diff --git a/lib/algorithms/iterative/ImplicitlyRestartedLanczos.h b/lib/algorithms/iterative/ImplicitlyRestartedLanczos.h
new file mode 100644
index 00000000..a8723f32
--- /dev/null
+++ b/lib/algorithms/iterative/ImplicitlyRestartedLanczos.h
@@ -0,0 +1,625 @@
+    /*************************************************************************************
+
+    Grid physics library, www.github.com/paboyle/Grid 
+
+    Source file: ./lib/algorithms/iterative/ImplicitlyRestartedLanczos.h
+
+    Copyright (C) 2015
+
+Author: Peter Boyle <paboyle@ph.ed.ac.uk>
+Author: Chulwoo Jung
+Author: Guido Cossu
+
+    This program is free software; you can redistribute it and/or modify
+    it under the terms of the GNU General Public License as published by
+    the Free Software Foundation; either version 2 of the License, or
+    (at your option) any later version.
+
+    This program is distributed in the hope that it will be useful,
+    but WITHOUT ANY WARRANTY; without even the implied warranty of
+    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+    GNU General Public License for more details.
+
+    You should have received a copy of the GNU General Public License along
+    with this program; if not, write to the Free Software Foundation, Inc.,
+    51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
+
+    See the full license in the file "LICENSE" in the top level distribution directory
+    *************************************************************************************/
+    /*  END LEGAL */
+#ifndef GRID_IRL_H
+#define GRID_IRL_H
+
+#include <string.h> //memset
+
+namespace Grid {
+
+  enum IRLdiagonalisation { 
+    IRLdiagonaliseWithDSTEGR,
+    IRLdiagonaliseWithQR,
+    IRLdiagonaliseWithEigen
+  };
+
+////////////////////////////////////////////////////////////////////////////////
+// Helper class for sorting the evalues AND evectors by Field
+// Use pointer swizzle on vectors
+////////////////////////////////////////////////////////////////////////////////
+template<class Field>
+class SortEigen {
+ private:
+  static bool less_lmd(RealD left,RealD right){
+    return left > right;
+  }  
+  static bool less_pair(std::pair<RealD,Field const*>& left,
+                        std::pair<RealD,Field const*>& right){
+    return left.first > (right.first);
+  }  
+  
+ public:
+  void push(std::vector<RealD>& lmd,std::vector<Field>& evec,int N) {
+    
+    ////////////////////////////////////////////////////////////////////////
+    // PAB: FIXME: VERY VERY VERY wasteful: takes a copy of the entire vector set.
+    //    : The vector reorder should be done by pointer swizzle somehow
+    ////////////////////////////////////////////////////////////////////////
+    std::vector<Field> cpy(lmd.size(),evec[0]._grid);
+    for(int i=0;i<lmd.size();i++) cpy[i] = evec[i];
+    
+    std::vector<std::pair<RealD, Field const*> > emod(lmd.size());    
+
+    for(int i=0;i<lmd.size();++i)  emod[i] = std::pair<RealD,Field const*>(lmd[i],&cpy[i]);
+
+    partial_sort(emod.begin(),emod.begin()+N,emod.end(),less_pair);
+
+    typename std::vector<std::pair<RealD, Field const*> >::iterator it = emod.begin();
+    for(int i=0;i<N;++i){
+      lmd[i]=it->first;
+      evec[i]=*(it->second);
+      ++it;
+    }
+  }
+  void push(std::vector<RealD>& lmd,int N) {
+    std::partial_sort(lmd.begin(),lmd.begin()+N,lmd.end(),less_lmd);
+  }
+  bool saturated(RealD lmd, RealD thrs) {
+    return fabs(lmd) > fabs(thrs);
+  }
+};
+
+/////////////////////////////////////////////////////////////
+// Implicitly restarted lanczos
+/////////////////////////////////////////////////////////////
+template<class Field> 
+class ImplicitlyRestartedLanczos {
+
+private:       
+
+  int MaxIter;   // Max iterations
+  int Nstop;     // Number of evecs checked for convergence
+  int Nk;        // Number of converged sought
+  int Nm;        // Nm -- total number of vectors
+  RealD eresid;
+  IRLdiagonalisation diagonalisation;
+  ////////////////////////////////////
+  // Embedded objects
+  ////////////////////////////////////
+           SortEigen<Field> _sort;
+  LinearOperatorBase<Field> &_Linop;
+    OperatorFunction<Field> &_poly;
+
+  /////////////////////////
+  // Constructor
+  /////////////////////////
+public:       
+ ImplicitlyRestartedLanczos(LinearOperatorBase<Field> &Linop, // op
+			    OperatorFunction<Field> & poly,   // polynomial
+			    int _Nstop, // really sought vecs
+			    int _Nk,    // sought vecs
+			    int _Nm,    // total vecs
+			    RealD _eresid, // resid in lmd deficit 
+			    int _MaxIter,  // Max iterations
+			    IRLdiagonalisation _diagonalisation= IRLdiagonaliseWithEigen ) :
+    _Linop(Linop),    _poly(poly),
+      Nstop(_Nstop), Nk(_Nk), Nm(_Nm),
+      eresid(_eresid),  MaxIter(_MaxIter),
+      diagonalisation(_diagonalisation)
+      { };
+
+  ////////////////////////////////
+  // Helpers
+  ////////////////////////////////
+  static RealD normalise(Field& v) 
+  {
+    RealD nn = norm2(v);
+    nn = sqrt(nn);
+    v = v * (1.0/nn);
+    return nn;
+  }
+  
+  void orthogonalize(Field& w, std::vector<Field>& evec, int k)
+  {
+    typedef typename Field::scalar_type MyComplex;
+    MyComplex ip;
+    
+    for(int j=0; j<k; ++j){
+      ip = innerProduct(evec[j],w); 
+      w = w - ip * evec[j];
+    }
+    normalise(w);
+  }
+
+/* Rudy Arthur's thesis pp.137
+------------------------
+Require: M > K P = M − K †
+Compute the factorization AVM = VM HM + fM eM 
+repeat
+  Q=I
+  for i = 1,...,P do
+    QiRi =HM −θiI Q = QQi
+    H M = Q †i H M Q i
+  end for
+  βK =HM(K+1,K) σK =Q(M,K)
+  r=vK+1βK +rσK
+  VK =VM(1:M)Q(1:M,1:K)
+  HK =HM(1:K,1:K)
+  →AVK =VKHK +fKe†K † Extend to an M = K + P step factorization AVM = VMHM + fMeM
+until convergence
+*/
+  void calc(std::vector<RealD>& eval,  std::vector<Field>& evec, const Field& src, int& Nconv)
+  {
+    
+    GridBase *grid = evec[0]._grid;
+    assert(grid == src._grid);
+    
+    std::cout << GridLogMessage <<"**************************************************************************"<< std::endl;
+    std::cout << GridLogMessage <<" ImplicitlyRestartedLanczos::calc() starting iteration 0 /  "<< MaxIter<< std::endl;
+    std::cout << GridLogMessage <<"**************************************************************************"<< std::endl;
+    std::cout << GridLogMessage <<" -- seek   Nk    = " << Nk    <<" vectors"<< std::endl;
+    std::cout << GridLogMessage <<" -- accept Nstop = " << Nstop <<" vectors"<< std::endl;
+    std::cout << GridLogMessage <<" -- total  Nm    = " << Nm    <<" vectors"<< std::endl;
+    std::cout << GridLogMessage <<" -- size of eval = " << eval.size() << std::endl;
+    std::cout << GridLogMessage <<" -- size of evec = " << evec.size() << std::endl;
+    if ( diagonalisation == IRLdiagonaliseWithDSTEGR ) {
+      std::cout << GridLogMessage << "Diagonalisation is DSTEGR "<<std::endl;
+    } else if ( diagonalisation == IRLdiagonaliseWithQR ) { 
+      std::cout << GridLogMessage << "Diagonalisation is QR "<<std::endl;
+    }  else if ( diagonalisation == IRLdiagonaliseWithEigen ) { 
+      std::cout << GridLogMessage << "Diagonalisation is Eigen "<<std::endl;
+    }
+    std::cout << GridLogMessage <<"**************************************************************************"<< std::endl;
+    
+    assert(Nm == evec.size() && Nm == eval.size());
+	
+    std::vector<RealD> lme(Nm);  
+    std::vector<RealD> lme2(Nm);
+    std::vector<RealD> eval2(Nm);
+
+    Eigen::MatrixXd    Qt = Eigen::MatrixXd::Zero(Nm,Nm);
+
+    std::vector<int>   Iconv(Nm);
+    std::vector<Field>  B(Nm,grid); // waste of space replicating
+    
+    Field f(grid);
+    Field v(grid);
+    
+    int k1 = 1;
+    int k2 = Nk;
+    
+    Nconv = 0;
+    
+    RealD beta_k;
+  
+    // Set initial vector
+    evec[0] = src;
+    std::cout << GridLogMessage <<"norm2(src)= " << norm2(src)<<std::endl;
+    
+    normalise(evec[0]);
+    std::cout << GridLogMessage <<"norm2(evec[0])= " << norm2(evec[0]) <<std::endl;
+    
+    // Initial Nk steps
+    for(int k=0; k<Nk; ++k) step(eval,lme,evec,f,Nm,k);
+    
+    // Restarting loop begins
+    int iter;
+    for(iter = 0; iter<MaxIter; ++iter){
+      
+      std::cout<< GridLogMessage <<" **********************"<< std::endl;
+      std::cout<< GridLogMessage <<" Restart iteration = "<< iter << std::endl;
+      std::cout<< GridLogMessage <<" **********************"<< std::endl;
+      
+      for(int k=Nk; k<Nm; ++k) step(eval,lme,evec,f,Nm,k);
+      
+      f *= lme[Nm-1];
+      
+      // getting eigenvalues
+      for(int k=0; k<Nm; ++k){
+	eval2[k] = eval[k+k1-1];
+	lme2[k] = lme[k+k1-1];
+      }
+      Qt = Eigen::MatrixXd::Identity(Nm,Nm);
+      diagonalize(eval2,lme2,Nm,Nm,Qt,grid);
+
+      // sorting
+      _sort.push(eval2,Nm);
+      
+      // Implicitly shifted QR transformations
+      Qt = Eigen::MatrixXd::Identity(Nm,Nm);
+      for(int ip=k2; ip<Nm; ++ip){ 
+	// Eigen replacement for qr_decomp ???
+	qr_decomp(eval,lme,Nm,Nm,Qt,eval2[ip],k1,Nm);
+      }
+    
+      for(int i=0; i<(Nk+1); ++i) B[i] = 0.0;
+	  
+      for(int j=k1-1; j<k2+1; ++j){
+	for(int k=0; k<Nm; ++k){
+	  B[j].checkerboard = evec[k].checkerboard;
+	  B[j] += Qt(j,k) * evec[k];
+	}
+      }
+      for(int j=k1-1; j<k2+1; ++j) evec[j] = B[j];
+      
+      // Compressed vector f and beta(k2)
+      f *= Qt(k2-1,Nm-1);
+      f += lme[k2-1] * evec[k2];
+      beta_k = norm2(f);
+      beta_k = sqrt(beta_k);
+      std::cout<< GridLogMessage<<" beta(k) = "<<beta_k<<std::endl;
+      
+      RealD betar = 1.0/beta_k;
+      evec[k2] = betar * f;
+      lme[k2-1] = beta_k;
+      
+      // Convergence test
+      for(int k=0; k<Nm; ++k){    
+	eval2[k] = eval[k];
+	lme2[k] = lme[k];
+      }
+      Qt = Eigen::MatrixXd::Identity(Nm,Nm);
+      diagonalize(eval2,lme2,Nk,Nm,Qt,grid);
+      
+      for(int k = 0; k<Nk; ++k) B[k]=0.0;
+      
+      for(int j = 0; j<Nk; ++j){
+	for(int k = 0; k<Nk; ++k){
+	  B[j].checkerboard = evec[k].checkerboard;
+	  B[j] += Qt(j,k) * evec[k];
+	}
+      }
+
+      Nconv = 0;
+      for(int i=0; i<Nk; ++i){
+	
+	_Linop.HermOp(B[i],v);
+	    
+	RealD vnum = real(innerProduct(B[i],v)); // HermOp.
+	RealD vden = norm2(B[i]);
+	eval2[i] = vnum/vden;
+	v -= eval2[i]*B[i];
+	RealD vv = norm2(v);
+	
+	std::cout.precision(13);
+	std::cout << GridLogMessage << "[" << std::setw(3)<< std::setiosflags(std::ios_base::right) <<i<<"] ";
+	std::cout << "eval = "<<std::setw(25)<< std::setiosflags(std::ios_base::left)<< eval2[i];
+	std::cout << " |H B[i] - eval[i]B[i]|^2 "<< std::setw(25)<< std::setiosflags(std::ios_base::right)<< vv<< std::endl;
+	
+	// change the criteria as evals are supposed to be sorted, all evals smaller(larger) than Nstop should have converged
+	if((vv<eresid*eresid) && (i == Nconv) ){
+	  Iconv[Nconv] = i;
+	  ++Nconv;
+	}
+	
+      }  // i-loop end
+      
+      std::cout<< GridLogMessage <<" #modes converged: "<<Nconv<<std::endl;
+
+      if( Nconv>=Nstop ){
+	goto converged;
+      }
+    } // end of iter loop
+    
+    std::cout << GridLogMessage <<"**************************************************************************"<< std::endl;
+    std::cout<< GridLogError    <<" ImplicitlyRestartedLanczos::calc() NOT converged.";
+    std::cout << GridLogMessage <<"**************************************************************************"<< std::endl;
+    abort();
+	
+  converged:
+    // Sorting
+    eval.resize(Nconv);
+    evec.resize(Nconv,grid);
+    for(int i=0; i<Nconv; ++i){
+      eval[i] = eval2[Iconv[i]];
+      evec[i] = B[Iconv[i]];
+    }
+    _sort.push(eval,evec,Nconv);
+    
+    std::cout << GridLogMessage <<"**************************************************************************"<< std::endl;
+    std::cout << GridLogMessage << "ImplicitlyRestartedLanczos CONVERGED ; Summary :\n";
+    std::cout << GridLogMessage <<"**************************************************************************"<< std::endl;
+    std::cout << GridLogMessage << " -- Iterations  = "<< iter   << "\n";
+    std::cout << GridLogMessage << " -- beta(k)     = "<< beta_k << "\n";
+    std::cout << GridLogMessage << " -- Nconv       = "<< Nconv  << "\n";
+    std::cout << GridLogMessage <<"**************************************************************************"<< std::endl;
+  }
+
+private:
+/* Saad PP. 195
+1. Choose an initial vector v1 of 2-norm unity. Set β1 ≡ 0, v0 ≡ 0
+2. For k = 1,2,...,m Do:
+3. wk:=Avk−βkv_{k−1}      
+4. αk:=(wk,vk)       // 
+5. wk:=wk−αkvk       // wk orthog vk 
+6. βk+1 := ∥wk∥2. If βk+1 = 0 then Stop
+7. vk+1 := wk/βk+1
+8. EndDo
+ */
+  void step(std::vector<RealD>& lmd,
+	    std::vector<RealD>& lme, 
+	    std::vector<Field>& evec,
+	    Field& w,int Nm,int k)
+  {
+    const RealD tiny = 1.0e-20;
+    assert( k< Nm );
+    
+    _poly(_Linop,evec[k],w);      // 3. wk:=Avk−βkv_{k−1}
+    
+    if(k>0) w -= lme[k-1] * evec[k-1];
+    
+    ComplexD zalph = innerProduct(evec[k],w); // 4. αk:=(wk,vk)
+    RealD     alph = real(zalph);
+    
+    w = w - alph * evec[k];// 5. wk:=wk−αkvk
+    
+    RealD beta = normalise(w); // 6. βk+1 := ∥wk∥2. If βk+1 = 0 then Stop
+    // 7. vk+1 := wk/βk+1
+    
+    lmd[k] = alph;
+    lme[k] = beta;
+    
+    if ( k > 0 ) orthogonalize(w,evec,k); // orthonormalise
+    if ( k < Nm-1) evec[k+1] = w;
+    
+    if ( beta < tiny ) std::cout << GridLogMessage << " beta is tiny "<<beta<<std::endl;
+  }
+      
+  void diagonalize_Eigen(std::vector<RealD>& lmd, std::vector<RealD>& lme, 
+			 int Nk, int Nm,  
+			 Eigen::MatrixXd & Qt, // Nm x Nm
+			 GridBase *grid)
+  {
+    Eigen::MatrixXd TriDiag = Eigen::MatrixXd::Zero(Nk,Nk);
+
+    for(int i=0;i<Nk;i++)   TriDiag(i,i)   = lmd[i];
+    for(int i=0;i<Nk-1;i++) TriDiag(i,i+1) = lme[i];
+    for(int i=0;i<Nk-1;i++) TriDiag(i+1,i) = lme[i];
+    
+    Eigen::SelfAdjointEigenSolver<Eigen::MatrixXd> eigensolver(TriDiag);
+
+    for (int i = 0; i < Nk; i++) {
+      lmd[Nk-1-i] = eigensolver.eigenvalues()(i);
+    }
+    for (int i = 0; i < Nk; i++) {
+      for (int j = 0; j < Nk; j++) {
+	Qt(Nk-1-i,j) = eigensolver.eigenvectors()(j,i);
+      }
+    }
+  }
+  ///////////////////////////////////////////////////////////////////////////
+  // File could end here if settle on Eigen ???
+  ///////////////////////////////////////////////////////////////////////////
+
+  void qr_decomp(std::vector<RealD>& lmd,   // Nm 
+		 std::vector<RealD>& lme,   // Nm 
+		 int Nk, int Nm,            // Nk, Nm
+		 Eigen::MatrixXd& Qt,       // Nm x Nm matrix
+		 RealD Dsh, int kmin, int kmax)
+  {
+    int k = kmin-1;
+    RealD x;
+    
+    RealD Fden = 1.0/hypot(lmd[k]-Dsh,lme[k]);
+    RealD c = ( lmd[k] -Dsh) *Fden;
+    RealD s = -lme[k] *Fden;
+      
+    RealD tmpa1 = lmd[k];
+    RealD tmpa2 = lmd[k+1];
+    RealD tmpb  = lme[k];
+
+    lmd[k]   = c*c*tmpa1 +s*s*tmpa2 -2.0*c*s*tmpb;
+    lmd[k+1] = s*s*tmpa1 +c*c*tmpa2 +2.0*c*s*tmpb;
+    lme[k]   = c*s*(tmpa1-tmpa2) +(c*c-s*s)*tmpb;
+    x        =-s*lme[k+1];
+    lme[k+1] = c*lme[k+1];
+      
+    for(int i=0; i<Nk; ++i){
+      RealD Qtmp1 = Qt(k,i);
+      RealD Qtmp2 = Qt(k+1,i);
+      Qt(k,i)  = c*Qtmp1 - s*Qtmp2;
+      Qt(k+1,i)= s*Qtmp1 + c*Qtmp2; 
+    }
+
+    // Givens transformations
+    for(int k = kmin; k < kmax-1; ++k){
+      
+      RealD Fden = 1.0/hypot(x,lme[k-1]);
+      RealD c = lme[k-1]*Fden;
+      RealD s = - x*Fden;
+	
+      RealD tmpa1 = lmd[k];
+      RealD tmpa2 = lmd[k+1];
+      RealD tmpb  = lme[k];
+
+      lmd[k]   = c*c*tmpa1 +s*s*tmpa2 -2.0*c*s*tmpb;
+      lmd[k+1] = s*s*tmpa1 +c*c*tmpa2 +2.0*c*s*tmpb;
+      lme[k]   = c*s*(tmpa1-tmpa2) +(c*c-s*s)*tmpb;
+      lme[k-1] = c*lme[k-1] -s*x;
+
+      if(k != kmax-2){
+	x = -s*lme[k+1];
+	lme[k+1] = c*lme[k+1];
+      }
+
+      for(int i=0; i<Nk; ++i){
+	RealD Qtmp1 = Qt(k,i);
+	RealD Qtmp2 = Qt(k+1,i);
+	Qt(k,i)     = c*Qtmp1 -s*Qtmp2;
+	Qt(k+1,i)   = s*Qtmp1 +c*Qtmp2;
+      }
+    }
+  }
+
+  void diagonalize(std::vector<RealD>& lmd, std::vector<RealD>& lme, 
+		   int Nk, int Nm,   
+		   Eigen::MatrixXd & Qt,
+		   GridBase *grid)
+  {
+    Qt = Eigen::MatrixXd::Identity(Nm,Nm);
+    if ( diagonalisation == IRLdiagonaliseWithDSTEGR ) {
+      diagonalize_lapack(lmd,lme,Nk,Nm,Qt,grid);
+    } else if ( diagonalisation == IRLdiagonaliseWithQR ) { 
+      diagonalize_QR(lmd,lme,Nk,Nm,Qt,grid);
+    }  else if ( diagonalisation == IRLdiagonaliseWithEigen ) { 
+      diagonalize_Eigen(lmd,lme,Nk,Nm,Qt,grid);
+    } else { 
+      assert(0);
+    }
+  }
+
+#ifdef USE_LAPACK
+void LAPACK_dstegr(char *jobz, char *range, int *n, double *d, double *e,
+                   double *vl, double *vu, int *il, int *iu, double *abstol,
+                   int *m, double *w, double *z, int *ldz, int *isuppz,
+                   double *work, int *lwork, int *iwork, int *liwork,
+                   int *info);
+#endif
+
+void diagonalize_lapack(std::vector<RealD>& lmd,
+			std::vector<RealD>& lme, 
+			int Nk, int Nm,  
+			Eigen::MatrixXd& Qt,
+			GridBase *grid)
+{
+#ifdef USE_LAPACK
+  const int size = Nm;
+  int NN = Nk;
+  double evals_tmp[NN];
+  double evec_tmp[NN][NN];
+  memset(evec_tmp[0],0,sizeof(double)*NN*NN);
+  double DD[NN];
+  double EE[NN];
+  for (int i = 0; i< NN; i++) {
+    for (int j = i - 1; j <= i + 1; j++) {
+      if ( j < NN && j >= 0 ) {
+	if (i==j) DD[i] = lmd[i];
+	if (i==j) evals_tmp[i] = lmd[i];
+	if (j==(i-1)) EE[j] = lme[j];
+      }
+    }
+  }
+  int evals_found;
+  int lwork = ( (18*NN) > (1+4*NN+NN*NN)? (18*NN):(1+4*NN+NN*NN)) ;
+  int liwork =  3+NN*10 ;
+  int iwork[liwork];
+  double work[lwork];
+  int isuppz[2*NN];
+  char jobz = 'V'; // calculate evals & evecs
+  char range = 'I'; // calculate all evals
+  //    char range = 'A'; // calculate all evals
+  char uplo = 'U'; // refer to upper half of original matrix
+  char compz = 'I'; // Compute eigenvectors of tridiagonal matrix
+  int ifail[NN];
+  int info;
+  int total = grid->_Nprocessors;
+  int node  = grid->_processor;
+  int interval = (NN/total)+1;
+  double vl = 0.0, vu = 0.0;
+  int il = interval*node+1 , iu = interval*(node+1);
+  if (iu > NN)  iu=NN;
+  double tol = 0.0;
+  if (1) {
+    memset(evals_tmp,0,sizeof(double)*NN);
+    if ( il <= NN){
+      LAPACK_dstegr(&jobz, &range, &NN,
+		    (double*)DD, (double*)EE,
+		    &vl, &vu, &il, &iu, // these four are ignored if second parameteris 'A'
+		    &tol, // tolerance
+		    &evals_found, evals_tmp, (double*)evec_tmp, &NN,
+		    isuppz,
+		    work, &lwork, iwork, &liwork,
+		    &info);
+      for (int i = iu-1; i>= il-1; i--){
+	evals_tmp[i] = evals_tmp[i - (il-1)];
+	if (il>1) evals_tmp[i-(il-1)]=0.;
+	for (int j = 0; j< NN; j++){
+	  evec_tmp[i][j] = evec_tmp[i - (il-1)][j];
+	  if (il>1) evec_tmp[i-(il-1)][j]=0.;
+	}
+      }
+    }
+    {
+      grid->GlobalSumVector(evals_tmp,NN);
+      grid->GlobalSumVector((double*)evec_tmp,NN*NN);
+    }
+  } 
+  // Safer to sort instead of just reversing it, 
+  // but the document of the routine says evals are sorted in increasing order. 
+  // qr gives evals in decreasing order.
+  for(int i=0;i<NN;i++){
+    lmd [NN-1-i]=evals_tmp[i];
+    for(int j=0;j<NN;j++){
+      Qt((NN-1-i),j)=evec_tmp[i][j];
+    }
+  }
+#else 
+  assert(0);
+#endif
+}
+
+  void diagonalize_QR(std::vector<RealD>& lmd, std::vector<RealD>& lme, 
+		      int Nk, int Nm,   
+		      Eigen::MatrixXd & Qt,
+		      GridBase *grid)
+  {
+    int Niter = 100*Nm;
+    int kmin = 1;
+    int kmax = Nk;
+
+    // (this should be more sophisticated)
+    for(int iter=0; iter<Niter; ++iter){
+      
+      // determination of 2x2 leading submatrix
+      RealD dsub = lmd[kmax-1]-lmd[kmax-2];
+      RealD dd = sqrt(dsub*dsub + 4.0*lme[kmax-2]*lme[kmax-2]);
+      RealD Dsh = 0.5*(lmd[kmax-2]+lmd[kmax-1] +dd*(dsub/fabs(dsub)));
+      // (Dsh: shift)
+	
+      // transformation
+      qr_decomp(lmd,lme,Nk,Nm,Qt,Dsh,kmin,kmax); // Nk, Nm
+	
+      // Convergence criterion (redef of kmin and kamx)
+      for(int j=kmax-1; j>= kmin; --j){
+	RealD dds = fabs(lmd[j-1])+fabs(lmd[j]);
+	if(fabs(lme[j-1])+dds > dds){
+	  kmax = j+1;
+	  goto continued;
+	}
+      }
+      Niter = iter;
+      return;
+
+    continued:
+      for(int j=0; j<kmax-1; ++j){
+	RealD dds = fabs(lmd[j])+fabs(lmd[j+1]);
+	if(fabs(lme[j])+dds > dds){
+	  kmin = j+1;
+	  break;
+	}
+      }
+    }
+    std::cout << GridLogError << "[QL method] Error - Too many iteration: "<<Niter<<"\n";
+    abort();
+  }
+
+ };
+}
+#endif