Quantum Communication and Model Simulation

Background

The rapid growth of high-resolution visual content in modern communication systems has intensified the demand for robust and efficient image transmission under noisy and bandwidth-limited conditions. Although classical techniques such as OFDM and advanced source coding have significantly improved reliability, compressed image data remain highly sensitive to channel impairments, where even small transmission errors can cause severe perceptual degradation. Recent studies have demonstrated that quantum communication can provide enhanced robustness by exploiting quantum superposition and high-dimensional state representations. In particular, frequency-domain quantum processing using the quantum Fourier transform enables orthogonal representations that are inherently resilient to noise, analogous to classical OFDM but operating within the quantum domain. Furthermore, multi-qubit encoding allows multiple bits to be jointly represented in a single quantum state, improving noise tolerance and scalability compared to single-qubit approaches. These developments motivate the exploration of structured quantum transmission frameworks that combine frequency-domain processing and multi-qubit encoding to support high-fidelity image communication.

The symposium, which serves as a specialized session of the 4th International Conference on Applied Physics and Mathematical Modeling (CONF-APMM 2026), will focus on quantum and simulation.

Goal/Rationale

Although quantum communication has demonstrated promising theoretical advantages, its While prior work has shown the potential of quantum communication for image transmission, existing systems often rely on either time-domain representations or limited single-qubit encoding, restricting noise resilience and scalability. Separately, quantum OFDM-based approaches demonstrate that frequency-domain quantum processing can significantly improve robustness against fading and interference. However, a unified framework that systematically exploits frequency-domain processing together with scalable multi-qubit encoding for compressed image transmission remains underexplored. The goal of this work is to bridge this gap by developing and evaluating a frequency-domain multi-qubit quantum image transmission framework inspired by quantum OFDM principles. By integrating multi-qubit encoding with quantum Fourier transform–based processing, the proposed system aims to enhance noise robustness while maintaining controlled bandwidth usage and practical system complexity. The framework is designed to operate with standard image codecs such as JPEG and HEIF and is evaluated under realistic quantum noise conditions. Through extensive performance analysis, this study establishes clear design trade-offs between encoding complexity, frequency-domain processing, and reconstructed image quality, providing a principled foundation for scalable quantum image communication systems.

Scope

This work focuses on end-to-end quantum image transmission frameworks that leverage frequency-domain processing and multi-qubit encoding to improve robustness under noisy channel conditions. The scope is intentionally limited to quantum–classical hybrid systems, where compressed image bitstreams are mapped to quantum states and processed using quantum Fourier transform–based architectures, including both QFT-based multi-qubit transmission and quantum OFDM-inspired designs. Emphasis is placed on fair bandwidth-constrained comparisons across different qubit sizes, as well as on practical performance metrics relevant to image fidelity, including BER, PSNR, SSIM, and UQI. The study does not aim to replace classical codecs or implement full quantum hardware, but instead provides a system-level and algorithmic evaluation of how frequency-domain quantum processing and high-dimensional encoding jointly improve transmission quality. By unifying insights from quantum OFDM and frequency-domain multi-qubit communication, this work defines a clear experimental and methodological scope for advancing practical, noise-resilient quantum image transmission systems.