Born–Huang expansion
E4701
The Born–Huang expansion is a quantum mechanical method that systematically improves upon the Born–Oppenheimer approximation by including couplings between electronic and nuclear motions in molecular systems.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Born–Huang expansion canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T65239 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Born–Huang expansion Context triple: [Born–Oppenheimer approximation, hasRefinement, Born–Huang expansion]
-
A.
Born–Oppenheimer approximation
The Born–Oppenheimer approximation is a fundamental method in molecular quantum mechanics that simplifies calculations by treating nuclear motion as much slower than electronic motion, allowing their behaviors to be separated.
-
B.
Feynman–Kac formula
The Feynman–Kac formula is a fundamental result connecting solutions of certain partial differential equations with expectations over stochastic processes, forming a bridge between quantum mechanics, probability theory, and mathematical finance.
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C.
Feynman–Hellmann theorem
The Feynman–Hellmann theorem is a result in quantum mechanics that relates the derivative of an energy eigenvalue with respect to a parameter in the Hamiltonian to the expectation value of the corresponding derivative of the Hamiltonian.
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D.
Feynman checkerboard model
The Feynman checkerboard model is a path-integral-based lattice model introduced by Richard Feynman to illustrate and derive the behavior of relativistic quantum particles, particularly the Dirac equation in one spatial dimension.
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E.
Bose–Einstein statistics
Bose–Einstein statistics is a quantum statistical framework that describes the distribution and collective behavior of indistinguishable bosons, underpinning phenomena such as Bose–Einstein condensation.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Born–Huang expansion Target entity description: The Born–Huang expansion is a quantum mechanical method that systematically improves upon the Born–Oppenheimer approximation by including couplings between electronic and nuclear motions in molecular systems.
-
A.
Born–Oppenheimer approximation
The Born–Oppenheimer approximation is a fundamental method in molecular quantum mechanics that simplifies calculations by treating nuclear motion as much slower than electronic motion, allowing their behaviors to be separated.
-
B.
Feynman–Kac formula
The Feynman–Kac formula is a fundamental result connecting solutions of certain partial differential equations with expectations over stochastic processes, forming a bridge between quantum mechanics, probability theory, and mathematical finance.
-
C.
Feynman–Hellmann theorem
The Feynman–Hellmann theorem is a result in quantum mechanics that relates the derivative of an energy eigenvalue with respect to a parameter in the Hamiltonian to the expectation value of the corresponding derivative of the Hamiltonian.
-
D.
Feynman checkerboard model
The Feynman checkerboard model is a path-integral-based lattice model introduced by Richard Feynman to illustrate and derive the behavior of relativistic quantum particles, particularly the Dirac equation in one spatial dimension.
-
E.
Bose–Einstein statistics
Bose–Einstein statistics is a quantum statistical framework that describes the distribution and collective behavior of indistinguishable bosons, underpinning phenomena such as Bose–Einstein condensation.
- F. None of above. chosen
Statements (41)
| Predicate | Object |
|---|---|
| instanceOf |
molecular quantum mechanics method
ⓘ
quantum mechanical method ⓘ theoretical chemistry concept ⓘ |
| accountsFor |
nonadiabatic transitions
ⓘ
vibronic coupling ⓘ |
| applicableWhen |
Born–Oppenheimer approximation breaks down
ⓘ
electronic states are close in energy ⓘ |
| appliesTo |
coupled electron–nuclear motion
ⓘ
molecular systems ⓘ |
| assumes | separation of electronic and nuclear coordinates as a starting point ⓘ |
| basedOn | Born–Oppenheimer approximation ⓘ |
| category |
approximation method in quantum chemistry
ⓘ
perturbative treatment of nonadiabatic effects ⓘ |
| decomposes | molecular wavefunction into electronic and nuclear parts ⓘ |
| describes | electronic and nuclear motions beyond the adiabatic approximation ⓘ |
| extends | adiabatic representation of molecular states ⓘ |
| field |
molecular physics
ⓘ
quantum mechanics ⓘ theoretical chemistry ⓘ |
| frameworkFor | systematic inclusion of electron–nuclear coupling terms ⓘ |
| improvesUpon | Born–Oppenheimer approximation ⓘ |
| includes |
couplings between electronic and nuclear motions
ⓘ
nonadiabatic couplings ⓘ |
| introducedIn | Born and Huang’s work on crystal lattice dynamics ⓘ |
| introduces | corrections to adiabatic potential energy surfaces ⓘ |
| mathematicalForm |
coupled electronic state expansion
ⓘ
series expansion in nuclear coordinates ⓘ |
| namedAfter |
Kun Huang
ⓘ
Max Born ⓘ |
| purpose |
to account for breakdown of the adiabatic approximation
ⓘ
to systematically improve the Born–Oppenheimer approximation ⓘ |
| relatedTo |
conical intersections
ⓘ
diabatic and adiabatic representations ⓘ molecular spectroscopy ⓘ nonadiabatic dynamics ⓘ |
| requires | calculation of nonadiabatic coupling matrix elements ⓘ |
| usedIn |
high-precision molecular structure calculations
ⓘ
molecular spectroscopy line-shape analysis ⓘ theory of vibronic spectra ⓘ |
| uses | expansion of the total molecular wavefunction ⓘ |
| wavefunctionType | total electron–nuclear wavefunction ⓘ |
How these facts were elicited
The pipeline generated the facts above by prompting gpt-5.1 with this entity's name + description and the instruction below.
Instruction
You are a knowledge base construction expert. Given a subject entity and a description of it, return factual statements that you know for the subject as a JSON list of dictionaries(triples), where keys must be "subject", "predicate" and "object". The number of facts may be very high, between 25 to 50 or more, for very popular subjects. For less popular subjects, the number of facts can be very low, like 5 or 10. # Requirements - If you don't know the subject at all, return an empty list. - If the subject is not a named entity, return an empty list. - Include at least one triple where predicate is "instanceOf". - Do not get too wordy. - Separate several objects into multiple triples with one object.
Input
Subject: Born–Huang expansion Description of subject: The Born–Huang expansion is a quantum mechanical method that systematically improves upon the Born–Oppenheimer approximation by including couplings between electronic and nuclear motions in molecular systems.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.