Overview

The Ocean Plastic Problem

Ocean plastic pollution is one of the most pressing environmental challenges of our time. According to research, more than 8 million tons of plastic waste enters our oceans each year, threatening marine ecosystems, wildlife, and human health.

Current cleanup efforts face significant challenges:

  • The vast scale of the oceans

  • Dynamic movement of plastic due to currents and winds

  • Resource constraints for cleanup operations

  • Logistical complexity of deployment and collection

Quantum Optimization Approach

mohituQ leverages quantum computing and quantum-inspired algorithms to address these challenges by:

  1. Modeling the Problem: Formulating ocean plastic cleanup as a complex optimization problem with multiple objectives

  2. Quantum Algorithms: Using advanced quantum algorithms like DQI and QAOA to find optimal or near-optimal solutions

  3. Simulation: Creating realistic models of ocean currents and plastic distribution

  4. Validation: Comparing quantum solutions with classical approaches to quantify potential advantages

System Architecture

The mohituQ system consists of several key components:

+-------------------+     +----------------------+     +------------------+
| Data Acquisition  |---->| Optimization Engine  |---->| Visualization    |
| & Processing      |     | (Quantum/Classical)  |     | & Analysis       |
+-------------------+     +----------------------+     +------------------+
        |                           |                          |
        v                           v                          v
+-------------------+     +----------------------+     +------------------+
| Ocean Current     |     | Solution Evaluation  |     | Deployment       |
| Modeling          |     | & Refinement         |     | Planning         |
+-------------------+     +----------------------+     +------------------+

Key Research Questions

mohituQ aims to address several key research questions:

  1. How can we formulate ocean plastic cleanup as a quantum optimization problem?

  2. What quantum algorithms are most effective for different aspects of this problem?

  3. How does the performance of quantum solutions compare to classical approaches?

  4. What are the resource requirements for practical implementation?

  5. How can we integrate real-time data and adaptive strategies?

Next Steps

Continue to the Installation page to learn how to set up mohituQ on your system.