Sensor Positioning

Aqarios | PushQuantum

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PushQuantum

Sensor Positioning

If this is your first competition on Aqora, we highly recommend you follow the H2 Groundstate Energy Tutorial to get familar with the platform and the CLI.

Downloading the template

To download the template for this use case, you can run the following command in the terminal

aqora template aqarios-pushquantum-24

This will download the template into a folder called aqarios-pushquantum-24.

You can then open the folder in Visual Studio Code by running the following command in the terminal

aqora lab -p aqarios-pushquantum-24

This should open the folder in Visual Studio Code. If you receive a prompt, you can click on "Yes, I trust the authors".

Getting Started

You can find a template notebook in submission/solution.ipynb. Fill in your solution. You can run the notebook locally to test your solution by running the following in the terminal

aqora test

And when you are ready to submit run

aqora upload

Luna

Getting Started with Luna

This section provides guidance on using the Luna platform to tackle the quantum computing challenge. Below are essential resources and instructions to navigate Luna’s features effectively. Review all provided links and documentation for a seamless experience.

Overview of Luna

Luna is Aqarios’ quantum optimization platform, designed to simplify access to advanced quantum and hybrid quantum-classical algorithms. It provides tools for custom optimization problems, such as this challenge.

For detailed information, consult the Luna Documentation, which covers:

Service functionality.
User guides.
Supported algorithms.

Getting Started with Luna

Steps to set up Luna and begin solving the challenge:

Retrieve your API token from the API Token Retrieval Page.
Follow the setup steps in the Get Started section of the Luna Documentation.
Use the Luna Python SDK or REST API to integrate the platform into your workflow. For installation and basic usage, consult the setup and examples subsections.

Key Subsections

Authentication: Learn how to authenticate requests using your API token.
Environment Setup: Instructions on setting up Luna locally or on a cloud-based Jupyter notebook.

LunaSolve: Custom Optimization

For this challenge, leverage LunaSolve, specifically its Custom Optimization capabilities.

Refer to Preparing Your QUBO for structuring the Quadratic Unconstrained Binary Optimization (QUBO) problem.
Ensure the optimization problem aligns with the challenge’s requirements and is formatted correctly for LunaSolve.

Detailed Sections

Problem Encoding: Guidelines for encoding optimization problems as QUBOs.
Solution Process: How Luna processes QUBO formulations using quantum and hybrid algorithms.

User Guides: Optimization Formats

Luna supports multiple input formats for optimization tasks. Refer to the Optimization Formats section to learn about:

Supported formats.
Conversion guidelines for compatibility with Luna.

Example Input Formats

JSON-based QUBO representation.
Matrix-based representations for advanced use cases.

Algorithms: Overview

Participants will solve the challenge using Luna’s advanced algorithms. For a comprehensive understanding, refer to the Algorithms - Overview section. Key algorithms include:

Quantum Annealing: Suitable for combinatorial optimization tasks.
Hybrid Solvers: Combine classical and quantum approaches for enhanced scalability.

Each algorithm description includes:

Applicable use cases.
Performance benchmarks.
Usage instructions via the API.

Additional Resources

Luna Documentation Home
Retrieve API Token
Challenge Overview: Familiarize yourself with the challenge’s goals and constraints under the "Overview" tab.

For questions or support, use the hackathon’s communication channels or email us directly.