Science illustrations made by people without quantitative sensibility
From a tweet I saw retweeted by someone I follow (lost the reference), this is supposed to be a depiction of the Chicxulub impact:
My first impression (soon confirmed by minor geometry) was that that impact was too big; yes, the meteor was big for a meteor (ask the dinosaurs…), but the Earth is really really big compared to meteors. Something that created such a large explosion on impact wouldn't just kill 75% of the species on Earth, it would probably kill everything on the planet down to the last replicating protein structure, boil the oceans, and poison the atmosphere for millions of years.
Think Vorlon planet-killer, not Centauri mass driver. 🤓
Using a graphical estimation method (fit a circle over that segment of the Earth to get the radius in pixels, so that we can translate pixels into kilometers), we can see that this is an overestimation of at least 6-fold in linear dimensions (the actual crater diameter is ~150km):
6-fold increase in linear dimensions implies 216-fold increase in volume (and therefore mass); using the estimated energy of the actual impact from the Wikipedia, the energy of the impact above would be between $2.81 \times 10^{26}$ and $1.25 \times 10^{28}$ J or up to around 22 billion times the explosive power of the largest H-bomb ever detonated, the Tsar Bomba.
The area of the Earth is 510.1 million square kilometers, so that's 43 Tsar Bombas per square kilometer --- which is a lot, considering that the one Tsar Bomba that was detonated had a complete destruction radius in excess of 60 km (or an area of 11,310 square kilometers) and partial destruction (of weaker structures) at distances beyond 100 km (or an area of 31,416 square kilometers). And, again, that's 43 of those per square kilometer; so, yeah, that would probably have been the end of all life as we know it on Earth, and I wouldn't be here blogging about it.
A more accurate measurement, using a bit of trigonometry (though still using Eye 1.0 for the tangents):
Because of the eye-based estimation, it's a good idea to do some sensitivity analysis:
(Results are slightly different for the measured case because of full-precision calculation as opposed to dropped digits in the original, hand-calculator and sticky notes-based calculation.)
It gets worse. In some depictions we see the meteor, and it's rendered at the size of a planetoid (using the graphical method here too, because it's quick and accurate enough):
For additional context, the diameter of the Moon is 3,474 km, so the meteor in the image above is almost 1/3 the diameter of the Moon (28% to be more accurate) and that impact crater is over 1/2 the diameter of the Moon (60% to be more accurate).
Solar energy density in context
2 square kilometers for 100 MW nameplate capacity… and they're in the shade in that photo, so not producing anything at the moment.
Capacity factor for solar is [for obvious reasons] hard bound at 50%. For California, our solar CF is 26%; let's give Peter Mayle's Provence slightly better CF at 30%, and those 2 square km of non-dispatchable capacity become about 1/20 of a single Siemens SGT-9000H (fits in 1200 square meters with a lot of space to spare for admin offices and break room, works 24/7).
Nano-review of R Programming Compiler for the iPad
Basics: Available on the iOS app store; uses a remote server to run the code, so must have a net connection. Free for the baseline but seven dollars for plots and to use packages, which I paid. The extended keyboard is very helpful considering the limitations of the iPad keyboard. (Also runs on the iPhone and the iPod touch, though I haven't used it on them yet.)
I wouldn't use it to develop code or even to run serious models, but if there's a need to do a quick simulation or analysis (or even as a matrix calculator), it's better than Numbers. Can also be used offline to browse (and edit) code, though not to run it.
The programmer-joke code snippet in the above screen capture run instantly over a free lobby internet in a hotel conference center, so the service is pretty efficient for these small tasks, which are the things I'd be using this for.
Some retailers plan to eat the losses from tariffs
From Bain and Company on Twitter:
My comment (on twitter): Yeah, these are well-behaved cost and demand functions so when a tariff is added to the cost, typically the quantity drops and the price rises, unless there's some specific strategic reason to incur short-term opportunity costs.
Rationale (from any Econ 101 course, but I felt like drawing my own, just for fun):
Note that Bain's breakpoint at 50% of the tariff is the solution to the problem under linear demand with constant marginal cost, but other shapes of demand can make that number much bigger, for example, this exponential leads to 74% (numbers rounded in the diagram but not in the computation):
The demand function is nothing awkward or surprising, just a nice decreasing exponential:
On the other hand, if the marginal cost decreases with quantity, particularly if marginal cost is strongly convex, there's a chance the actual price increase from a tariff is higher than the tariff, even with linear demand:
Note that this is different from lazy markup pricing. Lazy markup pricing always raises the price by more than the tariff, so in places where such outdated pricing practices [cough Portugal /cough] are common, tariffs have a disproportionate negative impact on the economy and general welfare.
Late non-numerical entry: Another news item based on not understanding the life cycle of technologies
From Bloomberg (among many others) we learn that there's a new solar energy accumulator technology, and as usual the news write it up as if product deployment at scale is right around the corner, whereas what we have here is a lab testing rig… that's a lot of steps before there's a product at scale. And many of those steps are covered with oubliettes.
