def eis_phipsi(phi, psi, k, prec=10, t=1, cmplx=False):
r"""
Return Fourier expansion of Eisenstein series at the cusp oo.
INPUT:
- ``phi`` -- Dirichlet character.
- ``psi`` -- Dirichlet character.
- ``k`` -- integer, the weight of the Eistenstein series.
- ``prec`` -- integer (default: 10).
- ``t`` -- integer (default: 1).
OUTPUT:
The Fourier expansion of the Eisenstein series $E_k^{\phi,\psi, t}$ (as
defined by [Diamond-Shurman]).
EXAMPLES:
sage: phi = DirichletGroup(3)[1]
sage: psi = DirichletGroup(5)[1]
sage: E = eisenstein_series_at_inf(phi, psi, 4)
"""
N1, N2 = phi.level(), psi.level()
N = N1 * N2
#The Fourier expansion of the Eisenstein series at infinity is in the field Q(zeta_Ncyc)
Ncyc = lcm([euler_phi(N1), euler_phi(N2)])
if cmplx == True:
CC = ComplexField(53)
pi = ComplexField().pi()
I = ComplexField().gen()
R = CC
zeta = CC(exp(2 * pi * I / Ncyc))
else:
R = CyclotomicField(Ncyc)
zeta = R.zeta(Ncyc)
phi, psi = phi.base_extend(R), psi.base_extend(R)
Q = PowerSeriesRing(R, 'q')
q = Q.gen()
s = O(q**prec)
#Weight 2 with trivial characters is calculated separately
if k == 2 and phi.conductor() == 1 and psi.conductor() == 1:
if t == 1:
raise TypeError('E_2 is not a modular form.')
s = 1 / 24 * (t - 1)
for m in srange(1, prec):
for n in srange(1, prec / m + 1):
s += n * (q**(m * n) - t * q**(m * n * t))
return s + O(q**prec)
if psi.level() == 1 and k == 1:
s -= phi.bernoulli(k) / k
elif phi.level() == 1:
s -= psi.bernoulli(k) / k
for m in srange(1, prec / t):
for n in srange(1, prec / t / m + 1):
s += 2 * phi(m) * psi(n) * n**(k - 1) * q**(m * n * t)
return s + O(q**prec)
def local_coordinates_at_infinity(self, prec=20, name='t'):
"""
For the genus `g` hyperelliptic curve `y^2 = f(x)`, return
`(x(t), y(t))` such that `(y(t))^2 = f(x(t))`, where `t = x^g/y` is
the local parameter at infinity
INPUT:
- ``prec`` -- desired precision of the local coordinates
- ``name`` -- generator of the power series ring (default: ``t``)
OUTPUT:
`(x(t),y(t))` such that `y(t)^2 = f(x(t))` and `t = x^g/y`
is the local parameter at infinity
EXAMPLES::
sage: R.<x> = QQ['x']
sage: H = HyperellipticCurve(x^5-5*x^2+1)
sage: x,y = H.local_coordinates_at_infinity(10)
sage: x
t^-2 + 5*t^4 - t^8 - 50*t^10 + O(t^12)
sage: y
t^-5 + 10*t - 2*t^5 - 75*t^7 + 50*t^11 + O(t^12)
::
sage: R.<x> = QQ['x']
sage: H = HyperellipticCurve(x^3-x+1)
sage: x,y = H.local_coordinates_at_infinity(10)
sage: x
t^-2 + t^2 - t^4 - t^6 + 3*t^8 + O(t^12)
sage: y
t^-3 + t - t^3 - t^5 + 3*t^7 - 10*t^11 + O(t^12)
AUTHOR:
- Jennifer Balakrishnan (2007-12)
"""
g = self.genus()
pol = self.hyperelliptic_polynomials()[0]
K = LaurentSeriesRing(self.base_ring(), name, default_prec=prec + 2)
t = K.gen()
L = PolynomialRing(K, 'x')
x = L.gen()
i = 0
w = (x**g / t)**2 - pol
wprime = w.derivative(x)
if pol.degree() == 2 * g + 1:
x = t**-2
else:
x = t**-1
for i in range((RR(log(prec + 2) / log(2))).ceil()):
x = x - w(x) / wprime(x)
y = x**g / t
return x + O(t**(prec + 2)), y + O(t**(prec + 2))
def local_coordinates_at_nonweierstrass(self, P, prec=20, name='t'):
"""
For a non-Weierstrass point `P = (a,b)` on the hyperelliptic
curve `y^2 = f(x)`, return `(x(t), y(t))` such that `(y(t))^2 = f(x(t))`,
where `t = x - a` is the local parameter.
INPUT:
- ``P = (a, b)`` -- a non-Weierstrass point on self
- ``prec`` -- desired precision of the local coordinates
- ``name`` -- gen of the power series ring (default: ``t``)
OUTPUT:
`(x(t),y(t))` such that `y(t)^2 = f(x(t))` and `t = x - a`
is the local parameter at `P`
EXAMPLES::
sage: R.<x> = QQ['x']
sage: H = HyperellipticCurve(x^5-23*x^3+18*x^2+40*x)
sage: P = H(1,6)
sage: x,y = H.local_coordinates_at_nonweierstrass(P,prec=5)
sage: x
1 + t + O(t^5)
sage: y
6 + t - 7/2*t^2 - 1/2*t^3 - 25/48*t^4 + O(t^5)
sage: Q = H(-2,12)
sage: x,y = H.local_coordinates_at_nonweierstrass(Q,prec=5)
sage: x
-2 + t + O(t^5)
sage: y
12 - 19/2*t - 19/32*t^2 + 61/256*t^3 - 5965/24576*t^4 + O(t^5)
AUTHOR:
- Jennifer Balakrishnan (2007-12)
"""
d = P[1]
if d == 0:
raise TypeError(
"P = %s is a Weierstrass point. Use local_coordinates_at_weierstrass instead!"
% P)
pol = self.hyperelliptic_polynomials()[0]
L = PowerSeriesRing(self.base_ring(), name)
t = L.gen()
L.set_default_prec(prec)
K = PowerSeriesRing(L, 'x')
pol = K(pol)
x = K.gen()
b = P[0]
f = pol(t + b)
for i in range((RR(log(prec) / log(2))).ceil()):
d = (d + f / d) / 2
return t + b + O(t**(prec)), d + O(t**(prec))
def eisenstein_series_at_inf(phi, psi, k, prec=10, t=1, base_ring=None):
r"""
Return Fourier expansion of Eistenstein series at a cusp.
INPUT:
- ``phi`` -- Dirichlet character.
- ``psi`` -- Dirichlet character.
- ``k`` -- integer, the weight of the Eistenstein series.
- ``prec`` -- integer (default: 10).
- ``t`` -- integer (default: 1).
OUTPUT:
The Fourier expansion of the Eisenstein series $E_k^{\phi,\psi, t}$ (as
defined by [Diamond-Shurman]) at the specific cusp.
EXAMPLES:
sage: phi = DirichletGroup(3)[1]
sage: psi = DirichletGroup(5)[1]
sage: E = eisenstein_series_at_inf(phi, psi, 4)
"""
N1, N2 = phi.level(), psi.level()
N = N1 * N2
#The Fourier expansion of the Eisenstein series at infinity is in the field Q(zeta_Ncyc)
Ncyc = lcm([euler_phi(N1), euler_phi(N2)])
if base_ring == None:
base_ring = CyclotomicField(Ncyc)
Q = PowerSeriesRing(base_ring, 'q')
q = Q.gen()
s = O(q**prec)
#Weight 2 with trivial characters is calculated separately
if k == 2 and phi.conductor() == 1 and psi.conductor() == 1:
if t == 1:
raise TypeError('E_2 is not a modular form.')
s = 1 / 24 * (t - 1)
for m in srange(1, prec):
for n in srange(1, prec / m):
s += n * (q**(m * n) - t * q**(m * n * t))
return s + O(q**prec)
if psi.level() == 1 and k == 1:
s -= phi.bernoulli(k) / k
elif phi.level() == 1:
s -= psi.bernoulli(k) / k
for m in srange(1, prec / t):
for n in srange(1, prec / t / m + 1):
s += 2 * base_ring(phi(m)) * base_ring(
psi(n)) * n**(k - 1) * q**(m * n * t)
return s + O(q**prec)
def hz_pullback(self, mu):
r"""
Compute the pullbacks to Hirzebruch--Zagier curves.
This computes the pullback f(\tau * \mu, \tau * \mu') of f to the embedded half-plane H * (\mu, \mu') where \mu' is the conjugate of \mu. The result is a modular form of level equal to the norm of \mu.
INPUT:
- ``mu`` -- a totally-positive integer in the base-field K.
OUTPUT: an OrthogonalModularForm for a signature (2, 1) lattice
WARNING: the output's weyl vector is not implemented
EXAMPLES::
sage: from weilrep import *
sage: x = var('x')
sage: K.<sqrt13> = NumberField(x * x - 13)
sage: HMF(K).eisenstein_series(2, 15).hz_pullback(4 - sqrt13)
1 + 24*q + O(q^2)
"""
K = self.base_field()
mu = K(mu)
nn = mu.norm()
tt = mu.trace()
if tt <= 0 or nn <= 0:
raise ValueError(
'You called hz_pullback with a number that is not totally-positive!'
)
d = K.discriminant()
a = isqrt((tt * tt - 4 * nn) / d)
h = self.fourier_expansion()
t, = PowerSeriesRing(QQ, 't').gens()
d = K.discriminant()
prec = floor(h.prec() / (tt / 2 + 2 * a / sqrt(d)))
if d % 4:
f = sum([
p[n] * t**((i * tt + n * a) / 2)
for i, p in enumerate(h.list()) for n in p.exponents()
]) + O(t**prec)
else:
f = sum([
p[n] * t**((i * tt + 2 * n * a) / 2)
for i, p in enumerate(h.list()) for n in p.exponents()
]) + O(t**prec)
return OrthogonalModularFormLorentzian(self.weight(),
WeilRep(matrix([[-2 * nn]])),
f,
scale=self.scale(),
weylvec=vector([0]),
qexp_representation='shimura')
def eis_G(a, b, N, k, Q=None, t=1, prec=20):
if Q == None:
Q = PowerSeriesRing(QQ, 'q')
R = Q.base_ring()
q = Q.gen()
a = ZZ(a % N)
b = ZZ(b % N)
s = 0
if k == 1:
if a == 0 and not b == 0:
s = QQ(1) / QQ(2) - QQ(b % N) / QQ(N)
elif b == 0 and not a == 0:
s = QQ(1) / QQ(2) - QQ(a % N) / QQ(N)
elif k > 1:
if b == 0:
s = -N**(k - 1) * ber_pol(QQ(a % N) / QQ(N), k) / QQ(k)
#If a == 0 or b ==0 the loop has to start at 1
starta, startb = 0, 0
if a == 0:
starta = 1
if b == 0:
startb = 1
for v in srange(starta, (prec / t + a) / N):
for w in srange(startb, (prec / t / abs((-a + v * N)) + b) / N + 1):
s += q**(t * (a + v * N) * (b + w * N)) * (a + v * N)**(k - 1)
if (-a + v * N) > 0 and (-b + w * N) > 0:
s += (-1)**k * q**(t * (-a + v * N) *
(-b + w * N)) * (-a + v * N)**(k - 1)
return s + O(q**floor(prec))
def eis_H(a, b, N, k, Q=None, t=1, prec=10):
if Q == None:
Q = PowerSeriesRing(CyclotomicField(N), 'q')
R = Q.base_ring()
zetaN = R.zeta(N)
q = Q.gen()
a = ZZ(a % N)
b = ZZ(b % N)
s = 0
if k == 1:
if a == 0 and not b == 0:
s = -QQ(1) / QQ(2) * (1 + zetaN**b) / (1 - zetaN**b)
elif b == 0 and not a == 0:
s = -QQ(1) / QQ(2) * (1 + zetaN**a) / (1 - zetaN**a)
elif a != 0 and b != 0:
s = -QQ(1) / QQ(2) * ((1 + zetaN**a) / (1 - zetaN**a) +
(1 + zetaN**b) / (1 - zetaN**b))
elif k > 1:
s = hurwitz_hat(-b, N, 1 - k, zetaN)
for m in srange(1, prec / t):
for n in srange(1, prec / t / m + 1):
s += (zetaN**(-a * m - b * n) +
(-1)**k * zetaN**(a * m + b * n)) * n**(k - 1) * q**(m * n)
return s + O(q**floor(prec))
def pad(self, target_param_level):
"""
When constructed the q-expansions are in the default parameter $q_N$,
where $N$ is the level of the form. When taking products, the
parameters should be in $q_{N'}$, where $N'$ is the target level.
This helper function peforms that renormalization by padding with zeros.
"""
try:
assert (target_param_level % self.param_level == 0)
except AssertionError:
print(
"target parameter level should be a multiple of current parameter level"
)
return
shift = int(target_param_level / self.param_level)
R = self.series.base_ring()
Q = PowerSeriesRing(R, 'q' + str(target_param_level))
qN = Q.gen()
s = 0
for i in range(self.series.prec() * shift):
if i % shift == 0:
s += self.series[int(i / shift)] * qN**i
else:
s += 0 * qN**i
s += O(qN**(self.series.prec() * shift + shift - 1))
self.series = s
self.param_level = target_param_level
def J_inv_ZZ(self):
r"""
Return the rational Fourier expansion of ``J_inv``,
where the parameter ``d`` is replaced by ``1``.
This is the main function used to determine all Fourier expansions!
.. NOTE:
The Fourier expansion of ``J_inv`` for ``d!=1``
is given by ``J_inv_ZZ(q/d)``.
.. TODO:
The functions that are used in this implementation are
products of hypergeometric series with other, elementary,
functions. Implement them and clean up this representation.
EXAMPLES::
sage: from sage.modular.modform_hecketriangle.series_constructor import MFSeriesConstructor
sage: MFSeriesConstructor(prec=3).J_inv_ZZ()
q^-1 + 31/72 + 1823/27648*q + O(q^2)
sage: MFSeriesConstructor(group=5, prec=3).J_inv_ZZ()
q^-1 + 79/200 + 42877/640000*q + O(q^2)
sage: MFSeriesConstructor(group=5, prec=3).J_inv_ZZ().parent()
Laurent Series Ring in q over Rational Field
sage: MFSeriesConstructor(group=infinity, prec=3).J_inv_ZZ()
q^-1 + 3/8 + 69/1024*q + O(q^2)
"""
F1 = lambda a, b: self._series_ring([ZZ(0)] + [
rising_factorial(a, k) * rising_factorial(b, k) /
(ZZ(k).factorial())**2 * sum(
ZZ(1) / (a + j) + ZZ(1) / (b + j) - ZZ(2) / ZZ(1 + j)
for j in range(ZZ(0), ZZ(k)))
for k in range(ZZ(1), ZZ(self._prec + 1))
], ZZ(self._prec + 1))
F = lambda a, b, c: self._series_ring([
rising_factorial(a, k) * rising_factorial(b, k) / rising_factorial(
c, k) / ZZ(k).factorial()
for k in range(ZZ(0), ZZ(self._prec + 1))
], ZZ(self._prec + 1))
a = self._group.alpha()
b = self._group.beta()
Phi = F1(a, b) / F(a, b, ZZ(1))
q = self._series_ring.gen()
# the current implementation of power series reversion is slow
# J_inv_ZZ = ZZ(1) / ((q*Phi.exp()).reverse())
temp_f = (q * Phi.exp()).polynomial()
new_f = temp_f.revert_series(temp_f.degree() + 1)
J_inv_ZZ = ZZ(1) / (new_f + O(q**(temp_f.degree() + 1)))
return J_inv_ZZ
def __init__(self, f, x0, singular_data, order=None):
r"""Initialize a PuiseuxTSeries using a set of :math:`\pi = \{\tau\}`
data.
Parameters
----------
f, x, y : polynomial
A plane algebraic curve.
x0 : complex
The x-center of the Puiseux series expansion.
singular_data : list
The output of :func:`singular`.
t : variable
The variable in which the Puiseux t series is represented.
"""
R = f.parent()
x, y = R.gens()
extension_polynomial, xpart, ypart = singular_data
L = LaurentSeriesRing(ypart.base_ring(), 't')
t = L.gen()
self.f = f
self.t = t
self._xpart = xpart
self._ypart = ypart
# store x-part attributes. handle the centered at infinity case
self.x0 = x0
if x0 == infinity:
x0 = QQ(0)
self.center = x0
# extract and store information about the x-part of the puiseux series
xpart = xpart(t, 0)
xpartshift = xpart - x0
ramification_index, xcoefficient = xpartshift.laurent_polynomial(
).dict().popitem()
self.xcoefficient = xcoefficient
self.ramification_index = QQ(ramification_index).numerator()
self.xpart = xpart
# extract and store information about the y-part of the puiseux series
self.ypart = L(ypart(t, 0))
self._initialize_extension(extension_polynomial)
# determine the initial order. See the order property
val = L(ypart(t, O(t))).prec()
self._singular_order = 0 if val == infinity else val
self._regular_order = self._p.degree(x)
# extend to have at least two elements
self.extend(nterms=1)
# the curve, x-part, and terms output by puiseux make the puiseux
# series unique. any mutability only adds terms
self.__parent = self.ypart.parent()
self._hash = hash((self.f, self.xpart, self.ypart))
def a(offset, f):
if not f:
return O(q**f.prec())
val = f.valuation()
prec = f.prec()
return (q**val *
R([(i + offset) * f[i]
for i in range(val, prec)])).add_bigoh(prec -
floor(offset))
def eis_E(cv, dv, N, k, Q=None, param_level=1, prec=10):
r"""
Computes the coefficient of the Eisenstein series for $\Gamma(N)$.
Not intended to be called by user.
INPUT:
- cv - int, the first coordinate of the vector determining the \Gamma(N)
Eisenstein series
- dv - int, the second coordinate of the vector determining the \Gamma(N)
Eisenstein series
- N - int, the level of the Eisenstein series to be computed
- k - int, the weight of the Eisenstein seriess to be computed
- Q - power series ring, the ring containing the q-expansion to be computed
- param_level - int, the parameter of the returned series will be
q_{param_level}
- prec - int, the precision. The series in q_{param_level} will be truncated
after prec coefficients
OUTPUT:
- an element of the ring Q, which is the Fourier expansion of the Eisenstein
series
"""
if Q == None:
Q = PowerSeriesRing(CyclotomicField(N), 'q')
R = Q.base_ring()
zetaN = R.zeta(N)
q = Q.gen()
cv = cv % N
dv = dv % N
#if dv == 0 and cv == 0 and k == 2:
# raise ValueError("E_2 is not a modular form")
if k == 1:
if cv == 0 and dv == 0:
raise ValueError("that shouldn't have happened...")
elif cv == 0 and dv != 0:
s = QQ(1) / QQ(2) * (1 + zetaN**dv) / (1 - zetaN**dv)
elif cv != 0:
s = QQ(1) / QQ(2) - QQ(cv) / QQ(N) + floor(QQ(cv) / QQ(N))
elif k > 1:
if cv == 0:
s = hurwitz_hat(QQ(dv), QQ(N), 1 - k, zetaN)
else:
s = 0
for n1 in xrange(1, prec): # this is n/m in DS
for n2 in xrange(1, prec / n1 + 1): # this is m in DS
if Mod(n1, N) == Mod(cv, N):
s += n2**(k - 1) * zetaN**(dv * n2) * q**(n1 * n2)
if Mod(n1, N) == Mod(-cv, N):
s += (-1)**k * n2**(k - 1) * zetaN**(-dv * n2) * q**(n1 * n2)
return s + O(q**floor(prec))
def _compute_nth_coeff(self, n, twist=None):
r"""
Computes the coefficient of T^n.
"""
#TODO: Check that n is not too big
#TODO implement twist
Phis = self._Phis
p = Phis.parent().prime()
if n == 0:
return sum(
[self._basic_integral(a, 0, twist) for a in range(1, p)])
p_prec, var_prec = Phis.precision_absolute()
max_j = Phis.parent().coefficient_module().length_of_moments(p_prec)
ans_prec = max_j - (n / (p - 1)).floor() - min(
max_j, n) - (max_j / p).floor()
if ans_prec == 0:
return self._coefficient_ring(0)
#prec = self._Phis.parent()#precision_absolute()[0] #Not quite right, probably
#print "@@@@n =", n, "prec =", prec
cjns = list(logp_binom(n, p, max_j + 1))
#print cjns
teich = Phis.parent().base_ring().base_ring().teichmuller
#Next line should work but loses precision!!!
ans = sum([
cjns[j] *
sum([((~teich(a))**j) * self._basic_integral(a, j, twist)
for a in range(1, p)])
for j in range(1, min(max_j, len(cjns)))
])
#Instead do this messed up thing
w = ans.parent().gen()
#ans = 0*w
#for j in range(1,min(max_j, len(cjns))):
# ans_term = [0*w] * var_prec
# for a in range(1,p):
# term = (((~teich(a)) ** j) * self._basic_integral(a, j, twist)).list()
# for i in range(min(var_prec, len(term))):
# ans_term[i] += term[i]
# ans += cjns[j] * sum([ans_term[i] * w**i for i in range(var_prec)])
#print ans_prec
ans_prec = O(p**ans_prec)
#print ans_prec
#print ans
for i in range(ans.degree() + 1):
ans += ans_prec * w**i
return ans
def eis_F(cv, dv, N, k, Q=None, prec=10, t=1):
"""
Computes the coefficient of the Eisenstein series for $\Gamma(N)$.
Not indented to be called by user.
INPUT:
- cv - int, the first coordinate of the vector determining the \Gamma(N)
Eisenstein series
- dv - int, the second coordinate of the vector determining the \Gamma(N)
Eisenstein series
- N - int, the level of the Eisenstein series to be computed
- k - int, the weight of the Eisenstein seriess to be computed
- Q - power series ring, the ring containing the q-expansion to be computed
- param_level - int, the parameter of the returned series will be
q_{param_level}
- prec - int, the precision. The series in q_{param_level} will be truncated
after prec coefficients
OUTPUT:
- an element of the ring Q, which is the Fourier expansion of the Eisenstein
series
"""
if Q == None:
Q = PowerSeriesRing(CyclotomicField(N), 'q{}'.format(N))
R = Q.base_ring()
zetaN = R.zeta(N)
q = Q.gen()
s = 0
if k == 1:
if cv % N == 0 and dv % N != 0:
s = QQ(1) / QQ(2) * (1 + zetaN**dv) / (1 - zetaN**dv)
elif cv % N != 0:
s = QQ(1) / QQ(2) - QQ(cv) / QQ(N) + floor(QQ(cv) / QQ(N))
elif k > 1:
s = -ber_pol(QQ(cv) / QQ(N) - floor(QQ(cv) / QQ(N)), k) / QQ(k)
for n1 in xrange(1, ceil(prec / QQ(t))): # this is n/m in DS
for n2 in xrange(1,
ceil(prec / QQ(t) / QQ(n1)) + 1): # this is m in DS
if Mod(n1, N) == Mod(cv, N):
s += N**(1 - k) * n1**(k - 1) * zetaN**(dv * n2) * q**(t * n1 *
n2)
if Mod(n1, N) == Mod(-cv, N):
s += (-1)**k * N**(1 - k) * n1**(k - 1) * zetaN**(
-dv * n2) * q**(t * n1 * n2)
return s + O(q**floor(prec))
def apply_triangular_matrix(self, delta):
"""
If self is a q-expansion and q = exp(2*pi*I*tau), then applying a
triangular matrix [[a,b],[0,d]] to tau gives a well-defined
q-expansion as long as the base ring contains zeta_d.
Warning: The correct slash-action would also multiply with det(delta)^k/2 but we carefully avoid that in all applications of apply_triangular_matrix.
"""
R = self.series.base_ring()
a, b, d = delta[0][0], delta[0][1], delta[1][1]
"""
Reduce the fraction a/d
"""
a2, d2 = (a / d).numerator(), (a / d).denominator()
b2, d3 = (b / d).numerator(), (b / d).denominator()
zetad = R.zeta(d3 * self.param_level)
Q = PowerSeriesRing(R, 'q' + str(self.param_level * d2))
qNd = Q.gen()
s = 0
for i in range(self.series.prec()):
s += self.series[i] * zetad**(i * b2) * qNd**(i * a2)
s = s + O(qNd**(self.series.prec()))
s = s * d**(-self.weight)
return QExpansion(self.level * d2, self.weight, s,
self.param_level * d2)
def prune(self, tar_param_level):
"""
Prunes terms from the q-expansion to return a series in the desired
parameter
"""
try:
assert (self.param_level % tar_param_level == 0)
except AssertionError:
print(
"target parameter level should be a divsor of current parameter level"
)
return
R = self.series.base_ring()
Q = PowerSeriesRing(R, 'q' + str(tar_param_level))
q = Q.gen()
s = 0
for i in range(self.series.prec() * tar_param_level //
self.param_level):
s += self.series[i * (self.param_level // tar_param_level)] * q**i
s += O(q**(self.series.prec() * tar_param_level // self.param_level))
self.series = s
self.param_level = tar_param_level
def product_space(chi, k, weights=False, base_ring=None, verbose=False):
r"""
Computes all eisenstein series, and products of pairs of eisenstein series
of lower weight, lying in the space of modular forms of weight $k$ and
nebentypus $\chi$.
INPUT:
- chi - Dirichlet character, the nebentypus of the target space
- k - an integer, the weight of the target space
OUTPUT:
- a matrix of coefficients of q-expansions, which are the products of
Eisenstein series in M_k(chi).
WARNING: It is only for principal chi that we know that the resulting
space is the whole space of modular forms.
"""
if weights == False:
weights = srange(1, k / 2 + 1)
weight_dict = {}
weight_dict[-1] = [w for w in weights if w % 2] # Odd weights
weight_dict[1] = [w for w in weights if not w % 2] # Even weights
try:
N = chi.modulus()
except AttributeError:
if chi.parent() == ZZ:
N = chi
chi = DirichletGroup(N)[0]
Id = DirichletGroup(1)[0]
if chi(-1) != (-1)**k:
raise ValueError('chi(-1)!=(-1)^k')
sturm = ModularForms(N, k).sturm_bound() + 1
if N > 1:
target_dim = dimension_modular_forms(chi, k)
else:
target_dim = dimension_modular_forms(1, k)
D = DirichletGroup(N)
# product_space should ideally be called over number fields. Over complex
# numbers the exact linear algebra solutions might not exist.
if base_ring == None:
base_ring = CyclotomicField(euler_phi(N))
Q = PowerSeriesRing(base_ring, 'q')
q = Q.gen()
d = len(D)
prim_chars = [phi.primitive_character() for phi in D]
divs = divisors(N)
products = Matrix(base_ring, [])
indexlist = []
rank = 0
if verbose:
print(D)
print('Sturm bound', sturm)
#TODO: target_dim needs refinment in the case of weight 2.
print('Target dimension', target_dim)
for i in srange(0, d): # First character
phi = prim_chars[i]
M1 = phi.conductor()
for j in srange(0, d): # Second character
psi = prim_chars[j]
M2 = psi.conductor()
if not M1 * M2 in divs:
continue
parity = psi(-1) * phi(-1)
for t1 in divs:
if not M1 * M2 * t1 in divs:
continue
#TODO: THE NEXT CONDITION NEEDS TO BE CORRECTED. THIS IS JUST A TEST
if phi.bar() == psi and not (
k == 2): #and i==0 and j==0 and t1==1):
E = eisenstein_series_at_inf(phi, psi, k, sturm, t1,
base_ring).padded_list()
try:
products.T.solve_right(vector(base_ring, E))
except ValueError:
products = Matrix(products.rows() + [E])
indexlist.append([k, i, j, t1])
rank += 1
if verbose:
print('Added ', [k, i, j, t1])
print('Rank is now', rank)
if rank == target_dim:
return products, indexlist
for t in divs:
if not M1 * M2 * t1 * t in divs:
continue
for t2 in divs:
if not M1 * M2 * t1 * t2 * t in divs:
continue
for l in weight_dict[parity]:
if l == 1 and phi.is_odd():
continue
if i == 0 and j == 0 and (l == 2 or l == k - 2):
continue
#TODO: THE NEXT CONDITION NEEDS TO BE REMOVED. THIS IS JUST A TEST
if l == 2 or l == k - 2:
continue
E1 = eisenstein_series_at_inf(
phi, psi, l, sturm, t1 * t, base_ring)
E2 = eisenstein_series_at_inf(
phi**(-1), psi**(-1), k - l, sturm, t2 * t,
base_ring)
#If chi is non-principal this needs to be changed to be something like chi*phi^(-1) instead of phi^(-1)
E = (E1 * E2 + O(q**sturm)).padded_list()
try:
products.T.solve_right(vector(base_ring, E))
except ValueError:
products = Matrix(products.rows() + [E])
indexlist.append([l, k - l, i, j, t1, t2, t])
rank += 1
if verbose:
print('Added ',
[l, k - l, i, j, t1, t2, t])
print('Rank', rank)
if rank == target_dim:
return products, indexlist
return products, indexlist
def e_phipsi(phi,
psi,
k,
t=1,
prec=5,
mat=Matrix([[1, 0], [0, 1]]),
base_ring=None):
r"""
Computes the Eisenstein series attached to the characters psi, phi as
defined on p129 of Diamond--Shurman hit by mat \in \SL_2(\Z)
INPUT:
- psi, a primitive Dirichlet character
- phi, a primitive Dirichlet character
- k, int -- the weight
- t, int -- the shift
- prec, the desired absolute precision, can be fractional. The expansion will be up to O(q_w^(floor(w*prec))), where w is the width of the cusp.
- mat, a matrix - typically taking $i\infty$ to some other cusp
- base_ring, a ring - the ring in which the modular forms are defined
OUTPUT:
- an instance of QExpansion
"""
chi2 = phi
chi1 = psi
try:
assert (QQ(chi1(-1)) * QQ(chi2(-1)) == (-1)**k)
except AssertionError:
print("Parity of characters must match parity of weight")
return None
N1 = chi1.level()
N2 = chi2.level()
N = t * N1 * N2
mat2, Tn = find_correct_matrix(mat, N)
#By construction gamma = mat2 * Tn * mat**(-1) is in Gamma0(N) so if E is our Eisenstein series we can evaluate E|mat = chi(gamma) * E|mat2*Tn.
#Since E|mat2 has a Fourier expansion in qN, the matrix Tn acts as a a twist. The value c_gamma = chi(gamma) is calculated below.
#The point of swapping mat with mat2 is that mat2 satisfies C|N, C>0, (A,N)=1 and N|B and our formulas for the coefficients require this condition.
A, B, C, D = mat2.list()
gamma = mat2 * Tn * mat**(-1)
if base_ring == None:
Nbig = lcm(N, euler_phi(N1 * N2))
base_ring = CyclotomicField(Nbig, 'zeta' + str(Nbig))
zetaNbig = base_ring.gen()
zetaN = zetaNbig**(Nbig / N)
else:
zetaN = base_ring.zeta(N)
g = gcd(t, C)
g1 = gcd(N1 * g, C)
g2 = gcd(N2 * g, C)
#Resulting Eisenstein series will have Fourier expansion in q_N**(g1g2)=q_(N/gcd(N,g1g2))**(g1g2/gcd(N,g1g2))
Q = PowerSeriesRing(base_ring, 'q' + str(N / gcd(N, g1 * g2)))
qN = Q.gen()
zeta_Cg = zetaN**(N / (C / g))
zeta_tmp = zeta_Cg**(inverse_mod(-A * ZZ(t / g), C / g))
#Calculating a few values that will be used repeatedly
chi1bar_vals = [base_ring(chi1.bar()(i)) for i in range(N1)]
cp_list1 = [i for i in range(N1) if gcd(i, N1) == 1]
chi2bar_vals = [base_ring(chi2.bar()(i)) for i in range(N2)]
cp_list2 = [i for i in range(N2) if gcd(i, N2) == 1]
#Computation of the Fourier coefficients
ser = O(qN**floor(prec * N / gcd(N, g1 * g2)))
for n in range(1, ceil(prec * N / QQ(g1 * g2)) + 1):
f = 0
for m in divisors(n) + list(map(lambda x: -x, divisors(n))):
a = 0
for r1 in cp_list1:
b = 0
if ((C / g1) * r1 - QQ(n) / QQ(m)) % ((N1 * g) / g1) == 0:
for r2 in cp_list2:
if ((C / g2) * r2 - m) % ((N2 * g) / g2) == 0:
b += chi2bar_vals[r2] * zeta_tmp**(
(n / m - (C / g1) * r1) / ((N1 * g) / g1) *
(m - (C / g2) * r2) / ((N2 * g) / g2))
a += chi1bar_vals[r1] * b
a *= sign(m) * m**(k - 1)
f += a
f *= zetaN**(inverse_mod(A, N) * (g1 * g2) / C * n)
#The additional factor zetaN**(n*Tn[0][1]) comes from the twist by Tn
ser += zetaN**(n * g1 * g2 * Tn[0][1]) * f * qN**(n * (
(g1 * g2) / gcd(N, g1 * g2)))
#zk(chi1, chi2, c)
gauss1 = base_ring(gauss_sum_corr(chi1.bar()))
gauss2 = base_ring(gauss_sum_corr(chi2.bar()))
zk = 2 * (N2 * t / QQ(g2))**(k - 1) * (t / g) * gauss1 * gauss2
#The following is a temporary fix for a bug in sage
if base_ring == CC:
G = DirichletGroup(N1 * N2, CC)
G[0] #Otherwise chi1.bar().extend(N1*N2).base_extend(CC) or chi2.bar().extend(N1*N2).base_extend(CC) will produce an error
#Constant term
#c_gamma comes from replacing mat with mat2.
c_gamma = chi1bar_vals[gamma[1][1] % N1] * chi2bar_vals[gamma[1][1] % N2]
if N1.divides(C) and ZZ(C / N1).divides(t) and gcd(t / (C / N1), N1) == 1:
ser += (-1)**(k - 1) * gauss2 / QQ(
N2 * (g2 / g)**(k - 1)) * chi1bar_vals[(-A * t / g) % N1] * Sk(
chi1.bar().extend(N1 * N2).base_extend(base_ring) *
chi2.extend(N1 * N2).base_extend(base_ring), k)
elif k == 1 and N2.divides(C) and ZZ(C / N2).divides(t) and gcd(
t / (C / N2), N2) == 1:
ser += gauss1 / QQ(N1) * chi2bar_vals[(-A * t / g) % N2] * Sk(
chi1.extend(N1 * N2).base_extend(base_ring) *
chi2.bar().extend(N1 * N2).base_extend(base_ring), k)
return QExpansion(
N, k,
2 / zk * c_gamma * ser + O(qN**floor(prec * N / gcd(N, g1 * g2))),
N / gcd(N, g1 * g2))
