Over a million developers have joined DZone.
{{announcement.body}}
{{announcement.title}}

Physical Constants in Python

DZone's Guide to

Physical Constants in Python

Python and SciPy library are pretty powerful scientific tools. In this post, we put this to the test using a famous problem from the world of physics.

· Big Data Zone ·
Free Resource

The open source HPCC Systems platform is a proven, easy to use solution for managing data at scale. Visit our Easy Guide to learn more about this completely free platform, test drive some code in the online Playground, and get started today.

You can find a large collection of physical constants in scipy.constants. The most frequently used constants are available directly, and hundreds more are in a dictionary physical_constants.

The fine structure constant α is defined as a function of other physical constants:

The following code shows that the fine structure constant and the other constants that go into it are available in scipy.constants.

    import scipy.constants as sc

    a = sc.elementary_charge**2
    b = 4 * sc.pi * sc.epsilon_0 * sc.hbar * sc.c
    assert( abs(a/b - sc.fine_structure) < 1e-13 )

Eddington's Constant

In the 1930s, Arthur Eddington believed that the number of photons in the observable universe was exactly the Eddington number:

Since at the time the fine structure constant was thought to be 1/136, this made the number of photons a nice even 136 × 2 256. Later he revised his number when it looked like the fine structure constant was 1/137. According to the Python code above, the current estimate is more like 1/137.036.

Eddington was a very accomplished scientist, though he had some ideas that seem odd today. His number is a not a bad estimate, though nobody believes it could be exact.

Related Posts

The constants in scipy.constants have come up in a couple previous blog posts.

The post on Koide's coincidence shows how to use the physical_constants dictionary, which includes not just the physical constant values but also their units and uncertainty.

The post on Benford's law shows that the leading digits of the constants in scipy.constants follow the logarithmic distribution observed by Frank Benford (and earlier by Simon Newcomb).

Managing data at scale doesn’t have to be hard. Find out how the completely free, open source HPCC Systems platform makes it easier to update, easier to program, easier to integrate data, and easier to manage clusters. Download and get started today.

Topics:
scipy ,python ,big data ,scientific python ,tutorial

Published at DZone with permission of

Opinions expressed by DZone contributors are their own.

{{ parent.title || parent.header.title}}

{{ parent.tldr }}

{{ parent.urlSource.name }}