# Distributed Quantum Computing and Network Control for Accelerated VQE

arXiv: https://arxiv.org/abs/2101.02504 · HTML: https://mlsanity.com/paper/2101.02504/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 7 Jan 2021.

## Built on by (most cited first, 5 of 5)

- [Adversarial Robustness of Partitioned Quantum Classifiers](https://mlsanity.com/paper/2502.20403/) (2025)
- [Shuffle-QUDIO: accelerate distributed VQE with trainability enhancement and measurement reduction](https://mlsanity.com/paper/2209.12454/) (2022)
- [Multi-GPU-Enabled Hybrid Quantum-Classical Workflow in Quantum-HPC Middleware: Applications in Quantum Simulations](https://mlsanity.com/paper/2403.05828/) (2024)
- [Adversarial Effects on Expressibility and Trainability in Distributed Variational Quantum Algorithms](https://mlsanity.com/paper/2605.03629/) (2026)
- [Distributed Quantum Learning over Near-term Devices: Convergence Analysis and Security Design](https://mlsanity.com/paper/2606.20606/) (2026)

## Abstract (arXiv)

Interconnecting small quantum computers will be essential in the future for creating large scale, robust quantum computers. Methods for distributing monolithic quantum algorithms efficiently are thus needed. In this work we consider an approach for distributing the accelerated variational quantum eigensolver (AVQE) algorithm over arbitrary sized - in terms of number of qubits - distributed quantum computers. We consider approaches for distributing qubit assignments of the Ansatz states required to estimate the expectation value of Hamiltonian operators in quantum chemistry in a parallelized computation and provide a systematic approach to generate distributed quantum circuits for distributed quantum computing. Moreover, we propose an architecture for a distributed quantum control system in the settings of centralized and decentralized network control.