Quantum Algorithm Framework for Phase-Contrast Transmission Electron Microscopy Image Simulation
- URL: http://arxiv.org/abs/2602.13438v1
- Date: Fri, 13 Feb 2026 20:26:27 GMT
- Title: Quantum Algorithm Framework for Phase-Contrast Transmission Electron Microscopy Image Simulation
- Authors: Sean D. Lam, Roberto dos Reis,
- Abstract summary: We present a quantum algorithmic framework for simulating phase-contrast transmission electron microscopy (CTEM) image formation.<n>The framework provides a physics-grounded mapping from CTEM theory to quantum circuits.
- Score: 0.16114012813668935
- License: http://creativecommons.org/licenses/by/4.0/
- 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 $N\times N$ grid is amplitude-encoded into a $2\log_2 N$-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 MoS$_2$ over experimentally relevant parameters, and provide resource estimates and key assumptions that determine end-to-end runtime. While extracting complete $N\times N$ intensity images requires $O(N^2/ε^2)$ 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.
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