ruvnet--ruflo/v3/plugins/quantum-optimizer/tests/bridges.test.ts

/**
 * Quantum Optimizer Plugin - Bridges Tests
 *
 * Tests for quantum optimizer bridge initialization and lifecycle
 */

import { describe, it, expect, beforeEach, afterEach } from 'vitest';

// Note: The quantum-optimizer plugin uses a different bridge pattern
// These tests are structured for when a dedicated bridge is added

describe('QuantumOptimizerBridge (Mock)', () => {
  // Mock bridge implementation for testing
  class MockQuantumBridge {
    private _initialized = false;

    get initialized(): boolean {
      return this._initialized;
    }

    async initialize(): Promise<void> {
      this._initialized = true;
    }

    async dispose(): Promise<void> {
      this._initialized = false;
    }

    async solveQubo(
      problem: { variables: number; linear?: number[]; quadratic?: number[] },
      config: { numReads: number }
    ): Promise<{ energy: number; assignment: number[]; optimal: boolean }> {
      if (!this._initialized) {
        throw new Error('Bridge not initialized');
      }

      // Simple mock solving
      const assignment = new Array(problem.variables).fill(0);
      for (let i = 0; i < problem.variables; i++) {
        assignment[i] = Math.random() > 0.5 ? 1 : 0;
      }

      // Calculate mock energy
      let energy = 0;
      if (problem.linear) {
        for (let i = 0; i < problem.variables; i++) {
          energy += (problem.linear[i] ?? 0) * assignment[i];
        }
      }

      return {
        energy,
        assignment,
        optimal: config.numReads >= 1000,
      };
    }

    async runGrover(
      searchSpace: { size: number; oracle: string },
      _config: { method: string }
    ): Promise<{ solutions: number[]; queries: number }> {
      if (!this._initialized) {
        throw new Error('Bridge not initialized');
      }

      // Optimal number of queries for Grover
      const optimalQueries = Math.floor(Math.PI / 4 * Math.sqrt(searchSpace.size));

      // Mock solutions
      const solutions = [Math.floor(Math.random() * searchSpace.size)];

      return {
        solutions,
        queries: optimalQueries,
      };
    }

    async runQAOA(
      graph: { nodes: number; edges: [number, number][] },
      _circuit: { depth: number; shots: number }
    ): Promise<{ solution: number[]; approximationRatio: number }> {
      if (!this._initialized) {
        throw new Error('Bridge not initialized');
      }

      const solution = new Array(graph.nodes).fill(0);
      for (let i = 0; i < graph.nodes; i++) {
        solution[i] = Math.random() > 0.5 ? 1 : 0;
      }

      return {
        solution,
        approximationRatio: 0.7 + Math.random() * 0.2,
      };
    }
  }

  let bridge: MockQuantumBridge;

  beforeEach(() => {
    bridge = new MockQuantumBridge();
  });

  afterEach(async () => {
    await bridge.dispose();
  });

  describe('initialization', () => {
    it('should start uninitialized', () => {
      expect(bridge.initialized).toBe(false);
    });

    it('should initialize successfully', async () => {
      await bridge.initialize();
      expect(bridge.initialized).toBe(true);
    });

    it('should cleanup on dispose', async () => {
      await bridge.initialize();
      await bridge.dispose();
      expect(bridge.initialized).toBe(false);
    });
  });

  describe('solveQubo', () => {
    beforeEach(async () => {
      await bridge.initialize();
    });

    it('should solve QUBO problem', async () => {
      const problem = {
        variables: 5,
        linear: [1, -1, 2, -2, 1],
      };
      const config = { numReads: 100 };

      const result = await bridge.solveQubo(problem, config);

      expect(result.assignment).toHaveLength(5);
      expect(result.assignment.every(v => v === 0 || v === 1)).toBe(true);
      expect(typeof result.energy).toBe('number');
    });

    it('should indicate optimality for high read counts', async () => {
      const problem = { variables: 3 };
      const config = { numReads: 1000 };

      const result = await bridge.solveQubo(problem, config);

      expect(result.optimal).toBe(true);
    });

    it('should throw when not initialized', async () => {
      const newBridge = new MockQuantumBridge();
      await expect(
        newBridge.solveQubo({ variables: 3 }, { numReads: 10 })
      ).rejects.toThrow();
    });
  });

  describe('runGrover', () => {
    beforeEach(async () => {
      await bridge.initialize();
    });

    it('should run Grover search', async () => {
      const searchSpace = {
        size: 1000,
        oracle: 'x == target',
      };
      const config = { method: 'standard' };

      const result = await bridge.runGrover(searchSpace, config);

      expect(result.solutions.length).toBeGreaterThan(0);
      expect(result.queries).toBeGreaterThan(0);
      // Grover's algorithm achieves sqrt speedup
      expect(result.queries).toBeLessThan(searchSpace.size);
    });

    it('should use optimal number of queries', async () => {
      const searchSpace = {
        size: 10000,
        oracle: 'x == 42',
      };
      const config = { method: 'optimal' };

      const result = await bridge.runGrover(searchSpace, config);

      // Optimal queries is approximately pi/4 * sqrt(N)
      const expectedOptimal = Math.floor(Math.PI / 4 * Math.sqrt(10000));
      expect(result.queries).toBeCloseTo(expectedOptimal, -1);
    });
  });

  describe('runQAOA', () => {
    beforeEach(async () => {
      await bridge.initialize();
    });

    it('should run QAOA optimization', async () => {
      const graph = {
        nodes: 4,
        edges: [[0, 1], [1, 2], [2, 3], [3, 0]] as [number, number][],
      };
      const circuit = { depth: 2, shots: 1024 };

      const result = await bridge.runQAOA(graph, circuit);

      expect(result.solution).toHaveLength(4);
      expect(result.approximationRatio).toBeGreaterThan(0);
      expect(result.approximationRatio).toBeLessThanOrEqual(1);
    });

    it('should return valid binary solution', async () => {
      const graph = {
        nodes: 5,
        edges: [[0, 1], [1, 2], [2, 3], [3, 4]] as [number, number][],
      };
      const circuit = { depth: 3, shots: 2048 };

      const result = await bridge.runQAOA(graph, circuit);

      expect(result.solution.every(v => v === 0 || v === 1)).toBe(true);
    });
  });
});

describe('Simulated Annealing', () => {
  // Helper functions for testing annealing concepts

  function simulatedAnnealing(
    energy: (state: number[]) => number,
    initial: number[],
    temperature: { initial: number; final: number; type: 'exponential' | 'linear' },
    iterations: number
  ): { state: number[]; energy: number } {
    let current = [...initial];
    let currentEnergy = energy(current);
    let best = [...current];
    let bestEnergy = currentEnergy;

    for (let i = 0; i < iterations; i++) {
      // Calculate temperature
      const t = temperature.type === 'exponential'
        ? temperature.initial * Math.pow(temperature.final / temperature.initial, i / iterations)
        : temperature.initial - (temperature.initial - temperature.final) * (i / iterations);

      // Generate neighbor by flipping random bit
      const neighbor = [...current];
      const flipIdx = Math.floor(Math.random() * neighbor.length);
      neighbor[flipIdx] = 1 - neighbor[flipIdx];

      const neighborEnergy = energy(neighbor);
      const delta = neighborEnergy - currentEnergy;

      // Accept if better or with probability based on temperature
      if (delta < 0 || Math.random() < Math.exp(-delta / t)) {
        current = neighbor;
        currentEnergy = neighborEnergy;

        if (currentEnergy < bestEnergy) {
          best = [...current];
          bestEnergy = currentEnergy;
        }
      }
    }

    return { state: best, energy: bestEnergy };
  }

  it('should minimize simple energy function', () => {
    // Energy function: sum of bits (minimum at all zeros)
    const energy = (state: number[]) => state.reduce((s, v) => s + v, 0);
    const initial = [1, 1, 1, 1, 1];

    const result = simulatedAnnealing(
      energy,
      initial,
      { initial: 10, final: 0.01, type: 'exponential' },
      1000
    );

    expect(result.energy).toBeLessThanOrEqual(2);  // Should find low energy state
  });

  it('should find optimal solution with enough iterations', () => {
    // Energy function: count of 1s (optimal is all zeros)
    const energy = (state: number[]) => state.filter(v => v === 1).length;
    const initial = [1, 1, 1, 1];

    const result = simulatedAnnealing(
      energy,
      initial,
      { initial: 5, final: 0.001, type: 'exponential' },
      2000
    );

    expect(result.energy).toBe(0);  // Should find global minimum
    expect(result.state.every(v => v === 0)).toBe(true);
  });

  it('should handle linear temperature schedule', () => {
    const energy = (state: number[]) => state.reduce((s, v) => s + v, 0);
    const initial = [1, 1, 1];

    const result = simulatedAnnealing(
      energy,
      initial,
      { initial: 5, final: 0.1, type: 'linear' },
      500
    );

    expect(result.energy).toBeLessThan(3);
  });
});

describe('DAG Analysis', () => {
  // Helper for topological sort (used in scheduling)

  function topologicalSort(
    nodes: string[],
    edges: { source: string; target: string }[]
  ): string[] | null {
    const inDegree = new Map<string, number>();
    const adjacency = new Map<string, string[]>();

    // Initialize
    for (const node of nodes) {
      inDegree.set(node, 0);
      adjacency.set(node, []);
    }

    // Build graph
    for (const edge of edges) {
      adjacency.get(edge.source)?.push(edge.target);
      inDegree.set(edge.target, (inDegree.get(edge.target) ?? 0) + 1);
    }

    // Kahn's algorithm
    const queue: string[] = [];
    for (const [node, degree] of inDegree) {
      if (degree === 0) queue.push(node);
    }

    const result: string[] = [];
    while (queue.length > 0) {
      const node = queue.shift()!;
      result.push(node);

      for (const neighbor of adjacency.get(node) ?? []) {
        const newDegree = (inDegree.get(neighbor) ?? 0) - 1;
        inDegree.set(neighbor, newDegree);
        if (newDegree === 0) queue.push(neighbor);
      }
    }

    return result.length === nodes.length ? result : null;
  }

  it('should topologically sort DAG', () => {
    const nodes = ['a', 'b', 'c', 'd'];
    const edges = [
      { source: 'a', target: 'b' },
      { source: 'a', target: 'c' },
      { source: 'b', target: 'd' },
      { source: 'c', target: 'd' },
    ];

    const sorted = topologicalSort(nodes, edges);

    expect(sorted).not.toBeNull();
    expect(sorted).toHaveLength(4);
    expect(sorted![0]).toBe('a');  // a has no dependencies
    expect(sorted![3]).toBe('d');  // d depends on b and c
  });

  it('should return null for cyclic graph', () => {
    const nodes = ['a', 'b', 'c'];
    const edges = [
      { source: 'a', target: 'b' },
      { source: 'b', target: 'c' },
      { source: 'c', target: 'a' },  // Cycle!
    ];

    const sorted = topologicalSort(nodes, edges);

    expect(sorted).toBeNull();
  });

  it('should handle empty graph', () => {
    const sorted = topologicalSort([], []);
    expect(sorted).toEqual([]);
  });

  it('should handle disconnected nodes', () => {
    const nodes = ['a', 'b', 'c'];
    const edges: { source: string; target: string }[] = [];

    const sorted = topologicalSort(nodes, edges);

    expect(sorted).not.toBeNull();
    expect(sorted).toHaveLength(3);
  });
});