We solve a number of problems in quantum computing by applying genetic algorithms. We use the bitset class of C++ to represent any data type for genetic algorithms. Thus we have a flexible way to solve any optimization problem. The Bell-CHSH inequality and entanglement measures are studied ...
Quantum computers provide a valuable resource to solve computational problems. The maximization of the objective function of a computational problem is a crucial problem in gate-model quantum computers. The objective function estimation is a high-cost procedure that requires several rounds of quantum com...
Quantum annealing is a generic solver for optimization problems that uses fictitious quantum fluctuation. The most groundbreaking progress in the research field of quantum annealing is its hardware implementation, i.e., the so-called quantum annealer, using artificial spins. However, the connectivity be...
“We want to be sure that the quantum computer we are developing can help solve relevant problems early on. Therefore, we work in close collaboration with industrial companies,” says theoretical physicist Giulia Ferrini, one of the leaders of Chalmers University of Technology’s quantum computer ...
Quantum Inspired Swarm and Evolutionary Computing Algorithms for Optimization Problems Last update 8 June 2021 Guest Editors: Hari Mohan Pandey Mili Pant Abdesslem Layeb Ankit Chaudhary Actions for selected articles Select all/Deselect all Download PDFs...
論文概要 軌道のユニタリ変換による分子ハミルトニアンの不変性を利用し、Wavefunction Adapted Hamiltonian Through Orbital Rotation (WAHTOR)アルゴリズムによりVQEのdepthを大幅に減少させることができるが、ここではWAHTORの非断熱版を考案。 論文を理解する上で重要な
BAQIS Quafu Group, "Quafu-Qcover: Explore Combinatorial Optimization Problems on Cloud-based Quantum Computers", arXiv:2305.17979 (2023). Authors The first release of Qcover was developed by the quantum operating system team in Beijing Academy of Quantum Information Sciences. ...
Factoring numbers is one of those problems for which we still do not have an efficient classical algorithm, and much of cybersecurity, in particular encryption, depends on this assumed computational hardness. In 1994, Peter Shor gave a blueprint of a quantum algorithm that would factorize a ...
Accordingly, the possibility of quantum enhanced optimization has driven much interest in quantum technologies. Here we demonstrate the application of the Google Sycamore superconducting qubit quantum processor to combinatorial optimization problems with the quantum approximate optimization algorithm (QAOA). ...
Optimization is a problem that seems to be particularly suitable for current NISQ devices. In particular, the Variational Quantum Eigensolver (VQE)8,9,10seems to be the state-of-the-art algorithm for solving molecule Hamiltonians. Although it can solve optimization problems defined over discrete ...