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
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()
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,
return fmt.format(self.degree(), self.base_ring())
- def characteristic_polynomial(self):
+ 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)
- x0 = J.zero()
- c = 1
- for g in J.gens():
- x0 += c*g
- c +=1
- if not x0.is_regular():
- raise ValueError("don't know a regular element")
- # Get the vector space (as opposed to module) so that
- # span_of_basis() works.
- V = x0.vector().parent().ambient_vector_space()
- V1 = V.span_of_basis( (x0**k).vector() for k in range(r) )
- B = V1.basis() + V1.complement().basis()
- W = V.span_of_basis(B)
+ idmat = identity_matrix(J.base_ring(), n)
- 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()
+ W = self._charpoly_basis_space()
+ W = W.change_ring(R.fraction_field())
- # A matrix implementation 1
+ # 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 = [e(k) for k in range(r+1, n+1)]
- A_of_x = block_matrix(1, n, (l1 + l2))
+ 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())
- a = []
- for i in range(n):
- A_cols = A.columns()
- A_cols[i] = xr
- numerator = column_matrix(A.base_ring(), A_cols).det()
- denominator = A.det()
- ai = numerator/denominator
- a.append(ai)
+ return (A_of_x, x, xr, A_of_x.det())
+
+
+ @cached_method
+ def characteristic_polynomial(self):
+ """
- # Note: all entries past the rth should be zero.
- return a
+ .. 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
+ Alizadeh, Example 11.11::
+
+ sage: J = JordanSpinEJA(3)
+ sage: p = J.characteristic_polynomial(); p
+ X1^2 - X2^2 - X3^2 + (-2*t)*X1 + t^2
+ sage: xvec = J.one().vector()
+ sage: p(*xvec)
+ t^2 - 2*t + 1
+
+ """
+ r = self.rank()
+ n = self.dimension()
+
+ # 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)
+
+ # Note: all entries past the rth should be zero. The
+ # coefficient of the highest power (x^r) is 1, but it doesn't
+ # appear in the solution vector which contains coefficients
+ # for the other powers (to make them sum to x^r).
+ if (r < n):
+ a[r] = 1 # corresponds to x^r
+ else:
+ # When the rank is equal to the dimension, trying to
+ # assign a[r] goes out-of-bounds.
+ a.append(1) # corresponds to x^r
+
+ return sum( a[k]*(t**k) for k in range(len(a)) )
def inner_product(self, x, y):
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:
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):
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:
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)
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
+
+ """
+ if not self.is_invertible():
+ raise 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)
+ return (~self.quadratic_representation())(self)
def is_invertible(self):
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,
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:
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::
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
"""
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):
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
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")
projects / sage.d.git / blobdiff