Quantum Workflow 🚀

Welcome to Quantum Workflow, a project designed to enhance workflow scheduling using quantum computing techniques. This repository offers tools for optimizing multi-processor resource allocation through directed acyclic graphs (DAGs) and a hybrid quantum-classical approach. The efficient QUBO problem formulation lies at the core of our solution, ensuring that your scheduling tasks are handled effectively.

Table of Contents

1. Introduction
2. Features
3. Getting Started
4. Installation
5. Usage
6. Example
7. Contributing
8. License
9. Contact
10. Releases

Introduction

In today's fast-paced world, efficient task scheduling is crucial. Traditional methods often struggle to keep up with complex workflows, especially when multiple processors are involved. Quantum Workflow leverages the power of quantum algorithms to provide an advanced solution for scheduling tasks. By using a hybrid approach, we combine classical and quantum computing methods to tackle the challenges of workflow optimization.

Features

• Hybrid Quantum-Classical Approach: Seamlessly integrates classical algorithms with quantum techniques.
• Efficient Resource Allocation: Optimizes multi-processor use through smart scheduling.
• Visual Tools: Advanced visualization tools help you understand and manage workflows.
• QUBO Problem Formulation: Ensures efficient and effective solutions to scheduling problems.
• Open Source: Community-driven project with contributions welcome.

Getting Started

To get started with Quantum Workflow, follow these steps to set up your environment and run the project.

Prerequisites

Make sure you have the following installed:

• Python 3.7 or higher
• Qiskit
• Required libraries (see Installation section)

Installation

1. Clone the repository:

   git clone https://github.com/meet-c-viradiya/quantum-workflow.git
   cd quantum-workflow

2. Install the required packages:

   pip install -r requirements.txt

Usage

Once installed, you can start using Quantum Workflow for your scheduling needs. The main script is located in the src directory.

Run the main script:

python src/main.py

Example

To see how the Quantum Workflow can be applied, check the examples provided in the examples directory. Here’s a simple way to visualize a task scheduling scenario:

from quantum_workflow import Scheduler

scheduler = Scheduler()
scheduler.add_task("Task 1", duration=2)
scheduler.add_task("Task 2", duration=3)
scheduler.schedule()

This code snippet demonstrates how to create a scheduler, add tasks, and schedule them efficiently.

Contributing

We welcome contributions from everyone. To contribute:

1. Fork the repository.
2. Create a new branch (git checkout -b feature-branch).
3. Make your changes and commit them (git commit -m 'Add new feature').
4. Push to the branch (git push origin feature-branch).
5. Create a pull request.

Your contributions help improve the project and make it more useful for everyone.

License

This project is licensed under the MIT License. See the LICENSE file for details.

Contact

For questions or feedback, feel free to reach out:

• Email: [email protected]
• GitHub: meet-c-viradiya

Releases

To download the latest release, visit the Releases section. Download the appropriate files and execute them to get started with the latest features and improvements.

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Thank you for checking out Quantum Workflow! We hope you find it useful for your quantum computing and scheduling needs. If you have any questions or suggestions, please reach out through the contact information provided. Happy coding!