Optimization Suite
QAOA for combinatorial optimization, VQE for molecular simulation, hybrid solvers, and comprehensive benchmarking against classical alternatives.
The Optimization Suite tackles NP-hard combinatorial problems using Quantum Approximate Optimization Algorithm (QAOA), Variational Quantum Eigensolver (VQE) for chemistry and materials simulation, and hybrid quantum-classical solvers. Every quantum solution is benchmarked against best-known classical algorithms with automatic routing to whichever performs better.
Quantum optimization algorithm development and benchmarking.
What's Included
QAOA Implementation
Quantum Approximate Optimization Algorithm for Max-Cut, graph coloring, scheduling, and routing problems with tunable depth.
VQE Solver
Variational Quantum Eigensolver for ground-state energy estimation in molecular simulation and materials science.
Hybrid Solvers
Combined quantum-classical optimization with warm-starting, parameter sharing, and intelligent workload splitting.
Quantum Annealing Bridge
Abstract interface to D-Wave quantum annealing for Ising model and QUBO formulations.
Benchmarking Framework
Automated comparison of quantum solutions against classical solvers (Gurobi, CPLEX, simulated annealing) with statistical significance testing.
Specs & Parameters
Use Cases
Logistics Optimization
Vehicle routing, warehouse layout, and supply chain scheduling using QAOA with proven improvement over classical heuristics.
Portfolio Optimization
Markowitz portfolio optimization with quantum-enhanced risk-return tradeoff analysis for financial services.
Materials Discovery
VQE-based ground-state energy calculations for new materials and catalyst design.
Ready for Optimization Suite?
Typical engagement: 4-8 weeks. From assessment to deployment, Qubit handles the full pipeline.