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From: meron@cars3.uchicago.edu
Subject: Re: Neural Nets and Quantum Mechanics/Computation
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References: <31FFD52A.6339@axon.cs.byu.edu> <290598840wnr@chmqst.demon.co.uk> <320909B7.5DA5@axon.cs.byu.edu> <320BCE4A.101C@citicorp.com> <Dvw6Ir.7zG@midway.uchicago.edu> <3210B213.D89@citicorp.com>
Date: Tue, 13 Aug 1996 20:04:01 GMT
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Xref: glinda.oz.cs.cmu.edu comp.ai.neural-nets:32983 sci.physics:207158

In article <3210B213.D89@citicorp.com>, Robert Fung <robert.fung@citicorp.com> writes:
>meron@cars3.uchicago.edu wrote:
> > 
> > In article <320BCE4A.101C@citicorp.com>, Robert Fung 
> <robert.fung@citicorp.com> writes:
> > >
> > >    In Digital Signal Processing, conversion is done from a
> > >    "continuous" function to a discrete function. The Nyquist
> > >    limit is DSP's Uncertainty Principle since there are many
> > >    discrete  possibilities for a given continuous function.
> > >
> > It is the other way around.  There are many (an infinity, in fact)
> > continuous functions corresponding to a given set of discrete values.
>
>
>       Ah. Thank you. I'm glad it's the other way around and 
>       not totally wrong :)
> > 
> > >    In QM on the other end, the problem is you have discrete
> > >    functions and Heisenberg's uncertainty rules there.
> > 
> > Who said that in QM you've discrete functions?
>
>       Maybe the word "function" was used too abstractly or 
>       taken too literally :)

"Function" may indeed mean many things.  I assume that our difference 
stems from the fact that I assumed you're talking about wave functions 
(which, as a rule, are continuous) while you had in mind physical 
parameters, like energy, momentum etc. which in QM are often (though 
not always) discrete.

Mati Meron			| "When you argue with a fool,
meron@cars.uchicago.edu		|  chances are he is doing just the same"
