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@@ -80,4 +80,72 @@ DEBUG:__main__:
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The result is saved in the folder `data/topdata` as a JSON file — giving a model name helps keeping
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track of these outputs.
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Note that for Calabi–Yau dimensions larger than four, the additional
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Note that for Calabi–Yau dimensions larger than four, the additional
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## period_computation
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`period_computation.sage` provides classes for working with Picard–Fuchs operators and their
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period solutions: `PFOperator`, `PFIdeal` and `Period`, together with Ansatz variants of the first and
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last (`PFOperatorAnsatz`, `PeriodAnsatz`) used to search for unknown operators or periods of a given
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z- and theta-degree.
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A `PFOperator` is parsed from a string in the variables `z0, ..., z<n-1>` and `theta0, ..., theta<n-1>`,
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the logarithmic derivatives theta_i = z_i d/dz_i. For example, the quintic's Picard–Fuchs operator:
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```python
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L = PFOperator(
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"theta0^4 - 3125*z0*theta0^4 - 6250*z0*theta0^3 - 4375*z0*theta0^2 - 1250*z0*theta0 - 120*z0",
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no_variables=1,
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)
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L.simplify().operator_string
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```
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```term
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'-5*(5*theta0 + 4)*(5*theta0 + 3)*(5*theta0 + 2)*(5*theta0 + 1)*z0 + theta0^4'
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```
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An operator (or a `PFIdeal` of several) can be solved for its power series solution at given indicial
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exponents and order.
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```python
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ideal = PFIdeal([L])
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period = ideal.find_power_series_solution(indicials=[0], order=3)[0]
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period.period_string
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```
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```term
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'168168000*z0^3 + 113400*z0^2 + 120*z0 + 1'
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```
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The reverse direction is supported too: given a `Period`, `find_annihilating_operators` searches for
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`PFOperator`s of a given z- and theta-degree that annihilate it, by solving an Ansatz of unknown
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coefficients via linear algebra. Both directions extend to several moduli, e.g. for the two-parameter
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model P_{2,2,2,1,1}[8]:
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```python
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M1 = PFOperator(
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"theta1*(-2*theta0 + 2*theta1 - 1) + 2*(theta0 - 2*theta1 - 1)*(theta0 - 2*theta1)*z1",
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no_variables=2,
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)
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M2 = PFOperator(
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"theta0^2*(2*(theta0 - 2*theta1)*z1 - theta1) - 16*(2*theta0 + 1)*(4*theta0 + 1)*(4*theta0 + 3)*z0*z1",
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no_variables=2,
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)
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ideal = PFIdeal([M1, M2])
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period = ideal.find_power_series_solution(indicials=[0, 1 / 2], order=6)[0]
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recovered = period.find_annihilating_operators(z_degree=1, theta_degree=2)
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period.period_string
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recovered[0].simplify().operator_string
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```
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```term
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'-1/45045*(60886425600*z0^3*z1^3 - 2767564800*z0^2*z1^4 + 100638720*z0*z1^5 - 14192640*z1^6 + 830269440*z0^2*z1^3 - 30750720*z0*z1^4 + 4193280*z1^5 - 242161920*z0^2*z1^2 + 9884160*z0*z1^3 - 1281280*z1^4 - 3459456*z0*z1^2 + 411840*z1^3 + 1441440*z0*z1 - 144144*z1^2 + 60060*z1 - 45045)*sqrt(z1)'
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'-2*(theta0 - 2*theta1)*(theta0 - 2*theta1 - 1)*z1 + (2*theta0 - 2*theta1 + 1)*theta1'
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```
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`recovered[0]` is, up to scale, `M1` — recovered purely from `M1`, `M2`'s shared power series
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solution.
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