Science and Big Data: Mercury at Perihelion

Science or Science Fiction?  Actually not a bad title for a Science Fiction book, but unfortunately the title has been taken.  By Einstein.  It is interesting from the point of view of computation, maintaining data along with just how good paper and pencil can be in solving problems.

In the science mythos, which really isn’t a mythology but certainty this one plays out like one, Isaac Newton noticed that his Laws of Gravity was not correct when you included the orbit of Mercury.  Which when you think about it that was not the century or  timeframe we normally think about computers and electronics.  Mainly because there was no electronics or computers in Isaac Newton's time.  So how did they do the calculation for the orbits?  How did they do the observations, how could they be so exact that a small variation in Mercury’s orbit was observed.  And they used mathematical tools created before the telescope was invented.

Darn it!  No calculators?  What did they use?

Simple: They used drafting tools, paper and pencil, as well scissors in some cases.  Really. The orbits of the planets would be carefully drawn on a piece of vellum or similar and then the ellipse would be cut out.  Then a single cut along the major axis toward the location of the sun in the elliptical diagram, stopping at the center of the circle representing the sun.  Now a cone would be made.  For some reason, I still do not fully understand, there was an eccentricity in the orbit of Mercury compared to the other observable planets.  This process was used to confirm or drive the discovery of Neptune, not sure which.  That's not the point of this blog.  The point is that why the cloud to store data?

Kepler calculations:

Check out the lab at: https://chemphys.purduecal.edu/~ncrelich/PortableDocuments/PHYS152/152%20Spring2009/11_Lab11-Keplers-LawsfromWd.pdf , this lab walks you through the process of using Keplers laws with respect to the Orbit of Mercury and I think should be able to help explain what the heck the deal is with Mercury.  Once you are done, write a computer program that solves that orbital component for different solar systems, use current data from the extrasolar planetary research.  Or use Excel, which does a great job with things like orbital mechanics. 

In this case you can use Excel to do some of the orbital calculations for Mercury.  But what  if you live in a world without the “Housewifes of Orange County” or Excel?  You might for fun do the calculations as a parlor game.  Yep, really, a game you played with others.  In the 1700s.  Using data from early telescopes and a system of calculations created by Kepler.  You most likely didn't play the calculate the orbit of Mercury with Newton, he was a loner.  But it is a game that could be done with Logo or TouchDevelop Turtle.

Now in the world of big data, where is the data that has been collected by visual observations since 1687 or so (date of the initial Mercury observations)  maintained?

More on storing big data as time goes on. 

For this I am reading the following books (yes books, otherwise the imaging effort for the Kindle has fallen short, but it is getting better):

  • Relativity: The Special and General Theory by Albert Einstein (it is the one he wrote with very few equations, or as he says on the cover: “A clear explanation that anyone can understand”.  You decide, it is a free Kindle book so check it out)
  • Mathematical Principles of Natural Philosophy, by Isaac Newton, Third Edition (Kindle edition, the images by Newton, must be sharp for most of the book, but as this book is available at most Libraries, check it out. You do need to see the diagrams for it to make sense.  Why? This uses the Newton approach to the Calculus not our modern approach and lot’s and lot’s of diagrams with triangles.  Beware: You may find this a fairly easy read as Newton is explaining his approach to Math and Astronomy, and spends time explaining the approach.  It has homework and solutions as well, always like solutions.

Why read these?  Well, my goal is to demonstrate a way to measure the speed of light somewhat accurately using the Arduino/Netduino, prisms (need to get those ordered) and some other stuff. 

What does this have to do with Big Data? Well it’s simple, to demonstrate big data, one needs to find interesting big data.  Astronomy has been collecting big data for CENTURIES!  However, one must understand the data.  Astronomical data is quite accurate, exactly presented as there was a requirement that others repeat the experiment or repeat the observation.  Also, repeating observations, like repeating the calculations for orbits means that I get to write software that I can tell is accurate, or not.

Where is Einstein in all of this?

Einstein and Newton both used tools that were not based in computers to solve their problems, and quite often much more accurately than computers do today.  But the nice thing about computers is that they are cheap, reliable and do what you tell them to do.  If you are using an apprentice to do the observations because you like to sleep at night, the apprentice might goof off.  Usually not, but I know when 3 AM rolls around, I get real sleepy and I am pretty sure that happened back in the old days as well.

So the goal here is to get to a point where we can use sensors to measure the speed of light using cheap things.

And if this sounds hard to do, your phone may use the speed of light measurement in the gyroscope that you are using for your game play, etc. 

(Although, the MEMs gyroscope is more widely used, there a some that use the Ring Gyro approach which measures the changes in the speed of light when the frame of reference varies.))

Here is a diagram.  Now the question is this: Why create a sensor that measures the speed of light?  Why indeed.  Because it is a sensor and there will be a trillion internet connected sensors of one sort or another in a short period of time, so all sensors are interesting.  From dumb, but awesomely named Magnet-Ring Sensor (just a switch) to the Interference based Speed of Light Sensors, all of these are fascinating to me.  And easy to blog about.

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