Actual source code: ks-lrep.c

      1: /*
      2:    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
      3:    SLEPc - Scalable Library for Eigenvalue Problem Computations
      4:    Copyright (c) 2002-, Universitat Politecnica de Valencia, Spain

      6:    This file is part of SLEPc.
      7:    SLEPc is distributed under a 2-clause BSD license (see LICENSE).
      8:    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
      9: */
     10: /*
     11:    SLEPc eigensolver: "krylovschur"

     13:    Method: thick-restarted Lanczos for Linear Response eigenvalue problems

     15:    References:

     17:        [1] Z. Teng, R.-C. Li, "Convergence analysis of Lanczos-type methods for the
     18:            linear response eigenvalue problem", J. Comput. Appl. Math. 247, 2013.

     20:        [2] F. Alvarruiz, B. Mellado-Pinto, J. E. Roman, "Restarted Lanczos methods
     21:            for the linear response eigenvalue problem", in preparation, 2026.

     23: */
     24: #include <slepc/private/epsimpl.h>
     25: #include "krylovschur.h"

     27: static PetscErrorCode Orthog_Teng(Vec x,BV U,BV V,PetscInt j,PetscScalar *h,PetscScalar *c)
     28: {
     29:   PetscInt i;

     31:   PetscFunctionBegin;
     32:   PetscCall(BVSetActiveColumns(U,0,j));
     33:   PetscCall(BVSetActiveColumns(V,0,j));
     34:   /* c = U^* x */
     35:   PetscCall(BVDotVec(U,x,c));
     36:   /* x = x-V*c */
     37:   PetscCall(BVMultVec(V,-1.0,1.0,x,c));
     38:   /* accumulate orthog coeffs into h */
     39:   for (i=0;i<2*j;i++) h[i] += c[i];
     40:   PetscFunctionReturn(PETSC_SUCCESS);
     41: }

     43: /* Orthogonalize vector x against first j vectors in U and V
     44: v is column j-1 of V */
     45: static PetscErrorCode OrthogonalizeVector_Teng(Vec x,BV U,BV V,PetscInt j,Vec u,PetscReal *beta,PetscInt k,PetscScalar *h)
     46: {
     47:   PetscReal alpha;
     48:   PetscInt  i,l;

     50:   PetscFunctionBegin;
     51:   PetscCall(PetscArrayzero(h,2*j));

     53:   /* Local orthogonalization */
     54:   l = j==k+1?0:j-2;  /* 1st column to orthogonalize against */
     55:   PetscCall(VecDotRealPart(x,u,&alpha));
     56:   for (i=l;i<j-1;i++) h[i] = beta[i];
     57:   h[j-1] = alpha;
     58:   /* x = x-V(:,l:j-1)*h(l:j-1) */
     59:   PetscCall(BVSetActiveColumns(V,l,j));
     60:   PetscCall(BVMultVec(V,-1.0,1.0,x,h+l));

     62:   /* Full orthogonalization */
     63:   PetscCall(Orthog_Teng(x,U,V,j,h,h+2*j));
     64:   PetscFunctionReturn(PETSC_SUCCESS);
     65: }

     67: static PetscErrorCode EPSLREPLanczos_Teng(EPS eps,Mat K,Mat M,BV U,BV V,PetscReal *alpha,PetscReal *beta,PetscInt k,PetscInt *min,PetscBool *breakdown)
     68: {
     69:   PetscInt       j,m = *min;
     70:   Vec            u,v,uh,vh;
     71:   PetscReal      beta0;
     72:   PetscScalar    *hwork,lhwork[100],gamma;
     73:   PetscBool      alloc=PETSC_FALSE;

     75:   PetscFunctionBegin;
     76:   if (4*m > 100) {
     77:     PetscCall(PetscMalloc1(4*m,&hwork));
     78:     alloc = PETSC_TRUE;
     79:   } else hwork = lhwork;

     81:   /* Normalize initial vector */
     82:   if (k==0) {
     83:     if (eps->nini==0) PetscCall(BVSetRandomColumn(V,0));
     84:     PetscCall(BVGetColumn(U,0,&u));
     85:     PetscCall(BVGetColumn(V,0,&v));
     86:     PetscCall(MatMult(M,v,u));
     87:     PetscCall(VecDot(u,v,&gamma));
     88:     beta0 = PetscSqrtReal(PetscRealPart(gamma));
     89:     if (beta0==0.0) {
     90:       if (breakdown) *breakdown = PETSC_TRUE;
     91:       *min = 1; m = 0;
     92:     } else {
     93:       PetscCall(VecScale(u,1.0/beta0));
     94:       PetscCall(VecScale(v,1.0/beta0));
     95:     }
     96:     PetscCall(BVRestoreColumn(U,0,&u));
     97:     PetscCall(BVRestoreColumn(V,0,&v));
     98:   }

    100:   for (j=k;j<m;j++) {
    101:     /* j+1 columns (indices 0 to j) have been computed */
    102:     PetscCall(BVGetColumn(U,j+1,&uh));
    103:     PetscCall(BVGetColumn(V,j+1,&vh));
    104:     PetscCall(BVGetColumn(U,j,&u));
    105:     PetscCall(MatMult(K,u,vh));
    106:     PetscCall(OrthogonalizeVector_Teng(vh,U,V,j+1,u,beta,k,hwork));
    107:     alpha[j] = PetscRealPart(hwork[j]);
    108:     PetscCall(MatMult(M,vh,uh));
    109:     PetscCall(VecDot(uh,vh,&gamma));
    110:     beta[j] = PetscSqrtReal(PetscRealPart(gamma));
    111:     if (beta[j]==0.0) {
    112:       if (breakdown) *breakdown = PETSC_TRUE;
    113:       *min = j+1; m = j;
    114:     } else {
    115:       PetscCall(VecScale(uh,1.0/beta[j]));
    116:       PetscCall(VecScale(vh,1.0/beta[j]));
    117:     }
    118:     PetscCall(BVRestoreColumn(U,j+1,&uh));
    119:     PetscCall(BVRestoreColumn(V,j+1,&vh));
    120:     PetscCall(BVRestoreColumn(U,j,&u));
    121:   }
    122:   if (alloc) PetscCall(PetscFree(hwork));
    123:   PetscFunctionReturn(PETSC_SUCCESS);
    124: }

    126: static PetscErrorCode EPSComputeVectors_LREP_Teng(EPS eps)
    127: {
    128:   Mat         H;
    129:   Vec         u,v,w;
    130:   BV          U,V;
    131:   IS          is[2];
    132:   PetscInt    k;
    133:   PetscScalar lambda;
    134:   PetscBool   reduced;

    136:   PetscFunctionBegin;
    137:   PetscCall(STGetMatrix(eps->st,0,&H));
    138:   PetscCall(MatNestGetISs(H,is,NULL));
    139:   PetscCall(SlepcCheckMatLREPReduced(H,&reduced));
    140:   PetscCall(BVGetSplitRows(eps->V,is[0],is[1],&V,&U));
    141:   for (k=0;k<eps->nconv;k++) {
    142:     PetscCall(BVGetColumn(V,k,&v));
    143:     /* approx eigenvector is [eigr[k]*v; u] */
    144:     lambda = eps->eigr[k];
    145:     PetscCall(STBackTransform(eps->st,1,&lambda,&eps->eigi[k]));
    146:     PetscCall(VecScale(v,lambda));
    147:     PetscCall(BVRestoreColumn(V,k,&v));
    148:   }
    149:   if (!reduced) {
    150:     /* the eigenvector [v;u] = J*[y;x] where [y;x] is the reduced eigenvector
    151:        and J = 1/sqrt(2)[I I; I -I], i.e, v=1/sqrt(2)*(y+x) u=1/sqrt(2)*(y-x) */
    152:     PetscCall(BVCreateVec(V,&w));
    153:     for (k=0;k<eps->nconv;k++) {
    154:       PetscCall(BVGetColumn(U,k,&u));
    155:       PetscCall(BVGetColumn(V,k,&v));
    156:       PetscCall(VecCopy(u,w));
    157:       PetscCall(VecCopy(v,u));
    158:       PetscCall(VecAXPY(u,-1.0,w));
    159:       PetscCall(VecAXPY(v,1.0,w));
    160:       PetscCall(BVRestoreColumn(U,k,&u));
    161:       PetscCall(BVRestoreColumn(V,k,&v));
    162:     }
    163:     PetscCall(VecDestroy(&w));
    164:   }
    165:   PetscCall(BVRestoreSplitRows(eps->V,is[0],is[1],&V,&U));
    166:   /* Normalize eigenvectors */
    167:   PetscCall(BVSetActiveColumns(eps->V,0,eps->nconv));
    168:   PetscCall(BVNormalize(eps->V,NULL));
    169:   PetscFunctionReturn(PETSC_SUCCESS);
    170: }

    172: PetscErrorCode EPSSetUp_KrylovSchur_LREP(EPS eps)
    173: {
    174:   EPS_KRYLOVSCHUR *ctx = (EPS_KRYLOVSCHUR*)eps->data;
    175:   PetscBool       flg;

    177:   PetscFunctionBegin;
    178:   PetscCheck((eps->problem_type==EPS_LREP),PetscObjectComm((PetscObject)eps),PETSC_ERR_ARG_WRONGSTATE,"Problem type should be LREP");
    179:   EPSCheckUnsupportedCondition(eps,EPS_FEATURE_ARBITRARY | EPS_FEATURE_REGION | EPS_FEATURE_EXTRACTION | EPS_FEATURE_BALANCE,PETSC_TRUE," with LREP structure");
    180:   PetscCall(EPSSetDimensions_Default(eps,&eps->nev,&eps->ncv,&eps->mpd));
    181:   PetscCheck(eps->ncv<=eps->nev+eps->mpd,PetscObjectComm((PetscObject)eps),PETSC_ERR_USER_INPUT,"The value of ncv must not be larger than nev+mpd");
    182:   if (eps->max_it==PETSC_DETERMINE) eps->max_it = PetscMax(100,2*eps->n/eps->ncv)*((eps->stop==EPS_STOP_THRESHOLD)?10:1);

    184:   PetscCall(PetscObjectTypeCompare((PetscObject)eps->st,STSHIFT,&flg));
    185:   PetscCheck(flg,PetscObjectComm((PetscObject)eps),PETSC_ERR_SUP,"Krylov-Schur LREP only supports shift ST");
    186:   if (!eps->which) eps->which = EPS_SMALLEST_MAGNITUDE;

    188:   if (!ctx->keep) ctx->keep = 0.5;
    189:   PetscCall(STSetStructured(eps->st,PETSC_FALSE));

    191:   PetscCall(EPSAllocateSolution(eps,1));
    192:   /* Teng */
    193:   eps->ops->solve = EPSSolve_KrylovSchur_LREP_Teng;
    194:   eps->ops->computevectors = EPSComputeVectors_LREP_Teng;
    195:   PetscCall(DSSetType(eps->ds,DSHEP));
    196:   PetscCall(DSSetCompact(eps->ds,PETSC_TRUE));
    197:   PetscCall(DSSetExtraRow(eps->ds,PETSC_TRUE));
    198:   PetscCall(DSAllocate(eps->ds,eps->ncv+1));
    199:   PetscFunctionReturn(PETSC_SUCCESS);
    200: }

    202: PetscErrorCode EPSSolve_KrylovSchur_LREP_Teng(EPS eps)
    203: {
    204:   EPS_KRYLOVSCHUR   *ctx = (EPS_KRYLOVSCHUR*)eps->data;
    205:   PetscInt          i,k,l,ld,nv,nconv=0,nevsave,ma,na,Ma,Na;
    206:   Mat               H,Q,K,M,A,B;
    207:   BV                U,V;
    208:   IS                is[2];
    209:   PetscReal         *a,*b,beta;
    210:   PetscBool         reduced,breakdown=PETSC_FALSE;
    211:   const PetscScalar scal[] = { 1.0, -1.0 };

    213:   PetscFunctionBegin;
    214:   PetscCall(DSGetLeadingDimension(eps->ds,&ld));

    216:   /* Extract matrix blocks */
    217:   PetscCall(STGetMatrix(eps->st,0,&H));
    218:   PetscCall(MatNestGetISs(H,is,NULL));
    219:   PetscCall(SlepcCheckMatLREPReduced(H,&reduced));
    220:   if (reduced) {
    221:     PetscCall(MatNestGetSubMat(H,0,1,&K));
    222:     PetscCall(MatNestGetSubMat(H,1,0,&M));
    223:   } else {
    224:     PetscCall(MatNestGetSubMat(H,0,0,&A));
    225:     PetscCall(MatNestGetSubMat(H,0,1,&B));
    226:     PetscCall(MatGetSize(A,&Ma,&Na));
    227:     PetscCall(MatGetLocalSize(A,&ma,&na));
    228:     /* K = A-B */
    229:     PetscCall(MatCreate(PetscObjectComm((PetscObject)A),&K));
    230:     PetscCall(MatSetSizes(K,ma,na,Ma,Na));
    231:     PetscCall(MatSetType(K,MATCOMPOSITE));
    232:     PetscCall(MatCompositeAddMat(K,A));
    233:     PetscCall(MatCompositeAddMat(K,B));
    234:     PetscCall(MatAssemblyBegin(K,MAT_FINAL_ASSEMBLY));
    235:     PetscCall(MatAssemblyEnd(K,MAT_FINAL_ASSEMBLY));
    236:     PetscCall(MatCompositeSetScalings(K,scal));
    237:     /* M = A+B */
    238:     PetscCall(MatCreate(PetscObjectComm((PetscObject)A),&M));
    239:     PetscCall(MatSetSizes(M,ma,na,Ma,Na));
    240:     PetscCall(MatSetType(M,MATCOMPOSITE));
    241:     PetscCall(MatCompositeAddMat(M,A));
    242:     PetscCall(MatCompositeAddMat(M,B));
    243:     PetscCall(MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY));
    244:     PetscCall(MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY));
    245:   }

    247:   /* Get the split bases */
    248:   PetscCall(BVGetSplitRows(eps->V,is[0],is[1],&V,&U));

    250:   nevsave  = eps->nev;
    251:   eps->nev = (eps->nev+1)/2;
    252:   l = 0;

    254:   /* Restart loop */
    255:   while (eps->reason == EPS_CONVERGED_ITERATING) {
    256:     eps->its++;

    258:     /* Compute an nv-step Lanczos factorization */
    259:     nv = PetscMin(eps->nconv+eps->mpd,eps->ncv);
    260:     PetscCall(DSSetDimensions(eps->ds,nv,eps->nconv,eps->nconv+l));
    261:     PetscCall(DSGetArrayReal(eps->ds,DS_MAT_T,&a));
    262:     b = a + ld;
    263:     PetscCall(EPSLREPLanczos_Teng(eps,K,M,U,V,a,b,eps->nconv+l,&nv,&breakdown));
    264:     beta = b[nv-1];
    265:     PetscCall(DSRestoreArrayReal(eps->ds,DS_MAT_T,&a));
    266:     PetscCall(DSSetDimensions(eps->ds,nv,eps->nconv,eps->nconv+l));
    267:     PetscCall(DSSetState(eps->ds,l?DS_STATE_RAW:DS_STATE_INTERMEDIATE));
    268:     PetscCall(BVSetActiveColumns(eps->V,eps->nconv,nv));

    270:     /* Solve projected problem */
    271:     PetscCall(DSSolve(eps->ds,eps->eigr,eps->eigi));
    272:     PetscCall(DSSort(eps->ds,eps->eigr,eps->eigi,NULL,NULL,NULL));
    273:     PetscCall(DSUpdateExtraRow(eps->ds));
    274:     PetscCall(DSSynchronize(eps->ds,eps->eigr,eps->eigi));

    276:     /* Check convergence */
    277:     for (i=0;i<nv;i++) eps->eigr[i] = PetscSqrtReal(PetscRealPart(eps->eigr[i]));
    278:     PetscCall(EPSKrylovConvergence(eps,PETSC_FALSE,eps->nconv,nv-eps->nconv,beta,0.0,1.0,&k));
    279:     EPSSetCtxThreshold(eps,eps->eigr,eps->eigi,eps->errest,k,nv);
    280:     PetscCall((*eps->stopping)(eps,eps->its,eps->max_it,k,eps->nev,&eps->reason,eps->stoppingctx));
    281:     nconv = k;

    283:     /* Update l */
    284:     if (eps->reason != EPS_CONVERGED_ITERATING || breakdown || k==nv) l = 0;
    285:     else l = PetscMax(1,(PetscInt)((nv-k)*ctx->keep));
    286:     if (!ctx->lock && l>0) { l += k; k = 0; } /* non-locking variant: reset no. of converged pairs */
    287:     if (l) PetscCall(PetscInfo(eps,"Preparing to restart keeping l=%" PetscInt_FMT " vectors\n",l));

    289:     if (eps->reason == EPS_CONVERGED_ITERATING) {
    290:       PetscCheck(!breakdown,PetscObjectComm((PetscObject)eps),PETSC_ERR_CONV_FAILED,"Breakdown in LREP Krylov-Schur (beta=%g)",(double)beta);
    291:       /* Prepare the Rayleigh quotient for restart */
    292:       PetscCall(DSTruncate(eps->ds,k+l,PETSC_FALSE));
    293:     }
    294:     /* Update the corresponding vectors
    295:        U(:,idx) = U*Q(:,idx),  V(:,idx) = V*Q(:,idx) */
    296:     PetscCall(DSGetMat(eps->ds,DS_MAT_Q,&Q));
    297:     PetscCall(BVMultInPlace(U,Q,eps->nconv,k+l));
    298:     PetscCall(BVMultInPlace(V,Q,eps->nconv,k+l));
    299:     PetscCall(DSRestoreMat(eps->ds,DS_MAT_Q,&Q));

    301:     if (eps->reason == EPS_CONVERGED_ITERATING && !breakdown) {
    302:       PetscCall(BVCopyColumn(eps->V,nv,k+l));
    303:       if (eps->stop==EPS_STOP_THRESHOLD && nv-k<5) {  /* reallocate */
    304:         eps->ncv = eps->mpd+k;
    305:         PetscCall(BVRestoreSplitRows(eps->V,is[0],is[1],&V,&U));
    306:         PetscCall(EPSReallocateSolution(eps,eps->ncv+1));
    307:         PetscCall(BVGetSplitRows(eps->V,is[0],is[1],&V,&U));
    308:         for (i=nv;i<eps->ncv;i++) eps->perm[i] = i;
    309:         PetscCall(DSReallocate(eps->ds,eps->ncv+1));
    310:         PetscCall(DSGetLeadingDimension(eps->ds,&ld));
    311:       }
    312:     }
    313:     eps->nconv = k;
    314:     PetscCall(EPSMonitor(eps,eps->its,nconv,eps->eigr,eps->eigi,eps->errest,nv));
    315:   }

    317:   eps->nev = nevsave;

    319:   PetscCall(DSTruncate(eps->ds,eps->nconv,PETSC_TRUE));
    320:   PetscCall(BVRestoreSplitRows(eps->V,is[0],is[1],&V,&U));
    321:   if (!reduced) {
    322:     PetscCall(MatDestroy(&K));
    323:     PetscCall(MatDestroy(&M));
    324:   }
    325:   PetscFunctionReturn(PETSC_SUCCESS);
    326: }