Why do scientists get things wrong?

By Dr. Christina Smith

It occurred to me over the last couple of weeks that lots of people have found the changing information and guidelines, recommendations, and findings on COVID-19 to be surprising, sometimes frustrating, and perhaps don’t understand why things can change so rapidly. I’ve heard things like “why should I trust this information if its different to last week’s?” I’m not an epidemiologist or any kind of bio-anything scientist so that’s the only thing I’ll be saying about COVID-19. But, it dawned on me that perhaps it isn’t completely clear that people at the forefront of any field in science are really piecing together bits of information and evidence the best way they can to try and figure out what is happening. With time and enough information the explanations (often – not always) become more and more in agreement but with newer problems and smaller amounts of information, the findings that people come up with can vary wildly.

Intro to Infection Modelling

Like everyone else, the COVID-19 pandemic has drastically changed how our group operates and interacts. However, we've been luckier than others in our operations since relatively few projects that are currently active require access to the university experimental facilities which are now closed. 

Everyone has a different way of coping with the anxiety and stress that an unprecedented event like this one produces. For many scientists, there is a certain comfort in information. Sometimes the act of defining, modeling, classifying can make you feel as if you have more control over an uncontrollable situation and, at least, you might gain insight that might be actionable. 

The next two articles on this blog, submitted by the Postdocs, discuss the pandemic. The first, below, tries to consider the modeling of these systems. The second tries to grapple with the things that scientists get "wrong," by laying bare how piecing together a real-world puzzle from incomplete information can sometimes lead to dramatic shifts in our understanding of how these systems operate. In times like these, the public often turns to scientists for advice and it's important to remember that none of us has a crystal ball.

Wherever you are, I hope you are as safe and secure as you can be and are managing the physical and mental toll. No matter your circumstances you aren't alone in this.

by Dr. Paul Godin

With the COVID-19 pandemic drastically impacting our day-to-day lives, I thought it worth examining how epidemiologist model infections and how social distancing can “flatten the curve”.  (Note, this idea was inspired by Peter Taylor, who provided the initial matlab code to run the simulations)

Characterizing the atmosphere of exoplanet K2-141b

 

The image above (Credit: ESO/L. Calçada) shows CoRoT-7b, an exoplanet located so close to its parent star that the input of radiation causes the surface to melt. It is for this reason that these strange worlds are called "Lava Planets" and they have unique atmospheres that are made up of rocky vapours. PVL PhD student Giang Nguyen has been working on understanding how a similar world, K2-141b, operates in collaboration with Prof. Nick Cowan at McGill University. There will be a paper out soon, but Giang provides a preview of the work below.

by Giang Nguyen

K2-141b belongs to a subset of rocky planets that orbit very closely to their star and are tidally locked. The dayside of the planet is hot enough to not only melt rocks (about half the planet is one giant magma ocean, hence the name lava planet) but to vapourize them as well. This vapourization process ultimately creates a thin atmosphere that may be detectable from hundreds of light year away with the right space telescopes.

For my work, I have been using computer models to simulate the atmosphere of K2-141b. I considered two cases: a sodium atmosphere and a silica atmosphere. Sodium is chosen as it is the most volatile component in minerals while silica is chosen as it is expected to be the most abundant for rocky planets. The atmospheric model is based on the shallow-wave equations with steady-state flow driven mainly by the temperature contrast between the planet’s permanent dayside and nightside hemispheres. As expected, since sodium is much more volatile, the pressure of the sodium atmosphere is more than 50 times that of the silica atmosphere. This also allows the sodium atmosphere to exist beyond the day-night terminator while the silica atmosphere collapses just before this point. However, as sodium has a lower heat capacity than silica, the sodium atmosphere cools off much faster which has implications for observations. In either case, the wind exceeds 1.5 km/s which is useful for high-dispersion spectroscopy.