Month: April 2023

  • Another reason to point lights down

    ‘Skyward light, wayward light’, this blog, December 14, 2022:

    One of the simplest ways [to prevent light pollution] is in fact to have no public lighting installation that casts light upward, into the sky, but keeps it all facing down. Doing this will subtract the installation’s contribution to light pollution, improve energy-use efficiency by not ‘wasting’ any light thrown upwards and reduce the power consumed by limiting it to that required to illuminate only what needs to be illuminated, together with surfaces that limit the amount of light scattered upward.

    Add to this…

    ‘Why Are Insects Drawn to Light? A Perennial Question Gets a New Answer.’, New York Times, April 27, 2023:

    A team led by biologists Samuel Fabian at Imperial College London and Yash Sondhi at Florida International University argue that when many insects see a bright light at night, they believe they’ve found the direction of the sky and attempt to orient themselves along an up-and-down axis. …

    The new study also offers a hint of how to mitigate the effect … The research team found that insects seem least affected when they fly under lights that are projected straight down, as opposed to lights that shine upward or that have been mounted horizontally. This finding dovetails with longstanding advice from researchers to limit light pollution by using downward pointing light fixtures that illuminate only the nearby ground

  • The gap between language and quantum mechanics

    Physics World has a fantastic article about the problem with using a language invented, in Terry Pratchett’s words, “to tell other monkeys where the ripe fruit is”, to describe the peculiar but very much real possibilities created by the rules of quantum mechanics. Excerpt:

    … despite the burgeoning growth of quantum technology, one thing that hasn’t changed is the cumbersome and counterintuitive language we use to talk about all things quantum. While the reality of entanglement and superposition is beyond all reasonable doubt, it is as maddening as ever to describe them in words. Quantum phenomena are strange, but that does not mean we should be satisfied with strange language to describe them.

    From the very early days of quantum mechanics, Albert Einstein, Niels Bohr, Werner Heisenberg and others strove to understand this new-fangled non-classical physics of quantum 1.0. Their struggle concerned a gap between how we talk about phenomena and how we encounter them in the laboratory. That gap was created by the imperfect metaphorical language still largely used to characterize non-classical phenomena.

    The authors have written that the terms that writers, journalists, and scientists reach for when describing quantum phenomena to people who don’t have the mathematical awareness (for want of a better description) are probably adding to the confusion instead of clarifying quantum mechanics, and diminishing its realness. ‘Superposition’ is a good example: it’s a word that captures a particular phenomenon, but when you try to spell it out, in toto with no exceptions, to someone who doesn’t understand the math of it, you use some metaphors and approximations that either create an incomplete picture or an obscured one. And both add to quantum physics’s mystery and spookiness, which are counterproductive.

    This has been a familiar challenge in my experience covering high-energy physics as well, were the protagonists are often particles and forces that are best described using mathematical grammar (amplitudes, matrices, groups, etc.) rather than the language that facilitates everyday life. This is why I think the molasses metaphor (and minor variations of it) may well have been the most used of its kind in 2012, when the Higgs boson, and its corresponding energy field, dominated physics news: in the New York Times‘s words, “What is the Higgs field? … It has been described as a kind of cosmic molasses, dragging on particles as they move through it”. In an instructive 2013 paper, Stewart Alsop and Steven Beale wrote (emphasis in the original) about the problems with such metaphors:

    At some point, of course, all analogical thinking breaks down—the Higgs phenomena is not a crowd or molasses. Perhaps a weakness with these analogies is their reliance on a ‘medium’ as the object node mapped to the Higgs field. This is probably unavoidable, but it results in a number of points of potential confusion. The concept of a medium is generally understood to be a volume filled with a physical substance that can be manipulated and controlled. This is not the case in the standard model of the Higgs field, which is understood to be uniform and constant. The familiar conception of a medium is insufficient to fully understand the Higgs field in this respect. A medium can be entered and exited because it is localized, it can be concentrated in one location and minimized in another, and it is composed of matter and has its own mass and energy. Mapping these attributes onto the Higgs field leads to a line of reasoning reminiscent of 19th century aether theories.

    Obviously metaphors aren’t going to be perfect. That’s almost always the case. Instead, they’re handy because they capture a particularly interesting subset of something larger, more complicated, and get that across by drawing on things a person is already familiar with, like, of course, molasses. Through history, this has progressively become harder to do, and scientists themselves have taken note of it from time to time. For example, Werner Heisenberg delivered a speech in 1932, while receiving the Nobel Prize for physics, in which he pointed out the need to discard visualisation or, more accurately, visualisability as a means to unravelling the pending mysteries of atomic physics. He said it quite eloquently, so let me quote him:

    … the path so far traced by the quantum theory indicates that an understanding of those still unclarified features of atomic physics can only be acquired by foregoing visualization and objectification to an extent greater than that customary hitherto. We have probably no reason to regret this, because the thought of the great epistemological difficulties with which the visual atom concept of earlier physics had to contend gives us the hope that the abstracter atomic physics developing at present will one day fit more harmoniously into the great edifice of Science.

    This said, metaphors and analogies vis-à-vis quantum mechanics (getting quantum computing right took considerable effort, for a famous example) have become particularly problematic because this field of study has created technologies that are beginning to enter the public consciousness at large. There is now a greater price to pay by misunderstanding, for example, that quantum teleportation refers to bulk matter, as in Star Trek, rather than to information or, in fact, that entanglement is in Albert Einstein’s words “spooky action at a distance”. But it’s not spooky; it’s just something we don’t have the language for.

    But quantum mechanics and its consequent technologies don’t have a monopoly on being shortchanged by imprecise communication. Climate change is in the same boat. There is also another kind of price that has already been paid across the vast majority of science: a widespread belief among certain (sadly prevalent) groups of people that they understand science when they really don’t, leading to an inflated belief in the abilities and importance of science while overlooking our tendency to confuse faith for truly knowing something. (I have written about this before here, here, and here, among other instances.)

    Finally, the question of the gaps between language as we use it and quantum mechanics is reminiscent of a plot point in China Miéville’s Embassytown, where people designated “ambassadors” can only speak in pairs, simultaneously: each ambassador utters a different word-meaning, and their alien interlocutors combine the duo’s words-meanings to understand what they’re saying. In the book, these two word-meanings are written like a fraction – one word on top, a line in the middle, and the other at the bottom. But thanks to Miéville’s prose, we know that that’s only a partial representation of what’s really going on in the story. We come upon a relatable sensation in the film Arrival.

    Embassytown was a gratifying read that delved into the relationships between language and storytelling as much as between a language, its grammar, and its symbols. Like good fantasy fiction, it steadily yet gently dismantles the cognitive dissonance that reality sometimes foists on us – in this case, that would be cognising why English or for that matter any linear human language will always fall short of describing true simultaneity.

    One workaround, according to the Physics World article above, is that rather than trying to bend our language around the barely tractable and math-laden processes of quantum mechanics, we should describe the field in terms of its outcomes. To know more, do read the article.

  • Where do scientists communicate their work?

    A group of Spanish researchers analysed the mentions of scientific papers authored by scientists (affiliated with Spain) on the social media, on Wikipedia, and on news outlets, blogs and policy documents to understand where the consumers of such scientific information were located. They selected 3,653 authors, and the following platforms/modes in their analysis: Twitter, Facebook (public pages only), Wikipedia citations, news mentions, blogs, and peers (“number of received post-publication review in forums such as PubPeer or Publons”). Per their April 11 arXiv preprint paper:

    • Social science, environment or ecology, clinical medicine, and agricultural sciences papers had good traction on all platforms/modes.
    • Space sciences, geosciences, plant and animal science, biology and biochemistry, molecular biology and genetics, and neuroscience and behaviour had good traction on all platforms/modes except policy reports.
    • Immunology, psychiatry/psychology, microbiology, pharmacology and toxicology, chemistry, physics, engineering, and materials science had moderate traction on all platforms/modes.
    • Of the lot in the point above, immunology found greater mention in “policy reports”, microbiology on Facebook, psychiatry on Wikipedia, and physics in news reports and on blogs.
    • Finally, arts and humanities, mathematics, computer science, and economics and business had the “lowest dissemination” on all these channels.
    • Overall: “social media plays a central role, blogs and news mentions play an intermediate role, and Wikipedia and policy mentions are positioned in the periphery”.

    Clearly a useful study, even if it is limited to authors in/from Spain – something the paper itself neglects to mention until page 7.

    The data for the analysis was retrieved on March 2021, and the papers included were published between 2016 and 2020. I am not sure if 2020 was included; if it was, the papers on microbiology, molecular biology, pharmacology, and immunology could be over-represented in the results, including the last one in “policy reports”.

    Even then the results are valuable because they indicate where the science communicators need to be. I would also be interested where the (Spanish?) misinformation and disinformation in these fields are and whether there is any overlap of channels. (An overlap would be unsurprising if only because false information spreads faster, at least on Twitter.)

    The authors of the study write in conclusion:

    The requirements for defining a communication policy cannot be the same in areas such as Clinical Medicine, which receives great attention from all channels, or Mathematics, which captures less social interest. Likewise, there are scientific fields where a certain channel is particularly relevant. We can conclude that a research dissemination plan or a transfer plan should be adapted to the area in which researchers publish.

  • Games grimy and green

    Every day, I spend an hour or three playing a game called Factorio, in which you mine and process natural resources with which to build and automate ever-larger factories that manufacture materials for research, transport, power, and weapons. Once your factories get big enough (say, when they consume 10 MW), Factorio is less like a game and more like a simulator, and wherein your task is to automate your setup to the extent possible while emitting as little pollution as you can. I currently operate a 120-MW mini-empire of factories, and parts of it are already more complicated than I can describe. The game’s fun lies in being able to optimise your setup across several interacting factors in order to maximise sustainability and efficiency and minimise conflict (which arises due to expansion and pollution). If you like building things that just work, Factorio will ping your reward pathways enough to leave you ecstatic.

    A rocket-manufacturing facility in Factorio.

    This morning, while browsing the web in search of a solution for a problem with one of my factories, I came across a game called Terra Nil. Here, you reclaim a degraded ecosystem by rewatering and re-greening it using machines, leading up – among other things – to completely restoring the land and removing all machines. There are multiple landscape types to begin with, three difficulty levels, and each combination (unless it’s extremely difficult) has no one solution. The best thing for me about Terra Nil, unlike Factorio, is that the visuals accompanying the re-greening process – water flowing anew in once dry channels, wetlands coming to life around a hydroponium, a thunderstorm over young forests – are very soothing on the mind. Also unlike Factorio, pollution is not inevitable in Terra Nil, and Terra Nil also has a design that accentuates the lushness of its scenarios instead of the grimy look that Factorio uses.

    This said, both games are similar to the extent that they incorporate a sci-fi narrative that means, among other things, the technologies in use aren’t realistic, nor do they embody stories about why pollution is bad or ecosystem restoration is good. Put another way, how you narrativise the stories available to tell in each game is up to you. If you’re playing with your children, you can use Factorio to show, say, how quickly pollution builds or Terra Nil to say how expensive cleaning up pollution can be. If you’re playing with India’s Union environment ministry, Factorio can help you see how pollution in one area needn’t affect another and— you get the drift.

    A Terra Nil scenario with an almost completely restored landscape.

    I discovered two more similar games, where the player consumes limited resources in order to build things and achieve some goal, that I hope to try next week: Dyson Sphere Program and Oxygen Not Included.