the large frequency limit, the three distinct channels towards the final steady state are found, namely under damped to superconducting phase, over damped to superconducting and normal phase, which can be captured essentially by the low lying spectrum of quasi-normal modes in the time averaged approximation, reminiscent of the effective field theory perspective.

preprint2013arXiv

Poor man's holography: How far can it go?

One of the most exciting things in recent theoretical physics is the suspicion that gravity may be holographic, dual to some sort of quantum field theory living on the boundary with one less dimension. Such a suspicion has been supported mainly by a variety of specific examples from string theory. This paper is intended to purport the holographic gravity from a different perspective. Namely we propose that such a holography can actually be observed within the context of Einstein's gravity, where neither is spacetime required to be asymptotically AdS nor the boundary to be located at conformal infinity. We show that our holography works remarkably well at least at the level of thermodynamics and hydrodynamics. In particular, a perfect matching between the bulk gravity and boundary system is found not only for the equilibrium variation but also for the non-equilibrium entropy production, where a method of conserved current is seen to be efficient in relating the black hole perturbation in the bulk gravity and the non-equilibrium thermodynamics on the boundary.

preprint2012arXiv

A discussion on "generality of shear thickening in dense suspensions"

In a recent Nature Materials article, Brown et al. reported a generality of shear thickening in dense suspensions and demonstrated that shear thickening can be masked by a yield stress and can be recovered when the yield stress is decreased to below a threshold. However, the generality of the shear thickening reported in the article may not be necessary true when a high electric/magnetic field is applied on an ER/MR fluid. Shear thickening of ER fluid and MR fluid under high electric/magnetic fields at low shear rates, indicating an obvious phase change inside the dense suspensions has been observed.

preprint2012arXiv

Fluid/gravity duality with Petrov-like boundary condition in a spacetime with a cosmological constant

Recently it has been shown that imposing Petrov type I condition on the boundary may reduce the Einstein's equation to the Navier-Stokes equation in the non-relativistic and near-horizon limit. In this paper we extend this framework to a spacetime with a cosmological constant. By explicit construction we show that the Navier-Stokes equation can be derived from both black brane background and spatially curved spacetime. We also conjecture that imposing Petrov type I condition on the boundary should be equivalent to the conventional method using the hydrodynamical expansion of the metric in the near horizon limit.

preprint2012arXiv

Geometries with the second Poincaré symmetry

The second Poincaré kinematical group serves as one of new ones in addition to the known possible kinematics. The geometries with the second Poincaré symmetry is presented and their properties are analyzed. On the geometries, the new mechanics based on the principle of relativity with two universal constants $(c,l)$ can be established.

preprint2012arXiv

Holographic RG flows and transport coefficients in Einstein-Gauss-Bonnet-Maxwell theory

We apply the membrane paradigm and the holographic Wilsonian approach to the Einstein-Gauss-Bonnet-Maxwell theory. The transport coefficients for a quark-gluon plasma living on the cutoff surface are derived in a spacetime of charged black brane. Because of the mixing of the Gauss-Bonnet coupling and the Maxwell fields, the vector modes/shear modes of the metric and Maxwell fluctuations turn out to be very difficult to decouple. We firstly evaluate the AC conductivity at a finite cutoff surface by solving the equation of motion numerically, then manage to derive the radial flow of DC conductivity with the use of the Kubo formula. It turns out that our analytical results match the numerical data in low frequency limit very well. The diffusion constant $D(u_c)$ is also derived in a long wavelength expansion limit. We find it depends on the Gauss-Bonnet coupling as well as the position of the cutoff surface.

preprint2012arXiv

Incompressible Navier-Stokes Equation from Einstein-Maxwell and Gauss-Bonnet-Maxwell Theories

The dual fluid description for a general cutoff surface at radius r=r_c outside the horizon in the charged AdS black brane bulk space-time is investigated, first in the Einstein-Maxwell theory. Under the non-relativistic long-wavelength expansion with parameter ε, the coupled Einstein-Maxwell equations are solved up to O(ε^2). The incompressible Navier-Stokes equation with external force density is obtained as the constraint equation at the cutoff surface. For non-extremal black brane, the viscosity of the dual fluid is determined by the regularity of the metric fluctuation at the horizon, whose ratio to entropy density η/s is independent of both the cutoff r_c and the black brane charge. Then, we extend our discussion to the Gauss-Bonnet-Maxwell case, where the incompressible Navier-Stokes equation with external force density is also obtained at a general cutoff surface. In this case, it turns out that the ratio η/s is independent of the cutoff r_c but dependent on the charge density of the black brane.

preprint2012arXiv

Magnetohydrodynamics from gravity

Imposing the Petrov-like boundary condition on the hypersurface at finite cutoff, we derive the hydrodynamic equation on the hypersurface from the bulk Einstein equation with electromagnetic field in the near horizon limit. We first get the general framework for spacetime with matter field, and then derive the incompressible Navier-Stokes equations for black holes with electric charge and magnetic charge respectively. Especially, in the magnetic case, the standard magnetohydrodynamic equations will arise due to the existence of the background electromagnetic field on the hypersurface.

preprint2012arXiv

New Geometry with All Killing Vectors Spanning the Poincaré Algebra

The new 4D geometry whose Killing vectors span the Poincaré algebra is presented and its structure is analyzed. The new geometry can be regarded as the Poincaré-invariant solution of the degenerate extension of the vacuum Einstein field equations with a negative cosmological constant and provides a static cosmological space-time with a Lobachevsky space. The motion of free particles in the space-time is discussed.

preprint2011arXiv

Critical Phenomena and Thermodynamic Geometry of RN-AdS Black Holes

The phase transition of Reissner-Nordström black holes in $(n+1)$-dimensional anti-de Sitter spacetime is studied in details using the thermodynamic analogy between a RN-AdS black hole and a van der Waals liquid gas system. We first investigate critical phenomena of the RN-AdS black hole. The critical exponents of relevant thermodynamical quantities are evaluated. We find identical exponents for a RN-AdS black hole and a Van der Waals liquid gas system. This suggests a possible universality in the phase transitions of these systems. We finally study the thermodynamic behavior using the equilibrium thermodynamic state space geometry and find that the scalar curvature diverges exactly at the van der Waals-like critical point where the heat capacity at constant charge of the black hole diverges.

preprint2011arXiv

Dynamics of Gravity as Thermodynamics on the Spherical Holographic Screen

The dynamics of general Lovelock gravity, viewed on an arbitrary spherically symmetric surface as a holographic screen, is recast as the form of some generalized first law of thermodynamics on the screen. From this observation together with other two distinct aspects, where exactly the same temperature and entropy on the screen arise, it is argued that the thermodynamic interpretation of gravity is physically meaningful not only on the horizon, but also on a general spherically symmetric screen.

preprint2011arXiv

From Petrov-Einstein to Navier-Stokes in Spatially Curved Spacetime

We generalize the framework in arXiv:1104.5502 to the case that an embedding may have a nonvanishing intrinsic curvature. Directly employing the Brown-York stress tensor as the fundamental variables, we study the effect of finite perturbations of the extrinsic curvature while keeping the intrinsic metric fixed. We show that imposing a Petrov type I condition on the hypersurface geometry may reduce to the incompressible Navier-Stokes equation for a fluid moving in spatially curved spacetime in the near-horizon limit.

preprint2011arXiv

Some Peculiarities of Newton-Hooke Space-Times

Newton-Hooke space-times are the non-relativistic limit of (anti-)de Sitter space-times. We investigate some peculiar facts about the Newton-Hooke space-times, among which the "extraordinary Newton-Hooke quantum mechanics" and the "anomalous Newton-Hooke space-times" are discussed in detail. Analysis on the Lagrangian/action formalism is performed in the discussion of the Newton-Hooke quantum mechanics, where the path integral point of view plays an important role, and the physically measurable density of probability is clarified.

preprint2010arXiv

Geometries for Possible Kinematics

The algebras for all possible Lorentzian and Euclidean kinematics with $\frak{so}(3)$ isotropy except static ones are re-classified. The geometries for algebras are presented by contraction approach. The relations among the geometries are revealed. Almost all geometries fall into pairs. There exists $t \leftrightarrow 1/(ν^2t)$ correspondence in each pair. In the viewpoint of differential geometry, there are only 9 geometries, which have right signature and geometrical spatial isotropy. They are 3 relativistic geometries, 3 absolute-time geometries, and 3 absolute-space geometries.

preprint2010arXiv

Reversible shear thickening at low shear rates of electrorheological fluids under electric fields

Shear thickening is a phenomenon of significant viscosity increase of colloidal suspensions. While electrorheological (ER) fluids can be turned into a solid-like material by applying an electric field, their shear strength is widely represented by the attractive electrostatic interaction between ER particles. By shearing ER fluids between two concentric cylinders, we show a reversible shear thickening of ER fluids above a low critical shear rate (<1 s-1) and a high critical electric field strength (>100 V/mm), which could be characterized by a modified Mason number. Shear thickening and electrostatic particle interaction-induced inter-particle friction forces is considered to be the real origin of the high shear strength of ER fluids, while the applied electric field controls the extent of shear thickening. The electric field-controlled reversible shear thickening has implications for high-performance ER/magnetorheological (MR) fluid design, clutch fluids with high friction forces triggered by applying local electric field, other field-responsive materials and intelligent systems.

preprint2010arXiv

Thermodynamics of Black Holes from Equipartition of Energy and Holography

A gravitational potential in the relativistic case is introduced as an alternative to Wald's potential used by Verlinde, which reproduces the familiar entropy/area relation S=A/4 (in the natural units) when Verlinde's idea is applied to the black hole case. Upon using the equipartition rule, the correct form of the Komar mass (energy) can also be obtained, which leads to the Einstein equations. It is explicitly shown that our entropy formula agrees with Verlinde's entropy variation formula in spherical cases. The stationary space-times, especially the Kerr-Newman black hole, are then discussed, where it is shown that the equipartition rule involves the reduced mass, instead of the ADM mass, on the horizon of the black hole.

preprint2004arXiv

Drinfeld-Manin Instanton and Its Noncommutative Generalization

The Drinfeld-Manin construction of U(N) instanton is reformulated in the ADHM formulism, which gives explicit general solutions of the ADHM constraints for U(N) (N>=2k-1) k-instantons. For the N<2k-1 case, implicit results are given systematically as further constraints, which can be used to the collective coordinate integral. We find that this formulism can be easily generalized to the noncommutative case, where the explicit solutions are as well obtained.

Yu Tian

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75 published item(s)

Skills-Coach: A Self-Evolving Skill Optimizer via Training-Free GRPO

Quench Dynamics in Holographic First-Order Phase Transition

Spreading and Structural Balance on Signed Networks

Extended black hole thermodynamics from extended Iyer-Wald formalism

Knowledge Distillation to Ensemble Global and Interpretable Prototype-Based Mammogram Classification Models

Protected Transverse Electric Waves in Topological Dielectric Waveguides

ACPL: Anti-curriculum Pseudo-labelling for Semi-supervised Medical Image Classification

Artifact-Tolerant Clustering-Guided Contrastive Embedding Learning for Ophthalmic Images

Coarse-to-Fine: Hierarchical Multi-task Learning for Natural Language Understanding

Collapsing dust thin shells in Einstein-Gauss-Bonnet gravity

Contrastive Transformer-based Multiple Instance Learning for Weakly Supervised Polyp Frame Detection

Critical phenomena in dynamical scalarization of charged black hole

Deep One-Class Classification via Interpolated Gaussian Descriptor

Design of a Biomimetic Tactile Sensor for Material Classification

Experimental Realization of a Quantum Refrigerator Driven by Indefinite Causal Orders

Face Anti-Spoofing by Learning Polarization Cues in a Real-World Scenario

Generalized Visual Quality Assessment of GAN-Generated Face Images

Logarithmic correction to black hole entropy from the nonlocality of quantum gravity

NVUM: Non-Volatile Unbiased Memory for Robust Medical Image Classification

Perturbed and Strict Mean Teachers for Semi-supervised Semantic Segmentation

Pixel-wise Energy-biased Abstention Learning for Anomaly Segmentation on Complex Urban Driving Scenes

The topological RN-AdS black holes cannot be overcharged by the new version of gedanken experiment

Thermodynamic equilibrium condition and the first law of thermodynamics for charged perfect fluids in electromagnetic and gravitational fields

Detecting, Localising and Classifying Polyps from Colonoscopy Videos using Deep Learning

Holographic Abrikosov lattice: vortex matter from black hole

Unsupervised Dual Adversarial Learning for Anomaly Detection in Colonoscopy Video Frames

Dynamical Phase Transition from Nonequilibrium Dynamics of Dark Solitons

Few-Shot Anomaly Detection for Polyp Frames from Colonoscopy

Holographic boiling and generalized thermodynamic description beyond local equilibrium

Holographic Superfluid Solitons with Backreaction

Hybrid Multiple Attention Network for Semantic Segmentation in Aerial Images

Large-area printing of ferroelectric surface and super-domains for efficient solar water splitting

On NOMA-Based mmWave Communications

Semantic Graph Convolutional Networks for 3D Human Pose Regression

Experimental Observation of Equilibrium and Dynamical Quantum Phase Transitions via Out-of-Time-Ordered Correlators

Dynamical stability of the Holographic System with Two Competing Orders

Hadronic production of $D(2550)$, $D^*(2600)$, $D(2750)$, $D^*_1(2760)$ and $D^*_3(2760)$

In Situ Simultaneous Measuring Forces Acted on Individual Legs of Water Striders According to Archimedes' Principle

Linear and quadratic in temperature resistivity from holography

Modave Lectures on Applied AdS/CFT with Numerics

Nonlinear Transport in a Two Dimensional Holographic Superconductor

Note on Zero Temperature Holographic Superfluids

Towards Quantum Turbulence in Finite Temperature Bose-Einstein Condensates

Zero Temperature Holographic Superfluids with Two Competing Orders

From Petrov-Einstein-Dilaton-Axion to Navier-Stokes equation in anisotropic model

Holographic Interpretation of Acoustic Black Holes

Holographic Thermal Relaxation in Superfluid Turbulence

The Quasi-normal Modes of Charged Scalar Fields in Kerr-Newman black hole and Its Geometric Interpretation

Time domain analysis of superradiant instability for the charged stringy black hole-mirror system

Wavelet-based fast time-resolved magnetic sensing with electronic spins in diamond

Bulk Viscosity of dual Fluid at Finite Cutoff Surface via Gravity/Fluid correspondence in Einstein-Maxwell Gravity

Doubled Conformal Compactification

Entropy of isolated horizon from surface term of gravitational action

Holographic Entropy Production

The Petrov-like boundary condition at finite cutoff surface in Gravity/Fluid duality

The Universal Property of the Entropy Sum of Black Holes in All Dimensions

Fluid/Gravity Correspondence For General Non-rotating Black Holes

Generalized Kerr/CFT correspondence with electromagnetic field

Periodically Driven Holographic Superconductor

Poor man's holography: How far can it go?

A discussion on "generality of shear thickening in dense suspensions"

Fluid/gravity duality with Petrov-like boundary condition in a spacetime with a cosmological constant

Geometries with the second Poincaré symmetry

Holographic RG flows and transport coefficients in Einstein-Gauss-Bonnet-Maxwell theory

Incompressible Navier-Stokes Equation from Einstein-Maxwell and Gauss-Bonnet-Maxwell Theories

Magnetohydrodynamics from gravity

New Geometry with All Killing Vectors Spanning the Poincaré Algebra

Critical Phenomena and Thermodynamic Geometry of RN-AdS Black Holes

Dynamics of Gravity as Thermodynamics on the Spherical Holographic Screen

From Petrov-Einstein to Navier-Stokes in Spatially Curved Spacetime

Some Peculiarities of Newton-Hooke Space-Times

Geometries for Possible Kinematics

Reversible shear thickening at low shear rates of electrorheological fluids under electric fields

Thermodynamics of Black Holes from Equipartition of Energy and Holography

Hadronic production of $D(2550)$, $D^(2600)$, $D(2750)$, $D^_1(2760)$ and $D^*_3(2760)$