Results 101 to 110 of about 3,959 (191)

QAOA in Quantum Datacenters: Parallelization, Simulation, and Orchestration

2025 IEEE International Conference on Quantum Software (QSW)
Scaling quantum computing requires networked systems, leveraging HPC for distributed simulation now and quantum networks in the future. Quantum datacenters will be the primary access point for users, but current approaches demand extensive manual decisions and hardware expertise.
Amana Liaqat, Ahmed Darwish 0009, Adrian Roman, Stephen DiAdamo   +3 more
openaire   +2 more sources

Toward a linear-ramp QAOA protocol: evidence of a scaling advantage in solving some combinatorial optimization problems

npj Quantum Information
The quantum approximate optimization algorithm (QAOA) is a promising algorithm for solving combinatorial optimization problems (COPs), with performance governed by variational parameters $${\{{\gamma }_{i},{\beta }_{i}\}}_{i = 0}^{p-1}$$ { γ i , β i } i =
J. A. Montañez-Barrera, Kristel Michielsen   +1 more
doaj   +1 more source

Trainability Barriers in Low-Depth QAOA Landscapes

Proceedings of the 21st ACM International Conference on Computing Frontiers
The Quantum Alternating Operator Ansatz (QAOA) is a prominent variational quantum algorithm for solving combinatorial optimization problems. Its effectiveness depends on identifying input parameters that yield high-quality solutions. However, understanding the complexity of training QAOA remains an under-explored area.
Joel Rajakumar, John K. Golden, Andreas Bärtschi, Stephan J. Eidenbenz   +3 more
openaire   +2 more sources

Strategies for Noise-Resilient Quantum Approximate Optimization Algorithms: A Review and Classification of Error Mitigation

IEEE Access
The Quantum Approximate Optimization Algorithm (QAOA) is a leading candidate for solving combinatorial optimization problems on near-term quantum hardware.
Kimchhor Chiv, Leanghok Hour, Sanghyeon Lee, Tara Kit, Tae-Kyung Kim, Youngsun Han   +5 more
doaj   +1 more source

Clifford Accelerated Adaptive QAOA

Clifford Circuit Initializaton improves on initial guess of parameters on Parametric Quantum Circuits (PQCs) by leveraging efficient simulation of circuits made out of gates from the Clifford Group. The parameter space is pre-optimized by exploring the Hilbert space in a reduced ensemble of Clifford-expressible points (Clifford Points), providing ...
Lisart-Liebermann, Théo, Medina, Arcesio Castañeda   +1 more
openaire   +2 more sources

Advantages of multistage quantum walks over QAOA

CoRR
Methods to find the solution state for optimization problems encoded into Ising Hamiltonians are a very active area of current research. In this work we compare the quantum approximate optimization algorithm (QAOA) with multi-stage quantum walks (MSQW).
Lasse Gerblich, Tamanna Dasanjh, Horatio Q. X. Wong, David Ross, Leonardo Novo, Nicholas Chancellor, Viv Kendon   +6 more
openaire   +2 more sources

Performance of parity QAOA for the signed Max-Cut problem

New Journal of Physics
The practical implementation of quantum optimization algorithms on noisy intermediate-scale quantum devices requires accounting for their limited connectivity. As such, the Parity architecture was introduced to overcome this limitation by encoding binary
Anita Weidinger, Glen Bigan Mbeng, Michael Fellner, Davit Khachatryan, Wolfgang Lechner   +4 more
doaj   +1 more source

A Cyclic Layerwise QAOA Training

The quantum approximate optimization algorithm (QAOA) is a hybrid quantum-classical algorithm for solving combinatorial optimization problems. Multi-angle QAOA (MA-QAOA), which assigns independent parameters to each Hamiltonian operator term, achieves superior approximation performance even with fewer layers than standard QAOA.
Jang, Enhyeok, Chen, Zihan, Ha, Dongho, Choi, Seungwoo, Lee, Yongju, Kwon, Jaewon, Zhang, Eddy Z., Huang, Yipeng, Ro, Won Woo   +8 more
openaire   +2 more sources

Equivariant QAOA and the Duel of the Mixers

Constructing an optimal mixer for Quantum Approximate Optimization Algorithm (QAOA) Hamiltonian is crucial for enhancing the performance of QAOA in solving combinatorial optimization problems. We present a systematic methodology for constructing the QAOA tailored mixer Hamiltonian, ensuring alignment with the inherent symmetries of classical ...
Tsvelikhovskiy, Boris, Safro, Ilya, Alexeev, Yuri   +2 more
openaire   +2 more sources

Extrapolation method to optimize linear-ramp QAOA parameters: Evaluation of QAOA runtime scaling

14 pages, 15 ...
Dehn, Vanessa, Zaefferer, Martin, Hellstern, Gerhard, Reiter, Florentin, Wellens, Thomas   +4 more
openaire   +2 more sources