Solving PDEs with the FFT [Python]

This video describes how to solve PDEs with the Fast Fourier Transform (FFT) in Python.

These lectures follow Chapter 2 from:
"Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control" by Brunton and Kutz

This video was produced at the University of Washington

[fzigunov]

Dr. Brunton, I just would like to thank you. I'm towards the end of my PhD in fluid mechanics and your lectures have been an integral part of it. You're an awesome presenter and teacher!!

[pradiptahafid]

0:29. Is he writing with the mirror effect? I thought he writes normally and during the editing, he mirrors the video. Anyway, Trully blessed the modern era because of you. For someone who does not come from a math background, this video is a gem. I have been spending 2 weeks on your books and videos. They are amazing.

[nezv]

I've always wanted to make a video series like these. So many students feel like there is a big mystical gap between these concepts and the hands-on of coding and using them. Your videos do a great job of demystifying, keep up the good work!

[flaguser]

I had always thought that the videos are mirrored in post production. But after seeing Steve write a mirrored "FFT" by mistake at the start, I'm not sure anymore. So he actually trained to write mirrored after all. I'm really thankful!

[pierrestemmettmusic]

My new favourite youtube channel of all time! Thank you Steve Brunton you're a hero. The sole reason I am passing my degree.

[mohammadumair]

Dr. Brunton, you have played a cruel trick, a cruel trick indeed! 😅

[HassanKhan-csho]

This video lecture series by you have been a life changing experience for me. you have truly demystified on how to go from complex mathematical concept to coding it and then applying it. the elegance with which you implement the algorithm in code is really motivating for me to apply it myself and test under different applications. Thank you sir and i hope you keep us mesmerized further with your future lectures.

[mathieug]

That was a good lecture! I didn't look at those math in like 10 years.

[pipertripp]

ha. First time I've ever seen someone write "backwards" on a lightboard. It's such cool tech. Probably makes teaching a lot more engaging for the presenter since they can look at the class the entire time.

[qiguosun]

Dr.Brunton's lecture just like art.

[apostoloskountouris]

Hi ambidextrous mirror magician Steve!
Your videos are outstanding and you are a real teacher!
However I must say that you are a very sneaky individual for doing this inverse writing FFT (3 letters) in the beginning making this surprised look and then starting all over!
Very sneaky indeed!
cheers!

[DeonMitton]

That trick was very clever... I bet people were thinking hard about that one !

[dypoet]

I have been thinking Steve must been writing the text left to right and flipped the video so that we won't see the text opposite. But at the beginning he wrote the text from right to left accidentally. Does this means he has been writing/drawing in the opposite way all the time?

[leilikheirkhah]

Thanks Dr. Brunton, your teaching style is incredibly great! The video helped me alot.

[felipegabriel]

Nice lecture, those plots were awesome!

[alialavib]

Great job posting videos amid all this

[williamcoggins]

Amazing content! Do you think this approach can be use to solve the time - independent Schrodinger eqn?

[stepanshcherbinin]

It is a great pleasure to watch this lection. Thanks!

[LucasDimoveo]

I'm a stay-at-home parent on the journey of self-learning mathematics until I can go to university. Knowing that I'll be able to approach interesting and difficult applied problems with Python and PDEs is a huge motivator. Thank you for making your material public!


Other than a background in Scientific Computing, Calculus and ODEs, and (introductory) Linear Algebra, what else would you recommend as preparation for your book?

[ismaelpour]

Thank you, Thank you, Thank you. Truly life-changing ✌