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Travelling Salesman Problem Quantum Benchmark

QAOA / Variational Quantum Eigensolver (VQE) · Optimization · 30 qubits · Qiskit, PennyLane, D-Wave Ocean

Benchmark of quantum approaches to the Travelling Salesman Problem, a canonical NP-hard combinatorial optimization task. Instances are encoded as QUBO/Ising Hamiltonians and solved using QAOA or VQE on gate-based hardware, or via quantum annealing. Current NISQ-era implementations handle instances of up to roughly six cities, making TSP a demanding test of quantum optimizer quality.

TSPcombinatorial-optimizationQAOAVQEQUBO
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3 credible sources · last verified 6 months ago

Benchmark of quantum approaches to the Travelling Salesman Problem, a canonical NP-hard combinatorial optimization task. Instances are encoded as QUBO/Ising Hamiltonians and solved using QAOA or VQE on gate-based hardware, or via quantum annealing. Current NISQ-era implementations handle instances of up to roughly six cities, making TSP a demanding test of quantum optimizer quality.

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Key Metrics
Max cities (NISQ)
~6
Encoding
QUBO/Ising Hamiltonian
Qubits used
30
Why It Matters

Exposes the harsh scaling reality of quantum optimization: the most famous NP-hard problem remains limited to toy sizes on current quantum hardware.

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Hardware

Various (IBM Quantum, D-Wave, simulators)

Framework

Qiskit, PennyLane, D-Wave Ocean