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Physical Review B 2025年第15期111卷 155423-155423页

作者： Yuan Hong Zhen-Guo Fu Zhou-Wei-Yu Chen Feng Chi Zhigang Wang Wei Zhang Ping Zhang Institute of Applied Physics and Computational Mathematics and National Key Laboratory of Computational Physics Beijing 100088 China Graduate School China Academy of Engineering Physics Beijing 100088 China School of Mathematics and Computational Science Xiangtan University Xiangtan 411105 China School of Electronic and Information Engineering Zhongshan Institute University of Electronic Science and Technology of China Zhongshan 528400 China

We study the quantum transport in double quantum dots (DQD) sandwiched between surfaces of topological insulator (TI) Bi2Te3, which possess strong spin-orbit coupling (SOC) and dC3v double group symmetry. Different from the spin-conserved case with two-dimensional electron gas (2DEG) electrodes, the conductance displays a universal scaling relation for different Fermi energy associated with the topological nature/linear dispersion of topological surface states. The interplay between direct interdot tunneling and surface state mediated interaction leads to tunable Dicke and Fano effects with changing the interdot distance. We propose nano-rulers with different measurement range and resolution based on the Fano q-factor. Furthermore, when applying an in-plane Zeeman field, a crossover from a double-peak shape to a quad-peak shape in conductance curve appears. Moreover, the rotational symmetry of the system could also be revealed from the conductance pattern. Our findings contribute to a better understanding of the quantum transport in the presence of electrode's SOC topological states.

关键词： Surface states

Thermal disorder and phonon softening in the ferroelectric phase transition of lead titanate

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Physical Review B 2025年第9期111卷 094113-094113页

作者： Pinchen Xie Yixiao Chen Weinan E Roberto Car Program in Applied and Computational Mathematics Princeton University Princeton New Jersey 08544 USA AI for Science Institute Beijing China and Center for Machine Learning Research and School of Mathematical Sciences Peking University Beijing China

We report a molecular dynamics study of ab initio quality of the ferroelectric phase transition in crystalline PbTiO3. We model anharmonicity accurately in terms of potential energy and polarization surfaces trained on density functional theory data with modern machine learning techniques. Our simulations demonstrate that the transition has a strong order-disorder character, in agreement with diffraction experiments, and provide fresh insight into the approach to equilibrium across the phase transition. We find that the emergence and disappearance of the macroscopic polarization is driven by dipolar switching at the nanometer scale. We also computed the infrared optical absorption spectra in both the ferroelectric and the paraelectric phases, finding good agreement with the experimental Raman frequencies. Often, the almost ideal displacive character of the soft mode detected by Raman scattering in the paraelectric phase has been contrasted with the order-disorder character of the transition suggested by diffraction experiments. We settle this issue by showing that the soft mode coexists with a strong Debye relaxation associated with thermal disordering of the dipoles. The Debye relaxation feature is centered at zero frequency and appears near the transition temperature in both the ferroelectric and the paraelectric phases.

关键词： Ferroelectricity

Synergetic effects of multiple junction and surface hydroxyl in Cu/CuO/Cu2O/TiO2 heterostructures towards highly efficient photocatalysts for hydrogen generation

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Materials science for Energy Technologies 2025年 8卷 131-142页

作者： Subagyo, Riki Anindika, Garcelina Rizky Aufkani, Afif Akmal Zhang, Lei Ardhyananta, Hosta Burhan, R.Y. Perry Nugraheni, Zjahra Vianita Akhlus, Syafsir Bahruji, Hasliza Prasetyoko, Didik Wellia, Diana Vanda Ivansyah, Atthar Luqman Arramel Kusumawati, Yuly Department of Chemistry Faculty of Science and Analytic Data Institut Teknologi Sepuluh Nopember Surabaya60111 Indonesia Center of Excellence Applied Physics and Chemistry Nano Center Indonesia Jl PUSPIPTEK South Tangerang Banten15314 Indonesia Department of Physics National University of Singapore Singapore117551 Singapore Department of Materials and Metallurgical Engineering Faculty of Industrial Technology and Systems Engineering Institut Teknologi Sepuluh Nopember Surabaya60111 Indonesia Centre of Advanced Material and Energy Science Universiti Brunei Darussalam Jalan Tungku Link BE 1410 Brunei Department of Chemistry Faculty of Mathematics and Natural Sciences Universitas Andalas Padang25163 Indonesia Master Program in Computational Science Faculty of Mathematics and Natural Science Institut Teknologi Bandung Jalan Ganesha No. 10 Bandung40132 Indonesia Instrumentation and Computational Physics Research Group Department of Physics Faculty of Mathematics and Natural Sciences Institut Teknologi Bandung Jalan Ganesha No.10 West Java Bandung40132 Indonesia

The implementation of titanium dioxide (TiO2) as a photocatalyst material in hydrogen (H2) evolution reaction (HER) has embarked renewed interest in the past decade. Rapid electron-hole pairs recombination and wide band gap of a photo-sensitive material of TiO2 are detrimental toward the targeted catalytical reaction. In this study, we present the rational design, fabrication, photocatalytic performance of TiO2-Cu/CuO/Cu2O heterostructures (CuTi) using viable chemical reduction method. The Z-scheme and S-scheme are succesfully generated across the TiO2/CuO/Cu2O interfaces, while the Schottky junction arises on the Cu perimeters. This is evidenced from the blue shifted about 0.3 eV of Cu 2p core level determined by using X-ray photoemission spectroscopy (XPS), in combination with the formation of inverse V-shape of the Mott-Schottky plots. In addition, we find that Cu/CuO/Cu2O facilitates photon absorption range up to the visible region. The multiple heterojunction and the large number of OHsurface enhanced charge carrier transfer are associated to the suppression of photoluminescence (PL) intensity, high surface hydroxyl (OHsurface) density in CuTi probed by XPS, and fast electron transfer based on the electrochemical measurements. The presence of OHsurface inhibits the recombination of electron. A significant H2 photogeneration rate enhancement is achieved when an optimized 5 wt% Cu/CuO/Cu2O concentration is used on TiO2 to achieve 7,157.19 μmol·g−1 (1,789.30 μmol·g−1·h−1). Based on this finding, zero emission energy innitiative could be materialized under multiple heterojunctions in photocatalytic process is beneficial for enhancing the H2 production. © 2025 The Authors

关键词： Titanium dioxide

Hiring under Congestion and Algorithmic Monoculture: Value of Strategic Behavior

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arXiv 2025年

作者： Baek, Jackie Bastani, Hamsa Chen, Shihan Stern School of Business New York University United States Wharton School University of Pennsylvania United States Graduate Group in Applied Mathematics and Computational Science University of Pennsylvania United States

We study the impact of strategic behavior in a setting where firms compete to hire a shared pool of applicants, and firms use a common algorithm to evaluate the applicants. Each applicant is associated with a scalar score that is observed by all firms, provided by the algorithm. Firms simultaneously make interview decisions, where the number of interviews is capacity-constrained. Job offers are given to those who pass the interview, and an applicant who receives multiple offers accept one of them uniformly at random. We fully characterize the set of Nash equilibria under this model. Defining social welfare as the total number of applicants hired, we then compare the social welfare at a Nash equilibrium to a naive baseline where all firms interview applicants with the highest scores. We show that the Nash equilibrium greatly improves upon social welfare compared to the naive baseline, especially when the interview capacity is small and the number of firms is large. We also show that the price of anarchy is small, providing further appeal for the equilibrium solution. We then study how the firms may converge to a Nash equilibrium. We show that when firms make interview decisions sequentially and each firm takes the best response action assuming they are the last to act, this process converges to an equilibrium when interview capacities are small. However, we show that the task of computing the best response is difficult if firms have to use its own historical samples to estimate it, while this task becomes trivial if firms have information on the degree of competition for each applicant. Therefore, converging to an equilibrium can be greatly facilitated if firms have information on the level of competition for each applicant. Copyright © 2025, The Authors. All rights reserved.

关键词： Nash equilibrium

Machine learning of microstructure–property relationships in materials with robust features from foundational vision transformers

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arXiv 2025年

作者： Whitman, Sheila E. Latypov, Marat I. Graduate Interdisciplinary Program in Applied Mathematics University of Arizona TucsonAZ85721 United States Department of Materials Science and Engineering University of Arizona TucsonAZ85721 United States

Machine learning of microstructure–property relationships from data is an emerging approach in computational materials science. Most existing machine learning efforts focus on the development of task-specific models for each microstructure–property relationship. We propose utilizing pre-trained foundational vision transformers for the extraction of task-agnostic microstructure features and subsequent light-weight machine learning of a microstructure-dependent property. We demonstrate our approach with pre-trained state-of-the-art vision transformers (CLIP, DINOV2, SAM) in two case studies on machine-learning: (i) elastic modulus of two-phase microstructures based on simulations data;and (ii) Vicker’s hardness of Ni-base and Co-base superalloys based on experimental data published in literature. Our results show the potential of foundational vision transformers for robust microstructure representation and efficient machine learning of microstructure–property relationships without the need for expensive task-specific training or fine-tuning of bespoke deep learning models. © 2025, CC BY.

关键词： Elastic moduli

Unbiased Parameter Estimation for Bayesian Inverse Problems

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arXiv 2025年

作者： Chada, Neil K. Jasra, Ajay Maama, Mohamed Tempone, Raul Department of Mathematics City University of Hong Kong China School of Data Science The Chinese University of Hong Kong Shenzhen CN Shenzhen China Applied Mathematics and Computational Science Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia

In this paper we consider the estimation of unknown parameters in Bayesian inverse problems. In most cases of practical interest, there are several barriers to performing such estimation, This includes a numerical approximation of a solution of a differential equation and, even if exact solutions are available, an analytical intractability of the marginal likelihood and its associated gradient, which is used for parameter estimation. The focus of this article is to deliver unbiased estimates of the unknown parameters, that is, stochastic estimators that, in expectation, are equal to the maximizer of the marginal likelihood, and possess no numerical approximation error. Based upon the ideas of [4] we develop a new approach for unbiased parameter estimation for Bayesian inverse problems. We prove unbiasedness and establish numerically that the associated estimation procedure is faster than the current state-of-the-art methodology for this problem. We demonstrate the performance of our methodology on a range of problems which include a PDE and ODE. Copyright © 2025, The Authors. All rights reserved.

关键词： Markov processes

Are there type-III multiferroics?

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arXiv 2025年

作者： Wang, Haojin Liu, Haitao Ye, Meng Li, Yuanchang Advanced Research Institute of Multidisciplinary Science Beijing Institute of Technology Beijing100081 China Institute of Applied Physics and Computational Mathematics Beijing100088 China National Key Laboratory of Computational Physics Beijing100088 China Graduate School of China Academy of Engineering Physics Beijing100193 China

Multiferroics are known to be classified into two types. However, type-I lacks sufficient magnetoelectric coupling and type-II lacks sufficient electric polarization, making both practically difficult. In this work, we explore the possibility of type-III multiferroics, where the origins of ferroelectricity and magnetism are highly intertwined but not causally related, with a combination of strong magnetoelectric coupling and large polarization. Our first-principles calculations predict that monolayer TiCdO4 is such a type-III ferroelectric-ferromagnetic multiferroics with both electronic and magnetic orders originating from competing electron populations on oxygen atoms. It shows an electric polarization of 50 µC/m2 while the maximum linear and quadratic magnetoelectric response are as high as 35000 ps/m and 1.59 × 10−14 s/A, respectively. Our study opens up new perspectives for the discovery and design of much-anticipated multiferroics that can be used for cross-modulation. © 2025, CC BY.

关键词： Ferroelectricity

Integrating Chain-of-Thought and Retrieval Augmented Generation Enhances Rare Disease Diagnosis from Clinical Notes

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arXiv 2025年

作者： Wu, Da Wang, Zhanliang Nguyen, Quan Wang, Kai Raymond G. Perelman Center for Cellular and Molecular Therapeutics Children's Hospital of Philadelphia PhiladelphiaPA19104 United States Applied Mathematics and Computational Science Graduate Program University of Pennsylvania PhiladelphiaPA19104 United States Bioengineering Graduate Program University of Pennsylvania PhiladelphiaPA19104 United States Department of Pathology and Laboratory Medicine Perelman School of Medicine University of Pennsylvania PhiladelphiaPA19104 United States

Background: Several studies show that large language models (LLMs) struggle with phenotype-driven gene prioritization for rare diseases. These studies typically use Human Phenotype Ontology (HPO) terms to prompt foundation models like GPT and LLaMA to predict candidate genes. However, in real-world settings, foundation models are not optimized for domain-specific tasks like clinical diagnosis, yet inputs are unstructured clinical notes rather than standardized terms. How LLMs can be instructed to predict candidate genes or disease diagnosis from unstructured clinical notes remains a major challenge. Methods: We introduce RAG-driven CoT and CoT-driven RAG, two methods that combine Chain-of-Thought (CoT) and Retrieval Augmented Generation (RAG) to analyze clinical notes. A five-question CoT protocol mimics expert reasoning, while RAG retrieves data from sources like HPO and OMIM (Online Mendelian Inheritance in Man). We evaluated these approaches on rare disease datasets, including 5,980 Phenopacket-derived notes, 255 literature-based narratives, and 220 in-house clinical notes from Children’s Hospital of Philadelphia. Results: We found that recent foundations models, including Llama 3.3-70B-Instruct and DeepSeek-R1-Distill-Llama-70B, outperformed earlier versions such as Llama 2 and GPT-3.5. We also showed that RAG-driven CoT and CoT-driven RAG both outperform foundation models in candidate gene prioritization from clinical notes;in particular, both methods with DeepSeek backbone resulted in a top-10 gene accuracy of over 40% on Phenopacket-derived clinical notes. RAG-driven CoT works better for high-quality notes, where early retrieval can anchor the subsequent reasoning steps in domain-specific evidence, while CoT-driven RAG has advantage when processing lengthy and noisy notes. Conclusions: Integrating CoT and RAG enhances LLMs’ understanding of clinical notes in the context of rare disease diagnosis, and can facilitate various downstream medical tasks. © 2025, CC

关键词： Chains

Complete Characterizations of Intermediate and Final State Wave Functions with Photoionization of Polarized Rb

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Physical Review Letters 2025年第12期134卷 123204-123204页

作者： Huanyu Ma Linxuan Zhang Xincheng Wang Zhihan Zou Rujin Lv Zhenjie Shen Ahai Chen Matthias Weidemüller Kiyoshi Ueda Center for Transformative Science and School of Physical Science and Technology ShanghaiTech University Shanghai 201210 China Shanghai Advanced Research Institute Chinese Academy of Sciences Shanghai 201210 China National Key Laboratory of Computational Physics Institute of Applied Physics and Computational Mathematics Beijing 100088 China Graduate School China Academy of Engineering Physics Beijing 100193 China Physikalisches Institut Universität Heidelberg Im Neuenheimer Feld 226 69120 Heidelberg Germany

The amplitude and phase of a photoionization channel provide deep insights into the nature of ionization dynamics. Here, we propose a novel experimental approach to retrieve these parameters from the photoelectron momentum distribution (PMD), where a 400 nm femtosecond laser is used to ionize polarized Rb atoms prepared in the 5p state. The magnetic quantum numbers of polarized atoms are well controlled by breaking down the symmetry of the cooling laser in a magneto-optical trap reaction microscope. From the tilt angle of the PMD and the interference structure of εs and εd ionization channels, we are able to extract their relative amplitude and phase shift, in good agreement with ab initio calculations. This exhibits a benchmark one-photon single ionization study of the hydrogen-like atom, providing a complete measurement with full characterizations of intermediate and final state wave functions.

关键词： Wave functions

Effective Dimension Aware Fractional-Order Stochastic Gradient Descent for Convex Optimization Problems

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arXiv 2025年

作者： Partohaghighi, Mohammad Marcia, Roummel Chen, YangQuan Electrical Engineering and Computer Science graduate program University of California Merced United States Department of Applied Mathematics University of California Merced MercedCA United States Lab Department of Mechanical Engineering School of Engineering University of California MercedCA95343 United States

Fractional-order stochastic gradient descent (FOSGD) leverages a fractional exponent to capture long-memory effects in optimization, yet its practical impact is often constrained by the difficulty of tuning and stabilizing this exponent. In this work, we introduce 2SED Fractional-Order Stochastic Gradient Descent (2SEDFOSGD), a novel method that synergistically combines the Two-Scale Effective Dimension (2SED) algorithm with FOSGD to automatically calibrate the fractional exponent in a data-driven manner. By continuously gauging model sensitivity and effective dimensionality, 2SED dynamically adjusts the exponent to curb erratic oscillations and enhance convergence rates. Theoretically, we demonstrate how this dimension-aware adaptation retains the benefits of fractional memory while averting the sluggish or unstable behaviors frequently observed in naive fractional SGD. Empirical evaluations across multiple benchmarks confirm that our 2SED-driven fractional exponent approach not only converges faster but also achieves more robust final performance, suggesting broad applicability for fractional-order methodologies in large-scale machine learning and related domains. © 2025, CC BY.

关键词： Convex optimization