WikiEdge:ArXiv速遞/2025-03-04

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摘要

  • 原文標題：The subpath number of cactus graphs
  • 中文標題：仙人掌圖的子路徑數
  • 發佈日期：2025-03-04 14:55:49+00:00
  • 作者：Martin Knor, Jelena Sedlar, Riste Škrekovski, Yu Yang
  • 分類：math.CO, 05C30, 05C38
  • 原文連結：http://arxiv.org/abs/2503.02683v1

原文摘要：The subpath number of a graph G is defined as the total number of subpaths in G, and it is closely related to the number of subtrees, a well-studied topic in graph theory. This paper is a continuation of our previous paper [5], where we investigated the subpath number and identified extremal graphs within the classes of trees, unicyclic graphs, bipartite graphs, and cycle chains. Here, we focus on the subpath number of cactus graphs and characterize all maximal and minimal cacti with n vertices and k cycles. We prove that maximal cacti are cycle chains in which all interior cycles are triangles, while the two end-cycles differ in length by at most one. In contrast, minimal cacti consist of k triangles, all sharing a common vertex, with the remaining vertices forming a tree attached to this joint vertex. By comparing extremal cacti with respect to the subpath number to those that are extremal for the subtree number and the Wiener index, we demonstrate that the subpath number does not correlate with either of these quantities, as their corresponding extremal graphs differ. 中文摘要：圖的子路徑數定義為圖中所有子路徑的總數，它與子樹數密切相關，後者是圖論中一個被廣泛研究的主題。本文是我們之前論文[5]的延續，在那篇論文中我們研究了子路徑數，並在樹、單環圖、二分圖和環鏈等圖類中識別了極值圖。本文中，我們專注於仙人掌圖的子路徑數，並刻畫了所有具有n個頂點和k個環的極大和極小仙人掌圖。我們證明了極大仙人掌圖是環鏈，其中所有內部環都是三角形，而兩個端環的長度最多相差一。相反，極小仙人掌圖由k個三角形組成，這些三角形共享一個公共頂點，其餘頂點形成一個附着於該公共頂點的樹。通過比較子路徑數的極值仙人掌圖與子樹數和維納指數的極值圖，我們證明了子路徑數與這兩個量不相關，因為它們的極值圖不同。

摘要

  • 原文標題：Enhancing the charging performance of an atomic quantum battery
  • 中文標題：提升原子量子電池的充電性能
  • 發佈日期：2025-03-04 15:46:20+00:00
  • 作者：Ming-Liang Hu, Ting Gao, Heng Fan
  • 分類：quant-ph
  • 原文連結：http://arxiv.org/abs/2503.02727v1

原文摘要：We study a quantum battery (QB) model composed of two atoms, where the charger and battery elements are coupled to a multimode vacuum field that serves as a mediator for energy transfer. Different figures of merit such as ergotropy, charging time, and charging efficiency are analyzed, putting emphasis on the role of various control parameters on the charging performance. It is found that there is a range of angle between the transition dipole moments and interatomic axis in which the QB can be charged. The optimal charging performance is achieved if the atomic dipole moments are perpendicular or parallel to the interatomic axis. The charging performance also improves with the decrease of the interatomic distance. Besides, the charged ergotropy can be enhanced by increasing the initial ergotropy of the charger and it is beneficial to charge the QB starting from a passive state. 中文摘要：我們研究了一個由兩個原子組成的量子電池（QB）模型，其中充電器和電池元件耦合到一個多模真空場，該場作為能量轉移的媒介。我們分析了諸如功容量、充電時間和充電效率等不同的性能指標，重點研究了各種控制參數對充電性能的影響。研究發現，在過渡偶極矩和原子間軸之間存在一定角度範圍內，量子電池可以被充電。如果原子偶極矩垂直於或平行於原子間軸，則可以實現最佳充電性能。充電性能還隨着原子間距離的減小而提高。此外，通過增加充電器的初始功容量可以增強充電後的功容量，並且從被動狀態開始充電對量子電池是有益的。

摘要

  • 原文標題：First Measurement of the Decay Dynamics in the Semileptonic Transition of the $D^{+(0)}$ into the Axial-vector Meson $\bar K_1(1270)$
  • 中文標題：$D^{+(0)}$ 到軸矢量介子 $\bar K_1(1270)$ 的半輕衰變中衰變動力學的首次測量
  • 發佈日期：2025-03-04 02:09:02+00:00
  • 作者：BESIII Collaboration, M. Ablikim, M. N. Achasov, P. Adlarson, X. C. Ai, R. Aliberti, A. Amoroso, Q. An, Y. Bai, O. Bakina, Y. Ban, H. -R. Bao, V. Batozskaya, K. Begzsuren, N. Berger, M. Berlowski, M. Bertani, D. Bettoni, F. Bianchi, E. Bianco, A. Bortone, I. Boyko, R. A. Briere, A. Brueggemann, H. Cai, M. H. Cai, X. Cai, A. Calcaterra, G. F. Cao, N. Cao, S. A. Cetin, X. Y. Chai, J. F. Chang, G. R. Che, Y. Z. Che, G. Chelkov, C. H. Chen, Chao Chen, G. Chen, H. S. Chen, H. Y. Chen, M. L. Chen, S. J. Chen, S. L. Chen, S. M. Chen, T. Chen, X. R. Chen, X. T. Chen, Y. B. Chen, Y. Q. Chen, Z. J. Chen, Z. K. Chen, S. K. Choi, X. Chu, G. Cibinetto, F. Cossio, J. J. Cui, H. L. Dai, J. P. Dai, A. Dbeyssi, R. E. de Boer, D. Dedovich, C. Q. Deng, Z. Y. Deng, A. Denig, I. Denysenko, M. Destefanis, F. De Mori, B. Ding, X. X. Ding, Y. Ding, Y. Ding, Y. X. Ding, J. Dong, L. Y. Dong, M. Y. Dong, X. Dong, M. C. Du, S. X. Du, S. X. Du, Y. Y. Duan, Z. H. Duan, P. Egorov, G. F. Fan, J. J. Fan, Y. H. Fan, J. Fang, J. Fang, S. S. Fang, W. X. Fang, Y. Q. Fang, R. Farinelli, L. Fava, F. Feldbauer, G. Felici, C. Q. Feng, J. H. Feng, Y. T. Feng, M. Fritsch, C. D. Fu, J. L. Fu, Y. W. Fu, H. Gao, X. B. Gao, Y. N. Gao, Y. N. Gao, Y. Y. Gao, Yang Gao, S. Garbolino, I. Garzia, P. T. Ge, Z. W. Ge, C. Geng, E. M. Gersabeck, A. Gilman, K. Goetzen, J. D. Gong, L. Gong, W. X. Gong, W. Gradl, S. Gramigna, M. Greco, M. H. Gu, Y. T. Gu, C. Y. Guan, A. Q. Guo, L. B. Guo, M. J. Guo, R. P. Guo, Y. P. Guo, A. Guskov, J. Gutierrez, K. L. Han, T. T. Han, F. Hanisch, K. D. Hao, X. Q. Hao, F. A. Harris, K. K. He, K. L. He, F. H. Heinsius, C. H. Heinz, Y. K. Heng, C. Herold, T. Holtmann, P. C. Hong, G. Y. Hou, X. T. Hou, Y. R. Hou, Z. L. Hou, H. M. Hu, J. F. Hu, Q. P. Hu, S. L. Hu, T. Hu, Y. Hu, Z. M. Hu, G. S. Huang, K. X. Huang, L. Q. Huang, P. Huang, X. T. Huang, Y. P. Huang, Y. S. Huang, T. Hussain, N. Hüsken, N. in der Wiesche, J. Jackson, S. Janchiv, Q. Ji, Q. P. Ji, W. Ji, X. B. Ji, X. L. Ji, Y. Y. Ji, Z. K. Jia, D. Jiang, H. B. Jiang, P. C. Jiang, S. J. Jiang, T. J. Jiang, X. S. Jiang, Y. Jiang, J. B. Jiao, J. K. Jiao, Z. Jiao, S. Jin, Y. Jin, M. Q. Jing, X. M. Jing, T. Johansson, S. Kabana, N. Kalantar-Nayestanaki, X. L. Kang, X. S. Kang, M. Kavatsyuk, B. C. Ke, V. Khachatryan, A. Khoukaz, R. Kiuchi, O. B. Kolcu, B. Kopf, M. Kuessner, X. Kui, N. Kumar, A. Kupsc, W. Kühn, Q. Lan, W. N. Lan, T. T. Lei, M. Lellmann, T. Lenz, C. Li, C. Li, C. H. Li, C. K. Li, Cheng Li, D. M. Li, F. Li, G. Li, H. B. Li, H. J. Li, H. N. Li, Hui Li, J. R. Li, J. S. Li, K. Li, K. L. Li, K. L. Li, L. J. Li, Lei Li, M. H. Li, M. R. Li, P. L. Li, P. R. Li, Q. M. Li, Q. X. Li, R. Li, T. Li, T. Y. Li, W. D. Li, W. G. Li, X. Li, X. H. Li, X. L. Li, X. Y. Li, X. Z. Li, Y. Li, Y. G. Li, Y. P. Li, Z. J. Li, Z. Y. Li, C. Liang, H. Liang, Y. F. Liang, Y. T. Liang, G. R. Liao, L. B. Liao, M. H. Liao, Y. P. Liao, J. Libby, A. Limphirat, C. C. Lin, C. X. Lin, D. X. Lin, L. Q. Lin, T. Lin, B. J. Liu, B. X. Liu, C. Liu, C. X. Liu, F. Liu, F. H. Liu, Feng Liu, G. M. Liu, H. Liu, H. B. Liu, H. H. Liu, H. M. Liu, Huihui Liu, J. B. Liu, J. J. Liu, K. Liu, K. Liu, K. Y. Liu, Ke Liu, L. Liu, L. C. Liu, Lu Liu, P. L. Liu, Q. Liu, S. B. Liu, T. Liu, W. K. Liu, W. M. Liu, W. T. Liu, X. Liu, X. Liu, X. Y. Liu, Y. Liu, Y. Liu, Y. Liu, Y. B. Liu, Z. A. Liu, Z. D. Liu, Z. Q. Liu, X. C. Lou, F. X. Lu, H. J. Lu, J. G. Lu, Y. Lu, Y. H. Lu, Y. P. Lu, Z. H. Lu, C. L. Luo, J. R. Luo, J. S. Luo, M. X. Luo, T. Luo, X. L. Luo, Z. Y. Lv, X. R. Lyu, Y. F. Lyu, Y. H. Lyu, F. C. Ma, H. Ma, H. L. Ma, J. L. Ma, L. L. Ma, L. R. Ma, Q. M. Ma, R. Q. Ma, R. Y. Ma, T. Ma, X. T. Ma, X. Y. Ma, Y. M. Ma, F. E. Maas, I. MacKay, M. Maggiora, S. Malde, Y. J. Mao, Z. P. Mao, S. Marcello, F. M. Melendi, Y. H. Meng, Z. X. Meng, J. G. Messchendorp, G. Mezzadri, H. Miao, T. J. Min, R. E. Mitchell, X. H. Mo, B. Moses, N. Yu. Muchnoi, J. Muskalla, Y. Nefedov, F. Nerling, L. S. Nie, I. B. Nikolaev, Z. Ning, S. Nisar, Q. L. Niu, W. D. Niu, S. L. Olsen, Q. Ouyang, S. Pacetti, X. Pan, Y. Pan, A. Pathak, Y. P. Pei, M. Pelizaeus, H. P. Peng, Y. Y. Peng, K. Peters, J. L. Ping, R. G. Ping, S. Plura, V. Prasad, F. Z. Qi, H. R. Qi, M. Qi, S. Qian, W. B. Qian, C. F. Qiao, J. H. Qiao, J. J. Qin, J. L. Qin, L. Q. Qin, L. Y. Qin, P. B. Qin, X. P. Qin, X. S. Qin, Z. H. Qin, J. F. Qiu, Z. H. Qu, C. F. Redmer, A. Rivetti, M. Rolo, G. Rong, S. S. Rong, F. Rosini, Ch. Rosner, M. Q. Ruan, N. Salone, A. Sarantsev, Y. Schelhaas, K. Schoenning, M. Scodeggio, K. Y. Shan, W. Shan, X. Y. Shan, Z. J. Shang, J. F. Shangguan, L. G. Shao, M. Shao, C. P. Shen, H. F. Shen, W. H. Shen, X. Y. Shen, B. A. Shi, H. Shi, J. L. Shi, J. Y. Shi, S. Y. Shi, X. Shi, H. L. Song, J. J. Song, T. Z. Song, W. M. Song, Y. X. Song, S. Sosio, S. Spataro, F. Stieler, S. S Su, Y. J. Su, G. B. Sun, G. X. Sun, H. Sun, H. K. Sun, J. F. Sun, K. Sun, L. Sun, S. S. Sun, T. Sun, Y. C. Sun, Y. H. Sun, Y. J. Sun, Y. Z. Sun, Z. Q. Sun, Z. T. Sun, C. J. Tang, G. Y. Tang, J. Tang, L. F. Tang, M. Tang, Y. A. Tang, L. Y. Tao, M. Tat, J. X. Teng, J. Y. Tian, W. H. Tian, Y. Tian, Z. F. Tian, I. Uman, B. Wang, B. Wang, Bo Wang, C. Wang, Cong Wang, D. Y. Wang, H. J. Wang, J. J. Wang, K. Wang, L. L. Wang, L. W. Wang, M. Wang, M. Wang, N. Y. Wang, S. Wang, T. Wang, T. J. Wang, W. Wang, W. Wang, W. P. Wang, X. Wang, X. F. Wang, X. J. Wang, X. L. Wang, X. N. Wang, Y. Wang, Y. D. Wang, Y. F. Wang, Y. H. Wang, Y. L. Wang, Y. N. Wang, Y. Q. Wang, Yaqian Wang, Yi Wang, Yuan Wang, Z. Wang, Z. L. Wang, Z. L. Wang, Z. Q. Wang, Z. Y. Wang, D. H. Wei, H. R. Wei, F. Weidner, S. P. Wen, Y. R. Wen, U. Wiedner, G. Wilkinson, M. Wolke, C. Wu, J. F. Wu, L. H. Wu, L. J. Wu, Lianjie Wu, S. G. Wu, S. M. Wu, X. Wu, X. H. Wu, Y. J. Wu, Z. Wu, L. Xia, X. M. Xian, B. H. Xiang, T. Xiang, D. Xiao, G. Y. Xiao, H. Xiao, Y. L. Xiao, Z. J. Xiao, C. Xie, K. J. Xie, X. H. Xie, Y. Xie, Y. G. Xie, Y. H. Xie, Z. P. Xie, T. Y. Xing, C. F. Xu, C. J. Xu, G. F. Xu, H. Y. Xu, H. Y. Xu, M. Xu, Q. J. Xu, Q. N. Xu, T. D. Xu, W. L. Xu, X. P. Xu, Y. Xu, Y. Xu, Y. C. Xu, Z. S. Xu, H. Y. Yan, L. Yan, W. B. Yan, W. C. Yan, W. P. Yan, X. Q. Yan, H. J. Yang, H. L. Yang, H. X. Yang, J. H. Yang, R. J. Yang, T. Yang, Y. Yang, Y. F. Yang, Y. H. Yang, Y. Q. Yang, Y. X. Yang, Y. Z. Yang, M. Ye, M. H. Ye, Z. J. Ye, Junhao Yin, Z. Y. You, B. X. Yu, C. X. Yu, G. Yu, J. S. Yu, M. C. Yu, T. Yu, X. D. Yu, Y. C. Yu, C. Z. Yuan, H. Yuan, J. Yuan, J. Yuan, L. Yuan, S. C. Yuan, Y. Yuan, Z. Y. Yuan, C. X. Yue, Ying Yue, A. A. Zafar, S. H. Zeng, X. Zeng, Y. Zeng, Y. J. Zeng, Y. J. Zeng, X. Y. Zhai, Y. H. Zhan, A. Q. Zhang, B. L. Zhang, B. X. Zhang, D. H. Zhang, G. Y. Zhang, G. Y. Zhang, H. Zhang, H. Zhang, H. C. Zhang, H. H. Zhang, H. Q. Zhang, H. R. Zhang, H. Y. Zhang, J. Zhang, J. Zhang, J. J. Zhang, J. L. Zhang, J. Q. Zhang, J. S. Zhang, J. W. Zhang, J. X. Zhang, J. Y. Zhang, J. Z. Zhang, Jianyu Zhang, L. M. Zhang, Lei Zhang, N. Zhang, P. Zhang, Q. Zhang, Q. Y. Zhang, R. Y. Zhang, S. H. Zhang, Shulei Zhang, X. M. Zhang, X. Y Zhang, X. Y. Zhang, Y. Zhang, Y. Zhang, Y. T. Zhang, Y. H. Zhang, Y. M. Zhang, Z. D. Zhang, Z. H. Zhang, Z. L. Zhang, Z. L. Zhang, Z. X. Zhang, Z. Y. Zhang, Z. Y. Zhang, Z. Z. Zhang, Zh. Zh. Zhang, G. Zhao, J. Y. Zhao, J. Z. Zhao, L. Zhao, Lei Zhao, M. G. Zhao, N. Zhao, R. P. Zhao, S. J. Zhao, Y. B. Zhao, Y. L. Zhao, Y. X. Zhao, Z. G. Zhao, A. Zhemchugov, B. Zheng, B. M. Zheng, J. P. Zheng, W. J. Zheng, X. R. Zheng, Y. H. Zheng, B. Zhong, X. Zhong, H. Zhou, J. Q. Zhou, J. Y. Zhou, S. Zhou, X. Zhou, X. K. Zhou, X. R. Zhou, X. Y. Zhou, Y. Z. Zhou, Z. C. Zhou, A. N. Zhu, J. Zhu, K. Zhu, K. J. Zhu, K. S. Zhu, L. Zhu, L. X. Zhu, S. H. Zhu, T. J. Zhu, W. D. Zhu, W. D. Zhu, W. J. Zhu, W. Z. Zhu, Y. C. Zhu, Z. A. Zhu, X. Y. Zhuang, J. H. Zou, J. Zu
  • 分類：hep-ex
  • 原文連結：http://arxiv.org/abs/2503.02196v1

原文摘要：Using $e^+e^-$ collision data taken at the center-of-mass energy of 3.773 GeV with the BESIII detector, corresponding to an integrated luminosity of 20.3 fb$^{-1}$, we report the first amplitude and angular analyses of the semileptonic decays $D^{+(0)}\to K^-\pi^+\pi^{0(-)} e^+\nu_e$. From the amplitude analysis, we determine for the first time the hadronic form factors of the semileptonic $D$ decays into the axial-vector meson $\bar{K}_1(1270)$ to be $r_A=(-11.2\pm1.0\pm0.9)\times10^{-2}$ and $r_V = (-4.3\pm 1.0\pm2.4)\times 10^{-2}$. The angular analysis yields an up-down asymmetry $\mathcal{A}^\prime_{ud} = 0.01\pm0.11$, which is consistent with the Standard Model prediction. 中文摘要：使用BESIII探測器在3.773 GeV質心能量下採集的$e^+e^-$對撞數據，對應積分亮度為20.3 fb$^{-1}$，我們首次報告了半輕子衰變$D^{+(0)}\to K^-\pi^+\pi^{0(-)} e^+\nu_e$的振幅和角分佈分析。通過振幅分析，我們首次確定了半輕子$D$衰變到軸矢量介子$\bar{K}_1(1270)$的強子形狀因子為$r_A=(-11.2\pm1.0\pm0.9)\times10^{-2}$和$r_V = (-4.3\pm 1.0\pm2.4)\times 10^{-2}$。角分佈分析得到的上下不對稱性$\mathcal{A}^\prime_{ud} = 0.01\pm0.11$，與標準模型的預測一致。

摘要

  • 原文標題：Super-Linear Growth and Rising Inequality in Online Social Communities: Insights from Reddit
  • 中文標題：在線社交社區中的超線性增長與不平等加劇：來自Reddit的洞察
  • 發佈日期：2025-03-04 14:22:45+00:00
  • 作者：Guilherme Machado, Diogo Pacheco, Ronaldo Menezes, Gareth Baxter
  • 分類：physics.soc-ph
  • 原文連結：http://arxiv.org/abs/2503.02661v1

原文摘要：We study the effect of the number of users on the activity of communities within the online content sharing and discussion platform Reddit, called subreddits. We found that comment activity on Reddit has a heavy-tailed distribution, where a large fraction of the comments are made by a small set of users. Furthermore, as subreddits grow in size, this behavior becomes stronger, with activity (measured by the comments made in a subreddit) becoming even more centralised in a (relatively) smaller core of users. We verify that these changes are not explained by finite size nor by sampling effects. Instead, we observe a systematic change of the distribution with subreddit size. To quantify the centralisation and inequality of activity in a subreddit, we used the Gini coefficient. We found that as subreddits grow in users, so does the Gini coefficient, seemingly as a natural effect of the scaling. We found that the excess number of comments (the total number of comments minus the total number of users) follows a power law with exponent 1.27. For each subreddit we considered a snapshot of one month of data, as a compromise between statistical relevance and change in the system's dynamics. We show results over the whole year 2021 (with each subreddit having twelve snapshots, at most), nevertheless all results were consistent when using a single month or different years. 中文摘要：我們研究了用戶數量對在線內容分享和討論平台Reddit（稱為subreddits）中社區活動的影響。我們發現，Reddit上的評論活動呈現出重尾分佈，即大部分評論由一小部分用戶完成。此外，隨着subreddits規模的擴大，這種行為變得更加明顯，活動（通過subreddit中的評論數量衡量）更加集中在（相對）較小的核心用戶群體中。我們驗證了這些變化不能通過有限規模或抽樣效應來解釋。相反，我們觀察到分佈隨着subreddit規模的系統性變化。為了量化subreddit中活動的集中度和不平等性，我們使用了基尼係數。我們發現，隨着subreddits用戶數量的增加，基尼係數也隨之增加，這似乎是規模擴展的自然結果。我們發現，評論的過剩數量（總評論數減去總用戶數）遵循指數為1.27的冪律分佈。對於每個subreddit，我們考慮了一個月的數據快照，作為統計相關性和系統動態變化之間的折衷。我們展示了2021年全年的結果（每個subreddit最多有十二個快照），然而，使用單個月份或不同年份時，所有結果都是一致的。

摘要

  • 原文標題：Inferring Galactic Parameters from Chemical Abundances with Simulation-Based Inference
  • 中文標題：基於模擬推理從化學豐度推斷銀河系參數
  • 發佈日期：2025-03-04 10:05:58+00:00
  • 作者：Tobias Buck, Berkay Günes, Giuseppe Viterbo, William H. Oliver, Sven Buder
  • 分類：astro-ph.GA, astro-ph.IM, physics.comp-ph, physics.data-an, physics.space-ph
  • 原文連結：http://arxiv.org/abs/2503.02456v1

原文摘要：Galactic chemical abundances provide crucial insights into fundamental galactic parameters, such as the high-mass slope of the initial mass function (IMF) and the normalization of Type Ia supernova (SN Ia) rates. Constraining these parameters is essential for advancing our understanding of stellar feedback, metal enrichment, and galaxy formation processes. However, traditional Bayesian inference techniques, such as Hamiltonian Monte Carlo (HMC), are computationally prohibitive when applied to large datasets of modern stellar surveys. We leverage simulation-based-inference (SBI) as a scalable, robust, and efficient method for constraining galactic parameters from stellar chemical abundances and demonstrate its the advantages over HMC in terms of speed, scalability, and robustness against model misspecifications. We combine a Galactic Chemical Evolution (GCE) model, CHEMPY, with a neural network emulator and a Neural Posterior Estimator (NPE) to train our SBI pipeline. Mock datasets are generated using CHEMPY, including scenarios with mismatched nucleosynthetic yields, with additional tests conducted on data from a simulated Milky Way-like galaxy. SBI results are benchmarked against HMC-based inference, focusing on computational performance, accuracy, and resilience to systematic discrepancies. SBI achieves a $\sim75,600\times$ speed-up compared to HMC, reducing inference runtime from $\gtrsim42$ hours to mere seconds for thousands of stars. Inference on $1,000$ stars yields precise estimates for the IMF slope ($\alpha_{\rm IMF} = -2.298 \pm 0.002$) and SN Ia normalization ($\log_{10}(N_{\rm Ia}) = -2.885 \pm 0.003$), deviating less than 0.05% from the ground truth. SBI also demonstrates similar robustness to model misspecification than HMC, recovering accurate parameters even with alternate yield tables or data from a cosmological simulation. (shortened...) 中文摘要：銀河化學豐度為基本銀河參數提供了關鍵的見解，例如初始質量函數（IMF）的高質量斜率和Ia型超新星（SN Ia）速率的歸一化。約束這些參數對於推進我們對恆星反饋、金屬富集和星系形成過程的理解至關重要。然而，傳統的貝葉斯推斷技術，如哈密頓蒙特卡洛（HMC），在處理現代恆星調查的大數據集時計算上是不切實際的。我們利用基於模擬的推斷（SBI）作為一種可擴展、穩健且高效的方法，從恆星化學豐度中約束銀河參數，並展示了其在速度、可擴展性和對模型錯誤設定的魯棒性方面相對於HMC的優勢。我們將銀河化學演化（GCE）模型CHEMPY與神經網絡模擬器和神經後驗估計器（NPE）結合，訓練我們的SBI管道。使用CHEMPY生成模擬數據集，包括核合成產量不匹配的情景，並在模擬的類似銀河系的數據上進行額外測試。SBI結果與基於HMC的推斷進行基準測試，重點關注計算性能、準確性和對系統差異的恢復能力。SBI實現了與HMC相比約75,600倍的加速，將數千顆恆星的推斷運行時間從超過42小時減少到僅幾秒鐘。對1,000顆恆星的推斷得出了IMF斜率（$\alpha_{\rm IMF} = -2.298 \pm 0.002$）和SN Ia歸一化（$\log_{10}(N_{\rm Ia}) = -2.885 \pm 0.003$）的精確估計，與真實值的偏差小於0.05%。SBI還展示了與HMC相似的模型錯誤設定魯棒性，即使使用替代的產量表或來自宇宙學模擬的數據，也能恢復準確的參數。（簡化...）

摘要

  • 原文標題：Calibration of the mechanical boundary conditions for a patient-specific thoracic aorta model including the heart motion effect
  • 中文標題：患者特異性胸主動脈模型的機械邊界條件校準，包括心臟運動效應
  • 發佈日期：2025-03-04 10:50:10+00:00
  • 作者：Leonardo Geronzi, Aline Bel-Brunon, Antonio Martinez, Michel Rochette, Marco Sensale, Olivier Bouchot, Alain Lalande, Siyu Lin, Pier Paolo Valentini, Marco Evangelos Biancolini
  • 分類：physics.med-ph, cs.NA, math.NA
  • 原文連結：http://arxiv.org/abs/2503.02485v1

原文摘要：Objective: we propose a procedure for calibrating 4 parameters governing the mechanical boundary conditions (BCs) of a thoracic aorta (TA) model derived from one patient with ascending aortic aneurysm. The BCs reproduce the visco-elastic structural support provided by the soft tissue and the spine and allow for the inclusion of the heart motion effect. Methods: we first segment the TA from magnetic resonance imaging (MRI) angiography and derive the heart motion by tracking the aortic annulus from cine-MRI. A rigid-wall fluid-dynamic simulation is performed to derive the time-varying wall pressure field. We build the finite element model considering patient-specific material properties and imposing the derived pressure field and the motion at the annulus boundary. The calibration, which involves the zero-pressure state computation, is based on purely structural simulations. After obtaining the vessel boundaries from the cine-MRI sequences, an iterative procedure is performed to minimize the distance between them and the corresponding boundaries derived from the deformed structural model. A strongly-coupled fluid-structure interaction (FSI) analysis is finally performed with the tuned parameters and compared to the purely structural simulation. Results and Conclusion: the calibration with structural simulations allows to reduce maximum and mean distances between image-derived and simulation-derived boundaries from 8.64 mm to 6.37 mm and from 2.24 mm to 1.83 mm, respectively. The maximum root mean square error between the deformed structural and FSI surface meshes is 0.19 mm. This procedure may prove crucial for increasing the model fidelity in replicating the real aortic root kinematics. 中文摘要：摘要：目標：我們提出了一種用於校準控制患者特異性胸主動脈（TA）模型機械邊界條件（BCs）的4個參數的程序，該模型源自一名患有升主動脈瘤的患者。這些邊界條件再現了軟組織和脊柱提供的粘彈性結構支持，並允許納入心臟運動效應。方法：我們首先從磁共振成像（MRI）血管造影中分割出胸主動脈，並通過追蹤電影MRI中的主動脈環來推導心臟運動。進行剛性壁流體動力學模擬以推導隨時間變化的壁壓力場。我們構建了有限元模型，考慮了患者特異性材料屬性，並施加了推導出的壓力場和環邊界的運動。校準過程涉及零壓力狀態計算，基於純結構模擬。在從電影MRI序列中獲得血管邊界後，執行迭代程序以最小化它們與從變形結構模型推導出的相應邊界之間的距離。最後，使用調整後的參數進行強耦合流體-結構相互作用（FSI）分析，並與純結構模擬進行比較。結果和結論：通過結構模擬的校準，圖像推導和模擬推導的邊界之間的最大和平均距離分別從8.64毫米減少到6.37毫米和從2.24毫米減少到1.83毫米。變形結構和FSI表面網格之間的最大均方根誤差為0.19毫米。該程序可能對提高模型在複製真實主動脈根部運動學方面的保真度至關重要。

摘要

  • 原文標題：Prospects for Pentaquark Baryon Search with the Upgraded LEPS2 Facility
  • 中文標題：升級版LEPS2設施下五夸克重子搜索的前景
  • 發佈日期：2025-03-04 11:47:40+00:00
  • 作者：T. Nakano, S. Ajimura, Y. Asano, S. Dat'e, T. Hashimoto, A. Higashi, T. Hotta, T. Ishikawa, H. Katsuragawa, R. Kobayakawa, H. Kohri, K. Mizutani, Y. Ohashi, H. Ohkuma, S. Y. Ryu, S. Suzuki, S. Tanaka, K. Watanabe, B. Yan, T. Yorita, M. Yosoi, G. Kojima, M. Miyabe, N. Muramatsu, H. Ohnishi, Y. Sada, H. Shimizu, A. O. Tokiyasu, M. Niiyama, K. Nishi, J. K. Ahn, Y. Ma, T. H. Nam, C. Rangacharyulu, M. Sumihama, C. Yoshida
  • 分類：hep-ex, nucl-ex
  • 原文連結：http://arxiv.org/abs/2503.02528v1

原文摘要：We present prospects for the $\Theta^+$ pentaquark baryon search using the newly constructed LEPS2 facility at SPring-8. The LEPS2 detector system features significant improvements in acceptance for multi-particle final states compared to previous experiments. Our search employs two complementary strategies: direct production in the $\gamma n \to K^-\Theta^+$ reaction using a liquid deuterium target with a photon beam up to 2.4 GeV, and $\bar{K}^{*0}$-associated $\Theta^+$ production using a liquid hydrogen target with a photon beam up to 2.9 GeV. The extended acceptance covers both forward and large angle regions, effectively spanning the kinematic regions explored by previous LEPS and CLAS experiments. The large acceptance and improved resolution of LEPS2, combined with these complementary approaches, provide unprecedented sensitivity for establishing the existence of the $\Theta^+$ or placing definitive upper limits on its production. 中文摘要：我們展示了使用SPring-8新建設的LEPS2設施進行$\Theta^+$五夸克重子搜索的前景。LEPS2探測器系統在多粒子末態接受度方面相比之前的實驗有顯著改進。我們的搜索採用兩種互補策略：使用能量高達2.4 GeV的光子束和液態氘靶直接產生$\gamma n \to K^-\Theta^+$反應，以及使用能量高達2.9 GeV的光子束和液態氫靶進行$\bar{K}^{*0}$相關的$\Theta^+$產生。擴展的接受度覆蓋了前向和大角度區域，有效涵蓋了之前LEPS和CLAS實驗探索的運動學區域。LEPS2的大接受度和改進的解像度，結合這些互補方法，為確定$\Theta^+$的存在或對其產生設定明確的上限提供了前所未有的靈敏度。

摘要

  • 原文標題：A New $\sim 5σ$ Tension at Characteristic Redshift from DESI DR1 and DES-SN5YR observations
  • 中文標題：DESI DR1 和 DES-SN5YR 觀測中特徵紅移處的新 $\sim 5σ$ 張力
  • 發佈日期：2025-03-04 18:58:15+00:00
  • 作者：Purba Mukherjee, Anjan A Sen
  • 分類：astro-ph.CO, cs.LG, gr-qc, hep-th
  • 原文連結：http://arxiv.org/abs/2503.02880v1

原文摘要：We perform a model-independent reconstruction of the angular diameter distance ($D_{A}$) using the Multi-Task Gaussian Process (MTGP) framework with DESI-DR1 BAO and DES-SN5YR datasets. We calibrate the comoving sound horizon at the baryon drag epoch $r_d$ to the Planck best-fit value, ensuring consistency with early-universe physics. With the reconstructed $D_A$ at two key redshifts, $z\sim 1.63$ (where $D_{A}^{\prime} =0$) and at $z\sim 0.512$ (where $D_{A}^{\prime} = D_{A}$), we derive the expansion rate of the Universe $H(z)$ at these redshifts. Our findings reveal that at $z\sim 1.63$, the $H(z)$ is fully consistent with the Planck-2018 $\Lambda$CDM prediction, confirming no new physics at that redshift. However, at $z \sim 0.512$, the derived $H(z)$ shows a more than $5\sigma$ discrepancy with the Planck-2018 $\Lambda$CDM prediction, suggesting a possible breakdown of the $\Lambda$CDM model as constrained by Planck-2018 at this lower redshift. This emerging $\sim 5\sigma$ tension at $z\sim 0.512$, distinct from the existing ``Hubble Tension, may signal the first strong evidence for new physics at low redshifts. 中文摘要：我們使用多任務高斯過程（MTGP）框架結合DESI-DR1 BAO和DES-SN5YR數據集，對角直徑距離（$D_{A}$）進行了模型無關的重建。我們將重子拖曳時期的共動聲視界$r_d$校準為普朗克最佳擬合值，確保與早期宇宙物理學的一致性。通過重建的兩個關鍵紅移處的$D_A$，即$z\sim 1.63$（其中$D_{A}^{\prime} =0$）和$z\sim 0.512$（其中$D_{A}^{\prime} = D_{A}$），我們推導了這些紅移處的宇宙膨脹率$H(z)$。我們的研究結果表明，在$z\sim 1.63$處，$H(z)$與普朗克-2018 $\Lambda$CDM預測完全一致，確認在該紅移處沒有新的物理現象。然而，在$z \sim 0.512$處，推導出的$H(z)$與普朗克-2018 $\Lambda$CDM預測顯示出超過$5\sigma$的差異，表明在較低紅移處，普朗克-2018約束的$\Lambda$CDM模型可能失效。這一在$z\sim 0.512$處新出現的$\sim 5\sigma$張力，與現有的「哈勃張力」不同，可能是低紅移處新物理現象的第一個強有力證據。

摘要

  • 原文標題：Trust and Friction: Negotiating How Information Flows Through Decentralized Social Media
  • 中文標題：信任與摩擦：去中心化社交媒體中信息流動的協商
  • 發佈日期：2025-03-04 00:29:32+00:00
  • 作者：Sohyeon Hwang, Priyanka Nanayakkara, Yan Shvartzshnaider
  • 分類：cs.HC, cs.CY, cs.SI
  • 原文連結：http://arxiv.org/abs/2503.02150v1

原文摘要：Decentralized social media protocols enable users in independent, user-hosted servers (i.e., instances) to interact with each other while they self-govern. This community-based model of social media governance opens up new opportunities for tailored decision-making about information flows -- i.e., what user data is shared to whom and when -- and in turn, for protecting user privacy. To better understand how community governance shapes privacy expectations on decentralized social media, we conducted a semi-structured interview with 23 users of the Fediverse, a decentralized social media network. Our findings illustrate important factors that shape a community's understandings of information flows, such as rules and proactive efforts from admins who are perceived as trustworthy. We also highlight governance frictions between communities that raise new privacy risks due to incompatibilities in values, security practices, and software. Our findings highlight the unique challenges of decentralized social media, suggest design opportunities to address frictions, and outline the role of participatory decision-making to realize the full potential of decentralization. 中文摘要：去中心化社交媒體協議使得獨立、用戶託管的伺服器（即實例）中的用戶可以相互交互，同時實現自我治理。這種基於社區的社交媒體治理模式為信息流的定製決策（即哪些用戶數據在何時與誰共享）以及保護用戶私隱提供了新的機會。為了更好地理解社區治理如何塑造去中心化社交媒體上的私隱期望，我們對23名Fediverse（一個去中心化社交媒體網絡）用戶進行了半結構化訪談。我們的研究結果揭示了塑造社區對信息流理解的重要因素，例如被視為可信的管理員的規則和積極努力。我們還強調了社區之間的「治理摩擦」，這些摩擦由於價值觀、安全實踐和軟件的不兼容性而引發新的私隱風險。我們的研究結果突出了去中心化社交媒體的獨特挑戰，提出了解決摩擦的設計機會，並概述了參與式決策在實現去中心化全部潛力中的作用。

摘要

  • 原文標題：In-Depth Analysis of Automated Acne Disease Recognition and Classification
  • 中文標題：深度分析自動痤瘡疾病識別與分類
  • 發佈日期：2025-03-04 17:58:44+00:00
  • 作者：Afsana Ahsan Jeny, Masum Shah Junayed, Md Robel Mia, Md Baharul Islam
  • 分類：cs.CV
  • 原文連結：http://arxiv.org/abs/2503.02835v1

原文摘要：Facial acne is a common disease, especially among adolescents, negatively affecting both physically and psychologically. Classifying acne is vital to providing the appropriate treatment. Traditional visual inspection or expert scanning is time-consuming and difficult to differentiate acne types. This paper introduces an automated expert system for acne recognition and classification. The proposed method employs a machine learning-based technique to classify and evaluate six types of acne diseases to facilitate the diagnosis of dermatologists. The pre-processing phase includes contrast improvement, smoothing filter, and RGB to L*a*b color conversion to eliminate noise and improve the classification accuracy. Then, a clustering-based segmentation method, k-means clustering, is applied for segmenting the disease-affected regions that pass through the feature extraction step. Characteristics of these disease-affected regions are extracted based on a combination of gray-level co-occurrence matrix (GLCM) and Statistical features. Finally, five different machine learning classifiers are employed to classify acne diseases. Experimental results show that the Random Forest (RF) achieves the highest accuracy of 98.50%, which is promising compared to the state-of-the-art methods. 中文摘要：面部痤瘡是一種常見疾病，尤其在青少年中，對身體和心理都有負面影響。痤瘡的分類對於提供適當的治療至關重要。傳統的視覺檢查或專家掃描耗時且難以區分痤瘡類型。本文介紹了一種用於痤瘡識別和分類的自動化專家系統。所提出的方法採用基於機器學習的技術對六種痤瘡疾病進行分類和評估，以輔助皮膚科醫生的診斷。預處理階段包括對比度增強、平滑濾波和RGB到L*a*b顏色轉換，以消除噪聲並提高分類準確性。然後，應用基於聚類的分割方法——k均值聚類，對通過特徵提取步驟的疾病影響區域進行分割。這些疾病影響區域的特徵基於灰度共生矩陣（GLCM）和統計特徵的組合進行提取。最後，採用五種不同的機器學習分類器對痤瘡疾病進行分類。實驗結果表明，隨機森林（RF）達到了98.50%的最高準確率，與現有最先進的方法相比具有顯著優勢。

摘要

  • 原文標題：Evaluating a Digital Speech Therapy App for Stuttering: A Pilot Validation Study
  • 中文標題：評估一款針對口吃的數字語音治療應用：一項試點驗證研究
  • 發佈日期：2025-03-04 16:07:16+00:00
  • 作者：Urvisha Shethia, Vedali Inamdar, Viraj Kulkarni
  • 分類：cs.HC
  • 原文連結：http://arxiv.org/abs/2503.02743v1

原文摘要：Stuttering is a speech disorder that disrupts fluency and often leads to significant psychological and social challenges. This study evaluates the effectiveness of Eloquent, a digital speech therapy app, by analyzing pre-therapy and post-therapy speech samples using the Stuttering Severity Index-4 (SSI-4) and the S24 communication and attitude scale. Results indicate significant improvements in fluency, with reductions in SSI-4 scores across reading, speaking, duration, and physical concomitant metrics. Additionally, participants demonstrated a more positive attitude towards communication post-therapy, as evidenced by lower S24 scores. These findings highlight the potential of technology-driven, structured speech therapy interventions to deliver measurable improvements in stuttering severity and communication confidence. 中文摘要：口吃是一種影響言語流暢性的語言障礙，常導致顯著的心理和社會挑戰。本研究通過使用口吃嚴重程度指數-4（SSI-4）和S24溝通與態度量表，分析治療前後的言語樣本，評估了數字言語治療應用Eloquent的有效性。結果表明，在閱讀、說話、持續時間和身體伴隨指標方面，SSI-4得分顯著降低，流暢性顯著提高。此外，參與者在治療後的溝通態度更加積極，S24得分降低證明了這一點。這些發現突顯了技術驅動的結構化言語治療干預在改善口吃嚴重程度和溝通信心方面的潛力。

取自 "http://zh.wikiedge.org/index.php?title=WikiEdge:ArXiv速递/2025-03-04&oldid=2745"