Prépublication
· 2026 arXiv
EN
We first derived the formulae of recursive reduction and dlog-form differential equations for arbitrary tree-level cosmological correlator, taking the external relations of massless bulk propagators into consideration. The differential equations could be syste...
Jiaqi Chen, Yi-Xiao Tao et al.
#hep-ph
Prépublication
· 2026 arXiv
EN
Precision spectroscopy underpins quantum sensing, atomic timekeeping, and the search for terrestrial-mass exoplanets. Finding an Earth-Sun analog requires fractional splitting of spectral features that rivals the precision of the best laboratory spectroscopy....
Connor Fredrick, Ryan K. Cole et al.
#astro-ph.IM
Prépublication
· 2026 arXiv
EN
We study a two-component dark matter model in which a real singlet scalar and an inert doublet scalar are simultaneously present alongside the Standard Model, each stabilized by an independent discrete symmetry. The real singlet undergoes a strong first-order...
Deeksha Dattaram Naik, Arnab Chaudhuri
#hep-ph
Prépublication
· 2026 arXiv
EN
Effectively preparing for changes in extreme flooding requires understanding present and future rainfall extremes with return periods up to $\sim$100-1000 years, including changes in intensity, spatial structure at km-scale and sub-daily temporal variability....
Henry Addison, Elizabeth J. Kendon et al.
#physics.ao-ph
Prépublication
· 2026 arXiv
EN
AI weather prediction models are often regarded as black boxes. Despite their impressive skill, there is little understanding of how the input data is processed during inference to produce the forecast. This limitation arises from the use of high-dimensional l...
Matthias Beylich, Kirsten I. Tempest et al.
#physics.ao-ph
Prépublication
· 2026 arXiv
EN
While LLM agents can generate visually plausible CAD assemblies, these designs often fail to fulfill their intended physical functions. We study functional CAD design, a setting where agents interpret underspecified requests to construct and iteratively revise...
Wenqian Zhang, Yangyi Huang et al.
#cs.CV
Prépublication
· 2026 arXiv
EN
Reinforcement learning enables mobile robots to make fast and scalable navigation decisions in constrained human-shared environments. However, directly extending single-robot approaches to multi-robot settings often fails to ensure safety and efficiency, espec...
Zehao Wang, Jianpeng Yao et al.
#cs.RO
Prépublication
· 2026 arXiv
EN
In this paper, we systematically investigate the mechanisms, scaling behavior, and generalization of physical Recursive self-improvement. We introduce PhysRSI-eval to quantify physical RSI through a five-axis metric: First-Attempt Performance, Efficiency, Succ...
Zekai Li, Jiayi Yu et al.
#cs.RO
Prépublication
· 2026 arXiv
EN
The goal of a world model is to capture the dynamics of an environment. This has the great appeal that it allows agents to plan and simulate a course of actions with the help of a world model. For these uses to be reliable, however, the learned dynamics must b...
Heejeong Nam, Divyat Mahajan et al.
#cs.AI
Prépublication
· 2026 arXiv
EN
Many modern language models have adopted hybrid architectures that incorporate both linear-time recurrence and softmax attention. Modern recurrence layers provide a highly expressive mixing mechanism while ensuring high throughput by compressing contextual inf...
Xingyu Shen, Yingfa Chen et al.
#cs.CL
Prépublication
· 2026 arXiv
EN
Context compression improves long-context efficiency but may introduce faithfulness issues through an information bottleneck. Existing evaluations rely on QA metrics, but a reader can still answer correctly from an unfaithful compression, so these metrics unde...
Ziqing Man, Di Wu et al.
#cs.CL
Prépublication
· 2026 arXiv
EN
In this note, we introduce the Hubble susceptibility of cosmological-collider masses, encoded in the scale dependence of the squeezed-limit oscillation. Heavy fields generically receive Hubble-induced mass corrections during inflation, and we show that the loc...
Shuntaro Aoki, Masahide Yamaguchi
#hep-th