Date: 2026-03-09T09:12:00+00:00

Actual source code: qarnoldi.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 quadratic eigensolver: "qarnoldi"

     13:    Method: Q-Arnoldi

     15:    Algorithm:

     17:        Quadratic Arnoldi with Krylov-Schur type restart.

     19:    References:

     21:        [1] K. Meerbergen, "The Quadratic Arnoldi method for the solution
     22:            of the quadratic eigenvalue problem", SIAM J. Matrix Anal.
     23:            Appl. 30(4):1462-1482, 2009.
     24: */

     26: #include <slepc/private/pepimpl.h>
     27: #include <petscblaslapack.h>

     29: typedef struct {
     30:   PetscReal keep;         /* restart parameter */
     31:   PetscBool lock;         /* locking/non-locking variant */
     32: } PEP_QARNOLDI;

     34: static PetscErrorCode PEPSetUp_QArnoldi(PEP pep)
     35: {
     36:   PEP_QARNOLDI   *ctx = (PEP_QARNOLDI*)pep->data;
     37:   PetscBool      flg;

     39:   PetscFunctionBegin;
     40:   PEPCheckQuadratic(pep);
     41:   PEPCheckShiftSinvert(pep);
     42:   PetscCall(PEPSetDimensions_Default(pep,pep->nev,&pep->ncv,&pep->mpd));
     43:   PetscCheck(ctx->lock || pep->mpd>=pep->ncv,PetscObjectComm((PetscObject)pep),PETSC_ERR_SUP,"Should not use mpd parameter in non-locking variant");
     44:   if (pep->max_it==PETSC_DETERMINE) pep->max_it = PetscMax(100,4*pep->n/pep->ncv);
     45:   if (!pep->which) PetscCall(PEPSetWhichEigenpairs_Default(pep));
     46:   PetscCheck(pep->which!=PEP_ALL,PetscObjectComm((PetscObject)pep),PETSC_ERR_SUP,"This solver does not support computing all eigenvalues");

     48:   PetscCall(STGetTransform(pep->st,&flg));
     49:   PetscCheck(flg,PetscObjectComm((PetscObject)pep),PETSC_ERR_SUP,"Solver requires the ST transformation flag set, see STSetTransform()");

     51:   /* set default extraction */
     52:   if (!pep->extract) pep->extract = PEP_EXTRACT_NONE;
     53:   PEPCheckUnsupported(pep,PEP_FEATURE_NONMONOMIAL | PEP_FEATURE_EXTRACT);

     55:   if (!ctx->keep) ctx->keep = 0.5;

     57:   PetscCall(PEPAllocateSolution(pep,0));
     58:   PetscCall(PEPSetWorkVecs(pep,4));

     60:   PetscCall(DSSetType(pep->ds,DSNHEP));
     61:   PetscCall(DSSetExtraRow(pep->ds,PETSC_TRUE));
     62:   PetscCall(DSAllocate(pep->ds,pep->ncv+1));
     63:   PetscFunctionReturn(PETSC_SUCCESS);
     64: }

     66: static PetscErrorCode PEPExtractVectors_QArnoldi(PEP pep)
     67: {
     68:   PetscInt       k=pep->nconv;
     69:   Mat            X,X0;

     71:   PetscFunctionBegin;
     72:   if (pep->nconv==0) PetscFunctionReturn(PETSC_SUCCESS);
     73:   PetscCall(DSVectors(pep->ds,DS_MAT_X,NULL,NULL));

     75:   /* update vectors V = V*X */
     76:   PetscCall(DSGetMat(pep->ds,DS_MAT_X,&X));
     77:   PetscCall(MatDenseGetSubMatrix(X,0,k,0,k,&X0));
     78:   PetscCall(BVMultInPlace(pep->V,X0,0,k));
     79:   PetscCall(MatDenseRestoreSubMatrix(X,&X0));
     80:   PetscCall(DSRestoreMat(pep->ds,DS_MAT_X,&X));
     81:   PetscFunctionReturn(PETSC_SUCCESS);
     82: }

     84: /*
     85:   Compute a step of Classical Gram-Schmidt orthogonalization
     86: */
     87: static PetscErrorCode PEPQArnoldiCGS(PEP pep,PetscScalar *H,PetscBLASInt ldh,PetscScalar *h,PetscBLASInt j,BV V,Vec t,Vec v,Vec w,PetscReal *onorm,PetscReal *norm,PetscScalar *work)
     88: {
     89:   PetscBLASInt   ione = 1,j_1 = j+1;
     90:   PetscReal      x,y;
     91:   PetscScalar    dot,one = 1.0,zero = 0.0;

     93:   PetscFunctionBegin;
     94:   /* compute norm of v and w */
     95:   if (onorm) {
     96:     PetscCall(VecNorm(v,NORM_2,&x));
     97:     PetscCall(VecNorm(w,NORM_2,&y));
     98:     *onorm = SlepcAbs(x,y);
     99:   }

    101:   /* orthogonalize: compute h */
    102:   PetscCall(BVDotVec(V,v,h));
    103:   PetscCall(BVDotVec(V,w,work));
    104:   if (j>0) PetscCallBLAS("BLASgemv",BLASgemv_("C",&j_1,&j,&one,H,&ldh,work,&ione,&one,h,&ione));
    105:   PetscCall(VecDot(w,t,&dot));
    106:   h[j] += dot;

    108:   /* orthogonalize: update v and w */
    109:   PetscCall(BVMultVec(V,-1.0,1.0,v,h));
    110:   if (j>0) {
    111:     PetscCallBLAS("BLASgemv",BLASgemv_("N",&j_1,&j,&one,H,&ldh,h,&ione,&zero,work,&ione));
    112:     PetscCall(BVMultVec(V,-1.0,1.0,w,work));
    113:   }
    114:   PetscCall(VecAXPY(w,-h[j],t));

    116:   /* compute norm of v and w */
    117:   if (norm) {
    118:     PetscCall(VecNorm(v,NORM_2,&x));
    119:     PetscCall(VecNorm(w,NORM_2,&y));
    120:     *norm = SlepcAbs(x,y);
    121:   }
    122:   PetscFunctionReturn(PETSC_SUCCESS);
    123: }

    125: /*
    126:   Compute a run of Q-Arnoldi iterations
    127: */
    128: static PetscErrorCode PEPQArnoldi(PEP pep,Mat A,PetscInt k,PetscInt *M,Vec v,Vec w,PetscReal *beta,PetscBool *breakdown,PetscScalar *work)
    129: {
    130:   PetscInt           i,j,l,m = *M,ldh;
    131:   PetscBLASInt       jj,ldhh;
    132:   Vec                t = pep->work[2],u = pep->work[3];
    133:   BVOrthogRefineType refinement;
    134:   PetscReal          norm=0.0,onorm,eta;
    135:   PetscScalar        *H,*c = work + m;

    137:   PetscFunctionBegin;
    138:   *beta = 0.0;
    139:   PetscCall(MatDenseGetArray(A,&H));
    140:   PetscCall(MatDenseGetLDA(A,&ldh));
    141:   PetscCall(BVGetOrthogonalization(pep->V,NULL,&refinement,&eta,NULL));
    142:   PetscCall(BVInsertVec(pep->V,k,v));
    143:   for (j=k;j<m;j++) {
    144:     /* apply operator */
    145:     PetscCall(VecCopy(w,t));
    146:     if (pep->Dr) PetscCall(VecPointwiseMult(v,v,pep->Dr));
    147:     PetscCall(STMatMult(pep->st,0,v,u));
    148:     PetscCall(VecCopy(t,v));
    149:     if (pep->Dr) PetscCall(VecPointwiseMult(t,t,pep->Dr));
    150:     PetscCall(STMatMult(pep->st,1,t,w));
    151:     PetscCall(VecAXPY(u,pep->sfactor,w));
    152:     PetscCall(STMatSolve(pep->st,u,w));
    153:     PetscCall(VecScale(w,-1.0/(pep->sfactor*pep->sfactor)));
    154:     if (pep->Dr) PetscCall(VecPointwiseDivide(w,w,pep->Dr));
    155:     PetscCall(VecCopy(v,t));
    156:     PetscCall(BVSetActiveColumns(pep->V,0,j+1));

    158:     /* orthogonalize */
    159:     PetscCall(PetscBLASIntCast(j,&jj));
    160:     PetscCall(PetscBLASIntCast(ldh,&ldhh));
    161:     switch (refinement) {
    162:       case BV_ORTHOG_REFINE_NEVER:
    163:         PetscCall(PEPQArnoldiCGS(pep,H,ldhh,H+ldh*j,jj,pep->V,t,v,w,NULL,&norm,work));
    164:         *breakdown = PETSC_FALSE;
    165:         break;
    166:       case BV_ORTHOG_REFINE_ALWAYS:
    167:         PetscCall(PEPQArnoldiCGS(pep,H,ldhh,H+ldh*j,jj,pep->V,t,v,w,NULL,NULL,work));
    168:         PetscCall(PEPQArnoldiCGS(pep,H,ldhh,c,jj,pep->V,t,v,w,&onorm,&norm,work));
    169:         for (i=0;i<=j;i++) H[ldh*j+i] += c[i];
    170:         if (norm < eta * onorm) *breakdown = PETSC_TRUE;
    171:         else *breakdown = PETSC_FALSE;
    172:         break;
    173:       case BV_ORTHOG_REFINE_IFNEEDED:
    174:         PetscCall(PEPQArnoldiCGS(pep,H,ldhh,H+ldh*j,jj,pep->V,t,v,w,&onorm,&norm,work));
    175:         /* ||q|| < eta ||h|| */
    176:         l = 1;
    177:         while (l<3 && norm < eta * onorm) {
    178:           l++;
    179:           onorm = norm;
    180:           PetscCall(PEPQArnoldiCGS(pep,H,ldhh,c,jj,pep->V,t,v,w,NULL,&norm,work));
    181:           for (i=0;i<=j;i++) H[ldh*j+i] += c[i];
    182:         }
    183:         if (norm < eta * onorm) *breakdown = PETSC_TRUE;
    184:         else *breakdown = PETSC_FALSE;
    185:         break;
    186:     }
    187:     PetscCall(VecScale(v,1.0/norm));
    188:     PetscCall(VecScale(w,1.0/norm));

    190:     H[j+1+ldh*j] = norm;
    191:     if (j<m-1) PetscCall(BVInsertVec(pep->V,j+1,v));
    192:   }
    193:   *beta = norm;
    194:   PetscCall(MatDenseRestoreArray(A,&H));
    195:   PetscFunctionReturn(PETSC_SUCCESS);
    196: }

    198: static PetscErrorCode PEPSolve_QArnoldi(PEP pep)
    199: {
    200:   PEP_QARNOLDI   *ctx = (PEP_QARNOLDI*)pep->data;
    201:   PetscInt       j,k,l,lwork,nv,nconv;
    202:   Vec            v=pep->work[0],w=pep->work[1];
    203:   Mat            Q,S;
    204:   PetscScalar    *work;
    205:   PetscReal      beta,norm,x,y;
    206:   PetscBool      breakdown=PETSC_FALSE,sinv;

    208:   PetscFunctionBegin;
    209:   lwork = 7*pep->ncv;
    210:   PetscCall(PetscMalloc1(lwork,&work));
    211:   PetscCall(PetscObjectTypeCompare((PetscObject)pep->st,STSINVERT,&sinv));
    212:   PetscCall(RGPushScale(pep->rg,sinv?pep->sfactor:1.0/pep->sfactor));
    213:   PetscCall(STScaleShift(pep->st,sinv?pep->sfactor:1.0/pep->sfactor));

    215:   /* Get the starting Arnoldi vector */
    216:   for (j=0;j<2;j++) {
    217:     if (j>=pep->nini) PetscCall(BVSetRandomColumn(pep->V,j));
    218:   }
    219:   PetscCall(BVCopyVec(pep->V,0,v));
    220:   PetscCall(BVCopyVec(pep->V,1,w));
    221:   PetscCall(VecNorm(v,NORM_2,&x));
    222:   PetscCall(VecNorm(w,NORM_2,&y));
    223:   norm = SlepcAbs(x,y);
    224:   PetscCall(VecScale(v,1.0/norm));
    225:   PetscCall(VecScale(w,1.0/norm));

    227:   /* clean projected matrix (including the extra-arrow) */
    228:   PetscCall(DSSetDimensions(pep->ds,PETSC_DETERMINE,PETSC_DETERMINE,PETSC_DETERMINE));
    229:   PetscCall(DSGetMat(pep->ds,DS_MAT_A,&S));
    230:   PetscCall(MatZeroEntries(S));
    231:   PetscCall(DSRestoreMat(pep->ds,DS_MAT_A,&S));

    233:    /* Restart loop */
    234:   l = 0;
    235:   while (pep->reason == PEP_CONVERGED_ITERATING) {
    236:     pep->its++;

    238:     /* Compute an nv-step Arnoldi factorization */
    239:     nv = PetscMin(pep->nconv+pep->mpd,pep->ncv);
    240:     PetscCall(DSGetMat(pep->ds,DS_MAT_A,&S));
    241:     PetscCall(PEPQArnoldi(pep,S,pep->nconv+l,&nv,v,w,&beta,&breakdown,work));
    242:     PetscCall(DSRestoreMat(pep->ds,DS_MAT_A,&S));
    243:     PetscCall(DSSetDimensions(pep->ds,nv,pep->nconv,pep->nconv+l));
    244:     PetscCall(DSSetState(pep->ds,l?DS_STATE_RAW:DS_STATE_INTERMEDIATE));
    245:     PetscCall(BVSetActiveColumns(pep->V,pep->nconv,nv));

    247:     /* Solve projected problem */
    248:     PetscCall(DSSolve(pep->ds,pep->eigr,pep->eigi));
    249:     PetscCall(DSSort(pep->ds,pep->eigr,pep->eigi,NULL,NULL,NULL));
    250:     PetscCall(DSUpdateExtraRow(pep->ds));
    251:     PetscCall(DSSynchronize(pep->ds,pep->eigr,pep->eigi));

    253:     /* Check convergence */
    254:     PetscCall(PEPKrylovConvergence(pep,PETSC_FALSE,pep->nconv,nv-pep->nconv,beta,&k));
    255:     PetscCall((*pep->stopping)(pep,pep->its,pep->max_it,k,pep->nev,&pep->reason,pep->stoppingctx));
    256:     nconv = k;

    258:     /* Update l */
    259:     if (pep->reason != PEP_CONVERGED_ITERATING || breakdown) l = 0;
    260:     else {
    261:       l = PetscMax(1,(PetscInt)((nv-k)*ctx->keep));
    262:       PetscCall(DSGetTruncateSize(pep->ds,k,nv,&l));
    263:     }
    264:     if (!ctx->lock && l>0) { l += k; k = 0; } /* non-locking variant: reset no. of converged pairs */
    265:     if (l) PetscCall(PetscInfo(pep,"Preparing to restart keeping l=%" PetscInt_FMT " vectors\n",l));

    267:     if (pep->reason == PEP_CONVERGED_ITERATING) {
    268:       if (PetscUnlikely(breakdown)) {
    269:         /* Stop if breakdown */
    270:         PetscCall(PetscInfo(pep,"Breakdown Quadratic Arnoldi method (it=%" PetscInt_FMT " norm=%g)\n",pep->its,(double)beta));
    271:         pep->reason = PEP_DIVERGED_BREAKDOWN;
    272:       } else {
    273:         /* Prepare the Rayleigh quotient for restart */
    274:         PetscCall(DSTruncate(pep->ds,k+l,PETSC_FALSE));
    275:       }
    276:     }
    277:     /* Update the corresponding vectors V(:,idx) = V*Q(:,idx) */
    278:     PetscCall(DSGetMat(pep->ds,DS_MAT_Q,&Q));
    279:     PetscCall(BVMultInPlace(pep->V,Q,pep->nconv,k+l));
    280:     PetscCall(DSRestoreMat(pep->ds,DS_MAT_Q,&Q));

    282:     pep->nconv = k;
    283:     PetscCall(PEPMonitor(pep,pep->its,nconv,pep->eigr,pep->eigi,pep->errest,nv));
    284:   }
    285:   PetscCall(BVSetActiveColumns(pep->V,0,pep->nconv));
    286:   for (j=0;j<pep->nconv;j++) {
    287:     pep->eigr[j] *= pep->sfactor;
    288:     pep->eigi[j] *= pep->sfactor;
    289:   }

    291:   PetscCall(STScaleShift(pep->st,sinv?1.0/pep->sfactor:pep->sfactor));
    292:   PetscCall(RGPopScale(pep->rg));

    294:   PetscCall(DSTruncate(pep->ds,pep->nconv,PETSC_TRUE));
    295:   PetscCall(PetscFree(work));
    296:   PetscFunctionReturn(PETSC_SUCCESS);
    297: }

    299: static PetscErrorCode PEPQArnoldiSetRestart_QArnoldi(PEP pep,PetscReal keep)
    300: {
    301:   PEP_QARNOLDI *ctx = (PEP_QARNOLDI*)pep->data;

    303:   PetscFunctionBegin;
    304:   if (keep==(PetscReal)PETSC_DEFAULT || keep==(PetscReal)PETSC_DECIDE) ctx->keep = 0.5;
    305:   else {
    306:     PetscCheck(keep>=0.1 && keep<=0.9,PetscObjectComm((PetscObject)pep),PETSC_ERR_ARG_OUTOFRANGE,"The keep argument must be in the range [0.1,0.9]");
    307:     ctx->keep = keep;
    308:   }
    309:   PetscFunctionReturn(PETSC_SUCCESS);
    310: }

    312: /*@
    313:    PEPQArnoldiSetRestart - Sets the restart parameter for the Q-Arnoldi
    314:    method, in particular the proportion of basis vectors that must be kept
    315:    after restart.

    317:    Logically Collective

    319:    Input Parameters:
    320: +  pep  - the polynomial eigensolver context
    321: -  keep - the number of vectors to be kept at restart

    323:    Options Database Key:
    324: .  -pep_qarnoldi_restart \<keep\> - sets the restart parameter

    326:    Note:
    327:    Allowed values are in the range [0.1,0.9]. The default is 0.5.

    329:    Level: advanced

    331: .seealso: [](ch:pep), `PEPQARNOLDI`, `PEPQArnoldiGetRestart()`
    332: @*/
    333: PetscErrorCode PEPQArnoldiSetRestart(PEP pep,PetscReal keep)
    334: {
    335:   PetscFunctionBegin;
    338:   PetscTryMethod(pep,"PEPQArnoldiSetRestart_C",(PEP,PetscReal),(pep,keep));
    339:   PetscFunctionReturn(PETSC_SUCCESS);
    340: }

    342: static PetscErrorCode PEPQArnoldiGetRestart_QArnoldi(PEP pep,PetscReal *keep)
    343: {
    344:   PEP_QARNOLDI *ctx = (PEP_QARNOLDI*)pep->data;

    346:   PetscFunctionBegin;
    347:   *keep = ctx->keep;
    348:   PetscFunctionReturn(PETSC_SUCCESS);
    349: }

    351: /*@
    352:    PEPQArnoldiGetRestart - Gets the restart parameter used in the Q-Arnoldi method.

    354:    Not Collective

    356:    Input Parameter:
    357: .  pep - the polynomial eigensolver context

    359:    Output Parameter:
    360: .  keep - the restart parameter

    362:    Level: advanced

    364: .seealso: [](ch:pep), `PEPQARNOLDI`, `PEPQArnoldiSetRestart()`
    365: @*/
    366: PetscErrorCode PEPQArnoldiGetRestart(PEP pep,PetscReal *keep)
    367: {
    368:   PetscFunctionBegin;
    370:   PetscAssertPointer(keep,2);
    371:   PetscUseMethod(pep,"PEPQArnoldiGetRestart_C",(PEP,PetscReal*),(pep,keep));
    372:   PetscFunctionReturn(PETSC_SUCCESS);
    373: }

    375: static PetscErrorCode PEPQArnoldiSetLocking_QArnoldi(PEP pep,PetscBool lock)
    376: {
    377:   PEP_QARNOLDI *ctx = (PEP_QARNOLDI*)pep->data;

    379:   PetscFunctionBegin;
    380:   ctx->lock = lock;
    381:   PetscFunctionReturn(PETSC_SUCCESS);
    382: }

    384: /*@
    385:    PEPQArnoldiSetLocking - Choose between locking and non-locking variants of
    386:    the Q-Arnoldi method.

    388:    Logically Collective

    390:    Input Parameters:
    391: +  pep  - the polynomial eigensolver context
    392: -  lock - `PETSC_TRUE` if the locking variant must be selected

    394:    Options Database Key:
    395: .  -pep_qarnoldi_locking - sets the locking flag

    397:    Note:
    398:    The default is to lock converged eigenpairs when the method restarts.
    399:    This behavior can be changed so that all directions are kept in the
    400:    working subspace even if already converged to working accuracy (the
    401:    non-locking variant).

    403:    Level: advanced

    405: .seealso: [](ch:pep), `PEPQARNOLDI`, `PEPQArnoldiGetLocking()`
    406: @*/
    407: PetscErrorCode PEPQArnoldiSetLocking(PEP pep,PetscBool lock)
    408: {
    409:   PetscFunctionBegin;
    412:   PetscTryMethod(pep,"PEPQArnoldiSetLocking_C",(PEP,PetscBool),(pep,lock));
    413:   PetscFunctionReturn(PETSC_SUCCESS);
    414: }

    416: static PetscErrorCode PEPQArnoldiGetLocking_QArnoldi(PEP pep,PetscBool *lock)
    417: {
    418:   PEP_QARNOLDI *ctx = (PEP_QARNOLDI*)pep->data;

    420:   PetscFunctionBegin;
    421:   *lock = ctx->lock;
    422:   PetscFunctionReturn(PETSC_SUCCESS);
    423: }

    425: /*@
    426:    PEPQArnoldiGetLocking - Gets the locking flag used in the Q-Arnoldi method.

    428:    Not Collective

    430:    Input Parameter:
    431: .  pep - the polynomial eigensolver context

    433:    Output Parameter:
    434: .  lock - the locking flag

    436:    Level: advanced

    438: .seealso: [](ch:pep), `PEPQARNOLDI`, `PEPQArnoldiSetLocking()`
    439: @*/
    440: PetscErrorCode PEPQArnoldiGetLocking(PEP pep,PetscBool *lock)
    441: {
    442:   PetscFunctionBegin;
    444:   PetscAssertPointer(lock,2);
    445:   PetscUseMethod(pep,"PEPQArnoldiGetLocking_C",(PEP,PetscBool*),(pep,lock));
    446:   PetscFunctionReturn(PETSC_SUCCESS);
    447: }

    449: static PetscErrorCode PEPSetFromOptions_QArnoldi(PEP pep,PetscOptionItems PetscOptionsObject)
    450: {
    451:   PetscBool      flg,lock;
    452:   PetscReal      keep;

    454:   PetscFunctionBegin;
    455:   PetscOptionsHeadBegin(PetscOptionsObject,"PEP Q-Arnoldi Options");

    457:     PetscCall(PetscOptionsReal("-pep_qarnoldi_restart","Proportion of vectors kept after restart","PEPQArnoldiSetRestart",0.5,&keep,&flg));
    458:     if (flg) PetscCall(PEPQArnoldiSetRestart(pep,keep));

    460:     PetscCall(PetscOptionsBool("-pep_qarnoldi_locking","Choose between locking and non-locking variants","PEPQArnoldiSetLocking",PETSC_FALSE,&lock,&flg));
    461:     if (flg) PetscCall(PEPQArnoldiSetLocking(pep,lock));

    463:   PetscOptionsHeadEnd();
    464:   PetscFunctionReturn(PETSC_SUCCESS);
    465: }

    467: static PetscErrorCode PEPView_QArnoldi(PEP pep,PetscViewer viewer)
    468: {
    469:   PEP_QARNOLDI   *ctx = (PEP_QARNOLDI*)pep->data;
    470:   PetscBool      isascii;

    472:   PetscFunctionBegin;
    473:   PetscCall(PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&isascii));
    474:   if (isascii) {
    475:     PetscCall(PetscViewerASCIIPrintf(viewer,"  %d%% of basis vectors kept after restart\n",(int)(100*ctx->keep)));
    476:     PetscCall(PetscViewerASCIIPrintf(viewer,"  using the %slocking variant\n",ctx->lock?"":"non-"));
    477:   }
    478:   PetscFunctionReturn(PETSC_SUCCESS);
    479: }

    481: static PetscErrorCode PEPDestroy_QArnoldi(PEP pep)
    482: {
    483:   PetscFunctionBegin;
    484:   PetscCall(PetscFree(pep->data));
    485:   PetscCall(PetscObjectComposeFunction((PetscObject)pep,"PEPQArnoldiSetRestart_C",NULL));
    486:   PetscCall(PetscObjectComposeFunction((PetscObject)pep,"PEPQArnoldiGetRestart_C",NULL));
    487:   PetscCall(PetscObjectComposeFunction((PetscObject)pep,"PEPQArnoldiSetLocking_C",NULL));
    488:   PetscCall(PetscObjectComposeFunction((PetscObject)pep,"PEPQArnoldiGetLocking_C",NULL));
    489:   PetscFunctionReturn(PETSC_SUCCESS);
    490: }

    492: /*MC
    493:    PEPQARNOLDI - PEPQARNOLDI = "qarnoldi" - The Quadratic Arnoldi method (Q-Arnoldi)
    494:    for quadratic eigenvalue problems.

    496:    Notes:
    497:    This solver is available for quadratic eigenproblems only.

    499:    It implements the Q-Arnoldi method {cite:p}`Mee09`, which is not guaranteed
    500:    to be numerically stable. Users should prefer `PEPTOAR`, which
    501:    provides a similar algorithm with guaranteed numerical stability.

    503:    Level: beginner

    505: .seealso: [](ch:pep), `PEP`, `PEPType`, `PEPSetType()`
    506: M*/
    507: SLEPC_EXTERN PetscErrorCode PEPCreate_QArnoldi(PEP pep)
    508: {
    509:   PEP_QARNOLDI   *ctx;

    511:   PetscFunctionBegin;
    512:   PetscCall(PetscNew(&ctx));
    513:   pep->data = (void*)ctx;

    515:   pep->lineariz = PETSC_TRUE;
    516:   ctx->lock     = PETSC_TRUE;

    518:   pep->ops->solve          = PEPSolve_QArnoldi;
    519:   pep->ops->setup          = PEPSetUp_QArnoldi;
    520:   pep->ops->setfromoptions = PEPSetFromOptions_QArnoldi;
    521:   pep->ops->destroy        = PEPDestroy_QArnoldi;
    522:   pep->ops->view           = PEPView_QArnoldi;
    523:   pep->ops->backtransform  = PEPBackTransform_Default;
    524:   pep->ops->computevectors = PEPComputeVectors_Default;
    525:   pep->ops->extractvectors = PEPExtractVectors_QArnoldi;
    526:   pep->ops->setdefaultst   = PEPSetDefaultST_Transform;

    528:   PetscCall(PetscObjectComposeFunction((PetscObject)pep,"PEPQArnoldiSetRestart_C",PEPQArnoldiSetRestart_QArnoldi));
    529:   PetscCall(PetscObjectComposeFunction((PetscObject)pep,"PEPQArnoldiGetRestart_C",PEPQArnoldiGetRestart_QArnoldi));
    530:   PetscCall(PetscObjectComposeFunction((PetscObject)pep,"PEPQArnoldiSetLocking_C",PEPQArnoldiSetLocking_QArnoldi));
    531:   PetscCall(PetscObjectComposeFunction((PetscObject)pep,"PEPQArnoldiGetLocking_C",PEPQArnoldiGetLocking_QArnoldi));
    532:   PetscFunctionReturn(PETSC_SUCCESS);
    533: }