Virtual Annealing Machine | Quantum-Inspired Optimization

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⚡ Each annealing run costs {{ANNEALING_COST}} LOT tokens. Make sure you have sufficient balance.

Run Annealing Computation

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What is Simulated Annealing?

Simulated Annealing is a quantum-inspired optimization algorithm that finds the minimum energy configuration of a system. It's based on the Ising model where spins (±1) interact with each other. This technique is used in quantum computers and has applications in optimization, machine learning, and combinatorial problems.

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How it works:

Pay {{ANNEALING_COST}} LOT tokens to unlock one computation
Configure annealing parameters (spins, temperature, steps)
Run the computation in your browser
View results and energy minimization visualization

Annealing Parameters

Configure your optimization run

✅ Payment confirmed! Configure parameters and start annealing.

Number of Spins (N) Number of variables in the Ising model (2-100)

Initial Temperature (T₀) Starting temperature for annealing

Cooling Rate (α) Temperature reduction factor (0 < α < 1)

Number of Steps Total annealing iterations

Computation Progress

Initializing... Energy: --

⏳ Annealing computation is running in your browser. This may take a few moments...

Annealing Results

Optimization results and spin configuration

✅ Annealing completed successfully!

Final Energy

--

Steps Completed

--

Optimal Spin Configuration

↑ = +1 (spin up) | ↓ = -1 (spin down)

Energy Evolution

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Understanding the results:
The algorithm found the spin configuration with the lowest energy. Lower energy means a better solution. The chart shows how energy decreased over time as the temperature was lowered.

About Virtual Annealing

🔬 The Science

Simulated Annealing is inspired by the physical process of annealing in metallurgy. It uses the Metropolis-Hastings algorithm to explore the solution space, accepting worse solutions with decreasing probability as temperature lowers, helping avoid local minima.

⚛️ Ising Model

The energy function is: E = -Σ J_ij s_i s_j - Σ h_i s_i where s_i ∈ {+1, -1} are spins, J_ij are interaction strengths, and h_i are external fields.

💰 Blockchain Integration

This system uses LOT tokens (ERC-20) for payment. Each computation requires a blockchain transaction, ensuring fair usage and enabling a decentralized computational marketplace.

🚀 Applications

Annealing algorithms are used in: Optimization problems, Machine learning, Drug discovery, Financial modeling, Logistics planning, Circuit design, and many other fields requiring combinatorial optimization.

Resources

📖 Documentation 🔗 Learn About Simulated Annealing 🦊 Get MetaMask ⚡ Qubitchain Gateway