예제 #1
0
 def _eval_(self, x, D):  #symbolic value
     D = Integer(D)
     if D % 4 > 1:
         raise ValueError('Not a discriminant')
     f = D.squarefree_part()
     if f % 4 > 1 and not D % 4:
         f *= 4
     m = D // f
     if f != D:
         L = QuadraticLFunction()
         return prod(1 - p**(-x) * kronecker(f, p)
                     for p in prime_divisors(m)) * L(x, f)
     if D == 1:
         return prod(1 - p**(-x) * kronecker(f, p)
                     for p in prime_divisors(m)) * zeta(x)
     try:
         return quadratic_L_function__exact(x, D)
     except TypeError:
         pass
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