def mass__by_Siegel_densities(self,
odd_algorithm="Pall",
even_algorithm="Watson"):
"""
Gives the mass of transformations (det 1 and -1).
WARNING: THIS IS BROKEN RIGHT NOW... =(
Optional Arguments:
- When p > 2 -- odd_algorithm = "Pall" (only one choice for now)
- When p = 2 -- even_algorithm = "Kitaoka" or "Watson"
REFERENCES:
- Nipp's Book "Tables of Quaternary Quadratic Forms".
- Papers of Pall (only for p>2) and Watson (for `p=2` -- tricky!).
- Siegel, Milnor-Hussemoller, Conway-Sloane Paper IV, Kitoaka (all of which
have problems...)
EXAMPLES::
sage: Q = DiagonalQuadraticForm(ZZ, [1,1,1,1])
sage: m = Q.mass__by_Siegel_densities(); m
1/384
sage: m - (2^Q.dim() * factorial(Q.dim()))^(-1)
0
::
sage: Q = DiagonalQuadraticForm(ZZ, [1,1,1])
sage: m = Q.mass__by_Siegel_densities(); m
1/48
sage: m - (2^Q.dim() * factorial(Q.dim()))^(-1)
0
"""
## Setup
n = self.dim()
s = (n - 1) // 2
if n % 2 != 0:
char_d = squarefree_part(2 *
self.det()) ## Accounts for the det as a QF
else:
char_d = squarefree_part(self.det())
## Form the generic zeta product
generic_prod = ZZ(2) * (pi)**(-ZZ(n) * (n + 1) / 4)
##########################################
generic_prod *= (self.det())**(
ZZ(n + 1) / 2) ## ***** This uses the Hessian Determinant ********
##########################################
#print "gp1 = ", generic_prod
generic_prod *= prod([gamma__exact(ZZ(j) / 2) for j in range(1, n + 1)])
#print "\n---", [(ZZ(j)/2, gamma__exact(ZZ(j)/2)) for j in range(1,n+1)]
#print "\n---", prod([gamma__exact(ZZ(j)/2) for j in range(1,n+1)])
#print "gp2 = ", generic_prod
generic_prod *= prod([zeta__exact(ZZ(j)) for j in range(2, 2 * s + 1, 2)])
#print "\n---", [zeta__exact(ZZ(j)) for j in range(2, 2*s+1, 2)]
#print "\n---", prod([zeta__exact(ZZ(j)) for j in range(2, 2*s+1, 2)])
#print "gp3 = ", generic_prod
if (n % 2 == 0):
generic_prod *= quadratic_L_function__exact(n // 2,
ZZ(-1)**(n // 2) * char_d)
#print " NEW = ", ZZ(1) * quadratic_L_function__exact(n/2, (-1)**(n/2) * char_d)
#print
#print "gp4 = ", generic_prod
#print "generic_prod =", generic_prod
## Determine the adjustment factors
adj_prod = ZZ.one()
for p in prime_divisors(2 * self.det()):
## Cancel out the generic factors
p_adjustment = prod([1 - ZZ(p)**(-j) for j in range(2, 2 * s + 1, 2)])
if (n % 2 == 0):
p_adjustment *= (1 - kronecker(
(-1)**(n // 2) * char_d, p) * ZZ(p)**(-n // 2))
#print " EXTRA = ", ZZ(1) * (1 - kronecker((-1)**(n/2) * char_d, p) * ZZ(p)**(-n/2))
#print "Factor to cancel the generic one:", p_adjustment
## Insert the new mass factors
if p == 2:
if even_algorithm == "Kitaoka":
p_adjustment = p_adjustment / self.Kitaoka_mass_at_2()
elif even_algorithm == "Watson":
p_adjustment = p_adjustment / self.Watson_mass_at_2()
else:
raise TypeError(
"There is a problem -- your even_algorithm argument is invalid. Try again. =("
)
else:
if odd_algorithm == "Pall":
p_adjustment = p_adjustment / self.Pall_mass_density_at_odd_prime(
p)
else:
raise TypeError(
"There is a problem -- your optional arguments are invalid. Try again. =("
)
#print "p_adjustment for p =", p, "is", p_adjustment
## Put them together (cumulatively)
adj_prod *= p_adjustment
#print "Cumulative adj_prod =", adj_prod
## Extra adjustment for the case of a 2-dimensional form.
#if (n == 2):
# generic_prod *= 2
## Return the mass
mass = generic_prod * adj_prod
return mass
def mass__by_Siegel_densities(self, odd_algorithm="Pall", even_algorithm="Watson"):
"""
Gives the mass of transformations (det 1 and -1).
WARNING: THIS IS BROKEN RIGHT NOW... =(
Optional Arguments:
- When p > 2 -- odd_algorithm = "Pall" (only one choice for now)
- When p = 2 -- even_algorithm = "Kitaoka" or "Watson"
REFERENCES:
- Nipp's Book "Tables of Quaternary Quadratic Forms".
- Papers of Pall (only for p>2) and Watson (for `p=2` -- tricky!).
- Siegel, Milnor-Hussemoller, Conway-Sloane Paper IV, Kitoaka (all of which
have problems...)
EXAMPLES::
sage: Q = DiagonalQuadraticForm(ZZ, [1,1,1,1])
sage: Q.mass__by_Siegel_densities()
1/384
sage: Q.mass__by_Siegel_densities() - (2^Q.dim() * factorial(Q.dim()))^(-1)
0
::
sage: Q = DiagonalQuadraticForm(ZZ, [1,1,1])
sage: Q.mass__by_Siegel_densities()
1/48
sage: Q.mass__by_Siegel_densities() - (2^Q.dim() * factorial(Q.dim()))^(-1)
0
"""
## Setup
n = self.dim()
s = (n-1) // 2
if n % 2 != 0:
char_d = squarefree_part(2*self.det()) ## Accounts for the det as a QF
else:
char_d = squarefree_part(self.det())
## Form the generic zeta product
generic_prod = ZZ(2) * (pi)**(-ZZ(n) * (n+1) / 4)
##########################################
generic_prod *= (self.det())**(ZZ(n+1)/2) ## ***** This uses the Hessian Determinant ********
##########################################
#print "gp1 = ", generic_prod
generic_prod *= prod([gamma__exact(ZZ(j)/2) for j in range(1,n+1)])
#print "\n---", [(ZZ(j)/2, gamma__exact(ZZ(j)/2)) for j in range(1,n+1)]
#print "\n---", prod([gamma__exact(ZZ(j)/2) for j in range(1,n+1)])
#print "gp2 = ", generic_prod
generic_prod *= prod([zeta__exact(ZZ(j)) for j in range(2, 2*s+1, 2)])
#print "\n---", [zeta__exact(ZZ(j)) for j in range(2, 2*s+1, 2)]
#print "\n---", prod([zeta__exact(ZZ(j)) for j in range(2, 2*s+1, 2)])
#print "gp3 = ", generic_prod
if (n % 2 == 0):
generic_prod *= ZZ(1) * quadratic_L_function__exact(n/2, (-1)**(n/2) * char_d)
#print " NEW = ", ZZ(1) * quadratic_L_function__exact(n/2, (-1)**(n/2) * char_d)
#print
#print "gp4 = ", generic_prod
#print "generic_prod =", generic_prod
## Determine the adjustment factors
adj_prod = 1
for p in prime_divisors(2 * self.det()):
## Cancel out the generic factors
p_adjustment = prod([1 - ZZ(p)**(-j) for j in range(2, 2*s+1, 2)])
if (n % 2 == 0):
p_adjustment *= ZZ(1) * (1 - kronecker((-1)**(n/2) * char_d, p) * ZZ(p)**(-n/2))
#print " EXTRA = ", ZZ(1) * (1 - kronecker((-1)**(n/2) * char_d, p) * ZZ(p)**(-n/2))
#print "Factor to cancel the generic one:", p_adjustment
## Insert the new mass factors
if p == 2:
if even_algorithm == "Kitaoka":
p_adjustment = p_adjustment / self.Kitaoka_mass_at_2()
elif even_algorithm == "Watson":
p_adjustment = p_adjustment / self.Watson_mass_at_2()
else:
raise TypeError("There is a problem -- your even_algorithm argument is invalid. Try again. =(")
else:
if odd_algorithm == "Pall":
p_adjustment = p_adjustment / self.Pall_mass_density_at_odd_prime(p)
else:
raise TypeError("There is a problem -- your optional arguments are invalid. Try again. =(")
#print "p_adjustment for p =", p, "is", p_adjustment
## Put them together (cumulatively)
adj_prod *= p_adjustment
#print "Cumulative adj_prod =", adj_prod
## Extra adjustment for the case of a 2-dimensional form.
#if (n == 2):
# generic_prod *= 2
## Return the mass
mass = generic_prod * adj_prod
return mass