Internal:Hybrid Computing

Distributed Noisy Intermediate-Scale Quantum Computers (D-NISQ)

The D-NISQ model presented by [1] describes a hierarchical architecture of hybrid classical/quantum processors to break up large computations into smaller sub problems. Resource management of limited qubits and noisy quantum computation make domain decomposition a necessary method to practically use many quantum algorithms. The D-NISQ model has four layers. Consider the application to Quantum Hadamard Edge Detection qHED:

Decomposition Layer

The first layer is performed classically. Consider a 1024x1024 medical image. This comes out to 1,048,576 pixels requiring 20 (2^20) qubits plus 1 ancillary qubit for the QHED algorithm. Additionally, the amplitude encoding process expands exponentially with regards to qubit number. We can divide the image into separate sub images and solve either iteratively or in parallel (multithreading). Each sub image is now considered to be a sub input of the overall problem.

Figure 1 Example of 1024x1024 Medical image decomposed into 256x256 sub images.

References

[1] Acampora, Giovanni, et al. “D-NISQ: A Reference Model for Distributed Noisy Intermediate-Scale Quantum Computers.” Information Fusion, vol. 89, 2023, pp. 16–28., https://doi.org/10.1016/j.inffus.2022.08.003.