The International Year of Sound

In 2015, DTLR celebrated the International Year of Light.  Alas, I was not even aware that 2020 is the International Year of Sound until I received this month's issue of Physics Today.  As a former member of the Acoustical Society of America (ASA), I wish I had known of this earlier.  In the past I've contributed to research in both physiological acoustics and later ultrasound imaging, but have been away from the field over over a decade.  Nonetheless, I am pleased to recognize the International Year of Sound, if only during its final weeks.

Don't let lecture notes rot

Last week Nature Physics published an op-ed titled "Don't Let Lecture Notes Rot" (vol. 16, p. 1167).  It makes the case for physicists to make their lecture notes available more broadly than for just their own students, particularly in advanced courses where an individualistic perspective can be appreciated by students and even other faculty worldwide.  The op-ed also discusses some of the logistical issues involved in making such notes both available and findable. 

As an example of making lecture notes available, Springer's 50-year old series, Lecture Notes in Physics, long predates the internet, but still seems to be going strong; it is accompanied by their series Undergraduate Lecture Notes in Physics, which seems to be about 10 years old.  During my graduate research in physics in the late 1990s, there were two particularly useful volumes of LNP that I relied on and cited in my dissertation.  Nowadays, individual professors can simply post their course notes on their personal websites, though they may need encouraging from their colleagues and students, and perhaps university department heads.  

One of the mechanisms discussed for making the most interesting or useful lecture notes findable is for faculty to share annotated reading lists or reference lists.  These often appear in course syllabi, though I agree with the op-ed that some annotation would make these lists even more useful.  I think this principle applies even more broadly.  For instance, I have never taught an upper level physics course, but I can certainly share some books that I found useful as I was studying physics, in the spirit of helping others navigate the landscape of learning materials.  However, bear in mind that my experience dates from the late 1990s, and I am unfamiliar with more recent literature in the field, as well as online offerings such as the MIT OpenCourseware mentioned in the op-ed.

Here I will focus on three standard subjects:  classical mechanics, classical electromagnetic theory, and thermodynamics & statistical physics.  I will also discuss a nonstandard one, fluid dynamics.  Let me start by saying that in retrospect, the textbooks assigned for my undergraduate courses in these topics did not suit me at all.  It wasn't until graduate school that I expanded my reach to a serious study of texts other than those I was assigned, particularly when I was studying for the qualifying exams.  So, the discussion below focuses particularly on books I consulted heavily during those studies.  Of greatest interest are books that have a good balance of theory and solved problems.

For undergraduate classical mechanics, my hands-down favorite must be Marion & Thornton's Classical Dynamics of Particles and Systems, a book almost ideally suited for preparing for the qualifying exams.  I also occasionally consulted Symon's Mechanics, whose chapter on gravitation includes a vector field theory/PDE formulation of classical gravity not found in Marion & Thornton.  Symon also briefly discusses fluid dynamics and acoustics, topics absent from Marion & Thornton.  At the graduate level, I must confess I am not a fan of Goldstein's Classical Mechanics.  Were I to revisit theoretical mechanics, I would take a look at Fetter & Walecka's Theoretical Mechanics of Particles and Continua, Scheck's Mechanics:  From Newton's Laws to Deterministic Chaos, and a little book by Leech, Classical Mechanics.

For electromagnetic theory, my clear favorite is Griffiths' Introduction to Electrodynamics, which in my view is at the pinnacle of undergraduate physics textbooks.  I regret that I did not encounter the book until my first year in graduate school, but it too is ideal preparation for the qualifiers.  Griffiths does not dwell much on electrical circuits though, so I supplemented it with Electromagnetic Fields and Waves, by Lorrain, Corson, & Lorrain.  A backup reference was Nayfeh & Brussel's Electricity and Magnetism.  Finally, as an example of alternate perspectives discussed in the Nature Physics op-ed, Schwartz's Principles of Electrodynamics puts special relativity at the heart of its development of the theory, making Maxwell's equations seem much more natural than the conventional presentations do.  I hope that all physics students get exposed to Schwartz's approach at some point in their learning careers.  Another alternate perspective is presented in Kovetz's Electromagnetic Theory, which includes integrated discussion of continuum mechanics and thermodynamics, topics not often found in undergrad E&M.  A bridge to graduate level books like Jackson's nerve-wracking Classical Electrodynamics could be Heald & Marion's Classical Electromagnetic Radiation.

Thermodynamics and Statistical Mechanics by Greiner, Neise, and Stocker, part of Greiner's Classical Theoretical Physics series, is a superb qualifying exam study resource for those topics.  When I actually took graduate level statistical physics, I found Statistical Mechanics:  An Advanced Course with Problems and Solutions, by Kubo, Ichimura, Usui, and Hashitsume, a superb backup resource.  There are many other books I would look at were I to revisit thermal/statistical physics, but one worth mentioning is Reichl's A Modern Course in Statistical Physics, which includes coverage of nonequilibrium phenomena.

A physicist should begin the study of fluid dynamics with the two chapters on it in the Feynman Lectures on Physics.  The main text I learned fluid dynamics from was the first edition of Fluid Mechanics by Pijush K. Kundu.  It is an exceptional choice, one that I would highly recommend to others.  This is a field blessed with many fine books.  I found particularly useful the following:

• Aris, Vectors, Tensors, and the Basic Equations of Fluid Mechanics, a major source for Kundu's presentation of the derivation of the Navier-Stokes equations.
  
• Choudhuri, The Physics of Fluids and Plasmas:  An Introduction for Astrophysicists, which makes connections with the kinetic theory of gases, plasma physics, and magnetohydrodynamics.
• Tritton, Physical Fluid Dynamics, very much an experimentalist's perspective.
  

The list of fluid dynamics books I would consult were I to return to the field is too long to outline here.  I will just mention Batchelor's An Introduction to Fluid Dynamics, Falkovich's Fluid Mechanics:  A Short Course for Physicists, Guyon et al.'s Physical Hydrodynamics, Panton's Incompressible Flow, and Yih's Fluid Mechanics:  A Concise Introduction to the Theory.

I will end with a few other miscellaneous books I found useful in my studies:  Optics, by Hecht; Optical Properties of Solids, by Fox; Waves, by Crawford (part of the Berkeley Physics Course); Group Theory in Physics, by Tung; Physical Chemistry, by Atkins; Giant Molecules:  Here, There, and Everywhere..., by Grosberg & Khokhlov; and naturally the Landau & Lifshitz Course of Theoretical Physics.

"In our quest for accurate simulations, are we computing too much and thinking too little?"

The title of this post is a quote from Kerry Emanuel's essay published earlier this year, "The Relevance of Theory for Contemporary Research in Atmospheres, Oceans, and Climate".  He expresses a concern that numerical models of these phenomena, and attempts to improve their predictive performance by brute force, have supplanted the value of theoretical reasoning in advancing atmospheric and oceanic science.  The need to cope with large data sets and computational methodology has supplanted the study of scientific theory and physics in the curriculum, resulting in an unbalanced focus by both students and researchers, in his view.  He presents the argument more forcefully and eloquently than I can, so DTLR recommends this essay to all its readers.

Reference

K. Emanuel, 2020:  The relevance of theory for contemporary research in atmospheres, oceans, and climate.  AGU Advances, 1 (2), e2019AV000129.

 

A Perspective on the Legacy of Edward Lorenz

Recently I stumbled upon a paper published last year by James McWilliams, "A Perspective on the Legacy of Edward Lorenz".  The paper discusses what McWilliams considers to be Lorenz's four most important ideas:

1. Available potential energy in the atmospheric general circulation;
2. The Lorenz model's chaotic dynamics and strange attractor;
3. The limits of weather predictability; and
4. The "slow manifold".
   

My own thesis research directly applies versions of the first two of these ideas, so I owe a lot to him.  I had the privilege of meeting Prof. Lorenz when he was well in his late 80s.  The occasion was an annual meeting of the American Meterological Society in San Diego, in January 2004.  A symposium in Lorenz's honor was held, and he gave the final presentation of the symposium.  Earlier in the day, a poster session was included in the festivities, and he graciously visited the posters.  My mentor and I first encountered him there.  We introduced ourselves and shook his hand, but otherwise exchanged very few words with him.  We also spoke briefly with him after his presentation at the end of the symposium.  One of his biographers described him as "reticent" and that is consistent with my brief experience with him.

Not being part of an elite institution, I do not often meet major figures in the history of science.  My brief encounter with Lorenz was one such instance.  Here is a picture of the cover of the symposium booklet.

Reference

J. C. McWilliams, 2019:  A perspective on the legacy of Edward Lorenz.  Earth and Space Science, 6 (3):  336-350.

Carlo Rovelli's rant about statistical illiteracy

In the Guardian earlier this week, physicist Carlo Rovelli has an op-ed railing about statistical illiteracy, which he says can be fatal in a pandemic.  He opposes early criticisms of COVID-19 epidemiological models "estimating rather than accurately depicting how severe the virus might be."  Aside from that, he never actually makes clear why statistical illiteracy can be fatal.

Let us focus then on other aspects of his argument that children should be "taught the fundamental ideas of probability theory and statistics".  For example, he writes:

We use probabilistic reasoning every day, and most of us have a vague understanding of averages, variability and correlations. But we use them in an approximate fashion, often making errors. Statistics sharpen and refine these notions, giving them a precise definition, allowing us to reliably evaluate, for instance, whether a medicine or a building is dangerous or not.

On the contrary, we should be using probabilistic reasoning and statistical ideas in an approximate fashion.  To pretend that the nominal precision of probabilistic and statistical claims can be taken seriously in any but the most sterile situations is just as dangerous as the statistical illiteracy Rovelli complains about (see Kay & King, 2020; Weisberg, 2014; Derman, 2011; Taleb, 2007; I won't rehearse the case made eloquently by these writers).  See also my recent post.  

The most important statistical contribution to the evalution of medicines, to take Rovelli's example, is in the rigorous sequence of phased clinical trials (described in ICH, 1997), rather than specific methods of data analysis.  Phased clinical trials are designed to learn and confirm knowledge about the efficacy and safety of a proposed drug or biologic in a sequence of designed studies in three phases, culminating in the third phase consisting of at least two randomized, blinded, controlled clinical trials.  It is the features of study design and mutually reinforcing knowledge from all phases that makes decisions about medicines reliable, with data analytical methodology playing only a supporting role.

Rovelli writes:

Without probability and statistics, we would not have anything like the efficacy of modern medicine, quantum mechanics, weather forecasts or sociology. To take a couple of random but significant examples, it was thanks to statistics that we were able to understand that smoking is bad for us, and that asbestos kills.

The first example, the causal assocation of smoking and lung cancer, is a masterpiece of epidemiological reasoning, described well by Freedman (1999, Sec. 8).  Of one of the statistical models used in the research, Freedman writes,

The realism of the model, of course, is open to serious doubt:  patients are not hospitalized at random.This limits the usefulness of confidence intervals and P-values. Scientifically, the strength of the case against smoking rests not so much on the P-values, but more on the size of the effect, on its coherence and on extensive replication both with the original research design and with many other designs. Replication guards against chance capitalization and, at least to some extent, against confounding—if there is some variation in study design.

Freedman concludes:

The strength of the case rests on the size and coherence of the effects, the design of the underlying epidemiologic studies, and on replication in many contexts. Great care was taken to exclude alternative explanations for the findings. Even so, the argument depends on a complex interplay among many lines of evidence. Regression models are peripheral to the enterprise.

I actually agree with Rovelli that probability and statistics have made important contributions to medicine, quantum theory, and weather forecasting.  However to include sociology in this list is questionable.

Statisicians themselves are in intense disageement over how statistical methods such as p-values should be used and interpreted, as illustrated in last year's special issue of The American Statistician (TAS) on "Statistical Inference in the 21st Century:  A World Beyond p < 0.05", and the "Statistics Debate" sponsored by the National Institute of Statistical Sciences, held earlier this month.  How then do we expect to teach children about statisics?  Perhaps the only positive outcome of the TAS special issue is the final paper of the collection, describing a course on statistical thinking "beyond calculations" (Steel et al., 2019).  I would favor a course of this kind rather than technical training on probability theory and statistical methods that Rovelli seems to be advocating.  Rovelli's rice-throwing story would fit very well within such a course, and illustrates how approximate thinking about statistics can be more concrete and intuitive than a bunch of technical mathematics. 

References

Emanuel Derman, 2011:  Models. Behaving. Badly.  Why Confusing Illusion with Reality Can Lead to Disaster, on Wall Street and in Life.   New York:  Free Press.

David Freedman, 1999:  From association to causation:  some remarks on the history of statistics.  Statistical Science, 14 (3):  243-258. 

International Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use (1997), ICH Harmonised Tripartite Guideline: General Considerations for Clinical Trials, E8.

John Kay and Mervyn King, 2020:  Radical Uncertainty:  Decision-Making Beyond the Numbers.  New York:  W. W. Norton.

E. Ashley Steel, Martin Liermann, and Peter Guttorp, 2019:  Beyond calculations:  a course on statistical thinking.  The American Statistician, 73 (Supplement 1):  392-401.

Nassim Nicholas Taleb, 2007:  The Black Swan:  The Impact of the Highly Improbable.  New York:  Random House.

Herbert I. Weisberg, 2014:  Willful Ignorance:  The Mismeasure of Uncertainty.  Hoboken:  Wiley.

The Nobel Prizes 2014-2020

In its first year, this blog commented here and here on the 2013 Nobel Prize in Physics; however I failed to comment on any of the prizes in following years.  As we are now wrapping up Nobel week 2020, let me offer a few observations on the prizes in physics and chemistry in the years since 2013.  Before I do that, I want to also note last year's Economics Prize for work applying randomized trials to social science.  Such a worthy achievement reflects well on two earlier advocates of randomized trials, statisticians Ronald A. Fisher and Austin Bradford Hill, who pioneered their use in agriculture and medicine, respectively.

Physics

 

I am especially pleased to see two of the subsequent prizes in physics were awarded for technological innovations, namely 2014 (blue LEDs) and 2018 (inventions in laser physics).  It is my view that applied physics is part of physics proper, and should be recognized as such at the highest levels.  Other recent prizes in this vein include 2009 (fiber optics and CCD sensors), half of the 2005 prize (optical frequency comb), and 2000 (the integrated circuit, and semiconductor heterostructures).

 

The 2017 prize to the prime movers of the LIGO collaboration for discovering gravitational waves was arguably premature at the time, as I had misgivings about certain methodological details of the original discovery.  However I think the evidence base accumulated since then, and the methodological improvements, have been both impressive and convincing.  I am prepared to join other voices proclaiming that we are living in the era of gravitational wave astronomy.

The 2019 and 2020 prizes are unusual in that they have gone for two years in a row to achievements in astrophysics and astronomy.  Following the same pattern, each year one theoretical astrophysicist and two observational astronomers shared the prize.  In 2019, the theorist James Peebles essentially received a lifetime achievement award for his contributions to the standard model of cosmology, while Michel Mayor and Didier Queloz were honored for the first discovery of an exoplanet orbiting a solar-like star.  This year, Roger Penrose was honored for his theoretical work on black holes.  Laureates Reinhard Genzel and Andrea Ghez are the heads of two competing groups making observations at Sagittarius A*, who determined that the center of the Milky Way galazy is occupied by a "supermassive compact object".  This last is carefully worded; the obvious implication is that this object is a Black Hole, but the Nobel Committee chose not to use those words.  I am pleased that the leads of these fiercely competitive groups were honored together.

Finally, it is notable that though the third year of the Nobel Prize in Physics included its first female laureate (Marie Curie, 1903), a 60 year gap occurred before the second (Maria Goeppert Mayer, 1963), and a 55-year gap occured before the third (Donna Strickland, 2018).  Only a two-year gap separated the third and fourth women laureates.  I started the study of physics 28 years ago and saw year after year pass with no female laureates, while several possible female candidates passed away, like Deborah Jin who died at age 47.  It's therefore breathtaking to see two female laureates in just the last two years!  Hopefully this is not simply a 'market correction' but rather a 'new normal' (apologies for the cliche'd analogy).

 

Chemistry

 

First I can't resist bragging that the 2014 prize was awarded to physicists.  Most of the recent prizes have been for technological innovations like theirs, with many being specific to the life sciences.  This is befitting chemistry's status as the "central science", overlapping on one end with physics and at the other with biology and medicine.  Finally, it is notable that 4 of the 7 ever female laureates were awarded in the last 11 years (Ada Yonath, 2009; Frances Arnold, 2018; and this year's laureates Emannuelle Charpentier and Jennifer Doudna).

Before this year, each woman laureate in physics or chemistry had died before the next one was awarded in her field; most tragically, Irene Joliot-Curie winning the year after her mother died.  The exception was Frances Arnold's 2018 award while Ada Yonath was still alive.  However now there are four living female laureates in chemistry and two in physics, an unprecedented occurrence, but let us hope these numbers will only increase moving forward.  

 

(By my count, there are currently 7 living female laureates in physiology and medicine; 10 in peace; 6 in literature; and only 1 in economics, though that prize has a shorter history than the others.)

Matt Ridley on "What the Pandemic has taught us about Science"

This weekend's issue of the Wall Street Journal features an insightful essay by Matt Ridley, in the Review section, titled "What the Pandemic has taught us about Science".  Two of the best passages are the following very simple observations:

"Seeing science as a game of guess-and-test clarifies what has been happening these past months.  Science is not about pronouncing with certainty on the known facts of the world; it is about exploring the unknown by testing guesses, some of which prove wrong."

"The health of science depends on tolerating, even encouraging, at least some disagreement.  In practice, science is prevented from turning into religion not by asking scientists to challenge their own theories but by getting them to challenge each other, sometimes with gusto."

I strongly recommend the article to DTLR readers, even if you may nit-pick a few details.