q-Gaussian distribution
E809119
The q-Gaussian distribution is a generalized probability distribution arising in Tsallis statistics that extends the normal (Gaussian) distribution to model systems with heavy tails and nonextensive behavior.
All labels observed (1)
| Label | Occurrences |
|---|---|
| q-Gaussian distribution canonical | 2 |
How this entity was disambiguated
This entity first appeared as the object of triple T9593168 — 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: q-Gaussian distribution Context triple: [Tsallis, proposedConcept, q-Gaussian distribution]
-
A.
Gaussian distribution
The Gaussian distribution, also known as the normal distribution, is a fundamental continuous probability distribution characterized by its symmetric bell-shaped curve and central role in statistics and the natural sciences.
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B.
Glauber–Sudarshan P function
The Glauber–Sudarshan P function is a quasi-probability distribution in quantum optics that represents quantum states in terms of coherent states, often revealing nonclassical properties through its singular or non-positive behavior.
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C.
Gaussian
Gaussian is a widely used computational chemistry software package that performs electronic structure calculations, including density functional theory, for molecules and materials.
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D.
Carsey-Werner Distribution
Carsey-Werner Distribution is a television distribution company best known for handling popular sitcoms produced by Carsey-Werner, including major hits from the late 1980s and 1990s.
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E.
Dirichlet distribution
The Dirichlet distribution is a family of continuous multivariate probability distributions commonly used as a prior over categorical or multinomial parameters in Bayesian statistics.
- 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: q-Gaussian distribution Target entity description: The q-Gaussian distribution is a generalized probability distribution arising in Tsallis statistics that extends the normal (Gaussian) distribution to model systems with heavy tails and nonextensive behavior.
-
A.
Gaussian distribution
The Gaussian distribution, also known as the normal distribution, is a fundamental continuous probability distribution characterized by its symmetric bell-shaped curve and central role in statistics and the natural sciences.
-
B.
Glauber–Sudarshan P function
The Glauber–Sudarshan P function is a quasi-probability distribution in quantum optics that represents quantum states in terms of coherent states, often revealing nonclassical properties through its singular or non-positive behavior.
-
C.
Gaussian
Gaussian is a widely used computational chemistry software package that performs electronic structure calculations, including density functional theory, for molecules and materials.
-
D.
Carsey-Werner Distribution
Carsey-Werner Distribution is a television distribution company best known for handling popular sitcoms produced by Carsey-Werner, including major hits from the late 1980s and 1990s.
-
E.
Dirichlet distribution
The Dirichlet distribution is a family of continuous multivariate probability distributions commonly used as a prior over categorical or multinomial parameters in Bayesian statistics.
- F. None of above. chosen
Statements (47)
| Predicate | Object |
|---|---|
| instanceOf |
Tsallis distribution
ⓘ
generalized Gaussian distribution ⓘ probability distribution ⓘ |
| arisesIn | Tsallis statistics NERFINISHED ⓘ |
| belongsTo | non-Gaussian stable-like distributions ⓘ |
| generalizes | normal distribution NERFINISHED ⓘ |
| hasFamilyName | q-Gaussian family ⓘ |
| hasFiniteMeanCondition | q < 2 ⓘ |
| hasFiniteVarianceCondition | q < 5/3 ⓘ |
| hasInfiniteMean | for 2 ≤ q < 3 ⓘ |
| hasInfiniteVariance | for 5/3 ≤ q < 3 ⓘ |
| hasLimitingCase | uniform distribution as q → -∞ (in a bounded domain, formal) ⓘ |
| hasParameter |
location parameter
ⓘ
q ⓘ scale parameter ⓘ |
| hasShapeParameter | q ⓘ |
| hasSupport |
bounded support for q < 1
ⓘ
unbounded support for 1 ≤ q < 3 ⓘ |
| hasTailBehavior |
Gaussian tails for q = 1
ⓘ
compact support for q < 1 ⓘ power-law tails for 1 < q < 3 ⓘ |
| isAlternativeTo | Student-t distribution for heavy tails ⓘ |
| isAssociatedWith | Tsallis entropy NERFINISHED ⓘ |
| isBasedOn | nonextensive statistical mechanics ⓘ |
| isConnectedTo | central limit theorems in nonextensive statistics ⓘ |
| isDefinedOn | real line ⓘ |
| isEvenFunction | true ⓘ |
| isNonNormalizableFor | q ≥ 3 ⓘ |
| isNormalizableFor | q < 3 ⓘ |
| isParameterizedBy | entropic index q ⓘ |
| isRelatedTo |
q-exponential function
ⓘ
q-logarithm ⓘ |
| isSpecialCaseOf | q-exponential family ⓘ |
| isSymmetric | true ⓘ |
| isUnimodal | true ⓘ |
| isUsedIn |
complex systems theory
ⓘ
econophysics ⓘ plasma physics ⓘ statistical physics ⓘ turbulence modeling ⓘ |
| isUsedToModel |
anomalous diffusion
ⓘ
heavy-tailed phenomena ⓘ nonextensive systems ⓘ systems with long-range interactions ⓘ systems with long-term memory ⓘ |
| maximizes | Tsallis entropy under suitable constraints ⓘ |
| reducesTo | normal distribution when q = 1 ⓘ |
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: q-Gaussian distribution Description of subject: The q-Gaussian distribution is a generalized probability distribution arising in Tsallis statistics that extends the normal (Gaussian) distribution to model systems with heavy tails and nonextensive behavior.
Referenced by (2)
Full triples — surface form annotated when it differs from this entity's canonical label.