Adding holo from l-vectors
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This commit is contained in:
Julian Piribauer
2026-10-27 14:35:32 +01:00
parent f5f960b42e
commit e9804cfa70
4 changed files with 351 additions and 265 deletions
+4 -3
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@@ -82,12 +82,13 @@ The result is saved in the folder `data/topdata` as a JSON file — giving a
track of these outputs.
Note that for Calabi–Yau dimensions larger than four, the additional
## period_computation
## Operators and periods
`period_computation.sage` provides classes for working with Picard–Fuchs operators and their
`operators.sage` and `period.sage` provide classes for working with Picard–Fuchs operators and their
period solutions: `PFOperator`, `PFIdeal` and `Period`, together with Ansatz variants of the first and
last (`PFOperatorAnsatz`, `PeriodAnsatz`) used to search for unknown operators or periods of a given
z- and theta-degree.
z- and theta-degree. The operator classes live in `operators.sage`, the period classes in `period.sage`;
since the two depend on each other, load `period.sage`, which also loads `operators.sage`.
A `PFOperator` is parsed from a string in the variables `z0, ..., z<n-1>` and `theta0, ..., theta<n-1>`,
the logarithmic derivatives theta_i = z_i d/dz_i. For example, the quintic's Picard&ndash;Fuchs operator:
@@ -1,6 +1,6 @@
import copy
import logging
from sage.all import sage_eval, PolynomialRing, QQ, SR, function, log, matrix, prod, solve, var
from sage.all import sage_eval, PolynomialRing, QQ, SR, function, prod, solve, var
load("sage/util.py")
@@ -384,263 +384,3 @@ class PFIdeal:
"Found %d power series solution(s) for indicials %s at order %d.", len(solutions), indicials, order
)
return solutions
class Period:
"""
A class representing a period as a formal power series in z-variables and their logs.
The coefficients are stored in a dictionary of dictionaries, where the first key is the multi-index
of the logarithmic part and the second key is the multi-index of the z-variables.
So, for example, the coefficient of
log(z0)^2 * log(z1) * z0^3 * z1^2 would be stored as coefficients[(2, 1)][(3, 2)]
"""
def _initialise_ring(self):
z_names = ['z%d' % i for i in range(self.no_variables)]
log_names = ['L%d' % i for i in range(self.no_variables)]
ring = PolynomialRing(QQ, z_names + log_names)
z_gens = ring.gens()[:self.no_variables]
log_gens = ring.gens()[self.no_variables:]
return ring, z_gens, log_gens # type: (PolynomialRing, list, list)
def _period_from_string(self, period_string: str) -> dict:
ring, z_gens, log_gens = self._initialise_ring()
log_of_z = dict(zip(z_gens, log_gens))
def log(zi):
try:
return log_of_z[zi]
except (KeyError, TypeError):
raise ValueError(
"log(...) may only be applied to one of the z-variables z0, ..., z%d"
% (self.no_variables - 1)
)
parse_locals = dict(ring.gens_dict())
parse_locals['log'] = log
try:
expression = ring(sage_eval(period_string, locals=parse_locals))
except Exception as e:
raise ValueError("Invalid period string: %s" % e)
coefficients = {}
for coeff, monomial in expression:
exponents = monomial.exponents()[0]
z_index = tuple(exponents[:self.no_variables])
log_index = tuple(exponents[self.no_variables:])
coefficients.setdefault(log_index, {})[z_index] = coeff
return coefficients
def _period_to_string(self) -> str:
ring, z_gens, log_gens = self._initialise_ring()
expression = ring(0)
for log_index, z_dict in self.coefficients.items():
for z_index, coeff in z_dict.items():
monomial = coeff
for i in range(self.no_variables):
monomial *= (log_gens[i] ** log_index[i]) * (z_gens[i] ** z_index[i])
expression += monomial
log_substitutions = {log_gens[i]: log(SR(z_gens[i])) for i in range(self.no_variables)}
result = SR(expression).subs(log_substitutions)
# A nonzero indicial ρ_i means the coefficients above are for z_i^k, but the
# actual solution is z_i^(ρ_i + k); make that explicit in the printed form.
indicial_prefactor = prod(
(SR(z_gens[i]) ** self.indicials[i] for i in range(self.no_variables) if self.indicials[i] != 0),
SR(1),
)
if indicial_prefactor != 1:
result *= indicial_prefactor
return str(result)
def _max_z_degree(self) -> int:
# Highest total z-degree (sum of the z-multi-index) among all coefficients.
if not self.coefficients:
return 0
return max(
sum(z_index)
for z_dict in self.coefficients.values()
for z_index in z_dict
)
def _truncate_coefficients(self, order: int) -> dict:
# Drop every (log_index, z_index) entry whose total z-degree exceeds order,
# removing it from the dictionary rather than merely zeroing it out.
truncated = {}
for log_index, z_dict in self.coefficients.items():
kept = {z_index: coeff for z_index, coeff in z_dict.items() if sum(z_index) <= order}
if kept:
truncated[log_index] = kept
return truncated
def _apply_theta(self, coefficients: dict, index: int) -> dict:
"""
Applies the logarithmic derivative theta_i = z_i * d/dz_i once to a coefficients dict of the same
shape as self.coefficients. It uses the product rule
theta_i(z^a log(z)^k) = a_i * z^a log(z)^k + k_i * z^a log(z)^(k - e_i).
z_index entries are offsets from self.indicials: a stored z_index of a really means
z^(a + self.indicials[index]), so theta_i's eigenvalue is a_i + self.indicials[index]
rather than the bare a_i (self.indicials is all-zero unless explicitly given, in which
case this reduces to the ordinary power-series rule).
"""
result = {}
for log_index, z_dict in coefficients.items():
for z_index, coeff in z_dict.items():
a_i = z_index[index] + self.indicials[index]
if a_i != 0:
inner = result.setdefault(log_index, {})
inner[z_index] = inner.get(z_index, 0) + a_i * coeff
k_i = log_index[index]
if k_i != 0:
lowered_log_index = log_index[:index] + (k_i - 1,) + log_index[index + 1:]
inner = result.setdefault(lowered_log_index, {})
inner[z_index] = inner.get(z_index, 0) + k_i * coeff
return result
def apply_operator(self, pf_operator: PFOperator) -> "Period":
"""
Applies a PFOperator to this period and returns the result as a new Period,
truncated to self.order. Each monomial of the operator is normalised as
coeff * z^p * theta^q (see PFOperator's docstring), so theta^q is applied
to the period first and the result is then multiplied by coeff * z^p.
"""
if pf_operator.no_variables != self.no_variables:
raise ValueError(
"Variable count mismatch: period has %d variable(s), operator has %d."
% (self.no_variables, pf_operator.no_variables)
)
result_coefficients = {}
for monomial_coeff, monomial in pf_operator.operator:
exponents = monomial.exponents()[0]
z_exponents = exponents[:self.no_variables]
theta_exponents = exponents[self.no_variables:]
term = self.coefficients
for i, power in enumerate(theta_exponents):
for _ in range(power):
term = self._apply_theta(term, i)
for log_index, z_dict in term.items():
inner = result_coefficients.setdefault(log_index, {})
for z_index, coeff in z_dict.items():
shifted_z_index = tuple(z_index[i] + z_exponents[i] for i in range(self.no_variables))
inner[shifted_z_index] = inner.get(shifted_z_index, 0) + monomial_coeff * coeff
result_coefficients = {
log_index: {z_index: c for z_index, c in z_dict.items() if c != 0}
for log_index, z_dict in result_coefficients.items()
}
result_coefficients = {log_index: z_dict for log_index, z_dict in result_coefficients.items() if z_dict}
return Period(
no_variables=self.no_variables,
coefficients=result_coefficients,
order=self.order,
indicials=self.indicials,
)
def find_annihilating_operators(self, z_degree: int, theta_degree: int) -> list:
"""
Finds operators annihilating this period among PFOperator Ansätze of the given
z- and theta-degree.
"""
ansatz = PFOperatorAnsatz(self.no_variables, theta_degree, z_degree)
unknowns = ansatz.unknowns
equations = [
coeff
for z_dict in self.apply_operator(ansatz).coefficients.values()
for coeff in z_dict.values()
]
coefficient_rows = [[SR(equation).coefficient(b) for b in unknowns] for equation in equations]
kernel_basis = matrix(QQ, coefficient_rows, ncols=len(unknowns)).right_kernel().basis()
operators = []
for basis_vector in kernel_basis:
solution = {unknowns[j]: basis_vector[j] for j in range(len(unknowns))}
solved_operator = ansatz.operator.map_coefficients(lambda c: SR(c).subs(solution))
operators.append(PFOperator(str(solved_operator), no_variables=self.no_variables))
return operators
def __init__(
self,
no_variables: int = 1,
coefficients: dict = None,
period_string: str = None,
order: int = None,
indicials: list = None,
):
self.no_variables = no_variables
# indicials[i] is the (rational) Frobenius exponent ρ_i of z_i: a stored
# z-index of a really represents z^(a + indicials[i]).
self.indicials = list(indicials) if indicials is not None else [0] * no_variables
# Use coefficients or period_string to initialize the period
if period_string is not None:
if coefficients is not None:
raise ValueError("Provide either coefficients or period_string, not both.")
self.coefficients = self._period_from_string(period_string)
self.period_string = period_string
logger.debug("Using string for initialisation.")
elif coefficients is None:
self.coefficients = {}
else:
self.coefficients = coefficients
self.period_string = self._period_to_string()
logger.debug("Using coefficients for initialisation.")
if order is None:
self.order = self._max_z_degree()
logger.debug("Order not provided, using maximum z-degree: %d", self.order)
else:
self.coefficients = self._truncate_coefficients(order)
self.order = order
self.period_string = self._period_to_string()
logger.debug("Truncated coefficients to order %d.", self.order)
logger.info("Initialised Period in %d variables at order %d.", self.no_variables, self.order)
class PeriodAnsatz(Period):
"""
A class for period Ansätze, characterised by number of variables and their z- and log-multi-degrees.
"""
def __init__(self, no_variables: int, z_degree: int, log_degree: int, indicials: list = None):
self.no_variables = no_variables
self.z_degree = z_degree
self.log_degree = log_degree
log_indices = _multi_indices(self.no_variables, log_degree)
z_indices = _multi_indices(self.no_variables, z_degree)
# Every (log_index, z_index) pair allowed by the degree bounds gets its own
# fresh unknown, to be solved for once a PFOperator is applied to the Ansatz.
coefficients = {
log_index: {
z_index: var("a_" + "_".join(str(x) for x in log_index + z_index))
for z_index in z_indices
}
for log_index in log_indices
}
super().__init__(no_variables=no_variables, coefficients=coefficients, order=z_degree, indicials=indicials)
self.expansion_coefficients = self.coefficients
logger.info(
"Initialised PeriodAnsatz with %d unknown coefficient(s).",
sum(len(z_dict) for z_dict in self.expansion_coefficients.values()),
)
+345
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@@ -0,0 +1,345 @@
import logging
from sage.all import sage_eval, PolynomialRing, QQ, SR, ceil, factorial, floor, log, matrix, prod, var
load("sage/operators.sage")
# Logger
logger = logging.getLogger(__name__)
logging.basicConfig(level=logging.DEBUG)
class Period:
"""
A class representing a period as a formal power series in z-variables and their logs.
The coefficients are stored in a dictionary of dictionaries, where the first key is the multi-index
of the logarithmic part and the second key is the multi-index of the z-variables.
So, for example, the coefficient of
log(z0)^2 * log(z1) * z0^3 * z1^2 would be stored as coefficients[(2, 1)][(3, 2)]
"""
def _initialise_ring(self):
z_names = ['z%d' % i for i in range(self.no_variables)]
log_names = ['L%d' % i for i in range(self.no_variables)]
ring = PolynomialRing(QQ, z_names + log_names)
z_gens = ring.gens()[:self.no_variables]
log_gens = ring.gens()[self.no_variables:]
return ring, z_gens, log_gens # type: (PolynomialRing, list, list)
def _period_from_string(self, period_string: str) -> dict:
ring, z_gens, log_gens = self._initialise_ring()
log_of_z = dict(zip(z_gens, log_gens))
def log(zi):
try:
return log_of_z[zi]
except (KeyError, TypeError):
raise ValueError(
"log(...) may only be applied to one of the z-variables z0, ..., z%d"
% (self.no_variables - 1)
)
parse_locals = dict(ring.gens_dict())
parse_locals['log'] = log
try:
expression = ring(sage_eval(period_string, locals=parse_locals))
except Exception as e:
raise ValueError("Invalid period string: %s" % e)
coefficients = {}
for coeff, monomial in expression:
exponents = monomial.exponents()[0]
z_index = tuple(exponents[:self.no_variables])
log_index = tuple(exponents[self.no_variables:])
coefficients.setdefault(log_index, {})[z_index] = coeff
return coefficients
def _period_to_string(self) -> str:
ring, z_gens, log_gens = self._initialise_ring()
expression = ring(0)
for log_index, z_dict in self.coefficients.items():
for z_index, coeff in z_dict.items():
monomial = coeff
for i in range(self.no_variables):
monomial *= (log_gens[i] ** log_index[i]) * (z_gens[i] ** z_index[i])
expression += monomial
log_substitutions = {log_gens[i]: log(SR(z_gens[i])) for i in range(self.no_variables)}
result = SR(expression).subs(log_substitutions)
# A nonzero indicial ρ_i means the coefficients above are for z_i^k, but the
# actual solution is z_i^(ρ_i + k); make that explicit in the printed form.
indicial_prefactor = prod(
(SR(z_gens[i]) ** self.indicials[i] for i in range(self.no_variables) if self.indicials[i] != 0),
SR(1),
)
if indicial_prefactor != 1:
result *= indicial_prefactor
return str(result)
def _max_z_degree(self) -> int:
# Highest total z-degree (sum of the z-multi-index) among all coefficients.
if not self.coefficients:
return 0
return max(
sum(z_index)
for z_dict in self.coefficients.values()
for z_index in z_dict
)
def _truncate_coefficients(self, order: int) -> dict:
# Drop every (log_index, z_index) entry whose total z-degree exceeds order,
# removing it from the dictionary rather than merely zeroing it out.
truncated = {}
for log_index, z_dict in self.coefficients.items():
kept = {z_index: coeff for z_index, coeff in z_dict.items() if sum(z_index) <= order}
if kept:
truncated[log_index] = kept
return truncated
def _apply_theta(self, coefficients: dict, index: int) -> dict:
"""
Applies the logarithmic derivative theta_i = z_i * d/dz_i once to a coefficients dict of the same
shape as self.coefficients. It uses the product rule
theta_i(z^a log(z)^k) = a_i * z^a log(z)^k + k_i * z^a log(z)^(k - e_i).
z_index entries are offsets from self.indicials: a stored z_index of a really means
z^(a + self.indicials[index]), so theta_i's eigenvalue is a_i + self.indicials[index]
rather than the bare a_i (self.indicials is all-zero unless explicitly given, in which
case this reduces to the ordinary power-series rule).
"""
result = {}
for log_index, z_dict in coefficients.items():
for z_index, coeff in z_dict.items():
a_i = z_index[index] + self.indicials[index]
if a_i != 0:
inner = result.setdefault(log_index, {})
inner[z_index] = inner.get(z_index, 0) + a_i * coeff
k_i = log_index[index]
if k_i != 0:
lowered_log_index = log_index[:index] + (k_i - 1,) + log_index[index + 1:]
inner = result.setdefault(lowered_log_index, {})
inner[z_index] = inner.get(z_index, 0) + k_i * coeff
return result
def apply_operator(self, pf_operator: PFOperator) -> "Period":
"""
Applies a PFOperator to this period and returns the result as a new Period,
truncated to self.order. Each monomial of the operator is normalised as
coeff * z^p * theta^q (see PFOperator's docstring), so theta^q is applied
to the period first and the result is then multiplied by coeff * z^p.
"""
if pf_operator.no_variables != self.no_variables:
raise ValueError(
"Variable count mismatch: period has %d variable(s), operator has %d."
% (self.no_variables, pf_operator.no_variables)
)
result_coefficients = {}
for monomial_coeff, monomial in pf_operator.operator:
exponents = monomial.exponents()[0]
z_exponents = exponents[:self.no_variables]
theta_exponents = exponents[self.no_variables:]
term = self.coefficients
for i, power in enumerate(theta_exponents):
for _ in range(power):
term = self._apply_theta(term, i)
for log_index, z_dict in term.items():
inner = result_coefficients.setdefault(log_index, {})
for z_index, coeff in z_dict.items():
shifted_z_index = tuple(z_index[i] + z_exponents[i] for i in range(self.no_variables))
inner[shifted_z_index] = inner.get(shifted_z_index, 0) + monomial_coeff * coeff
result_coefficients = {
log_index: {z_index: c for z_index, c in z_dict.items() if c != 0}
for log_index, z_dict in result_coefficients.items()
}
result_coefficients = {log_index: z_dict for log_index, z_dict in result_coefficients.items() if z_dict}
return Period(
no_variables=self.no_variables,
coefficients=result_coefficients,
order=self.order,
indicials=self.indicials,
)
def find_annihilating_operators(self, z_degree: int, theta_degree: int) -> list:
"""
Finds operators annihilating this period among PFOperator Ansätze of the given
z- and theta-degree.
"""
ansatz = PFOperatorAnsatz(self.no_variables, theta_degree, z_degree)
unknowns = ansatz.unknowns
equations = [
coeff
for z_dict in self.apply_operator(ansatz).coefficients.values()
for coeff in z_dict.values()
]
coefficient_rows = [[SR(equation).coefficient(b) for b in unknowns] for equation in equations]
kernel_basis = matrix(QQ, coefficient_rows, ncols=len(unknowns)).right_kernel().basis()
operators = []
for basis_vector in kernel_basis:
solution = {unknowns[j]: basis_vector[j] for j in range(len(unknowns))}
solved_operator = ansatz.operator.map_coefficients(lambda c: SR(c).subs(solution))
operators.append(PFOperator(str(solved_operator), no_variables=self.no_variables))
return operators
def __init__(
self,
no_variables: int = 1,
coefficients: dict = None,
period_string: str = None,
order: int = None,
indicials: list = None,
):
self.no_variables = no_variables
# indicials[i] is the (rational) Frobenius exponent ρ_i of z_i: a stored
# z-index of a really represents z^(a + indicials[i]).
self.indicials = list(indicials) if indicials is not None else [0] * no_variables
# Use coefficients or period_string to initialize the period
if period_string is not None:
if coefficients is not None:
raise ValueError("Provide either coefficients or period_string, not both.")
self.coefficients = self._period_from_string(period_string)
self.period_string = period_string
logger.debug("Using string for initialisation.")
elif coefficients is None:
self.coefficients = {}
else:
self.coefficients = coefficients
self.period_string = self._period_to_string()
logger.debug("Using coefficients for initialisation.")
if order is None:
self.order = self._max_z_degree()
logger.debug("Order not provided, using maximum z-degree: %d", self.order)
else:
self.coefficients = self._truncate_coefficients(order)
self.order = order
self.period_string = self._period_to_string()
logger.debug("Truncated coefficients to order %d.", self.order)
logger.info("Initialised Period in %d variables at order %d.", self.no_variables, self.order)
@classmethod
def from_l_vectors(cls, l_vectors: list, order: int) -> "Period":
"""
Computes the holomorphic (fundamental) period directly from the GLSM/Mori charge
vectors l^(1), ..., l^(m) of a toric Calabi-Yau (m = number of moduli), via the
hypergeometric-type sum
varpi_0(z) = sum_{a in Z_{>=0}^m}
(prod_j Gamma(1 - l_num^(j).a)) / (prod_i Gamma(1 + l_den^(i).a)) * z^a,
see e.g. Hosono-Klemm-Theisen-Yau. l_vectors is a list of the m charge vectors, each
given as [numerator part, denominator part]: the components landing in the numerator
resp. denominator Gamma-functions (for a Calabi-Yau hypersurface/CICY, these are the
nef-partition weight(s) resp. the toric divisor charges). For m = 1 the outer list may
be dropped, e.g. the quintic is given by [[-5], [1, 1, 1, 1, 1]], while P^4_{1,1,2,2,6}[12]
is given by [[[-6], [3, 2, 1, 0, 0, 0]], [[0], [0, 0, -3, 1, 1, 1]]].
For a Calabi-Yau charge vector the numerator Gamma-functions never hit a pole, since
their argument only grows as a grows; only the denominator factors can vanish - at a
non-positive-integer argument - which is exactly what truncates each a_k to a finite
range once the others are fixed. This makes summing directly over that range far
cheaper than solving the full Picard-Fuchs system term by term.
"""
# A single charge vector [numerator part, denominator part] has integer entries in its parts.
if l_vectors and l_vectors[0] and not isinstance(l_vectors[0][0], (list, tuple)):
l_vectors = [l_vectors]
if any(len(l_vector) != 2 for l_vector in l_vectors):
raise ValueError("Each charge vector must be given as [numerator part, denominator part].")
m = len(l_vectors)
numerator_charges = [l_vector[0] for l_vector in l_vectors]
denominator_charges = [l_vector[1] for l_vector in l_vectors]
len0 = len(numerator_charges[0]) if m else 0
len1 = len(denominator_charges[0]) if m else 0
# Each denominator Gamma-factor is linear in a; pivot it on the smallest index j with
# a nonzero coefficient there. Since a is built up from a_{m-1} down to a_0, every
# other index still appearing in that linear form is then already fixed, turning the
# factor's pole at non-positive integers into a concrete bound on a_j.
pivots = [[] for _ in range(m)]
for i in range(len1):
charges = [denominator_charges[k][i] for k in range(m)]
j = next(k for k in range(m) if charges[k] != 0)
pivots[j].append(charges)
coefficients = {}
a = [0] * m
def recurse(j, num_partial, den_partial, degree):
if j < 0:
numerator = prod(factorial(-x) for x in num_partial)
denominator = prod(factorial(x) for x in den_partial)
coefficients[tuple(a)] = QQ(numerator) / QQ(denominator)
return
lower, upper = 0, order - degree
for charges in pivots[j]:
c = charges[j]
bound = -QQ(sum(charges[k] * a[k] for k in range(j + 1, m))) / QQ(c)
if c < 0:
upper = min(upper, floor(bound))
else:
lower = max(lower, ceil(bound))
for a_j in range(lower, upper + 1):
a[j] = a_j
recurse(
j - 1,
[num_partial[jj] + numerator_charges[j][jj] * a_j for jj in range(len0)],
[den_partial[ii] + denominator_charges[j][ii] * a_j for ii in range(len1)],
degree + a_j,
)
recurse(m - 1, [0] * len0, [0] * len1, 0)
logger.info("Computed holomorphic period from l-vectors for %d moduli at order %d.", m, order)
return cls(no_variables=m, coefficients={tuple([0] * m): coefficients}, order=order)
class PeriodAnsatz(Period):
"""
A class for period Ansätze, characterised by number of variables and their z- and log-multi-degrees.
"""
def __init__(self, no_variables: int, z_degree: int, log_degree: int, indicials: list = None):
self.no_variables = no_variables
self.z_degree = z_degree
self.log_degree = log_degree
log_indices = _multi_indices(self.no_variables, log_degree)
z_indices = _multi_indices(self.no_variables, z_degree)
# Every (log_index, z_index) pair allowed by the degree bounds gets its own
# fresh unknown, to be solved for once a PFOperator is applied to the Ansatz.
coefficients = {
log_index: {
z_index: var("a_" + "_".join(str(x) for x in log_index + z_index))
for z_index in z_indices
}
for log_index in log_indices
}
super().__init__(no_variables=no_variables, coefficients=coefficients, order=z_degree, indicials=indicials)
self.expansion_coefficients = self.coefficients
logger.info(
"Initialised PeriodAnsatz with %d unknown coefficient(s).",
sum(len(z_dict) for z_dict in self.expansion_coefficients.values()),
)
+1 -1
View File
@@ -2,7 +2,7 @@ import os
from sage.all import * # noqa: F401
load(os.path.join(os.path.dirname(__file__), "..", "sage", "period_computation.sage"))
load(os.path.join(os.path.dirname(__file__), "..", "sage", "period.sage"))
def test_apply_operator_univariate():