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A review on quantum approximate optimization algorithm and its variants
Abstract The Quantum Approximate Optimization Algorithm (QAOA) is a highly promising
variational quantum algorithm that aims to solve combinatorial optimization problems that …
variational quantum algorithm that aims to solve combinatorial optimization problems that …
Challenges and opportunities in quantum optimization
Quantum computers have demonstrable ability to solve problems at a scale beyond brute-
force classical simulation. Interest in quantum algorithms has developed in many areas …
force classical simulation. Interest in quantum algorithms has developed in many areas …
Evidence of scaling advantage for the quantum approximate optimization algorithm on a classically intractable problem
The quantum approximate optimization algorithm (QAOA) is a leading candidate algorithm
for solving optimization problems on quantum computers. However, the potential of QAOA to …
for solving optimization problems on quantum computers. However, the potential of QAOA to …
Quantum optimization: Potential, challenges, and the path forward
Recent advances in quantum computers are demonstrating the ability to solve problems at a
scale beyond brute force classical simulation. As such, a widespread interest in quantum …
scale beyond brute force classical simulation. As such, a widespread interest in quantum …
Avoiding barren plateaus using classical shadows
Variational quantum algorithms are promising algorithms for achieving quantum advantage
on near-term devices. The quantum hardware is used to implement a variational wave …
on near-term devices. The quantum hardware is used to implement a variational wave …
Avoiding barren plateaus via transferability of smooth solutions in a Hamiltonian variational ansatz
A large ongoing research effort focuses on variational quantum algorithms (VQAs),
representing leading candidates to achieve computational speed-ups on current quantum …
representing leading candidates to achieve computational speed-ups on current quantum …
Large-scale quantum approximate optimization on nonplanar graphs with machine learning noise mitigation
Quantum computers are increasing in size and quality but are still very noisy. Error
mitigation extends the size of the quantum circuits that noisy devices can meaningfully …
mitigation extends the size of the quantum circuits that noisy devices can meaningfully …
Scaling of the quantum approximate optimization algorithm on superconducting qubit based hardware
Quantum computers may provide good solutions to combinatorial optimization problems by
leveraging the Quantum Approximate Optimization Algorithm (QAOA). The QAOA is often …
leveraging the Quantum Approximate Optimization Algorithm (QAOA). The QAOA is often …
Parameter concentrations in quantum approximate optimization
The quantum approximate optimization algorithm (QAOA) has become a cornerstone of
contemporary quantum applications development. In QAOA, a quantum circuit is trained—by …
contemporary quantum applications development. In QAOA, a quantum circuit is trained—by …
[HTML][HTML] Short-depth QAOA circuits and quantum annealing on higher-order ising models
We present a direct comparison between QAOA (Quantum Alternating Operator Ansatz), and
QA (Quantum Annealing) on 127 qubit problem instances. QAOA with p= 1, 2 rounds is …
QA (Quantum Annealing) on 127 qubit problem instances. QAOA with p= 1, 2 rounds is …