Example #1
0
File: RMT.cpp Project: Phali/libs
 // }}}
 itpp::Mat<std::complex<double> > RandomGUE(int const dim, std::string normalization="sigma_offdiag=1", double const percentage_away=0.1){ //{{{
   if (normalization=="sigma_offdiag=1"){
     return RandomGUEDeltaOne(dim);
   }	
   else if (normalization=="unfolded mean_level_spacing=1"){
     itpp::Mat<std::complex<double> > U(dim, dim), tmp(dim,dim);
     itpp::Vec<std::complex<double> > vec1(dim);
     itpp::Vec<double> eigenvalues(dim);
     FlatSpectrumGUE(U, eigenvalues);
     for (int i=0; i<dim; i++){
       vec1=itpp::elem_mult(conj(U.get_col(i)), to_cvec(eigenvalues));
       for (int j=i; j<dim; j++){
         tmp(i,j)=vec1*U.get_col(j);
         if (i<j){tmp(j,i)=conj(tmp(i,j));}
       }
     }
     return tmp;
     // std::cout  << eigenvalues << 	std::endl ;
     // ya dentro de temp tenemos a una matriz que no esta 
     // unfolded. tengo que encontrar los eigenvectores,
     // luego los eigenvalores, eso diagonalizarlos y chan 
   } else {
     std::cerr  << "Illegal normalization RandomGUE" << percentage_away;
     exit(1);
   }
   // Aca poner un factor de normalizacion opcional
 }
Example #2
0
// }}}
itpp::Mat<std::complex<double> > RandomCUE(int const dim) { //{{{
    itpp::Mat<std::complex<double> > H;
    H = RandomGUEDeltaOne(dim);

    itpp::Mat<std::complex<double> > U(dim,dim);
    itpp::Vec<double> eigenvalues(dim);
    eig_sym(H, eigenvalues, U);
//     FlatSpectrumGUE(U, eigenvalues);
    //     return exp( 2*itpp::pi*std::complex<double>(0.,1.)*  itpp:randu())*U;
    return exp(2.*itpp::pi*std::complex<double>(0.,1.) *itpp::randu() )*U;
}
Example #3
0
File: RMT.cpp Project: Phali/libs
 // }}}
 void FlatSpectrumGUE(itpp::Mat<std::complex<double> >& U, itpp::Vec<double>& eigenvalues){ // {{{
   int dim=eigenvalues.size();
   if(dim != U.rows() || dim != U.cols()){
     std::cerr << "error, dimensionenes no apropiadas "
       << " en FlatSpectrumGUE" <<std::endl  ;
     exit(1);
   }
   itpp::Mat<std::complex<double> > temp(dim,dim);
   bool exito=false;
   for( ; !exito ; ){
     temp=RandomGUEDeltaOne(dim);
     itpp::eig_sym(temp, eigenvalues, U);
     eigenvalues/=sqrt(4*dim);
     exito=unfoldcircular(eigenvalues);
   }
 }
Example #4
0
File: RMT.cpp Project: Phali/libs
 // }}}
 itpp::Vec<double> FlatSpectrumGUE(int const dim, double const percen_out=0.2){ //{{{
   int extra_per_side=itpp::round_i(std::ceil(0.5*percen_out*dim));
   int dim_large=itpp::round_i(std::ceil(dim+2*extra_per_side));
   itpp::Mat<std::complex<double> > temp(dim_large,dim_large);
   itpp::Vec<double> eigenvalues(dim);
   itpp::Vec<double> eigenvalues_enlarged(dim_large);
   // 		eigenvalues.set_size(dim_enlarged);
   temp=RandomGUEDeltaOne(dim_large);
   itpp::eig_sym(temp, eigenvalues_enlarged);
   eigenvalues_enlarged /= sqrt(4*dim_large);
   if (eigenvalues_enlarged(extra_per_side)<-1 ||
       eigenvalues_enlarged(dim+extra_per_side-1)> 1){
     std::cout<<"UUps, we need to a bigger part of the "
       <<" spectrum in routine FlatSpectrumGUE";
     exit(1);
   }
   unfoldcircular(eigenvalues_enlarged);
   eigenvalues=eigenvalues_enlarged.get(extra_per_side,
       dim+extra_per_side-1);
   return eigenvalues;
 }