Books to Read While the Algae Grow in Your Fur, May 2019

Attention conservation notice: I have no taste, and no qualifications to opine on international political economy and the global financial crises of 2008--, social theory, the history of the Roman Empire, or even the history of statistics. Also, I seem to have done a lot of re-reading this month.

Linda Nagata, Vast

Science fiction, rising above the level of mind candy. I read this twenty years ago, and re-read it this spring because the sequel has, at last, come out. It's just as good as I recalled at conveying the sense of wonder and desolation, the scale and age and strangeness of the universe. What my memory hadn't retained was how Nagata combines both an unsparing, utterly unsentimental narration with many genuinely affecting --- I hesitate to say "human" --- experiences. (That last might be because I am now middle aged, rather than in the prolonged adolescence of graduate school, and have more basis on which to relate to those moments.) Also, the moments of horror are a lot more effectively horrifying than I recalled. But if I try to go further in this line I will merely repeat what Henry said, only less eloquently. I will just say that this deserves to be a classic of science fiction, and that if you like well-written hard (*) SF, you owe it to yourself to read this.

*: As for the hardness of the SF, Nagata doesn't play any tricks with special relativity; the closest she comes is a slower-than-light drive that effectively tilts gravity locally. (This would of course have interesting general-relativistic implications.) Drexler-style molecular nanotechnology and mind-uploading are big parts of the book, and there are of course disputes over whether those are scientifically viable, but I am inclined to accept them as "very difficult but not flat-out impossible". This makes the book harder SF than pretty much all of Niven and a good deal of Egan.

While on this subject: Henry describes Vast's "philosopher cells" as "cellular automata turned lethal". I am prepared to go further --- I'm pretty sure Nagata was directly inspired by popular accounts (perhaps in Levy's Artificial Life, or Poundstone's [also-ought-to-be-a-classic] Recursive Universe) of cellular automata as distributed, self-reproducing systems. Indeed, some aspects of her depictions of Lot's attempts to sway the philosopher cells make me think that she played around with CA simulators. On the other hand, I think her depictions of evolutionary design derive from Drexler's Engines of Creation, rather than, say, SFI's Evolving Cellular Automata Project or even John Holland.

Robyn Bennis, The Devil's Guide to Managing Difficulty People

Mind candy: contemporary comic fantasy, featuring central Florida, Boston, and Hell. (Obvious jokes are obvious, and made in the book.)

Judy L. Klein, Statistical Visions in Time: A History of Time Series Analysis, 1662--1938

While it's 20 years old now, I'm not aware of anything which can really replace or even complement it as a history of the development of time series up to the self-conscious introduction of the ideas of stationary stochastic processes and the Wold decomposition. I recommend it unreservedly for anyone seriously interested in time series analysis.

There are two parts. Part I looks at the roots of common time series techniques in non-scientific mathematical practice, especially in business and finance. This includes things like differencing series; using index numbers and looking at relative changes; moving averages; transposing series into "cycle time" and averaging to extract typical seasonal (or longer-term) patterns; etc. In each case, Klein documents a progression from "commercial arithmetic" or "political arithmetic" to, gradually, the use of these techniques for scientific investigation. (There are some demi-Marxist hints here about social structure controlling what people are able to perceive. Klein does not follow up on these hints, which is just as well.)

Part II traces the path through which statistical and probabilistic concepts which were originally developed for looking at cross-sections through a population at one time, such as probability distributions (especially the Gaussian distribution), correlat