@title GiNaC @value{VERSION}
@subtitle An open framework for symbolic computation within the C++ programming language
@subtitle @value{UPDATED}
-@author The GiNaC Group:
-@author Christian Bauer, Alexander Frink, Richard Kreckel, Jens Vollinga
+@author @uref{http://www.ginac.de}
@page
@vskip 0pt plus 1filll
for example (@pxref{Complex expressions}), do @emph{not} evaluate if applied
to such symbols. Likewise @code{log(exp(x))} does not evaluate to @code{x},
because of the unknown imaginary part of @code{x}.
-On the other hand, if you are sure that your symbols will hold only real values, you
-would like to have such functions evaluated. Therefore GiNaC allows you to specify
+On the other hand, if you are sure that your symbols will hold only real
+values, you would like to have such functions evaluated. Therefore GiNaC
+allows you to specify
the domain of the symbol. Instead of @code{symbol x("x");} you can write
@code{realsymbol x("x");} to tell GiNaC that @code{x} stands in for real values.
+@cindex @code{possymbol()}
+Furthermore, it is also possible to declare a symbol as positive. This will,
+for instance, enable the automatic simplification of @code{abs(x)} into
+@code{x}. This is done by declaying the symbol as @code{possymbol x("x");}.
+
@node Numbers, Constants, Symbols, Basic concepts
@c node-name, next, previous, up
@}
@end example
+@cindex @code{is_zero_matrix()}
+The method @code{matrix::is_zero_matrix()} returns @code{true} only if
+all entries of the matrix are zeros. There is also method
+@code{ex::is_zero_matrix()} which returns @code{true} only if the
+expression is zero or a zero matrix.
+
@cindex @code{transpose()}
There are three ways to do arithmetic with matrices. The first (and most
direct one) is to use the methods provided by the @code{matrix} class:
The @code{scalar_products} object @code{sp} acts as a storage for the
scalar products added to it with the @code{.add()} method. This method
takes three arguments: the two expressions of which the scalar product is
-taken, and the expression to replace it with. After @code{sp.add(A, B, 0)},
-@code{simplify_indexed()} will replace all scalar products of indexed
-objects that have the symbols @code{A} and @code{B} as base expressions
-with the single value 0. The number, type and dimension of the indices
-don't matter; @samp{A~mu~nu*B.mu.nu} would also be replaced by 0.
+taken, and the expression to replace it with.
@cindex @code{expand()}
The example above also illustrates a feature of the @code{expand()} method:
function
@example
- ex clifford_unit(const ex & mu, const ex & metr, unsigned char rl = 0,
- bool anticommuting = false);
+ ex clifford_unit(const ex & mu, const ex & metr, unsigned char rl = 0);
@end example
-where @code{mu} should be a @code{varidx} class object indexing the
-generators, an index @code{mu} with a numeric value may be of type
-@code{idx} as well.
+where @code{mu} should be a @code{idx} (or descendant) class object
+indexing the generators.
Parameter @code{metr} defines the metric @math{M(i, j)} and can be
represented by a square @code{matrix}, @code{tensormetric} or @code{indexed} class
-object. Optional parameter @code{rl} allows to distinguish different
-Clifford algebras, which will commute with each other. The last
-optional parameter @code{anticommuting} defines if the anticommuting
-assumption (i.e.
-@tex
-$e_i e_j + e_j e_i = 0$)
-@end tex
-@ifnottex
-e~i e~j + e~j e~i = 0)
-@end ifnottex
-will be used for contraction of Clifford units. If the @code{metric} is
-supplied by a @code{matrix} object, then the value of
-@code{anticommuting} is calculated automatically and the supplied one
-will be ignored. One can overcome this by giving @code{metric} through
-matrix wrapped into an @code{indexed} object.
+object. In fact, any expression either with two free indices or without
+indices at all is admitted as @code{metr}. In the later case an @code{indexed}
+object with two newly created indices with @code{metr} as its
+@code{op(0)} will be used.
+Optional parameter @code{rl} allows to distinguish different
+Clifford algebras, which will commute with each other.
Note that the call @code{clifford_unit(mu, minkmetric())} creates
something very close to @code{dirac_gamma(mu)}, although
@cindex @code{clifford::get_metric()}
The method @code{clifford::get_metric()} returns a metric defining this
Clifford number.
-@cindex @code{clifford::is_anticommuting()}
-The method @code{clifford::is_anticommuting()} returns the
-@code{anticommuting} property of a unit.
If the matrix @math{M(i, j)} is in fact symmetric you may prefer to create
the Clifford algebra units with a call like that
@example
@{
...
- varidx nu(symbol("nu"), 4);
+ idx i(symbol("i"), 4);
realsymbol s("s");
ex M = diag_matrix(lst(1, -1, 0, s));
- ex e = clifford_unit(nu, M);
- ex e0 = e.subs(nu == 0);
- ex e1 = e.subs(nu == 1);
- ex e2 = e.subs(nu == 2);
- ex e3 = e.subs(nu == 3);
+ ex e = clifford_unit(i, M);
+ ex e0 = e.subs(i == 0);
+ ex e1 = e.subs(i == 1);
+ ex e2 = e.subs(i == 2);
+ ex e3 = e.subs(i == 3);
...
@}
@end example
@example
ex lst_to_clifford(const ex & v, const ex & mu, const ex & metr,
- unsigned char rl = 0, bool anticommuting = false);
+ unsigned char rl = 0);
ex lst_to_clifford(const ex & v, const ex & e);
@end example
with @samp{e.k}
directly supplied in the second form of the procedure. In the first form
the Clifford unit @samp{e.k} is generated by the call of
-@code{clifford_unit(mu, metr, rl, anticommuting)}. The previous code may be rewritten
+@code{clifford_unit(mu, metr, rl)}. The previous code may be rewritten
with the help of @code{lst_to_clifford()} as follows
@example
@{
...
- varidx nu(symbol("nu"), 4);
+ idx i(symbol("i"), 4);
realsymbol s("s");
ex M = diag_matrix(lst(1, -1, 0, s));
- ex e0 = lst_to_clifford(lst(1, 0, 0, 0), nu, M);
- ex e1 = lst_to_clifford(lst(0, 1, 0, 0), nu, M);
- ex e2 = lst_to_clifford(lst(0, 0, 1, 0), nu, M);
- ex e3 = lst_to_clifford(lst(0, 0, 0, 1), nu, M);
+ ex e0 = lst_to_clifford(lst(1, 0, 0, 0), i, M);
+ ex e1 = lst_to_clifford(lst(0, 1, 0, 0), i, M);
+ ex e2 = lst_to_clifford(lst(0, 0, 1, 0), i, M);
+ ex e3 = lst_to_clifford(lst(0, 0, 0, 1), i, M);
...
@}
@end example
@example
ex clifford_moebius_map(const ex & a, const ex & b, const ex & c,
const ex & d, const ex & v, const ex & G,
- unsigned char rl = 0, bool anticommuting = false);
+ unsigned char rl = 0);
ex clifford_moebius_map(const ex & M, const ex & v, const ex & G,
- unsigned char rl = 0, bool anticommuting = false);
+ unsigned char rl = 0);
@end example
It takes a list or vector @code{v} and makes the Moebius (conformal or
the matrix @samp{M = [[a, b], [c, d]]}. The parameter @code{G} defines
the metric of the surrounding (pseudo-)Euclidean space. This can be an
indexed object, tensormetric, matrix or a Clifford unit, in the later
-case the optional parameters @code{rl} and @code{anticommuting} are ignored
-even if supplied. The returned value of this function is a list of
-components of the resulting vector.
+case the optional parameter @code{rl} is ignored even if supplied.
+Depending from the type of @code{v} the returned value of this function
+is either a vector or a list holding vector's components.
@cindex @code{clifford_max_label()}
Finally the function
@end example
for checking whether one expression is equal to another, or equal to zero,
-respectively.
+respectively. See also the method @code{ex::is_zero_matrix()},
+@pxref{Matrices}.
@subsection Ordering expressions