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[FTheoryTools] Add model 1511.03209
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HereAround committed Aug 9, 2024
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{
"model_index": "46",
"arxiv_data": {
"id": "1511.03209",
"doi": "10.48550/arXiv.1511.03209",
"version": "3",
"discipline": "hep-th",
"link": "https://arxiv.org/abs/1511.03209",
"model_location": {
"section": "2",
"equation": "2.11",
"page": "3"
}
},
"journal_data": {
"doi": "https://doi.org/10.1007/JHEP12(2015)164",
"journal": "JHEP",
"volume": "12",
"pages": "164",
"year": "2015",
"link": "https://link.springer.com/article/10.1007/JHEP12(2015)164",
"model_location": {
"section": "2",
"equation": "2.11",
"page": "3"
}
},
"paper_metadata": {
"authors": ["Washington Taylor", "Yi-Nan Wang"],
"title": "The F-theory geometry with the most flux vacua",
"description": "The F-theory geometry with most flux vacua",
"buzzwords": ["GUT model", "Tate", "U(1)", "SU(5)"]
},
"model_descriptors": {
"type": "tate",
"description": "The F-theory geometry with most flux vacua",
"gauge_algebra": ["e(8)","e(8)","e(8)","e(8)","e(8)","e(8)","e(8)","e(8)","e(8)","f(4)","f(4)","f(4)","f(4)","f(4)","f(4)","f(4)","f(4)","g(2)","g(2)","g(2)","g(2)","g(2)","g(2)","g(2)","g(2)","g(2)","g(2)","g(2)","g(2)","g(2)","g(2)","g(2)","g(2)","su(2)","su(2)","su(2)","su(2)","su(2)","su(2)","su(2)","su(2)","su(2)","su(2)","su(2)","su(2)","su(2)","su(2)","su(2)","su(2)"]
},
"model_data": {
"base_dim": 3,
"model_sections": ["a1", "a2", "a3", "a4", "a6"],
"a1": "a1",
"a2": "a2",
"a3": "a3",
"a4": "a4",
"a6": "a6",
"classes_of_model_sections_in_basis_of_Kbar_and_defining_classes": [
[1, 2, 3, 4, 6]
],
"resolutions": [
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]
]
]
}
}
Original file line number Diff line number Diff line change
Expand Up @@ -161,6 +161,12 @@ Hypersurface model over a concrete base
julia> hypersurface_equation_parametrization(h2)
b*w*v^2 - c0*u^4 - c1*u^3*v - c2*u^2*v^2 - c3*u*v^3 + w^2
```
In principle, we can even create the model with the largest number of F-theory vacua.
This happens by executing the line `h = literature_model(arxiv_id = "1511.03209")`.
However, this line will currently run for a long time on a normal personal computer
(likely about half and hour or even more), due to the massive complexity of computing
the Tate sections of this global Tate model. We are investigating ways of achieve
a speed-up for this construction.
"""
function literature_model(; doi::String="", arxiv_id::String="", version::String="", equation::String="", type::String="", model_parameters::Dict{String,<:Any} = Dict{String,Any}(), base_space::FTheorySpace = affine_space(NormalToricVariety, 0), model_sections::Dict{String, <:Any} = Dict{String,Any}(), defining_classes::Dict{String, <:Any} = Dict{String,Any}(), completeness_check::Bool = true)
model_dict = _find_model(doi, arxiv_id, version, equation, type)
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