Astrophysics Corner Part 11 - Observations at an Astrophysics PhD Defence

I spent the week travelling and attending some astrophysics related activities, specifically witnessing the public portion of my son Scott’s PhD thesis defense, at McGill University in Montreal, Canada. That made it difficult to keep up with the usual writing and publishing related blog, which was intended to be related to the educational status of writers in the Amazon Top 100. There are some fascinating data there (all taken from public sources), with many interesting sociological implications. I will write about in the next couple of weeks. In the mean time, it might be of interest to people to read about the process of the Astrophysics PhD defense, since this blog is occasionally related to science as well as science fiction.

So, this blog will include some observations about the process of the PhD thesis defense (as observed by an educated layman), neutron star astrophysics in general and magnetars in particular and the culture of science, as experienced by the people who actually perform advanced scientific research. Naturally, I will keep these observations mostly anonymous, to preserve everyone’s right to privacy.

Observations at the PhD defence.

- Before the defense actually began, I overheard the grad students who were to attend discussing Battlestar Gallactica and Firefly.  Some expressed disappointment with the fact that Firefly had been cancelled before the story arc had been properly completed. There were discussions about the new BSG versus the old series, which they must have seen in rerun or DVD given their age. So, yes, get some astrophysics grad students together and they will spontaneously discuss SF.

- It rapidly became clear that a PhD thesis defence is no piece of cake.  After the presentation was over, the examiners asked tough, pointed questions.  It clearly isn't easy for the candidate, who has half a dozen subject experts drill him (or her) on their area of expertise, so the candidate has a lot of ground to potentially cover.

-  In this case, that included (but is not necessarily limited to):

• the fundamental physics of neutron stars - the hypothesized creation from supernovas of high mass stars, their theoretical internal structure, how magnetic field effects give rise to hot spots on the crust, how magnetic field behaviour in the atmosphere and nearby space gives rise to various observed photon energies, how rotating magnetic fields cause energy to be lost to the vacuum of space, energy losses due to magnetic field decay, etc.
• the mathematical modeling of the associated physics - identifying the black body component caused by hot spots versus the power law component caused by upper atmosphere synchrotron/cyclotron radiation, the braking index of magnetars caused by magnetic decay and rotational spin-down , the formulas for characteristic age, magnetic field strength deduced from periods and period derivatives, etc.
• use of fairly complicated statistical theory - small n Poisson statistics versus larger n Gaussian statistics, correlation and regression analysis, probability density functions, goodness of fit tests, confidence intervals, time series analysis, power spectra, etc.
• population statistics about magnetars, high magnetic field neutron stars, radio pulsars, binary system pulsars that were the keys to categorizing these different physical phenomena.
• the evolutionary theory that ties all of the above together, from their birth in supernovas to their eventual cooling into non-detection, and all of the stages in between, which will depend on the characteristics of the progenitor stars and the environment in which they are born.
• galactic scale astronomy - scale height of magnetars relative to the galactic plane, possible effects of selection bias due to dust and interstellar matter when interpreting data, location of the solar system relative to galactic plane, comparison with these results with measures from OB star studies and other methods.
• instrumentation effects - interference from soft proton flaring, responses of CCDs such as out-of-time events, the relative merits of different satellite telescopes, their orbits and physical makeup, energy levels they were designed to study.
• and lots more, which we will just call miscellaneous.

- In Scott’s case, he was defending a thesis which examined the phenomenon of magnetars in the largest sense - i.e. an overview of the entire population, based on his own observational research supplemented by wider reading. Naturally, the content that the candidate is expected to have mastered will depend on the focus of his or her thesis.

- The idea that a physics/math major ought to be able to think on his or her feet and do an order of magnitude calculation in their head (or perhaps on a chalkboard) is still highly prized.  No calculators or spreadsheets allowed, and you best be able to do a quick derivative or integral, at least to give a sense of how the underlying function works and what it means.

- A well done PowerPoint (or similar product) slideshow is still a very effective way of communicating a lot of complex information.  Good graphics, especially with effective colour use and carefully differentiated marker symbols can encapsulate a lot of data.

- The XY diagram or scatter chart is still a great way to illustrate the relationship between variables. Smart committee members can glean a lot from that and even suggest things that the author didn't see at first.  That is how science advances - everyone sees things a little differently and that keeps the research advancing.

- The dynamic tension between theorists and observationalists (or experimentalists) is ever present.  And that's good because it is central to the progress of science too.

- When the grilling was over, I gathered that the parties appreciated all of the above, and cut the candidate some slack for not knowing everything (just most of everything).

- When a corkscrew is broken, and a bottle of celebratory wine is at stake, a roomful of astrophysicists can improvise a repair as quickly as a roomful of engineers.  Intelligence plus motivation is unbeatable.

- A roomful of astrophysicists is smarter than the dialogue from The Big Bang Theory and has nearly as good a sense of comic timing and witty repartee.
At the Going Away Party

- A few days later, Scott’s PhD supervisor, Vicki Kaspi, had a party at her house for the members of her group that would be graduating or moving on to other jobs and activities. This could include completing their Master’s or PhD or finishing up a post-doc. A post doctoral fellowship is an intermediate stage between being a grad student and a more permanent career in academia.

- They were an engaging, pleasant group and Vicki and her husband (a renowned research cardiologist) were very fine hosts. Their children were also pleasant helpers - their hamster was fun too.

- Naturally, the concern about post-doc positions and other jobs was there. Not everyone who goes into advanced scientific research gets a faculty position. That’s just supply and demand. And not everyone wants a faculty position. Some people prefer to branch out into the private sector after exploring academia, either for the money and career potential or for the feeling that they are involved in research that affects people’s daily lives.

- Interestingly enough, one of the non-university sectors that employs people with this training is the field generally known as “data science”.

- That can include companies like Google and Amazon, who are always looking for high IQ people to develop new algorithms for data mining, internet searches, artificial intelligence tools and the like.

- It can also include big financial firms, pension funds, and so forth, who are looking for data analysts who can think outside the box, and learn, use and develop very advanced statistical techniques to make big money. I noted that many companies of this sort on Linked In were specifically looking for people with PhDs in math, physics and astronomy.

- It can also include people like me, who do applied research for businesses, governments and post-secondary institutions, develop data warehouses, and solve focussed data problems for decision makers. So, I think it is fair to say that I felt a sort of kinship with this group, even though I am not in the astrophysics PhD stream.

- Down deep, all data analysts speak the same language and want the same things - accurate data, interesting and challenging problems and the use of evidence to solve problems and learn what makes the world tick, whether the physical world on the scale of galaxies or the social world on the scale of small groups.

On Montreal and McGill

- By the way, Montreal is a great city and McGill is a great university with a lovely campus. If you visit, be sure to see Mount Royal Park, designed by the same person who did Central Park in New York (Fredrick Law Olmstead). And visit the physics building at McGill, where you will see the original lab equipment and notes of the Nobel laureate Ernest Rutherford, who did some of his best work at McGill.