X-Git-Url: http://gitweb.michael.orlitzky.com/?a=blobdiff_plain;f=mjo%2Feja%2Feuclidean_jordan_algebra.py;h=be281bfb99d0ef86e73fa7d4a2d3643f54d605e3;hb=83f719b66100fdb5bf5035355c48b5337be6b11e;hp=5ccf2f29fd480f4a499d55fc3d9dad85942dc6f4;hpb=99a85a92ed375722e51f7842dcc8d370b134629b;p=sage.d.git diff --git a/mjo/eja/euclidean_jordan_algebra.py b/mjo/eja/euclidean_jordan_algebra.py index 5ccf2f2..be281bf 100644 --- a/mjo/eja/euclidean_jordan_algebra.py +++ b/mjo/eja/euclidean_jordan_algebra.py @@ -7,10 +7,37 @@ what can be supported in a general Jordan Algebra. from sage.all import * +def eja_minimal_polynomial(x): + """ + Return the minimal polynomial of ``x`` in its parent EJA + """ + return x._x.matrix().minimal_polynomial() + + def eja_rn(dimension, field=QQ): """ Return the Euclidean Jordan Algebra corresponding to the set `R^n` under the Hadamard product. + + EXAMPLES: + + This multiplication table can be verified by hand:: + + sage: J = eja_rn(3) + sage: e0,e1,e2 = J.gens() + sage: e0*e0 + e0 + sage: e0*e1 + 0 + sage: e0*e2 + 0 + sage: e1*e1 + e1 + sage: e1*e2 + 0 + sage: e2*e2 + e2 + """ # The FiniteDimensionalAlgebra constructor takes a list of # matrices, the ith representing right multiplication by the ith @@ -21,3 +48,54 @@ def eja_rn(dimension, field=QQ): for i in xrange(dimension) ] A = FiniteDimensionalAlgebra(QQ,Qs,assume_associative=True) return JordanAlgebra(A) + + +def eja_ln(dimension, field=QQ): + """ + Return the Jordan algebra corresponding to the Lorenzt "ice cream" + cone of the given ``dimension``. + + EXAMPLES: + + This multiplication table can be verified by hand:: + + sage: J = eja_ln(4) + sage: e0,e1,e2,e3 = J.gens() + sage: e0*e0 + e0 + sage: e0*e1 + e1 + sage: e0*e2 + e2 + sage: e0*e3 + e3 + sage: e1*e2 + 0 + sage: e1*e3 + 0 + sage: e2*e3 + 0 + + In one dimension, this is the reals under multiplication:: + + sage: J1 = eja_ln(1) + sage: J2 = eja_rn(1) + sage: J1 == J2 + True + + """ + Qs = [] + id_matrix = identity_matrix(field,dimension) + for i in xrange(dimension): + ei = id_matrix.column(i) + Qi = zero_matrix(field,dimension) + Qi.set_row(0, ei) + Qi.set_column(0, ei) + Qi += diagonal_matrix(dimension, [ei[0]]*dimension) + # 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) + + A = FiniteDimensionalAlgebra(QQ,Qs,assume_associative=True) + return JordanAlgebra(A)