]> gitweb.michael.orlitzky.com - sage.d.git/blobdiff - mjo/eja/euclidean_jordan_algebra.py
eja: recurse more directly in minimal_polynomial().
[sage.d.git] / mjo / eja / euclidean_jordan_algebra.py
index 52e1383383cac83a8fa91e3f63c39c8795d8b533..8f623b4491ca1439d0905b5b91bcfe25cf754ecb 100644 (file)
@@ -5,40 +5,94 @@ 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.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
 
 class FiniteDimensionalEuclideanJordanAlgebra(FiniteDimensionalAlgebra):
     @staticmethod
-    def __classcall__(cls, field, mult_table, names='e', category=None):
-        fda = super(FiniteDimensionalEuclideanJordanAlgebra, cls)
-        return fda.__classcall_private__(cls,
-                                         field,
-                                         mult_table,
-                                         names,
-                                         category)
+    def __classcall_private__(cls,
+                              field,
+                              mult_table,
+                              names='e',
+                              assume_associative=False,
+                              category=None,
+                              rank=None):
+        n = len(mult_table)
+        mult_table = [b.base_extend(field) for b in mult_table]
+        for b in mult_table:
+            b.set_immutable()
+            if not (is_Matrix(b) and b.dimensions() == (n, n)):
+                raise ValueError("input is not a multiplication table")
+        mult_table = tuple(mult_table)
+
+        cat = MagmaticAlgebras(field).FiniteDimensional().WithBasis()
+        cat.or_subcategory(category)
+        if assume_associative:
+            cat = cat.Associative()
+
+        names = normalize_names(n, names)
 
-    def __init__(self, field, mult_table, names='e', category=None):
+        fda = super(FiniteDimensionalEuclideanJordanAlgebra, cls)
+        return fda.__classcall__(cls,
+                                 field,
+                                 mult_table,
+                                 assume_associative=assume_associative,
+                                 names=names,
+                                 category=cat,
+                                 rank=rank)
+
+
+    def __init__(self, field,
+                 mult_table,
+                 names='e',
+                 assume_associative=False,
+                 category=None,
+                 rank=None):
+        self._rank = rank
         fda = super(FiniteDimensionalEuclideanJordanAlgebra, self)
-        fda.__init__(field, mult_table, names, category)
+        fda.__init__(field,
+                     mult_table,
+                     names=names,
+                     category=category)
 
 
     def _repr_(self):
         """
         Return a string representation of ``self``.
         """
-        return "Euclidean Jordan algebra of degree {} over {}".format(self.degree(), self.base_ring())
+        fmt = "Euclidean Jordan algebra of degree {} over {}"
+        return fmt.format(self.degree(), self.base_ring())
 
     def rank(self):
         """
         Return the rank of this EJA.
         """
-        raise NotImplementedError
+        if self._rank is None:
+            raise ValueError("no rank specified at genesis")
+        else:
+            return self._rank
 
 
     class Element(FiniteDimensionalAlgebraElement):
         """
         An element of a Euclidean Jordan algebra.
+
+        Since EJAs are commutative, the "right multiplication" matrix is
+        also the left multiplication matrix and must be symmetric::
+
+            sage: set_random_seed()
+            sage: n = ZZ.random_element(1,10).abs()
+            sage: J = eja_rn(5)
+            sage: J.random_element().matrix().is_symmetric()
+            True
+            sage: J = eja_ln(5)
+            sage: J.random_element().matrix().is_symmetric()
+            True
+
         """
 
         def __pow__(self, n):
@@ -57,6 +111,18 @@ class FiniteDimensionalEuclideanJordanAlgebra(FiniteDimensionalAlgebra):
                 return A.element_class(A, self.vector()*(self.matrix()**(n-1)))
 
 
+        def span_of_powers(self):
+            """
+            Return the vector space spanned by successive powers of
+            this element.
+            """
+            # The dimension of the subalgebra can't be greater than
+            # the big algebra, so just put everything into a list
+            # and let span() get rid of the excess.
+            V = self.vector().parent()
+            return V.span( (self**d).vector() for d in xrange(V.dimension()) )
+
+
         def degree(self):
             """
             Compute the degree of this element the straightforward way
@@ -73,17 +139,129 @@ class FiniteDimensionalEuclideanJordanAlgebra(FiniteDimensionalAlgebra):
                 sage: (e0 - e1).degree()
                 2
 
+            In the spin factor algebra (of rank two), all elements that
+            aren't multiples of the identity are regular::
+
+                sage: set_random_seed()
+                sage: n = ZZ.random_element(1,10).abs()
+                sage: J = eja_ln(n)
+                sage: x = J.random_element()
+                sage: x == x.coefficient(0)*J.one() or x.degree() == 2
+                True
+
             """
-            d = 0
-            V = self.vector().parent()
-            vectors = [(self**d).vector()]
-            while V.span(vectors).dimension() > d:
-                d += 1
-                vectors.append((self**d).vector())
-            return d
+            return self.span_of_powers().dimension()
+
+
+        def subalgebra_generated_by(self):
+            """
+            Return the associative subalgebra of the parent EJA generated
+            by this element.
+
+            TESTS::
+
+                sage: set_random_seed()
+                sage: n = ZZ.random_element(1,10).abs()
+                sage: J = eja_rn(n)
+                sage: x = J.random_element()
+                sage: x.subalgebra_generated_by().is_associative()
+                True
+                sage: J = eja_ln(n)
+                sage: x = J.random_element()
+                sage: x.subalgebra_generated_by().is_associative()
+                True
+
+            """
+            # First get the subspace spanned by the powers of myself...
+            V = self.span_of_powers()
+            F = self.base_ring()
+
+            # Now figure out the entries of the right-multiplication
+            # matrix for the successive basis elements b0, b1,... of
+            # that subspace.
+            mats = []
+            for b_right in V.basis():
+                eja_b_right = self.parent()(b_right)
+                b_right_rows = []
+                # The first row of the right-multiplication matrix by
+                # b1 is what we get if we apply that matrix to b1. The
+                # second row of the right multiplication matrix by b1
+                # is what we get when we apply that matrix to b2...
+                for b_left in V.basis():
+                    eja_b_left = self.parent()(b_left)
+                    # Multiply in the original EJA, but then get the
+                    # coordinates from the subalgebra in terms of its
+                    # basis.
+                    this_row = V.coordinates((eja_b_left*eja_b_right).vector())
+                    b_right_rows.append(this_row)
+                b_right_matrix = matrix(F, b_right_rows)
+                mats.append(b_right_matrix)
+
+            # It's an algebra of polynomials in one element, and EJAs
+            # are power-associative.
+            return FiniteDimensionalEuclideanJordanAlgebra(F, mats, assume_associative=True)
+
 
         def minimal_polynomial(self):
-            return self.matrix().minimal_polynomial()
+            """
+            EXAMPLES::
+
+                sage: set_random_seed()
+                sage: n = ZZ.random_element(1,10).abs()
+                sage: J = eja_rn(n)
+                sage: x = J.random_element()
+                sage: x.degree() == x.minimal_polynomial().degree()
+                True
+
+            ::
+
+                sage: set_random_seed()
+                sage: n = ZZ.random_element(1,10).abs()
+                sage: J = eja_ln(n)
+                sage: x = J.random_element()
+                sage: x.degree() == x.minimal_polynomial().degree()
+                True
+
+            The minimal polynomial and the characteristic polynomial coincide
+            and are known (see Alizadeh, Example 11.11) for all elements of
+            the spin factor algebra that aren't scalar multiples of the
+            identity::
+
+                sage: set_random_seed()
+                sage: n = ZZ.random_element(2,10).abs()
+                sage: J = eja_ln(n)
+                sage: y = J.random_element()
+                sage: while y == y.coefficient(0)*J.one():
+                ....:     y = J.random_element()
+                sage: y0 = y.vector()[0]
+                sage: y_bar = y.vector()[1:]
+                sage: actual = y.minimal_polynomial()
+                sage: x = SR.symbol('x', domain='real')
+                sage: expected = x^2 - 2*y0*x + (y0^2 - norm(y_bar)^2)
+                sage: bool(actual == expected)
+                True
+
+            """
+            # The element we're going to call "minimal_polynomial()" on.
+            # Either myself, interpreted as an element of a finite-
+            # dimensional algebra, or an element of an associative
+            # subalgebra.
+            elt = None
+
+            if self.parent().is_associative():
+                elt = FiniteDimensionalAlgebraElement(self.parent(), self)
+            else:
+                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()))
+
+            # Recursive call, but should work since elt lives in an
+            # associative algebra.
+            return elt.minimal_polynomial()
+
 
         def characteristic_polynomial(self):
             return self.matrix().characteristic_polynomial()
@@ -122,10 +300,7 @@ def eja_rn(dimension, field=QQ):
     Qs = [ matrix(field, dimension, dimension, lambda k,j: 1*(k == j == i))
            for i in xrange(dimension) ]
 
-    # Assuming associativity is wrong here, but it works to
-    # temporarily trick the Jordan algebra constructor into using the
-    # multiplication table.
-    return FiniteDimensionalEuclideanJordanAlgebra(field,Qs)
+    return FiniteDimensionalEuclideanJordanAlgebra(field,Qs,rank=dimension)
 
 
 def eja_ln(dimension, field=QQ):
@@ -175,4 +350,8 @@ def eja_ln(dimension, field=QQ):
         Qi[0,0] = Qi[0,0] * ~field(2)
         Qs.append(Qi)
 
-    return FiniteDimensionalEuclideanJordanAlgebra(field,Qs)
+    # 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).
+    rank = min(dimension,2)
+    return FiniteDimensionalEuclideanJordanAlgebra(field,Qs,rank=rank)