X-Git-Url: http://gitweb.michael.orlitzky.com/?a=blobdiff_plain;f=mjo%2Feja%2Feuclidean_jordan_algebra.py;h=30d04f4a352b7d553470bd456d18d224e2ec5428;hb=31baec0eee0c53b0cfe379c744cdf174aa57ebd9;hp=b5cef0a8ba16f8a2afb0a66a0f38a6ac6daaa6ae;hpb=9fca3c9328ffbdbdb853a889362f75f4c38a6d7d;p=sage.d.git diff --git a/mjo/eja/euclidean_jordan_algebra.py b/mjo/eja/euclidean_jordan_algebra.py index b5cef0a..30d04f4 100644 --- a/mjo/eja/euclidean_jordan_algebra.py +++ b/mjo/eja/euclidean_jordan_algebra.py @@ -5,12 +5,405 @@ are used in optimization, and have some additional nice methods beyond what can be supported in a general Jordan Algebra. """ -from sage.categories.magmatic_algebras import MagmaticAlgebras +from sage.categories.finite_dimensional_algebras_with_basis import FiniteDimensionalAlgebrasWithBasis +from sage.categories.morphism import SetMorphism from sage.structure.element import is_Matrix from sage.structure.category_object import normalize_names from sage.algebras.finite_dimensional_algebras.finite_dimensional_algebra import FiniteDimensionalAlgebra from sage.algebras.finite_dimensional_algebras.finite_dimensional_algebra_element import FiniteDimensionalAlgebraElement +from sage.algebras.finite_dimensional_algebras.finite_dimensional_algebra_morphism import FiniteDimensionalAlgebraMorphism, FiniteDimensionalAlgebraHomset + + +class FiniteDimensionalEuclideanJordanAlgebraHomset(FiniteDimensionalAlgebraHomset): + + def has_coerce_map_from(self, S): + """ + EXAMPLES:: + + sage: J = RealSymmetricEJA(2) + sage: H = J.Hom(J) + sage: H.has_coerce_map_from(QQ) + True + + """ + try: + # The Homset classes override has_coerce_map_from() with + # something that crashes when it's given e.g. QQ. + if S.is_subring(self.codomain().base_ring()): + return True + except: + pclass = super(FiniteDimensionalEuclideanJordanAlgebraHomset, self) + return pclass.has_coerce_map_from(S) + + + def _coerce_map_from_(self, S): + """ + EXAMPLES:: + + sage: J = RealSymmetricEJA(2) + sage: H = J.Hom(J) + sage: H.coerce(2) + Morphism from Euclidean Jordan algebra of degree 3 over Rational + Field to Euclidean Jordan algebra of degree 3 over Rational Field + given by matrix + [2 0 0] + [0 2 0] + [0 0 2] + + """ + C = self.codomain() + R = C.base_ring() + if S.is_subring(R): + h = S.hom(self.codomain()) + return SetMorphism(Hom(S,C), lambda x: h(x).operator()) + + + def __call__(self, x): + """ + EXAMPLES:: + + sage: J = RealSymmetricEJA(2) + sage: H = J.Hom(J) + sage: H(2) + Morphism from Euclidean Jordan algebra of degree 3 over Rational + Field to Euclidean Jordan algebra of degree 3 over Rational Field + given by matrix + [2 0 0] + [0 2 0] + [0 0 2] + + """ + if x in self.base_ring(): + cols = self.domain().dimension() + rows = self.codomain().dimension() + x = x*identity_matrix(self.codomain().base_ring(), rows, cols) + return FiniteDimensionalEuclideanJordanAlgebraMorphism(self, x) + + + def one(self): + """ + Return the identity morphism, but as a member of the right + space (so that we can add it, multiply it, etc.) + """ + cols = self.domain().dimension() + rows = self.codomain().dimension() + mat = identity_matrix(self.base_ring(), rows, cols) + return FiniteDimensionalEuclideanJordanAlgebraMorphism(self, mat) + + + +class FiniteDimensionalEuclideanJordanAlgebraMorphism(FiniteDimensionalAlgebraMorphism): + """ + A linear map between two finite-dimensional EJAs. + + This is a very thin wrapper around FiniteDimensionalAlgebraMorphism + that does only a few things: + + 1. Avoids the ``unitary`` and ``check`` arguments to the constructor + that will always be ``False``. This is necessary because these + are homomorphisms with respect to ADDITION, but the SageMath + machinery wants to check that they're homomorphisms with respect + to (Jordan) MULTIPLICATION. That obviously doesn't work. + + 2. Inputs and outputs the underlying matrix with respect to COLUMN + vectors, unlike the parent class. + + 3. Allows us to add, subtract, negate, multiply (compose), and + invert morphisms in the obvious way. + + If this seems a bit heavyweight, it is. I would have been happy to + use a the ring morphism that underlies the finite-dimensional + algebra morphism, but they don't seem to be callable on elements of + our EJA, and you can't add/multiply/etc. them. + """ + def _add_(self, other): + """ + Add two EJA morphisms in the obvious way. + + EXAMPLES:: + + sage: J = RealSymmetricEJA(3) + sage: x = J.zero() + sage: y = J.one() + sage: x.operator() + y.operator() + Morphism from Euclidean Jordan algebra of degree 6 over Rational + Field to Euclidean Jordan algebra of degree 6 over Rational Field + given by matrix + [1 0 0 0 0 0] + [0 1 0 0 0 0] + [0 0 1 0 0 0] + [0 0 0 1 0 0] + [0 0 0 0 1 0] + [0 0 0 0 0 1] + + TESTS:: + + sage: set_random_seed() + sage: J = random_eja() + sage: x = J.random_element() + sage: y = J.random_element() + sage: (x.operator() + y.operator()) in J.Hom(J) + True + + """ + P = self.parent() + if not other in P: + raise ValueError("summands must live in the same space") + + return FiniteDimensionalEuclideanJordanAlgebraMorphism( + P, + self.matrix() + other.matrix() ) + + + def __init__(self, parent, f): + FiniteDimensionalAlgebraMorphism.__init__(self, + parent, + f.transpose(), + unitary=False, + check=False) + + + def __invert__(self): + """ + EXAMPLES:: + + sage: J = RealSymmetricEJA(2) + sage: x = J.linear_combination(zip(range(len(J.gens())), J.gens())) + sage: x.is_invertible() + True + sage: ~x.operator() + Morphism from Euclidean Jordan algebra of degree 3 over Rational + Field to Euclidean Jordan algebra of degree 3 over Rational Field + given by matrix + [-3/2 2 -1/2] + [ 1 0 0] + [-1/2 0 1/2] + sage: x.operator_matrix().inverse() + [-3/2 2 -1/2] + [ 1 0 0] + [-1/2 0 1/2] + + TESTS:: + + sage: set_random_seed() + sage: J = random_eja() + sage: x = J.random_element() + sage: not x.is_invertible() or ( + ....: (~x.operator()).matrix() == x.operator_matrix().inverse() ) + True + + """ + A = self.matrix() + if not A.is_invertible(): + raise ValueError("morphism is not invertible") + + P = self.parent() + return FiniteDimensionalEuclideanJordanAlgebraMorphism(self.parent(), + A.inverse()) + + def _lmul_(self, right): + """ + Compose two EJA morphisms using multiplicative notation. + + EXAMPLES:: + + sage: J = RealSymmetricEJA(2) + sage: x = J.zero() + sage: y = J.one() + sage: x.operator() * y.operator() + Morphism from Euclidean Jordan algebra of degree 3 over Rational + Field to Euclidean Jordan algebra of degree 3 over Rational Field + given by matrix + [0 0 0] + [0 0 0] + [0 0 0] + + :: + + sage: J = RealSymmetricEJA(2) + sage: x = J.linear_combination(zip(range(len(J.gens())), J.gens())) + sage: x.operator() + Morphism from Euclidean Jordan algebra of degree 3 over Rational + Field to Euclidean Jordan algebra of degree 3 over Rational Field + given by matrix + [ 0 1 0] + [1/2 1 1/2] + [ 0 1 2] + sage: 2*x.operator() + Morphism from Euclidean Jordan algebra of degree 3 over Rational + Field to Euclidean Jordan algebra of degree 3 over Rational Field + given by matrix + [0 2 0] + [1 2 1] + [0 2 4] + sage: x.operator()*2 + Morphism from Euclidean Jordan algebra of degree 3 over Rational + Field to Euclidean Jordan algebra of degree 3 over Rational Field + given by matrix + [0 2 0] + [1 2 1] + [0 2 4] + + TESTS:: + + sage: set_random_seed() + sage: J = random_eja() + sage: x = J.random_element() + sage: y = J.random_element() + sage: (x.operator() * y.operator()) in J.Hom(J) + True + + """ + try: + # I think the morphism classes break the coercion framework + # somewhere along the way, so we have to do this ourselves. + right = self.parent().coerce(right) + except: + pass + + if not right.codomain() is self.domain(): + raise ValueError("(co)domains must agree for composition") + + return FiniteDimensionalEuclideanJordanAlgebraMorphism( + self.parent(), + self.matrix()*right.matrix() ) + + __mul__ = _lmul_ + + + def __pow__(self, n): + """ + + TESTS:: + + sage: J = JordanSpinEJA(4) + sage: e0,e1,e2,e3 = J.gens() + sage: x = -5/2*e0 + 1/2*e2 + 20*e3 + sage: Qx = x.quadratic_representation() + sage: Qx^0 + Morphism from Euclidean Jordan algebra of degree 4 over Rational + Field to Euclidean Jordan algebra of degree 4 over Rational Field + given by matrix + [1 0 0 0] + [0 1 0 0] + [0 0 1 0] + [0 0 0 1] + sage: (x^0).quadratic_representation() == Qx^0 + True + + """ + if n == 0: + # We get back the stupid identity morphism which doesn't + # live in the right space. + return self.parent().one() + elif n == 1: + return self + else: + return FiniteDimensionalAlgebraMorphism.__pow__(self,n) + + + def _neg_(self): + """ + Negate this morphism. + + EXAMPLES:: + + sage: J = RealSymmetricEJA(2) + sage: x = J.one() + sage: -x.operator() + Morphism from Euclidean Jordan algebra of degree 3 over Rational + Field to Euclidean Jordan algebra of degree 3 over Rational Field + given by matrix + [-1 0 0] + [ 0 -1 0] + [ 0 0 -1] + + TESTS:: + + sage: set_random_seed() + sage: J = random_eja() + sage: x = J.random_element() + sage: -x.operator() in J.Hom(J) + True + + """ + return FiniteDimensionalEuclideanJordanAlgebraMorphism( + self.parent(), + -self.matrix() ) + + + def _repr_(self): + """ + We override only the representation that is shown to the user, + because we want the matrix to be with respect to COLUMN vectors. + + TESTS: + + Ensure that we see the transpose of the underlying matrix object: + + sage: J = RealSymmetricEJA(3) + sage: x = J.linear_combination(zip(range(len(J.gens())), J.gens())) + sage: L = x.operator() + sage: L + Morphism from Euclidean Jordan algebra of degree 6 over Rational + Field to Euclidean Jordan algebra of degree 6 over Rational Field + given by matrix + [ 0 1 2 0 0 0] + [1/2 3/2 2 1/2 1 0] + [ 1 2 5/2 0 1/2 1] + [ 0 1 0 3 4 0] + [ 0 1 1/2 2 4 2] + [ 0 0 2 0 4 5] + sage: L._matrix + [ 0 1/2 1 0 0 0] + [ 1 3/2 2 1 1 0] + [ 2 2 5/2 0 1/2 2] + [ 0 1/2 0 3 2 0] + [ 0 1 1/2 4 4 4] + [ 0 0 1 0 2 5] + + """ + return "Morphism from {} to {} given by matrix\n{}".format( + self.domain(), self.codomain(), self.matrix()) + + + def __sub__(self, other): + """ + Subtract one morphism from another using addition and negation. + + EXAMPLES:: + + sage: J = RealSymmetricEJA(2) + sage: L1 = J.one().operator() + sage: L1 - L1 + Morphism from Euclidean Jordan algebra of degree 3 over Rational + Field to Euclidean Jordan algebra of degree 3 over Rational + Field given by matrix + [0 0 0] + [0 0 0] + [0 0 0] + + TESTS:: + + sage: set_random_seed() + sage: J = random_eja() + sage: x = J.random_element() + sage: y = J.random_element() + sage: x.operator() - y.operator() in J.Hom(J) + True + + """ + return self + (-other) + + + def matrix(self): + """ + Return the matrix of this morphism with respect to a left-action + on column vectors. + """ + return FiniteDimensionalAlgebraMorphism.matrix(self).transpose() + class FiniteDimensionalEuclideanJordanAlgebra(FiniteDimensionalAlgebra): @staticmethod @@ -30,7 +423,7 @@ class FiniteDimensionalEuclideanJordanAlgebra(FiniteDimensionalAlgebra): raise ValueError("input is not a multiplication table") mult_table = tuple(mult_table) - cat = MagmaticAlgebras(field).FiniteDimensional().WithBasis() + cat = FiniteDimensionalAlgebrasWithBasis(field) cat.or_subcategory(category) if assume_associative: cat = cat.Associative() @@ -48,6 +441,15 @@ class FiniteDimensionalEuclideanJordanAlgebra(FiniteDimensionalAlgebra): natural_basis=natural_basis) + def _Hom_(self, B, cat): + """ + Construct a homset of ``self`` and ``B``. + """ + return FiniteDimensionalEuclideanJordanAlgebraHomset(self, + B, + category=cat) + + def __init__(self, field, mult_table, @@ -69,7 +471,6 @@ class FiniteDimensionalEuclideanJordanAlgebra(FiniteDimensionalAlgebra): True """ - self._charpoly = None # for caching self._rank = rank self._natural_basis = natural_basis self._multiplication_table = mult_table @@ -88,9 +489,132 @@ class FiniteDimensionalEuclideanJordanAlgebra(FiniteDimensionalAlgebra): return fmt.format(self.degree(), self.base_ring()) + def _a_regular_element(self): + """ + Guess a regular element. Needed to compute the basis for our + characteristic polynomial coefficients. + """ + gs = self.gens() + z = self.sum( (i+1)*gs[i] for i in range(len(gs)) ) + if not z.is_regular(): + raise ValueError("don't know a regular element") + return z + + + @cached_method + def _charpoly_basis_space(self): + """ + Return the vector space spanned by the basis used in our + characteristic polynomial coefficients. This is used not only to + compute those coefficients, but also any time we need to + evaluate the coefficients (like when we compute the trace or + determinant). + """ + z = self._a_regular_element() + V = z.vector().parent().ambient_vector_space() + V1 = V.span_of_basis( (z**k).vector() for k in range(self.rank()) ) + b = (V1.basis() + V1.complement().basis()) + return V.span_of_basis(b) + + + @cached_method + def _charpoly_coeff(self, i): + """ + Return the coefficient polynomial "a_{i}" of this algebra's + general characteristic polynomial. + + Having this be a separate cached method lets us compute and + store the trace/determinant (a_{r-1} and a_{0} respectively) + separate from the entire characteristic polynomial. + """ + (A_of_x, x, xr, detA) = self._charpoly_matrix_system() + R = A_of_x.base_ring() + if i >= self.rank(): + # Guaranteed by theory + return R.zero() + + # Danger: the in-place modification is done for performance + # reasons (reconstructing a matrix with huge polynomial + # entries is slow), but I don't know how cached_method works, + # so it's highly possible that we're modifying some global + # list variable by reference, here. In other words, you + # probably shouldn't call this method twice on the same + # algebra, at the same time, in two threads + Ai_orig = A_of_x.column(i) + A_of_x.set_column(i,xr) + numerator = A_of_x.det() + A_of_x.set_column(i,Ai_orig) + + # We're relying on the theory here to ensure that each a_i is + # indeed back in R, and the added negative signs are to make + # the whole charpoly expression sum to zero. + return R(-numerator/detA) + + + @cached_method + def _charpoly_matrix_system(self): + """ + Compute the matrix whose entries A_ij are polynomials in + X1,...,XN, the vector ``x`` of variables X1,...,XN, the vector + corresponding to `x^r` and the determinent of the matrix A = + [A_ij]. In other words, all of the fixed (cachable) data needed + to compute the coefficients of the characteristic polynomial. + """ + r = self.rank() + n = self.dimension() + + # Construct a new algebra over a multivariate polynomial ring... + 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) + + idmat = identity_matrix(J.base_ring(), n) + + W = self._charpoly_basis_space() + W = W.change_ring(R.fraction_field()) + # Starting with the standard coordinates x = (X1,X2,...,Xn) + # and then converting the entries to W-coordinates allows us + # to pass in the standard coordinates to the charpoly and get + # back the right answer. Specifically, with x = (X1,X2,...,Xn), + # we have + # + # W.coordinates(x^2) eval'd at (standard z-coords) + # = + # W-coords of (z^2) + # = + # W-coords of (standard coords of x^2 eval'd at std-coords of z) + # + # We want the middle equivalent thing in our matrix, but use + # the first equivalent thing instead so that we can pass in + # standard coordinates. + x = J(vector(R, R.gens())) + l1 = [column_matrix(W.coordinates((x**k).vector())) for k in range(r)] + l2 = [idmat.column(k-1).column() for k in range(r+1, n+1)] + A_of_x = block_matrix(R, 1, n, (l1 + l2)) + xr = W.coordinates((x**r).vector()) + return (A_of_x, x, xr, A_of_x.det()) + + + @cached_method def characteristic_polynomial(self): """ + + .. WARNING:: + + This implementation doesn't guarantee that the polynomial + denominator in the coefficients is not identically zero, so + theoretically it could crash. The way that this is handled + in e.g. Faraut and Koranyi is to use a basis that guarantees + the denominator is non-zero. But, doing so requires knowledge + of at least one regular element, and we don't even know how + to do that. The trade-off is that, if we use the standard basis, + the resulting polynomial will accept the "usual" coordinates. In + other words, we don't have to do a change of basis before e.g. + computing the trace or determinant. + EXAMPLES: The characteristic polynomial in the spin algebra is given in @@ -104,72 +628,22 @@ class FiniteDimensionalEuclideanJordanAlgebra(FiniteDimensionalAlgebra): t^2 - 2*t + 1 """ - if self._charpoly is not None: - return self._charpoly - r = self.rank() n = self.dimension() - # First, compute the basis B... - x0 = self.zero() - c = 1 - 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 = J.zero().vector().parent().ambient_vector_space() - W = V.span_of_basis(B) - - def e(k): - # The coordinates of e_k with respect to the basis B. - # But, the e_k are elements of B... - return identity_matrix(J.base_ring(), n).column(k-1).column() - - # A matrix implementation 1 - x = J(vector(R, R.gens())) - l1 = [column_matrix(W.coordinates((x**k).vector())) for k in range(r)] - l2 = [e(k) for k in range(r+1, n+1)] - 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_of_x.columns() - A_cols[i] = xr - numerator = column_matrix(A_of_x.base_ring(), A_cols).det() - ai = numerator/denominator - a.append(ai) + # The list of coefficient polynomials a_1, a_2, ..., a_n. + a = [ self._charpoly_coeff(i) for i in range(n) ] # 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. + R = a[0].parent() 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 @@ -181,8 +655,7 @@ class FiniteDimensionalEuclideanJordanAlgebra(FiniteDimensionalAlgebra): # 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 + return sum( a[k]*(t**k) for k in range(len(a)) ) def inner_product(self, x, y): @@ -269,6 +742,16 @@ class FiniteDimensionalEuclideanJordanAlgebra(FiniteDimensionalAlgebra): An element of a Euclidean Jordan algebra. """ + def __dir__(self): + """ + Oh man, I should not be doing this. This hides the "disabled" + methods ``left_matrix`` and ``matrix`` from introspection; + in particular it removes them from tab-completion. + """ + return filter(lambda s: s not in ['left_matrix', 'matrix'], + dir(self.__class__) ) + + def __init__(self, A, elt=None): """ EXAMPLES: @@ -410,17 +893,37 @@ class FiniteDimensionalEuclideanJordanAlgebra(FiniteDimensionalAlgebra): def characteristic_polynomial(self): """ - Return my characteristic polynomial (if I'm a regular - element). + Return the characteristic polynomial of this element. + + EXAMPLES: + + The rank of `R^3` is three, and the minimal polynomial of + the identity element is `(t-1)` from which it follows that + the characteristic polynomial should be `(t-1)^3`:: + + sage: J = RealCartesianProductEJA(3) + sage: J.one().characteristic_polynomial() + t^3 - 3*t^2 + 3*t - 1 + + Likewise, the characteristic of the zero element in the + rank-three algebra `R^{n}` should be `t^{3}`:: + + sage: J = RealCartesianProductEJA(3) + sage: J.zero().characteristic_polynomial() + t^3 + + The characteristic polynomial of an element should evaluate + to zero on that element:: + + sage: set_random_seed() + sage: x = RealCartesianProductEJA(3).random_element() + sage: p = x.characteristic_polynomial() + sage: x.apply_univariate_polynomial(p) + 0 - Eventually this should be implemented in terms of the parent - algebra's characteristic polynomial that works for ALL - elements. """ - if self.is_regular(): - return self.minimal_polynomial() - else: - raise NotImplementedError('irregular element') + p = self.parent().characteristic_polynomial() + return p(*self.vector()) def inner_product(self, other): @@ -530,30 +1033,47 @@ class FiniteDimensionalEuclideanJordanAlgebra(FiniteDimensionalAlgebra): sage: J = JordanSpinEJA(2) sage: e0,e1 = J.gens() - sage: x = e0 + e1 + sage: x = sum( J.gens() ) sage: x.det() 0 + + :: + sage: J = JordanSpinEJA(3) sage: e0,e1,e2 = J.gens() - sage: x = e0 + e1 + e2 + sage: x = sum( J.gens() ) sage: x.det() -1 + TESTS: + + An element is invertible if and only if its determinant is + non-zero:: + + sage: set_random_seed() + sage: x = random_eja().random_element() + sage: x.is_invertible() == (x.det() != 0) + True + """ - cs = self.characteristic_polynomial().coefficients(sparse=False) - r = len(cs) - 1 - if r >= 0: - return cs[0] * (-1)**r - else: - raise ValueError('charpoly had no coefficients') + P = self.parent() + r = P.rank() + p = P._charpoly_coeff(0) + # The _charpoly_coeff function already adds the factor of + # -1 to ensure that _charpoly_coeff(0) is really what + # appears in front of t^{0} in the charpoly. However, + # we want (-1)^r times THAT for the determinant. + return ((-1)**r)*p(*self.vector()) def inverse(self): """ Return the Jordan-multiplicative inverse of this element. - We can't use the superclass method because it relies on the - algebra being associative. + ALGORITHM: + + We appeal to the quadratic representation as in Koecher's + Theorem 12 in Chapter III, Section 5. EXAMPLES: @@ -564,12 +1084,12 @@ class FiniteDimensionalEuclideanJordanAlgebra(FiniteDimensionalAlgebra): sage: n = ZZ.random_element(1,10) sage: J = JordanSpinEJA(n) sage: x = J.random_element() - sage: while x.is_zero(): + sage: while not x.is_invertible(): ....: x = J.random_element() sage: x_vec = x.vector() sage: x0 = x_vec[0] sage: x_bar = x_vec[1:] - sage: coeff = 1/(x0^2 - x_bar.inner_product(x_bar)) + sage: coeff = ~(x0^2 - x_bar.inner_product(x_bar)) sage: inv_vec = x_vec.parent()([x0] + (-x_bar).list()) sage: x_inverse = coeff*inv_vec sage: x.inverse() == J(x_inverse) @@ -584,48 +1104,35 @@ class FiniteDimensionalEuclideanJordanAlgebra(FiniteDimensionalAlgebra): sage: J.one().inverse() == J.one() True - If an element has an inverse, it acts like one. TODO: this - can be a lot less ugly once ``is_invertible`` doesn't crash - on irregular elements:: + If an element has an inverse, it acts like one:: sage: set_random_seed() sage: J = random_eja() sage: x = J.random_element() - sage: try: - ....: x.inverse()*x == J.one() - ....: except: - ....: True + sage: (not x.is_invertible()) or (x.inverse()*x == J.one()) True - """ - if self.parent().is_associative(): - elt = FiniteDimensionalAlgebraElement(self.parent(), self) - return elt.inverse() + The inverse of the inverse is what we started with:: - # TODO: we can do better once the call to is_invertible() - # doesn't crash on irregular elements. - #if not self.is_invertible(): - # raise ValueError('element is not invertible') + sage: set_random_seed() + sage: J = random_eja() + sage: x = J.random_element() + sage: (not x.is_invertible()) or (x.inverse().inverse() == x) + True - # We do this a little different than the usual recursive - # call to a finite-dimensional algebra element, because we - # wind up with an inverse that lives in the subalgebra and - # we need information about the parent to convert it back. - V = self.span_of_powers() - assoc_subalg = self.subalgebra_generated_by() - # Mis-design warning: the basis used for span_of_powers() - # and subalgebra_generated_by() must be the same, and in - # the same order! - elt = assoc_subalg(V.coordinates(self.vector())) + The zero element is never invertible:: - # This will be in the subalgebra's coordinates... - fda_elt = FiniteDimensionalAlgebraElement(assoc_subalg, elt) - subalg_inverse = fda_elt.inverse() + sage: set_random_seed() + sage: J = random_eja().zero().inverse() + Traceback (most recent call last): + ... + ValueError: element is not invertible - # So we have to convert back... - basis = [ self.parent(v) for v in V.basis() ] - pairs = zip(subalg_inverse.vector(), basis) - return self.parent().linear_combination(pairs) + """ + if not self.is_invertible(): + raise ValueError("element is not invertible") + + return (~self.quadratic_representation())(self) def is_invertible(self): @@ -766,6 +1273,16 @@ class FiniteDimensionalEuclideanJordanAlgebra(FiniteDimensionalAlgebra): return self.span_of_powers().dimension() + def left_matrix(self): + """ + Our parent class defines ``left_matrix`` and ``matrix`` + methods whose names are misleading. We don't want them. + """ + raise NotImplementedError("use operator_matrix() instead") + + matrix = left_matrix + + def minimal_polynomial(self): """ Return the minimal polynomial of this element, @@ -887,14 +1404,37 @@ class FiniteDimensionalEuclideanJordanAlgebra(FiniteDimensionalAlgebra): return W.linear_combination(zip(self.vector(), B)) + def operator(self): + """ + Return the left-multiplication-by-this-element + operator on the ambient algebra. + + TESTS:: + + sage: set_random_seed() + sage: J = random_eja() + sage: x = J.random_element() + sage: y = J.random_element() + sage: x.operator()(y) == x*y + True + sage: y.operator()(x) == x*y + True + + """ + P = self.parent() + return FiniteDimensionalEuclideanJordanAlgebraMorphism( + Hom(P,P), + self.operator_matrix() ) + + + def operator_matrix(self): """ Return the matrix that represents left- (or right-) multiplication by this element in the parent algebra. - We have to override this because the superclass method - returns a matrix that acts on row vectors (that is, on - the right). + We implement this ourselves to work around the fact that + our parent class represents everything with row vectors. EXAMPLES: @@ -977,7 +1517,7 @@ class FiniteDimensionalEuclideanJordanAlgebra(FiniteDimensionalAlgebra): sage: D = (x0^2 - x_bar.inner_product(x_bar))*D sage: D = D + 2*x_bar.tensor_product(x_bar) sage: Q = block_matrix(2,2,[A,B,C,D]) - sage: Q == x.quadratic_representation() + sage: Q == x.quadratic_representation().matrix() True Test all of the properties from Theorem 11.2 in Alizadeh:: @@ -986,38 +1526,76 @@ class FiniteDimensionalEuclideanJordanAlgebra(FiniteDimensionalAlgebra): sage: J = random_eja() sage: x = J.random_element() sage: y = J.random_element() + sage: Lx = x.operator() + sage: Lxx = (x*x).operator() + sage: Qx = x.quadratic_representation() + sage: Qy = y.quadratic_representation() + sage: Qxy = x.quadratic_representation(y) + sage: Qex = J.one().quadratic_representation(x) + sage: n = ZZ.random_element(10) + sage: Qxn = (x^n).quadratic_representation() Property 1: - sage: actual = x.quadratic_representation(y) - sage: expected = ( (x+y).quadratic_representation() - ....: -x.quadratic_representation() - ....: -y.quadratic_representation() ) / 2 - sage: actual == expected + sage: 2*Qxy == (x+y).quadratic_representation() - Qx - Qy True Property 2: sage: alpha = QQ.random_element() - sage: actual = (alpha*x).quadratic_representation() - sage: expected = (alpha^2)*x.quadratic_representation() - sage: actual == expected + sage: (alpha*x).quadratic_representation() == (alpha^2)*Qx + True + + Property 3: + + sage: not x.is_invertible() or ( Qx(x.inverse()) == x ) + True + + sage: not x.is_invertible() or ( + ....: ~Qx + ....: == + ....: x.inverse().quadratic_representation() ) + True + + sage: Qxy(J.one()) == x*y + True + + Property 4: + + sage: not x.is_invertible() or ( + ....: x.quadratic_representation(x.inverse())*Qx + ....: == Qx*x.quadratic_representation(x.inverse()) ) + True + + sage: not x.is_invertible() or ( + ....: x.quadratic_representation(x.inverse())*Qx + ....: == + ....: 2*x.operator()*Qex - Qx ) + True + + sage: 2*x.operator()*Qex - Qx == Lxx True Property 5: - sage: Qy = y.quadratic_representation() - sage: actual = J(Qy*x.vector()).quadratic_representation() - sage: expected = Qy*x.quadratic_representation()*Qy - sage: actual == expected + sage: Qy(x).quadratic_representation() == Qy*Qx*Qy True Property 6: - sage: k = ZZ.random_element(1,10) - sage: actual = (x^k).quadratic_representation() - sage: expected = (x.quadratic_representation())^k - sage: actual == expected + sage: Qxn == (Qx)^n + True + + Property 7: + + sage: not x.is_invertible() or ( + ....: Qx*x.inverse().operator() == Lx ) + True + + Property 8: + + sage: not x.operator_commutes_with(y) or ( + ....: Qx(y)^n == Qxn(y^n) ) True """ @@ -1026,9 +1604,9 @@ class FiniteDimensionalEuclideanJordanAlgebra(FiniteDimensionalAlgebra): elif not other in self.parent(): raise TypeError("'other' must live in the same algebra") - L = self.operator_matrix() - M = other.operator_matrix() - return ( L*M + M*L - (self*other).operator_matrix() ) + L = self.operator() + M = other.operator() + return ( L*M + M*L - (self*other).operator() ) def span_of_powers(self): @@ -1111,12 +1689,11 @@ class FiniteDimensionalEuclideanJordanAlgebra(FiniteDimensionalAlgebra): TESTS:: sage: set_random_seed() - sage: J = RealCartesianProductEJA(5) - sage: c = J.random_element().subalgebra_idempotent() - sage: c^2 == c - True - sage: J = JordanSpinEJA(5) - sage: c = J.random_element().subalgebra_idempotent() + sage: J = random_eja() + sage: x = J.random_element() + sage: while x.is_nilpotent(): + ....: x = J.random_element() + sage: c = x.subalgebra_idempotent() sage: c^2 == c True @@ -1172,22 +1749,80 @@ class FiniteDimensionalEuclideanJordanAlgebra(FiniteDimensionalAlgebra): EXAMPLES:: sage: J = JordanSpinEJA(3) - sage: e0,e1,e2 = J.gens() - sage: x = e0 + e1 + e2 + sage: x = sum(J.gens()) sage: x.trace() 2 + :: + + sage: J = RealCartesianProductEJA(5) + sage: J.one().trace() + 5 + + TESTS: + + The trace of an element is a real number:: + + sage: set_random_seed() + sage: J = random_eja() + sage: J.random_element().trace() in J.base_ring() + True + """ - cs = self.characteristic_polynomial().coefficients(sparse=False) - if len(cs) >= 2: - return -1*cs[-2] - else: - raise ValueError('charpoly had fewer than 2 coefficients') + P = self.parent() + r = P.rank() + p = P._charpoly_coeff(r-1) + # The _charpoly_coeff function already adds the factor of + # -1 to ensure that _charpoly_coeff(r-1) is really what + # appears in front of t^{r-1} in the charpoly. However, + # we want the negative of THAT for the trace. + return -p(*self.vector()) def trace_inner_product(self, other): """ Return the trace inner product of myself and ``other``. + + TESTS: + + The trace inner product is commutative:: + + sage: set_random_seed() + sage: J = random_eja() + sage: x = J.random_element(); y = J.random_element() + sage: x.trace_inner_product(y) == y.trace_inner_product(x) + True + + The trace inner product is bilinear:: + + sage: set_random_seed() + sage: J = random_eja() + sage: x = J.random_element() + sage: y = J.random_element() + sage: z = J.random_element() + sage: a = QQ.random_element(); + sage: actual = (a*(x+z)).trace_inner_product(y) + sage: expected = ( a*x.trace_inner_product(y) + + ....: a*z.trace_inner_product(y) ) + sage: actual == expected + True + sage: actual = x.trace_inner_product(a*(y+z)) + sage: expected = ( a*x.trace_inner_product(y) + + ....: a*x.trace_inner_product(z) ) + sage: actual == expected + True + + The trace inner product satisfies the compatibility + condition in the definition of a Euclidean Jordan algebra:: + + sage: set_random_seed() + sage: J = random_eja() + sage: x = J.random_element() + sage: y = J.random_element() + sage: z = J.random_element() + sage: (x*y).trace_inner_product(z) == y.trace_inner_product(x*z) + True + """ if not other in self.parent(): raise TypeError("'other' must live in the same algebra")