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D4CNN×AnaCal: Physics-informed Machine Learning for Accurate and Precise Weak-lensing Shear Estimation

  • Authors: Shurui Lin, 书睿 林, Xiangchong Li, Ji Li, Shengcao Cao, Xin Liu, Yu-Xiong Wang

Shurui Lin et al 2026 The Astrophysical Journal 1006 .

  • Provider: AAS Journals

Caption: Figure 7.

Transformation of measured shape under rotation for our CNN model, as in Figure 3. The same galaxy profile with fixed ellipticity (e = 0.4) but different orientations (−90° to +90° between the x-axis and the major axis) is fed into the model. The predicted e1 and e2 components (blue and orange points) are compared against theoretical sine/cosine functions (dashed and dashed–dotted curves) scaled to match the measured amplitude. The vertical dotted lines mark the key reference angles at −45°, 0°, and +45°.

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