Weird Energy with DF-CCSD(T) on pre-built 1.2 binary

1

Dear all,

I’m attempted a DF-FNO-CCSD(T)/aug-cc-pvdz computation on sumanene. I’m getting an asinine energy. If I use cc-pvdz I get a normal energy that is about the same as another program’s CCSD energies. I installed stable release 1.2.1 and the python 3.5 version of it for linux. The hardware is intel haswell cpu’s.

 0   0 1 82301976411.2597808838 82301976411.2597808838 180071.6863671333       79
  1   1 1 -11765764147947413438464.0000000000 -11765764148029716168704.0000000000 5189755552069629.0000000000     1039
  2   2 1 18577504081805034984135645462528.0000000000 18577504093570799348831936839680.0000000000 13953090784875981570048.0000000000     1042
  3   3 1 -10975754574997206597632.0000000000 -18577504092780789161197672857600.0000000000 2850375421929338594918400.0000000000     1058

Here’s the input file

memory 120 GB
molecule {
0 1
C 3.269671140 0.262382661 0.000000000
C -1.638988443 0.201021220 2.834237354
C -1.638988443 0.201021220 -2.834237354
H 3.645686428 1.289803000 0.000000000
H -1.846170088 1.221151217 3.170972567
C 1.219967165 -0.666672220 0.713456211
C 0.020624067 -0.681664789 1.405951372
C 0.020624067 -0.681664789 -1.405951372
C 1.219967165 -0.666672220 -0.713456211
C -1.215021798 -0.697111167 -0.692495161
C -1.215021798 -0.697111167 0.692495161
C 2.350712693 -0.010518009 1.202305693
C -0.133462307 -0.041571814 2.636656855
C -0.133462307 -0.041571814 -2.636656855
C 2.350712693 -0.010518009 -1.202305693
C -2.215754163 -0.067601818 -1.434351162
C -2.215754163 -0.067601818 1.434351162
C 2.253218542 0.518128480 2.489250128
C 1.019790334 0.502709825 3.201425874
C 1.019790334 0.502709825 -3.201425874
C 2.253218542 0.518128480 -2.489250128
C -3.291380529 0.448817382 -0.712175746
C -3.291380529 0.448817382 0.712175746
H 3.077229877 1.077986926 2.924280546
H 0.974199492 1.051697677 4.138560570
H 0.974199492 1.051697677 -4.138560570
H 3.077229877 1.077986926 -2.924280546
H -4.090407292 0.988386795 -1.214280023
H -4.090407292 0.988386795 1.214280023
H 4.154760170 -0.387272435 0.000000000
H -2.069145762 -0.465075312 3.593654516
H -2.069145762 -0.465075312 -3.593654516
H -1.846170088 1.221151217 -3.170972567
}

set {
basis aug-cc-pvdz
guess sad
reference rhf
scf_type DF
cc_type DF
freeze_core true
OCC_TOLERANCE 1.0e-5
}

energy(‘fno-ccsd(t)’)

2

I get the same with the latest developer version. Furthermore it is not caused by the FNO approx, the FNO part looks normal and DF-CCSD(T) gives the same nonsense.

The DF tensor could have some linear dependencies perhaps? The conventional FNO-CCSD(T) seems to work:

   Iter  DIIS          Energy       d(Energy)          |d(T)|     time
      0   0 1   -2.8444805434   -2.8444805434    0.0447735979      330
      1   1 1   -2.8491945311   -0.0047139877    0.0190091062      344
      2   2 1   -2.8540707763   -0.0048762452    0.0088988976      323
3

+1 for linear depends in the inverse coulomb metric. Best to raise this on GitHub so the developers can add this to a TODO list.

4

@bkw Do you have a github account and want to write an issue? If not I can make a post for you. Please include link to this forum post.

5

@hokru I’ll get on it.

6

@hokru I posted this to github

1 Like
7

What if you set a smaller value for DF_FITTING_CONDITION? Try 1e-7.

8

Oh but you’ll have to do this on 1.3 since 1.2 isn’t passing the value properly.

9

Would you recommend I grab the nightly version then?

10

Not yet. There is a patch posted that might fix the problem, but it is not included yet.

Meanwhile you can run with conventional integrals cc_type conv. The integrals transformation takes some additional time, but overall it wont be much slower for this problem size.

11

Well, it looks like somehow symmetry is the problem.

You can run your current calculation setting symmetry c1 in the geometry block. As DF-FNO-CCSD(T) does not use symmetry anyway, this is essentially no loss in speed.

Please try and let us know.

12

@hokru I’m running it now

@hokru disabling symmetry for the scf seems to fix the issue. The energies are about the same as MRCC’s DF-CCSD(T) code. Thank you for the assistance.