25 Jul
2020
25 Jul
'20
6:26 a.m.
The LGP-30 has been discussed here (often fondly) a few times so I thought this might be
of interest. Adds a bit of fame to the little guy that I wasn't aware of.
I was reading the wikipedia web page on chaos theory and found this passage:
"Edward Lorenz was an early pioneer of the theory. His interest in chaos came about
accidentally through his work on weather prediction in 1961.[12] Lorenz was using a simple
digital computer, a Royal McBee LGP-30, to run his weather simulation. He wanted to see a
sequence of data again, and to save time he started the simulation in the middle of its
course. He did this by entering a printout of the data that corresponded to conditions in
the middle of the original simulation. To his surprise, the weather the machine began to
predict was completely different from the previous calculation. "
https://en.wikipedia.org/wiki/Chaos_theory#History
Will
26 Jul
26 Jul
5:24 p.m.
On 7/25/2020 8:26 AM, Will Cooke via cctalk wrote:
The LGP-30 has been discussed here (often fondly) a
few times so I thought this might be of interest. Adds a bit of fame to the little guy
that I wasn't aware of.
I was reading the wikipedia web page on chaos theory and found this passage:
"Edward Lorenz was an early pioneer of the theory. His interest in chaos came about
accidentally through his work on weather prediction in 1961.[12] Lorenz was using a simple
digital computer, a Royal McBee LGP-30, to run his weather simulation. He wanted to see a
sequence of data again, and to save time he started the simulation in the middle of its
course. He did this by entering a printout of the data that corresponded to conditions in
the middle of the original simulation. To his surprise, the weather the machine began to
predict was completely different from the previous calculation. "
https://en.wikipedia.org/wiki/Chaos_theory#History
Will
So, either he mis-entered something, or possibly the result of a
different state of a random number generator somewhere?
5:44 p.m.
Jay Jaeger wrote on Sun, 26 Jul 2020 19:24:24 -0500
So, either he mis-entered something, or possibly the
result of a
different state of a random number generator somewhere?
He dumped the full state of the simulation to paper with six digits
after the decimal point even though the internal calculations used eight
digits (I don't remember the actual precisions involved). So when he
restarted the simulation from the middle he introduced errors of less
than 1 per million and fully expected the results to be the same for the
days he had already simulated so he could continue a little further. But
he was shocked that the simulation went in a different direction and the
results were totally different after only a few days.
This is an absurd sensitivity to initial conditions that had never been
noticed in any system before. He compared it to whether a butterfly
flapped its wings or not in the middle of the Amazon making a difference
on there being a nice day or a huge storm on the other side of the world
a week later. This is the infamous "butterfly effect".
All this came after eliminating all kinds of possible errors, of course.
The first thing we thought back then when something like this happened
was not "I found a new theory" but "the hardware is probably flaky or
there is a compiler bug".
- Jecel
27 Jul
27 Jul
4:44 a.m.
On Sun, Jul 26, 2020, 8:44 PM Jecel Assumpcao Jr via cctalk <
cctalk at classiccmp.org> wrote:
Jay Jaeger wrote on Sun, 26 Jul 2020 19:24:24 -0500
Does the code listing exist on the web?
Bill
So, either he mis-entered something, or possibly
the result of a
different state of a random number generator somewhere?
He dumped the full state of the simulation to paper with six digits
after the decimal point even though the internal calculations used eight
digits (I don't remember the actual precisions involved). So when he
restarted the simulation from the middle he introduced errors of less
than 1 per million and fully expected the results to be the same for the
days he had already simulated so he could continue a little further. But
he was shocked that the simulation went in a different direction and the
results were totally different after only a few days.
This is an absurd sensitivity to initial conditions that had never been
noticed in any system before. He compared it to whether a butterfly
flapped its wings or not in the middle of the Amazon making a difference
on there being a nice day or a huge storm on the other side of the world
a week later. This is the infamous "butterfly effect".
All this came after eliminating all kinds of possible errors, of course.
The first thing we thought back then when something like this happened
was not "I found a new theory" but "the hardware is probably flaky or
there is a compiler bug".
- Jecel
5:33 a.m.
On July 27, 2020 at 6:44 AM Bill Degnan via cctalk
<cctalk at classiccmp.org> wrote:
Does the code listing exist on the web?Bill
>
I'm not aware of the code being available anywhere, but I haven't really looked.
I did find one paper by Lorenz where he describes his weather forecasting simulations. I
can find it again and send a link if anyone wants. But on the broader spectrum of chaos
theory perhaps the most notable introduction is James Gleik's book "Chaos."
Here is a link to it on archive.org
https://archive.org/details/chaos-james-gleick
Will
5:43 a.m.
On July 27, 2020 at 7:33 AM Will Cooke via cctalk
<cctalk at classiccmp.org> wrote:
> On July 27, 2020 at 6:44 AM Bill Degnan via cctalk <cctalk at classiccmp.org>
wrote:> Does the code listing exist on the web?Bill>I'm not aware of the code
being available anywhere, but I haven't really looked. I did find one paper by Lorenz
where he describes his weather forecasting simulations. I can find it again and send a
link if anyone wants.
Here is the link to the paper. "the Nature and Theory of the General Circulation of
the Atmosphere"
It's 10 MB and 180+ pages.
http://users.uoa.gr/~pjioannou/historical/Lorenz-1967.pdf
3:10 p.m.
Will Cooke via cctalk wrote:
This is more like a research monograph that was published later. The
original paper is
Edward N. Lorenz, "Deterministic Nonperiodic Flow",? Journal of The
Atmospheric Sciences,
Vol. 20, March 1963, pp. 130-141.
It is at multiple locations in the web. One source is:
http://www.astro.puc.cl/~rparra/tools/PAPERS/lorenz1962.pdf
At Cornell I took John Guckenheimer's and Steve Strogatz's courses, in
addition to the more EE-focused nonlinear systems course taught by
Hsiao-Dong Chiang.? Really beautiful stuff.
carlos.
On July 27,
2020 at 7:33 AM Will Cooke via cctalk <cctalk at classiccmp.org> wrote:
> On July 27, 2020 at 6:44 AM Bill Degnan via cctalk <cctalk at classiccmp.org>
wrote:> Does the code listing exist on the web?Bill>I'm not aware of the code
being available anywhere, but I haven't really looked. I did find one paper by Lorenz
where he describes his weather forecasting simulations. I can find it again and send a
link if anyone wants.
Here is the link to the paper. "the Nature and Theory
of the General Circulation of the Atmosphere"
It's 10 MB and 180+ pages.
http://users.uoa.gr/~pjioannou/historical/Lorenz-1967.pdf
5:05 p.m.
New subject: Altair clone follow-up
for those involved in the recent altair clone discussion, there's now
one up on EPAY:? 283958927640
(Not mine and I know nothing about it...)
Steve
6:19 p.m.
Theoriginal paper is
Edward N. Lorenz, "Deterministic Nonperiodic
Flow", Journal of TheAtmospheric Sciences,Vol. 20, March 1963, pp. 130-141.
It is at multiple locations in the web. One source is:
http://www.astro.puc.cl/~rparra/tools/PAPERS/lorenz1962.pdf
At Cornell I took John Guckenheimer's and Steve Strogatz's courses, inaddition to
the more EE-focused nonlinear systems course taught byHsiao-Dong Chiang. Really beautiful
stuff.
carlos.
Thanks! Looks like a really interesting read.
Will
9:48 p.m.
Will Cooke via cctalk wrote:
Theoriginal paper is
What I think is most awesome, in terms of the role that computing held
in this discovery, is that mathematicians since the early 20th century
took as granted the idea that the "limit sets" of the trajectories of
solutions of time-differential equations were either periodic (also
called limit cycles)? or singletons (stable or unstable equilibria at a
single point in space).? Lorenz, through digital integration of a simple
third-order differential equation, proved that there were other kinds of
limit sets.? These limit sets are distributed in space and occupy
geometries that we now call "fractal".? When they are the result of a
chaotic solution to a differential equation, we call them "strange
attractors".? The first one that was studied was Lorenz's strange
attractor, which, in 3D space, looks like a butterfly. I don't know if
there is any connection between its shape and the popular "butterfly
altering an initial airflow in the dynosaur's era" interpretation (by
the way, utterly dumb for anyone who knows about real-life nonlinear
dynamical systems).? But what I do know, is that mathematicians had to
suddenly backtrack 50 years and try to understand how they could be so
wrong.? And that's how chaos theory emerged.? Thanks to numerical
computation.
carlos.
Edward N. Lorenz, "Deterministic Nonperiodic
Flow", Journal of TheAtmospheric Sciences,Vol. 20, March 1963, pp. 130-141.
It is at multiple locations in the web. One source is:
http://www.astro.puc.cl/~rparra/tools/PAPERS/lorenz1962.pdf
At Cornell I took John Guckenheimer's and Steve Strogatz's courses, inaddition to
the more EE-focused nonlinear systems course taught byHsiao-Dong Chiang. Really beautiful
stuff.
carlos.
Thanks! Looks like a really interesting read.
Will
10:07 p.m.
Carlos E Murillo-Sanchez wrote:
Will Cooke via cctalk wrote:
"dinosaur", argh.
? Theoriginal paper is
What I think is most awesome, in terms of the role that computing held
in this discovery, is that mathematicians since the early 20th century
took as granted the idea that the "limit sets" of the trajectories of
solutions of time-differential equations were either periodic (also
called limit cycles)? or singletons (stable or unstable equilibria at
a single point in space).? Lorenz, through digital integration of a
simple third-order differential equation, proved that there were other
kinds of limit sets.? These limit sets are distributed in space and
occupy geometries that we now call "fractal".? When they are the
result of a chaotic solution to a differential equation, we call them
"strange attractors".? The first one that was studied was Lorenz's
strange attractor, which, in 3D space, looks like a butterfly. I don't
know if there is any connection between its shape and the popular
"butterfly altering an initial airflow in the dynosaur's era"
interpretation (by the way, utterly dumb for anyone who knows about
real-life nonlinear dynamical systems).? But what I do know, is that
mathematicians had to suddenly backtrack 50 years and try to
understand how they could be so wrong.? And that's how chaos theory
emerged.? Thanks to numerical computation.
carlos.
Edward N. Lorenz, "Deterministic Nonperiodic
Flow",? Journal of
TheAtmospheric Sciences,Vol. 20, March 1963, pp. 130-141.
It is at multiple locations in the web. One source is:
http://www.astro.puc.cl/~rparra/tools/PAPERS/lorenz1962.pdf
At Cornell I took John Guckenheimer's and Steve Strogatz's courses,
inaddition to the more EE-focused nonlinear systems course taught
byHsiao-Dong Chiang.? Really beautiful stuff.
carlos.
Thanks!? Looks like a really interesting read.
Will
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billdegnan＠gmail.com -
ce.murillosanchez＠gmail.com -
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wrcooke＠wrcooke.net