Resources, Readings, and References

Textbook

The course will make regular reference to [Mahajan, 2014, Weinstein, 2012, Weinstein and Adam, 2008] and [Munroe, 2014]. These will be supplemented by [Mahajan, 2010, Olshanii, 2013] and [Munroe, 2022].

Podcasts

The following podcasts will be assigned to stimulate discussion about being creative, how to succeed at failing, etc.

• How to Be Creative: A series of podcasts exploring creativity, including:

  • How to Be Creative

  • Where Does Creativity Come From (and Why Do Schools Kill It Off)?

  • Where Do Good Ideas Come From?: Discusses brainstorming.

  • A Good Idea Is Not Good Enough:

  • How to Fail Like a Pro:

• How to Succeed at Failing: A series of podcasts exploring how to fail successfully:

  • Part 1: The Chain of Events: Discusses the Lahaina fire which will form a basis for some examples used in class.

  • Part 2: Life and Death

  • Part 3: Grit vs. Quit

  • Part 4: Extreme Resiliency

• Freakonomics Radio Goes Back to School:

  • What Exactly Is College For?

  • The University of Impossible-to-Get-Into

  • “I Don’t Think the Country Is Turning Away From College.”

  • What Is the Future of College — and Does It Have Room for Men?

  • “If We’re All in It for Ourselves, Who Are We?”: Interesting interview with Tania Tetlow, the current president of Fordham University.

I have some issues here with the discussion of music and Alfred Cortot’s “careless technique”. Ask me. (MMF)

• Practice: How does one achieve mastery? In class I will compare mastering music (piano) with physics.

  • How to Become Great at Just About Anything: Interview with Anders Ericsson, from whom the 10,000 hour idea originates. Emphasizes the importance of deliberate practice.

  • Deliberate Practice: How Education Fails to Produce Expertise: A brief post by Sanjoy Mahajan – the author of one of our texts.

  • How to Get More Grit in Your Life: Discussion of Grit

References

[Boy89]

John P. Boyd. Chebyshev and Fourier Spectral Methods. Volume 49 of Lecture Notes in Engineering. Dover, Berlin Heidelberg, 2 edition, 1989. ISBN 978-0486411835. URL: http://www-personal.umich.edu/~jpboyd/BOOK_Spectral2000.html.

[JK76]

E. T. Jaynes and Oscar Kempthorne. Confidence Intervals vs Bayesian Intervals, pages 175–257. Springer Netherlands, 1976. URL: http://dx.doi.org/10.1007/978-94-010-1436-6_6, doi:10.1007/978-94-010-1436-6_6.

[LMC+22]

Fernando Llorente, Luca Martino, Ernesto Curbelo, Javier López‐Santiago, and David Delgado. On the safe use of prior densities for Bayesian model selection. WIREs Comput. Statistics, July 2022. URL: http://dx.doi.org/10.1002/wics.1595, arXiv:2206.05210, doi:10.1002/wics.1595.

[Lor92]

Thomas J. Loredo. Promise of Bayesian Inference for Astrophysics, pages 275–297. Springer New York, 1992. URL: http://dx.doi.org/10.1007/978-1-4613-9290-3_31, doi:10.1007/978-1-4613-9290-3_31.

[Mah10]

Sanjoy Mahajan. Street-Fighting Mathematics: The Art of Educated Guessing and Opportunistic Problem Solving. The MIT Press, March 2010. ISBN 9780262265881. URL: http://dx.doi.org/10.7551/mitpress/7728.001.0001, doi:10.7551/mitpress/7728.001.0001.

[Mah14]

Sanjoy Mahajan. The Art of Insight in Science and Engineering: Mastering Complexity. The MIT Press, 11 2014. ISBN 9780262325233. doi:10.7551/mitpress/9017.001.0001.

[Mer07]

N. D. Mermin. Quantum Computer Science: An Introduction. Cambridge University Press, 2007. ISBN 978-0-511-33982-0. URL: https://www.cambridge.org/core/books/quantum-computer-science/66462590D10C8010017CF1D7C45708D7, doi:10.1017/CBO9780511813870.

[ML03]

Cleve Moler and Charles Van Loan. Nineteen dubious ways to compute the exponential of a matrix, twenty-five years later. SIAM Review, 45(1):3–49, 2003. URL: http://dx.doi.org/10.1137/S00361445024180, doi:10.1137/S00361445024180.

[Mun14]

Randall Munroe. What If?: Serious Scientific Answers to Absurd Hypothetical Questions. Houghton Mifflin Harcourt, 2014. ISBN 0-544-27299-4.

[Mun22]

Randall Munroe. What If? 2: Additional Serious Scientific Answers to Absurd Hypothetical Questions. Riverhead Books, New York, 2022. ISBN 9781473680623.

[NC10]

Michael A. Nielsen and Isaac L. Chuang. Quantum Computation and Quantum Information. Cambridge University Press, 2010. URL: https://doi.org/10.1017%2Fcbo9780511976667, doi:10.1017/cbo9780511976667.

[Ols13]

Maxim Olshanii. Back-of-the-Envelope Quantum Mechanics (With Extensions to Many-Body Systems and Integrable PDEs). World Scientific, April 2013. ISBN 9789814508476. URL: https://doi.org/10.1142%2F8811, doi:10.1142/8811.

[PTVF07]

William H. Press, Saul A. Teukolsky, William T. Vetterling, and Brian P. Flannery. Numerical Recipes: The Art of Scientific Computing. Cambridge University Press, third edition, 2007.

[Schrodinger52]

Erwin Schrödinger. Statistical Thermodynamics. Dover Publications, 1952. ISBN 0-486-66101-6.

[TPMuller19]

Maria Antónia Amaral Turkman, Carlos Daniel Paulino, and Peter Müller. Computational Bayesian Statistics: An Introduction. Volume 11 of Institute of Mathematical Statistics Textbooks. Cambridge University Press, Cambridge, UK, 2019. ISBN 978-1-108-48103-8. doi:10.1017/9781108646185.

[vT11]

Udo von Toussaint. Bayesian inference in physics. Rev. Mod. Phys., 83:943–999, September 2011. URL: https://link.aps.org/doi/10.1103/RevModPhys.83.943, doi:10.1103/RevModPhys.83.943.

[Wei12]

Lawrence Weinstein. Guesstimation 2.0: Solving Today's Problems on the Back of a Napkin. Princeton University Press, 2012. ISBN 9780691150802.

[WA08]

Lawrence Weinstein and John Adam. Guesstimation: Solving the World's Problems on the Back of a Cocktail Napkin. Princeton University Press, 2008. ISBN 9780691129495.

Linear Algebra

• Essence of linear algebra: A great set of highly visual videos by 3Blue1Brown getting you up to abstract vector spaces.

• MIT 18.06 Linear Algebra: A set of video lectures and accompanying material for the MIT Linear Algebra course.

• Qiskit Linear Algebra: A short introduction that is part of the Qiskit platform.

• Appendix A of [Mermin, 2007] has a nice short review of Dirac notation.