+ In the future, this can be extended to a complete system of
+ orthogonal idempotents.
+
+ INPUT:
+
+ - ``c`` -- an idempotent of this algebra.
+
+ OUTPUT:
+
+ A triple (J0, J5, J1) containing two subalgebras and one subspace
+ of this algebra,
+
+ - ``J0`` -- the algebra on the eigenspace of ``c.operator()``
+ corresponding to the eigenvalue zero.
+
+ - ``J5`` -- the eigenspace (NOT a subalgebra) of ``c.operator()``
+ corresponding to the eigenvalue one-half.
+
+ - ``J1`` -- the algebra on the eigenspace of ``c.operator()``
+ corresponding to the eigenvalue one.
+
+ These are the only possible eigenspaces for that operator, and this
+ algebra is a direct sum of them. The spaces ``J0`` and ``J1`` are
+ orthogonal, and are subalgebras of this algebra with the appropriate
+ restrictions.
+
+ SETUP::
+
+ sage: from mjo.eja.eja_algebra import random_eja, RealSymmetricEJA
+
+ EXAMPLES:
+
+ The canonical example comes from the symmetric matrices, which
+ decompose into diagonal and off-diagonal parts::
+
+ sage: J = RealSymmetricEJA(3)
+ sage: C = matrix(QQ, [ [1,0,0],
+ ....: [0,1,0],
+ ....: [0,0,0] ])
+ sage: c = J(C)
+ sage: J0,J5,J1 = J.peirce_decomposition(c)
+ sage: J0
+ Euclidean Jordan algebra of dimension 1...
+ sage: J5
+ Vector space of degree 6 and dimension 2...
+ sage: J1
+ Euclidean Jordan algebra of dimension 3...
+ sage: J0.one().to_matrix()
+ [0 0 0]
+ [0 0 0]
+ [0 0 1]
+ sage: orig_df = AA.options.display_format
+ sage: AA.options.display_format = 'radical'
+ sage: J.from_vector(J5.basis()[0]).to_matrix()
+ [ 0 0 1/2*sqrt(2)]
+ [ 0 0 0]
+ [1/2*sqrt(2) 0 0]
+ sage: J.from_vector(J5.basis()[1]).to_matrix()
+ [ 0 0 0]
+ [ 0 0 1/2*sqrt(2)]
+ [ 0 1/2*sqrt(2) 0]
+ sage: AA.options.display_format = orig_df
+ sage: J1.one().to_matrix()
+ [1 0 0]
+ [0 1 0]
+ [0 0 0]
+
+ TESTS:
+
+ 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
+ True
+ sage: J1.superalgebra() == J and J1.dimension() == J.dimension()
+ True
+
+ The decomposition is into eigenspaces, and its components are
+ therefore necessarily orthogonal. Moreover, the identity
+ 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():
+ ....: while x.is_nilpotent():
+ ....: x = J.random_element()
+ sage: c = x.subalgebra_idempotent()
+ sage: J0,J5,J1 = J.peirce_decomposition(c)
+ sage: ipsum = 0
+ sage: for (w,y,z) in zip(J0.basis(), J5.basis(), J1.basis()):
+ ....: w = w.superalgebra_element()
+ ....: y = J.from_vector(y)
+ ....: z = z.superalgebra_element()
+ ....: ipsum += w.inner_product(y).abs()
+ ....: ipsum += w.inner_product(z).abs()
+ ....: ipsum += y.inner_product(z).abs()
+ sage: ipsum
+ 0
+ sage: J1(c) == J1.one()
+ True
+ sage: J0(J.one() - c) == J0.one()
+ True
+
+ """
+ if not c.is_idempotent():
+ raise ValueError("element is not idempotent: %s" % c)
+
+ # Default these to what they should be if they turn out to be
+ # trivial, because eigenspaces_left() won't return eigenvalues
+ # corresponding to trivial spaces (e.g. it returns only the
+ # eigenspace corresponding to lambda=1 if you take the
+ # decomposition relative to the identity element).
+ trivial = self.subalgebra(())
+ J0 = trivial # eigenvalue zero
+ J5 = VectorSpace(self.base_ring(), 0) # eigenvalue one-half
+ J1 = trivial # eigenvalue one
+
+ for (eigval, eigspace) in c.operator().matrix().right_eigenspaces():
+ if eigval == ~(self.base_ring()(2)):
+ J5 = eigspace
+ else:
+ gens = tuple( self.from_vector(b) for b in eigspace.basis() )
+ subalg = self.subalgebra(gens, check_axioms=False)
+ if eigval == 0:
+ J0 = subalg
+ elif eigval == 1:
+ J1 = subalg
+ else:
+ raise ValueError("unexpected eigenvalue: %s" % eigval)
+
+ return (J0, J5, J1)
+
+
+ def random_element(self, thorough=False):
+ r"""
+ Return a random element of this algebra.
+
+ Our algebra superclass method only returns a linear
+ combination of at most two basis elements. We instead
+ want the vector space "random element" method that
+ returns a more diverse selection.
+
+ INPUT:
+
+ - ``thorough`` -- (boolean; default False) whether or not we
+ should generate irrational coefficients for the random
+ element when our base ring is irrational; this slows the
+ algebra operations to a crawl, but any truly random method
+ should include them
+
+ """
+ # For a general base ring... maybe we can trust this to do the
+ # right thing? Unlikely, but.
+ V = self.vector_space()
+ v = V.random_element()
+
+ if self.base_ring() is AA:
+ # The "random element" method of the algebraic reals is
+ # stupid at the moment, and only returns integers between
+ # -2 and 2, inclusive:
+ #
+ # https://trac.sagemath.org/ticket/30875
+ #
+ # Instead, we implement our own "random vector" method,
+ # and then coerce that into the algebra. We use the vector
+ # space degree here instead of the dimension because a
+ # subalgebra could (for example) be spanned by only two
+ # vectors, each with five coordinates. We need to
+ # generate all five coordinates.
+ if thorough:
+ v *= QQbar.random_element().real()
+ else:
+ v *= QQ.random_element()
+
+ return self.from_vector(V.coordinate_vector(v))
+
+ def random_elements(self, count, thorough=False):
+ """
+ Return ``count`` random elements as a tuple.
+
+ INPUT:
+
+ - ``thorough`` -- (boolean; default False) whether or not we
+ should generate irrational coefficients for the random
+ elements when our base ring is irrational; this slows the
+ algebra operations to a crawl, but any truly random method
+ should include them
+
+ SETUP::
+
+ sage: from mjo.eja.eja_algebra import JordanSpinEJA
+
+ EXAMPLES::
+
+ sage: J = JordanSpinEJA(3)
+ sage: x,y,z = J.random_elements(3)
+ sage: all( [ x in J, y in J, z in J ])
+ True
+ sage: len( J.random_elements(10) ) == 10
+ True
+
+ """
+ return tuple( self.random_element(thorough)
+ for idx in range(count) )
+
+
+ @cached_method
+ def _charpoly_coefficients(self):
+ r"""
+ The `r` polynomial coefficients of the "characteristic polynomial
+ of" function.
+
+ SETUP::
+
+ sage: from mjo.eja.eja_algebra import random_eja
+
+ TESTS:
+
+ 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
+
+ """
+ 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.gens()[k].operator().matrix()[i,j]
+ for k in range(n) )
+
+ L_x = matrix(F, n, n, L_x_i_j)
+
+ r = None
+ if self.rank.is_in_cache():
+ r = self.rank()
+ # There's no need to pad the system with redundant
+ # columns if we *know* they'll be redundant.
+ n = r
+
+ # Compute an extra power in case the rank is equal to
+ # the dimension (otherwise, we would stop at x^(r-1)).
+ x_powers = [ (L_x**k)*self.one().to_vector()
+ for k in range(n+1) ]
+ A = matrix.column(F, x_powers[:n])
+ AE = A.extended_echelon_form()
+ E = AE[:,n:]
+ A_rref = AE[:,:n]
+ if r is None:
+ r = A_rref.rank()
+ b = x_powers[r]
+
+ # The theory says that only the first "r" coefficients are
+ # nonzero, and they actually live in the original polynomial
+ # ring and not the fraction field. We negate them because in
+ # the actual characteristic polynomial, they get moved to the
+ # other side where x^r lives. We don't bother to trim A_rref
+ # down to a square matrix and solve the resulting system,
+ # because the upper-left r-by-r portion of A_rref is
+ # guaranteed to be the identity matrix, so e.g.
+ #
+ # A_rref.solve_right(Y)
+ #
+ # would just be returning Y.
+ return (-E*b)[:r].change_ring(R)
+
+ @cached_method
+ def rank(self):
+ r"""
+ Return the rank of this EJA.
+
+ This is a cached method because we know the rank a priori for
+ all of the algebras we can construct. Thus we can avoid the
+ expensive ``_charpoly_coefficients()`` call unless we truly
+ need to compute the whole characteristic polynomial.
+
+ SETUP::
+
+ sage: from mjo.eja.eja_algebra import (HadamardEJA,
+ ....: JordanSpinEJA,
+ ....: RealSymmetricEJA,
+ ....: ComplexHermitianEJA,
+ ....: QuaternionHermitianEJA,
+ ....: random_eja)
+
+ EXAMPLES:
+
+ The rank of the Jordan spin algebra is always two::
+
+ sage: JordanSpinEJA(2).rank()
+ 2
+ sage: JordanSpinEJA(3).rank()
+ 2
+ sage: JordanSpinEJA(4).rank()
+ 2
+
+ The rank of the `n`-by-`n` Hermitian real, complex, or
+ quaternion matrices is `n`::
+
+ sage: RealSymmetricEJA(4).rank()
+ 4
+ sage: ComplexHermitianEJA(3).rank()
+ 3
+ sage: QuaternionHermitianEJA(2).rank()
+ 2
+
+ TESTS:
+
+ Ensure that every EJA that we know how to construct has a
+ 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
+ True
+ sage: r > 0 or (r == 0 and J.is_trivial())
+ True
+
+ 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
+ sage: J.rank() == cached # long time
+ True
+
+ """
+ return len(self._charpoly_coefficients())
+
+
+ def subalgebra(self, basis, **kwargs):
+ r"""
+ Create a subalgebra of this algebra from the given basis.
+ """
+ from mjo.eja.eja_subalgebra import FiniteDimensionalEJASubalgebra
+ return FiniteDimensionalEJASubalgebra(self, basis, **kwargs)
+
+
+ def vector_space(self):
+ """
+ Return the vector space that underlies this algebra.
+
+ SETUP::
+
+ sage: from mjo.eja.eja_algebra import RealSymmetricEJA
+
+ EXAMPLES::
+
+ sage: J = RealSymmetricEJA(2)
+ sage: J.vector_space()
+ Vector space of dimension 3 over...
+
+ """
+ return self.zero().to_vector().parent().ambient_vector_space()
+
+
+
+class RationalBasisEJA(FiniteDimensionalEJA):
+ r"""
+ New class for algebras whose supplied basis elements have all rational entries.
+
+ SETUP::
+
+ sage: from mjo.eja.eja_algebra import BilinearFormEJA
+
+ EXAMPLES:
+
+ The supplied basis is orthonormalized by default::
+
+ sage: B = matrix(QQ, [[1, 0, 0], [0, 25, -32], [0, -32, 41]])
+ sage: J = BilinearFormEJA(B)
+ sage: J.matrix_basis()
+ (
+ [1] [ 0] [ 0]
+ [0] [1/5] [32/5]
+ [0], [ 0], [ 5]
+ )
+
+ """
+ def __init__(self,
+ basis,
+ jordan_product,
+ inner_product,
+ field=AA,
+ check_field=True,
+ **kwargs):
+
+ if check_field:
+ # Abuse the check_field parameter to check that the entries of
+ # out basis (in ambient coordinates) are in the field QQ.
+ if not all( all(b_i in QQ for b_i in b.list()) for b in basis ):
+ raise TypeError("basis not rational")
+
+ self._rational_algebra = None
+ if field is not QQ:
+ # There's no point in constructing the extra algebra if this
+ # one is already rational.
+ #
+ # Note: the same Jordan and inner-products work here,
+ # because they are necessarily defined with respect to
+ # ambient coordinates and not any particular basis.
+ self._rational_algebra = FiniteDimensionalEJA(
+ basis,
+ jordan_product,
+ inner_product,
+ field=QQ,
+ orthonormalize=False,
+ check_field=False,
+ check_axioms=False)
+
+ super().__init__(basis,
+ jordan_product,
+ inner_product,
+ field=field,
+ check_field=check_field,
+ **kwargs)
+
+ @cached_method
+ def _charpoly_coefficients(self):
+ r"""
+ SETUP::
+
+ sage: from mjo.eja.eja_algebra import (BilinearFormEJA,
+ ....: JordanSpinEJA)
+
+ EXAMPLES:
+
+ The base ring of the resulting polynomial coefficients is what
+ it should be, and not the rationals (unless the algebra was
+ already over the rationals)::
+
+ sage: J = JordanSpinEJA(3)
+ sage: J._charpoly_coefficients()
+ (X1^2 - X2^2 - X3^2, -2*X1)
+ sage: a0 = J._charpoly_coefficients()[0]
+ sage: J.base_ring()
+ Algebraic Real Field
+ sage: a0.base_ring()
+ Algebraic Real Field
+
+ """
+ if self._rational_algebra is None:
+ # There's no need to construct *another* algebra over the
+ # rationals if this one is already over the
+ # rationals. Likewise, if we never orthonormalized our
+ # basis, we might as well just use the given one.
+ return super()._charpoly_coefficients()
+
+ # Do the computation over the rationals. The answer will be
+ # the same, because all we've done is a change of basis.
+ # Then, change back from QQ to our real base ring
+ a = ( a_i.change_ring(self.base_ring())
+ for a_i in self._rational_algebra._charpoly_coefficients() )
+
+ if self._deortho_matrix is None:
+ # This can happen if our base ring was, say, AA and we
+ # chose not to (or didn't need to) orthonormalize. It's
+ # still faster to do the computations over QQ even if
+ # the numbers in the boxes stay the same.
+ return tuple(a)
+
+ # Otherwise, convert the coordinate variables back to the
+ # deorthonormalized ones.
+ R = self.coordinate_polynomial_ring()
+ from sage.modules.free_module_element import vector
+ X = vector(R, R.gens())
+ BX = self._deortho_matrix*X
+
+ subs_dict = { X[i]: BX[i] for i in range(len(X)) }
+ return tuple( a_i.subs(subs_dict) for a_i in a )
+
+class ConcreteEJA(RationalBasisEJA):
+ r"""
+ A class for the Euclidean Jordan algebras that we know by name.
+
+ These are the Jordan algebras whose basis, multiplication table,
+ rank, and so on are known a priori. More to the point, they are
+ the Euclidean Jordan algebras for which we are able to conjure up
+ a "random instance."
+
+ SETUP::
+
+ sage: from mjo.eja.eja_algebra import ConcreteEJA
+
+ TESTS:
+
+ 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
+
+ Since our basis is orthonormal with respect to the algebra's inner
+ product, and since we know that this algebra is an EJA, any
+ left-multiplication operator's matrix will be symmetric because
+ 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()
+ True
+ """
+
+ @staticmethod
+ def _max_random_instance_size():
+ """
+ Return an integer "size" that is an upper bound on the size of
+ this algebra when it is used in a random test
+ case. Unfortunately, the term "size" is ambiguous -- when
+ dealing with `R^n` under either the Hadamard or Jordan spin
+ product, the "size" refers to the dimension `n`. When dealing
+ with a matrix algebra (real symmetric or complex/quaternion
+ Hermitian), it refers to the size of the matrix, which is far
+ less than the dimension of the underlying vector space.
+
+ This method must be implemented in each subclass.
+ """
+ raise NotImplementedError
+
+ @classmethod
+ def random_instance(cls, *args, **kwargs):
+ """
+ Return a random instance of this type of algebra.
+
+ This method should be implemented in each subclass.
+ """
+ from sage.misc.prandom import choice
+ eja_class = choice(cls.__subclasses__())
+
+ # These all bubble up to the RationalBasisEJA superclass
+ # constructor, so any (kw)args valid there are also valid
+ # here.
+ return eja_class.random_instance(*args, **kwargs)
+
+
+class MatrixEJA:
+ @staticmethod
+ def dimension_over_reals():
+ r"""
+ The dimension of this matrix's base ring over the reals.
+
+ The reals are dimension one over themselves, obviously; that's
+ just `\mathbb{R}^{1}`. Likewise, the complex numbers `a + bi`
+ have dimension two. Finally, the quaternions have dimension
+ four over the reals.
+
+ This is used to determine the size of the matrix returned from
+ :meth:`real_embed`, among other things.
+ """
+ raise NotImplementedError
+
+ @classmethod
+ def real_embed(cls,M):
+ """
+ Embed the matrix ``M`` into a space of real matrices.
+
+ The matrix ``M`` can have entries in any field at the moment:
+ the real numbers, complex numbers, or quaternions. And although
+ they are not a field, we can probably support octonions at some
+ point, too. This function returns a real matrix that "acts like"
+ the original with respect to matrix multiplication; i.e.
+
+ real_embed(M*N) = real_embed(M)*real_embed(N)
+
+ """
+ if M.ncols() != M.nrows():
+ raise ValueError("the matrix 'M' must be square")
+ return M
+
+
+ @classmethod
+ def real_unembed(cls,M):
+ """
+ The inverse of :meth:`real_embed`.
+ """
+ if M.ncols() != M.nrows():
+ raise ValueError("the matrix 'M' must be square")
+ if not ZZ(M.nrows()).mod(cls.dimension_over_reals()).is_zero():
+ raise ValueError("the matrix 'M' must be a real embedding")
+ return M
+
+ @staticmethod
+ def jordan_product(X,Y):
+ return (X*Y + Y*X)/2
+
+ @classmethod
+ def trace_inner_product(cls,X,Y):
+ r"""
+ Compute the trace inner-product of two real-embeddings.
+
+ SETUP::
+
+ sage: from mjo.eja.eja_algebra import (RealSymmetricEJA,
+ ....: ComplexHermitianEJA,
+ ....: QuaternionHermitianEJA)
+
+ EXAMPLES::
+
+ This gives the same answer as it would if we computed the trace
+ from the unembedded (original) matrices::
+
+ sage: set_random_seed()
+ sage: J = RealSymmetricEJA.random_instance()
+ sage: x,y = J.random_elements(2)
+ sage: Xe = x.to_matrix()
+ sage: Ye = y.to_matrix()
+ sage: X = J.real_unembed(Xe)
+ sage: Y = J.real_unembed(Ye)
+ sage: expected = (X*Y).trace()
+ sage: actual = J.trace_inner_product(Xe,Ye)
+ sage: actual == expected
+ True
+
+ ::
+
+ sage: set_random_seed()
+ sage: J = ComplexHermitianEJA.random_instance()
+ sage: x,y = J.random_elements(2)
+ sage: Xe = x.to_matrix()
+ sage: Ye = y.to_matrix()
+ sage: X = J.real_unembed(Xe)
+ sage: Y = J.real_unembed(Ye)
+ sage: expected = (X*Y).trace().real()
+ sage: actual = J.trace_inner_product(Xe,Ye)
+ sage: actual == expected
+ True
+
+ ::
+
+ sage: set_random_seed()
+ sage: J = QuaternionHermitianEJA.random_instance()
+ sage: x,y = J.random_elements(2)
+ sage: Xe = x.to_matrix()
+ sage: Ye = y.to_matrix()
+ sage: X = J.real_unembed(Xe)
+ sage: Y = J.real_unembed(Ye)
+ sage: expected = (X*Y).trace().coefficient_tuple()[0]
+ sage: actual = J.trace_inner_product(Xe,Ye)
+ sage: actual == expected
+ True
+
+ """
+ Xu = cls.real_unembed(X)
+ Yu = cls.real_unembed(Y)
+ tr = (Xu*Yu).trace()
+
+ try:
+ # Works in QQ, AA, RDF, et cetera.
+ return tr.real()
+ except AttributeError:
+ # A quaternion doesn't have a real() method, but does
+ # have coefficient_tuple() method that returns the
+ # coefficients of 1, i, j, and k -- in that order.
+ return tr.coefficient_tuple()[0]
+
+
+class RealMatrixEJA(MatrixEJA):
+ @staticmethod
+ def dimension_over_reals():
+ return 1
+
+
+class RealSymmetricEJA(ConcreteEJA, RealMatrixEJA):
+ """
+ The rank-n simple EJA consisting of real symmetric n-by-n
+ matrices, the usual symmetric Jordan product, and the trace inner
+ product. It has dimension `(n^2 + n)/2` over the reals.
+
+ SETUP::
+
+ sage: from mjo.eja.eja_algebra import RealSymmetricEJA
+
+ EXAMPLES::
+
+ sage: J = RealSymmetricEJA(2)
+ sage: e0, e1, e2 = J.gens()
+ sage: e0*e0
+ e0
+ sage: e1*e1
+ 1/2*e0 + 1/2*e2
+ sage: e2*e2
+ e2
+
+ In theory, our "field" can be any subfield of the reals::
+
+ sage: RealSymmetricEJA(2, field=RDF, check_axioms=True)
+ Euclidean Jordan algebra of dimension 3 over Real Double Field
+ sage: RealSymmetricEJA(2, field=RR, check_axioms=True)
+ Euclidean Jordan algebra of dimension 3 over Real Field with
+ 53 bits of precision
+
+ TESTS:
+
+ The dimension of this algebra is `(n^2 + n) / 2`::
+
+ sage: set_random_seed()
+ sage: n_max = RealSymmetricEJA._max_random_instance_size()
+ sage: n = ZZ.random_element(1, n_max)
+ sage: J = RealSymmetricEJA(n)
+ sage: J.dimension() == (n^2 + n)/2
+ True
+
+ 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()
+ sage: X = x.to_matrix()
+ sage: Y = y.to_matrix()
+ sage: expected = (X*Y + Y*X)/2
+ sage: actual == expected
+ True
+ sage: J(expected) == x*y
+ True
+
+ We can change the generator prefix::
+
+ sage: RealSymmetricEJA(3, prefix='q').gens()
+ (q0, q1, q2, q3, q4, q5)
+
+ We can construct the (trivial) algebra of rank zero::
+
+ sage: RealSymmetricEJA(0)
+ Euclidean Jordan algebra of dimension 0 over Algebraic Real Field
+
+ """
+ @classmethod
+ def _denormalized_basis(cls, n):
+ """
+ Return a basis for the space of real symmetric n-by-n matrices.
+
+ SETUP::
+
+ sage: from mjo.eja.eja_algebra import RealSymmetricEJA
+
+ TESTS::
+
+ sage: set_random_seed()
+ sage: n = ZZ.random_element(1,5)
+ sage: B = RealSymmetricEJA._denormalized_basis(n)
+ sage: all( M.is_symmetric() for M in B)
+ True
+
+ """
+ # The basis of symmetric matrices, as matrices, in their R^(n-by-n)
+ # coordinates.
+ S = []
+ for i in range(n):
+ for j in range(i+1):
+ Eij = matrix(ZZ, n, lambda k,l: k==i and l==j)
+ if i == j:
+ Sij = Eij
+ else:
+ Sij = Eij + Eij.transpose()
+ S.append(Sij)
+ return tuple(S)
+
+
+ @staticmethod
+ def _max_random_instance_size():
+ return 4 # Dimension 10
+
+ @classmethod
+ def random_instance(cls, **kwargs):
+ """
+ Return a random instance of this type of algebra.
+ """
+ n = ZZ.random_element(cls._max_random_instance_size() + 1)
+ return cls(n, **kwargs)
+
+ def __init__(self, n, **kwargs):
+ # We know this is a valid EJA, but will double-check
+ # if the user passes check_axioms=True.
+ if "check_axioms" not in kwargs: kwargs["check_axioms"] = False
+
+ super(RealSymmetricEJA, self).__init__(self._denormalized_basis(n),
+ self.jordan_product,
+ self.trace_inner_product,
+ **kwargs)
+
+ # TODO: this could be factored out somehow, but is left here
+ # because the MatrixEJA is not presently a subclass of the
+ # FDEJA class that defines rank() and one().
+ self.rank.set_cache(n)
+ idV = matrix.identity(ZZ, self.dimension_over_reals()*n)
+ self.one.set_cache(self(idV))
+
+
+
+class ComplexMatrixEJA(MatrixEJA):
+ # A manual dictionary-cache for the complex_extension() method,
+ # since apparently @classmethods can't also be @cached_methods.
+ _complex_extension = {}
+
+ @classmethod
+ def complex_extension(cls,field):
+ r"""
+ The complex field that we embed/unembed, as an extension
+ of the given ``field``.
+ """
+ if field in cls._complex_extension:
+ return cls._complex_extension[field]
+
+ # Sage doesn't know how to adjoin the complex "i" (the root of
+ # x^2 + 1) to a field in a general way. Here, we just enumerate
+ # all of the cases that I have cared to support so far.
+ if field is AA:
+ # Sage doesn't know how to embed AA into QQbar, i.e. how
+ # to adjoin sqrt(-1) to AA.
+ F = QQbar
+ elif not field.is_exact():
+ # RDF or RR
+ F = field.complex_field()
+ else:
+ # Works for QQ and... maybe some other fields.
+ R = PolynomialRing(field, 'z')
+ z = R.gen()
+ F = field.extension(z**2 + 1, 'I', embedding=CLF(-1).sqrt())
+
+ cls._complex_extension[field] = F
+ return F
+
+ @staticmethod
+ def dimension_over_reals():
+ return 2
+
+ @classmethod
+ def real_embed(cls,M):
+ """
+ Embed the n-by-n complex matrix ``M`` into the space of real
+ matrices of size 2n-by-2n via the map the sends each entry `z = a +
+ bi` to the block matrix ``[[a,b],[-b,a]]``.
+
+ SETUP::
+
+ sage: from mjo.eja.eja_algebra import ComplexMatrixEJA
+
+ EXAMPLES::
+
+ sage: F = QuadraticField(-1, 'I')
+ sage: x1 = F(4 - 2*i)
+ sage: x2 = F(1 + 2*i)
+ sage: x3 = F(-i)
+ sage: x4 = F(6)
+ sage: M = matrix(F,2,[[x1,x2],[x3,x4]])
+ sage: ComplexMatrixEJA.real_embed(M)
+ [ 4 -2| 1 2]
+ [ 2 4|-2 1]
+ [-----+-----]
+ [ 0 -1| 6 0]
+ [ 1 0| 0 6]
+
+ TESTS:
+
+ Embedding is a homomorphism (isomorphism, in fact)::
+
+ sage: set_random_seed()
+ sage: n = ZZ.random_element(3)
+ sage: F = QuadraticField(-1, 'I')
+ sage: X = random_matrix(F, n)
+ sage: Y = random_matrix(F, n)
+ sage: Xe = ComplexMatrixEJA.real_embed(X)
+ sage: Ye = ComplexMatrixEJA.real_embed(Y)
+ sage: XYe = ComplexMatrixEJA.real_embed(X*Y)
+ sage: Xe*Ye == XYe
+ True
+
+ """
+ super(ComplexMatrixEJA,cls).real_embed(M)
+ n = M.nrows()
+
+ # We don't need any adjoined elements...
+ field = M.base_ring().base_ring()
+
+ blocks = []
+ for z in M.list():
+ a = z.real()
+ b = z.imag()
+ blocks.append(matrix(field, 2, [ [ a, b],
+ [-b, a] ]))
+
+ return matrix.block(field, n, blocks)
+
+
+ @classmethod
+ def real_unembed(cls,M):
+ """
+ The inverse of _embed_complex_matrix().
+
+ SETUP::
+
+ sage: from mjo.eja.eja_algebra import ComplexMatrixEJA
+
+ EXAMPLES::
+
+ sage: A = matrix(QQ,[ [ 1, 2, 3, 4],
+ ....: [-2, 1, -4, 3],
+ ....: [ 9, 10, 11, 12],
+ ....: [-10, 9, -12, 11] ])
+ sage: ComplexMatrixEJA.real_unembed(A)
+ [ 2*I + 1 4*I + 3]
+ [ 10*I + 9 12*I + 11]
+
+ TESTS:
+
+ Unembedding is the inverse of embedding::
+
+ sage: set_random_seed()
+ sage: F = QuadraticField(-1, 'I')
+ sage: M = random_matrix(F, 3)
+ sage: Me = ComplexMatrixEJA.real_embed(M)
+ sage: ComplexMatrixEJA.real_unembed(Me) == M
+ True
+
+ """
+ super(ComplexMatrixEJA,cls).real_unembed(M)
+ n = ZZ(M.nrows())
+ d = cls.dimension_over_reals()
+ F = cls.complex_extension(M.base_ring())
+ i = F.gen()
+
+ # Go top-left to bottom-right (reading order), converting every
+ # 2-by-2 block we see to a single complex element.
+ elements = []
+ for k in range(n/d):
+ for j in range(n/d):
+ submat = M[d*k:d*k+d,d*j:d*j+d]
+ if submat[0,0] != submat[1,1]:
+ raise ValueError('bad on-diagonal submatrix')
+ if submat[0,1] != -submat[1,0]:
+ raise ValueError('bad off-diagonal submatrix')
+ z = submat[0,0] + submat[0,1]*i
+ elements.append(z)
+
+ return matrix(F, n/d, elements)
+
+
+class ComplexHermitianEJA(ConcreteEJA, ComplexMatrixEJA):
+ """
+ The rank-n simple EJA consisting of complex Hermitian n-by-n
+ matrices over the real numbers, the usual symmetric Jordan product,
+ and the real-part-of-trace inner product. It has dimension `n^2` over
+ the reals.
+
+ SETUP::
+
+ sage: from mjo.eja.eja_algebra import ComplexHermitianEJA
+
+ EXAMPLES:
+
+ In theory, our "field" can be any subfield of the reals::
+
+ sage: ComplexHermitianEJA(2, field=RDF, check_axioms=True)
+ Euclidean Jordan algebra of dimension 4 over Real Double Field
+ sage: ComplexHermitianEJA(2, field=RR, check_axioms=True)
+ Euclidean Jordan algebra of dimension 4 over Real Field with
+ 53 bits of precision
+
+ TESTS:
+
+ The dimension of this algebra is `n^2`::
+
+ sage: set_random_seed()
+ sage: n_max = ComplexHermitianEJA._max_random_instance_size()
+ sage: n = ZZ.random_element(1, n_max)
+ sage: J = ComplexHermitianEJA(n)
+ sage: J.dimension() == n^2
+ True
+
+ 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()
+ sage: X = x.to_matrix()
+ sage: Y = y.to_matrix()
+ sage: expected = (X*Y + Y*X)/2
+ sage: actual == expected
+ True
+ sage: J(expected) == x*y
+ True
+
+ We can change the generator prefix::
+
+ sage: ComplexHermitianEJA(2, prefix='z').gens()
+ (z0, z1, z2, z3)
+
+ We can construct the (trivial) algebra of rank zero::
+
+ sage: ComplexHermitianEJA(0)
+ Euclidean Jordan algebra of dimension 0 over Algebraic Real Field
+
+ """
+
+ @classmethod
+ def _denormalized_basis(cls, n):
+ """
+ Returns a basis for the space of complex Hermitian n-by-n matrices.
+
+ Why do we embed these? Basically, because all of numerical linear
+ algebra assumes that you're working with vectors consisting of `n`
+ entries from a field and scalars from the same field. There's no way
+ to tell SageMath that (for example) the vectors contain complex
+ numbers, while the scalar field is real.
+
+ SETUP::
+
+ sage: from mjo.eja.eja_algebra import ComplexHermitianEJA
+
+ TESTS::
+
+ sage: set_random_seed()
+ sage: n = ZZ.random_element(1,5)
+ sage: B = ComplexHermitianEJA._denormalized_basis(n)
+ sage: all( M.is_symmetric() for M in B)
+ True
+
+ """
+ field = ZZ
+ R = PolynomialRing(field, 'z')
+ z = R.gen()
+ F = field.extension(z**2 + 1, 'I')
+ I = F.gen(1)
+
+ # This is like the symmetric case, but we need to be careful:
+ #
+ # * We want conjugate-symmetry, not just symmetry.
+ # * The diagonal will (as a result) be real.
+ #
+ S = []
+ Eij = matrix.zero(F,n)
+ for i in range(n):
+ for j in range(i+1):
+ # "build" E_ij
+ Eij[i,j] = 1
+ if i == j:
+ Sij = cls.real_embed(Eij)
+ S.append(Sij)
+ else:
+ # The second one has a minus because it's conjugated.
+ Eij[j,i] = 1 # Eij = Eij + Eij.transpose()
+ Sij_real = cls.real_embed(Eij)
+ S.append(Sij_real)
+ # Eij = I*Eij - I*Eij.transpose()
+ Eij[i,j] = I
+ Eij[j,i] = -I
+ Sij_imag = cls.real_embed(Eij)
+ S.append(Sij_imag)
+ Eij[j,i] = 0
+ # "erase" E_ij
+ Eij[i,j] = 0
+
+ # Since we embedded these, we can drop back to the "field" that we
+ # started with instead of the complex extension "F".
+ return tuple( s.change_ring(field) for s in S )
+
+
+ def __init__(self, n, **kwargs):
+ # We know this is a valid EJA, but will double-check
+ # if the user passes check_axioms=True.
+ if "check_axioms" not in kwargs: kwargs["check_axioms"] = False
+
+ super(ComplexHermitianEJA, self).__init__(self._denormalized_basis(n),
+ self.jordan_product,
+ self.trace_inner_product,
+ **kwargs)
+ # TODO: this could be factored out somehow, but is left here
+ # because the MatrixEJA is not presently a subclass of the
+ # FDEJA class that defines rank() and one().
+ self.rank.set_cache(n)
+ idV = matrix.identity(ZZ, self.dimension_over_reals()*n)
+ self.one.set_cache(self(idV))
+
+ @staticmethod
+ def _max_random_instance_size():
+ return 3 # Dimension 9
+
+ @classmethod
+ def random_instance(cls, **kwargs):
+ """
+ Return a random instance of this type of algebra.
+ """
+ n = ZZ.random_element(cls._max_random_instance_size() + 1)
+ return cls(n, **kwargs)
+
+class QuaternionMatrixEJA(MatrixEJA):
+
+ # A manual dictionary-cache for the quaternion_extension() method,
+ # since apparently @classmethods can't also be @cached_methods.
+ _quaternion_extension = {}
+
+ @classmethod
+ def quaternion_extension(cls,field):
+ r"""
+ The quaternion field that we embed/unembed, as an extension
+ of the given ``field``.
+ """
+ if field in cls._quaternion_extension:
+ return cls._quaternion_extension[field]
+
+ Q = QuaternionAlgebra(field,-1,-1)
+
+ cls._quaternion_extension[field] = Q
+ return Q
+
+ @staticmethod
+ def dimension_over_reals():
+ return 4
+
+ @classmethod
+ def real_embed(cls,M):
+ """
+ Embed the n-by-n quaternion matrix ``M`` into the space of real
+ matrices of size 4n-by-4n by first sending each quaternion entry `z
+ = a + bi + cj + dk` to the block-complex matrix ``[[a + bi,
+ c+di],[-c + di, a-bi]]`, and then embedding those into a real
+ matrix.
+
+ SETUP::
+
+ sage: from mjo.eja.eja_algebra import QuaternionMatrixEJA
+
+ EXAMPLES::
+
+ sage: Q = QuaternionAlgebra(QQ,-1,-1)
+ sage: i,j,k = Q.gens()
+ sage: x = 1 + 2*i + 3*j + 4*k
+ sage: M = matrix(Q, 1, [[x]])
+ sage: QuaternionMatrixEJA.real_embed(M)
+ [ 1 2 3 4]
+ [-2 1 -4 3]
+ [-3 4 1 -2]
+ [-4 -3 2 1]
+
+ Embedding is a homomorphism (isomorphism, in fact)::
+
+ sage: set_random_seed()
+ sage: n = ZZ.random_element(2)
+ sage: Q = QuaternionAlgebra(QQ,-1,-1)
+ sage: X = random_matrix(Q, n)
+ sage: Y = random_matrix(Q, n)
+ sage: Xe = QuaternionMatrixEJA.real_embed(X)
+ sage: Ye = QuaternionMatrixEJA.real_embed(Y)
+ sage: XYe = QuaternionMatrixEJA.real_embed(X*Y)
+ sage: Xe*Ye == XYe
+ True
+
+ """
+ super(QuaternionMatrixEJA,cls).real_embed(M)
+ quaternions = M.base_ring()
+ n = M.nrows()
+
+ F = QuadraticField(-1, 'I')
+ i = F.gen()
+
+ blocks = []
+ for z in M.list():
+ t = z.coefficient_tuple()
+ a = t[0]
+ b = t[1]
+ c = t[2]
+ d = t[3]
+ cplxM = matrix(F, 2, [[ a + b*i, c + d*i],
+ [-c + d*i, a - b*i]])
+ realM = ComplexMatrixEJA.real_embed(cplxM)
+ blocks.append(realM)
+
+ # We should have real entries by now, so use the realest field
+ # we've got for the return value.
+ return matrix.block(quaternions.base_ring(), n, blocks)
+
+
+
+ @classmethod
+ def real_unembed(cls,M):
+ """
+ The inverse of _embed_quaternion_matrix().
+
+ SETUP::
+
+ sage: from mjo.eja.eja_algebra import QuaternionMatrixEJA
+
+ EXAMPLES::
+
+ sage: M = matrix(QQ, [[ 1, 2, 3, 4],
+ ....: [-2, 1, -4, 3],
+ ....: [-3, 4, 1, -2],
+ ....: [-4, -3, 2, 1]])
+ sage: QuaternionMatrixEJA.real_unembed(M)
+ [1 + 2*i + 3*j + 4*k]
+
+ TESTS:
+
+ Unembedding is the inverse of embedding::
+
+ sage: set_random_seed()
+ sage: Q = QuaternionAlgebra(QQ, -1, -1)
+ sage: M = random_matrix(Q, 3)
+ sage: Me = QuaternionMatrixEJA.real_embed(M)
+ sage: QuaternionMatrixEJA.real_unembed(Me) == M
+ True
+
+ """
+ super(QuaternionMatrixEJA,cls).real_unembed(M)
+ n = ZZ(M.nrows())
+ d = cls.dimension_over_reals()
+
+ # Use the base ring of the matrix to ensure that its entries can be
+ # multiplied by elements of the quaternion algebra.
+ Q = cls.quaternion_extension(M.base_ring())
+ i,j,k = Q.gens()
+
+ # Go top-left to bottom-right (reading order), converting every
+ # 4-by-4 block we see to a 2-by-2 complex block, to a 1-by-1
+ # quaternion block.
+ elements = []
+ for l in range(n/d):
+ for m in range(n/d):
+ submat = ComplexMatrixEJA.real_unembed(
+ M[d*l:d*l+d,d*m:d*m+d] )
+ if submat[0,0] != submat[1,1].conjugate():
+ raise ValueError('bad on-diagonal submatrix')
+ if submat[0,1] != -submat[1,0].conjugate():
+ raise ValueError('bad off-diagonal submatrix')
+ z = submat[0,0].real()
+ z += submat[0,0].imag()*i
+ z += submat[0,1].real()*j
+ z += submat[0,1].imag()*k
+ elements.append(z)
+
+ return matrix(Q, n/d, elements)
+
+
+class QuaternionHermitianEJA(ConcreteEJA, QuaternionMatrixEJA):
+ r"""
+ The rank-n simple EJA consisting of self-adjoint n-by-n quaternion
+ matrices, the usual symmetric Jordan product, and the
+ real-part-of-trace inner product. It has dimension `2n^2 - n` over
+ the reals.
+
+ SETUP::
+
+ sage: from mjo.eja.eja_algebra import QuaternionHermitianEJA
+
+ EXAMPLES:
+
+ In theory, our "field" can be any subfield of the reals::
+
+ sage: QuaternionHermitianEJA(2, field=RDF, check_axioms=True)
+ Euclidean Jordan algebra of dimension 6 over Real Double Field
+ sage: QuaternionHermitianEJA(2, field=RR, check_axioms=True)
+ Euclidean Jordan algebra of dimension 6 over Real Field with
+ 53 bits of precision
+
+ TESTS:
+
+ The dimension of this algebra is `2*n^2 - n`::
+
+ sage: set_random_seed()
+ sage: n_max = QuaternionHermitianEJA._max_random_instance_size()
+ sage: n = ZZ.random_element(1, n_max)
+ sage: J = QuaternionHermitianEJA(n)
+ sage: J.dimension() == 2*(n^2) - n
+ True
+
+ 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()
+ sage: X = x.to_matrix()
+ sage: Y = y.to_matrix()
+ sage: expected = (X*Y + Y*X)/2
+ sage: actual == expected
+ True
+ sage: J(expected) == x*y
+ True
+
+ We can change the generator prefix::
+
+ sage: QuaternionHermitianEJA(2, prefix='a').gens()
+ (a0, a1, a2, a3, a4, a5)
+
+ We can construct the (trivial) algebra of rank zero::
+
+ sage: QuaternionHermitianEJA(0)
+ Euclidean Jordan algebra of dimension 0 over Algebraic Real Field
+
+ """
+ @classmethod
+ def _denormalized_basis(cls, n):
+ """
+ Returns a basis for the space of quaternion Hermitian n-by-n matrices.
+
+ Why do we embed these? Basically, because all of numerical
+ linear algebra assumes that you're working with vectors consisting
+ of `n` entries from a field and scalars from the same field. There's
+ no way to tell SageMath that (for example) the vectors contain
+ complex numbers, while the scalar field is real.
+
+ SETUP::
+
+ sage: from mjo.eja.eja_algebra import QuaternionHermitianEJA
+
+ TESTS::
+
+ sage: set_random_seed()
+ sage: n = ZZ.random_element(1,5)
+ sage: B = QuaternionHermitianEJA._denormalized_basis(n)
+ sage: all( M.is_symmetric() for M in B )
+ True
+
+ """
+ field = ZZ
+ Q = QuaternionAlgebra(QQ,-1,-1)
+ I,J,K = Q.gens()
+
+ # This is like the symmetric case, but we need to be careful:
+ #
+ # * We want conjugate-symmetry, not just symmetry.
+ # * The diagonal will (as a result) be real.
+ #
+ S = []
+ Eij = matrix.zero(Q,n)
+ for i in range(n):
+ for j in range(i+1):
+ # "build" E_ij
+ Eij[i,j] = 1
+ if i == j:
+ Sij = cls.real_embed(Eij)
+ S.append(Sij)
+ else:
+ # The second, third, and fourth ones have a minus
+ # because they're conjugated.
+ # Eij = Eij + Eij.transpose()
+ Eij[j,i] = 1
+ Sij_real = cls.real_embed(Eij)
+ S.append(Sij_real)
+ # Eij = I*(Eij - Eij.transpose())
+ Eij[i,j] = I
+ Eij[j,i] = -I
+ Sij_I = cls.real_embed(Eij)
+ S.append(Sij_I)
+ # Eij = J*(Eij - Eij.transpose())
+ Eij[i,j] = J
+ Eij[j,i] = -J
+ Sij_J = cls.real_embed(Eij)
+ S.append(Sij_J)
+ # Eij = K*(Eij - Eij.transpose())
+ Eij[i,j] = K
+ Eij[j,i] = -K
+ Sij_K = cls.real_embed(Eij)
+ S.append(Sij_K)
+ Eij[j,i] = 0
+ # "erase" E_ij
+ Eij[i,j] = 0
+
+ # Since we embedded these, we can drop back to the "field" that we
+ # started with instead of the quaternion algebra "Q".
+ return tuple( s.change_ring(field) for s in S )
+
+
+ def __init__(self, n, **kwargs):
+ # We know this is a valid EJA, but will double-check
+ # if the user passes check_axioms=True.
+ if "check_axioms" not in kwargs: kwargs["check_axioms"] = False
+
+ super(QuaternionHermitianEJA, self).__init__(self._denormalized_basis(n),
+ self.jordan_product,
+ self.trace_inner_product,
+ **kwargs)
+ # TODO: this could be factored out somehow, but is left here
+ # because the MatrixEJA is not presently a subclass of the
+ # FDEJA class that defines rank() and one().
+ self.rank.set_cache(n)
+ idV = matrix.identity(ZZ, self.dimension_over_reals()*n)
+ self.one.set_cache(self(idV))
+
+
+ @staticmethod
+ def _max_random_instance_size():
+ r"""
+ The maximum rank of a random QuaternionHermitianEJA.
+ """
+ return 2 # Dimension 6
+
+ @classmethod
+ def random_instance(cls, **kwargs):
+ """
+ Return a random instance of this type of algebra.
+ """
+ n = ZZ.random_element(cls._max_random_instance_size() + 1)
+ return cls(n, **kwargs)
+
+
+class HadamardEJA(ConcreteEJA):
+ """
+ Return the Euclidean Jordan Algebra corresponding to the set
+ `R^n` under the Hadamard product.
+
+ Note: this is nothing more than the Cartesian product of ``n``
+ copies of the spin algebra. Once Cartesian product algebras
+ are implemented, this can go.