names='e',
assume_associative=False,
category=None,
- rank=None):
+ rank=None,
+ natural_basis=None,
+ inner_product=None):
n = len(mult_table)
mult_table = [b.base_extend(field) for b in mult_table]
for b in mult_table:
assume_associative=assume_associative,
names=names,
category=cat,
- rank=rank)
+ rank=rank,
+ natural_basis=natural_basis,
+ inner_product=inner_product)
- def __init__(self, field,
+ def __init__(self,
+ field,
mult_table,
names='e',
assume_associative=False,
category=None,
- rank=None):
+ rank=None,
+ natural_basis=None,
+ inner_product=None):
+ """
+ EXAMPLES:
+
+ By definition, Jordan multiplication commutes::
+
+ sage: set_random_seed()
+ sage: J = random_eja()
+ sage: x = J.random_element()
+ sage: y = J.random_element()
+ sage: x*y == y*x
+ True
+
+ """
self._rank = rank
+ self._natural_basis = natural_basis
+ self._inner_product = inner_product
fda = super(FiniteDimensionalEuclideanJordanAlgebra, self)
fda.__init__(field,
mult_table,
fmt = "Euclidean Jordan algebra of degree {} over {}"
return fmt.format(self.degree(), self.base_ring())
+
+ def inner_product(self, x, y):
+ """
+ The inner product associated with this Euclidean Jordan algebra.
+
+ Will default to the trace inner product if nothing else.
+
+ EXAMPLES:
+
+ The inner product must satisfy its axiom for this algebra to truly
+ be 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).inner_product(z) == y.inner_product(x*z)
+ True
+
+ """
+ if (not x in self) or (not y in self):
+ raise TypeError("arguments must live in this algebra")
+ if self._inner_product is None:
+ return x.trace_inner_product(y)
+ else:
+ return self._inner_product(x,y)
+
+
+ def natural_basis(self):
+ """
+ Return a more-natural representation of this algebra's basis.
+
+ Every finite-dimensional Euclidean Jordan Algebra is a direct
+ sum of five simple algebras, four of which comprise Hermitian
+ matrices. This method returns the original "natural" basis
+ for our underlying vector space. (Typically, the natural basis
+ is used to construct the multiplication table in the first place.)
+
+ Note that this will always return a matrix. The standard basis
+ in `R^n` will be returned as `n`-by-`1` column matrices.
+
+ EXAMPLES::
+
+ sage: J = RealSymmetricEJA(2)
+ sage: J.basis()
+ Family (e0, e1, e2)
+ sage: J.natural_basis()
+ (
+ [1 0] [0 1] [0 0]
+ [0 0], [1 0], [0 1]
+ )
+
+ ::
+
+ sage: J = JordanSpinEJA(2)
+ sage: J.basis()
+ Family (e0, e1)
+ sage: J.natural_basis()
+ (
+ [1] [0]
+ [0], [1]
+ )
+
+ """
+ if self._natural_basis is None:
+ return tuple( b.vector().column() for b in self.basis() )
+ else:
+ return self._natural_basis
+
+
def rank(self):
"""
Return the rank of this EJA.
An element of a Euclidean Jordan algebra.
"""
+ def __init__(self, A, elt=None):
+ """
+ EXAMPLES:
+
+ The identity in `S^n` is converted to the identity in the EJA::
+
+ sage: J = RealSymmetricEJA(3)
+ sage: I = identity_matrix(QQ,3)
+ sage: J(I) == J.one()
+ True
+
+ This skew-symmetric matrix can't be represented in the EJA::
+
+ sage: J = RealSymmetricEJA(3)
+ sage: A = matrix(QQ,3, lambda i,j: i-j)
+ sage: J(A)
+ Traceback (most recent call last):
+ ...
+ ArithmeticError: vector is not in free module
+
+ """
+ # Goal: if we're given a matrix, and if it lives in our
+ # parent algebra's "natural ambient space," convert it
+ # into an algebra element.
+ #
+ # The catch is, we make a recursive call after converting
+ # the given matrix into a vector that lives in the algebra.
+ # This we need to try the parent class initializer first,
+ # to avoid recursing forever if we're given something that
+ # already fits into the algebra, but also happens to live
+ # in the parent's "natural ambient space" (this happens with
+ # vectors in R^n).
+ try:
+ FiniteDimensionalAlgebraElement.__init__(self, A, elt)
+ except ValueError:
+ natural_basis = A.natural_basis()
+ if elt in natural_basis[0].matrix_space():
+ # Thanks for nothing! Matrix spaces aren't vector
+ # spaces in Sage, so we have to figure out its
+ # natural-basis coordinates ourselves.
+ V = VectorSpace(elt.base_ring(), elt.nrows()**2)
+ W = V.span( _mat2vec(s) for s in natural_basis )
+ coords = W.coordinates(_mat2vec(elt))
+ FiniteDimensionalAlgebraElement.__init__(self, A, coords)
+
def __pow__(self, n):
"""
Return ``self`` raised to the power ``n``.
instead of column vectors! We, on the other hand, assume column
vectors everywhere.
- EXAMPLES:
+ EXAMPLES::
+
+ sage: set_random_seed()
+ sage: x = random_eja().random_element()
+ sage: x.operator_matrix()*x.vector() == (x^2).vector()
+ True
+
+ A few examples of power-associativity::
sage: set_random_seed()
sage: x = random_eja().random_element()
- sage: x.matrix()*x.vector() == (x**2).vector()
+ sage: x*(x*x)*(x*x) == x^5
+ True
+ sage: (x*x)*(x*x*x) == x^5
+ True
+
+ We also know that powers operator-commute (Koecher, Chapter
+ III, Corollary 1)::
+
+ sage: set_random_seed()
+ sage: x = random_eja().random_element()
+ sage: m = ZZ.random_element(0,10)
+ sage: n = ZZ.random_element(0,10)
+ sage: Lxm = (x^m).operator_matrix()
+ sage: Lxn = (x^n).operator_matrix()
+ sage: Lxm*Lxn == Lxn*Lxm
True
"""
elif n == 1:
return self
else:
- return A.element_class(A, (self.matrix()**(n-1))*self.vector())
+ return A( (self.operator_matrix()**(n-1))*self.vector() )
def characteristic_polynomial(self):
raise NotImplementedError('irregular element')
+ def inner_product(self, other):
+ """
+ Return the parent algebra's inner product of myself and ``other``.
+
+ EXAMPLES:
+
+ The inner product in the Jordan spin algebra is the usual
+ inner product on `R^n` (this example only works because the
+ basis for the Jordan algebra is the standard basis in `R^n`)::
+
+ sage: J = JordanSpinEJA(3)
+ sage: x = vector(QQ,[1,2,3])
+ sage: y = vector(QQ,[4,5,6])
+ sage: x.inner_product(y)
+ 32
+ sage: J(x).inner_product(J(y))
+ 32
+
+ The inner product on `S^n` is `<X,Y> = trace(X*Y)`, where
+ multiplication is the usual matrix multiplication in `S^n`,
+ so the inner product of the identity matrix with itself
+ should be the `n`::
+
+ sage: J = RealSymmetricEJA(3)
+ sage: J.one().inner_product(J.one())
+ 3
+
+ Likewise, the inner product on `C^n` is `<X,Y> =
+ Re(trace(X*Y))`, where we must necessarily take the real
+ part because the product of Hermitian matrices may not be
+ Hermitian::
+
+ sage: J = ComplexHermitianEJA(3)
+ sage: J.one().inner_product(J.one())
+ 3
+
+ Ditto for the quaternions::
+
+ sage: J = QuaternionHermitianEJA(3)
+ sage: J.one().inner_product(J.one())
+ 3
+
+ TESTS:
+
+ Ensure that we can always compute an inner product, and that
+ it gives us back a real number::
+
+ sage: set_random_seed()
+ sage: J = random_eja()
+ sage: x = J.random_element()
+ sage: y = J.random_element()
+ sage: x.inner_product(y) in RR
+ True
+
+ """
+ P = self.parent()
+ if not other in P:
+ raise TypeError("'other' must live in the same algebra")
+
+ return P.inner_product(self, other)
+
+
+ def operator_commutes_with(self, other):
+ """
+ Return whether or not this element operator-commutes
+ with ``other``.
+
+ EXAMPLES:
+
+ The definition of a Jordan algebra says that any element
+ operator-commutes with its square::
+
+ sage: set_random_seed()
+ sage: x = random_eja().random_element()
+ sage: x.operator_commutes_with(x^2)
+ True
+
+ TESTS:
+
+ Test Lemma 1 from Chapter III of Koecher::
+
+ sage: set_random_seed()
+ sage: J = random_eja()
+ sage: u = J.random_element()
+ sage: v = J.random_element()
+ sage: lhs = u.operator_commutes_with(u*v)
+ sage: rhs = v.operator_commutes_with(u^2)
+ sage: lhs == rhs
+ True
+
+ """
+ if not other in self.parent():
+ raise TypeError("'other' must live in the same algebra")
+
+ A = self.operator_matrix()
+ B = other.operator_matrix()
+ return (A*B == B*A)
+
+
def det(self):
"""
Return my determinant, the product of my eigenvalues.
EXAMPLES::
- sage: J = JordanSpinSimpleEJA(2)
+ sage: J = JordanSpinEJA(2)
sage: e0,e1 = J.gens()
sage: x = e0 + e1
sage: x.det()
0
- sage: J = JordanSpinSimpleEJA(3)
+ sage: J = JordanSpinEJA(3)
sage: e0,e1,e2 = J.gens()
sage: x = e0 + e1 + e2
sage: x.det()
raise ValueError('charpoly had no coefficients')
+ 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.
+
+ EXAMPLES:
+
+ The inverse in the spin factor algebra is given in Alizadeh's
+ Example 11.11::
+
+ sage: set_random_seed()
+ sage: n = ZZ.random_element(1,10)
+ sage: J = JordanSpinEJA(n)
+ sage: x = J.random_element()
+ sage: while x.is_zero():
+ ....: 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: inv_vec = x_vec.parent()([x0] + (-x_bar).list())
+ sage: x_inverse = coeff*inv_vec
+ sage: x.inverse() == J(x_inverse)
+ True
+
+ TESTS:
+
+ The identity element is its own inverse::
+
+ sage: set_random_seed()
+ sage: J = random_eja()
+ 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::
+
+ sage: set_random_seed()
+ sage: J = random_eja()
+ sage: x = J.random_element()
+ sage: try:
+ ....: x.inverse()*x == J.one()
+ ....: except:
+ ....: True
+ True
+
+ """
+ if self.parent().is_associative():
+ elt = FiniteDimensionalAlgebraElement(self.parent(), self)
+ return elt.inverse()
+
+ # 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')
+
+ # 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()))
+
+ # This will be in the subalgebra's coordinates...
+ fda_elt = FiniteDimensionalAlgebraElement(assoc_subalg, elt)
+ subalg_inverse = fda_elt.inverse()
+
+ # 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)
+
+
+ def is_invertible(self):
+ """
+ Return whether or not this element is invertible.
+
+ We can't use the superclass method because it relies on
+ the algebra being associative.
+ """
+ return not self.det().is_zero()
+
+
def is_nilpotent(self):
"""
Return whether or not some power of this element is zero.
The identity element always has degree one, but any element
linearly-independent from it is regular::
- sage: J = JordanSpinSimpleEJA(5)
+ sage: J = JordanSpinEJA(5)
sage: J.one().is_regular()
False
sage: e0, e1, e2, e3, e4 = J.gens() # e0 is the identity
EXAMPLES::
- sage: J = JordanSpinSimpleEJA(4)
+ sage: J = JordanSpinEJA(4)
sage: J.one().degree()
1
sage: e0,e1,e2,e3 = J.gens()
aren't multiples of the identity are regular::
sage: set_random_seed()
- sage: n = ZZ.random_element(1,10).abs()
- sage: J = JordanSpinSimpleEJA(n)
+ sage: n = ZZ.random_element(1,10)
+ sage: J = JordanSpinEJA(n)
sage: x = J.random_element()
sage: x == x.coefficient(0)*J.one() or x.degree() == 2
True
return self.span_of_powers().dimension()
- def 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).
- """
- fda_elt = FiniteDimensionalAlgebraElement(self.parent(), self)
- return fda_elt.matrix().transpose()
-
-
def minimal_polynomial(self):
"""
EXAMPLES::
identity::
sage: set_random_seed()
- sage: n = ZZ.random_element(2,10).abs()
- sage: J = JordanSpinSimpleEJA(n)
+ sage: n = ZZ.random_element(2,10)
+ sage: J = JordanSpinEJA(n)
sage: y = J.random_element()
sage: while y == y.coefficient(0)*J.one():
....: y = J.random_element()
return elt.minimal_polynomial()
+ def natural_representation(self):
+ """
+ Return a more-natural representation of this element.
+
+ Every finite-dimensional Euclidean Jordan Algebra is a
+ direct sum of five simple algebras, four of which comprise
+ Hermitian matrices. This method returns the original
+ "natural" representation of this element as a Hermitian
+ matrix, if it has one. If not, you get the usual representation.
+
+ EXAMPLES::
+
+ sage: J = ComplexHermitianEJA(3)
+ sage: J.one()
+ e0 + e5 + e8
+ sage: J.one().natural_representation()
+ [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]
+
+ ::
+
+ sage: J = QuaternionHermitianEJA(3)
+ sage: J.one()
+ e0 + e9 + e14
+ sage: J.one().natural_representation()
+ [1 0 0 0 0 0 0 0 0 0 0 0]
+ [0 1 0 0 0 0 0 0 0 0 0 0]
+ [0 0 1 0 0 0 0 0 0 0 0 0]
+ [0 0 0 1 0 0 0 0 0 0 0 0]
+ [0 0 0 0 1 0 0 0 0 0 0 0]
+ [0 0 0 0 0 1 0 0 0 0 0 0]
+ [0 0 0 0 0 0 1 0 0 0 0 0]
+ [0 0 0 0 0 0 0 1 0 0 0 0]
+ [0 0 0 0 0 0 0 0 1 0 0 0]
+ [0 0 0 0 0 0 0 0 0 1 0 0]
+ [0 0 0 0 0 0 0 0 0 0 1 0]
+ [0 0 0 0 0 0 0 0 0 0 0 1]
+
+ """
+ B = self.parent().natural_basis()
+ W = B[0].matrix_space()
+ return W.linear_combination(zip(self.vector(), B))
+
+
+ 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).
+
+ EXAMPLES:
+
+ Test the first polarization identity from my notes, Koecher Chapter
+ III, or from Baes (2.3)::
+
+ sage: set_random_seed()
+ sage: J = random_eja()
+ sage: x = J.random_element()
+ sage: y = J.random_element()
+ sage: Lx = x.operator_matrix()
+ sage: Ly = y.operator_matrix()
+ sage: Lxx = (x*x).operator_matrix()
+ sage: Lxy = (x*y).operator_matrix()
+ sage: bool(2*Lx*Lxy + Ly*Lxx == 2*Lxy*Lx + Lxx*Ly)
+ True
+
+ Test the second polarization identity from my notes or from
+ Baes (2.4)::
+
+ sage: set_random_seed()
+ sage: J = random_eja()
+ sage: x = J.random_element()
+ sage: y = J.random_element()
+ sage: z = J.random_element()
+ sage: Lx = x.operator_matrix()
+ sage: Ly = y.operator_matrix()
+ sage: Lz = z.operator_matrix()
+ sage: Lzy = (z*y).operator_matrix()
+ sage: Lxy = (x*y).operator_matrix()
+ sage: Lxz = (x*z).operator_matrix()
+ sage: bool(Lx*Lzy + Lz*Lxy + Ly*Lxz == Lzy*Lx + Lxy*Lz + Lxz*Ly)
+ True
+
+ Test the third polarization identity from my notes or from
+ Baes (2.5)::
+
+ sage: set_random_seed()
+ sage: J = random_eja()
+ sage: u = J.random_element()
+ sage: y = J.random_element()
+ sage: z = J.random_element()
+ sage: Lu = u.operator_matrix()
+ sage: Ly = y.operator_matrix()
+ sage: Lz = z.operator_matrix()
+ sage: Lzy = (z*y).operator_matrix()
+ sage: Luy = (u*y).operator_matrix()
+ sage: Luz = (u*z).operator_matrix()
+ sage: Luyz = (u*(y*z)).operator_matrix()
+ sage: lhs = Lu*Lzy + Lz*Luy + Ly*Luz
+ sage: rhs = Luyz + Ly*Lu*Lz + Lz*Lu*Ly
+ sage: bool(lhs == rhs)
+ True
+
+ """
+ fda_elt = FiniteDimensionalAlgebraElement(self.parent(), self)
+ return fda_elt.matrix().transpose()
+
+
def quadratic_representation(self, other=None):
"""
Return the quadratic representation of this element.
Alizadeh's Example 11.12::
sage: set_random_seed()
- sage: n = ZZ.random_element(1,10).abs()
- sage: J = JordanSpinSimpleEJA(n)
+ sage: n = ZZ.random_element(1,10)
+ sage: J = JordanSpinEJA(n)
sage: x = J.random_element()
sage: x_vec = x.vector()
sage: x0 = x_vec[0]
Property 6:
- sage: k = ZZ.random_element(1,10).abs()
+ sage: k = ZZ.random_element(1,10)
sage: actual = (x^k).quadratic_representation()
sage: expected = (x.quadratic_representation())^k
sage: actual == expected
if other is None:
other=self
elif not other in self.parent():
- raise ArgumentError("'other' must live in the same algebra")
+ raise TypeError("'other' must live in the same algebra")
- return ( self.matrix()*other.matrix()
- + other.matrix()*self.matrix()
- - (self*other).matrix() )
+ L = self.operator_matrix()
+ M = other.operator_matrix()
+ return ( L*M + M*L - (self*other).operator_matrix() )
def span_of_powers(self):
sage: set_random_seed()
sage: x = random_eja().random_element()
sage: u = x.subalgebra_generated_by().random_element()
- sage: u.matrix()*u.vector() == (u**2).vector()
+ sage: u.operator_matrix()*u.vector() == (u**2).vector()
True
"""
sage: c = J.random_element().subalgebra_idempotent()
sage: c^2 == c
True
- sage: J = JordanSpinSimpleEJA(5)
+ sage: J = JordanSpinEJA(5)
sage: c = J.random_element().subalgebra_idempotent()
sage: c^2 == c
True
s = 0
minimal_dim = V.dimension()
for i in xrange(1, V.dimension()):
- this_dim = (u**i).matrix().image().dimension()
+ this_dim = (u**i).operator_matrix().image().dimension()
if this_dim < minimal_dim:
minimal_dim = this_dim
s = i
# Beware, solve_right() means that we're using COLUMN vectors.
# Our FiniteDimensionalAlgebraElement superclass uses rows.
u_next = u**(s+1)
- A = u_next.matrix()
+ A = u_next.operator_matrix()
c_coordinates = A.solve_right(u_next.vector())
# Now c_coordinates is the idempotent we want, but it's in
EXAMPLES::
- sage: J = JordanSpinSimpleEJA(3)
+ sage: J = JordanSpinEJA(3)
sage: e0,e1,e2 = J.gens()
sage: x = e0 + e1 + e2
sage: x.trace()
Return the trace inner product of myself and ``other``.
"""
if not other in self.parent():
- raise ArgumentError("'other' must live in the same algebra")
+ raise TypeError("'other' must live in the same algebra")
return (self*other).trace()
Qs = [ matrix(field, dimension, dimension, lambda k,j: 1*(k == j == i))
for i in xrange(dimension) ]
- return FiniteDimensionalEuclideanJordanAlgebra(field,Qs,rank=dimension)
+ return FiniteDimensionalEuclideanJordanAlgebra(field,
+ Qs,
+ rank=dimension,
+ inner_product=_usual_ip)
* The ``n``-by-``n`` rational symmetric matrices with the symmetric
product.
+ * The ``n``-by-``n`` complex-rational Hermitian matrices embedded
+ in the space of ``2n``-by-``2n`` real symmetric matrices.
+
+ * The ``n``-by-``n`` quaternion-rational Hermitian matrices embedded
+ in the space of ``4n``-by-``4n`` real symmetric matrices.
+
Later this might be extended to return Cartesian products of the
EJAs above.
Euclidean Jordan algebra of degree...
"""
- n = ZZ.random_element(1,5).abs()
+ n = ZZ.random_element(1,5)
constructor = choice([eja_rn,
- JordanSpinSimpleEJA,
- RealSymmetricSimpleEJA,
- ComplexHermitianSimpleEJA])
+ JordanSpinEJA,
+ RealSymmetricEJA,
+ ComplexHermitianEJA,
+ QuaternionHermitianEJA])
return constructor(n, field=QQ)
# Beware, orthogonal but not normalized!
Sij = Eij + Eij.transpose()
S.append(Sij)
- return S
+ return tuple(S)
def _complex_hermitian_basis(n, field=QQ):
TESTS::
sage: set_random_seed()
- sage: n = ZZ.random_element(1,5).abs()
+ sage: n = ZZ.random_element(1,5)
sage: all( M.is_symmetric() for M in _complex_hermitian_basis(n) )
True
S.append(Sij_real)
Sij_imag = _embed_complex_matrix(I*Eij - I*Eij.transpose())
S.append(Sij_imag)
- return S
+ return tuple(S)
+
+
+def _quaternion_hermitian_basis(n, field=QQ):
+ """
+ Returns a basis for the space of quaternion Hermitian n-by-n matrices.
+
+ TESTS::
+
+ sage: set_random_seed()
+ sage: n = ZZ.random_element(1,5)
+ sage: all( M.is_symmetric() for M in _quaternion_hermitian_basis(n) )
+ True
+
+ """
+ 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 = []
+ for i in xrange(n):
+ for j in xrange(i+1):
+ Eij = matrix(Q, n, lambda k,l: k==i and l==j)
+ if i == j:
+ Sij = _embed_quaternion_matrix(Eij)
+ S.append(Sij)
+ else:
+ # Beware, orthogonal but not normalized! The second,
+ # third, and fourth ones have a minus because they're
+ # conjugated.
+ Sij_real = _embed_quaternion_matrix(Eij + Eij.transpose())
+ S.append(Sij_real)
+ Sij_I = _embed_quaternion_matrix(I*Eij - I*Eij.transpose())
+ S.append(Sij_I)
+ Sij_J = _embed_quaternion_matrix(J*Eij - J*Eij.transpose())
+ S.append(Sij_J)
+ Sij_K = _embed_quaternion_matrix(K*Eij - K*Eij.transpose())
+ S.append(Sij_K)
+ return tuple(S)
+
+def _mat2vec(m):
+ return vector(m.base_ring(), m.list())
+
+def _vec2mat(v):
+ return matrix(v.base_ring(), sqrt(v.degree()), v.list())
def _multiplication_table_from_matrix_basis(basis):
"""
multiplication on the right is matrix multiplication. Given a basis
for the underlying matrix space, this function returns a
multiplication table (obtained by looping through the basis
- elements) for an algebra of those matrices.
+ elements) for an algebra of those matrices. A reordered copy
+ of the basis is also returned to work around the fact that
+ the ``span()`` in this function will change the order of the basis
+ from what we think it is, to... something else.
"""
# In S^2, for example, we nominally have four coordinates even
# though the space is of dimension three only. The vector space V
field = basis[0].base_ring()
dimension = basis[0].nrows()
- def mat2vec(m):
- return vector(field, m.list())
-
- def vec2mat(v):
- return matrix(field, dimension, v.list())
-
V = VectorSpace(field, dimension**2)
- W = V.span( mat2vec(s) for s in basis )
+ W = V.span( _mat2vec(s) for s in basis )
# Taking the span above reorders our basis (thanks, jerk!) so we
# need to put our "matrix basis" in the same order as the
# (reordered) vector basis.
- S = [ vec2mat(b) for b in W.basis() ]
+ S = tuple( _vec2mat(b) for b in W.basis() )
Qs = []
for s in S:
# why we're computing rows here and not columns.
Q_rows = []
for t in S:
- this_row = mat2vec((s*t + t*s)/2)
+ this_row = _mat2vec((s*t + t*s)/2)
Q_rows.append(W.coordinates(this_row))
Q = matrix(field, W.dimension(), Q_rows)
Qs.append(Q)
- return Qs
+ return (Qs, S)
def _embed_complex_matrix(M):
sage: x2 = F(1 + 2*i)
sage: x3 = F(-i)
sage: x4 = F(6)
- sage: M = matrix(F,2,[x1,x2,x3,x4])
+ sage: M = matrix(F,2,[[x1,x2],[x3,x4]])
sage: _embed_complex_matrix(M)
- [ 4 2| 1 -2]
- [-2 4| 2 1]
+ [ 4 -2| 1 2]
+ [ 2 4|-2 1]
[-----+-----]
- [ 0 1| 6 0]
- [-1 0| 0 6]
+ [ 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(5)
+ sage: F = QuadraticField(-1, 'i')
+ sage: X = random_matrix(F, n)
+ sage: Y = random_matrix(F, n)
+ sage: actual = _embed_complex_matrix(X) * _embed_complex_matrix(Y)
+ sage: expected = _embed_complex_matrix(X*Y)
+ sage: actual == expected
+ True
"""
n = M.nrows()
if M.ncols() != n:
- raise ArgumentError("the matrix 'M' must be square")
+ raise ValueError("the matrix 'M' must be square")
field = M.base_ring()
blocks = []
for z in M.list():
a = z.real()
b = z.imag()
- blocks.append(matrix(field, 2, [[a,-b],[b,a]]))
+ blocks.append(matrix(field, 2, [[a,b],[-b,a]]))
# We can drop the imaginaries here.
return block_matrix(field.base_ring(), n, blocks)
....: [ 9, 10, 11, 12],
....: [-10, 9, -12, 11] ])
sage: _unembed_complex_matrix(A)
- [ -2*i + 1 -4*i + 3]
- [ -10*i + 9 -12*i + 11]
+ [ 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: _unembed_complex_matrix(_embed_complex_matrix(M)) == M
+ True
+
"""
n = ZZ(M.nrows())
if M.ncols() != n:
- raise ArgumentError("the matrix 'M' must be square")
+ raise ValueError("the matrix 'M' must be square")
if not n.mod(2).is_zero():
- raise ArgumentError("the matrix 'M' must be a complex embedding")
+ raise ValueError("the matrix 'M' must be a complex embedding")
F = QuadraticField(-1, 'i')
i = F.gen()
for j in xrange(n/2):
submat = M[2*k:2*k+2,2*j:2*j+2]
if submat[0,0] != submat[1,1]:
- raise ArgumentError('bad real submatrix')
+ raise ValueError('bad on-diagonal submatrix')
if submat[0,1] != -submat[1,0]:
- raise ArgumentError('bad imag submatrix')
- z = submat[0,0] + submat[1,0]*i
+ raise ValueError('bad off-diagonal submatrix')
+ z = submat[0,0] + submat[0,1]*i
elements.append(z)
return matrix(F, n/2, elements)
-def RealSymmetricSimpleEJA(n, field=QQ):
+def _embed_quaternion_matrix(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.
+
+ 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: _embed_quaternion_matrix(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(5)
+ sage: Q = QuaternionAlgebra(QQ,-1,-1)
+ sage: X = random_matrix(Q, n)
+ sage: Y = random_matrix(Q, n)
+ sage: actual = _embed_quaternion_matrix(X)*_embed_quaternion_matrix(Y)
+ sage: expected = _embed_quaternion_matrix(X*Y)
+ sage: actual == expected
+ True
+
+ """
+ quaternions = M.base_ring()
+ n = M.nrows()
+ if M.ncols() != n:
+ raise ValueError("the matrix 'M' must be square")
+
+ 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]
+ cplx_matrix = matrix(F, 2, [[ a + b*i, c + d*i],
+ [-c + d*i, a - b*i]])
+ blocks.append(_embed_complex_matrix(cplx_matrix))
+
+ # We should have real entries by now, so use the realest field
+ # we've got for the return value.
+ return block_matrix(quaternions.base_ring(), n, blocks)
+
+
+def _unembed_quaternion_matrix(M):
+ """
+ The inverse of _embed_quaternion_matrix().
+
+ EXAMPLES::
+
+ sage: M = matrix(QQ, [[ 1, 2, 3, 4],
+ ....: [-2, 1, -4, 3],
+ ....: [-3, 4, 1, -2],
+ ....: [-4, -3, 2, 1]])
+ sage: _unembed_quaternion_matrix(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: _unembed_quaternion_matrix(_embed_quaternion_matrix(M)) == M
+ True
+
+ """
+ n = ZZ(M.nrows())
+ if M.ncols() != n:
+ raise ValueError("the matrix 'M' must be square")
+ if not n.mod(4).is_zero():
+ raise ValueError("the matrix 'M' must be a complex embedding")
+
+ Q = QuaternionAlgebra(QQ,-1,-1)
+ 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 xrange(n/4):
+ for m in xrange(n/4):
+ submat = _unembed_complex_matrix(M[4*l:4*l+4,4*m:4*m+4])
+ 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() + submat[0,0].imag()*i
+ z += submat[0,1].real()*j + submat[0,1].imag()*k
+ elements.append(z)
+
+ return matrix(Q, n/4, elements)
+
+
+# The usual inner product on R^n.
+def _usual_ip(x,y):
+ return x.vector().inner_product(y.vector())
+
+# The inner product used for the real symmetric simple EJA.
+# We keep it as a separate function because e.g. the complex
+# algebra uses the same inner product, except divided by 2.
+def _matrix_ip(X,Y):
+ X_mat = X.natural_representation()
+ Y_mat = Y.natural_representation()
+ return (X_mat*Y_mat).trace()
+
+
+class RealSymmetricEJA(FiniteDimensionalEuclideanJordanAlgebra):
"""
The rank-n simple EJA consisting of real symmetric n-by-n
matrices, the usual symmetric Jordan product, and the trace inner
EXAMPLES::
- sage: J = RealSymmetricSimpleEJA(2)
+ sage: J = RealSymmetricEJA(2)
sage: e0, e1, e2 = J.gens()
sage: e0*e0
e0
The degree of this algebra is `(n^2 + n) / 2`::
sage: set_random_seed()
- sage: n = ZZ.random_element(1,5).abs()
- sage: J = RealSymmetricSimpleEJA(n)
+ sage: n = ZZ.random_element(1,5)
+ sage: J = RealSymmetricEJA(n)
sage: J.degree() == (n^2 + n)/2
True
+ The Jordan multiplication is what we think it is::
+
+ sage: set_random_seed()
+ sage: n = ZZ.random_element(1,5)
+ sage: J = RealSymmetricEJA(n)
+ sage: x = J.random_element()
+ sage: y = J.random_element()
+ sage: actual = (x*y).natural_representation()
+ sage: X = x.natural_representation()
+ sage: Y = y.natural_representation()
+ sage: expected = (X*Y + Y*X)/2
+ sage: actual == expected
+ True
+ sage: J(expected) == x*y
+ True
+
"""
- S = _real_symmetric_basis(n, field=field)
- Qs = _multiplication_table_from_matrix_basis(S)
+ @staticmethod
+ def __classcall_private__(cls, n, field=QQ):
+ S = _real_symmetric_basis(n, field=field)
+ (Qs, T) = _multiplication_table_from_matrix_basis(S)
- return FiniteDimensionalEuclideanJordanAlgebra(field,Qs,rank=n)
+ fdeja = super(RealSymmetricEJA, cls)
+ return fdeja.__classcall_private__(cls,
+ field,
+ Qs,
+ rank=n,
+ natural_basis=T)
+ def inner_product(self, x, y):
+ return _matrix_ip(x,y)
-def ComplexHermitianSimpleEJA(n, field=QQ):
+
+class ComplexHermitianEJA(FiniteDimensionalEuclideanJordanAlgebra):
"""
The rank-n simple EJA consisting of complex Hermitian n-by-n
matrices over the real numbers, the usual symmetric Jordan product,
The degree of this algebra is `n^2`::
sage: set_random_seed()
- sage: n = ZZ.random_element(1,5).abs()
- sage: J = ComplexHermitianSimpleEJA(n)
+ sage: n = ZZ.random_element(1,5)
+ sage: J = ComplexHermitianEJA(n)
sage: J.degree() == n^2
True
- """
- S = _complex_hermitian_basis(n)
- Qs = _multiplication_table_from_matrix_basis(S)
- return FiniteDimensionalEuclideanJordanAlgebra(field, Qs, rank=n)
+ The Jordan multiplication is what we think it is::
+ sage: set_random_seed()
+ sage: n = ZZ.random_element(1,5)
+ sage: J = ComplexHermitianEJA(n)
+ sage: x = J.random_element()
+ sage: y = J.random_element()
+ sage: actual = (x*y).natural_representation()
+ sage: X = x.natural_representation()
+ sage: Y = y.natural_representation()
+ sage: expected = (X*Y + Y*X)/2
+ sage: actual == expected
+ True
+ sage: J(expected) == x*y
+ True
-def QuaternionHermitianSimpleEJA(n):
+ """
+ @staticmethod
+ def __classcall_private__(cls, n, field=QQ):
+ S = _complex_hermitian_basis(n)
+ (Qs, T) = _multiplication_table_from_matrix_basis(S)
+
+ fdeja = super(ComplexHermitianEJA, cls)
+ return fdeja.__classcall_private__(cls,
+ field,
+ Qs,
+ rank=n,
+ natural_basis=T)
+
+ def inner_product(self, x, y):
+ # Since a+bi on the diagonal is represented as
+ #
+ # a + bi = [ a b ]
+ # [ -b a ],
+ #
+ # we'll double-count the "a" entries if we take the trace of
+ # the embedding.
+ return _matrix_ip(x,y)/2
+
+
+class QuaternionHermitianEJA(FiniteDimensionalEuclideanJordanAlgebra):
"""
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.
- """
- pass
-def OctonionHermitianSimpleEJA(n):
- """
- This shit be crazy. It has dimension 27 over the reals.
- """
- n = 3
- pass
+ TESTS:
+
+ The degree of this algebra is `n^2`::
+
+ sage: set_random_seed()
+ sage: n = ZZ.random_element(1,5)
+ sage: J = QuaternionHermitianEJA(n)
+ sage: J.degree() == 2*(n^2) - n
+ True
+
+ The Jordan multiplication is what we think it is::
-def JordanSpinSimpleEJA(n, field=QQ):
+ sage: set_random_seed()
+ sage: n = ZZ.random_element(1,5)
+ sage: J = QuaternionHermitianEJA(n)
+ sage: x = J.random_element()
+ sage: y = J.random_element()
+ sage: actual = (x*y).natural_representation()
+ sage: X = x.natural_representation()
+ sage: Y = y.natural_representation()
+ sage: expected = (X*Y + Y*X)/2
+ sage: actual == expected
+ True
+ sage: J(expected) == x*y
+ True
+
+ """
+ @staticmethod
+ def __classcall_private__(cls, n, field=QQ):
+ S = _quaternion_hermitian_basis(n)
+ (Qs, T) = _multiplication_table_from_matrix_basis(S)
+
+ fdeja = super(QuaternionHermitianEJA, cls)
+ return fdeja.__classcall_private__(cls,
+ field,
+ Qs,
+ rank=n,
+ natural_basis=T)
+
+ def inner_product(self, x, y):
+ # Since a+bi+cj+dk on the diagonal is represented as
+ #
+ # a + bi +cj + dk = [ a b c d]
+ # [ -b a -d c]
+ # [ -c d a -b]
+ # [ -d -c b a],
+ #
+ # we'll quadruple-count the "a" entries if we take the trace of
+ # the embedding.
+ return _matrix_ip(x,y)/4
+
+
+class JordanSpinEJA(FiniteDimensionalEuclideanJordanAlgebra):
"""
The rank-2 simple EJA consisting of real vectors ``x=(x0, x_bar)``
with the usual inner product and jordan product ``x*y =
This multiplication table can be verified by hand::
- sage: J = JordanSpinSimpleEJA(4)
+ sage: J = JordanSpinEJA(4)
sage: e0,e1,e2,e3 = J.gens()
sage: e0*e0
e0
sage: e2*e3
0
- In one dimension, this is the reals under multiplication::
+ """
+ @staticmethod
+ def __classcall_private__(cls, n, field=QQ):
+ Qs = []
+ id_matrix = identity_matrix(field, n)
+ for i in xrange(n):
+ ei = id_matrix.column(i)
+ Qi = zero_matrix(field, n)
+ Qi.set_row(0, ei)
+ Qi.set_column(0, ei)
+ Qi += diagonal_matrix(n, [ei[0]]*n)
+ # The addition of the diagonal matrix adds an extra ei[0] in the
+ # upper-left corner of the matrix.
+ Qi[0,0] = Qi[0,0] * ~field(2)
+ Qs.append(Qi)
+
+ fdeja = super(JordanSpinEJA, cls)
+ return fdeja.__classcall_private__(cls, field, Qs)
+
+ def rank(self):
+ """
+ Return the rank of this Jordan Spin Algebra.
- sage: J1 = JordanSpinSimpleEJA(1)
- sage: J2 = eja_rn(1)
- sage: J1 == J2
- True
+ The rank of the spin algebra is two, unless we're in a
+ one-dimensional ambient space (because the rank is bounded by
+ the ambient dimension).
+ """
+ return min(self.dimension(),2)
- """
- Qs = []
- id_matrix = identity_matrix(field, n)
- for i in xrange(n):
- ei = id_matrix.column(i)
- Qi = zero_matrix(field, n)
- Qi.set_row(0, ei)
- Qi.set_column(0, ei)
- Qi += diagonal_matrix(n, [ei[0]]*n)
- # The addition of the diagonal matrix adds an extra ei[0] in the
- # upper-left corner of the matrix.
- Qi[0,0] = Qi[0,0] * ~field(2)
- Qs.append(Qi)
-
- # The rank of the spin factor algebra is two, UNLESS we're in a
- # one-dimensional ambient space (the rank is bounded by the
- # ambient dimension).
- return FiniteDimensionalEuclideanJordanAlgebra(field, Qs, rank=min(n,2))
+ def inner_product(self, x, y):
+ return _usual_ip(x,y)