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2509.25854 2026-06-10 eess.SP cs.IT math.IT 版本更新

Delay-Doppler Domain Channel Measurements and Modeling in High-Speed Railways

高速铁路中的延迟-多普勒域信道测量与建模

Hao Zhou, Yiyan Ma, Dan Fei, Weirong Liu, Zhengyu Zhang, Mi Yang, Guoyu Ma, Yunlong Lu, Ruisi He, Guoyu Wang, Cheng Li, Zhaohui Song, Bo Ai

AI总结针对高速铁路场景，提出基于LTE-R的延迟-多普勒域信道测量方法，建立准平稳区间和准不变区间模型，通过OTFS误码率验证准确性，支持6G高移动性通信。

Comments 15 pages, 10 figures

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DOI: 10.1109/TWC.2026.3684101
Journal ref: in IEEE Transactions on Wireless Communications, vol. 25, pp. 15725-15740, 2026

AI中文摘要

随着下一代无线通信系统需要在高频段和高移动性场景下运行，延迟-多普勒（DD）域多载波（DDMC）调制方案，如正交时频空（OTFS），相比正交频分复用（OFDM）展现出更高的可靠性。精确的DD域信道建模对于DDMC系统设计至关重要。然而，由于传统信道建模方法主要局限于时域、频域和空域，DD域信道建模的原理仍缺乏研究。为解决这一问题，我们提出了一种在高速铁路（HSR）场景下系统的DD域信道测量与建模方法。首先，我们设计了一种基于铁路长期演进（LTE-R）系统的DD域信道测量方法。其次，对于DD域信道建模，我们研究了准平稳区间、多径分量的统计功率建模，特别是DD域信道衰落系数的准不变区间。第三，通过371 km/h下的LTE-R测量，以准平稳区间为判定准则，建立了HSR场景下不同信道时变条件下的DD域信道模型。第四，通过OTFS传输的误码率比较验证了所提DD域信道模型的准确性。此外，仿真验证了在HSR场景中，DD域信道衰落系数的准不变区间在毫秒（ms）量级，远小于100 ms量级的准平稳区间长度。本研究可为高移动性环境下的DD域建模提供理论指导，支持未来6G及更高版本的DDMC和集成感知通信设计。

英文摘要

As next-generation wireless communication systems need to be able to operate in high-frequency bands and high-mobility scenarios, delay-Doppler (DD) domain multicarrier (DDMC) modulation schemes, such as orthogonal time frequency space (OTFS), demonstrate superior reliability over orthogonal frequency division multiplexing (OFDM). Accurate DD domain channel modeling is essential for DDMC system design. However, since traditional channel modeling approaches are mainly confined to time, frequency, and space domains, the principles of DD domain channel modeling remain poorly studied. To address this issue, we propose a systematic DD domain channel measurement and modeling methodology in high-speed railway (HSR) scenarios. First, we design a DD domain channel measurement method based on the long-term evolution for railway (LTE-R) system. Second, for DD domain channel modeling, we investigate quasi-stationary interval, statistical power modeling of multipath components, and particularly, the quasi-invariant intervals of DD domain channel fading coefficients. Third, via LTE-R measurements at 371 km/h, taking the quasi-stationary interval as the decision criterion, we establish DD domain channel models under different channel time-varying conditions in HSR scenarios. Fourth, the accuracy of proposed DD domain channel models is validated via bit error rate comparison of OTFS transmission. In addition, simulation verifies that in HSR scenario, the quasi-invariant interval of DD domain channel fading coefficient is on millisecond (ms) order of magnitude, which is much smaller than the quasi-stationary interval length on 100 ms order of magnitude. This study could provide theoretical guidance for DD domain modeling in high-mobility environments, supporting future DDMC and integrated sensing and communication designs for 6G and beyond.

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2501.15927 2026-06-10 gr-qc hep-th 版本更新

Observational implications of Wald-Gauss-Bonnet topological dark energy

Wald-Gauss-Bonnet拓扑暗能量的观测意义

Maria Petronikolou, Fotios K. Anagnostopoulos, Stylianos A. Tsilioukas, Spyros Basilakos, Emmanuel N. Saridakis

AI总结基于Wald-Gauss-Bonnet熵修改弗里德曼方程，引入与黑洞形成和合并率相关的暗能量项，通过贝叶斯分析检验其与晚期宇宙数据的兼容性，发现虽与观测一致但统计上不如ΛCDM模型。

Comments to appear in Journal of High Energy Astrophysics

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AI中文摘要

我们研究了Wald-Gauss-Bonnet (WGB)拓扑暗能量的观测意义，这是一种修改的宇宙学框架，源自应用于宇宙表观视界的引力-热力学猜想，用Wald-Gauss-Bonnet熵替代标准的Bekenstein-Hawking熵。假设表观视界与内部黑洞视界之间存在拓扑联系，我们推导了修改的弗里德曼方程，其中暗能量的演化取决于黑洞形成和合并率，这些率由宇宙恒星形成率近似。这些方程引入了对宇宙学常数的额外、依赖于天体物理学的贡献。我们测试了两种情景：一种宇宙学常数为零（$\Lambda = 0$），另一种具有修改的$\Lambda$，并通过贝叶斯分析对比晚期宇宙数据（SNIa、BAO、宇宙计时器）。尽管WGB框架与观测一致，但信息准则在统计上更支持标准$\Lambda$CDM模型。线性扰动分析表明，宇宙结构的增长与$\Lambda$CDM几乎无法区分，暗能量聚集可忽略，有效牛顿常数偏差极小。标准热历史也得以保持。总之，WGB宇宙学提供了一种现象学丰富的替代方案，将暗能量与黑洞天体物理学联系起来，同时与当前宇宙学数据兼容。

英文摘要

We investigate the observational implications of Wald--Gauss--Bonnet (WGB) topological dark energy, a modified cosmological framework derived from the gravity-thermodynamics conjecture applied to the Universe's apparent horizon, with the Wald--Gauss--Bonnet entropy replacing the standard Bekenstein--Hawking one. Assuming a topological connection between the apparent horizon and interior black hole (BH) horizons, we derive modified Friedmann equations where the evolution of dark energy depends on BH formation and merger rates, which are approximated by the cosmic star formation rate. These equations introduce an additional, astrophysics--dependent contribution to the cosmological constant. We test two scenarios, one with a vanishing cosmological constant ($Λ= 0$) and another with a modified $Λ$ against late--Universe data (SNIa, BAO, Cosmic Chronometers) via a Bayesian analysis. Although the WGB framework is consistent with observations, information criteria statistically favor the standard $Λ$CDM model. An analysis of linear perturbations shows that the growth of cosmic structures is nearly indistinguishable from that of $Λ$CDM, with negligible dark energy clustering and minimal deviation in the effective Newton's constant. The standard thermal history is also preserved. In conclusion, WGB cosmology presents a phenomenologically rich alternative that connects dark energy to black hole astrophysics while remaining compatible with current cosmological data.

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2509.24088 2026-06-10 cs.MA 版本更新

CORRECT: COndensed eRror RECognition via knowledge Transfer in multi-agent systems

CORRECT: 多智能体系统中基于知识迁移的浓缩错误识别

Yifan Yu, Moyan Li, Shaoyuan Xu, Jinmiao Fu, Xinhai Hou, Fan Lai, Bryan Wang

AI总结提出CORRECT框架，利用在线缓存蒸馏错误模式，实现轻量级、免训练的错误定位，在多智能体系统中提升错误识别效率，并在七个应用上取得最高19.8%的步骤级错误定位提升。

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AI中文摘要

多智能体系统（MAS）越来越能够处理复杂的现实任务，但它们对智能体间协调、工具使用和长程推理的依赖使得错误识别特别具有挑战性。微小的错误可以在智能体间传播，升级为任务失败，同时产生冗长且交织的执行轨迹，给人类开发者和自动化系统的调试与分析带来巨大成本。我们的关键洞察是，尽管失败轨迹（例如日志）表面存在差异，但MAS错误往往以相似的结构模式重复出现。本文提出CORRECT，这是首个轻量级、免训练的框架，利用在线缓存蒸馏的错误模式来识别失败结构，并在新请求中迁移知识。这种基于缓存的重用使得LLM能够在推理时进行有针对性的错误定位，避免了昂贵的重训练，同时能在亚秒级适应动态的MAS部署。为了支持该领域的严谨研究，我们还引入了CORRECT-Error，这是一个大规模数据集，包含通过新颖的错误注入管道（基于真实世界分布）收集的2000多条标注轨迹，并通过人工评估进一步验证，以确保与自然失败模式的一致性。在七个不同的MAS应用上的实验表明，CORRECT在步骤级错误定位上比现有先进方法提升了高达19.8%，且几乎零开销，显著缩小了自动化与人类级错误识别之间的差距。

英文摘要

Multi-agent systems (MAS) are increasingly capable of tackling complex real-world tasks, yet their reliance on inter-agent coordination, tool use, and long-horizon reasoning makes error recognition particularly challenging. Minor errors can propagate across agents, escalating into task failures while producing long, intertwined execution trajectories that impose significant costs for both human developers and automated systems to debug and analyze. Our key insight is that, despite surface differences in failure trajectories (e.g., logs), MAS errors often recur with similar structural patterns. This paper presents CORRECT, the first lightweight, training-free framework that leverages an online cache of distilled error schemata to recognize and transfer knowledge of failure structures across new requests. This cache-based reuse allows LLMs to perform targeted error localization at inference time, avoiding the need for expensive retraining while adapting to dynamic MAS deployments in subseconds. To support rigorous study in this domain, we also introduce CORRECT-Error, a large-scale dataset of over 2,000 annotated trajectories collected through a novel error-injection pipeline guided by real-world distributions, and further validated through human evaluation to ensure alignment with natural failure patterns. Experiments across seven diverse MAS applications show that CORRECT improves step-level error localization up to 19.8% over existing advances while at near-zero overhead, substantially narrowing the gap between automated and human-level error recognition.

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2509.22153 2026-06-10 eess.AS 版本更新

Towards Paradigm-General Suicide Risk Detection via Speech LLM

面向范式通用的语音自杀风险检测：基于语音大语言模型

Jialun Li, Weitao Jiang, Ziyun Cui, Yinan Duan, Diyang Qu, Chao Zhang, Runsen Chen, Chang Lei, Wen Wu

AI总结提出基于语音大语言模型和混合DoRA专家的方法，统一多种语音诱发范式，在1223名参与者十种范式上优于特定范式及传统联合学习模型，并泛化至未见范式。

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AI中文摘要

青少年自杀风险仍然是一个关键的公共卫生问题，语音提供了一种非侵入性且可扩展的检测方法。基于语音的自杀风险评估通常依赖于精心设计的语音诱发范式（例如，言语流畅性、朗读或问答）来探测认知和情感状态。然而，现有方法通常一次只关注单一范式。本文首次研究了跨范式方法，将多种语音诱发范式统一到单个模型中。具体而言，我们使用语音大语言模型作为骨干，结合混合DoRA专家（MoDE）动态捕捉跨评估的互补线索，并在1223名参与者跨越十种语音诱发范式的数据上进行测试。结果表明，MoDE优于特定范式和传统的联合学习模型。此外，它能够泛化到未见过的范式，并提供更好的置信度校准。

英文摘要

Suicide risk among adolescents remains a critical public health concern, and speech provides a non-invasive and scalable approach for its detection. Speech-based suicide risk assessment commonly relies on carefully designed speech elicitation paradigms (\textit{e.g.,} verbal fluency, reading, or question answering) to probe cognitive and affective states. Existing approaches, however, typically focus on one single paradigm at a time. This paper, for the first time, investigates cross-paradigm approaches that unify diverse speech elicitation paradigms within a single model. Specifically, we use a speech LLM as backbone with a mixture of DoRA experts (MoDE) to capture complementary cues across assessments dynamically, tested on 1,223 participants across ten speech elicitation paradigms. Results show that MoDE outperforms both paradigm-specific and conventional joint-learning models. Moreover, it can generalise to unseen paradigms and provide better confidence calibration.

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2509.19152 2026-06-10 cs.HC 版本更新

A Scoping Review of Mixed Initiative Visual Analytics in the Automation Renaissance

自动化复兴中混合主动视觉分析的范围综述

Shayan Monadjemi, Yuhan Guo, Kai Xu, Alex Endert, Anamaria Crisan

AI总结通过范围综述和集成分类法，揭示混合主动视觉分析系统中自动化程度与人类角色的关系，指出定义缺乏共识且协作交互潜力探索有限。

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DOI: 10.1111/cgf.70434

AI中文摘要

人工智能代理越来越多地集成到数据分析工作流中，执行以前主要由人类完成的任务。我们的研究探讨了自动化的引入如何重新校准人类与自动化技术之间的动态。为了探索这个问题，我们进行了一项范围综述，涵盖二十年来的混合主动视觉分析系统。为了描述和对比人类与自动化之间的关系，我们开发了一个集成分类法，以界定这些混合主动视觉分析工具的目标、它们支持的自动化程度以及人类假定的角色。在这里，我们描述了我们整合现有理论框架与我们开发的新代码的定性方法。我们的分析表明，可视化研究文献缺乏对混合主动系统定义的共识，并且只探索了人与自动化之间协作交互景观的有限潜力。我们的研究为推进视觉数据分析过程中人机协作的讨论提供了框架。我们的集成分类法以Web应用程序的形式提供，网址为：https://this https URL。

英文摘要

Artificial agents are increasingly integrated into data analysis workflows, carrying out tasks that were primarily done by humans. Our research explores how the introduction of automation recalibrates the dynamic between humans and automating technology. To explore this question, we conducted a scoping review encompassing twenty years of mixed-initiative visual analytic systems. To describe and contrast the relationship between humans and automation, we developed an integrated taxonomy to delineate the objectives of these mixed-initiative visual analytics tools, how much automation they support, and the assumed roles of humans. Here, we describe our qualitative approach of integrating existing theoretical frameworks with new codes we developed. Our analysis shows that the visualization research literature lacks consensus on the definition of mixed-initiative systems and explores a limited potential of the collaborative interaction landscape between people and automation. Our research provides a scaffold to advance the discussion of human-AI collaboration during visual data analysis. Our integrated taxonomy is available in the form of a web application on https://smonadjemi.github.io/miva.

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2509.18271 2026-06-10 astro-ph.CO astro-ph.GA 版本更新

Small-scale Lyman alpha forest cosmology with PRIYA: Constraints from XQ100 and KODIAQ-SQUAD one-dimensional flux power spectra

小尺度莱曼α森林宇宙学：基于PRIYA的XQ100和KODIAQ-SQUAD一维通量功率谱约束

Ming-Feng Ho, Mahdi Qezlou, Simeon Bird, Yanhui Yang, Camille Avestruz, M. A. Fernandez, Vid Iršič

AI总结利用PRIYA仿真框架分析XQ100和KODIAQ-SQUAD高分辨率类星体光谱的一维通量功率谱，在小尺度上约束宇宙学参数，发现XQ100数据能独立提供热历史约束，而KODIAQ-SQUAD受高柱密度吸收体选择偏差影响。

Comments 44 pages, 24 figures. Accepted version, matched to JCAP

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AI中文摘要

我们利用XQ100和KODIAQ-SQUAD的高分辨率类星体光谱，通过PRIYA仿真器对小尺度莱曼α森林一维通量功率谱（P1D）进行了新的宇宙学分析。PRIYA是一套涵盖多种宇宙学和非均匀HeII再电离参数的星系形成模拟套件，能够对P1D进行百分之几精度的预测。这些数据集在红移$z=2-5$时探测到$k \sim 6\,h\,\mathrm{Mpc}^{-1}$的尺度，提供了eBOSS等大体积巡天无法触及的非线性尺度信息。我们发现，XQ100的P1D在枢轴尺度$k_0 = 0.78\,\mathrm{Mpc}^{-1}$上对原初功率谱参数$(A_P, n_P)$的约束与PRIYA基于eBOSS DR14和Planck CMB的结果一致，尽管不确定性更大。值得注意的是，这是在无需外部IGM温度数据的情况下实现的，表明仅XQ100就能提供比eBOSS DR14更强的热历史约束。相比之下，KODIAQ-SQUAD的P1D倾向于显著更高的$A_P$值，这是由高柱密度吸收体（HCDs）的选择偏差所致。我们还发现，在$k > 0.045\,\mathrm{s/km}$尺度上的P1D对莱曼极限系统污染和热历史更敏感。当对$(A_P, n_P)$施加先验时，约化$\chi^2$保持不变，且推断的平均IGM温度不受影响，这表明宇宙学和热参数主要对不同尺度敏感。因此，XQ100的P1D为热噪声参数提供了互补信息，可与eBOSS或DESI的P1D测量联合拟合，以改进宇宙学约束。

英文摘要

We present a new cosmological analysis of the small-scale Lyman alpha forest 1D flux power spectrum (P1D) using high-resolution quasar spectra from XQ100 and KODIAQ-SQUAD, interpreted through the PRIYA emulator. PRIYA is a suite of galaxy formation simulations spanning a range of cosmological and inhomogeneous HeII reionization parameters, enabling few-percent-level predictions of the P1D. These datasets, probing down to $k \sim 6\,h\,\mathrm{Mpc}^{-1}$ at $z = 2-5$, offer access to non-linear scales inaccessible to large-volume surveys like eBOSS. We find that the XQ100 P1D yields constraints on the primordial power spectrum parameters $(A_P, n_P)$ at pivot scale $k_0 = 0.78\,\mathrm{Mpc}^{-1}$ that are consistent with PRIYA results from eBOSS DR14 and Planck CMB, albeit with broader uncertainties. Notably, this is achieved without external IGM temperature data, showing that XQ100 alone provides stronger constraints on thermal history than eBOSS DR14. In contrast, the KODIAQ-SQUAD P1D favors a significantly higher $A_P$ value, driven by the selection bias toward high-column density absorbers (HCDs). We also find that the P1D at $k > 0.045\,\mathrm{s/km}$ is more sensitive to Lyman limit system contamination and thermal history. When imposing a prior on $(A_P, n_P)$, the reduced $χ^2$ remains unchanged and the inferred mean IGM temperature is unaffected, suggesting that cosmological and thermal parameters are largely sensitive to different scales. The XQ100 P1D therefore provides complementary information on thermal nuisance parameters, which can be jointly fit with eBOSS or DESI P1D measurements to improve cosmological constraints.

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2509.17862 2026-06-10 cond-mat.mtrl-sci physics.chem-ph 版本更新

Insights into CO dimerization at electrified Cu interfaces from large-scale machine learning simulations

大规模机器学习模拟揭示带电铜界面上的CO二聚化机理

Sushree Jagriti Sahoo, Mikael Maraschin, Joel B Varley, Daniel S. Levine, Zachary Ulissi, C. Lawrence Zitnick, Wayu Takemura, Joseph A. Gauthier, Nitish Govindarajan, Muhammed Shuaibi

AI总结利用OC25数据集训练的机器学习模型，模拟Cu表面CO二聚化，发现其对电荷和阳离子身份不敏感，仅在极负电荷下稳定，而阶梯面在中等还原电位下更有利。

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AI中文摘要

固液界面催化是许多能源技术的基础，然而能够捕捉界面动力学的从头算模拟仍然过于昂贵。这里我们介绍Open Catalyst 2025 (OC25)，这是最大的固液界面数据集。为了展示OC25训练模型作为电催化实用工具的能力，我们研究了Cu表面上CO的二聚化，这是CO$_2$电还原的关键步骤。使用大晶胞（>800个原子）和长达7 ns的增强采样——这是迄今为止最大的显式溶剂CO二聚化研究——我们计算了不同表面电荷、阳离子身份和表面晶面下的自由能分布。我们发现二聚化对电荷和阳离子身份不敏感，仅在极负电荷密度下才有明显的稳定化，而扩展到阶梯面Cu(310)则在中等还原电位下显示出更有利的路径。我们的结果表明，OC25训练的模型为研究固液界面的电催化转化提供了可扩展的工具，能够实现比从头算方法高出数个数量级的模拟。

英文摘要

Catalysis at solid-liquid interfaces underpins many energy technologies, yet ab initio simulations that capture interfacial dynamics remain prohibitively expensive. Here we introduce Open Catalyst 2025 (OC25), the largest dataset for solid-liquid interfaces. To demonstrate OC25-trained models as practical tools for electrocatalysis, we investigate CO dimerization on Cu surfaces, a key step in CO$_2$ electroreduction. Using large cells (>800 atoms) and enhanced sampling up to 7 ns - the largest explicit-solvent CO dimerization study to date - we compute free-energy profiles under varied surface charge, cation identity, and surface facet. We find that dimerization is weakly sensitive to charge and cation identity, with appreciable stabilization only at the most negative charge densities, while extension to stepped Cu(310) reveals a more favorable pathway at modest reducing potentials. Our results demonstrate that OC25-trained models provide a scalable tool for investigating electrocatalytic transformations at solid-liquid interfaces, enabling simulations orders of magnitude beyond ab initio methods.

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2509.17372 2026-06-10 gr-qc astro-ph.IM 版本更新

Quantum Noise Reduction in the Space-based Gravitational Wave Antenna DECIGO Using Optical Springs and Homodyne Detection scheme

基于光学弹簧和零差探测方案的空间引力波天线DECIGO中的量子噪声抑制

Kenji Tsuji, Tomohiro Ishikawa, Kentaro Komori, Yutaro Enomoto, Yuta Michimura, Kurumi Umemura, Shoki Iwaguchi, Keiko Kokeyama, Seiji Kawamura

AI总结针对DECIGO探测器0.1-10 Hz频段的量子噪声，通过建立考虑衍射损耗的量子态模型，优化光学弹簧和零差探测配置，实现了高灵敏度，但不足以探测原初引力波。

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AI中文摘要

DECi-hertz干涉仪引力波天文台（DECIGO）是一个计划中的空间下一代引力波探测器，旨在观测源自宇宙暴胀的原初引力波。本文重点通过采用光学弹簧和零差探测方案，在仪器0.1至10 Hz的观测频带内降低量子噪声。尽管之前认为由于衍射损耗导致的量子态退化，失谐1000公里长的臂腔是无效的，但我们通过建立一个新的、严格的量子态模型，考虑衍射损耗导致的真空态混合，重新审视了这个问题。本文表明，即使存在衍射损耗，通过采用光学弹簧和零差探测方案的最优配置，也可以实现高灵敏度。然而，仅凭这些改进仍不足以达到探测原初引力波所需的灵敏度，因为其他技术噪声限制了进一步的提升。

英文摘要

The DECi-hertz Interferometer Gravitational-wave Observatory (DECIGO) is a planned space-based, next-generation gravitational wave detector aimed at observing primordial gravitational waves originating form cosmic inflation. This work focuses on reducing the quantum noise, in the instrument's observation band of 0.1 to 10 Hz, by employing optical springs and a homodyne detection scheme. Although detuning 1000\,km long arm cavities was previously considered ineffective due to quantum state degradation from diffraction losses, we revisit this problem by formulating a new, rigorous model for quantum state of light by accounting for the vacuum state mixing as a result of diffraction losses. This work shows that high sensitivities can be achieved by employing optimal configurations of optical springs and homodyne detection schemes even with diffraction losses. These improvements alone are still not sufficient to achieve sensitivities to detect primordial gravitational waves as other technical noises limit further improvement.

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2509.13431 2026-06-10 physics.med-ph 版本更新

Fast Electromagnetic and RF Circuit Co-Simulation for Passive Resonator Field Calculation and Optimization in MRI

用于MRI中无源谐振器场计算与优化的快速电磁与射频电路协同仿真

Zhonghao Zhang, Ming Lu, Hao Liang, Zhongliang Zu, Yi Gu, Xiao Wang, Yuankai Huo, Xinqiang Yan

AI总结提出一种协同仿真框架，通过单次全波电磁仿真结合电路计算与遗传算法，快速优化无源谐振器参数以增强MRI目标区域B1场，相对误差低于1%。

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DOI: 10.1016/j.mri.2026.110644
Journal ref: Magnetic Resonance Imaging 129 (2026) 110644

AI中文摘要

无源谐振器已广泛应用于MRI中以操控射频场分布。然而，使用全波电磁仿真优化这些结构在计算上是不可行的，特别是对于具有许多自由度的大型无源谐振器阵列。本工作提出了一种专门用于无源谐振器分析和优化的协同仿真框架。该框架执行一次全波电磁仿真，其中谐振器的集总元件被端口替代，随后进行电路级计算以评估任意电容器和电感器配置。这使得能够与遗传算法集成，快速优化谐振器参数并增强目标感兴趣区域（ROI）的B1场。我们在三种场景中验证了该方法：（1）球形体模上的单环无源谐振器，（2）圆柱体模上的双环阵列，以及（3）人体头部模型上的双环阵列。在所有情况下，协同仿真结果与全波仿真显示出极好的一致性，相对误差低于1%。由遗传算法驱动的优化涉及数万种电容器组合，在5分钟内完成，而等效的全波电磁扫描将需要不切实际的长计算时间。本工作首次将协同仿真方法扩展到无源谐振器设计，实现了快速、准确和可扩展的优化。该方法在保持全波精度的同时显著降低了计算负担，使其成为MRI中无源射频结构开发的强大工具。

英文摘要

Passive resonators have been widely used in MRI to manipulate RF field distributions. However, optimizing these structures using full-wave electromagnetic simulations is computationally prohibitive, particularly for large passive resonator arrays with many degrees of freedom. This work presents a co-simulation framework tailored specifically for the analysis and optimization of passive resonators. The framework performs a single full-wave electromagnetic simulation in which the resonator's lumped components are replaced by ports, followed by circuit-level computations to evaluate arbitrary capacitor and inductor configurations. This allows integration with a genetic algorithm to rapidly optimize resonator parameters and enhance the B1 field in a targeted region of interest (ROI). We validated the method in three scenarios: (1) a single-loop passive resonator on a spherical phantom, (2) a two-loop array on a cylindrical phantom, and (3) a two-loop array on a human head model. In all cases, the co-simulation results showed excellent agreement with full-wave simulations, with relative errors below 1%. The genetic-algorithm-driven optimization, involving tens of thousands of capacitor combinations, completed in under 5 minutes, whereas equivalent full-wave EM sweeps would require an impractically long computation time. This work extends co-simulation methodology to passive resonator design for first time, enabling the fast, accurate, and scalable optimization. The approach significantly reduces computational burden while preserving full-wave accuracy, making it a powerful tool for passive RF structure development in MRI.

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2509.12015 2026-06-10 physics.optics physics.app-ph physics.ins-det physics.plasm-ph 版本更新

Probing laser-driven surface and subsurface dynamics via grazing-incidence XFEL scattering and diffraction

通过掠入射XFEL散射和衍射探测激光驱动的表面和亚表面动力学

Lisa Randolph, Özgül Öztürk, Dmitriy Ksenzov, Lingen Huang, Thomas Kluge, S. V. Rahul, Victorien Bouffetier, Carsten Baehtz, Mohammadreza Banjafar, Erik Brambrink, Fabien Brieuc, Byoung Ick Cho, Sebastian Göde, Tobias Held, Hauke Höppner, Gerhard Jakob, Mathias Kläui, Zuzana Konôpková, Changhoo Lee, Gyusang Lee, Mikako Makita, Mikhail Mishchenko, Mianzhen Mo, Pascal D. Ndione, Michael Paulus, Alexander Pelka, Franziska Paschke-Bruehl, Thomas R. Preston, Baerbel Rethfeld, Christian Rödel, Michal Šmíd, Ling Wang, Sebastian T. Weber, Lennart Wollenweber, Jan-Patrick Schwinkendorf, Christian Gutt, Motoaki Nakatsutsumi

AI总结开发了一种掠入射X射线平台，结合GISAXS和GID，以皮秒分辨率同时探测飞秒激光照射金膜的表面纳米形貌和亚表面晶格动力学，克服了同步辐射通量限制，为超快激光-物质相互作用和温稠密物质理论提供严格基准。

Comments 19 pages, 4 figures

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DOI: 10.1107/S2052252526001727
Journal ref: IUCrJ Vol.13, Pages 249-259 (2026)

AI中文摘要

我们展示了一个掠入射X射线平台，该平台在X射线自由电子激光（XFEL）上以皮秒分辨率同时记录飞秒激光照射金膜（高于熔化阈值）的时间分辨掠入射小角X射线散射（GISAXS）和掠入射X射线衍射（GID）。通过调节X射线入射角，探测深度设定为几十纳米，从而实现对近表面动力学的深度选择性敏感。GISAXS解析了表面纳米形貌（相关长度、粗糙度）的超快变化，而GID量化了亚表面晶格压缩、晶粒取向、熔化和再结晶。该方法克服了同步辐射掠入射几何结构的光子通量限制，并为超快激光-物质相互作用和温稠密物质的复杂理论模型提供了严格的时间分辨基准。展望未来，相同的深度选择性方法非常适合惯性约束聚变（ICF）：它可以可视化影响不稳定性种子和燃烧传播的微米至亚微米尺度的埋藏界面扰动和界面热阻。

英文摘要

We demonstrate a grazing-incidence x-ray platform that simultaneously records time-resolved grazing-incidence small-angle x-ray scattering (GISAXS) and grazing-incidence x-ray diffraction (GID) from a femtosecond laser-irradiated gold film above the melting threshold, with picosecond resolution at an x-ray free-electron laser (XFEL). By tuning the x-ray incidence angle, the probe depth is set to tens of nanometers, enabling depth-selective sensitivity to near-surface dynamics. GISAXS resolves ultrafast changes in surface nanomorphology (correlation length, roughness), while GID quantifies subsurface lattice compression, grain orientation, melting, and recrystallization. The approach overcomes photon-flux limitations of synchrotron grazing-incidence geometries and provides stringent, time-resolved benchmarks for complex theoretical models of ultrafast laser-matter interaction and warm dense matter. Looking ahead, the same depth-selective methodology is well suited to inertial confinement fusion (ICF): it can visualize buried-interface perturbations and interfacial thermal resistance on micron to sub-micron scales that affect instability seeding and burn propagation.

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2509.07352 2026-06-10 gr-qc astro-ph.HE hep-ph 版本更新

Directed searches for gravitational waves from ultralight vector boson clouds around merger remnant and galactic black holes during the first part of the fourth LIGO-Virgo-KAGRA observing run

在LIGO-Virgo-KAGRA第四次观测运行的第一阶段中，对来自并合残余和银河系黑洞的超轻矢量玻色子云的引力波定向搜索

The LIGO Scientific Collaboration, the Virgo Collaboration, the KAGRA Collaboration, A. G. Abac, I. Abouelfettouh, F. Acernese, K. Ackley, C. Adamcewicz, S. Adhicary, D. Adhikari, N. Adhikari, R. X. Adhikari, V. K. Adkins, S. Afroz, A. Agapito, D. Agarwal, M. Agathos, N. Aggarwal, S. Aggarwal, O. D. Aguiar, I. -L. Ahrend, L. Aiello, A. Ain, P. Ajith, T. Akutsu, S. Albanesi, W. Ali, S. Al-Kershi, C. Alléné, A. Allocca, S. Al-Shammari, P. A. Altin, S. Alvarez-Lopez, W. Amar, O. Amarasinghe, A. Amato, F. Amicucci, C. Amra, A. Ananyeva, S. B. Anderson, W. G. Anderson, M. Andia, M. Ando, M. Andrés-Carcasona, T. Andrić, J. Anglin, S. Ansoldi, J. M. Antelis, S. Antier, M. Aoumi, E. Z. Appavuravther, S. Appert, S. K. Apple, K. Arai, A. Araya, M. C. Araya, M. Arca Sedda, J. S. Areeda, N. Aritomi, F. Armato, S. Armstrong, N. Arnaud, M. Arogeti, S. M. Aronson, K. G. Arun, G. Ashton, Y. Aso, L. Asprea, M. Assiduo, S. Assis de Souza Melo, S. M. Aston, P. Astone, F. Attadio, F. Aubin, K. AultONeal, G. Avallone, E. A. Avila, S. Babak, C. Badger, S. Bae, S. Bagnasco, L. Baiotti, R. Bajpai, T. Baka, A. M. Baker, K. A. Baker, T. Baker, G. Baldi, N. Baldicchi, M. Ball, G. Ballardin, S. W. Ballmer, S. Banagiri, B. Banerjee, D. Bankar, T. M. Baptiste, P. Baral, M. Baratti, J. C. Barayoga, B. C. Barish, D. Barker, N. Barman, P. Barneo, F. Barone, B. Barr, L. Barsotti, M. Barsuglia, D. Barta, A. M. Bartoletti, M. A. Barton, I. Bartos, A. Basalaev, R. Bassiri, A. Basti, M. Bawaj, P. Baxi, J. C. Bayley, A. C. Baylor, P. A. Baynard, M. Bazzan, V. M. Bedakihale, F. Beirnaert, M. Bejger, D. Belardinelli, A. S. Bell, D. S. Bellie, L. Bellizzi, W. Benoit, I. Bentara, J. D. Bentley, M. Ben Yaala, S. Bera, F. Bergamin, B. K. Berger, S. Bernuzzi, M. Beroiz, D. Bersanetti, T. Bertheas, A. Bertolini, J. Betzwieser, D. Beveridge, G. Bevilacqua, N. Bevins, R. Bhandare, R. Bhatt, D. Bhattacharjee, S. Bhattacharyya, S. Bhaumik, V. Biancalana, A. Bianchi, I. A. Bilenko, G. Billingsley, A. Binetti, S. Bini, C. Binu, S. Biot, O. Birnholtz, S. Biscoveanu, A. Bisht, M. Bitossi, M. -A. Bizouard, S. Blaber, J. K. Blackburn, L. A. Blagg, C. D. Blair, D. G. Blair, N. Bode, N. Boettner, G. Boileau, M. Boldrini, G. N. Bolingbroke, A. Bolliand, L. D. Bonavena, R. Bondarescu, F. Bondu, E. Bonilla, M. S. Bonilla, A. Bonino, R. Bonnand, A. Borchers, S. Borhanian, V. Boschi, S. Bose, V. Bossilkov, Y. Bothra, A. Boudon, L. Bourg, M. Boyle, A. Bozzi, C. Bradaschia, P. R. Brady, A. Branch, M. Branchesi, I. Braun, T. Briant, A. Brillet, M. Brinkmann, P. Brockill, E. Brockmueller, A. F. Brooks, B. C. Brown, D. D. Brown, M. L. Brozzetti, S. Brunett, G. Bruno, R. Bruntz, J. Bryant, Y. Bu, F. Bucci, J. Buchanan, O. Bulashenko, T. Bulik, H. J. Bulten, A. Buonanno, K. Burtnyk, R. Buscicchio, D. Buskulic, C. Buy, R. L. Byer, G. S. Cabourn Davies, R. Cabrita, V. Cáceres-Barbosa, L. Cadonati, G. Cagnoli, C. Cahillane, A. Calafat, T. A. Callister, E. Calloni, S. R. Callos, M. Canepa, G. Caneva Santoro, K. C. Cannon, H. Cao, L. A. Capistran, E. Capocasa, E. Capote, G. Capurri, G. Carapella, F. Carbognani, M. Carlassara, J. B. Carlin, T. K. Carlson, M. F. Carney, M. Carpinelli, G. Carrillo, J. J. Carter, G. Carullo, A. Casallas-Lagos, J. Casanueva Diaz, C. Casentini, S. Y. Castro-Lucas, S. Caudill, M. Cavaglià, R. Cavalieri, A. Ceja, G. Cella, P. Cerdá-Durán, E. Cesarini, N. Chabbra, W. Chaibi, A. Chakraborty, P. Chakraborty, S. Chakraborty, S. Chalathadka Subrahmanya, J. C. L. Chan, M. Chan, K. Chang, S. Chao, P. Charlton, E. Chassande-Mottin, C. Chatterjee, Debarati Chatterjee, Deep Chatterjee, M. Chaturvedi, S. Chaty, A. Chen, A. H. -Y. Chen, D. Chen, H. Chen, H. Y. Chen, S. Chen, Yanbei Chen, Yitian Chen, H. P. Cheng, P. Chessa, H. T. Cheung, S. Y. Cheung, F. Chiadini, G. Chiarini, A. Chiba, A. Chincarini, M. L. Chiofalo, A. Chiummo, C. Chou, S. Choudhary, N. Christensen, S. S. Y. Chua, G. Ciani, P. Ciecielag, M. Cieślar, M. Cifaldi, B. Cirok, F. Clara, J. A. Clark, T. A. Clarke, P. Clearwater, S. Clesse, F. Cleva, E. Coccia, E. Codazzo, P. -F. Cohadon, S. Colace, E. Colangeli, M. Colleoni, C. G. Collette, J. Collins, S. Colloms, A. Colombo, C. M. Compton, G. Connolly, L. Conti, T. R. Corbitt, I. Cordero-Carrión, S. Corezzi, N. J. Cornish, I. Coronado, A. Corsi, R. Cottingham, M. W. Coughlin, A. Couineaux, P. Couvares, D. M. Coward, R. Coyne, A. Cozzumbo, J. D. E. Creighton, T. D. Creighton, P. Cremonese, S. Crook, R. Crouch, J. Csizmazia, J. R. Cudell, T. J. Cullen, A. Cumming, E. Cuoco, M. Cusinato, L. V. Da Conceição, T. Dal Canton, S. Dal Pra, G. Dálya, B. D'Angelo, S. Danilishin, S. D'Antonio, K. Danzmann, K. E. Darroch, L. P. Dartez, R. Das, A. Dasgupta, V. Dattilo, A. Daumas, N. Davari, I. Dave, A. Davenport, M. Davier, T. F. Davies, D. Davis, L. Davis, M. C. Davis, P. Davis, E. J. Daw, M. Dax, J. De Bolle, M. Deenadayalan, J. Degallaix, M. De Laurentis, F. De Lillo, S. Della Torre, W. Del Pozzo, A. Demagny, F. De Marco, G. Demasi, F. De Matteis, N. Demos, T. Dent, A. Depasse, N. DePergola, R. De Pietri, R. De Rosa, C. De Rossi, M. Desai, R. DeSalvo, A. DeSimone, R. De Simone, A. Dhani, R. Diab, M. C. Díaz, M. Di Cesare, G. Dideron, T. Dietrich, L. Di Fiore, C. Di Fronzo, M. Di Giovanni, T. Di Girolamo, D. Diksha, J. Ding, S. Di Pace, I. Di Palma, D. Di Piero, F. Di Renzo, Divyajyoti, A. Dmitriev, J. P. Docherty, Z. Doctor, N. Doerksen, E. Dohmen, A. Doke, A. Domiciano De Souza, L. D'Onofrio, F. Donovan, K. L. Dooley, T. Dooney, S. Doravari, O. Dorosh, W. J. D. Doyle, M. Drago, J. C. Driggers, L. Dunn, U. Dupletsa, P. -A. Duverne, D. D'Urso, P. Dutta Roy, H. Duval, S. E. Dwyer, C. Eassa, W. E. East, M. Ebersold, T. Eckhardt, G. Eddolls, A. Effler, J. Eichholz, H. Einsle, M. Eisenmann, M. Emma, K. Endo, R. Enficiaud, L. Errico, R. Espinosa, M. Esposito, R. C. Essick, H. Estellés, T. Etzel, M. Evans, T. Evstafyeva, B. E. Ewing, J. M. Ezquiaga, F. Fabrizi, V. Fafone, S. Fairhurst, A. M. Farah, B. Farr, W. M. Farr, G. Favaro, M. Favata, M. Fays, M. Fazio, J. Feicht, M. M. Fejer, R. Felicetti, E. Fenyvesi, J. Fernandes, T. Fernandes, D. Fernando, S. Ferraiuolo, T. A. Ferreira, F. Fidecaro, P. Figura, A. Fiori, I. Fiori, M. Fishbach, R. P. Fisher, R. Fittipaldi, V. Fiumara, R. Flaminio, S. M. Fleischer, L. S. Fleming, E. Floden, H. Fong, J. A. Font, F. Fontinele-Nunes, C. Foo, B. Fornal, K. Franceschetti, F. Frappez, S. Frasca, F. Frasconi, J. P. Freed, Z. Frei, A. Freise, O. Freitas, R. Frey, W. Frischhertz, P. Fritschel, V. V. Frolov, G. G. Fronzé, M. Fuentes-Garcia, S. Fujii, T. Fujimori, P. Fulda, M. Fyffe, B. Gadre, J. R. Gair, S. Galaudage, V. Galdi, R. Gamba, A. Gamboa, S. Gamoji, D. Ganapathy, A. Ganguly, B. Garaventa, J. García-Bellido, C. García-Quirós, J. W. Gardner, K. A. Gardner, S. Garg, J. Gargiulo, X. Garrido, A. Garron, F. Garufi, P. A. Garver, C. Gasbarra, B. Gateley, F. Gautier, V. Gayathri, T. Gayer, G. Gemme, A. Gennai, V. Gennari, J. George, R. George, O. Gerberding, L. Gergely, Archisman Ghosh, Sayantan Ghosh, Shaon Ghosh, Shrobana Ghosh, Suprovo Ghosh, Tathagata Ghosh, J. A. Giaime, K. D. Giardina, D. R. Gibson, C. Gier, S. Gkaitatzis, J. Glanzer, F. Glotin, J. Godfrey, R. V. Godley, P. Godwin, A. S. Goettel, E. Goetz, J. Golomb, S. Gomez Lopez, B. Goncharov, G. González, P. Goodarzi, S. Goode, A. W. Goodwin-Jones, M. Gosselin, R. Gouaty, D. W. Gould, K. Govorkova, A. Grado, V. Graham, A. E. Granados, M. Granata, V. Granata, S. Gras, P. Grassia, J. Graves, C. Gray, R. Gray, G. Greco, A. C. Green, L. Green, S. M. Green, S. R. Green, C. Greenberg, A. M. Gretarsson, H. K. Griffin, D. Griffith, H. L. Griggs, G. Grignani, C. Grimaud, H. Grote, S. Grunewald, D. Guerra, D. Guetta, G. M. Guidi, A. R. Guimaraes, H. K. Gulati, F. Gulminelli, H. Guo, W. Guo, Y. Guo, Anuradha Gupta, I. Gupta, N. C. Gupta, S. K. Gupta, V. Gupta, N. Gupte, J. Gurs, N. Gutierrez, N. Guttman, F. Guzman, D. Haba, M. Haberland, S. Haino, E. D. Hall, E. Z. Hamilton, G. Hammond, M. Haney, J. Hanks, C. Hanna, M. D. Hannam, O. A. Hannuksela, A. G. Hanselman, H. Hansen, J. Hanson, S. Hanumasagar, R. Harada, A. R. Hardison, S. Harikumar, K. Haris, I. Harley-Trochimczyk, T. Harmark, J. Harms, G. M. Harry, I. W. Harry, J. Hart, B. Haskell, C. J. Haster, K. Haughian, H. Hayakawa, K. Hayama, M. C. Heintze, J. Heinze, J. Heinzel, H. Heitmann, F. Hellman, A. F. Helmling-Cornell, G. Hemming, O. Henderson-Sapir, M. Hendry, I. S. Heng, M. H. Hennig, C. Henshaw, M. Heurs, A. L. Hewitt, J. Heynen, J. Heyns, S. Higginbotham, S. Hild, S. Hill, Y. Himemoto, N. Hirata, C. Hirose, D. Hofman, B. E. Hogan, N. A. Holland, I. J. Hollows, D. E. Holz, L. Honet, D. J. Horton-Bailey, J. Hough, S. Hourihane, N. T. Howard, E. J. Howell, C. G. Hoy, C. A. Hrishikesh, P. Hsi, H. -F. Hsieh, H. -Y. Hsieh, C. Hsiung, S. -H. Hsu, W. -F. Hsu, Q. Hu, H. Y. Huang, Y. Huang, Y. T. Huang, A. D. Huddart, B. Hughey, V. Hui, S. Husa, R. Huxford, L. Iampieri, G. A. Iandolo, M. Ianni, G. Iannone, J. Iascau, K. Ide, R. Iden, A. Ierardi, S. Ikeda, H. Imafuku, Y. Inoue, G. Iorio, P. Iosif, M. H. Iqbal, J. Irwin, R. Ishikawa, M. Isi, K. S. Isleif, Y. Itoh, M. Iwaya, B. R. Iyer, C. Jacquet, P. -E. Jacquet, T. Jacquot, S. J. Jadhav, S. P. Jadhav, M. Jain, T. Jain, A. L. James, K. Jani, J. Janquart, N. N. Janthalur, S. Jaraba, P. Jaranowski, R. Jaume, W. Javed, A. Jennings, M. Jensen, W. Jia, J. Jiang, H. -B. Jin, G. R. Johns, N. A. Johnson, M. C. Johnston, R. Johnston, N. Johny, D. H. Jones, D. I. Jones, R. Jones, H. E. Jose, P. Joshi, S. K. Joshi, G. Joubert, J. Ju, L. Ju, K. Jung, J. Junker, V. Juste, H. B. Kabagoz, T. Kajita, I. Kaku, V. Kalogera, M. Kalomenopoulos, M. Kamiizumi, N. Kanda, S. Kandhasamy, G. Kang, N. C. Kannachel, J. B. Kanner, S. A. KantiMahanty, S. J. Kapadia, D. P. Kapasi, M. Karthikeyan, M. Kasprzack, H. Kato, T. Kato, E. Katsavounidis, W. Katzman, R. Kaushik, K. Kawabe, R. Kawamoto, D. Keitel, L. J. Kemperman, J. Kennington, F. A. Kerkow, R. 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AI总结使用LIGO数据，通过隐马尔可夫模型和带采样数据框架两种新半相干方法，对已知黑洞周围的超轻矢量玻色子云进行长瞬态和连续引力波的首次定向搜索，未发现信号但给出了质量约束。

Comments 34 pages, 4 figures

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AI中文摘要

我们首次展示了针对已知黑洞（BHs）周围超轻矢量玻色子云的长瞬态和连续引力波的定向搜索。我们使用了来自第四次LIGO-Virgo-KAGRA观测运行第一阶段的LIGO数据。这些搜索针对两种不同类型的黑洞，并采用了两种新的半相干方法：隐马尔可夫模型（HMM）跟踪用于并合残余黑洞GW230814_230901和GW231123_135430（本研究中称为GW230814和GW231123），以及一种使用带采样数据（BSD）框架的专用方法用于天鹅座X-1双星系统中的银河系黑洞。在没有发现来自矢量玻色子的信号证据的情况下，我们估计了可以约束的质量范围。对于针对GW231123和GW230814残余的HMM搜索，在1%误报概率假设下，我们以30%置信度排除了矢量玻色子质量分别在$[0.94, 1.08]$和$[2.75, 3.28] \times 10^{-13}$ eV范围内。尽管这些搜索仅对来自相对较远距离的并合残余的信号具有边际灵敏度，但未来的观测有望以高置信度产生更严格的约束。对于针对天鹅座X-1中黑洞的BSD搜索，在初始黑洞自旋大于0.5的假设下，我们以95%置信度排除了矢量玻色子质量在$[0.85, 1.59] \times 10^{-13}$ eV范围内。

英文摘要

We present the first directed searches for long-transient and continuous gravitational waves from ultralight vector boson clouds around known black holes (BHs). We use LIGO data from the first part of the fourth LIGO-Virgo-KAGRA observing run. The searches target two distinct types of BHs and use two new semicoherent methods: hidden Markov model (HMM) tracking for the remnant BHs of the mergers GW230814_230901 and GW231123_135430 (referred to as GW230814 and GW231123 in this study), and a dedicated method using the Band Sampled Data (BSD) framework for the galactic BH in the Cygnus X-1 binary system. Without finding evidence of a signal from vector bosons in the data, we estimate the mass range that can be constrained. For the HMM searches targeting the remnants from GW231123 and GW230814, we disfavor vector boson masses in the ranges $[0.94, 1.08]$ and $[2.75, 3.28] \times 10^{-13}$ eV, respectively, at 30% confidence, assuming a 1% false alarm probability. Although these searches are only marginally sensitive to signals from merger remnants at relatively large distances, future observations are expected to yield more stringent constraints with high confidence. For the BSD search targeting the BH in Cygnus X-1, we exclude vector boson masses in the range $[0.85, 1.59] \times 10^{-13}$ eV at 95% confidence, assuming an initial BH spin larger than 0.5.

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2509.08057 2026-06-10 astro-ph.CO 版本更新

Fiducial-Cosmology-dependent systematics for the DESI 2024 Full-Shape Analysis

DESI 2024全形状分析中的基准宇宙学依赖系统误差

R. Gsponer, S. Ramirez-Solano, F. Rodríguez-Martínez, M. Vargas-Magaña, S. Novell-Masot, N. Findlay, H. Gil-Marín, P. Zarrouk, S. Nadathur, A. Rocher, S. Brieden, A. Pérez-Fernández, J. Aguilar, S. Ahlen, D. Bianchi, D. Brooks, F. J. Castander, T. Claybaugh, A. Cuceu, A. de la Macorra, A. de Mattia, Arjun Dey, P. Doel, A. Font-Ribera, J. E. Forero-Romero, E. Gaztañaga, S. Gontcho A Gontcho, G. Gutierrez, J. Guy, C. Hahn, H. K. Herrera-Alcantar, K. Honscheid, C. Howlett, D. Huterer, M. Ishak, R. Joyce, R. Kehoe, D. Kirkby, T. Kisner, A. Kremin, O. Lahav, C. Lamman, M. Landriau, L. Le Guillou, M. E. Levi, C. Magneville, M. Manera, A. Meisner, R. Miquel, J. Moustakas, E. Mueller, N. Palanque-Delabrouille, W. J. Percival, F. Prada, I. Pérez-Ràfols, G. Rossi, L. Samushia, E. Sanchez, D. Schlegel, M. Schubnell, H. Seo, J. Silber, D. Sprayberry, G. Tarlé, B. A. Weaver, C. Zhao, R. Zhou, H. Zou

AI总结评估基准宇宙学选择对DESI DR1星系功率谱全形状分析的影响，使用模拟目录量化五种次级宇宙学下的系统偏移，发现偏移远低于统计不确定性。

Comments Matches published version, a short discussion was added to Section 6.1.1 and 7

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DOI: 10.1088/1475-7516/2026/06/010
Journal ref: J. Cosmol. Astropart. Phys. 06 (2026) 010

AI中文摘要

我们评估了基准宇宙学选择对DESI 2024数据发布1（DR1）中星系功率谱全形状（FS）拟合的宇宙学推断的影响。使用基于Planck 2018最佳拟合宇宙学的AbacusSummit DR1模拟目录套件，我们量化了在五种次级宇宙学（包括物质密度变化、冷却暗能量、更高有效中微子种类数、降低的成团幅度以及DESI DR1 BAO最佳拟合$w_0w_a$CDM宇宙学）下分析数据相对于DESI基线Planck 2018宇宙学引入的潜在系统偏移。我们研究了两种互补的FS分析方法：全建模（FM）和ShapeFit（SF），它们对假设的基准模型具有不同的敏感性。在所有示踪物中，我们发现对于FM，由基准宇宙学不匹配引起的系统偏移远低于DESI DR1统计不确定性，在$\Lambda$CDM情景中最大偏差为0.22$\sigma_\mathrm{DR1}$，在扩展的$w_0w_a$CDM拟合中包括SN Ia模拟数据时最大偏差为0.12$\sigma_\mathrm{DR1+SN}$。对于SF，压缩参数的偏移对于所有示踪物和宇宙学均低于0.45$\sigma_\mathrm{DR1}$。

英文摘要

We assess the impact of the fiducial cosmology choice on cosmological inference from full-shape (FS) fits of the galaxy power spectrum in the DESI 2024 Data Release 1 (DR1). Using a suite of AbacusSummit DR1 mock catalogues based on the Planck 2018 best-fit cosmology, we quantify potential systematic shifts introduced by analysing the data under five secondary cosmologies - featuring variations in matter density, thawing dark energy, higher effective number of neutrino species, reduced clustering amplitude, and the DESI DR1 BAO best-fit $w_0w_a$CDM cosmology - relative to DESI's baseline Planck 2018 cosmology. We investigate two complementary FS analysis approaches: full-modelling (FM) and ShapeFit (SF), each with distinct sensitivities to the assumed fiducial model. Across all tracers, we find for FM that systematic shifts induced by fiducial cosmology mismatches remain well below the DESI DR1 statistical uncertainties, with maximum deviations of 0.22$σ_\mathrm{DR1}$ in $Λ$CDM scenarios and 0.12$σ_\mathrm{DR1+SN}$ when including SN Ia mock data in extended $w_0w_a$CDM fits. For SF, the shifts in the compressed parameters remain below $0.45σ_\mathrm{DR1}$ for all tracers and cosmologies.

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2509.06188 2026-06-10 math.OC cs.SY eess.SY 版本更新

Ignore Drift, Embrace Simplicity: Constrained Nonlinear Control through Driftless Approximation

忽略漂移，拥抱简单：通过无漂移近似实现约束非线性控制

Ram Padmanabhan, Melkior Ornik

AI总结提出一种仅使用分段常数输入的非线性系统控制方法，通过构造线性无漂移近似并划分时间区间，证明误差单调收敛至零，满足输入约束。

Comments 13 pages, 8 figures

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AI中文摘要

我们提出了一种新颖的技术，用于在输入约束下驱动非线性系统达到目标状态。所提出的控制器仅由分段常数输入组成，这些输入来自原始非线性系统的简单线性无漂移近似。首先，我们仅利用初始状态下控制输入的效果来构建这个近似。接着，我们将时间范围划分为逐渐缩短的区间，并证明线性无漂移系统的最优控制器在非线性系统中相对于指定目标状态产生有界误差。我们还推导了保证满足输入约束的条件。在应用最优控制输入时，我们证明随着区间逐渐缩短，误差单调收敛到零，从而随时间实现任意接近目标状态。通过经典非线性系统的仿真示例，我们说明了所提技术如何在满足输入约束的同时达到目标状态。特别是，我们展示了即使底层理论的假设被违反，我们的方法也能完成任务。

英文摘要

We present a novel technique to drive a nonlinear system to reach a target state under input constraints. The proposed controller consists only of piecewise constant inputs, generated from a simple linear driftless approximation to the original nonlinear system. First, we construct this approximation using only the effect of the control input at the initial state. Next, we partition the time horizon into successively shorter intervals and show that optimal controllers for the linear driftless system result in a bounded error from a specified target state in the nonlinear system. We also derive conditions under which the input constraint is guaranteed to be satisfied. On applying the optimal control inputs, we show that the error monotonically converges to zero as the intervals become successively shorter, thus achieving arbitrary closeness to the target state with time. Using simulation examples on classical nonlinear systems, we illustrate how the presented technique is used to reach a target state while still satisfying input constraints. In particular, we show that our method completes the task even when assumptions of the underlying theory are violated.

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2505.09631 2026-06-10 physics.ed-ph physics.class-ph 版本更新

The Inverse Velocity Force and Automotive Physics

逆速度力与汽车物理学

Chris L. Lin

AI总结研究逆速度力F(v)=C/v在汽车性能分析中的核心作用，通过传动装置和电路控制解释其来源，并修正补充以描述全速域加速度及运动学，比较燃油车与电动车的扭矩-速度曲线。

Comments 19 pages, 8 figures

2509.05640 2026-06-10 cond-mat.str-el 版本更新

Exact many-body wavefunction of the Kondo model with time-dependent interaction strength

具有时间依赖相互作用强度的近藤模型的精确多体波函数

Parameshwar R. Pasnoori, Emil. A. Yuzbashyan

AI总结利用量子Knizhnik-Zamolodchikov框架，精确求解了具有特定时间依赖自旋交换耦合的近藤模型的非定态薛定谔方程，扩展了时间依赖可积性到量子模型类别。

Comments 34 pages, several typos fixed

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AI中文摘要

量子可积性已被广泛应用于量子场论、凝聚态物理和统计力学中的各种低维哈密顿量，以获得这些系统的能谱和热力学精确表达式。在大多数研究中，耦合常数在时间上是常数。这里我们给出了近藤哈密顿量在周期边界条件下的非定态薛定谔方程的精确解，其中自旋交换耦合$J(t)$具有形式$\lambda t + p(t) \pm \sqrt{(\lambda t + p(t))^2 + 4/3}$，$p(t)$是任意周期函数。与之前研究的基于经典Yang-Baxter结构和相关Knizhnik-Zamolodchikov方程的时间依赖可积模型不同，我们的方法基于量子Knizhnik-Zamolodchikov框架和量子Yang-Baxter代数。我们的结果将时间依赖可积性扩展到真正的量子模型类别，并为探索强关联系统中的相干非平衡动力学提供了新工具。

英文摘要

Quantum integrabilty has been applied to a large variety of low dimesional Hamiltonians in Quantum Field Theory, Condensed Matter Physics, and Statistical Mechanics to obtain exact expressions for the spectrum and thermodynamics of these systems. In most of these studies the coupling constants are constant in time. Here we present an exact solution of the nonstationary Schrödinger equation for the Kondo Hamiltonian with a time-dependent spin-exchange coupling $J(t)$ of the form $λt + p(t) \pm \sqrt{(λt + p(t))^2 + 4/3}$, where $p(t)$ is an arbitrary periodic function, under periodic boundary conditions. Unlike previously studied time-dependent integrable models, which are rooted in the classical Yang--Baxter structure and associated Knizhnik--Zamolodchikov equations, our approach is based on the quantum Knizhnik--Zamolodchikov framework and the quantum Yang--Baxter algebra. Our results broaden the domain of time-dependent integrability to a genuinely quantum class of models and provide a new tools for exploring coherent nonequilibrium dynamics in strongly correlated systems.

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2509.05480 2026-06-10 math.CV 版本更新

Rigidity of Kobayashi isometries of a class of 2-dimensional Lempert manifolds

一类二维Lempert流形的Kobayashi等距刚性

Anand Chavan

AI总结本文研究具有有限Carathéodory通用集的二维复流形的Kobayashi等距，证明其Kobayashi等距必为（反）全纯映射。

Comments Comments are welcome. Lemma 9 and Corollary 10 have been added for better exposition. Accepted for publication in Archiv der Mathematik

2509.03936 2026-06-10 cond-mat.supr-con 版本更新

Two-dimensional coherent spectroscopy of disordered superconductors in the narrow-band and broad-band limits

窄带和宽带极限下无序超导体的二维相干光谱

Naoto Tsuji

AI总结理论分析无序超导体在窄带和宽带极限下的二维相干光谱信号，揭示其与不同非线性磁化率的关联，并通过数值计算展示超导能隙频率处的阈值和共振行为。

Comments 24 pages, 16 figures

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DOI: 10.1103/68kq-n6g8
Journal ref: Phys. Rev. B 113, 214502 (2026)

AI中文摘要

我们理论分析了无序超导体在两种极限下的二维相干光谱（2DCS）信号：一种是具有正弦脉冲波的窄带极限，另一种是具有δ函数脉冲的宽带极限。窄带极限下的2DCS信号与三阶非线性磁化率$\chi^{(3)}(3\Omega; \Omega, \Omega, \Omega)$（三次谐波产生）和$\chi^{(3)}(\Omega; \Omega, \Omega, -\Omega)$（交流克尔效应）相关，而宽带极限下二维频率空间中沿对角线和水平线的信号则与另一种非线性磁化率$\chi^{(3)}(\Omega; \Omega, 0, 0)$（直流克尔效应）相关。我们基于BCS平均场理论和杂质的自洽玻恩近似，对超导体晶格模型数值评估了这些磁化率。窄带和宽带极限下的2DCS信号分别表现出超导能隙频率处的阈值行为和共振行为，其物理起源从准粒子和希格斯模式激发的角度进行了讨论。

英文摘要

We theoretically analyze two-dimensional coherent spectroscopy (2DCS) signals for disordered superconductors in two limits: One is the narrow-band limit with sinusoidal pulse waves, and the other is the broad-band limit with delta-function pulses. While the 2DCS signal in the narrow-band limit is related to the third-order nonlinear susceptibilities $χ^{(3)}(3Ω; Ω, Ω, Ω)$ (third harmonic generation) and $χ^{(3)}(Ω; Ω, Ω, -Ω)$ (ac Kerr effect), we find that in the broad-band limit the signal along the diagonal and horizontal lines in the two-dimensional frequency space is related to another nonlinear susceptibility $χ^{(3)}(Ω; Ω, 0, 0)$ (dc Kerr effect). We numerically evaluate those susceptibilities for a lattice model of superconductors based on the BCS mean-field theory and self-consistent Born approximation for impurities. The 2DCS signals in the narrow-band and broad-band limits show threshold and resonance behaviors at the superconducting-gap frequency, respectively, whose physical origin is discussed in light of quasiparticle and Higgs-mode excitations.

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2409.07213 2026-06-10 math.OC 版本更新

Exact SDP relaxations for a class of quadratic programs with finite and infinite quadratic constraints

一类具有有限和无限二次约束的二次规划问题的精确SDP松弛

Naohiko Arima, Sunyoung Kim, Masakazu Kojima

AI总结研究非凸二次目标函数在有限和无限二次约束下的精确SDP松弛条件，提出三个新充分条件并证明其关系，其中一个为最弱条件。

Comments 28pages, 6 figures

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AI中文摘要

我们研究在由有限和无限多个非凸二次不等式约束（半无限QCQP）定义的可行域上最小化非凸二次目标函数问题的精确半定规划（SDP）松弛。对于具有有限约束的QCQP，SDP松弛精确性的充分条件已被广泛研究，特别是Argue等人（MOR, 48:100-126, 2023）、Arima等人（SIOPT, 34:3194-3211, 2024）以及Joyce和Yang（MP, 205:539-558, 2024）的工作。在本文中，我们提出了三个新的充分条件，这些条件推广了这些工作中针对有限和半无限QCQP的现有条件。具体来说，我们建立了所提条件与现有条件之间的关系，并证明其中一个所提条件是它们中最弱的，因为它被所有其他条件所蕴含。还提供了说明性示例，以展示所提条件与现有条件相比的有效性。

英文摘要

We investigate exact semidefinite programming (SDP) relaxations for the problem of minimizing a nonconvex quadratic objective function over a feasible region defined by both finitely and infinitely many nonconvex quadratic inequality constraints (semi-infinite QCQPs). Sufficient conditions for the exactness of SDP relaxations for QCQPs with finitely many constraints have been extensively studied, notably by Argue et al. (MOR, 48:100-126, 2023), Arima et al. (SIOPT, 34:3194-3211, 2024), and Joyce and Yang (MP, 205:539-558, 2024). In this work, we present three new sufficient conditions that generalize the existing conditions in these works for both finite and semi-infinite QCQPs. Specifically, we establish relationships among the proposed and existing conditions, and prove that one of the proposed conditions is the weakest among them, since it is implied by all the others. Illustrative examples are also provided to demonstrate the effectiveness of the proposed conditions in comparison to the existing ones.

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2507.16440 2026-06-10 econ.GN q-fin.EC 版本更新

Measuring the Unmeasurable? Systematic Evidence on Scale Transformations in Subjective Survey Data

测量不可测量之物？主观调查数据中尺度转换的系统性证据

Caspar Kaiser, Anthony Lepinteur

AI总结本文通过实验和大量复制研究，量化主观调查中顺序响应尺度的非线性程度，发现系数符号和显著性稳健，但相对幅度受非线性影响显著。

2509.01003 2026-06-10 cond-mat.mes-hall 版本更新

Calculations of current in the cotunneling regime using Lindblad equations

使用Lindblad方程计算共隧穿区间的电流

Kian Maleki, Michael E. Flatté

AI总结本文采用Lindblad形式在马尔可夫近似下计算零维态通过隧穿势垒的共隧穿电流，并分析了自旋阻塞、退相干和自旋寿命对磁场和引线自旋极化的依赖性。

Comments disagreement between the authors about how the work should be revised to address referee comments

2508.18540 2026-06-10 cs.GR eess.IV 版本更新

Real-time 3D Visualization of Radiance Fields on Light Field Displays

光场显示上辐射场的实时3D可视化

Jonghyun Kim, Cheng Sun, Michael Stengel, Matthew Chan, Andrew Russell, Jaehyun Jung, Wil Braithwaite, David Luebke, Shalini De Mello

AI总结针对光场显示需要多视角高分辨率渲染而辐射场计算密集的问题，提出统一高效框架，通过共享中间扫描平面单次合成密集光场视图，实现实时渲染（200+ FPS），速度提升22倍。

Comments 19 pages, 14 figures. J. Kim, C. Sun, and M. Stengel contributed equally

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DOI: 10.1145/3820023

AI中文摘要

辐射场，包括其近期高效形式如3D高斯泼溅和稀疏体素，通过实现复杂环境的高保真重建，革新了逼真3D场景可视化，使其自然适用于光场显示。然而，集成这些技术面临重大计算挑战，因为光场显示需要从略微偏移的视点进行许多高分辨率渲染，而辐射场依赖于计算密集的体渲染，即使使用高效场景表示也难以达到实时速度。在本文中，我们提出一个统一且高效的框架，用于在光场显示上实时渲染辐射场。我们的方法不是独立重新渲染每个视图，而是将输入辐射场转换为共享的中间扫描平面，这些平面可以在单次过程中高效合成为密集的光场视图。我们的方法优先考虑共享、非定向平面缓存以实现实时性能，以微妙的视角相关颜色效果换取中等内存使用的适度增加。我们的框架无需重新训练即可推广到不同场景表示，并避免跨视图的重复计算。我们进一步在Looking Glass显示器上演示了实时交互应用，在45个渲染视图上以512p分辨率实现200+ FPS，实现无缝、沉浸式的3D交互观看体验。在标准基准测试中，与独立渲染每个视图相比，我们的方法实现了高达22倍的加速，同时基本保持了图像质量。

英文摘要

Radiance fields, including their recent efficient forms such as 3D Gaussian Splatting and Sparse Voxels, have revolutionized photorealistic 3D scene visualization by enabling high-fidelity reconstruction of complex environments, making them a natural match for light field displays. However, integrating these technologies presents significant computational challenges, as light field displays require many high-resolution renderings from slightly shifted viewpoints, while radiance fields rely on computationally intensive volume rendering, which is intractable to achieve real-time speeds even with efficient scene representations. In this paper, we propose a unified and efficient framework for real-time radiance field rendering on light field displays. Rather than re-rendering each view independently, our method converts the input radiance field into shared intermediate sweeping planes that can be efficiently composited into dense light-field views in a single pass. Our method prioritizes shared, non-directional plane caching for real-time performance, trading fine view-dependent color effects for a modest increase in intermediate memory usage. Our framework generalizes across different scene representations without retraining and avoids repeated computation across views. We further demonstrate a real-time interactive application on a Looking Glass display, achieving 200+ FPS at 512p across 45 rendered views and enabling seamless, immersive 3D interactive viewing experiences. On standard benchmarks, our method achieves up to 22x speedup compared to independently rendering each view, while largely preserving image quality.

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2508.17646 2026-06-10 hep-ph 版本更新

Investigating topped hadrons to probe the boundaries of the potential model

研究含顶夸克强子以探测势模型的边界

Si-Qiang Luo, Qi Huang, Xiang Liu

AI总结基于CMS和ATLAS合作组最近在t̄t阈值附近发现的赝标量增强结构，利用相对论势模型研究含顶夸克介子和重子的质量谱，并指出精确测量t̄t质量可检验势模型的局限性。

Comments 11 pages, 3 figures, 4 tables, published in Phys. Rev. D

2508.16538 2026-06-10 astro-ph.CO gr-qc 版本更新

Probing the Perturbative Reheating History of Decaying Oscillatory Inflation with ACT Constraints

利用ACT约束探测振荡暴胀的微扰再加热历史

Li-Yang Chen, Rongrong Zhai, Feng-Yi Zhang

AI总结通过微扰暴胀子衰变动力学计算，结合Planck 2018和ACT DR6数据，约束再加热参数空间，发现有效再加热（T_re ≳ 10^14 GeV）被强烈支持。

Comments 15 pages, 3 figures; journal reference and DOI added

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DOI: 10.1016/j.dark.2026.102247
Journal ref: Phys. Dark Univ. 52 (2026) 102247

AI中文摘要

宇宙微波背景（CMB）的精确测量现在为未知的再加热时期提供了强大的探测手段。在这项工作中，我们审视了一个受超引力启发的衰减振荡暴胀模型，用基于微扰暴胀子衰变的完全动力学计算取代了标准的特设再加热假设。通过数值追踪能量转移和状态方程演化，我们消除了与再加热持续时间相关的理论简并性，直接将微观衰变率Γ与可观测的谱指数n_s联系起来。我们将这些自洽的预测与Planck 2018和ACT DR6的联合约束进行了对比。我们的分析表明，可行的参数空间被严格限定：大爆炸核合成对热化的要求对耦合强度施加了严格的下限，而最新的ACT数据强烈支持高效再加热（T_re ≳ 10^14 GeV）的情景，有效地将模型推向瞬时再加热极限。这项研究突显了现代CMB数据约束早期宇宙粒子物理性质的能力。

英文摘要

Precision measurements of the Cosmic Microwave Background (CMB) now offer a powerful probe of the unknown reheating epoch. In this work, we scrutinize a decaying oscillatory inflation model inspired by supergravity, replacing standard ad hoc reheating assumptions with a fully dynamical calculation based on perturbative inflaton decay. By numerically tracking the energy transfer and the evolution of the equation of state, we eliminate the theoretical degeneracy associated with the reheating duration, directly linking the microphysical decay rate $Γ$ to the observable spectral index $n_s$. We confront these self-consistent predictions with the combined constraints from Planck 2018 and ACT DR6. Our analysis demonstrates that the viable parameter space is tightly bracketed: the thermalization requirement from Big Bang Nucleosynthesis imposes a strict lower bound on the coupling strength, while the latest ACT data strongly favor scenarios with efficient reheating ($T_{\text{re}} \gtrsim 10^{14}$ GeV), effectively pushing the model towards the instantaneous reheating limit. This study highlights the capability of modern CMB data to constrain the particle physics nature of the early universe.

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2508.13972 2026-06-10 econ.EM stat.ME 版本更新

A Flexible Approach to Augmenting a Bayesian VAR with Nonlinear Factors

一种增强贝叶斯VAR与非线性因子的灵活方法

Todd Clark, Florian Huber, Gary Koop

AI总结本文提出一种用回归树非参数建模非线性因子的向量自回归模型，通过因子方法简洁建模非线性，避免误设，实现高效贝叶斯计算，并适用于结构冲击识别。

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AI中文摘要

本文提出了一种向量自回归模型，该模型通过回归树非参数地建模非线性因子。我们的模型有四个主要优点。第一，因子方法的使用确保了非线性偏离被简洁地建模。特别是，它们表现出功能池化，即使用少量非线性因子来建模变量间的共同非线性。第二，非参数地建模潜在非线性降低了误设的风险。第三，即使在非常高维的模型中，使用MCMC的贝叶斯计算也是直接的，允许高效的逐方程估计，从而避免了诸如时变参数VAR等流行替代方法中出现的计算瓶颈。第四，现有的线性因子模型中识别结构性经济冲击的方法可以通过我们的模型直接适用于非线性情况。涉及人工数据和宏观经济数据的实验说明了我们模型的性质及其在预测和结构性经济分析中的有用性。

英文摘要

This paper proposes a vector autoregression augmented with nonlinear factors that are modeled nonparametrically using regression trees. There are four main advantages of our model. First, the use of factor methods ensures that departures from linearity are modeled parsimoniously. In particular, they exhibit functional pooling where a small number of nonlinear factors are used to model common nonlinearities across variables. Second, modeling potential nonlinearities nonparametrically lessens the risk of misspecification. Third, Bayesian computation using MCMC is straightforward even in very high-dimensional models, allowing for efficient, equation-by-equation estimation, thus avoiding computational bottlenecks that arise in popular alternatives such as the time-varying parameter VAR. Fourth, existing methods for identifying structural economic shocks in linear factor models can be adapted for the nonlinear case in a straightforward fashion using our model. Exercises involving artificial and macroeconomic data illustrate the properties of our model and its usefulness for forecasting and structural economic analysis.

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2508.00752 2026-06-10 math.CO math.RT 版本更新

The representation theory of somewhere-to-below shuffles

“某处至下方”洗牌的表征理论

Darij Grinberg

AI总结研究对称群代数中“某处至下方”洗牌元素及其线性组合（单侧循环洗牌）在任意Specht模上的特征值。

Comments 51 pages. Comments are welcome! v3 adds Example 3.9 and very minor corrections

2508.11521 2026-06-10 cond-mat.stat-mech cond-mat.mes-hall 版本更新

A Dynamical Bulk-Boundary Correspondence in Two Dimensional Topological Matter

二维拓扑物质中的动力学体-边界对应

Tomasz Masłowski, Jesko Sirker, Nicholas Sedlmayr

AI总结通过数值证据，发现二维拓扑物质中动力学自由能的边界贡献由非厄米动力学Loschmidt矩阵的带隙内能带决定，建立了非厄米矩阵谱与拓扑边界贡献的直接联系。

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DOI: 10.1088/1742-5468/ae6c16
Journal ref: Journal of Statistical Mechanics: Theory and Experiment, 053102 (2026)

AI中文摘要

我们提供了强有力的数值证据，证明二维拓扑物质中存在一种动力学体-边界对应，它表现为动力学自由能的边界贡献，并由一个二维非厄米动力学Loschmidt矩阵控制——这一设定在一维之外尚未被广泛探索。在量子淬火后，当时间演化哈密顿量是拓扑的时，Loschmidt矩阵的谱中会在连续动力学量子相变之间出现带隙内能带，而在我们研究的所有情况下，淬火到平凡相时这些能带缺失。通过拟合这些带隙内能带，我们表明它们解释了观测到的动力学自由能的边界贡献，从而支持了非厄米动力学矩阵谱与拓扑边界贡献之间的直接联系。结合之前对一维情况的研究，我们的结果提供了一个基于某些非厄米矩阵谱性质来理解和分类动力学拓扑现象的框架。

英文摘要

We provide strong numerical evidence for a dynamical bulk-boundary correspondence in two-dimensional topological matter which manifests itself as boundary contributions to the dynamical free energy and is governed by a two-dimensional non-Hermitian dynamical Loschmidt matrix -- a setting largely unexplored beyond one dimension. Following a quantum quench, in-gap bands emerge in the spectrum of the Loschmidt matrix between successive dynamical quantum phase transitions when the time-evolving Hamiltonian is topological, while they are absent for quenches into the trivial phase in all cases we have studied. By fitting these in-gap bands, we show that they account for the observed boundary contributions to the dynamical free energy thus supporting a direct connection between the spectrum of a non-Hermitian dynamical matrix and topological boundary contributions. Taken together with earlier studies of the one-dimensional case, our results provide a framework to understand and classify dynamical topological phenomena based on the spectral properties of certain non-Hermitian matrices.

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2508.08000 2026-06-10 math.AG 版本更新

Linearization of finite subgroups of Cremona groups over non-closed fields

非闭域上Cremona群有限子群的线性化

Boris Kunyavskii

AI总结研究全局域上Cremona群有限子群的线性化性质，构造了在整体域上非k-线性化但在所有位点k_v-线性化的双有理对合，主要工具是推广Manin-Voskresenskiı和Bogomolov-Prokhorov的不变量。

Comments 19 pages, revised according to referees' comments

2409.08354 2026-06-10 econ.EM 版本更新

Bayesian Dynamic Factor Models for High-Dimensional Matrix-Valued Time Series

高维矩阵值时间序列的贝叶斯动态因子模型

Joshua C. C. Chan, Wei Zhang

AI总结提出贝叶斯动态因子模型处理矩阵值时间序列，利用矩阵结构实现高维可处理性，并通过交叉熵重要性采样估计边际似然进行模型选择，在OECD宏观面板数据中优于静态矩阵因子基准。

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AI中文摘要

我们引入了一类用于矩阵值时间序列的贝叶斯动态因子模型，具有自回归因子动态和异质成分，允许随机波动、异常值以及捕获跨行和跨列相关性的Kronecker结构协方差。利用矩阵结构，我们使这些参数丰富的模型在高维中可处理，并开发了高效的Gibbs采样器进行估计。对于模型比较，我们提出了一种基于边际似然的交叉熵重要性采样估计的统一方法，该方法在共同准则下选择因子维度、向量与矩阵结构以及异质规范。蒙特卡洛实验证实该估计量可靠地恢复了真实模型。在应用于包含190个时间序列的OECD宏观经济面板时，数据支持横截面相关性和随机波动性，并且该模型在样本外预测中比静态矩阵因子基准具有统计显著的改进。

英文摘要

We introduce a class of Bayesian dynamic factor models for matrix-valued time series, with autoregressive factor dynamics and idiosyncratic components that allow stochastic volatility, outliers, and a Kronecker-structured covariance capturing cross-row and cross-column correlation. Exploiting the matrix structure, we make these richly parameterized models tractable in high dimensions and develop an efficient Gibbs sampler for estimation. For model comparison, we propose a unified approach based on the cross-entropy importance-sampling estimator of the marginal likelihood, which under a common criterion selects the factor dimension, a vector versus matrix structure, and the idiosyncratic specification. Monte Carlo experiments confirm that the estimator reliably recovers the true model. In an application to an OECD macroeconomic panel of 190 time series, the data favor both cross-sectional correlation and stochastic volatility, and the model delivers statistically significant out-of-sample forecast gains over a static matrix factor benchmark.

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2504.13345 2026-06-10 math-ph math.AG math.DG math.MP 版本更新

Lie Superheaps and their Groupification

李超堆及其群化

Andrew James Bruce

AI总结提出李超堆概念作为李超群的推广，利用点函子证明尖点李超堆与李超群范畴同构。

Comments 7 pages, minor editing changes. Accepted for publication in the Bulletin of the Polish Academy of Sciences - Mathematics

2508.01417 2026-06-10 math.GR math.CO 版本更新

Power Graph Classes and Overfullness

幂图类与过满性

Elie Feinsilber

AI总结研究有限群幂图的边着色数，证明幂图是过满的当且仅当它是第2类图当且仅当群是奇素数幂阶循环群。

Comments A V2 incorporating referee comments