X-Git-Url: http://gitweb.michael.orlitzky.com/?a=blobdiff_plain;f=mjo%2Feja%2Feja_algebra.py;h=fb016462abaef5b05e24defe19810855de4040bd;hb=b558f4e44d9f2c542a7b988f457abccc82a3641c;hp=2bad32c2f500193e4126b7c5e209c0acb3116ede;hpb=f0cabe7c6e37781e4f92c9ba0e0c7413a5f6b939;p=sage.d.git diff --git a/mjo/eja/eja_algebra.py b/mjo/eja/eja_algebra.py index 2bad32c..fb01646 100644 --- a/mjo/eja/eja_algebra.py +++ b/mjo/eja/eja_algebra.py @@ -230,7 +230,6 @@ class FiniteDimensionalEJA(CombinatorialFreeModule): We should compute that an element subalgebra is associative even if we circumvent the element method:: - sage: set_random_seed() sage: J = random_eja(field=QQ,orthonormalize=False) sage: x = J.random_element() sage: A = x.subalgebra_generated_by(orthonormalize=False) @@ -367,7 +366,7 @@ class FiniteDimensionalEJA(CombinatorialFreeModule): if orthonormalize: # Now "self._matrix_span" is the vector space of our - # algebra coordinates. The variables "X1", "X2",... refer + # algebra coordinates. The variables "X0", "X1",... refer # to the entries of vectors in self._matrix_span. Thus to # convert back and forth between the orthonormal # coordinates and the given ones, we need to stick the @@ -432,7 +431,6 @@ class FiniteDimensionalEJA(CombinatorialFreeModule): TESTS:: - sage: set_random_seed() sage: J = random_eja() sage: J(1) Traceback (most recent call last): @@ -457,7 +455,6 @@ class FiniteDimensionalEJA(CombinatorialFreeModule): TESTS:: - sage: set_random_seed() sage: J = random_eja() sage: n = J.dimension() sage: bi = J.zero() @@ -499,7 +496,6 @@ class FiniteDimensionalEJA(CombinatorialFreeModule): Our inner product is "associative," which means the following for a symmetric bilinear form:: - sage: set_random_seed() sage: J = random_eja() sage: x,y,z = J.random_elements(3) sage: (x*y).inner_product(z) == y.inner_product(x*z) @@ -510,7 +506,6 @@ class FiniteDimensionalEJA(CombinatorialFreeModule): Ensure that this is the usual inner product for the algebras over `R^n`:: - sage: set_random_seed() sage: J = HadamardEJA.random_instance() sage: x,y = J.random_elements(2) sage: actual = x.inner_product(y) @@ -523,7 +518,6 @@ class FiniteDimensionalEJA(CombinatorialFreeModule): one). This is in Faraut and Koranyi, and also my "On the symmetry..." paper:: - sage: set_random_seed() sage: J = BilinearFormEJA.random_instance() sage: n = J.dimension() sage: x = J.random_element() @@ -636,7 +630,6 @@ class FiniteDimensionalEJA(CombinatorialFreeModule): The values we've presupplied to the constructors agree with the computation:: - sage: set_random_seed() sage: J = random_eja() sage: J.is_associative() == J._jordan_product_is_associative() True @@ -758,7 +751,6 @@ class FiniteDimensionalEJA(CombinatorialFreeModule): Ensure that we can convert any element back and forth faithfully between its matrix and algebra representations:: - sage: set_random_seed() sage: J = random_eja() sage: x = J.random_element() sage: J(x.to_matrix()) == x @@ -871,7 +863,7 @@ class FiniteDimensionalEJA(CombinatorialFreeModule): sage: J = JordanSpinEJA(3) sage: p = J.characteristic_polynomial_of(); p - X1^2 - X2^2 - X3^2 + (-2*t)*X1 + t^2 + X0^2 - X1^2 - X2^2 + (-2*t)*X0 + t^2 sage: xvec = J.one().to_vector() sage: p(*xvec) t^2 - 2*t + 1 @@ -920,13 +912,13 @@ class FiniteDimensionalEJA(CombinatorialFreeModule): sage: J = HadamardEJA(2) sage: J.coordinate_polynomial_ring() - Multivariate Polynomial Ring in X1, X2... + Multivariate Polynomial Ring in X0, X1... sage: J = RealSymmetricEJA(3,field=QQ,orthonormalize=False) sage: J.coordinate_polynomial_ring() - Multivariate Polynomial Ring in X1, X2, X3, X4, X5, X6... + Multivariate Polynomial Ring in X0, X1, X2, X3, X4, X5... """ - var_names = tuple( "X%d" % z for z in range(1, self.dimension()+1) ) + var_names = tuple( "X%d" % z for z in range(self.dimension()) ) return PolynomialRing(self.base_ring(), var_names) def inner_product(self, x, y): @@ -948,7 +940,6 @@ class FiniteDimensionalEJA(CombinatorialFreeModule): Our inner product is "associative," which means the following for a symmetric bilinear form:: - sage: set_random_seed() sage: J = random_eja() sage: x,y,z = J.random_elements(3) sage: (x*y).inner_product(z) == y.inner_product(x*z) @@ -959,7 +950,6 @@ class FiniteDimensionalEJA(CombinatorialFreeModule): Ensure that this is the usual inner product for the algebras over `R^n`:: - sage: set_random_seed() sage: J = HadamardEJA.random_instance() sage: x,y = J.random_elements(2) sage: actual = x.inner_product(y) @@ -972,7 +962,6 @@ class FiniteDimensionalEJA(CombinatorialFreeModule): one). This is in Faraut and Koranyi, and also my "On the symmetry..." paper:: - sage: set_random_seed() sage: J = BilinearFormEJA.random_instance() sage: n = J.dimension() sage: x = J.random_element() @@ -1200,7 +1189,6 @@ class FiniteDimensionalEJA(CombinatorialFreeModule): The identity element acts like the identity, regardless of whether or not we orthonormalize:: - sage: set_random_seed() sage: J = random_eja() sage: x = J.random_element() sage: J.one()*x == x and x*J.one() == x @@ -1212,7 +1200,6 @@ class FiniteDimensionalEJA(CombinatorialFreeModule): :: - sage: set_random_seed() sage: J = random_eja(field=QQ, orthonormalize=False) sage: x = J.random_element() sage: J.one()*x == x and x*J.one() == x @@ -1226,7 +1213,6 @@ class FiniteDimensionalEJA(CombinatorialFreeModule): regardless of the base field and whether or not we orthonormalize:: - sage: set_random_seed() sage: J = random_eja() sage: actual = J.one().operator().matrix() sage: expected = matrix.identity(J.base_ring(), J.dimension()) @@ -1241,7 +1227,6 @@ class FiniteDimensionalEJA(CombinatorialFreeModule): :: - sage: set_random_seed() sage: J = random_eja(field=QQ, orthonormalize=False) sage: actual = J.one().operator().matrix() sage: expected = matrix.identity(J.base_ring(), J.dimension()) @@ -1257,7 +1242,6 @@ class FiniteDimensionalEJA(CombinatorialFreeModule): Ensure that the cached unit element (often precomputed by hand) agrees with the computed one:: - sage: set_random_seed() sage: J = random_eja() sage: cached = J.one() sage: J.one.clear_cache() @@ -1266,7 +1250,6 @@ class FiniteDimensionalEJA(CombinatorialFreeModule): :: - sage: set_random_seed() sage: J = random_eja(field=QQ, orthonormalize=False) sage: cached = J.one() sage: J.one.clear_cache() @@ -1379,7 +1362,6 @@ class FiniteDimensionalEJA(CombinatorialFreeModule): Every algebra decomposes trivially with respect to its identity element:: - sage: set_random_seed() sage: J = random_eja() sage: J0,J5,J1 = J.peirce_decomposition(J.one()) sage: J0.dimension() == 0 and J5.dimension() == 0 @@ -1392,7 +1374,6 @@ class FiniteDimensionalEJA(CombinatorialFreeModule): elements in the two subalgebras are the projections onto their respective subspaces of the superalgebra's identity element:: - sage: set_random_seed() sage: J = random_eja() sage: x = J.random_element() sage: if not J.is_trivial(): @@ -1518,6 +1499,64 @@ class FiniteDimensionalEJA(CombinatorialFreeModule): for idx in range(count) ) + def operator_polynomial_matrix(self): + r""" + Return the matrix of polynomials (over this algebra's + :meth:`coordinate_polynomial_ring`) that, when evaluated at + the basis coordinates of an element `x`, produces the basis + representation of `L_{x}`. + + SETUP:: + + sage: from mjo.eja.eja_algebra import (HadamardEJA, + ....: JordanSpinEJA) + + EXAMPLES:: + + sage: J = HadamardEJA(4) + sage: L_x = J.operator_polynomial_matrix() + sage: L_x + [X0 0 0 0] + [ 0 X1 0 0] + [ 0 0 X2 0] + [ 0 0 0 X3] + sage: x = J.one() + sage: d = zip(J.coordinate_polynomial_ring().gens(), x.to_vector()) + sage: L_x.subs(dict(d)) + [1 0 0 0] + [0 1 0 0] + [0 0 1 0] + [0 0 0 1] + + :: + + sage: J = JordanSpinEJA(4) + sage: L_x = J.operator_polynomial_matrix() + sage: L_x + [X0 X1 X2 X3] + [X1 X0 0 0] + [X2 0 X0 0] + [X3 0 0 X0] + sage: x = J.one() + sage: d = zip(J.coordinate_polynomial_ring().gens(), x.to_vector()) + sage: L_x.subs(dict(d)) + [1 0 0 0] + [0 1 0 0] + [0 0 1 0] + [0 0 0 1] + + """ + R = self.coordinate_polynomial_ring() + + def L_x_i_j(i,j): + # From a result in my book, these are the entries of the + # basis representation of L_x. + return sum( v*self.monomial(k).operator().matrix()[i,j] + for (k,v) in enumerate(R.gens()) ) + + n = self.dimension() + return matrix(R, n, n, L_x_i_j) + @cached_method def _charpoly_coefficients(self): r""" @@ -1533,7 +1572,6 @@ class FiniteDimensionalEJA(CombinatorialFreeModule): The theory shows that these are all homogeneous polynomials of a known degree:: - sage: set_random_seed() sage: J = random_eja() sage: all(p.is_homogeneous() for p in J._charpoly_coefficients()) True @@ -1541,16 +1579,9 @@ class FiniteDimensionalEJA(CombinatorialFreeModule): """ n = self.dimension() R = self.coordinate_polynomial_ring() - vars = R.gens() F = R.fraction_field() - def L_x_i_j(i,j): - # From a result in my book, these are the entries of the - # basis representation of L_x. - return sum( vars[k]*self.monomial(k).operator().matrix()[i,j] - for k in range(n) ) - - L_x = matrix(F, n, n, L_x_i_j) + L_x = self.operator_polynomial_matrix() r = None if self.rank.is_in_cache(): @@ -1631,7 +1662,6 @@ class FiniteDimensionalEJA(CombinatorialFreeModule): positive integer rank, unless the algebra is trivial in which case its rank will be zero:: - sage: set_random_seed() sage: J = random_eja() sage: r = J.rank() sage: r in ZZ @@ -1642,7 +1672,6 @@ class FiniteDimensionalEJA(CombinatorialFreeModule): Ensure that computing the rank actually works, since the ranks of all simple algebras are known and will be cached by default:: - sage: set_random_seed() # long time sage: J = random_eja() # long time sage: cached = J.rank() # long time sage: J.rank.clear_cache() # long time @@ -1771,7 +1800,7 @@ class RationalBasisEJA(FiniteDimensionalEJA): sage: J = JordanSpinEJA(3) sage: J._charpoly_coefficients() - (X1^2 - X2^2 - X3^2, -2*X1) + (X0^2 - X1^2 - X2^2, -2*X0) sage: a0 = J._charpoly_coefficients()[0] sage: J.base_ring() Algebraic Real Field @@ -1817,7 +1846,6 @@ class ConcreteEJA(FiniteDimensionalEJA): Our basis is normalized with respect to the algebra's inner product, unless we specify otherwise:: - sage: set_random_seed() sage: J = ConcreteEJA.random_instance() sage: all( b.norm() == 1 for b in J.gens() ) True @@ -1828,7 +1856,6 @@ class ConcreteEJA(FiniteDimensionalEJA): natural->EJA basis representation is an isometry and within the EJA the operator is self-adjoint by the Jordan axiom:: - sage: set_random_seed() sage: J = ConcreteEJA.random_instance() sage: x = J.random_element() sage: x.operator().is_self_adjoint() @@ -1902,11 +1929,11 @@ class ConcreteEJA(FiniteDimensionalEJA): return eja_class.random_instance(max_dimension, *args, **kwargs) -class MatrixEJA(FiniteDimensionalEJA): +class HermitianMatrixEJA(FiniteDimensionalEJA): @staticmethod def _denormalized_basis(A): """ - Returns a basis for the space of complex Hermitian n-by-n matrices. + Returns a basis for the given Hermitian matrix space. Why do we embed these? Basically, because all of numerical linear algebra assumes that you're working with vectors consisting of `n` @@ -1919,41 +1946,37 @@ class MatrixEJA(FiniteDimensionalEJA): sage: from mjo.hurwitz import (ComplexMatrixAlgebra, ....: QuaternionMatrixAlgebra, ....: OctonionMatrixAlgebra) - sage: from mjo.eja.eja_algebra import MatrixEJA + sage: from mjo.eja.eja_algebra import HermitianMatrixEJA TESTS:: - sage: set_random_seed() sage: n = ZZ.random_element(1,5) sage: A = MatrixSpace(QQ, n) - sage: B = MatrixEJA._denormalized_basis(A) + sage: B = HermitianMatrixEJA._denormalized_basis(A) sage: all( M.is_hermitian() for M in B) True :: - sage: set_random_seed() sage: n = ZZ.random_element(1,5) sage: A = ComplexMatrixAlgebra(n, scalars=QQ) - sage: B = MatrixEJA._denormalized_basis(A) + sage: B = HermitianMatrixEJA._denormalized_basis(A) sage: all( M.is_hermitian() for M in B) True :: - sage: set_random_seed() sage: n = ZZ.random_element(1,5) sage: A = QuaternionMatrixAlgebra(n, scalars=QQ) - sage: B = MatrixEJA._denormalized_basis(A) + sage: B = HermitianMatrixEJA._denormalized_basis(A) sage: all( M.is_hermitian() for M in B ) True :: - sage: set_random_seed() sage: n = ZZ.random_element(1,5) sage: A = OctonionMatrixAlgebra(n, scalars=QQ) - sage: B = MatrixEJA._denormalized_basis(A) + sage: B = HermitianMatrixEJA._denormalized_basis(A) sage: all( M.is_hermitian() for M in B ) True @@ -2058,7 +2081,7 @@ class MatrixEJA(FiniteDimensionalEJA): self.rank.set_cache(matrix_space.nrows()) self.one.set_cache( self(matrix_space.one()) ) -class RealSymmetricEJA(MatrixEJA, RationalBasisEJA, ConcreteEJA): +class RealSymmetricEJA(HermitianMatrixEJA, RationalBasisEJA, ConcreteEJA): """ The rank-n simple EJA consisting of real symmetric n-by-n matrices, the usual symmetric Jordan product, and the trace inner @@ -2091,7 +2114,6 @@ class RealSymmetricEJA(MatrixEJA, RationalBasisEJA, ConcreteEJA): The dimension of this algebra is `(n^2 + n) / 2`:: - sage: set_random_seed() sage: d = RealSymmetricEJA._max_random_instance_dimension() sage: n = RealSymmetricEJA._max_random_instance_size(d) sage: J = RealSymmetricEJA(n) @@ -2100,7 +2122,6 @@ class RealSymmetricEJA(MatrixEJA, RationalBasisEJA, ConcreteEJA): The Jordan multiplication is what we think it is:: - sage: set_random_seed() sage: J = RealSymmetricEJA.random_instance() sage: x,y = J.random_elements(2) sage: actual = (x*y).to_matrix() @@ -2152,7 +2173,7 @@ class RealSymmetricEJA(MatrixEJA, RationalBasisEJA, ConcreteEJA): -class ComplexHermitianEJA(MatrixEJA, RationalBasisEJA, ConcreteEJA): +class ComplexHermitianEJA(HermitianMatrixEJA, RationalBasisEJA, ConcreteEJA): """ The rank-n simple EJA consisting of complex Hermitian n-by-n matrices over the real numbers, the usual symmetric Jordan product, @@ -2192,7 +2213,6 @@ class ComplexHermitianEJA(MatrixEJA, RationalBasisEJA, ConcreteEJA): The dimension of this algebra is `n^2`:: - sage: set_random_seed() sage: d = ComplexHermitianEJA._max_random_instance_dimension() sage: n = ComplexHermitianEJA._max_random_instance_size(d) sage: J = ComplexHermitianEJA(n) @@ -2201,7 +2221,6 @@ class ComplexHermitianEJA(MatrixEJA, RationalBasisEJA, ConcreteEJA): The Jordan multiplication is what we think it is:: - sage: set_random_seed() sage: J = ComplexHermitianEJA.random_instance() sage: x,y = J.random_elements(2) sage: actual = (x*y).to_matrix() @@ -2253,7 +2272,7 @@ class ComplexHermitianEJA(MatrixEJA, RationalBasisEJA, ConcreteEJA): return cls(n, **kwargs) -class QuaternionHermitianEJA(MatrixEJA, RationalBasisEJA, ConcreteEJA): +class QuaternionHermitianEJA(HermitianMatrixEJA, RationalBasisEJA, ConcreteEJA): r""" The rank-n simple EJA consisting of self-adjoint n-by-n quaternion matrices, the usual symmetric Jordan product, and the @@ -2278,7 +2297,6 @@ class QuaternionHermitianEJA(MatrixEJA, RationalBasisEJA, ConcreteEJA): The dimension of this algebra is `2*n^2 - n`:: - sage: set_random_seed() sage: d = QuaternionHermitianEJA._max_random_instance_dimension() sage: n = QuaternionHermitianEJA._max_random_instance_size(d) sage: J = QuaternionHermitianEJA(n) @@ -2287,7 +2305,6 @@ class QuaternionHermitianEJA(MatrixEJA, RationalBasisEJA, ConcreteEJA): The Jordan multiplication is what we think it is:: - sage: set_random_seed() sage: J = QuaternionHermitianEJA.random_instance() sage: x,y = J.random_elements(2) sage: actual = (x*y).to_matrix() @@ -2343,7 +2360,7 @@ class QuaternionHermitianEJA(MatrixEJA, RationalBasisEJA, ConcreteEJA): n = ZZ.random_element(max_size + 1) return cls(n, **kwargs) -class OctonionHermitianEJA(MatrixEJA, RationalBasisEJA, ConcreteEJA): +class OctonionHermitianEJA(HermitianMatrixEJA, RationalBasisEJA, ConcreteEJA): r""" SETUP:: @@ -2660,7 +2677,6 @@ class BilinearFormEJA(RationalBasisEJA, ConcreteEJA): matrix. We opt not to orthonormalize the basis, because if we did, we would have to normalize the `s_{i}` in a similar manner:: - sage: set_random_seed() sage: n = ZZ.random_element(5) sage: M = matrix.random(QQ, max(0,n-1), algorithm='unimodular') sage: B11 = matrix.identity(QQ,1) @@ -2822,7 +2838,6 @@ class JordanSpinEJA(BilinearFormEJA): Ensure that we have the usual inner product on `R^n`:: - sage: set_random_seed() sage: J = JordanSpinEJA.random_instance() sage: x,y = J.random_elements(2) sage: actual = x.inner_product(y) @@ -2943,7 +2958,6 @@ class CartesianProductEJA(FiniteDimensionalEJA): The Jordan product is inherited from our factors and implemented by our CombinatorialFreeModule Cartesian product superclass:: - sage: set_random_seed() sage: J1 = HadamardEJA(2) sage: J2 = RealSymmetricEJA(2) sage: J = cartesian_product([J1,J2]) @@ -3080,7 +3094,6 @@ class CartesianProductEJA(FiniteDimensionalEJA): The cached unit element is the same one that would be computed:: - sage: set_random_seed() # long time sage: J1 = random_eja() # long time sage: J2 = random_eja() # long time sage: J = cartesian_product([J1,J2]) # long time @@ -3299,7 +3312,6 @@ class CartesianProductEJA(FiniteDimensionalEJA): The answer never changes:: - sage: set_random_seed() sage: J1 = random_eja() sage: J2 = random_eja() sage: J = cartesian_product([J1,J2]) @@ -3389,7 +3401,6 @@ class CartesianProductEJA(FiniteDimensionalEJA): The answer never changes:: - sage: set_random_seed() sage: J1 = random_eja() sage: J2 = random_eja() sage: J = cartesian_product([J1,J2]) @@ -3402,7 +3413,6 @@ class CartesianProductEJA(FiniteDimensionalEJA): produce the identity map, and mismatching them should produce the zero map:: - sage: set_random_seed() sage: J1 = random_eja() sage: J2 = random_eja() sage: J = cartesian_product([J1,J2]) @@ -3507,7 +3517,6 @@ def random_eja(max_dimension=None, *args, **kwargs): TESTS:: - sage: set_random_seed() sage: n = ZZ.random_element(1,5) sage: J = random_eja(max_dimension=n, field=QQ, orthonormalize=False) sage: J.dimension() <= n @@ -3533,3 +3542,129 @@ def random_eja(max_dimension=None, *args, **kwargs): # if the sub-call also Decides on a cartesian product. J2 = random_eja(new_max_dimension, *args, **kwargs) return cartesian_product([J1,J2]) + + +class ComplexSkewHermitianEJA(RationalBasisEJA): + r""" + The EJA described in Faraut and Koranyi's Exercise III.1.b. + """ + @staticmethod + def _denormalized_basis(A): + """ + SETUP:: + + sage: from mjo.hurwitz import ComplexMatrixAlgebra + sage: from mjo.eja.eja_algebra import ComplexSkewHermitianEJA + + TESTS:: + + sage: n = ZZ.random_element(1,2) + sage: A = ComplexMatrixAlgebra(2*n, scalars=QQ) + sage: B = ComplexSkewHermitianEJA._denormalized_basis(A) + sage: all( M.is_skew_hermitian() for M in B) + True + + """ + es = A.entry_algebra_gens() + gen = lambda A,m: A.monomial(m) + + basis = [] + + # The size of the blocks. We're going to treat these thing as + # 2x2 block matrices, + # + # [ x1 x2 ] + # [ -x2^* x1-conj ] + # + # where x1 is skew-Hermitian and x2 is symmetric. + # + m = A.nrows()/2 + + # We only loop through the top half of the matrix, because the + # bottom can be constructed from the top. + for i in range(m): + + # First do the top-left block, which is skew-Hermitian. + # We can compute the bottom-right block in the process. + for j in range(i+1): + if i == j: + # Top-left block's entry. + E_ii = gen(A, (i,j,es[1])) + + # Bottom-right block's entry. + E_ii += gen(A, (i+m,j+m,es[1])).conjugate() + basis.append(E_ii) + else: + for e in es: + # Top-left block's entry. + E_ij = gen(A, (i,j,e)) + E_ij -= E_ij.conjugate_transpose() + + # Bottom-right block's entry. + F_ij = gen(A, (i+m,j+m,e)).conjugate() + F_ij -= F_ij.conjugate_transpose() + + basis.append(E_ij + F_ij) + + # Now do the top-right block, which is symmetric, and compute + # the bottom-left block along the way. + for j in range(m,i+m+1): + if (i+m) == j: + # A symmetric (not Hermitian!) complex matrix can + # have both real and complex entries on its + # diagonal. + for e in es: + # Top-right block's entry. + E_ii = gen(A, (i,j,e)) + + # Bottom-left block's entry. + E_ii -= gen(A, (i-m,j-m,e)).conjugate() + basis.append(E_ii) + else: + for e in es: + # Top-right block's entry. BEWARE! We're not + # reflecting across the main diagonal as in + # (i,j)~(j,i). We're only reflecting across + # the diagonal for the top-right block. + E_ij = gen(A, (i,j,e)) + + # Shift it back to non-offset coords, transpose, + # and put it back: + # + # (i,j) -> (i,j-m) -> (j-m, i) -> (j-m, i+m) + E_ij += gen(A, (j-m,i+m,e)) + + # Bottom-left's block's below-diagonal entry. + # Just shift the top-right coords down m and + # left m. + F_ij = -gen(A, (i+m,j-m,e)).conjugate() + F_ij += -gen(A, (j,i,e)).conjugate() + + basis.append(E_ij + F_ij) + + return tuple( basis ) + + + def __init__(self, n, field=AA, **kwargs): + # New code; always check the axioms. + if "check_axioms" not in kwargs: kwargs["check_axioms"] = False + + from mjo.hurwitz import ComplexMatrixAlgebra + A = ComplexMatrixAlgebra(2*n, scalars=field) + + I_n = matrix.identity(ZZ, n) + J = matrix.block(ZZ, 2, 2, (0, I_n, -I_n, 0), subdivide=False) + J = A.from_list(J.rows()) + + def jordan_product(X,Y): + return (X*J*Y + Y*J*X)/2 + + def inner_product(X,Y): + return (X*Y.conjugate_transpose()).trace().real() + + super().__init__(self._denormalized_basis(A), + jordan_product, + inner_product, + field=field, + matrix_space=A, + **kwargs)