ruvector/crates/ruqu-algorithms/README.md
rUv b67f3c9962 feat: add READMEs and publish ruqu packages v2.0.3
Crates.io (v2.0.3):
- ruqu-core: High-performance quantum circuit simulator
- ruqu-algorithms: VQE, Grover, QAOA, Surface Code
- ruqu-exotic: Quantum-classical hybrid algorithms
- ruqu-wasm: WebAssembly bindings

npm (@ruvector/ruqu-wasm v2.0.3):
- Browser-native quantum simulation
- 25-qubit support with 105KB WASM bundle
- TypeScript definitions included

SEO-optimized READMEs with:
- Performance benchmarks
- API documentation
- Code examples
- ADR links

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-02-08 17:13:57 +00:00

3.9 KiB
Raw Permalink Blame History

ruqu-algorithms

Crates.io Documentation License

Production-ready quantum algorithms in Rust — VQE for chemistry, Grover's search, QAOA optimization, and Surface Code error correction.

Algorithms

Algorithm Use Case Speedup
VQE Molecular ground states, chemistry Exponential for certain problems
Grover Unstructured database search O(√N) vs O(N)
QAOA Combinatorial optimization (MaxCut) Approximate quantum advantage
Surface Code Quantum error correction Fault-tolerant computation

Installation

cargo add ruqu-algorithms

Variational Quantum Eigensolver (VQE)

Find ground state energies for molecular Hamiltonians:

use ruqu_algorithms::vqe::{VQE, Hamiltonian, Ansatz};

// H2 molecule Hamiltonian (simplified)
let hamiltonian = Hamiltonian::from_pauli_strings(&[
    ("ZZ", 0.5),
    ("XX", 0.3),
    ("YY", 0.3),
    ("II", -1.0),
]);

// UCCSD ansatz for chemistry
let ansatz = Ansatz::uccsd(n_qubits: 4, n_electrons: 2);

let vqe = VQE::new(hamiltonian, ansatz);
let result = vqe.optimize()?;

println!("Ground state energy: {:.6} Ha", result.energy);

Quadratic speedup for unstructured search:

use ruqu_algorithms::grover::{Grover, Oracle};

// Search for |101⟩ in 3-qubit space
let oracle = Oracle::from_target(0b101, 3);
let grover = Grover::new(oracle);

let result = grover.search()?;
println!("Found: {:03b}", result);  // 101

Optimal iterations: π/4 × √N for N items.

QAOA MaxCut

Approximate solutions to NP-hard graph problems:

use ruqu_algorithms::qaoa::{QAOA, Graph};

// Define graph edges
let graph = Graph::from_edges(&[
    (0, 1), (1, 2), (2, 3), (3, 0), (0, 2)
]);

let qaoa = QAOA::new(graph, depth: 3);
let result = qaoa.optimize()?;

println!("MaxCut partition: {:?}", result.partition);
println!("Cut value: {}", result.cut_value);

Surface Code Error Correction

Topological quantum error correction for fault-tolerant computing:

use ruqu_algorithms::surface_code::{SurfaceCode, Decoder};

let code = SurfaceCode::new(distance: 3);  // 3x3 lattice
let decoder = Decoder::mwpm();              // Minimum-weight perfect matching

// Encode logical qubit
let logical_state = code.encode_logical_zero();

// Simulate noise and correct
let noisy = code.apply_noise(logical_state, error_rate: 0.01);
let syndromes = code.measure_syndromes(&noisy);
let corrected = decoder.correct(&noisy, &syndromes)?;

Benchmarks

Algorithm Qubits Time Hardware
VQE (H2) 4 50ms/iteration M2
Grover (N=1024) 10 15ms M2
QAOA (depth=3) 8 100ms M2
Surface Code (d=3) 17 5ms/round M2

Documentation

License

MIT OR Apache-2.0