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apply_permutation_algebra for tensors from product rhs

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This commit is contained in:
Jiri Pittner 2025-10-17 15:07:43 +02:00
parent 1dd3905d14
commit 08cdf7c971
3 changed files with 110 additions and 6 deletions
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56
t.cc
View File

@ -3451,7 +3451,7 @@ cout <<mm;
cout <<m.getcount()<<" "<<v.getcount()<<" "<<mm.getcount()<<endl;
}
if(1)
if(0)
{
NRVec<double> v(12);
v.randomize(1.);
@ -3462,7 +3462,7 @@ cout<<"abssorted\n";
v.printsorted(cout,1,true);
}
if(1)
if(0)
{
NRSMat<double> v(4);
v.randomize(1.);
@ -3471,7 +3471,7 @@ cout<<"smat sorted\n";
v.printsorted(cout,1,false);
}
if(1)
if(0)
{
NRMat<double> v(4,5);
v.randomize(1.);
@ -3481,7 +3481,57 @@ v.printsorted(cout,1,false);
}
if(1)
{
//grassmann product of n identical rank=2 tensors in m-dim space
int n,m;
cin >>n>>m;
//generate the source tensor
INDEXGROUP g;
g.number=2;
g.symmetry= 0;
g.offset=0;
g.range=m;
Tensor<double> x(g);
x.randomize(1);
cout <<x;
//generate antisymmetrizer of even indices, with identity on odd indices
NRVec<NRVec_from1<int> > indexclasses(1);
indexclasses[0].resize(n);
for(int i=1; i<=n; ++i) {indexclasses[0][i]= i;}
PermutationAlgebra<int,int> a=general_antisymmetrizer(indexclasses,0,true);
//antisymmetrize only in the even indices
PermutationAlgebra<int,double> b(a.size());
for(int i=0; i<a.size(); ++i)
{
b[i].weight=a[i].weight;
b[i].perm.resize(2*n);
for(int j=1; j<=n; ++j)
{
b[i].perm[2*j-1] = 2*j-1;
b[i].perm[2*j] = 2*a[i].perm[j];
}
}
cout <<b;
//prepare output tensor (ignoring its symmetry)
INDEXGROUP gg;
gg.number= 2*n;
gg.symmetry= 0;
gg.offset=0;
gg.range=m;
Tensor<double> y(gg);
NRVec<Tensor<double> > rhsvec(n);
for(int i=0; i<n; ++i) rhsvec[i]=x;
y.apply_permutation_algebra(rhsvec,b,false,1.,0.);
cout <<y;
}
}//main

51
tensor.cc
View File

@ -924,6 +924,32 @@ for(int p=0; p<help_pa<T>->size(); ++p)
}
static int help_tn;
template<typename T>
static Tensor<T> *help_tv;
template<typename T>
static void permutationalgebra_callback2(const SUPERINDEX &I, T *v)
{
FLATINDEX J = superindex2flat(I);
for(int p=0; p<help_pa<T>->size(); ++p)
{
FLATINDEX Jp = J.permuted((*help_pa<T>)[p].perm,help_inverse);
T product;
//build product from the vector of tensors using the Jp index
int rankshift=0;
for(int i=0; i<help_tn; ++i)
{
int rank = help_tv<T>[i].rank();
FLATINDEX indi = Jp.subvector(rankshift,rankshift+rank-1);
if(i==0) product= help_tv<T>[i](indi);
else product *= help_tv<T>[i](indi);
rankshift += rank;
}
*v += help_alpha<T> * (*help_pa<T>)[p].weight * product;
}
}
template<typename T>
void Tensor<T>::apply_permutation_algebra(const Tensor<T> &rhs, const PermutationAlgebra<int,T> &pa, bool inverse, T alpha, T beta)
@ -932,6 +958,8 @@ if(beta!=(T)0) {if(beta!=(T)1) *this *= beta;} else clear();
if(alpha==(T)0) return;
copyonwrite();
if(rank()!=rhs.rank()) laerror("rank mismatch in apply_permutation_algebra");
help_t<T> = const_cast<Tensor<T> *>(&rhs);
help_pa<T> = &pa;
help_inverse = inverse;
@ -940,6 +968,29 @@ loopover(permutationalgebra_callback);
}
template<typename T>
void Tensor<T>::apply_permutation_algebra(const NRVec<Tensor<T> > &rhsvec, const PermutationAlgebra<int,T> &pa, bool inverse, T alpha, T beta)
{
if(beta!=(T)0) {if(beta!=(T)1) *this *= beta;} else clear();
if(alpha==(T)0) return;
copyonwrite();
int totrank=0;
for(int i=0; i<rhsvec.size(); ++i) totrank+=rhsvec[i].rank();
if(totrank!=rank()) laerror("rank mismatch in apply_permutation_algebra");
help_tv<T> = const_cast<Tensor<T> *>(&rhsvec[0]);
help_tn = rhsvec.size();
help_pa<T> = &pa;
help_inverse = inverse;
help_alpha<T> = alpha;
loopover(permutationalgebra_callback2);
}
template<typename T>
void Tensor<T>::split_index_group(int group)
{

9
tensor.h
View File

@ -41,8 +41,7 @@
//@@@ will not be particularly efficient
//
//@@@permutation of individual indices - chech the indices in sym groups remain adjacent, calculate result's shape, loopover the result and permute using unwind_callback
//@@@todo - implement index names - flat vector of names, and contraction by named index list
//@@@todo grassmann product and support for RDM and cumulat stuff
//@@@todo!!! - implement index names - flat vector of names, and contraction by named index list
namespace LA {
@ -217,8 +216,12 @@ public:
inline Tensor contractions( const INDEXLIST &il1, const Tensor &rhs2, const INDEXLIST &il2, T alpha=1, bool conjugate1=false, bool conjugate2=false) const {Tensor<T> r; r.addcontractions(*this,il1,rhs2,il2,alpha,0,true,conjugate1, conjugate2); return r; };
void apply_permutation_algebra(const Tensor &rhs, const PermutationAlgebra<int,T> &pa, bool inverse=false, T alpha=1, T beta=0); //general (not optimally efficient) symmetrizers, antisymmetrizers etc. acting on the flattened index list:
void apply_permutation_algebra(const NRVec<Tensor> &rhsvec, const PermutationAlgebra<int,T> &pa, bool inverse=false, T alpha=1, T beta=0); //avoids explicit outer product but not vectorized, rather inefficient
// this *=beta; for I over this: this(I) += alpha * sum_P c_P rhs(P(I))
// PermutationAlgebra can represent e.g. general_antisymmetrizer in Kucharski-Bartlett notation
// PermutationAlgebra can represent e.g. general_antisymmetrizer in Kucharski-Bartlett notation, or Grassmann products building RDM from cumulants
// Note that *this tensor can be e.g. antisymmetric while rhs is not and is being antisymmetrized by the PermutationAlgebra
// The efficiency is not optimal, even when avoiding the outer product, the calculation is done indexing element by element
// More efficient would be applying permutation algebra symbolically and efficiently computing term by term
void split_index_group(int group); //formal split of a non-symmetric index group WITHOUT the need for data reorganization
void merge_adjacent_index_groups(int groupfrom, int groupto); //formal merge of non-symmetric index groups WITHOUT the need for data reorganization
Tensor merge_index_groups(const NRVec<int> &groups) const;