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Jie Gu

Jie Gu contributes to research discovery and scholarly infrastructure.

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Published work

18 published item(s)

preprint2026arXiv

Counterexamples to the conjectured ordering between the waiting-time bound and the thermodynamic uncertainty bound on entropy production

Two widely used model-free lower bounds on the steady-state entropy production rate of a continuous-time Markov jump process are the thermodynamic uncertainty relation (TUR) bound $σ_\text{TUR}$, derived from the mean and variance of a current, and the waiting-time distribution (WTD) bound $σ_\mathcal{L}$, derived from the irreversibility of partially observed transition sequences together with their waiting times. It has been conjectured that $σ_{\mathcal L}$ is always at least as tight as $σ_{\mathrm{TUR}}$ when both are constructed from the same partially observed link. Here we provide four-state counterexamples in a nonequilibrium steady state where $σ_{\mathcal L}<σ_{\mathrm{TUR}}$. This result shows that no universal ordering exists between these two inference bounds under partial observation.

preprint2026arXiv

DeformMaster: An Interactive Physics-Neural World Model for Deformable Objects from Videos

World models for deformable objects should recover not only geometry and appearance, but also underlying physical dynamics, interaction grounding, and material behavior. Learning such a model from real videos is challenging because deformable linear, planar, and volumetric objects evolve under high-dimensional deformation, noisy interactions, and complex material response. The model must therefore infer a physical state from visual observations, roll it forward under new interactions, and render the resulting dynamics with high visual fidelity. We present DeformMaster, a video-derived interactive physics--neural world model that turns real interaction videos into an online interactive model of deformable objects within a unified dynamics-and-appearance framework. DeformMaster preserves structured physical rollout while using a neural residual to compensate for unmodeled effects, grounds sparse hand motion as distributed compliant actuator for hand--continuum interaction, represents material response with spatially varying constitutive experts, and drives high-fidelity 4D appearance from the predicted physical evolution. Experiments on real-world deformable-object sequences demonstrate DeformMaster's ability to roll out future dynamics and render dynamic appearance, outperforming state-of-the-art baselines while supporting novel action rollout, material-parameter variation, and dynamic novel-view synthesis.

preprint2022arXiv

Automated machine learning for secure key rate in discrete-modulated continuous-variable quantum key distribution

Continuous-variable quantum key distribution (CV QKD) with discrete modulation has attracted increasing attention due to its experimental simplicity, lower-cost implementation and compatibility with classical optical communication. Correspondingly, some novel numerical methods have been proposed to analyze the security of these protocols against collective attacks, which promotes key rates over one hundred kilometers of fiber distance. However, numerical methods are limited by their calculation time and resource consumption, for which they cannot play more roles on mobile platforms in quantum networks. To improve this issue, a neural network model predicting key rates in nearly real time has been proposed previously. Here, we go further and show a neural network model combined with Bayesian optimization. This model automatically designs the best architecture of neural network computing key rates in real time. We demonstrate our model with two variants of CV QKD protocols with quaternary modulation. The results show high reliability with secure probability as high as $99.15\%-99.59\%$, considerable tightness and high efficiency with speedup of approximately $10^7$ in both cases. This inspiring model enables the real-time computation of unstructured quantum key distribution protocols&#39; key rate more automatically and efficiently, which has met the growing needs of implementing QKD protocols on moving platforms.

preprint2022arXiv

Continuous and Distribution-free Probabilistic Wind Power Forecasting: A Conditional Normalizing Flow Approach

We present a data-driven approach for probabilistic wind power forecasting based on conditional normalizing flow (CNF). In contrast with the existing, this approach is distribution-free (as for non-parametric and quantile-based approaches) and can directly yield continuous probability densities, hence avoiding quantile crossing. It relies on a base distribution and a set of bijective mappings. Both the shape parameters of the base distribution and the bijective mappings are approximated with neural networks. Spline-based conditional normalizing flow is considered owing to its non-affine characteristics. Over the training phase, the model sequentially maps input examples onto samples of base distribution, given the conditional contexts, where parameters are estimated through maximum likelihood. To issue probabilistic forecasts, one eventually maps samples of the base distribution into samples of a desired distribution. Case studies based on open datasets validate the effectiveness of the proposed model, and allows us to discuss its advantages and caveats with respect to the state of the art.

preprint2022arXiv

Dielectric catastrophe at the Mott and Wigner transitions in a moiré superlattice

The metal-insulator transition (MIT) driven by electronic correlations is a fundamental and challenging problem in condensed-matter physics. Particularly, whether such a transition can be continuous remains open. The emergence of semiconducting moiré materials with continuously tunable bandwidth provides an ideal platform to study interaction-driven MITs. Although a bandwidth-tuned MIT at fixed full electron filling of the moiré superlattice has been reported recently, that at fractional filling, which involves translational symmetry breaking of the underlying superlattice, remains elusive. Here, we demonstrate bandwidth-tuned MITs in a MoSe2/WS2 moiré superlattice at both integer and fractional fillings using the exciton sensing technique. The bandwidth is controlled by an out-of-plane electric field. The dielectric response is probed optically with the 2s exciton in a remote WSe2 sensor layer. The exciton spectral weight is negligible for the metallic state, consistent with a large negative dielectric constant. It continuously vanishes when the transition is approached from the insulating side, corresponding to a diverging dielectric constant or a &#34;dielectric catastrophe&#34;. Our results support continuous interaction-driven MITs in a two-dimensional triangular lattice and stimulate future explorations of exotic quantum phases, such as quantum spin liquids, in their vicinities.

preprint2022arXiv

Peacock patterns and new integer invariants in topological string theory

Topological string theory near the conifold point of a Calabi-Yau threefold gives rise to factorially divergent power series which encode the all-genus enumerative information. These series lead to infinite towers of singularities in their Borel plane (also known as &#34;peacock patterns&#34;), and we conjecture that the corresponding Stokes constants are integer invariants of the Calabi-Yau threefold. We calculate these Stokes constants in some toric examples, confirming our conjecture and providing in some cases explicit generating functions for the new integer invariants, in the form of q-series. Our calculations in the toric case rely on the TS/ST correspondence, which promotes the asymptotic series near the conifold point to spectral traces of operators, and makes it easier to identify the Stokes data. The resulting mathematical structure turns out to be very similar to the one of complex Chern-Simons theory. In particular, spectral traces correspond to state integral invariants and factorize in holomorphic/anti-holomorphic blocks.

preprint2022arXiv

Peacock patterns and resurgence in complex Chern-Simons theory

The partition function of complex Chern-Simons theory on a 3-manifold with torus boundary reduces to a finite dimensional state-integral which is a holomorphic function of a complexified Planck&#39;s constant $τ$ in the complex cut plane and an entire function of a complex parameter $u$. This gives rise to a vector of factorially divergent perturbative formal power series whose Stokes rays form a peacock-like pattern in the complex plane. We conjecture that these perturbative series are resurgent, their trans-series involve two non-perturbative variables, their Stokes automorphism satisfies a unique factorization property and that it is given explicitly in terms of a fundamental matrix solution to a (dual) linear $q$-difference equation. We further conjecture that entries of the Stokes automorphism matrix are the 3D-indices of Dimofte-Gaiotto-Gukov. We provide proofs of our statements regarding the $q$-difference equations and their properties of their fundamental solutions and illustrate our conjectures regarding the Stokes matrices with numerical calculations for the two simplest hyperbolic $4_1$ and $5_2$ knots.

preprint2022arXiv

The descendants of the 3d-index

In the study of 3d-3d correspondence occurs a natural $q$-Weyl algebra associated to an ideal triangulation of a 3-manifold with torus boundary components, and a module of it. We study the action of this module on the (rotated) 3d-index of Dimofte-Gaiotto-Gukov and we conjecture some structural properties: bilinear factorization in terms of holomorphic blocks, pair of linear $q$-difference equations, the determination of the 3d-index in terms of a finite size matrix of rational functions and the asymptotic expansion of the $q$-series as $q$ tends to 1 to all orders. We illustrate our conjectures with computations for the case of the three simplest hyperbolic knots.

preprint2021arXiv

Sequential Convolutional Recurrent Neural Networks for Fast Automatic Modulation Classification

A novel and efficient end-to-end learning model for automatic modulation classification is proposed for wireless spectrum monitoring applications, which automatically learns from the time domain in-phase and quadrature data without requiring the design of hand-crafted expert features. With the intuition of convolutional layers with pooling serving as the role of front-end feature distillation and dimensionality reduction, sequential convolutional recurrent neural networks are developed to take complementary advantage of parallel computing capability of convolutional neural networks and temporal sensitivity of recurrent neural networks. Experimental results demonstrate that the proposed architecture delivers overall superior performance in signal to noise ratio range above -10~dB, and achieves significantly improved classification accuracy from 80\% to 92.1\% at high signal to noise ratio range, while drastically reduces the average training and prediction time by approximately 74% and 67%, respectively. Response patterns learned by the proposed architecture are visualized to better understand the physics of the model. Furthermore, a comparative study is performed to investigate the impacts of various sequential convolutional recurrent neural network structure settings on classification performance. A representative sequential convolutional recurrent neural network architecture with the two-layer convolutional neural network and subsequent two-layer long short-term memory neural network is developed to suggest the option for fast automatic modulation classification.

preprint2020arXiv

Dimensional Pricing Based on Dynamism of Load

Electricity supply is not simply a matter of quantity, but a time lasting service that matches with a wave-like load curve. It logically deserves a pricing based on the curve per se rather than simply integral of load. This paper introduces to price electricity consumption based on dynamism of load, which is an equivalent characterization of load. Orthonormal basis with definable and distinguishable periodicity that can linearly express load curves constitutes a space to capture the dynamism, where coefficients of the basis quantify the dynamism in multiple dimensions. A price function is proposed to map the coefficients to a numerical charge. A pricing model on the space specialized by the Fourier series is derived for the simplest one-source-one-subscriber system and generalized to a single-bus system with multiple sources and multiple subscribers. Examples will demonstrate the use of the proposed pricing and its effectiveness in reflecting the cost of generation to cope with load dynamism and guaranteeing fairness.

preprint2020arXiv

Non-perturbative approaches to the quantum Seiberg-Witten curve

We study various non-perturbative approaches to the quantization of the Seiberg-Witten curve of ${\cal N}=2$, $SU(2)$ super Yang-Mills theory, which is closely related to the modified Mathieu operator. The first approach is based on the quantum WKB periods and their resurgent properties. We show that these properties are encoded in the TBA equations of Gaiotto-Moore-Neitzke determined by the BPS spectrum of the theory, and we relate the Borel-resummed quantum periods to instanton calculus. In addition, we use the TS/ST correspondence to obtain a closed formula for the Fredholm determinant of the modified Mathieu operator. Finally, by using blowup equations, we explain the connection between this operator and the $τ$ function of Painleve $\rm III$.

preprint2020arXiv

Spatially mixed moiré excitons in two-dimensional van der Waals superlattices

Moiré superlattices open an unprecedented opportunity for tailoring interactions between quantum particles and their coupling to electromagnetic fields. Strong superlattice potential generates moiré minibands of excitons -- bound pairs of electrons and holes that reside either in a single layer (intralayer excitons) or two separate layers (interlayer excitons). The twist-angle-controlled interlayer hybridization of carriers can also mix the two types of excitons to combine the strengths of both. Here, we report a direct observation of spatially mixed moiré excitons in angle-aligned WSe2/WS2 and MoSe2/WS2 superlattices by optical reflectance spectroscopy. The strongly interacting interlayer and intralayer moiré excitons in WSe2/WS2 manifest energy level anticrossing and oscillator strength redistribution under a vertical electric field. We also observe doping-dependent exciton miniband renormalization and mixing near half filling of the first electron miniband of WS2. Our findings have significant implications for emerging correlated states in two-dimensional semiconductors, such as exciton condensates and Bose-Hubbard models, and optoelectronic applications of these materials.

preprint2020arXiv

Three Jahn-Teller states of matter in the spin-crossover system Mn(taa)

Three high-spin phases recently discovered in the spin-crossover system Mn(taa) are identified through analysis by a combination of first-principles calculations and Monte Carlo simulation as a low-temperature Jahn-Teller ordered (solid) phase, an intermediate-temperature dynamically correlated (liquid) phase, and an uncorrelated (gas) phase. In particular, the Jahn-Teller liquid phase arises from competition between mixing with low-spin impurities, which drive the disorder, and inter-molecular strain interactions. The latter are a key factor in both the spin-crossover phase transition and the magnetoelectric coupling. Jahn-Teller liquids may exist in other spin-crossover materials and materials that have multiple equivalent Jahn-Teller axes.

preprint2019arXiv

A Room Temperature Polariton Light-Emitting Diode Based on Monolayer WS2

Half-light half-matter quasiparticles termed exciton-polaritons arise through the strong coupling of excitons and cavity photons. They have been used to demonstrate a wide array of fundamental phenomena and potential applications ranging from Bose-Einstein like condensation to analog Hamiltonian simulators and chip-scale interferometers. Recently the two dimensional transition metal dichalcogenides (TMDs) owing to their large exciton binding energies, oscillator strength and valley degree of freedom have emerged as a very attractive platform to realize exciton-polaritons at elevated temperatures. Achieving electrical injection of polaritons is attractive both as a precursor to realizing electrically driven polariton lasers as well as for high speed light-emitting diodes (LED) for communication systems. Here we demonstrate an electrically driven polariton LED operating at room temperature using monolayer tungsten disulphide (WS2) as the emissive material. To realize this device, the monolayer WS2 is sandwiched between thin hexagonal boron nitride (hBN) tunnel barriers with graphene layers acting as the electrodes. The entire tunnel LED structure is embedded inside a one-dimensional distributed Bragg reflector (DBR) based microcavity structure. The extracted external quantum efficiency is ~0.1% and is comparable to recent demonstrations of bulk organic and carbon nanotube based polariton electroluminescence (EL) devices. The possibility to realize electrically driven polariton LEDs in atomically thin semiconductors at room temperature presents a promising step towards achieving an inversionless electrically driven laser in these systems as well as for ultrafast microcavity LEDs using van der Waals materials.

preprint2019arXiv

Elliptic Blowup Equations for 6d SCFTs. II: Exceptional Cases

The building blocks of 6d $(1,0)$ SCFTs include certain rank one theories with gauge group $G=SU(3),SO(8),F_4,E_{6,7,8}$. In this paper, we propose a universal recursion formula for the elliptic genera of all such theories. This formula is solved from the elliptic blowup equations introduced in our previous paper. We explicitly compute the elliptic genera and refined BPS invariants, which recover all previous results from topological string theory, modular bootstrap, Hilbert series, 2d quiver gauge theories and 4d $\mathcal{N}=2$ superconformal $H_{G}$ theories. We also observe an intriguing relation between the $k$-string elliptic genus and the Schur indices of rank $k$ $H_{G}$ SCFTs, as a generalization of Lockhart-Zotto&#39;s conjecture at the rank one cases. In a subsequent paper, we deal with all other non-Higgsable clusters with matters.

preprint2019arXiv

Elliptic Blowup Equations for 6d SCFTs. III: E-strings, M-strings and Chains

We establish the elliptic blowup equations for E-strings and M-strings and solve elliptic genera and refined BPS invariants from them. Such elliptic blowup equations can be derived from a path integral interpretation. We provide toric hypersurface construction for the Calabi-Yau geometries of M-strings and those of E-strings with up to three mass parameters turned on, as well as an approach to derive the perturbative prepotential directly from the local description of the Calabi-Yau threefolds. We also demonstrate how to systematically obtain blowup equations for all rank one 5d SCFTs from E-string by blow-down operations. Finally, we present blowup equations for E-M and M string chains.

preprint2019arXiv

Enhanced nonlinear interaction of polaritons via excitonic Rydberg states in monolayer WSe2

Strong optical nonlinearities play a central role in realizing quantum photonic technologies. In solid state systems, exciton-polaritons, which result from the hybridization of material excitations and cavity photons, are an attractive candidate to realize such nonlinearities. Here, the interaction between excitons forms the basis of the polaritonic nonlinearity. While the interaction between ground state excitons generates a notable optical nonlinearity, the strength of such ground state interactions is generally not sufficient to reach the regime of quantum nonlinear optics and strong single-polariton interactions. Excited states, however, feature enhanced interactions and therefore hold promise for accessing the quantum domain of single-photon nonlinearities, as demonstrated with high-lying Rydberg states of cold atomic systems. Excitons in excited states have recently been observed in monolayer transition metal dichalcogenides. Here we demonstrate the formation of exciton-polaritons using the first excited excitonic state in monolayer tungsten diselenide (WSe2) embedded in a microcavity. Owing to the larger exciton size compared to their ground state counterpart, the realized polaritons exhibit an enhanced nonlinear response by more than an order of magnitude, as evidenced through a modification of the cavity Rabi splitting. The demonstration of excited exciton-polaritons in two-dimensional semiconductors and their enhanced nonlinear response presents the first step towards the generation of strong photon interactions in solid state systems, a necessary building block for quantum photonic technologies.