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Wentao Yang

Publications and source records attributed to Wentao Yang.

34 records · Page 2Linked to original sources

Cooperative Energy Scheduling of Multi-Microgrids Based on Risk-Sensitive Reinforcement Learning

With the rapid development of distributed renewable energy, multi-microgrids play an increasingly important role in improving the flexibility and reliability of energy supply. Reinforcement learning has shown great potential in coordination strategies due to its model-free nature. Current methods lack explicit quantification of the relationship between individual and joint risk values, resulting in obscured credit assignment. Moreover, they often depend on explicit communication, which becomes inefficient as system complexity grows. To address these challenges, this paper proposes a risk-sensitive reinforcement learning framework with shared memory (RRL-SM) for multi-microgrid scheduling. Specifically, a risk-sensitive value factorization scheme is proposed to quantify the relationship between individual and joint risk values by leveraging distributional modeling and attention-based representations, thereby aligning local decisions with global risk objectives. An implicit shared-memory coordination mechanism is implemented through a global memory space to enhance the overall efficiency of decentralized decision-making. Collectively, the integrated approach delivers more reliable cooperative scheduling under renewable energy uncertainty. Simulation results show that RRL-SM reduces load-shedding risk by 84.5%, demonstrating a favorable balance between reliability and economic performance.

eess.SY↗

Adsorption Barrier Limits the Ice Inhibition Activity of Glycan-Rich Antifreeze Glycoproteins

Antifreeze glycoproteins (AFGPs) are among the most potent ice recrystallization inhibition (IRI) agents, yet the molecular basis for their counterintuitive decline in activity with increasing glycosylated threonine (T*) content remains unresolved. Through molecular dynamics simulations of model glycoproteins with increasing T* content, we show that potent IRI activity arises not only from the thermodynamic stability of strong ice-binding states, but also from their kinetic accessibility. Specifically, the free energy barrier for forming strong ice-binding states from the unbound state constitutes a critical kinetic bottleneck. Increasing T* content enhances the overall hydration capacity due to the additional glycan moieties, thereby imposing a greater desolvation penalty and elevating the adsorption barrier. This kinetic limitation, rather than the absence of strong ice-binding states, accounts for the experimentally observed decline in IRI activity. To quantify the structural basis of this behavior, we introduce a facial amphiphilicity index that integrates both spatial segregation and compositional ratio of hydrophilic and hydrophobic residues, and show that it correlates well with IRI activity. These findings highlight that facial amphiphilicity mediates a critical balance between binding stability and kinetic accessibility, providing a rational design principle for advanced IRI materials.

cond-mat.soft↗

Space-Optimized and Experimental Implementations of Regev's Quantum Factoring Algorithm

The integer factorization problem (IFP) underpins the security of RSA, yet becomes efficiently solvable on a quantum computer through Shor's algorithm. Regev's recent high-dimensional variant reduces the circuit size through lattice-based post-processing, but introduces substantial space overhead and lacks practical implementations. Here, we propose a qubit reuse method by intermediate-uncomputation that significantly reduces the space complexity of Regev's algorithm, inspired by reversible computing. Our basic strategy lowers the cost from \( O(n^{3/2}) \) to \( O(n^{5/4}) \), and refined strategies achieve \( O(n \log n) \)which is a space lower bound within this model. Simulations demonstrate the resulting time-space trade-offs and resource scaling. Moreover, we construct and compile quantum circuits that factor \( N = 35 \), verifying the effectiveness of our method through noisy simulations. A more simplified experimental circuit for Regev's algorithm is executed on a superconducting quantum computer, with lattice-based post-processing successfully retrieving the factors. These results advance the practical feasibility of Regev-style quantum factoring and provide guidance for future theoretical and experimental developments.

quant-ph↗

The Riemann Hypothesis Emerges in Dynamical Quantum Phase Transitions

The Riemann Hypothesis (RH), one of the most profound unsolved problems in mathematics, concerns the nontrivial zeros of the Riemann zeta function. Establishing connections between the RH and physical phenomena could offer new perspectives on its physical origin and verification. Here, we establish a direct correspondence between the nontrivial zeros of the zeta function and dynamical quantum phase transitions (DQPTs) in two realizable quantum systems, characterized by the averaged accumulated phase factor and the Loschmidt amplitude, respectively. This precise correspondence reveals that the RH can be viewed as the emergence of DQPTs at a specific temperature. We experimentally demonstrate this correspondence on a five-qubit spin-based system and further propose an universal quantum simulation framework for efficiently realizing both systems with polynomial resources, offering a quantum advantage for numerical verification of the RH. These findings uncover an intrinsic link between nonequilibrium critical dynamics and the RH, positioning quantum computing as a powerful platform for exploring one of mathematics' most enduring conjectures and beyond.

quant-ph↗

An NIP-like Notion in Abstract Elementary Classes

This paper is a contribution to "neo-stability" type of result for abstract elementary classes. Under certain set theoretic assumptions, we propose a definition and a characterization of NIP in AECs. The class of AECs with NIP properly contains the class of stable AECs. We show that for an AEC $K$ and $λ\geq LS(K)$, $K_λ$ is NIP if and only if there is a notion of nonforking on it which we call a w*-good frame. On the other hand, the negation of NIP leads to being able to encode subsets.

math.LO↗

Atomistic Insights into the Chain-Length-Dependent Antifreeze Activity of Oligoprolines

Ice recrystallization inhibition (IRI) activity of polymers generally increases with chain length. However, for polyproline (PPro), a highly potent cryoprotectant, the IRI activity varies nonmonotonically with the degree of polymerization (DP), i.e., DP=8 (P8) > DP=15 (P15) > DP=3 (P3). Herein, we employ molecular dynamics simulations to reveal the microscopic mechanism behind this nonmonotonic effect in PPro. Our findings indicate that the population of the PPII helix structure, which increases with DP, is not the primary reason for this effect. Instead, both single-molecule conformation and multi-molecule aggregation play critical roles. At the single-molecule level, PPro exhibits two types of thermodynamically stable conformations:linear (L) and coil (C), with the latter demonstrating enhanced IRI potency due to its stronger hydrophobicity and ice-binding capability. Notably, P8 has a higher content of the C conformation compared to P15, accounting for its superior IRI activity. Aligning with the conventional understandings, P3's lowest activity stems from its excessively small volume/coverage area on the ice surface. At the multi-molecule level, P15 shows a significantly higher tendency to aggregate than P8, which limits the ability of PPro molecules to fully spread at the ice-water interface and reduces their effective coverage of the ice surface, thereby diminishing its effectiveness. And P15's aggregation becomes significantly pronounced at high concentrations, amplifying the nonmonotonic effect. This work provides an atomistic insight into the nonmonotonic relationship between IRI activity and DP in PPro, offering valuable insights for the rational design of novel biocompatible antifreeze polymers.

cond-mat.soft↗

DocKylin: A Large Multimodal Model for Visual Document Understanding with Efficient Visual Slimming

Current multimodal large language models (MLLMs) face significant challenges in visual document understanding (VDU) tasks due to the high resolution, dense text, and complex layouts typical of document images. These characteristics demand a high level of detail perception ability from MLLMs. While increasing input resolution improves detail perception capability, it also leads to longer sequences of visual tokens, increasing computational costs and straining the models' ability to handle long contexts. To address these challenges, we introduce DocKylin, a document-centric MLLM that performs visual content slimming at both the pixel and token levels, thereby reducing token sequence length in VDU scenarios. We introduce an Adaptive Pixel Slimming (APS) preprocessing module to perform pixel-level slimming, increasing the proportion of informative pixels. Moreover, we propose a novel Dynamic Token Slimming (DTS) module to conduct token-level slimming, filtering essential tokens and removing others to adaptively create a more compact visual sequence. Experiments demonstrate DocKylin's promising performance across various VDU benchmarks and the effectiveness of each component.

cs.CV↗

On Stability and Existence of Models in Abstract Elementary Classes

For an abstract elementary class $\mathbf{K}$ and a cardinal $λ\geq LS(\mathbf{K})$, we prove under mild cardinal arithmetic assumptions, categoricity in two succesive cardinals, almost stability for $λ^+$-minimal types and continuity of splitting in $λ$, that stability in $λ$ is equivalent to the existence of a model in $λ^{++}$. The forward direction holds without any cardinal or categoricity assumptions, this result improves both [Vas18b, 12.1] and [MaYa24, 3.14]. Moreover, we prove a categoricity theorem for abstract elementary classes with weak amalgamation and tameness under mild structural assumptions in $λ$. A key feature of this result is that we do not assume amalgamation or arbitrarily large models.

math.LO↗

Hierarchical Side-Tuning for Vision Transformers

Fine-tuning pre-trained Vision Transformers (ViTs) has showcased significant promise in enhancing visual recognition tasks. Yet, the demand for individualized and comprehensive fine-tuning processes for each task entails substantial computational and memory costs, posing a considerable challenge. Recent advancements in Parameter-Efficient Transfer Learning (PETL) have shown potential for achieving high performance with fewer parameter updates compared to full fine-tuning. However, their effectiveness is primarily observed in simple tasks like image classification, while they encounter challenges with more complex vision tasks like dense prediction. To address this gap, this study aims to identify an effective tuning method that caters to a wider range of visual tasks. In this paper, we introduce Hierarchical Side-Tuning (HST), an innovative PETL method facilitating the transfer of ViT models to diverse downstream tasks. Diverging from existing methods that focus solely on fine-tuning parameters within specific input spaces or modules, HST employs a lightweight Hierarchical Side Network (HSN). This network leverages intermediate activations from the ViT backbone to model multi-scale features, enhancing prediction capabilities. To evaluate HST, we conducted comprehensive experiments across a range of visual tasks, including classification, object detection, instance segmentation, and semantic segmentation. Remarkably, HST achieved state-of-the-art performance in 13 out of the 19 tasks on the VTAB-1K benchmark, with the highest average Top-1 accuracy of 76.1%, while fine-tuning a mere 0.78M parameters. When applied to object detection and semantic segmentation tasks on the COCO and ADE20K testdev benchmarks, HST outperformed existing PETL methods and even surpassed full fine-tuning.

cs.CV↗

Building models in small cardinals in local abstract elementary classes

There are many results in the literature where superstablity-like independence notions, without any categoricity assumptions, have been used to show the existence of larger models. In this paper we show that \emph{stability} is enough to construct larger models for small cardinals assuming a mild locality condition for Galois types. $\mathbf{Theorem.}$ Suppose $λ<2^{\aleph_0}$. Let $\mathbf{K}$ be an abstract elementary class with $λ\geq LS(\mathbf{K})$. Assume $\mathbf{K}$ has amalgamation in $λ$, no maximal model in $λ$, and is stable in $λ$. If $\mathbf{K}$ is $(<λ^+, λ)$-local, then $\mathbf{K}$ has a model of cardinality $λ^{++}$. The set theoretic assumption that $λ<2^{\aleph_0}$ and model theoretic assumption of stability in $λ$ can be weakened to the model theoretic assumptions that $|\mathbf{S}^{na}(M)|< 2^{\aleph_0}$ for every $M \in \mathbf{K}_λ$ and stability for $λ$-algebraic types in $λ$. This is a significant improvement of Theorem 0.1., as the result holds on some unstable abstract elementary classes.

math.LO↗

Optimal Round and Sample-Size Complexity for Partitioning in Parallel Sorting

State-of-the-art parallel sorting algorithms for distributed-memory architectures are based on computing a balanced partitioning via sampling and histogramming. By finding samples that partition the sorted keys into evenly-sized chunks, these algorithms minimize the number of communication rounds required. Histogramming (computing positions of samples) guides sampling, enabling a decrease in the overall number of samples collected. We derive lower and upper bounds on the number of sampling/histogramming rounds required to compute a balanced partitioning. We improve on prior results to demonstrate that when using $p$ processors, $O(\log^* p)$ rounds with $O(p/\log^* p)$ samples per round suffice. We match that with a lower bound that shows that any algorithm with $O(p)$ samples per round requires at least $Ω(\log^* p)$ rounds. Additionally, we prove the $Ω(p \log p)$ samples lower bound for one round, thus proving that existing one round algorithms: sample sort, AMS sort and HSS have optimal sample size complexity. To derive the lower bound, we propose a hard randomized input distribution and apply classical results from the distribution theory of runs.

cs.DC↗

Phase shift and magnetic anisotropy induced field splitting of impurity states in (Li1-xFex)OHFeSe superconductor

Revealing the energy and spatial characteristics of impurity induced states in superconductors is essential for understanding their mechanism and fabricating new quantum state by manipulating impurities. Here by using high-resolution scanning tunneling microscopy/spectroscopy, we investigated the spatial distribution and magnetic field response of the impurity states in (Li1-xFex)OHFeSe. We detected two pairs of strong in-gap states on the "dumbbell" shaped defects. They display clear damped oscillations with different phase shifts and a direct phase-energy correlation. These features have long been predicted for classical Yu-Shiba-Rusinov (YSR) state, which are demonstrated here with unprecedented resolution for the first time. Moreover, upon applying magnetic field, all the in-gap state peaks remarkably split into two rather than shift, and the splitting strength is field orientation dependent. Via detailed numerical model calculations, we found such anisotropic splitting behavior can be naturally induced by a high-spin impurity coupled to anisotropic environment, highlighting how magnetic anisotropy affects the behavior of YSR states.

cond-mat.supr-con↗

Real-space Observation of Incommensurate Spin Density Wave and Coexisting Charge Density Wave on Cr(001) surface

In itinerant magnetic systems, a spin density wave (SDW) state can be induced by Fermi surface nesting and electron-electron interaction. It may intertwine with other orders such as charge density wave (CDW), while their relation is still yet to be understood. Here via spin-polarized scanning tunneling microscopy, we directly observed long-range spin modulation on Cr(001) surface, which corresponds to the well-known incommensurate SDW of bulk Cr. It displays 6.0 nm in-plane period and anti-phase behavior between adjacent (001) planes. Meanwhile, we simultaneously observed the coexisting CDW with half the period of SDW. Such SDW/CDW have highly correlated domain structures and are in-phase. Surprisingly, the CDW displays a contrast inversion around a density-of-states dip at -22 meV, indicating an anomalous CDW gap opened below EF. These observations support that the CDW is a secondary order driven by SDW. Our work is not only a real-space characterization of incommensurate SDW, but also provides insights on how SDW and CDW coexist.

cond-mat.mtrl-sci↗

Electronic structure and signature of Tomonaga-Luttinger liquid state in epitaxial CoSb$_{1-x}$ nanoribbons

Recently, monolayer CoSb/SrTiO$_3$ has been proposed as a candidate harboring interfacial superconductivity in analogy with monolayer FeSe/SrTiO$_3$. Experimentally, while the CoSb-based compounds manifesting as nanowires and thin films have been realized on SrTiO$_3$ substrates, serving as a rich playground, their electronic structures are still unknown and yet to be resolved. Here, we have fabricated CoSb$_{1-x}$ nanoribbons with quasi-one-dimensional stripes on SrTiO$_3$(001) substrates using molecular beam epitaxy, and investigated the electronic structure by in situ angle-resolved photoemission spectroscopy. Straight Fermi surfaces without lateral dispersions are observed. CoSb$_{1-x}$/SrTiO$_3$ is slightly hole doped, where the interfacial charge transfer is opposite to that in monolayer FeSe/SrTiO$_3$. The spectral weight near Fermi level exhibits power-law-like suppression and obeys a universal temperature scaling, serving as the signature of Tomonaga-Luttinger liquid (TLL) state. The obtained TLL parameter of $\sim$0.21 shows the underlying strong correlations. Our results not only suggest CoSb$_{1-x}$ nanoribbon as a representative TLL system, but also provide clues for further investigations on the CoSb-related interface.

cond-mat.str-el↗

High Accuracy Visible Light Positioning Based on Multi-target Tracking Algorithm

In this paper, we propose a multi-target image tracking algorithm based on continuously apative mean-shift (Cam-shift) and unscented Kalman filter. We improved the single-lamp tracking algorithm proposed in our previous work to multi-target tracking, and achieved better robustness in the case of occlusion, the real-time performance to complete one positioning and relatively high accuracy by dynamically adjusting the weights of the multi-target motion states. Our previous algorithm is limited to the analysis of tracking error. In this paper, the results of the tracking algorithm are evaluated with the tracking error we defined. Then combined with the double-lamp positioning algorithm, the real position of the terminal is calculated and evaluated with the positioning error we defined. Experiments show that the defined tracking error is 0.61cm and the defined positioning error for 3-D positioning is 3.29cm with the average processing time of 91.63ms per frame. Even if nearly half of the LED area is occluded, the tracking error remains at 5.25cm. All of this shows that the proposed visible light positioning (VLP) method can track multiple targets for positioning at the same time with good robustness, real-time performance and accuracy. In addition, the definition and analysis of tracking errors and positioning errors indicates the direction for future efforts to reduce errors.

eess.SP↗

Evidence of topological nodal lines and surface states in the centrosymmetric superconductor SnTaS2

The discovery of signatures of topological superconductivity in superconducting bulk materials with topological surface states has attracted intensive research interests recently. Utilizing angle-resolved photoemission spectroscopy and first-principles calculations, here, we demonstrate the existence of topological nodal-line states and drumheadlike surface states in centrosymmetric superconductor SnTaS2, which is a type-II superconductor with a critical transition temperature of about 3 K. The valence bands from Ta 5d orbitals and the conduction bands from Sn 5p orbitals cross each other, forming two nodal lines in the vicinity of the Fermi energy without the inclusion of spin-orbit coupling (SOC), protected by the spatial-inversion symmetry and time-reversal symmetry. The nodal lines are gapped out by SOC. The drumheadlike surface states, the typical characteristics in nodal-line semimetals, are quite visible near the Fermi level. Our findings indicate that SnTaS2 offers a promising platform for exploring the exotic properties of the topological nodal-line fermions and gives a help to study topological superconductivity.

cond-mat.supr-con↗