AI 中文总结
该研究针对即将到来的CMB和大尺度结构巡天需求，对CAMB进行重大更新，通过新处理超球贝塞尔函数等方法，为透镜化CMB和物质功率谱提供快速高精度预测，满足收敛目标，还探讨了相关约定依赖性，新算法和代码由LLMs或AI agents在人类监督下开发。
AI 中文摘要
即将到来的宇宙微波背景（CMB）和大尺度结构巡天需要理论功率谱在携带大部分约束能力的尺度上，数值误差远低于观测不确定性。我们描述了对CAMB的重大更新，旨在为两个关键输出提供快速、高精度预测：透镜化CMB和物质功率谱。核心进展是对用于非平坦宇宙学视线积分的超球贝塞尔函数的新处理。通过匹配它们在转折点的作用，一个领先阶的奥尔弗构造将弯曲的径向方程映射到平坦的球贝塞尔方程。得到的近似在平坦极限下是精确的，在转折点处保持平滑，并且在接近平坦时简化为平坦贝塞尔自变量和振幅的简单重新缩放。我们还描述了更新的积分器、重新校准的快速复合模型、稳定的参数化后弗里德曼暗能量演化以及CMB透镜精度的改进。通过将未加速的默认结果与更收敛的计算进行比较来评估数值收敛性。默认结果在与未来巡天相关的主要透镜化CMB和准线性物质功率范围内满足保守的逐点收敛目标$10^{-3}$。典型运行中测量的误差远小于此。我们还描述了在均匀计算试图表示再电离加热效应时，名义上线性物质功率谱的约定依赖性。基本上所有新算法和代码都是在人类监督下由大语言模型或人工智能代理开发的。
英文摘要
Upcoming cosmic microwave background (CMB) and large-scale-structure surveys require theoretical power spectra with numerical errors well below their observational uncertainties over the scales that carry most of the constraining power. We describe a substantial update to CAMB designed to provide fast, high-precision predictions for two key outputs: the lensed CMB and matter power spectra. The central development is a new treatment of the hyperspherical Bessel functions used for line-of-sight integration in non-flat cosmologies. A leading-order Olver construction maps the curved radial equation onto the flat spherical Bessel equation by matching their actions through the turning point. The resulting approximation is exact in the flat limit, remains smooth through the turning point, and reduces near flatness to a simple rescaling of the flat Bessel argument and amplitude. We also describe updated integrators, a recalibrated fast recombination model, stabilized parameterized post-Friedmann dark-energy evolution, and improvements to CMB lensing accuracy. Numerical convergence is assessed by comparing unboosted default results against more converged calculations. The defaults meet conservative $10^{-3}$ pointwise convergence targets over the main lensed-CMB and quasi-linear matter-power ranges relevant for future surveys. Errors measured in typical runs are substantially smaller than this. We also describe the convention dependence of the nominally linear matter power spectrum when a homogeneous calculation attempts to represent the effects of reionization heating. Essentially all of the new algorithms and code were developed with LLMs or AI agents under human supervision.
Comments25 pages, 4 figures. Code available at https://github.com/cmbant/camb
Journal refJCAP 10 (2026) 013
DOI：10.1088/1475-7516/2026/10/013
