If You Don’t Get A Quantum Computer For Christmas

Learn Quantum Mechanics with Haskell by Scott N. Walck.

Abstract:

To learn quantum mechanics, one must become adept in the use of various mathematical structures that make up the theory; one must also become familiar with some basic laboratory experiments that the theory is designed to explain. The laboratory ideas are naturally expressed in one language, and the theoretical ideas in another. We present a method for learning quantum mechanics that begins with a laboratory language for the description and simulation of simple but essential laboratory experiments, so that students can gain some intuition about the phenomena that a theory of quantum mechanics needs to explain. Then, in parallel with the introduction of the mathematical framework on which quantum mechanics is based, we introduce a calculational language for describing important mathematical objects and operations, allowing students to do calculations in quantum mechanics, including calculations that cannot be done by hand. Finally, we ask students to use the calculational language to implement a simplified version of the laboratory language, bringing together the theoretical and laboratory ideas.

You won’t find a quantum computer under your Christmas tree this year.

But Haskell + Walck will teach you the basics of quantum mechanics.

You may also want to read:

Structure and Interpretation of Quantum Mechanics – a Functional Framework (2003) by Jerzy Karczmarczuk.

You will have to search for it but “Gerald Jay Sussman & Jack Wisdom (2013): Functional Differential Geometry. The MIT Press.” is out on the net somewhere.

Very tough sledding but this snippet from the preface may tempt you into buying a copy:


But the single biggest difference between our treatment and others is that we integrate computer programming into our explanations. By programming a computer to interpret our formulas we soon learn whether or not a formula is correct. If a formula is not clear, it will not be interpretable. If it is wrong, we will get a wrong answer. In either case we are led to improve our program and as a result improve our understanding. We have been teaching advanced classical mechanics at MIT for many years using this strategy. We use precise functional notation and we have students program in a functional language. The students enjoy this approach and we have learned a lot ourselves. It is the experience of writing software for expressing the mathematical content and the insights that we gain from doing it that we feel is revolutionary. We want others to have a similar experience.

If that interests you, check out courses by Sussman at MITOpenCourseware.

Enjoy!

Comments are closed.