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 …
Quantum computing for high-energy physics: State of the art and challenges
Quantum computers offer an intriguing path for a paradigmatic change of computing in the
natural sciences and beyond, with the potential for achieving a so-called quantum …
natural sciences and beyond, with the potential for achieving a so-called quantum …
Optimization applications as quantum performance benchmarks
Combinatorial optimization is anticipated to be one of the primary use cases for quantum
computation in the coming years. The Quantum Approximate Optimization Algorithm and …
computation in the coming years. The Quantum Approximate Optimization Algorithm and …
Building spatial symmetries into parameterized quantum circuits for faster training
Practical success of quantum learning models hinges on having a suitable structure for the
parameterized quantum circuit. Such structure is defined both by the types of gates …
parameterized quantum circuit. Such structure is defined both by the types of gates …
Towards adiabatic quantum computing using compressed quantum circuits
C Mc Keever, M Lubasch - PRX Quantum, 2024 - APS
We describe tensor network algorithms to optimize quantum circuits for adiabatic quantum
computing. To suppress diabatic transitions, we include counterdiabatic driving in the …
computing. To suppress diabatic transitions, we include counterdiabatic driving in the …
An efficient quantum proactive incremental learning algorithm
L Li, J Li, Y Song, S Qin, Q Wen, F Gao - Science China Physics …, 2025 - Springer
In scenarios where a large amount of data needs to be learned, incremental learning can
make full use of old knowledge, significantly reduce the computational cost of the overall …
make full use of old knowledge, significantly reduce the computational cost of the overall …
[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 …
NISQ computers: a path to quantum supremacy
M AbuGhanem, H Eleuch - IEEE Access, 2024 - ieeexplore.ieee.org
The quest for quantum advantage, wherein quantum computers surpass the computational
capabilities of classical computers executing state-of-the-art algorithms on well-defined …
capabilities of classical computers executing state-of-the-art algorithms on well-defined …
Scaling quantum approximate optimization on near-term hardware
The quantum approximate optimization algorithm (QAOA) is an approach for near-term
quantum computers to potentially demonstrate computational advantage in solving …
quantum computers to potentially demonstrate computational advantage in solving …
Design and execution of quantum circuits using tens of superconducting qubits and thousands of gates for dense Ising optimization problems
We develop a hardware-efficient ansatz for variational optimization, derived from existing
ansatzes in the literature, that parametrizes subsets of all interactions in the cost Hamiltonian …
ansatzes in the literature, that parametrizes subsets of all interactions in the cost Hamiltonian …