# A hybrid-qudit representation of digital RGB images

**Authors:** Sreetama Das, Filippo Caruso  
**arXiv:** [2207.12550](https://arxiv.org/abs/2207.12550)  
**Date:** 2022-07-25  
**Summary page:** https://www.summarizepaper.com/en/paper/2207.12550v1/

## Key points

- Quantum image processing is a rapidly evolving field in quantum information and technology.
- The authors propose a novel quantum representation of RGB images that outperforms existing representations in terms of resource utilization.
- The proposed method uses two entangled quantum registers consisting of a total of 7 qutrits to encode color channels and their intensities.
- The authors generalize existing encoding methods by using both qubits and qutrits to encode pixel positions in rectangular images, aligning well with current progress in NISQ devices incorporating higher-dimensional quantum systems than qubits.
- The authors describe the image encoding method using higher-order qubit-qutrit gates and demonstrate the decomposition of these gates into simpler elementary gates.
- They use Google Cirq's quantum simulator to verify image retrieval and show that the complexity of the image encoding process is linear in the number of pixels.
- They discuss image compression and basic RGB image processing protocols using their proposed representation.
- The paper includes references to other works related to multiple-valued logic, superconducting circuits, and computer architecture, indicating potential avenues for future research.
- The authors acknowledge contributions from various sources, including developers who contributed to Cirq on Github.

## Summary

Quantum image processing is a rapidly evolving field in quantum information and technology. In this paper, the authors propose a novel quantum representation of RGB images that outperforms existing representations in terms of resource utilization. The proposed method uses two entangled quantum registers consisting of a total of 7 qutrits to encode color channels and their intensities. Additionally, the authors generalize existing encoding methods by using both qubits and qutrits to encode pixel positions in rectangular images. This hybrid-qudit approach aligns well with current progress in NISQ devices incorporating higher-dimensional quantum systems than qubits. The authors describe the image encoding method using higher-order qubit-qutrit gates and demonstrate the decomposition of these gates into simpler elementary gates. They use Google Cirq's quantum simulator to verify image retrieval and show that the complexity of the image encoding process is linear in the number of pixels. Furthermore, they discuss image compression and basic RGB image processing protocols using their proposed representation. The paper also includes references to other works related to multiple-valued logic, superconducting circuits, and computer architecture, indicating potential avenues for future research. The authors acknowledge contributions from various sources, including developers who contributed to Cirq on Github. Overall, this paper presents an innovative approach to quantum image processing that leverages advances in hybrid-qudit systems while minimizing resource usage. It provides valuable insights into how such techniques can be applied to real-world problems while highlighting areas for further investigation.