标题： 具有非恒定核解的图像减法 显示英文标题

标题： Image subtraction with non-constant kernel solutions

摘要： 结果表明，可以以最少的计算时间获得一种能够拟合核函数空间变化的非恒定核解。 与图像减法方法的新扩展相关的CPU成本几乎与拟合恒定核解的成本相同。 该方法通过一系列蒙特卡罗图像进行了验证。 模拟了点扩散函数（PSF）的变化和图像之间的微分旋转。 结果表明，即使在这些困难情况下，新方法也能达到最佳效果。 显然，最常见的仪器问题会自动被该方法纠正。 还证明了该方法不会受到图像欠采样的影响。 为了得出结论，该方法被应用于密集场的真实图像。 结果证明，在保持减影图像精度的同时，可以使用图像中更大的子区域进行拟合。 对于位于低密度场中的变源（如哈克拉透镜），这一结果尤为重要。 该方法在许多重要的天文学问题上还有许多其他有用的应用。 例如，超新星搜索应该从该方法中受益，但其他应用，如外星系造父变星调查，也应该能从中找到一些优势。 由于变异性搜索是天文学中的一个重要问题，肯定还会出现许多其他的应用。 总之，该方法在处理密集场真实图像时得到了成功应用。 显示英文摘要

摘要： It is demonstrated that non-constant kernel solution, that can fit the spatial variations of the kernel can be obtained with minimum computing time. The CPU cost required with this new extension of the image subtraction method is almost the same as for fitting constant kernel solution. The method is demonstrated with a serie of Monte-Carlo images. Differential PSF variations and differential rotation between the images are simulated. It is shown that this new method is able to achieve an optimal results even in these difficult cases. It is clear that the most frequents instrumental problems are automatically corrected by the method. It is also demonstrated that the method does not suffer problems with under-sampling of the images. To conclude the method is applied to real images of crowded field. It is proved that much larger sub-areas of the images can be used for the fit, while keeping the same accuracy in the subtracted image. This result is especially important in case of variables located in low density fields, like the Huchra lens. Many other useful applications of the method are possible for major astrophysical problems. For instance supernovas search should benefit the method, but other applications like Cepheids surveys in other galaxies should also find some advantage in using the method. Many other applications will certainly show-up, since variability search is a major issue in astronomy.