Deep learning interatomic potential for metal-doped silicon carbide nanotubes: Development, validation, and mechanical response

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qemu-system-x86_64 -m 8G -cpu host -smp 4 -boot d -hda vm_disk.qcow2 -netdev user,id=mynet0 -device e1000,netdev=mynet0 -serial stdio -enable-kvm

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SSIM (Structural Similarity Index Measure) compares two images by evaluating luminance, contrast, and structural patterns across local windows. It returns a score from -1 to 1: 1.0 means the images are pixel-identical, 0 means no structural correlation, and negative values mean the images are anti-correlated (less alike than random noise). For glyph comparison, it answers the question: do these two rendered characters share the same visual structure?

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