
Chemists provide theoretical interpretation to understand chemical reactions - dnetesn
https://phys.org/news/2017-12-chemists-theoretical-chemical-reactions.html
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comicjk
Computational chemist here. The phys.org article is a pretty bad rendering of
the original paper. The "theoretical interpretation" described in the headline
is nothing new. The actual scientific advance described in the paper is an
experimental (not theoretical) technique for measuring transition states of
molecules, involving making them very cold so the transition states last
longer. This lets us verify some quantum mechanics predictions, but we already
had a lot of verification. Calculating small-molecule reaction paths via
quantum mechanics has been a standard part of theoretical chemistry for
decades. We can do it at a very high level of accuracy using millions of CPU
hours, or at a passable level of accuracy using thousands of CPU hours.

Big molecules are still a challenge because the scaling of the accurate
methods is very bad (N^4 or worse, where N is the number of electrons!). These
calculations are something that quantum computers could theoretically do much
better than classical ones.

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muthdra
Dude, your job looks awesome. I have been thinking a lot about the
ramifications of chemestry computation since last year.

This comment
[https://news.ycombinator.com/item?id=16027737](https://news.ycombinator.com/item?id=16027737)
about how to get around NP-hardness made me go "Oh, can you even ask such a
question? Can you expect to solve getting around this kind of problem?" and so
I went researching.

I found the paper Complexity of Protein Folding
[https://www.gwern.net/docs/biology/1993-fraenkel.pdf](https://www.gwern.net/docs/biology/1993-fraenkel.pdf)
and chapter 4 exposes two possible realities: either nature solves NP-hard
problems in polynomial time or it functions in a classic Turing machine model.
I was like "Welp I guess when you put it like this, talking about nature
working within a machine model I suppose it sounds rather silly, yes. It may
be that nature just does her thing in her own way somehow." The paper says a
protein with 100 amino acids may assume 8^100 conformations and nature solves
for that in 1 second. Also the spin glass
[https://en.wikipedia.org/wiki/Spin_glass](https://en.wikipedia.org/wiki/Spin_glass)
model is apparently some other thing that nature solver eerly fast.

Can we chain these natural occurances in order to calculate a function with
inputs in record time?

~~~
Robotbeat
> Can we chain these natural occurances in order to calculate a function with
> inputs in record time?

That's essentially what a quantum computer does.

~~~
comicjk
But, a quantum computer would not in general solve NP-hard problems in
polynomial time (as far as we know). The known exponential speedups are for
"easier" problems like factoring and finding quantum ground states, which are
not NP-hard.

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isoprophlex
Is it me or is this article especially poorly worded? It took me a little too
much effort to figure out what this figure caption even means:

> Negative ions typically have a geometry that is very close to the transition
> state of the corresponding neutral reactions

CH3OHF anion is prepared and de-ionized with laser light. It dissociates into
methanol and F radial, under very slight changes of the involved molecular
geometries...?

~~~
QAPereo
Phys.org is a roaring dumpster fire, and frankly the domain should never show
up on HN. If it’s on phys.org, they found it somewhere, and that original
source will be far better than the half-assed version on phys.org.

Actual original paper...
[https://www.nature.com/articles/nchem.2804](https://www.nature.com/articles/nchem.2804)

~~~
maxerickson
The content at the phys.org link was written by the University of New Mexico
press shop (see my other comment).

~~~
QAPereo
And? HN deserves better... click on the DOI link at least and submit that, not
this garbled secondhand trash.

~~~
maxerickson
My point is mostly that the problem is larger than phys.org. UNM itself is the
source of the lesser article.

That phys.org just aggregates material available elsewhere is also an
additional reason not to link it. It's suggested to link original articles (in
a different sense than you are using) in the submission guidelines.

~~~
QAPereo
You’re certainly not wrong, and the endless parade of press releases and
aggregators of press releases are indeed, terrible. Having said that however,
I’ve never come across a site as popular and worthless as Phys.org (edit: in
this space at least). The AAAS, iiie and other maintain decent aggregators, or
the original is best.

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curlcntr
I can relate to their enthusiasm.

For a pchem thesis my advisor was seeing unexpected experimental results and
asked me to try explaining from first principles. I started with Schrodinger's
equation, let the math do the work, and wound up with a fairly reasonable
match.

Looking back on it now, perhaps I had a few too many free variables (J Neumann
– “with four parameters I can fit an elephant…”).

In any case, to me, it was so cool to see how such a fundamental equation
connects to very complex experimental processes.

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elcritch
This title has to be one of the most genericized-press-release titles posted
on HN. Almost every other experimental chemistry paper would technically fit
this title! Makes you feel for the copy writer trying to write a title for
some complex chemistry paper during the holidays. Despite the bland press
release title, it’s a pretty interesting experimental chemistry research and
the original paper reads well. It’s surprising how clear the (apparent)
transition peaks are in the graph data. These reactions occur on such
incredibly minuscule timescales it’s amazing to see it so clearly!

Interesting:

> The PES is fit using the permutation invariant polynomial–neural network
> (PIP-NN) method [49].

This caught my eye as I recall reading some earlier attempts at NN based
polynomial fitting in QM models, but this sounds more advanced. Does anyone
know if generalized neural net methods for fitting the potential energy curves
are common in QM modeling now? If so, are there limitations to the method
that’d prevent adopting it for fitting polynomials in other applications?

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mike741
are there non-theoretical interpretations?

