Antisymmetrise ERI tensor inside adccore during import

[mfherbst]

Antisymmetrise not on the python side but during the import into libtensor memory.

• pyscf working
• Psi4 working
• molsturm working
• veloxchem working
• Cleanup and rebasing
• Run the full adcc-bench suite
• Docs polishing

[mfherbst]

Some current timings on my laptop:

ccpVQZ water (restricted)

New version (this branch)

  import/eri/o1o1o1o1                    1s 633ms
  import/eri/o1o1o1v1                    1s 748ms
  import/eri/o1o1v1v1                    1s 968ms
  import/eri/o1v1o1v1                    3s 646ms
  import/eri/o1v1v1v1                    2s 240ms
  import/eri/v1v1v1v1                   10s 332ms

Old version (master)

  import/eri/o1o1o1o1                    1s  58ms
  import/eri/o1o1o1v1                    2s 544ms
  import/eri/o1o1v1v1                    1s 489ms
  import/eri/o1v1o1v1                    2s 654ms
  import/eri/o1v1v1v1                    1s 825ms
  import/eri/v1v1v1v1                   15s  86ms

def2-tzvp CH2NH2 radical (unrestricted)

New version (this branch)

  import/eri/o1o1o1o1                    3s 382ms
  import/eri/o1o1o1v1                    4s 388ms
  import/eri/o1o1v1v1                    4s 121ms
  import/eri/o1v1o1v1                    9s 169ms
  import/eri/o1v1v1v1                    6s 200ms
  import/eri/v1v1v1v1                   13s 942ms

Old version (master)

  import/eri/o1o1o1o1                    2s 880ms
  import/eri/o1o1o1v1                    9s 820ms
  import/eri/o1o1v1v1                    4s 337ms
  import/eri/o1v1o1v1                    9s 971ms
  import/eri/o1v1v1v1                   13s 368ms
  import/eri/v1v1v1v1                   53s 184ms

Memory water ADC2 this branch

Memory water ADC2 master

Memory CH2NH2 radical ADC3 this branch

Memory CH2NH2 radical ADC3 master

So adding them all up, for UHF the new version is better in timings. For RHF the total time is roughly the same. When it comes to memory, the requirement is greatly reduced for RHF and about similar for UHF with this PR.

[maxscheurer]

I trust you that the benchmarks are okay, nice to get rid of some code on the Python layer.

[mfherbst]

Just a final comment: On the noradrenaline testcase, this brought down the memory requirement from 398GB to 280GB (ca. -30%) 😄.