Monthly Archives: December 2022

Favourite Books of 2022

After last year, I wanted to slow my reading progress and hopefully find more joy in it, rather feeling like a hamster on a wheel. Of course, that’s not really how it turned out. For whatever reason, I flew through quite a few books early in the year and things just went from there.

Like last year, I read a lot of series, so that helps to really stack up the number, and for the most part, I enjoyed them. It does make picking “favourite” books harder though, as you can’t really pick one book from a series as a favourite. I suppose I could pick a series, like I did last year but…

I read a few “classic” sci-fi books this year in Dune and The Peripheral. Interestingly, both have found their way onto a screen, one as (finally!) a very good movie and the other as an Amazon Prime series. The finale of The Peripheral Amazon series was way out there, so while I’m somewhat interested to see where they go with it, I’m not as invested as I was early on. Eagerly waiting Dune part 2.

No real blockbusters I was looking forward to this year, although new books from James Rollins, Steven Konkoly, Jeremy Robinson, and Andrew Mayne were all good. If there was a disappointment among this year’s reads, I would have to say it was Starry Messenger by Neil deGrasse Tyson. I’ve really like some of his earlier work, and while this one was “okay”, it just felt too “both sides ism” for me.

I didn’t read Dennis E. Taylor’s new singleton book, Roadkill? I don’t even know the title, yikes! Bobiverse books 1-3 were still strongly represented though. I’ve even started to write a few posts about the books, trying to explain some of the science. The other thing you may notice is the Pinterest widget/embeds are now gone, replaced by something I coded myself. The Books page now shows all books read every year (instead of only the last 50) and the covers conveniently like to their Amazon Kindle page.

Okay, my favourite books of 2022. Despite being the much smaller percentage of my reading volume, non-fiction titles continue to dominate. I wouldn’t really put any of these books ahead of the other, they are all about the same. The Emerald Mile by Kevin Fedarko was fantastic. It had an unfair advantage as one of the trips I took this year was rafting the Colorado, so this book was such a great setup for that. American Prometheus, by Kai Bird was also great. A bit detailed at times but a very interesting perspective on Oppy. Christoper Nolan is making a movie, Oppenheimer, based on this book, really interested to see how that turns out. Also interesting that Oppenheimer was finally “cleared” of all wrongdoing and/or suspicion this year and issued an apology for his treatment and the stripping of his security clearance in 1954. Finally, Blake Crouch continues to impress, this year with Upgrade. Interesting idea and very interesting perspective.

There you have it. I really don’t want to read over 100 books again next year, I need to savior them, and hopefully remember more of them, although that is probably asking too much. May all your reading dreams for 2023 come true.

Post 1b – Bob’s Trip From Earth to Saturn

I thought I might do a smaller/quicker post about Bob’s trip from Earth to Saturn before he heads out to Epsilon Eridani. Since Bob isn’t moving very fast, no relativistic physics is required, you can get away with go ol’ Newtonian mechanics (kinematics really, we aren’t considering forces here).

The relevant excerpts are:
Chapter 13: Bob – August 17, 2133 – Enroute

“The side trip would take a bit over six days at a constant two-g acceleration”

“I was travelling at over 5000 km/s by the time I reached the second-largest planet in the solar system.”

Excerpts From: We Are Legion (We Are Bob) Copyright © Dennis E. Taylor 2016

The trickiest part of this calculation is to determine the distance from the Earth to Saturn in August of 2133. The Jet Propulsion Lab (JPL) puts out large data sets, called ephemerides, that provide high precision location and motion information for the planets and their moons (among other data). I used DE440, which is the most recent dataset, published in February of 2021. This article in The Astronomical Journal discusses the dataset and is pretty dense. Here’s a download link to DE440 and some other datasets.

Once you have the dataset, you need to figure out how to use it to calculate the data point you are interested in. Fortunately, there is an excellent Python module called Skyfield that makes it very easy to load these datasets and then use them to calculate things like the distance between planets at any given time covered by the dataset.

Here’s the Python code I used to calculate the distance to Saturn for April of 2133:

You need to setup your Python environment properly (with Skyfield installed), after that it should be pretty straight forward. Here’s a link to the code on Github.

The output of the script looks like this:


The distances are measured in astronomical units (AUs) and I ended up just using the last one, 9.893200822811535. The definition of an AU can be found here:

1 AU = 149597870700 meters (m)
9.893200822811535 AU = 1480001777500 m
Here's the setup I use to solve standard kinematics type problems:
d = 1480001777500 m
a = 2g = 2 * 9.80665 = 19.6133 m/s/s
t = ?
vi = 0 m/s
vf = ?

We determined the distance to Saturn for the correct date/time, we are told Bob was accelerating at a constant 2g, and I’m assuming he started from zero initial velocity when leaving Earth. This is not exactly true, as we know Bob was trying to avoid the missiles but we don’t know anything about the actual vectors and speeds involved in that, so this was easiest and won’t have a big impact on the final answer. The kinematics equation that relates d, a, v_i and solves for t is:

(1)   \begin{equation*} d = v_it + \frac{1}{2}at^2 \end{equation*}

Subbing in the values above gives us:

(2)   \begin{equation*} 1480001777500 = (0)t + \frac{1}{2}(19.6133)t^2 \end{equation*}

Solving this for t:

(3)   \begin{equation*} t = \sqrt{\frac{2 * 1480001777500}{19.6133}} \end{equation*}

(4)   \begin{equation*} t = 388481.8925 s \sim 4.5 days \end{equation*}

Here’s the same treatment for the variables d, a, v_i and v_f:

(5)   \begin{equation*} v_f^2 = v_i^2 + 2ad \end{equation*}

Subbing in the values above gives us:

(6)   \begin{equation*} v_f^2 = 0^2 + 2(19.6133)(1480001777500) \end{equation*}

Solving this for v_f:

(7)   \begin{equation*} v_f = \sqrt{2(19.6133)(1480001777500)} \end{equation*}

(8)   \begin{equation*} v_f = 7619411.902 m/s = 7619.4 km/s \end{equation*}

Hmm. While Dennis’ values are certainly in the same ballpark as the ones calculated above, there is some discrepancy. There are any number of explanations as to why that might be, so I’m not going to pick this apart any further.


Here is a plot showing the positions of the planets for the same timeframe (Apr 17, 2133). Not sure if Dennis planned it this way but Saturn is in a pretty favorable position.

NB: The scale for Mercury and Venus is a little janky in order to make the Sun noticeable. Distances are accurate from the Sun’s centre.