qcr:2604.64920.1

Distributed Implementation of Variational Quantum Eigensolver to Solve QUBO Problems

We present a distributed algorithm and implementation of the variational quantum eigensolver (VQE), termed distributed VQE (DVQE). DVQE, provided as an open-source Python package, enables the execution of parameterized quantum circuits across multiple logical quantum processing units (QPUs) in a distributed fashion. This approach addresses key hardware limitations of near-term quantum devices, including restricted qubit counts and limited circuit depth. Distributed ansatz circuits are constructed to preserve the quantum state fidelity of their monolithic counterparts, allowing consistent energy estimation while distributing the computational load. To improve the convergence and robustness of the optimization loop for identifying the variational parameters of the DVQE ansatz circuit, we use the ADAM optimizer in combination with metaheuristic initialization strategies, which outperform random initialization across various test cases. The complete DVQE pipeline is implemented in a modular Python package that accepts QUBO problems as input and supports monolithic and distributed execution modes. The framework leverages Qiskit to construct and simulate distributed circuits, and includes an internal greedy algorithm for automatic qubit allocation across multiple QPUs. Simulation results on QUBO benchmarks confirm the correctness of the approach, paving the way for real QPU deployment and further exploration of distributed quantum optimization. \textbf{The simulator is publicly available on \href{https://github.com/LSU-RAISE-LAB/DVQE.git}{GitHub} under a package named raiselab, with a collection of tutorial examples.}

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LSU-RAISE-LAB/DVQE

README.md

Raiselab: Resilient Advanced Infrastructure & Systems Engineering Lab

A modular hybrid Variational Quantum Eigensolver (VQE) framework for solving binary optimization problems using both monolithic and distributed quantum architectures.

🔬 Overview

Raiselab offers DVQE that is a general-purpose Variational Quantum Eigensolver built with extensibility, hybridization, and modularity in mind. It allows researchers to solve any QUBO (Quadratic Unconstrained Binary Optimization) problem using:

Monolithic quantum circuits (single QPU)
Distributed quantum circuits (multi-QPU, using entangled teleportation logic via DISKIT

This package supports different quantum initialization methods and advanced circuit distribution schemes.

🌟 Features

✅ Monolithic & Distributed Execution: Easily switch between single-QPU and multi-QPU modes.
🧠 Hybrid Optimizers: Combines gradient-based Adam optimizer with swarm-inspired metaheuristics initialization for ansatz parameters such as Black Hole, GWO, and ABC.
🔁 TeleGate Execution: Integrates DISKIT for simulating entangled circuit distribution across QPUs.
🛠 Flexible Ansatz Construction: Layered, parameterized quantum circuits with adjustable depth.
🔄 Circuit Remapping: Automatically distributes circuits based on QPU partitioning configuration.
🔬 QUBO to Pauli Hamiltonian: Translates binary quadratic problems into quantum Hamiltonians.
📉 Real-Time Convergence Tracking: Monitor parameter updates and early-stop based on tolerance.
🧪 Top-k Bitstring Evaluation: Selects final solution by comparing energy from most probable outcomes.
📈 Visualization Support: Render final circuits via Qiskit tools for debugging and analysis.
🧩 Modular Design: Each function is clearly grouped (initialization, circuit build, energy evaluation, decoding).

📚 Citation

If you use this framework or its solvers in your research, please cite:

M. Hasanzadeh and A. Kargarian, "Distributed Implementation of Variational Quantum Eigensolver to Solve QUBO Problems," https://arxiv.org/abs/2508.17471

👤 Author

Milad Hasanzadeh
Department of Electrical and Computer Engineering
Louisiana State University
📧 e.mhasanzadeh1377@yahoo.com

📅 Release Date: August 2025
📄 License: Academic and Research Use Only

📦 Installation

To install the package directly from GitHub:

pip install git+https://github.com/LSU-RAISE-LAB/DVQE.git

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Publication

doi:10.48550/arxiv.2508.17471

Distributed Implementation of Variational Quantum Eigensolver to Solve QUBO Problems

Milad Hasanzadeh, Amin Kargarian

Versions

v1 Latest

Apr 14, 2026

qcr:2604.64920.1

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