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Quantum Algorithm Framework for Phase-Contrast Transmission Electron Microscopy Image Simulation

Quantum Physics 2026-02-17 v1 Materials Science Computational Physics

Abstract

We present a quantum algorithmic framework for simulating phase-contrast transmission electron microscopy (CTEM) image formation using a fault-tolerant, gate-based quantum circuit model. The electron wavefield on an N×NN\times N grid is amplitude-encoded into a 2log2N2\log_2 N-qubit register. Free-space propagation and objective-lens aberrations are implemented via two-dimensional quantum Fourier transforms (QFTs) and diagonal phase operators in reciprocal space, while specimen interaction is modeled under the weak phase object approximation (WPOA) as a position-dependent phase grating. We validate projected potentials, contrast transfer function (CTF) behavior, and image contrast trends against classical multislice simulations for MoS2_2 over experimentally relevant parameters, and provide resource estimates and key assumptions that determine end-to-end runtime. While extracting complete N×NN\times N intensity images requires O(N2/ϵ2)O(N^2/\epsilon^2) measurements that preclude advantage for full-image reconstruction, the framework enables quantum advantage for tasks requiring Fourier-space queries, global image statistics, or phase-coherent observables inaccessible to classical intensity-only detection. This framework provides a physics-grounded mapping from CTEM theory to quantum circuits and establishes a baseline for extending toward full multislice and inelastic scattering models.

Keywords

Cite

@article{arxiv.2602.13438,
  title  = {Quantum Algorithm Framework for Phase-Contrast Transmission Electron Microscopy Image Simulation},
  author = {Sean D. Lam and Roberto dos Reis},
  journal= {arXiv preprint arXiv:2602.13438},
  year   = {2026}
}

Comments

28 pages, 9 figures (including appendices); supplementary code available at https://github.com/QuScope/examples-applications/blob/main/notebooks/Quantum_ctem_paper_full_example.ipynb

R2 v1 2026-07-01T10:36:13.468Z