From: Michael Orlitzky Date: Mon, 22 Jul 2019 20:50:28 +0000 (-0400) Subject: eja: get the characteristic_polynomial() for EJAs working. X-Git-Url: https://gitweb.michael.orlitzky.com/?a=commitdiff_plain;h=9fca3c9328ffbdbdb853a889362f75f4c38a6d7d;p=sage.d.git eja: get the characteristic_polynomial() for EJAs working. --- diff --git a/mjo/eja/euclidean_jordan_algebra.py b/mjo/eja/euclidean_jordan_algebra.py index da1145d..b5cef0a 100644 --- a/mjo/eja/euclidean_jordan_algebra.py +++ b/mjo/eja/euclidean_jordan_algebra.py @@ -69,6 +69,7 @@ class FiniteDimensionalEuclideanJordanAlgebra(FiniteDimensionalAlgebra): True """ + self._charpoly = None # for caching self._rank = rank self._natural_basis = natural_basis self._multiplication_table = mult_table @@ -87,28 +88,52 @@ class FiniteDimensionalEuclideanJordanAlgebra(FiniteDimensionalAlgebra): return fmt.format(self.degree(), self.base_ring()) + def characteristic_polynomial(self): + """ + EXAMPLES: + + The characteristic polynomial in the spin algebra is given in + Alizadeh, Example 11.11:: + + sage: J = JordanSpinEJA(3) + sage: p = J.characteristic_polynomial(); p + X1^2 - X2^2 - X3^2 + (-2*t)*X1 + t^2 + sage: xvec = J.one().vector() + sage: p(*xvec) + t^2 - 2*t + 1 + + """ + if self._charpoly is not None: + return self._charpoly + r = self.rank() n = self.dimension() - names = ['X' + str(i) for i in range(1,n+1)] - R = PolynomialRing(self.base_ring(), names) - J = FiniteDimensionalEuclideanJordanAlgebra(R, - self._multiplication_table, - rank=r) - x0 = J.zero() + # First, compute the basis B... + x0 = self.zero() c = 1 - for g in J.gens(): + for g in self.gens(): x0 += c*g c +=1 if not x0.is_regular(): raise ValueError("don't know a regular element") + V = x0.vector().parent().ambient_vector_space() + V1 = V.span_of_basis( (x0**k).vector() for k in range(self.rank()) ) + B = (V1.basis() + V1.complement().basis()) + + # Now switch to the polynomial rings. + + names = ['X' + str(i) for i in range(1,n+1)] + R = PolynomialRing(self.base_ring(), names) + J = FiniteDimensionalEuclideanJordanAlgebra(R, + self._multiplication_table, + rank=r) + B = [ b.change_ring(R.fraction_field()) for b in B ] # Get the vector space (as opposed to module) so that # span_of_basis() works. - V = x0.vector().parent().ambient_vector_space() - V1 = V.span_of_basis( (x0**k).vector() for k in range(r) ) - B = V1.basis() + V1.complement().basis() + V = J.zero().vector().parent().ambient_vector_space() W = V.span_of_basis(B) def e(k): @@ -123,16 +148,41 @@ class FiniteDimensionalEuclideanJordanAlgebra(FiniteDimensionalAlgebra): A_of_x = block_matrix(1, n, (l1 + l2)) xr = W.coordinates((x**r).vector()) a = [] + denominator = A_of_x.det() # This is constant for i in range(n): - A_cols = A.columns() + A_cols = A_of_x.columns() A_cols[i] = xr - numerator = column_matrix(A.base_ring(), A_cols).det() - denominator = A.det() + numerator = column_matrix(A_of_x.base_ring(), A_cols).det() ai = numerator/denominator a.append(ai) - # Note: all entries past the rth should be zero. - return a + # We go to a bit of trouble here to reorder the + # indeterminates, so that it's easier to evaluate the + # characteristic polynomial at x's coordinates and get back + # something in terms of t, which is what we want. + S = PolynomialRing(self.base_ring(),'t') + t = S.gen(0) + S = PolynomialRing(S, R.variable_names()) + t = S(t) + + # We're relying on the theory here to ensure that each entry + # a[i] is indeed back in R, and the added negative signs are + # to make the whole expression sum to zero. + a = [R(-ai) for ai in a] # corresponds to powerx x^0 through x^(r-1) + + # Note: all entries past the rth should be zero. The + # coefficient of the highest power (x^r) is 1, but it doesn't + # appear in the solution vector which contains coefficients + # for the other powers (to make them sum to x^r). + if (r < n): + a[r] = 1 # corresponds to x^r + else: + # When the rank is equal to the dimension, trying to + # assign a[r] goes out-of-bounds. + a.append(1) # corresponds to x^r + + self._charpoly = sum( a[k]*(t**k) for k in range(len(a)) ) + return self._charpoly def inner_product(self, x, y):