Deep Neural Networks for Modeling Astrophysical Nuclear Reacting Flows

Kavli Affiliate: Lile Wang |Summary:In astrophysical simulations, nuclear reacting flows pose computational challenges due to the stiffness of reaction networks. We introduce neural network-based surrogate models using the DeePODE framework to enhance simulation efficiency while maintaining accuracy and robustness. Our method replaces conventional stiff ODE solvers with deep learning models trained through evolutionary Monte Carlo […]


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Detecting Intermediate-mass Black Holes Using Quasar Microlensing

Kavli Affiliate: Luis C. Ho | First 5 Authors: Zihao Wu, Luis C. Ho, , , | Summary: Recent studies suggest that numerous intermediate-mass black holes (IMBHs) may wander undetected across the Universe, emitting little radiation. These IMBHs largely preserve their birth masses, offering critical insights into the formation of heavy black hole seeds and […]


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Kimina-Prover Preview: Towards Large Formal Reasoning Models with Reinforcement Learning

Kavli Affiliate: Ran Wang | First 5 Authors: Haiming Wang, Mert Unsal, Xiaohan Lin, Mantas Baksys, Junqi Liu | Summary: We introduce Kimina-Prover Preview, a large language model that pioneers a novel reasoning-driven exploration paradigm for formal theorem proving, as showcased in this preview release. Trained with a large-scale reinforcement learning pipeline from Qwen2.5-72B, Kimina-Prover […]


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Cosmogenic Neutrino Point Source and KM3-230213A

Kavli Affiliate: Zhuo Li | First 5 Authors: Qinyuan Zhang, Tian-Qi Huang, Zhuo Li, , | Summary: Cosmogenic neutrinos (CNs) are produced by ultra-high energy cosmic rays (UHECRs) interacting with cosmic background radiation. We investigated the properties of CN point/extended sources, i.e, the neutrino spectrum, and angular profile as functions of time, by assuming that […]


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Cosmogenic Neutrino Point Source and KM3-230213A

Kavli Affiliate: Zhuo Li | First 5 Authors: Qinyuan Zhang, Qinyuan Zhang, , , | Summary: Cosmogenic neutrinos (CNs) are produced by ultra-high energy cosmic rays (UHECRs) interacting with cosmic background radiation. We investigated the properties of CN point/extended sources, i.e, the neutrino spectrum, and angular profile as functions of time, by assuming that UHECR […]


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Bumblebee cosmology: The FLRW solution and the CMB temperature anisotropy

Kavli Affiliate: Lijing Shao | Summary:We put into test the idea of replacing dark energy by a vector field against the cosmic microwave background (CMB) observation using the simplest vector-tensor theory, where a massive vector field couples to the Ricci scalar and the Ricci tensor quadratically. First, a remarkable Friedmann-Lemaître-Robertson-Walker (FLRW) metric solution that is […]


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GenEDA: Towards Generative Netlist Functional Reasoning via Cross-Modal Circuit Encoder-Decoder Alignment

Kavli Affiliate: Jing Wang | First 5 Authors: Wenji Fang, Wenji Fang, , , | Summary: The success of foundation AI has motivated the research of circuit foundation models, which are customized to assist the integrated circuit (IC) design process. However, existing pre-trained circuit foundation models are typically limited to standalone encoders for predictive tasks […]


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The X-ray statistical properties of dust-obscured galaxies detected by eROSITA

Kavli Affiliate: Kohei Inayoshi | First 5 Authors: Akatoki Noboriguchi, Kohei Ichikawa, Yoshiki Toba, Tom Dwelly, Kohei Inayoshi | Summary: Dust-obscured galaxies (DOGs) are considered to be in a co-evolution phase, with the associated active galactic nuclei (AGN) obscured by dust and gas. Although the DOGs are thought to harbor rapidly growing SMBHs, their X-ray […]


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A Survey of Machine Learning Models and Datasets for the Multi-label Classification of Textual Hate Speech in English

Kavli Affiliate: Xian Chen | First 5 Authors: Julian Bäumler, Louis Blöcher, Lars-Joel Frey, Xian Chen, Markus Bayer | Summary: The dissemination of online hate speech can have serious negative consequences for individuals, online communities, and entire societies. This and the large volume of hateful online content prompted both practitioners’, i.e., in content moderation or […]


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Genetic Programming with Reinforcement Learning Trained Transformer for Real-World Dynamic Scheduling Problems

Kavli Affiliate: Xian Chen | First 5 Authors: Xian Chen, Rong Qu, Jing Dong, Ruibin Bai, Yaochu Jin | Summary: Dynamic scheduling in real-world environments often struggles to adapt to unforeseen disruptions, making traditional static scheduling methods and human-designed heuristics inadequate. This paper introduces an innovative approach that combines Genetic Programming (GP) with a Transformer […]


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