Dear all,Q(a).I have run HF -> RELCC and found that the SCF energieswritten in HF and RELCC parts are different:SCF energy in HF : -3383.6651884103194SCF energy in RELCC: -3383.772933531707167Is it fine? If so what is the reason of the difference?(BTW, what is the energy unit? Hartree?)I have attached the output file as chg0.out.
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<output_HF.txt>
Luuk
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<output_HF.txt>
On Aug 20, 2020, at 10:52 AM, Lorenzo Lodi <lodi...@gmail.com> wrote:
Incidentally, the correction to the shape of HF molecule potential energy curve due to .GAUNT comes out very large, in fact about as large as the overall non-Gaunt relativistic correction (ie, the difference between relativistic and non-relativistic energies). I wonder if this can be right as, especially for such a light molecule, I'd expect the Gaunt term to be small.
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Dear Lorenzo,
I took the liberty of fitting your data and doing a standard Dunham analysis (using just the 9 points between 1.4 and 2.2 bohr):
Re (Å) we (cm-1) wexe (cm-1)
NR-HF 0.89939 4462.42 90.63
DC-DHF 0.89938 4460.39 90.71
DC+Gaunt 0.89950 4459.57 90.91
So overall, I would say that as expected the Gaunt contribution is a bit larger than I would have expected, but still somewhat smaller than the usual scalar contribution for the harmonic frequency (we).
best regards, -Kirk
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Dear Kirk.
There is an uncertainty in a Dunham analysis depending on the choice of points and the degree of the polynomial fit.
You didn’t mention the degree of fit that you used but if you get wexe, you must have at least a cubic fit (maybe quartic(
Would it be easy for you to change the degree of polynomial ft to see whether and by how much the choice of polynomial fit affects the comparison you made.
Regards, Paul
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Dear Paul,
I actually used a 7th degree polynomial in bond displacement coordinates to 9 points, so it was close to a polynomial interpolation. Lower order polynomials of course decreased the accuracy of the fit, but it seemed the general trends were unchanged since the fits were of very similar quality for each curve. I can certainly post a comparison if this is of interest.
regards, -Kirk
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Dear Paul,
see attached.
regards, -Kirk
From: <dirac...@googlegroups.com> on behalf of Paul Bagus <ba...@paulbagus.com>
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Date: Friday, August 21, 2020 at 7:01 AM
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Dear Kirk,
A caution about polynomial fits. If you have the same number of coefficients in the polynomial as data points, as you write, you get a perfect fit. The polynomial exactly passes through all the data points. However the fit is likely to be physically meaningless. Hartree and Hartree wrote a book on numerical analysis with a beautiful example of how such a fit can go wrong. The polynomial, I think for a potential curve, had several oscillations to give a perfect fit but did not have a nice r(e) or w(e).
I have added printing the maximum and average error of the fit to the code that I use for a Dunham analysis. Large errors can come because the range of distances I use goes beyond the region where a polynomial is valid or there is an error in the data for the points. I try to avoid polynomials higher than quartic. Often, if the fit has errors, I reduce the range of distances in the points that I use.
Best Regards, Paul
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Dear Paul,
this is why I look very carefully at the coefficients of the resulting polynomial. It is straightforward for these types of fits to determine if things are well behaved or not. In general the coefficients should alternate in sign and the magnitudes should be dropping. I also only use this analysis for a very specific range of points around the minimum - generally no more than -0.4 bohr to +0.7 bohr and I use a specific distribution of points. But you're of course exactly right that polynomial fitting has the danger of giving one oscillations and odd behavior. Fortunately most ground state potential curves are very well behaved, at least in the near-equilibrium region and inspection of the coefficients is very reliable to tell if things are ok. But one can certainly see in what I posted for HF that even small changes in the fit can produce differences of more than a cm-1 in the harmonic frequency.
My code also prints average error and errors at each data point, so this can be helpful (as well as the range of data points in units of omega_e). The problem with using polynomials of only order quartic is that the fits are generally somewhat poor (generally much less than microHartree RMS for points covering the near-equilibrium region) and the anharmonicity depends on the quartic derivative, which is then not very stable without higher order terms.
best regards, -Kirk
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Kirk, We agree. Your comments and cautions are well taken. Regards, Paul
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How about using (1/R)**n for the fit? Have you tried that?
Also, have you tried Trond’s polfit in the utils/ directory?
-- Hans Jørgen
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I think years ago I compared different coordinate systems (1/R, SPF, etc.) and I've compared my results to others that have used expansions in 1/R, but after 30 years of using it, I'm pretty comfortable with powers of (r-re). At least I understand it really well. In some ways the final results can be just as sensitive to how you sample the potential as to how you fit it.
I haven't tried Trond's polfit, but a long time ago I compared my program to Dunning's version and the results were very similar.
-Kirk
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Hans, What would be the advantage of an expansion in (1/R)**n. It is a way of reproducing an LJ 6-12 potential relevant for vdW interactions but this is a restricted class of systems. Also if you want properties near re, I believe you can expand the 6-12 in a polynomial. Isn’t this correct? Paul
From: 'Hans Jørgen Aagaard Jensen' via dirac-users <dirac...@googlegroups.com>
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Hans, BTW. My understanding is that polfit gives you the polynomial expansion and minimum and derivates around the minimum. Does it also compute the spectroscopic constants or does one have to use the formulas for them in terms of the expansion coefficients? Paul
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I guess the advantage of the 1/R expansion is that it will not go to alternatively to +inf and -inf for R -> inf and increasing order, but on the other hand it has problems for R -> 0.
I just searched for “inverse R fit of diatomic potential energy curve” with google and selected the hits
J. Chem. Phys. 151, 024307 (2019); https://doi.org/10.1063/1.5100748
It seems that the best fits are obtained with a generalization of John Ogilvie’s suggestion to use (R-Re)/(R+Re) as “x”, which is finite both at R=0 and at R-> inf.
From no. 1, the thesis:

This was followed by discussion of other fits.
Hmm, a thought: the nuclear repulsion is exactly known and can be treated analytically. Why not fit the electronic energy curve which is finite at R=0 ???? One then obtains
V( R ) = V_NN( R ) + fit to E_el( R ). Would that not be more stable with the y_p variable (or another variable)? Has that been attempted ?
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If one wants to fit a whole diatomic potential curve, I think the best that I know of is from Bob LeRoy, the "modified Lennard-Jones oscillator" (MLJ) model. It uses the same "x" as you have below but with some very flexible options for introducing the correct long range (JCP 112, 3949). I'm not aware of anyone doing what you suggest with the exact nuclear-nuclear repulsion but then the electronic energy just goes to a constant at R=0? That might be a bit more difficult to enforce.
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