Abstract:Recovering high-resolution structural and compositional information from coherent X-ray measurements involves solving coupled, nonlinear, and ill-posed inverse problems. Ptychography reconstructs a complex transmission function from overlapping diffraction patterns, while X-ray fluorescence provides quantitative, element-specific contrast at lower spatial resolution. We formulate a joint variational framework that integrates these two modalities into a single nonlinear least-squares problem with shared spatial variables. This formulation enforces cross-modal consistency between structural and compositional estimates, improving conditioning and promoting stable convergence. The resulting optimization couples complementary contrast mechanisms (i.e., phase and absorption from ptychography, elemental composition from fluorescence) within a unified inverse model. Numerical experiments on simulated data demonstrate that the joint reconstruction achieves faster convergence, sharper and more quantitative reconstructions, and lower relative error compared with separate inversions. The proposed approach illustrates how multimodal variational formulations can enhance stability, resolution, and interpretability in computational X-ray imaging.
From: Chengru Zou [view email]
[v1]
Tue, 4 Nov 2025 00:44:46 UTC (17,561 KB)
[v2]
Sat, 2 May 2026 17:02:58 UTC (18,002 KB)
[v3]
Tue, 12 May 2026 14:30:16 UTC (18,002 KB)
[v4]
Fri, 12 Jun 2026 02:14:16 UTC (18,003 KB)
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