l103

Table of Contents

l103.catchall
l103.trust
l103.init
l103.localminsaddle
l103.deltas
l103.itemconverge
rfo
l103.optimizedparam
preddelta
l103.catchall

Table 189. Implementation level

TypeStatus
CML extraction template

Total implementation

HTML5 representation

Partial implementation


Table attributesTable. Template attributes

AttributeValue
source Gaussian log
idl103
nameBerny optimizations to minima and TS, STQN transition state searches
repeat*
pattern\s*\(Enter.*l103\..*
endPattern\s*Leave\sLink\s+103\s.*
endOffset1
xml:basel103.xml


Input. 

 (Enter /opt/G09/g09/l103.exe)
 
 GradGradGradGradGradGradGradGradGradGradGradGradGradGradGradGradGradGrad
 Berny optimization.
 Initialization pass.
                           ----------------------------
                           !    Initial Parameters    !
                           ! (Angstroms and Degrees)  !
 --------------------------                            --------------------------
 ! Name  Definition              Value          Derivative Info.                !
 --------------------------------------------------------------------------------
 ! R1    R(1,2)                  1.113          estimate D2E/DX2                !
 ! R2    R(1,3)                  1.113          estimate D2E/DX2                !
 ! R3    R(1,4)                  1.113          estimate D2E/DX2                !
 ! R4    R(1,5)                  1.113          estimate D2E/DX2                !
 ! A1    A(2,1,3)              109.4712         estimate D2E/DX2                !
 ! A2    A(2,1,4)              109.4712         estimate D2E/DX2                !
 ! A3    A(2,1,5)              109.4712         estimate D2E/DX2                !
 ! A4    A(3,1,4)              109.4712         estimate D2E/DX2                !
 ! A5    A(3,1,5)              109.4712         estimate D2E/DX2                !
 ! A6    A(4,1,5)              109.4712         estimate D2E/DX2                !
 --------------------------------------------------------------------------------
 Trust Radius=3.00D-01 FncErr=1.00D-07 GrdErr=1.00D-06
 Number of steps in this run=  20 maximum allowed number of steps= 100.
 GradGradGradGradGradGradGradGradGradGradGradGradGradGradGradGradGradGrad
 
  Leave Link  103 at Fri Sep 13 17:06:50 2013, MaxMem=  419430400 cpu:       0.0
  

Input. 

 GradGradGradGradGradGradGradGradGradGradGradGradGradGradGradGradGradGrad
 Berny optimization.
 Internal  Forces:  Max     0.002386724 RMS     0.000538609
 Search for a saddle point.
 Step number   1 out of a maximum of  137
 All quantities printed in internal units (Hartrees-Bohrs-Radians)
 Swaping is turned off.
 Second derivative matrix not updated -- analytic derivatives used.
     Eigenvalues ---   -0.03403   0.00144   0.00463   0.00759   0.00906
     Eigenvalues ---    0.01177   0.01317   0.01431   0.01623   0.01839
     Eigenvalues ---    0.40148   0.40211   0.40329   0.46257   0.48142
     Eigenvalues ---    0.51910   1.01166   1.025821000.000001000.00000
     Eigenvalues --- 1000.000001000.000001000.000001000.000001000.00000
     Eigenvalues --- 1000.000001000.00000
 Eigenvectors required to have negative eigenvalues:
                          R25       R14       R27       R16       D47
   1                    0.36641   0.36640   0.22975   0.22974  -0.19160
                          D48       D8        D11       D6        D9
   1                    0.19153   0.16306  -0.16304   0.15371  -0.15366
 RFO step:  Lambda0=9.155600927D-04 Lambda=-1.51225227D-04.
 Linear search not attempted -- option 19 set.
 Iteration  1 RMS(Cart)=  0.01149217 RMS(Int)=  0.00020982
 Iteration  2 RMS(Cart)=  0.00019717 RMS(Int)=  0.00012443
 Iteration  3 RMS(Cart)=  0.00000003 RMS(Int)=  0.00012443
 Variable       Old X    -DE/DX   Delta X   Delta X   Delta X     New X
                                 (Linear)    (Quad)   (Total)
    R1        2.63420   0.00003   0.00000   0.00038   0.00026   2.63446
    R2        2.63420   0.00004   0.00000   0.00037   0.00026   2.63446
   R41        2.01442   0.00057   0.00000  -0.00167  -0.00165   2.01277
    A1        1.93497   0.00006   0.00000  -0.00261  -0.00267   1.93230
    A2        2.13721  -0.00006   0.00000   0.00116   0.00111   2.13833
   A37        2.20391  -0.00012   0.00000   0.01113   0.01057   2.21448
    D1        3.00181  -0.00035   0.00000   0.00163   0.00163   3.00344
    D2       -0.15405  -0.00021   0.00000   0.00583   0.00583  -0.14822
   D49        0.00020   0.00000   0.00000  -0.00022  -0.00022  -0.00002
         Item               Value     Threshold  Converged?
 Maximum Force            0.002387     0.000450     NO 
 RMS     Force            0.000539     0.000300     NO 
 Maximum Displacement     0.044296     0.001800     NO 
 RMS     Displacement     0.011477     0.001200     NO 
 Predicted change in Energy= 3.932148D-04
 GradGradGradGradGradGradGradGradGradGradGradGradGradGradGradGradGradGrad
  

Output text. 

<comment class="example.output" id="l103">
    <module cmlx:templateRef="l103">
      <list cmlx:templateRef="berny">
        <scalar dataType="xsd:string" dictRef="g:optimization">Initialization pass.</scalar>
      </list>
      <module cmlx:lineCount="16" cmlx:templateRef="l103.init">
        <list cmlx:templateRef="length">
          <array dataType="xsd:string" size="4" dictRef="g:symbol">R1 R2 R3 R4</array>
          <array dataType="xsd:integer" size="4" dictRef="g:atom1">1 1 1 1</array>
          <array dataType="xsd:integer" size="4" dictRef="g:atom2">2 3 4 5</array>
          <array dataType="xsd:double" size="4" dictRef="cc:distance">1.113 1.113 1.113 1.113</array>
          <array delimiter="|" dataType="xsd:string" size="4" dictRef="g:deriv">|estimate D2E/DX2|estimate D2E/DX2|estimate D2E/DX2|estimate D2E/DX2|</array>
        </list>
        <list cmlx:templateRef="angle">
          <array dataType="xsd:string" size="5" dictRef="g:symbol">A1 A2 A3 A4 A5</array>
          <array dataType="xsd:integer" size="5" dictRef="g:atom1">2 2 2 3 3</array>
          <array dataType="xsd:integer" size="5" dictRef="g:atom2">1 1 1 1 1</array>
          <array dataType="xsd:integer" size="5" dictRef="g:atom3">3 4 5 4 5</array>
          <array dataType="xsd:double" size="5" dictRef="cc:angle">109.4712 109.4712 109.4712 109.4712 109.4712</array>
          <array delimiter="|" dataType="xsd:string" size="5" dictRef="g:deriv">|estimate D2E/DX2|estimate D2E/DX2|estimate D2E/DX2|estimate D2E/DX2|estimate D2E/DX2|</array>
        </list>
      </module>
      <module cmlx:lineCount="2" cmlx:templateRef="l103.trust">
        <scalar dataType="xsd:double" dictRef="g:trustrad">0.3</scalar>
        <scalar dataType="xsd:double" dictRef="g:fncerr">1.0E-7</scalar>
        <scalar dataType="xsd:double" dictRef="g:grderr">1.0E-6</scalar>
        <scalar dataType="xsd:integer" dictRef="g:nstep">20</scalar>
        <scalar dataType="xsd:integer" dictRef="g:allowedstep">100</scalar>
      </module>
    </module>
  </comment>

Output text. 

<comment class="example.output" id="l103.1">
<module cmlx:templateRef="l103">
  <list cmlx:templateRef="berny">
    <scalar dataType="xsd:string" dictRef="g:optimization">Internal Forces: Max 0.002386724 RMS 0.000538609</scalar>
  </list> Search for a saddle point. Step number 1 out of a maximum of 137 All quantities printed in internal units (Hartrees-Bohrs-Radians) Swaping is turned off. Second derivative matrix not updated -- analytic derivatives used. Eigenvalues --- -0.03403 0.00144 0.00463 0.00759 0.00906 Eigenvalues --- 0.01177 0.01317 0.01431 0.01623 0.01839 Eigenvalues --- 0.40148 0.40211 0.40329 0.46257 0.48142 Eigenvalues --- 0.51910 1.01166 1.025821000.000001000.00000 Eigenvalues --- 1000.000001000.000001000.000001000.000001000.00000 Eigenvalues --- 1000.000001000.00000 Eigenvectors required to have negative eigenvalues: R25 R14 R27 R16 D47 1 0.36641 0.36640 0.22975 0.22974 -0.19160 D48 D8 D11 D6 D9 1 0.19153 0.16306 -0.16304 0.15371 -0.15366 
  <module cmlx:lineCount="5" cmlx:templateRef="rfo"> RFO step: Lambda0=9.155600927D-04 Lambda=-1.51225227D-04. Linear search not attempted -- option 19 set. Iteration 1 RMS(Cart)= 0.01149217 RMS(Int)= 0.00020982 Iteration 2 RMS(Cart)= 0.00019717 RMS(Int)= 0.00012443 Iteration 3 RMS(Cart)= 0.00000003 RMS(Int)= 0.00012443 </module>
  <module cmlx:lineCount="11" cmlx:templateRef="l103.deltas">
    <list cmlx:lineCount="9" cmlx:templateRef="delta">
      <array dataType="xsd:string" dictRef="cc:variable" size="9">R1 R2 R41 A1 A2 A37 D1 D2 D49</array>
      <array dataType="xsd:double" dictRef="g:lastval" size="9">2.6342 2.6342 2.01442 1.93497 2.13721 2.20391 3.00181 -0.15405 2.0E-4</array>
      <array dataType="xsd:double" dictRef="cc:deriv" size="9">3.0E-5 4.0E-5 5.7E-4 6.0E-5 -6.0E-5 -1.2E-4 -3.5E-4 -2.1E-4 0.0</array>
      <array dataType="xsd:double" dictRef="cc:delta.linear" size="9">0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0</array>
      <array dataType="xsd:double" dictRef="cc:delta.quad" size="9">3.8E-4 3.7E-4 -0.00167 -0.00261 0.00116 0.01113 0.00163 0.00583 -2.2E-4</array>
      <array dataType="xsd:double" dictRef="cc:delta.total" size="9">2.6E-4 2.6E-4 -0.00165 -0.00267 0.00111 0.01057 0.00163 0.00583 -2.2E-4</array>
      <array dataType="xsd:double" dictRef="cc:newval" size="9">2.63446 2.63446 2.01277 1.9323 2.13833 2.21448 3.00344 -0.14822 -2.0E-5</array>
    </list>
  </module>
  <module cmlx:lineCount="5" cmlx:templateRef="l103.itemconverge">
    <list cmlx:lineCount="4" cmlx:templateRef="row">
      <array dataType="xsd:string" dictRef="g:item" />
      <array dataType="xsd:double" dictRef="g:value" size="4">4.5E-4 3.0E-4 0.0018 0.0012</array>
      <array dataType="xsd:double" dictRef="g:threshold" size="4">0.0 0.0 0.0 0.0</array>
      <array dataType="xsd:string" dictRef="g:converged" size="4">NO NO NO NO</array>
    </list>
  </module>
  <module cmlx:lineCount="1" cmlx:templateRef="preddelta">
    <list cmlx:templateRef="predicted">
      <scalar dataType="xsd:double" dictRef="g:predchange">3.932148E-4</scalar>
    </list>
  </module>
  <module cmlx:lineCount="1" cmlx:templateRef="l103.catchall">
    <list cmlx:templateRef="l103.discard">
      <scalar dataType="xsd:string" dictRef="x:discard">GradGradGradGradGradGradGradGradGradGradGradGradGradGradGradGradGradGrad</scalar>
    </list>
  </module>
</module>
  </comment>