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Source author record

Yue Sun

Yue Sun appears in the imported research catalog. Authorship, coauthor and topic links are available while profile ownership is still unclaimed.

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cond-mat.supr-concond-mat.str-elphysics.opticscond-mat.mes-hallMachine Learningquant-phArtificial IntelligenceComputer Visioncond-mat.mtrl-scieess.SYmath.OCSystems and Controlmath-phmath.DSmath.MPComputer Science and Game Theoryeess.IVgr-qchep-exInformation Theorymath.COmath.ITmath.PRMultiagent SystemsNetworking and Internet Architecturephysics.app-phq-fin.CPSocial and Information Networks

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Published work

51 published item(s)

preprint2026arXiv

HepScript: A Dual-Use DSL for Human-AI Collaborative Data Analysis Workflows in High-Energy Physics

The escalating data scale in High-Energy Physics (HEP) fuels a growing aspiration for higher analytical efficiency. While Large Language Models (LLMs) offer a path toward automation via agentic AI, they struggle with complex scientific workflows that require deep domain knowledge and are tightly coupled to experiment-specific codebases. To address this, we introduce a methodology centered on HepScript, a dual-use Domain-Specific Language (DSL) for HEP data analysis workflows. HepScript serves as a shared formal interface, abstracting HEP analysis logic into a constrained syntax that is both intuitive for human experts and reliably generable by AI agents. First developed for the Beijing Spectrometer III (BESIII) experiment, HepScript hides the complexity of the underlying software stack, translating high-level analysis intent into low-level, production-ready code. In our case studies, this abstraction reduces the required human-written code by 93\%. Crucially, HepScript's constrained grammar defines a tractable action space, enabling AI agents to autonomously generate executable specifications for core analysis stages directly from published literature with a 95\% success rate. Our work demonstrates a scalable pathway toward human-AI collaborative systems, where a formally specified DSL acts as an unambiguous translation layer between human expertise, AI automation, and production environment, rendering previously intractable automation problems solvable.

0 citations0 reviewsNo code linkedOpen access
preprint2023arXiv

Distance Guided Generative Adversarial Network for Explainable Binary Classifications

Despite the potential benefits of data augmentation for mitigating the data insufficiency, traditional augmentation methods primarily rely on the prior intra-domain knowledge. On the other hand, advanced generative adversarial networks (GANs) generate inter-domain samples with limited variety. These previous methods make limited contributions to describing the decision boundaries for binary classification. In this paper, we propose a distance guided GAN (DisGAN) which controls the variation degrees of generated samples in the hyperplane space. Specifically, we instantiate the idea of DisGAN by combining two ways. The first way is vertical distance GAN (VerDisGAN) where the inter-domain generation is conditioned on the vertical distances. The second way is horizontal distance GAN (HorDisGAN) where the intra-domain generation is conditioned on the horizontal distances. Furthermore, VerDisGAN can produce the class-specific regions by mapping the source images to the hyperplane. Experimental results show that DisGAN consistently outperforms the GAN-based augmentation methods with explainable binary classification. The proposed method can apply to different classification architectures and has potential to extend to multi-class classification.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

A Survey of Quantum Computing for Finance

Quantum computers are expected to surpass the computational capabilities of classical computers during this decade and have transformative impact on numerous industry sectors, particularly finance. In fact, finance is estimated to be the first industry sector to benefit from quantum computing, not only in the medium and long terms, but even in the short term. This survey paper presents a comprehensive summary of the state of the art of quantum computing for financial applications, with particular emphasis on stochastic modeling, optimization, and machine learning, describing how these solutions, adapted to work on a quantum computer, can potentially help to solve financial problems, such as derivative pricing, risk modeling, portfolio optimization, natural language processing, and fraud detection, more efficiently and accurately. We also discuss the feasibility of these algorithms on near-term quantum computers with various hardware implementations and demonstrate how they relate to a wide range of use cases in finance. We hope this article will not only serve as a reference for academic researchers and industry practitioners but also inspire new ideas for future research.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Characterization of GaN-based HEMTs Down to 4.2 K for Cryogenic Applications

The cryogenic performance of GaN-based HEMTs (high-electron-mobility transistors) is systematically investigated by the direct current (DC) and low-frequency noise (LFN) characteristics within the temperature (T) range from 300 K to 4.2 K. The important electrical merits of the device, including drain saturation current (IDsat), on-resistance (RON), transductance, subthreshold swing (SS), gate leakage current, and Schottky barrier height, are comprehensively characterized and their temperature-dependent behavior was statistically analyzed. In addition, the LFN of the device shows an evident behavior of 1/f noise from 10 Hz to 10 kHz in the measured temperature range and can be significantly reduced at cryogenic temperature. These results are of great importance to motivate further studies into the GaN-based cryo-devices and systems.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Escaping High-order Saddles in Policy Optimization for Linear Quadratic Gaussian (LQG) Control

First order policy optimization has been widely used in reinforcement learning. It guarantees to find the optimal policy for the state-feedback linear quadratic regulator (LQR). However, the performance of policy optimization remains unclear for the linear quadratic Gaussian (LQG) control where the LQG cost has spurious suboptimal stationary points. In this paper, we introduce a novel perturbed policy gradient (PGD) method to escape a large class of bad stationary points (including high-order saddles). In particular, based on the specific structure of LQG, we introduce a novel reparameterization procedure which converts the iterate from a high-order saddle to a strict saddle, from which standard random perturbations in PGD can escape efficiently. We further characterize the high-order saddles that can be escaped by our algorithm.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Large deviations principle for stationary solutions of stochastic differential equations with multiplicative noise

We study the large deviations principle (LDP) for stationary solutions of a class of stochastic differential equations (SDE) in infinite time intervals by the weak convergence approach, and then establish the LDP for the invariant measures of the SDE by the contraction principle. We further point out the equivalence of the rate function of the LDP for invariant measures induced by the LDP for stationary solutions and the rate function defined by quasi-potential. This fact gives another view of the quasi-potential introduced by Freidlin and Wentzell.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

R2P: A Deep Learning Model from mmWave Radar to Point Cloud

Recent research has shown the effectiveness of mmWave radar sensing for object detection in low visibility environments, which makes it an ideal technique in autonomous navigation systems. In this paper, we introduce Radar to Point Cloud (R2P), a deep learning model that generates smooth, dense, and highly accurate point cloud representation of a 3D object with fine geometry details, based on rough and sparse point clouds with incorrect points obtained from mmWave radar. These input point clouds are converted from the 2D depth images that are generated from raw mmWave radar sensor data, characterized by inconsistency, and orientation and shape errors. R2P utilizes an architecture of two sequential deep learning encoder-decoder blocks to extract the essential features of those radar-based input point clouds of an object when observed from multiple viewpoints, and to ensure the internal consistency of a generated output point cloud and its accurate and detailed shape reconstruction of the original object. We implement R2P to replace Stage 2 of our recently proposed 3DRIMR (3D Reconstruction and Imaging via mmWave Radar) system. Our experiments demonstrate the significant performance improvement of R2P over the popular existing methods such as PointNet, PCN, and the original 3DRIMR design.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

System Identification via Nuclear Norm Regularization

This paper studies the problem of identifying low-order linear systems via Hankel nuclear norm regularization. Hankel regularization encourages the low-rankness of the Hankel matrix, which maps to the low-orderness of the system. We provide novel statistical analysis for this regularization and carefully contrast it with the unregularized ordinary least-squares (OLS) estimator. Our analysis leads to new bounds on estimating the impulse response and the Hankel matrix associated with the linear system. We first design an input excitation and show that Hankel regularization enables one to recover the system using optimal number of observations in the true system order and achieve strong statistical estimation rates. Surprisingly, we demonstrate that the input design indeed matters, by showing that intuitive choices such as i.i.d. Gaussian input leads to provably sub-optimal sample complexity. To better understand the benefits of regularization, we also revisit the OLS estimator. Besides refining existing bounds, we experimentally identify when regularized approach improves over OLS: (1) For low-order systems with slow impulse-response decay, OLS method performs poorly in terms of sample complexity, (2) Hankel matrix returned by regularization has a more clear singular value gap that ease identification of the system order, (3) Hankel regularization is less sensitive to hyperparameter choice. Finally, we establish model selection guarantees through a joint train-validation procedure where we tune the regularization parameter for near-optimal estimation.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Towards Sample-efficient Overparameterized Meta-learning

An overarching goal in machine learning is to build a generalizable model with few samples. To this end, overparameterization has been the subject of immense interest to explain the generalization ability of deep nets even when the size of the dataset is smaller than that of the model. While the prior literature focuses on the classical supervised setting, this paper aims to demystify overparameterization for meta-learning. Here we have a sequence of linear-regression tasks and we ask: (1) Given earlier tasks, what is the optimal linear representation of features for a new downstream task? and (2) How many samples do we need to build this representation? This work shows that surprisingly, overparameterization arises as a natural answer to these fundamental meta-learning questions. Specifically, for (1), we first show that learning the optimal representation coincides with the problem of designing a task-aware regularization to promote inductive bias. We leverage this inductive bias to explain how the downstream task actually benefits from overparameterization, in contrast to prior works on few-shot learning. For (2), we develop a theory to explain how feature covariance can implicitly help reduce the sample complexity well below the degrees of freedom and lead to small estimation error. We then integrate these findings to obtain an overall performance guarantee for our meta-learning algorithm. Numerical experiments on real and synthetic data verify our insights on overparameterized meta-learning.

0 citations0 reviewsNo code linkedOpen access
preprint2021arXiv

Protonation-induced discrete superconducting phases in bulk FeSe single crystals

The superconducting transition temperature, $T_{\rm{c}}$, of FeSe can be significantly enhanced several-fold by applying pressure, electron doping, intercalating spacing layer, and reducing dimensionality. Various ordered electronic phases, such as nematicity and spin density waves, have also been observed accompanying high-$T_{\rm{c}}$ superconductivity. Investigation on the evolution of the electronic structure with $T_{\rm{c}}$ is essential to understanding electronic behavior and high-$T_{\rm{c}}$ superconductivity in FeSe and its derived superconductors. In this report, we have found a series of discrete superconducting phases, with a maximum $T_{\rm{c}}$ up to 44 K, in H$^+$-intercalated FeSe single crystals using an ionic liquid gating method. Accompanied with the increase of $T_{\rm{c}}$, suppression of the nematic phase and evolution from non-Fermi-liquid to Fermi-liquid behavior was observed. An abrupt change in the Fermi surface topology was proposed to explain the discrete superconducting phases. A band structure that favors the high-$T_{\rm{c}}$ superconducting phase was also revealed.

0 citations0 reviewsNo code linkedOpen access
preprint2021arXiv

Refined Eulerian numbers and ballot permutations

A ballot permutation is a permutation π such that in any prefix of π the descent number is not more than the ascent number. In this article, we obtained a formula in close form for the multivariate generating function of {A(n,d,j)}, which denote the number of permutations of length n with d descents and j as the first letter. Besides, by a series of calculations with generatingfunctionology, we confirm a recent conjecture of Wang and Zhang for ballot permutations.

0 citations0 reviewsNo code linkedOpen access
preprint2021arXiv

Sample Efficient Subspace-based Representations for Nonlinear Meta-Learning

Constructing good representations is critical for learning complex tasks in a sample efficient manner. In the context of meta-learning, representations can be constructed from common patterns of previously seen tasks so that a future task can be learned quickly. While recent works show the benefit of subspace-based representations, such results are limited to linear-regression tasks. This work explores a more general class of nonlinear tasks with applications ranging from binary classification, generalized linear models and neural nets. We prove that subspace-based representations can be learned in a sample-efficient manner and provably benefit future tasks in terms of sample complexity. Numerical results verify the theoretical predictions in classification and neural-network regression tasks.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

A Hierarchical User Intention-Habit Extract Network for Credit Loan Overdue Risk Detection

More personal consumer loan products are emerging in mobile banking APP. For ease of use, application process is always simple, which means that few application information is requested for user to fill when applying for a loan, which is not conducive to construct users' credit profile. Thus, the simple application process brings huge challenges to the overdue risk detection, as higher overdue rate will result in greater economic losses to the bank. In this paper, we propose a model named HUIHEN (Hierarchical User Intention-Habit Extract Network) that leverages the users' behavior information in mobile banking APP. Due to the diversity of users' behaviors, we divide behavior sequences into sessions according to the time interval, and use the field-aware method to extract the intra-field information of behaviors. Then, we propose a hierarchical network composed of time-aware GRU and user-item-aware GRU to capture users' short-term intentions and users' long-term habits, which can be regarded as a supplement to user profile. The proposed model can improve the accuracy without increasing the complexity of the original online application process. Experimental results demonstrate the superiority of HUIHEN and show that HUIHEN outperforms other state-of-art models on all datasets.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

A short note on solving box inequality and linear equality constrained optimization problem

This paper discusses a special kind of convex constrained optimization problem, whose constraints consist of box inequalities and linear equalities. For this problem, in addition to general optimization algorithms such as exact penalty algorithm and interior point algorithm, there is a simple iterative algorithm that is simple to implement, which is favored by machine learning practitioners.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

Achieving the depairing limit along $c$ axis in Fe$_{1+y}$Te$_{1-x}$Se$_x$ single crystals

We report the achieving of depairing current limit along $c$-axis in Fe$_{1+y}$Te$_{1-x}$Se$_x$ single crystals. A series of crystals with $T_{\rm{c}}$ ranging from 8.6 K to 13.7 K (different amount of excess Fe, $y$) were fabricated into $c$-axis bridges with a square-micrometer cross-section. The critical current density, $J_{\rm{c}}$, was directly estimated from the transport current-voltage measurements. The transport $J_{\rm{c}}$ reaches a very large value, which is about one order of magnitude larger than the depinning $J_{\rm{c}}$, but comparable to the calculated depairing $J_{\rm{c}}$ $\sim$ 2 $\times$ 10$^6$ A/cm$^2$ at 0 K, based on the Ginzburg-Landau (GL) theory. The temperature dependence of the depairing $J_{\rm{c}}$ follows the GL-theory ($\propto$ (1-$T/T_{\rm{c}}$)$^{3/2}$) down to $\sim$ 0.83 $T_{\rm{c}}$, then increases with a reduced slope at low temperatures, which can be qualitatively described by the Kupriyanov-Lukichev theory. Our study provides a new route to understand the behavior of depairing $J_{\rm{c}}$ in iron-based superconductors in a wide temperature range.

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preprint2020arXiv

Fully gapped superconductivity without sign reversal in the topological superconductor PbTaSe$_2$

We investigate the superconducting gap function of topological superconductor PbTaSe$_2$. Temperature, magnetic field, and three-dimensional (3D) field-angle dependences of the specific heat prove that the superconductivity of PbTaSe$_2$ is fully-gapped, with two isotropic $s$-wave gaps. The pair-breaking effect is probed by systematically increasing non-magnetic disorders through H$^+$-irradiations. The superconducting transition temperature, $T_{\rm{c}}$, is found to be robust against disorders, which suggests that the pairing should be sign-preserved rather than sign-reversed.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

Option Pricing using Quantum Computers

We present a methodology to price options and portfolios of options on a gate-based quantum computer using amplitude estimation, an algorithm which provides a quadratic speedup compared to classical Monte Carlo methods. The options that we cover include vanilla options, multi-asset options and path-dependent options such as barrier options. We put an emphasis on the implementation of the quantum circuits required to build the input states and operators needed by amplitude estimation to price the different option types. Additionally, we show simulation results to highlight how the circuits that we implement price the different option contracts. Finally, we examine the performance of option pricing circuits on quantum hardware using the IBM Q Tokyo quantum device. We employ a simple, yet effective, error mitigation scheme that allows us to significantly reduce the errors arising from noisy two-qubit gates.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

ResNeSt: Split-Attention Networks

It is well known that featuremap attention and multi-path representation are important for visual recognition. In this paper, we present a modularized architecture, which applies the channel-wise attention on different network branches to leverage their success in capturing cross-feature interactions and learning diverse representations. Our design results in a simple and unified computation block, which can be parameterized using only a few variables. Our model, named ResNeSt, outperforms EfficientNet in accuracy and latency trade-off on image classification. In addition, ResNeSt has achieved superior transfer learning results on several public benchmarks serving as the backbone, and has been adopted by the winning entries of COCO-LVIS challenge. The source code for complete system and pretrained models are publicly available.

0 citations0 reviewsNo code linkedOpen access
preprint2019arXiv

Evidence for nematic superconductivity of topological surface states in PbTaSe2

Spontaneous symmetry breaking has been a paradigm to describe the phase transitions in condensed matter physics. In addition to the continuous electromagnetic gauge symmetry, an unconventional superconductor can break discrete symmetries simultaneously, such as time reversal and lattice rotational symmetry. In this work we report a characteristic in-plane 2-fold behaviour of the resistive upper critical field and point-contact spectra on the superconducting semimetal PbTaSe2 with topological nodal-rings, despite its hexagonal lattice symmetry (or D_3h in bulk while C_3v on surface, to be precise). However, we do not observe any lattice rotational symmetry breaking signal from field-angle-dependent specific heat. It is worth noting that such surface-only electronic nematicity is in sharp contrast to the observation in the topological superconductor candidate, CuxBi2Se3, where the nematicity occurs in various bulk measurements. In combination with theory, superconducting nematicity is likely to emerge from the topological surface states of PbTaSe2, rather than the proximity effect. The issue of time reversal symmetry breaking is also addressed. Thus, our results on PbTaSe2 shed new light on possible routes to realize nematic superconductivity with nontrivial topology.

0 citations0 reviewsNo code linkedOpen access
preprint2016arXiv

Effects of Iodine Annealing on Fe1+yTe0.6Se0.4

Effects of iodine annealing to induce bulk superconductivity in Fe1+yTe0.6Se0.4 have been systematically studied by changing the molar ratio of iodine to the sample and annealing temperature. The optimal condition to induce bulk superconductivity with Tc ~14.5 K and self-field Jc(2 K) ~ 5x10^5 A/cm2 is found to be a molar ratio of iodine of 5-7 % at the annealing temperature of 400 C. Furthermore, the fact that no compounds containing iodine are detected in the crystal and a significant amount of FeTe2 is produced after the iodine annealing strongly indicate that the excess iron is consumed to form FeTe2 and iodine works as a catalyst in this process.

0 citations0 reviewsNo code linkedOpen access
preprint2016arXiv

Effects of Pnictogen Atmosphere Annealing in Fe$_{1+y}$Te$_{0.6}$Se$_{0.4}$

It has been clarified that bulk superconductivity in Fe$_{1+y}$Te$_{0.6}$Se$_{0.4}$ can be induced by annealing in an appropriate atmosphere to remove the harmful effects of excess iron. In order to clarify the details of the annealing process, we studied the changes in the physical properties and reaction products of Fe$_{1+y}$Te$_{0.6}$Se$_{0.4}$ annealed in pnictogen (P, As, Sb) atmospheres. Crystals annealed in a pnictogen atmosphere show bulk superconductivity and the values of $T_{c}$ and $J_{c}$ are about $14~$K and 2-4 $\times 10{^5}~$A/cm$^2$ ($2~$K, self-field), respectively. It is also found that the reaction rate increases with the increase in the saturated vapor pressure of the pnictogen. Unexpectedly, the reaction products of Fe$_{1+y}$Te$_{0.6}$Se$_{0.4}$ after annealing in a P atmosphere mainly consist of FeTe$_2$. In addition, the amount of P required to obtain the optimal $T_{c}$ is much smaller than the amount of excess iron, which is similar to the case of oxygen annealing. P, oxygen, and to some extent As could serve as catalysts to form FeTe$_2$ to remove excess iron.

0 citations0 reviewsNo code linkedOpen access
preprint2016arXiv

Electron carriers with possible Dirac-cone-like dispersion in FeSe$_{1-x}$S$_x$ ($x$ = 0 and 0.14) single crystals triggered by structural transition

We report detailed study of the transport properties of FeSe$_{1-x}$S$_x$ ($x$ = 0 and 0.14) single crystals grown by vapor transport method. 14\% S doping is found significantly suppress the structural transition from $T_s$ $\sim$ 86 K in FeSe to $\sim$ 49 K, although the superconducting transition temperature, $T_c$, is only slightly affected. A pronounced linear magnetoresistance (MR) is observed in both FeSe and FeSe$_{0.86}$S$_{0.14}$ single crystals, which is found to be triggered by the structural transition. The linear MR and related discussion indicate the possible existence of Dirac-cone-like state, which may come from the band shift induced by ferro-orbital order. The mobility of the Dirac-cone-like band is found to decrease after S doping. Besides, the invalid Kohler's scaling of MR is found for temperature below $T_s$ in both crystals, however the re-establishment of the Kohler's scaling at temperatures below 30 K is observed in FeSe, but not in FeSe$_{0.86}$S$_{0.14}$. All these observations above support that the orbital ordering causes the band reconstruction in FeSe, and also that the orbital ordering in FeSe is suppressed by the chemical pressure from S doping.

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preprint2016arXiv

Gain enhanced Fano resonance in a coupled photonic crystal cavity-waveguide structure

Systems with coupled cavities and waveguides have been demonstrated as optical switches and optical sensors. To optimize the functionalities of these optical devices, Fano resonance with asymmetric and steep spectral line shape has been used. We theoretically propose a coupled photonic crystal cavity-waveguide structure to achieve Fano resonance by placing partially reflecting elements in waveguide. To enhance Fano resonance, optical gain material is introduced into the cavity. As the gain increases, the transmission line shape becomes steepened and the transmissivity can be six times enhanced, giving a large contrast by a small frequency shift. It is prospected that the gain enhanced Fano resonance is very useful for optical switches and optical sensors.

0 citations0 reviewsNo code linkedOpen access
preprint2016arXiv

Influence of interstitial Fe to the phase diagram of Fe$_{1+y}$Te$_{1-x}$Se$_x$ single crystals

Superconductivity (SC) with the suppression of long-range antiferromagnetic (AFM) order is observed in the parent compounds of both iron-based and cuprate superconductors. The AFM wave vectors are bicollinear ($π$, 0) in the parent compound FeTe different from the collinear AFM order ($π$, $π$) in most iron pnictides. Study of the phase diagram of Fe$_{1+y}$Te$_{1-x}$Se$_x$ is the most direct way to investigate the competition between bicollinear AFM and SC. However, presence of interstitial Fe affects both magnetism and SC of Fe$_{1+y}$Te$_{1-x}$Se$_x$, which hinders the establishment of the real phase diagram. Here, we report the comparison of doping-temperature ($x$-$T$) phase diagrams for Fe$_{1+y}$Te$_{1-x}$Se$_x$ (0 $\leq$ $x$ $\leq$ 0.43) single crystals before and after removing interstitial Fe. Without interstitial Fe, the AFM state survives only for $x$ $<$ 0.05, and bulk SC emerges from $x$ = 0.05, and does not coexist with the AFM state. The previously reported spin glass state, and the coexistence of AFM and SC may be originated from the effect of the interstitial Fe. The phase diagram of Fe$_{1+y}$Te$_{1-x}$Se$_x$ is found to be similar to the case of the "1111" system such as LaFeAsO$_{1-x}$F$_x$, and is different from that of the "122" system.

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preprint2016arXiv

Low-Rank Positive Semidefinite Matrix Recovery from Corrupted Rank-One Measurements

We study the problem of estimating a low-rank positive semidefinite (PSD) matrix from a set of rank-one measurements using sensing vectors composed of i.i.d. standard Gaussian entries, which are possibly corrupted by arbitrary outliers. This problem arises from applications such as phase retrieval, covariance sketching, quantum space tomography, and power spectrum estimation. We first propose a convex optimization algorithm that seeks the PSD matrix with the minimum $\ell_1$-norm of the observation residual. The advantage of our algorithm is that it is free of parameters, therefore eliminating the need for tuning parameters and allowing easy implementations. We establish that with high probability, a low-rank PSD matrix can be exactly recovered as soon as the number of measurements is large enough, even when a fraction of the measurements are corrupted by outliers with arbitrary magnitudes. Moreover, the recovery is also stable against bounded noise. With the additional information of an upper bound of the rank of the PSD matrix, we propose another non-convex algorithm based on subgradient descent that demonstrates excellent empirical performance in terms of computational efficiency and accuracy.

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preprint2016arXiv

Observation of nonlinear thermal optical dynamics in a chalcogenide nanobeam cavity

We present a theoretical and experimental analysis of nonlinear thermo-optic effects in suspended chalcogenide glass nanobeam cavities. We measure the power dependent resonance peaks and characterise the dynamic nonlinear thermo-optic response of the cavity under modulated light input. Several distinct nonlinear characteristics are identified, including a modified spectral response containing periodic fringes, a critical wavelength jump and saturated time delay for modulation frequency faster than the thermal characteristic time. We reveal that the coupling to a parasitic Fabry-Perot cavity enables isolated thermal equilibrium states resulting in the discontinuous thermo-optic critical point.

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preprint2016arXiv

Recombination processes in CuInS$_{2}$/ZnS Nanocrystals during steady-state photoluminescence

We report on temperature- and excitation-power-dependent photoluminescence (PL) study of CuInS$_{2}$/ZnS nanocrystals dispersed on a SiO$_{2}$/Si substrate with a confocal micro-PL system. With increasing the excitation power at 22 K and room temperature, the PL spectra are blue-shifted because of the state filling. At low temperature, a small peak is observed at the low energy side of the spectrum, which could be due to the F$\ddot{o}$rster resonance energy transfer between different nanocrystals. The integrated PL intensity increases sublinearly as a function of excitation power with a power factor of around 2/3, which demonstrates the Auger recombination dominated process in the nanocrystals, especially under the high excitation power.

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preprint2016arXiv

Slow phonon vortices and defect modes in periodic nano-waveguides

We identify a broad class of phonon modes with persistent vortex fluxes at arbitrarily slow propagating velocities in periodic nano-waveguides. Such phonon vortices are associated with the split band-edges in dispersion dependencies, which can be engineered by waveguide design. Modulations introduced in such waveguides can support a pair of defect cavity phonon modes with an arbitrarily small frequency splitting. These features can find applications for sensing and nano-manipulation.

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preprint2016arXiv

Structural-transition-induced quasi two-dimensional Fermi surface in FeSe

We report detailed study of angular-dependent magnetoresistance (AMR) with tilting angel $θ$ from $c$-axis ranging from 0$^\circ$ to 360$^\circ$ on a high-quality FeSe single crystal. A pronounced AMR with twofold symmetry is observed, which is caused by the quasi two-dimensional (2D) Fermi surface. The pronounced AMR is observed only in the orthorhombic phase, indicating that the quasi-2D Fermi surface is induced by the structural transition. Details about the influence of the multiband effect to the AMR are also discussed. Besides, the angular response of a possible Dirac-cone-like band structure is investigated by analyzing the detailed magnetoresistance at different $θ$. The obtained characteristic field ($B^*$) can be also roughly scaled in the 2D approximation, which indicates that the Dirac-cone-like state is also 2D in nature.

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preprint2015arXiv

Critical current density, vortex dynamics, and phase diagram of FeSe single crystal

We present a comprehensive study of the vortex pinning and dynamics in a high-quality FeSe single crystal, which is free from doping introduced inhomogeneities and charged quasi-particle-scattering because of its innate superconductivity. Critical current density, $J_c$, is found to be almost isotropic, and reaches a value $\sim$ 3 $\times$ 10$^4$ A/cm$^2$ at 2 K (self-field) for both $H$ $\|$ $c$ and $ab$. The normalized magnetic relaxation rate $S$ (= $\mid$dln$M$/dln$t$$\mid$) shows a temperature insensitive plateau behavior in the intermediate temperature range with a relatively high creep rate ($S$ $\sim$ 0.02 under zero field), which is interpreted in the framework of the collective creep theory. A crossover from the elastic to plastic creep is observed, while the fish-tail effect is absent for both $H$ $\|$ $c$ and $ab$. Based on this observation, the origin of the fish-tail effect is also discussed. Combining the results of $J_c$ and $S$, vortex motion in FeSe single crystal is found to be dominated by sparse strong point-like pinning from nm-sized defects or imperfections. The weak collective pinning is also observed and proved in the form of large bundles. Besides, the vortex phase diagram of FeSe is also constructed and discussed.

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preprint2015arXiv

Enhancement of critical current density and mechanism of vortex pinning in H$^+$-irradiated FeSe single crystal

In this report, we comprehensively study the effect of H$^+$ irradiation on the critical current density, $J_c$, and vortex pinning in FeSe single crystal. It is found that the value of $J_c$ for FeSe is enhanced more than twice after 3-MeV H$^+$ irradiation. The scaling analyses of the vortex pinning force based on the Dew-Hughes model reveal that the H$^+$ irradiation successfully introduce point pinning centers into the crystal. We also find that the vortex creep rates are strongly suppressed after irradiation. Detailed analyses of the critical current dependent pinning energy based on the collective creep theory and extend Maley's method show that the H$^+$ irradiation enhances the value of $J_c$ before the flux creep, and also reduces the size of flux bundle, which will further reduce the field dependence of $J_c$ due to vortex motion.

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preprint2015arXiv

Evolution of superconducting and transport properties in annealed FeTe$_{1-x}$Se$_x$ (0.1 $\leq$ $x$ $\leq$ 0.4) multiband superconductors

We investigated the superconducting and transport properties in FeTe$_{1-x}$Se$_{x}$ (0.1 $\leq$ $x$ $\leq$ 0.4) single crystals prepared by O$_2$-annealing. Sharp superconducting transition width observed in magnetization measurement and the small residual resistivity prove the high quality of the crystals. All the crystals manifest large, homogeneous, and isotropic critical current density \emph{J}$_c$ with self-field value over 10$^5$ A/cm$^2$ at 2 K. The large and field-robust critical current densities prove that the superconductivity in FeTe$_{1-x}$Se$_{x}$ (0.1 $\leq$ $x$ $\leq$ 0.4) is in bulk nature. The values of anisotropy parameter close to $T_c$ for crystals with different Se doping levels all reside in the range of 2 - 3. Hall coefficients $R_H$ keeps positive and almost constant value at high temperatures, followed by a sudden decreases before reaching $T$$_c$, which indicates that the electron-type charge carriers become dominant at low temperatures. Furthermore, the characteristic temperature for the sudden decrease in $R_H$ gradually increases with Se doping.

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preprint2015arXiv

Longitudinal wave function control in single quantum dots with an applied magnetic field

Controlling single-particle wave functions in single semiconductor quantum dots is in demand to implement solid-state quantum information processing and spintronics. Normally, particle wave functions can be tuned transversely by an perpendicular magnetic field. We report a longitudinal wave function control in single quantum dots with a magnetic field. For a pure InAs quantum dot with a shape of pyramid or truncated pyramid, the hole wave function always occupies the base because of the less confinement at base, which induces a permanent dipole oriented from base to apex. With applying magnetic field along the base-apex direction, the hole wave function shrinks in the base plane. Because of the linear changing of the confinement for hole wave function from base to apex, the center of effective mass moves up during shrinking process. Due to the uniform confine potential for electrons, the center of effective mass of electrons does not move much, which results in a permanent dipole moment change and an inverted electron-hole alignment along the magnetic field direction. Manipulating the wave function longitudinally not only provides an alternative way to control the charge distribution with magnetic field but also a new method to tune electron-hole interaction in single quantum dots.

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preprint2015arXiv

Observation of coupling between zero- and two-dimensional semiconductor systems based on anomalous diamagnetic effects

We report the direct observation of coupling between a single self-assembled InAs quantum dot and a wetting layer, based on strong diamagnetic shifts of many-body exciton states using magneto-photoluminescence spectroscopy. An extremely large positive diamagnetic coefficient is observed when an electron in the wetting layer combines with a hole in the quantum dot; the coefficient is nearly one order of magnitude larger than that of the exciton states confined in the quantum dots. Recombination of electrons with holes in a quantum dot of the coupled system leads to an unusual negative diamagnetic effect, which is five times stronger than that in a pure quantum dot system. This effect can be attributed to the expansion of the wavefunction of remaining electrons in the wetting layer or the spread of electrons in the excited states of the quantum dot to the wetting layer after recombination. In this case, the wavefunction extent of the final states in the quantum dot plane is much larger than that of the initial states because of the absence of holes in the quantum dot to attract electrons. The properties of emitted photons that depend on the large electron wavefunction extents in the wetting layer indicate that the coupling occurs between systems of different dimensionality, which is also verified from the results obtained by applying a magnetic field in different configurations. This study paves a new way to observe hybrid states with zero- and two-dimensional structures, which could be useful for investigating the Kondo physics and implementing spin-based solid-state quantum information processing.

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preprint2015arXiv

Social Data Offloading in D2D-Enhanced Cellular Networks by Network Formation Games

Recently, cellular networks are severely overloaded by social-based services, such as YouTube, Facebook and Twitter, in which thousands of clients subscribe a common content provider (e.g., a popular singer) and download his/her content updates all the time. Offloading such traffic through complementary networks, such as a delay tolerant network formed by device-to-device (D2D) communications between mobile subscribers, is a promising solution to reduce the cellular burdens. In the existing solutions, mobile users are assumed to be volunteers who selfishlessly deliver the content to every other user in proximity while moving. However, practical users are selfish and they will evaluate their individual payoffs in the D2D sharing process, which may highly influence the network performance compared to the case of selfishless users. In this paper, we take user selfishness into consideration and propose a network formation game to capture the dynamic characteristics of selfish behaviors. In the proposed game, we provide the utility function of each user and specify the conditions under which the subscribers are guaranteed to converge to a stable network. Then, we propose a practical network formation algorithm in which the users can decide their D2D sharing strategies based on their historical records. Simulation results show that user selfishness can highly degrade the efficiency of data offloading, compared with ideal volunteer users. Also, the decrease caused by user selfishness can be highly affected by the cost ratio between the cellular transmission and D2D transmission, the access delays, and mobility patterns.

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preprint2014arXiv

Anisotropic Superconductivity of Ca1-xLaxFeAs2 (x ~ 0.18) Single Crystal

Anisotropic superconducting properties including the upper critical field Hc2, thermal activation energy U0, and critical current density Jc are systematically studied in a large Ca1-xLaxFeAs2 single crystal (x ~ 0.18). The obtained Hc2 bears a moderate anisotropy gamma of approximately 2-4.2, located between those of '122' Ba1-xKxFe2As2 (1 < gamma < 2) and '1111' NdFeAsO1-xFx (5 < gamma < 9.2). Both the magnitude of U0 and its field dependence are very similar to those of NdFeAsO1-xFx, also indicating anisotropic superconductivity. Moreover, high and anisotropic Jc's exceeding 10^5 A/cm2 have been calculated from the magnetization hysteresis loops, indicating the existence of strong bulk-dominated pinning in the present superconducting material.

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preprint2014arXiv

Bulk Superconductivity in Fe1+yTe0.6Se0.4 Induced by Removal of Excess Fe

Experimental evidences from transport, magnetic, and magneto-optical (MO) image measurements confirmed that arsenic (As) vapor annealing was another effective way to induce bulk superconductivity with isotropic, large, and homogenous superconducting critical current density (Jc) in Fe1+yTe0.6Se0.4 single crystal. Since As is an exotic and easily detectable heavy element to Fe1+yTe0.6Se0.4 single crystal, As vapor annealing is very advantageous for the study of annealing mechanism. Detailed micro-structural and elemental analyses exclude the possibility that intercalating or doping effect may happen in the other post-annealing methods, proving that Fe reacts with As on the surface of the crystal and the reaction itself acts as a driving force to drag excess Fe out. The removal of excess Fe results in the good superconductivity performance.

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preprint2014arXiv

Charge state control in single InAs/GaAs quantum dots by external electric and magnetic fields

We report a photoluminescence (PL) spectroscopy study of charge state control in single self-assembled InAs/GaAs quantum dots by applying electric and/or magnetic fields at 4.2 K. Neutral and charged exciton complexes were observed under applied bias voltages from -0.5 V to 0.5 V by controlling the carrier tunneling. The highly negatively charged exciton emission becomes stronger with increasing pumping power, arising from the fact that electrons have a smaller effective mass than holes and are more easily captured by the quantum dots. The integrated PL intensity of negatively charged excitons is affected significantly by a magnetic field applied along the sample growth axis. This observation is explained by a reduction in the electron drift velocity caused by an applied magnetic field, which increases the probability of non-resonantly excited electrons being trapped by localized potentials at the wetting layer interface, and results in fewer electrons distributed in the quantum dots. The hole drift velocity is also affected by the magnetic field, but it is much weaker.

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preprint2014arXiv

Dynamics and mechanism of oxygen annealing in Fe$_{1+y}$Te$_{0.6}$Se$_{0.4}$ single crystal

Iron chalcogenide Fe(Te,Se) attracted much attention due to its simple structure, which is favorable for probing the superconducting mechanism. Its less toxic nature compared with iron arsenides is also advantageous for applications of iron-based superconductors. By intercalating spacer layers, superconducting transition temperature has been raised over 40 K. On the other hand, the presence of excess Fe is almost unavoidable in Fe(Te,Se) single crystals, which hinders the appearance of bulk superconductivity and causes strong controversies over its fundamental properties. Here we report a systematical study of O$_2$-annealing dynamics in Fe$_{1+y}$Te$_{1-x}$Se$_{x}$ by controlling the amount of O$_2$, annealing temperature, and time. Bulk superconductivity can be gradually induced by increasing the amount of O$_2$ and annealing time at suitable temperatures. The optimally annealed crystals can be easily obtained by annealing with ~ 1.5% molar ratio of oxygen at 400 $^{\circ}$C for more than 1 hour. Superconductivity was witnessed to evolve mainly from the edge of the crystal to the central part. After the optimal annealing, the complete removal of excess Fe was demonstrated via STM measurements. Some fundamental properties were recharacterized and compared with those of as-grown crystals to discuss the influence of excess Fe.

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preprint2014arXiv

Magneto-optical characterizations of FeTe$_{0.5}$Se$_{0.5}$ thin films with critical current density over 1 MA/cm$^2$

We performed magneto-optical (MO) measurements on FeTe$_{0.5}$Se$_{0.5}$ thin films grown on LaAlO$_3$ (LAO) and Yttria-stabilized zirconia (YSZ) single-crystalline substrates. These thin films show superconducting transition temperature, ${T_c}$ $\sim$ 19 K, 4 K higher than the bulk sample. Typical roof-top patterns can be observed in the MO images of thin films grown on LAO and YSZ, from which a large and homogeneous critical current density, ${J_c}$, over 1 $\times$ 10$^6$ A/cm$^2$ at 5 K was obtained. Magnetic flux penetration measurement reveals that the current is almost isotropically distributed in the two thin films. Compared with bulk crystals, FeTe$_{0.5}$Se$_{0.5}$ thin film demonstrates not only higher ${T_c}$, but also much larger ${J_c}$, which is attractive for applications.

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preprint2014arXiv

Multiband Effect and Possible Dirac Fermions in Fe$_{1+y}$Te$_{0.6}$Se$_{0.4}$

We investigated the transport properties of Fe$_{1+y}$Te$_{0.6}$Se$_{0.4}$ single crystals with different amounts of excess Fe prepared by O$_2$ annealing. The O$_2$ annealing remarkably improves transport properties. In particular, a strongly nonlinear Hall resistivity was observed only in the fully-annealed crystal, and the magnetoresistance (MR) is drastically enhanced after annealing, reaching a value larger than 17% at 16 K and 14 T. The obvious change of transport properties after the annealing indicates that the band structure of Fe$_{1+y}$Te$_{0.6}$Se$_{0.4}$ is affected by the excess Fe. The nonlinear Hall resistivity and violation of (modified) Kohler's scaling of the large MR prove the multiband effects in the Fe$_{1+y}$Te$_{0.6}$Se$_{0.4}$ single crystal. The MR for the fully-annealed crystal develops linearly against magnetic field from intermediate field (e. g. 2 T at 16 K) to the measurement limit of 14 T. This phenomenon is interpreted by the existence of Dirac cone state, in which all the Dirac fermions occupy only the lowest Landau level in the quantum limit.

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preprint2013arXiv

Bulk Superconductivity in Fe$_{1+y}$Te$_{1-x}$Se$_{x}$ Induced by Annealing in Se and S Vapor

We reported that bulk superconductivity in Fe$_{1+y}$Te$_{1-x}$Se$_{x}$ can be induced by annealing in Se and S vapor. The well-annealed samples show a large critical current density, emph{J}$_c$ $\sim$ 2 - 4 $\times$ 10$^5$ A/cm$^2$. Combined with our previous reports about O$_2$ and Te annealing effects, we proved that bulk superconductivity can be successfully induced in Fe$_{1+y}$Te$_{1-x}$Se$_{x}$ by annealing in atmosphere of all chalcogens, such as O, S, Se and Te.

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preprint2013arXiv

Evolution of Superconductivity in Fe$_{1+y}$Te$_{1-x}$Se$_{x}$ Annealed in Te Vapor

We report a detailed study of the Te vapor annealing effect in Fe$_{1+y}$Te$_{0.6}$Se$_{0.4}$ single crystals. Bulk superconductivity can be gradually induced by annealing with increasing amount of Te, until the molar ratio of Te to the sample reaches 1 : 10. By further increasing Te molar ratio, superconducting volume is gradually reduced. Resistivity and Hall effect measurements manifest that annealing in Te vapor delocalizes the charge carriers by removing excess Fe. The optimally Te annealed crystal shows homogeneous critical current densities with a large value of $\sim$ 4.3 $\times$ 10$^5$ A/cm$^2$, which proves that the Te annealing is effective to induce bulk superconductivity in Fe$_{1+y}$Te$_{1-x}$Se$_{x}$.

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preprint2013arXiv

Large, Homogeneous, and Isotropic Critical Current Density in Oxygen-Annealed Fe1+yTe0.6Se0.4 Single Crystal

We reported a controllable way of removing excess Fe in Fe1+yTe0.6Se0.4 by annealing in a fixed amount of O2. Compared with the weak superconductivity induced by dilute acids, O2 annealing can successfully induce bulk superconductivity. Proper O2 annealing changes the temperature dependence of resistivity at low temperatures from semiconducting to metallic, which comes from the deintercalation of excess Fe. Critical current densities with field along the c-axis and ab-plane are found almost isotropic with large values of 3*10^5 A/cm2 and 2.5*10^5 A/cm2 at 2 K. Furthermore, magneto-optical images reveal isotropic current flow within the ab-plane.

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preprint2013arXiv

Magnetic relaxation and collective vortex creep in FeTe$_{0.6}$Se$_{0.4}$ single crystal

We study the vortex dynamics in high-quality FeTe$_{0.6}$Se$_{0.4}$ single crystal by performing magnetization measurements of the screening current density \emph{J}$_s$ and flux creep rate \emph{S}. Temperature dependence of \emph{S} shows a plateau in the intermediate temperature region with a high creep rate $\sim$ 0.03, which is interpreted in the framework of the collective creep theory. A crossover from elastic to plastic creep is observed. The glassy exponent and barrier height for flux creep are directly determined by extended Maley's method. \emph{J}$_s$ with flux creep, obtained from magnetic hysteresis loops, is successfully reproduced based on the collective creep analysis. We also approach critical current density without flux creep by means of the generalized inversion scheme, which proves that the $δ$\emph{l} and $δ$\emph{T}$_c$ pinning coexist in FeTe$_{0.6}$Se$_{0.4}$ single crystal.

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preprint2013arXiv

Specific Heat and Upper Critical Field of Sc5Ir4Si10 Superconductor

Temperature and magnetic field dependent specific heat of textured Sc5Ir4Si10 superconductor was investigated in detail. Based on the fitting of zero-field electronic specific heat by different gap structures as well as the discussion on field-induced specific heat coefficient, Sc5Ir4Si10 is proved to be an anisotropic s-wave superconductor with a gap anisotropy of 0.53. The anisotropy of upper critical field suggests the weakly one-dimensional Fermi surface, and the value is consistent with the gap anisotropy result obtained from the specific heat data.

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preprint2013arXiv

Twists and turns for metamaterials

We propose and verify experimentally a new concept for achieving strong nonlinear coupling between the electromagnetic and elastic properties in metamaterials. This coupling is provided through a novel degree of freedom in metamaterial design: internal rotation within structural elements. Our meta-atoms have high sensitivity to electromagnetic wave power, and the elastic and electromagnetic properties can be independently designed to optimise the response. We demonstrate a rich range of nonlinear phenomena including self-tuning and bistability, and provide a comprehensive experimental demonstration of the predicted effects.

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preprint2012arXiv

Anisotropies and Homogeneities of Superconducting Properties in Iron-Platinum-Arsenide Ca10(Pt3As8)(Fe1.79Pt0.21As2)5

We report a study on the anisotropy of superconducting properties in single crystalline Ca10(Pt4-δAs8)(Fe1.79Pt0.21As2)5 with Tc ~13.6 K. Under a field of 5 Oe, the sample reaches fully-diamagnetic state at ~10 K for H//c, and ~8 K for H//ab, indicating the presence of slight inhomogeneities. The magnetization measurements reveal fish-tail effect in the hysteresis loop for both H//c and H//ab. Averaged critical current densities at low magnetic fields along the c-axis and ab-plane Jc(H//c) and Jc(H//ab) at 5 K are estimated to be 0.9*10^5 and 0.7*10^5 A/cm2, respectively. Resistive transitions under magnetic field show broadening, which is consistent with a relatively large anisotropy of upper critical field. Magneto-optical images reveal homogenous current flow within the ab-plane.

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preprint2011arXiv

Slow-light enhanced optical forces between longitudinally shifted photonic-crystal nanowire waveguides

We reveal that slow-light enhanced optical forces between side-coupled photonic-crystal nanowire waveguides can be flexibly controlled by introducing a relative longitudinal shift. We predict that close to the photonic band-edge, where the group velocity is reduced, the transverse force can be tuned from repulse to attractive, and the force is suppressed for a particular shift value. Additionally the shift leads to symmetry breaking that can facilitate longitudinal forces acting on the waveguides, in contrast to unshifted structures where such forces vanish.

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preprint2010arXiv

Study of the Spin-weighted Spheroidal Equation in the Case of s=1

We present series study of using the method of super-symmetric quantum mechanics(SUSYQM) solving the spin-weighted spheroidal wave equation. In this paper, we obtain the first four terms of super-potential of the spin-weighted spheroidal wave equation in the case of s=1. These results may help summary the general form for the n-th term of the super-potential, which is proved correct by means of induction. We finally compute the ground eigenvalues and ground eigenfunction. All the results may be of significative for studies of electromagnetic radiation processes near rotating black holes and compute radiation reaction in curved space-time.

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preprint2010arXiv

The Spin-weighted Spheroidal Wave functions in the Case of s=1/2

The spin-weighted spheroidal equations in the case s=1/2 is thoroughly studied in the paper by means of the perturbation method in supersymmetry quantum mechanics. The first-five terms of the super-potential in the series of the parameter beta are given. The general form of the nth term of the superpotential is also obtained, which could derived from the previous terms W_{k}, k<n. From the results, it is easy to give the ground eigenfunction of the equation. Furthermore, the shape-invariance property is investigated in the series form of the parameter beta and is proven kept in this series form for the equations. This nice property guarantee one could obtain the excited eigenfunctions in the series form from the ground eigenfunctions by the method in supersymmetry quantum mechanics. This shows the perturbation method method in supersymmetry quantum mechanics could solve the spin-weight spheroidal wave equations completely in the series form of the small parameter beta.

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