npm install @claude-flow/plugin-quantum-optimizer

npx claude-flow plugins install --name @claude-flow/plugin-quantum-optimizer

import { QuantumOptimizerPlugin } from '@claude-flow/plugin-quantum-optimizer';

// Initialize the plugin
const plugin = new QuantumOptimizerPlugin();
await plugin.initialize();

// Solve a scheduling optimization problem
const schedule = await plugin.scheduleOptimize({
  tasks: [
    { id: 'build', duration: 10, dependencies: [], resources: ['cpu'], deadline: 30 },
    { id: 'test', duration: 5, dependencies: ['build'], resources: ['cpu'], deadline: 40 },
    { id: 'deploy', duration: 3, dependencies: ['test'], resources: ['network'], deadline: 50 }
  ],
  resources: [
    { id: 'cpu', capacity: 4, cost: 1.0 },
    { id: 'network', capacity: 2, cost: 0.5 }
  ],
  objective: 'makespan'
});

console.log('Optimal schedule:', schedule);

const result = await mcp.call('quantum/annealing-solve', {
  problem: {
    type: 'qubo',  // Quadratic Unconstrained Binary Optimization
    variables: 100,
    constraints: [...],
    objective: { 'x1': -1, 'x2': -1, 'x1_x2': 2 }
  },
  parameters: {
    numReads: 1000,
    annealingTime: 20,
    chainStrength: 1.0,
    temperature: {
      initial: 100,
      final: 0.01
    }
  },
  embedding: 'auto'
});

const result = await mcp.call('quantum/qaoa-optimize', {
  problem: {
    type: 'max_cut',
    graph: {
      nodes: 20,
      edges: [[0, 1], [1, 2], [2, 3], [0, 3], ...]
    },
    weights: { '0_1': 1.0, '1_2': 0.5, ... }
  },
  circuit: {
    depth: 3,  // QAOA circuit depth (p)
    optimizer: 'cobyla',
    initialParams: 'heuristic'
  },
  shots: 1024
});

const result = await mcp.call('quantum/grover-search', {
  searchSpace: {
    size: 1000000,  // 1M elements
    oracle: 'x.value > 100 && x.valid === true',
    structure: 'database'
  },
  targets: 1,
  iterations: 'optimal',
  amplification: {
    method: 'standard',
    boostFactor: 1.5
  }
});

const result = await mcp.call('quantum/dependency-resolve', {
  packages: [
    { name: 'react', version: '18.2.0', dependencies: { 'react-dom': '^18.0.0' }, conflicts: [] },
    { name: 'webpack', version: '5.88.0', dependencies: { 'loader-utils': '^3.0.0' }, conflicts: [] },
    // ... more packages
  ],
  constraints: {
    minimize: 'versions',  // Minimize total version count
    lockfile: existingLockfile,
    peer: true
  },
  solver: 'hybrid'
});

const result = await mcp.call('quantum/schedule-optimize', {
  tasks: [
    { id: 'task-1', duration: 10, dependencies: [], resources: ['gpu'], deadline: 100 },
    { id: 'task-2', duration: 5, dependencies: ['task-1'], resources: ['cpu'], deadline: 120 },
    { id: 'task-3', duration: 8, dependencies: [], resources: ['cpu', 'memory'], deadline: 80 }
  ],
  resources: [
    { id: 'cpu', capacity: 8, cost: 1.0 },
    { id: 'gpu', capacity: 2, cost: 5.0 },
    { id: 'memory', capacity: 64, cost: 0.1 }
  ],
  objective: 'weighted'  // Balance makespan and cost
});

interface QuantumOptimizerConfig {
  // Maximum problem variables (default: 10000)
  maxVariables: number;

  // Maximum iterations (default: 1000000)
  maxIterations: number;

  // Memory limit in bytes (default: 4GB)
  maxMemoryBytes: number;

  // CPU time limit in ms (default: 600000 = 10 min)
  maxCpuTimeMs: number;

  // QAOA circuit depth limit (default: 20)
  maxCircuitDepth: number;

  // Simulated qubit limit (default: 50)
  maxQubits: number;

  // Progress monitoring
  progressCheckIntervalMs: number;
  minProgressThreshold: number;
}