ScholarGate
Avustaja

Vertaile menetelmiä

Tarkastele valitsemiasi menetelmiä rinnakkain; eroavat rivit korostetaan.

Born-Oppenheimer-approksimaatio×Variaatiokvanttilaskennan ratkaisija×
TieteenalaKvanttilaskentaKvanttilaskenta
MenetelmäperheMachine learningMachine learning
Syntyvuosi19272014
KehittäjäMax Born and Julius Robert OppenheimerAlberto Peruzzo
TyyppiFundamental approximationHybrid quantum-classical algorithm
AlkuperäislähdeBorn, M., Oppenheimer, J. R. (1927). Zur Quantentheorie der Moleküle. Annalen der Physik, 84, 457–484. DOI ↗Peruzzo, A., McClean, J., Shadbolt, P., et al. (2014). A variational eigenvalue solver on a photonic quantum processor. Nature Communications, 5, 4213. DOI ↗
RinnakkaisnimetBO approximation, clamped nucleiVQE, hybrid quantum-classical
Liittyvät34
TiivistelmäThe Born-Oppenheimer (BO) Approximation is a foundational assumption in molecular quantum mechanics that nuclei can be treated as fixed while solving for electrons, and vice versa. Introduced by Born and Oppenheimer in 1927, this separation reduces the complex many-body electronic-nuclear problem to a sequence of simpler problems, enabling nearly all molecular calculations.The Variational Quantum Eigensolver (VQE) is a hybrid quantum-classical algorithm designed to find the lowest eigenvalue (ground state energy) of a quantum Hamiltonian. Introduced by Peruzzo et al. in 2014, it exploits the variational principle to combine the power of quantum circuits with classical optimization to solve chemistry and materials science problems on near-term quantum devices.
ScholarGateAineisto
  1. v1
  2. 3 Lähteet
  3. PUBLISHED
  1. v1
  2. 3 Lähteet
  3. PUBLISHED

Siirry hakuun Lataa diat

ScholarGateVertaile menetelmiä: Born-Oppenheimer Approximation · Variational Quantum Eigensolver. Haettu 2026-06-17 osoitteesta https://scholargate.app/fi/compare