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Ni1+δ metallic state and purely Ni−dx2−y2-occupied Fermi surface in SrNiO2-based superlattices at ambient pressure

Physical Review Materials 2025年第4期9卷 044802-044802页

作者： Miao Li Zhenyu Ding Yuqiang Liu Liangyu Li Gang Wu Xiaoping Yang High Magnetic Field Laboratory HFIPS Chinese Academy of Sciences Hefei 230031 China Science Island Branch of Graduate School University of Science and Technology of China Hefei 230026 China Institute of High Performance Computing (IHPC) Agency for Science Technology and Research (ASTAR) 1 Fusionopolis Way #16-16 Connexis Singapore 138632 Singapore

The rich physics of nickelates has garnered widespread attention, particularly for their superconductivity and the prominent Ni−dx2−y2-dominated Fermi surface. Motivated by the Ni1+δ superconductivity in infinite-layer NdNiO2 (Tc=15K) and high-pressure superconducting La3Ni2O7 (Tc=80K), we designed a (SrNiO2)2/(LaTiO3)1 superlattice with a two-dimensional confined bilayer NiO2. LaTiO3 acts as an electron donor, transferring a full electron to the NiO2 double layers due to the electronegativity difference between Ni(1.91) and Ti(1.54). This charge transfer transforms the Fermi surface from a multiorbital character, resembling that of NdNiO2, into one dominated purely by Ni1+δ−dx2−y2 orbitals. Factors that limited the transition temperature in NdNiO2, such as 5d−3d hybridization, self-doping between Nd and Ni atoms, and the weak p−d hybridization between Ni and O atoms, are effectively suppressed and enhanced, respectively. The nearest-neighbor eg hoppings closely resemble those in undoped infinite-layer NdNiO2, though they are smaller than those found in high-pressure La3Ni2O7. Similar to La3Ni2O7, this superlattice exhibits a low-spin magnetic state with instability stemming from nearly degenerate magnetic ground states. Additionally, F doping in NiO2 double layers can be used to fine tune the Ni valence state and the magnetic coupling, simulating the effects of oxygen pressure in the preparation. Our research offers new insights into the mechanisms driving high-Tc superconductivity in nickelates under ambient pressure, emphasizing the pivotal role of heterostructure engineering in these processes.

关键词： Fermi surface

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Risk-mediated dynamic regulation of effective contacts de-synchronizes outbreaks in metapopulation epidemic models

arXiv

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arXiv 2025年

作者： Zunker, Henrik Dönges, Philipp Lenz, Patrick Contreras, Seba Kühn, Martin J. Institute of Software Technology Department of High-Performance Computing German Aerospace Center Cologne Germany Max Planck Institute for Dynamics and Self-Organization Göttingen Germany Institute for the Dynamics of Complex Systems University of Göttingen Göttingen Germany Life and Medical Sciences Institute Bonn Center for Mathematical Life Sciences University of Bonn Bonn Germany

Metapopulation epidemic models help capture the spatial dimension of infectious disease spread by dividing heterogeneous populations into separate but interconnected communities, represented by nodes in a network. In the event of an epidemic, an important research question is, to what degree spatial information (i.e., regional or national) is relevant for mitigation and (local) policymakers. This study investigates the impact of different levels of information on nationwide epidemic outcomes, modeling the reaction to the measured hazard as a feedback loop reducing contact rates in a metapopulation model based on ordinary differential equations (ODEs). Using COVID-19 and high-resolution mobility data for Germany of 2020 as a case study, we found two markedly different regimes depending on the maximum contact reduction ψmax: mitigation and suppression. In the regime of (modest) mitigation, gradually increasing ψmax from zero to moderate levels delayed and spread out the onset of infection waves while gradually reducing the peak values. This effect was more pronounced when the contribution of regional information was low relative to national data. In the suppression regime, the feedback-induced contact reduction is strong enough to extinguish local outbreaks and decrease the mean and variance of the peak day distribution, thus regional information was more important. When suppression or elimination is impossible, ensuring local epidemics are desynchronized helps to avoid hospitalization or intensive care bottlenecks by reallocating resources from less-affected *** Codes 3404, 9210, 92B05 Copyright © 2025, The Authors. All rights reserved.

关键词： COVID-19

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Optimized circuits for windowed modular arithmetic with applications to quantum attacks against RSA

arXiv

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arXiv 2025年

作者： Luongo, Alessandro Narasimhachar, Varun Sireesh, Adithya Centre for Quantum Technologies National University of Singapore Singapore Inveriant Pte. Ltd. Singapore Institute of High Performance Computing Agency for Science Technology and Research Singapore School of Informatics University of Edinburgh Scotland United Kingdom

Windowed arithmetic [Gidney, 2019] is a technique for reducing the cost of quantum arithmetic circuits with space–time tradeoffs using memory queries to precomputed tables. It can reduce the asymptotic cost of modular exponentiation from O(n3) to O(n3/log2 n) operations, resulting in the current state-of-the-art compilations of quantum attacks against modern cryptography. In this work we introduce four optimizations to windowed modular exponentiation. We (1) show how the cost of unlookups can be reduced by 66% asymptotically in the number of bits, (2) illustrate how certain addresses can be bypassed, reducing both circuit depth and the overall lookup cost, (3) demonstrate that multiple lookup–addition operations can be merged into a single, larger lookup at the start of the modular exponentiation circuit, and (4) reduce the depth of the unary conversion for unlookups. On a logical level, this leads to a 3% improvement in Toffoli count and Toffoli depth for modular exponentiation circuits relevant to cryptographic applications. This translates to some improvements on [Gidney and Ekerå, 2021]’s factoring algorithm: for a given number of physical qubits, our improvements show a reduction in the expected runtime from 2% to 6% for factoring RSA-2048 *** Codes 81P68, 68Q09, 68Q12 © 2025, CC0.

关键词： Table lookup

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Vision-Language Model IP Protection via Prompt-based Learning

arXiv

引用

arXiv 2025年

作者： Wang, Lianyu Wang, Meng Fu, Huazhu Zhang, Daoqiang The Key Laboratory of Brain-Machine Intelligence Technology Ministry of Education China Centre for Innovation and Precision Eye Health Yong Loo Lin School of Medicine National University of Singapore Singapore Institute of High Performance Computing Agency for Science Technology and Research Singapore

Vision-language models (VLMs) like CLIP (Contrastive Language-Image Pre-Training) have seen remarkable success in visual recognition, highlighting the increasing need to safeguard the intellectual property (IP) of well-trained models. Effective IP protection extends beyond ensuring authorized usage;it also necessitates restricting model deployment to authorized data domains, particularly when the model is fine-tuned for specific target domains. However, current IP protection methods often rely solely on the visual backbone, which may lack sufficient semantic richness. To bridge this gap, we introduce IP-CLIP, a lightweight IP protection strategy tailored to CLIP, employing a prompt-based learning approach. By leveraging the frozen visual backbone of CLIP, we extract both image style and content information, incorporating them into the learning of IP prompt. This strategy acts as a robust barrier, effectively preventing the unauthorized transfer of features from authorized domains to unauthorized ones. Additionally, we propose a style-enhancement branch that constructs feature banks for both authorized and unauthorized domains. This branch integrates self-enhanced and cross-domain features, further strengthening IP-CLIP’s capability to block features from unauthorized domains. Finally, we present new three metrics designed to better balance the performance degradation of authorized and unauthorized domains. Comprehensive experiments in various scenarios demonstrate its promising potential for application in IP protection tasks for VLMs. © 2025, CC BY-NC-ND.

关键词： Semantics

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Passive on-chip isolators based on the thin-film lithium niobate platform

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Chinese Physics B 2025年第3期34卷 408-413页

作者： Jiacheng Liu Gongyu Xia Qilin Hong Pingyu Zhu Kai-Kai Zhang Keyu Xia Ping Xu Shiqiao Qin Zhihong Zhu College of Advanced Interdisciplinary Studies&Hunan Provincial Key Laboratory of Novel Nano Optoelectronic Information Materials and Devices National University of Defense TechnologyChangsha 410073China Institute for Quantum Information and State Key Laboratory of High-Performance Computing College of Computer Science and TechnologyNational University of Defense TechnologyChangsha 410073China College of Engineering and Applied Sciences National Laboratory of Solid State Microstructuresand Collaborative Innovation Center of Advanced MicrostructuresNanjing UniversityNanjing 210023China

Optical isolators,the photonic analogs of electronic diodes,are essential for ensuring the unidirectional flow of light in optical systems,thereby mitigating the destabilizing effects of back ***-film lithium niobate(TFLN),hailed as“the silicon of photonics,”has emerged as a pivotal material in the realm of chip-scale nonlinear optics,propelling the demand for compact optical *** report a breakthrough in the development of a fully passive,integrated optical isolator on the TFLN platform,leveraging the Kerr effect to achieve an impressive 10.3 dB of isolation with a minimal insertion loss of 1.87 *** theoretical simulations have demonstrated that our design,when applied to a microring resonator with a Q factor of 5×10^(6),can achieve 20 dB of isolation with an input power of merely 8 *** advancement underscores the immense potential of lithium niobate-based Kerr-effect isolators in propelling the integration and application of high-performance on-chip lasers,heralding a new era in integrated photonics.

关键词： thin-film lithium niobate Kerr effect optical isolator

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LLM Knows Geometry Better than Algebra: Numerical Understanding of LLM-Based Agents in A Trading Arena

arXiv

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arXiv 2025年

作者： Ma, Tianmi Du, Jiawei Huang, Wenxin Wang, Wenjie Xie, Liang Zhong, Xian Zhou, Joey Tianyi Hubei Key Laboratory of Transportation Internet of Things Wuhan University of Technology China Hubei Key Laboratory of Big Data Intelligent Analysis and Application Hubei University China Centre for Frontier AI Research Agency for Science Technology and Research Singapore Institute of High Performance Computing Agency for Science Technology and Research Singapore School of Computing National University of Singapore Singapore School of Science Wuhan University of Technology China

Recent advancements in large language models (LLMs) have significantly improved performance in natural language processing tasks. However, their ability to generalize to dynamic, unseen tasks, particularly in numerical reasoning, remains a challenge. Existing benchmarks mainly evaluate LLMs on problems with predefined optimal solutions, which may not align with real-world scenarios where clear answers are absent. To bridge this gap, we design the Agent Trading Arena, a virtual numerical game simulating complex economic systems through zero-sum games, where agents invest in stock portfolios. Our experiments reveal that LLMs, including GPT-4o, struggle with algebraic reasoning when dealing with plain-text stock data, often focusing on local details rather than global trends. In contrast, LLMs perform significantly better with geometric reasoning when presented with visual data, such as scatter plots or K-line charts, suggesting that visual representations enhance numerical reasoning. This capability is further improved by incorporating the reflection module, which aids in the analysis and interpretation of complex data. We validate our findings on NASDAQ STOCK dataset, where LLMs demonstrate stronger reasoning with visual data compared to text. Our code and data are publicly available at https://***/wekjsdvnm/***. © 2025, CC BY.

关键词： Natural language processing systems

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Ad2Mix: Adversarial and Adaptive Mixup for Unsupervised Domain Adaptation

Ad2Mix: Adversarial and Adaptive Mixup for Unsupervised Doma...

引用

IEEE Workshop on Applications of Computer Vision (WACV)

作者： Lei Zhu Yanyu Xu Yong Liu Rick Siow Mong Goh Xinxing Xu Technology and Research (A*STAR) Institute of High Performance Computing (IHPC) Agency for Science Singapore Republic of Singapore The Joint SDU-NTU Centre for Artificial Intelligence Research (C-FAIR) Shandong University Shandong China Microsoft Research Asia Singapore

ISBN: (数字)9798331510831

ISBN: (纸本)9798331510848

Transformer has recently gained tremendous popularity in unsupervised domain adaptation tasks due to its superior generalization ability. State-of-the-art methods leverage mixup to build an intermediate domain to reduce domain gap. However, such strategy becomes less effective when the domain gap becomes large, as the domain gap between intermediate domain and source domain is not minimized and the constructed intermediate domain is non informative. How to address the adaptation problem when domain gap becomes large is an important research problem in domain adaptation. In this paper, we propose an adversarial and adaptive mixup (Ad 2 mix) framework which gradually aligns the intermediate domain towards source domain to fully unleash the potential of both the transformer architecture and mixup to address the large domain gap problem. Specifically, we formulate a general framework for intermediate domain learning with mixup. We propose adversarial mixup with a specially designed mixup alike adversarial adaptation operation to reduce the domain gap between the intermediate domain and source domain. To construct an informative intermediate domain, unlike existing methods which utilize a Beta distribution to generate mixup coefficients to interpolate source and target data, we adaptively assign mixup coefficient for each target data instance based on their transferability and discriminativity information. Our framework creates a natural curriculum of intermediate domains from near source domain to near target domain for gradual adaptation. Extensive experimental studies and evaluations on three public domain adaptation benchmark datasets and one medical domain adaptation task demonstrate the superiority of our framework.

关键词： Computer vision Knowledge based systems Machine learning Benchmark testing Transformers

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Fundus Image Quality Assessment and Enhancement: a Systematic Review

arXiv

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arXiv 2025年

作者： Li, Heng Li, Haojin Ou, Mingyang Yu, Xiangyang Zhang, Xiaoqing Niu, Ke Fu, Huazhu Liu, Jiang Research Institute of Trustworthy Autonomous Systems SUSTech Shenzhen China Department of Computer Science and Engineering SUSTech Shenzhen China Center for High Performance Computing and Shenzhen Key Laboratory of Intelligent Bioinformatics Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China Computer School Beijing Information Science and Technology University Beijing China Singapore

As an affordable and convenient eye scan, fundus photography holds the potential for preventing vision impairment, especially in resource-limited regions. However, fundus image degradation is common under intricate imaging environments, impacting following diagnosis and treatment. Consequently, image quality assessment (IQA) and enhancement (IQE) are essential for ensuring the clinical value and reliability of fundus images. While existing reviews offer some overview of this field, a comprehensive analysis of the interplay between IQA and IQE, along with their clinical deployment challenges, is lacking. This paper addresses this gap by providing a thorough review of fundus IQA and IQE algorithms, research advancements, and practical applications. We outline the fundamentals of the fundus photography imaging system and the associated interferences, and then systematically summarize the paradigms in fundus IQA and IQE. Furthermore, we discuss the practical challenges and solutions in deploying IQA and IQE, as well as offer insights into potential future research directions. Copyright © 2025, The Authors. All rights reserved.

关键词： Photography

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Timing-Sequence Testing of Parallel Programs

引用

Journal of Computer Science & technology 2000年第1期15卷 84-95页

作者：梁煜李舒张辉韩承德 Center of High-Performance Computing Institute of Computing Technology Chinese Academy of Sciences Beijing P.R. China

Testing of parallel programs involves two parts-testing of controlflow within the processes and testing of timing-sequence. This paper focuses on thelatter, particularly on the timing-sequence of message-passing paradigms. Firstlythe coarse-grained SYN-sequence model is built up to describe the execution of distributed programs. All of the topics discussed in this paper are based on it. Themost direct way to test a program is to run it. A fault-free parallel program shouldbe of both correct computing results and proper SYN-sequence. In order to analyzethe validity of observed SYN-sequence, this paper presents the formal specification(Backus Normal Form) of the valid SYN-sequence. Till now there is little workabout the testing coverage for distributed programs. Calculating the number of thevalid SYN-sequences is the key to coverage problem, while the number of the validSYN-sequences is terribly large and it is very hard to obtain the combination lawamong SYN-events. In order to resolve this problem, this paper proposes an efficienttesting strategy- atomic SYN-event testing, which is to linearize the SYN-sequence(making it only consist of serial atomic SYN-events) first and then test each atomicSYN-event independently. This paper particularly provides the calculating formulaabout the number of the valid SYN-sequences for tree-topology atomic SYN-event(broadcast and combine). Furthermore, the number of valid SYN-sequences also,to some degree, mirrors the testability of parallel programs. Taking tree-topologyatomic SYN-event as an example, this paper demonstrates the testability and communication speed of the tree-topology atomic SYN-event under different numbersof branches in order to achieve a more satisfactory tradeoff between testability andcommunication efficiency.

关键词： timing-sequence testing SYN-sequence atomic SYN-event linearization coverage

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FundusGAN: A Hierarchical Feature-Aware Generative Framework for high-Fidelity Fundus Image Generation

arXiv

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arXiv 2025年

作者： Hou, Qingshan Wang, Meng Cao, Peng Ke, Zou Liu, Xiaoli Fu, Huazhu Zaiane, Osmar R. Computer Science and Engineering Northeastern University Shenyang China Key Laboratory of Intelligent Computing in Medical Image of Ministry of Education Northeastern University Shenyang China Alberta Machine Intelligence Institute University of Alberta Edmonton Canada Ophthalmology Yong Loo Lin School of Medicine National University of Singapore Singapore Institute of High Performance Computing Agency for Science Technology and Research Singapore

Recent advancements in ophthalmology foundation models such as RetFound have demonstrated remarkable diagnostic capabilities but require massive datasets for effective pre-training, creating significant barriers for development and deployment. To address this critical challenge, we propose FundusGAN, a novel hierarchical feature-aware generative framework specifically designed for high-fidelity fundus image synthesis. Our approach leverages a Feature Pyramid Network within its encoder to comprehensively extract multi-scale information, capturing both large anatomical structures and subtle pathological features. The framework incorporates a modified StyleGAN-based generator with dilated convolutions and strategic upsampling adjustments to preserve critical retinal structures while enhancing pathological detail representation. Comprehensive evaluations on the DDR, DRIVE, and IDRiD datasets demonstrate that FundusGAN consistently outperforms state-of-the-art methods across multiple metrics (SSIM: 0.8863, FID: 54.2, KID: 0.0436 on DDR). Furthermore, disease classification experiments reveal that augmenting training data with FundusGAN-generated images significantly improves diagnostic accuracy across multiple CNN architectures (up to 6.49% improvement with ResNet50). These results establish FundusGAN as a valuable foundation model component that effectively addresses data scarcity challenges in ophthalmological AI research, enabling more robust and generalizable diagnostic systems while reducing dependency on large-scale clinical data collection. Copyright © 2025, The Authors. All rights reserved.

关键词： Ophthalmology

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