# When Things Get Fractally Bad

So.

My country is now an onrushing catastrophe.

One remarkable thing about the disaster unfolding around us is that it has something of a fractal character. Zoom in on a small part of it, and you find the themes of the whole: Endemic sexism and racism; mass media so institutionally rotten they whiff anything important; contempt for science, expertise and basic adulthood maturity… Systemic failures playing out on the grand scale, but also leaving their signatures in the little moment-to-moment moves. Little eddies amid the maelstrom.

A crisis on all scales demands responses at all scales. Here is one action to support, in the small-to-medium range: Don’t let science go down the memory hole!

The safety of US government climate data is at risk. Trump plans to have climate change deniers running every agency concerned with climate change. So, scientists are rushing to back up the many climate databases held by US government agencies before he takes office.

We hope he won’t be rash enough to delete these precious records. But: better safe than sorry!

The Azimuth Climate Data Backup Project is part of this effort. So far our volunteers have backed up nearly 1 terabyte of climate data from NASA and other agencies. We’ll do a lot more! We just need some funds to pay for storage space and a server until larger institutions take over this task.

The project has already met its first funding goal, but more can’t hurt, and it’s open for contributions until 31 January. With more cash on hand, they can “back up more data, create a better interface for getting it, and put more work into making sure it’s error-free and authenticated.”

Just a few weeks ago, we saw a state government try to cover up the science of climate change, and there’s no reason to think that our new federal government will do anything less.

After the 31st, to support helping at larger scales, there’s the American Civil Liberties Union and Planned Parenthood.

# 17 Equations that Clogged My Social-Media Timeline

An image burbled up in my social-media feed the other day, purporting to be a list of “17 Equations that Changed the World.” It’s actually been circulating for a while (since early 2014), and purports to summarize the book by that name written by Ian Stewart. This list is typo-ridden, historically inaccurate and generally indicative of a lousy knowledge-distribution process that lets us down at every stage, from background research to fact-checking to copy-editing.
Continue reading 17 Equations that Clogged My Social-Media Timeline

In the wake of ScienceOnline2011, at which the two sessions I co-moderated went pleasingly well, my Blogohedron-related time and energy has largely gone to doing the LaTeXnical work for this year’s Open Laboratory anthology. I have also made a few small contributions to the Azimuth Project, including a Python implementation of a stochastic Hopf bifurcation model.

I continue to fall behind in writing the book reviews I have promised (to myself, if to nobody else). At ScienceOnline, I scored a free copy of Greg Gbur’s new textbook, Mathematical Methods for Optical Physics and Engineering. Truth be told, at the book-and-author shindig where they had the books written by people attending the conference all laid out and wrapped in anonymizing brown paper, I gauged which one had the proper size and weight for a mathematical-methods textbook and snarfed that. On the logic, you see, that if anyone who was not a physics person drew that book from the pile, they’d probably be sad. (The textbook author was somewhat complicit in this plan.) I am happy to report that I’ve found it a good textbook; it should be useful for advanced undergraduates, procrastinating graduate students and those seeking a clear introduction to techniques used in optics but not commonly addressed in broad-spectrum mathematical-methods books.

# Python Exercise: The Logistic Map

Nostalgi-O-Vision, activate!

A month or so after I was born, my parents bought an Atari 400 game console. It plugged into the television set, and it had a keyboard with no moving keys, intended to be child- and spill-proof. Thanks to the box of cartridges we had beside it, Asteroids and Centipede were burnt into my brain at a fundamental level. The hours I lost blowing up all my own bases in Star Raiders — for which accomplishment the game awarded you the new rank of “garbage scow captain” — I hesitate to reckon. We also had a Basic XL cartridge and an SIO cassette deck, so you could punch in a few TV screens’ worth of code to make, say, the light-cycle game from TRON, and then save your work to an audio cassette tape.

From my vantage point in the twenty-first century, it seems so strange: you could push in a cartridge, close the little door, turn on your TV set and be able to program.

Random fun items currently floating up through the arXivotubes include the following. Exercise: find the shortest science-fiction story which can connect all these e-prints, visiting each node only once.

Robert H. Brandenberger, “String Gas Cosmology” (arXiv:0808.0746).

String gas cosmology is a string theory-based approach to early universe cosmology which is based on making use of robust features of string theory such as the existence of new states and new symmetries. A first goal of string gas cosmology is to understand how string theory can effect the earliest moments of cosmology before the effective field theory approach which underlies standard and inflationary cosmology becomes valid. String gas cosmology may also provide an alternative to the current standard paradigm of cosmology, the inflationary universe scenario. Here, the current status of string gas cosmology is reviewed.

Dimitri Skliros, Mark Hindmarsh, “Large Radius Hagedorn Regime in String Gas Cosmology” (arXiv:0712.1254, to be published in Phys. Rev. D).
The morning’s plenary talks began with Diana Dabby (Franklin W. Olin College of Engineering), who spoke about chaotic transformations one can apply to music in order to generate musical variations, as in “Variations on a Theme of Beethoven.” Her scheme begins by breaking the musical performance into a sequence of pitches, denoted $$p_i$$, and then mapping each $$p_i$$ to a section of a dynamical trajectory on a chaotic attractor like the Lorentz owl/butterfly mask.