EWASS is over and I'm still alive; the 1200-strong horde of barbarous astronomers has been sent back to the hellish netherworld from whence they came. I finally booked my summer holiday to see the total solar eclipse from Grand Teton (hello darkness, bye bye money - also, Expedia seems designed to make the whole process as nerve-inducing as watching a horror movie while receiving random electric shocks). My flat has been restored to something approaching normality. Today we have a scientific visitor hanging around after EWASS. Tonight/early tomorrow morning a friend arrives for a week of holiday and on Wednesday I'm giving a 90 minute public talk.
Wheeee.....
Monday, 3 July 2017
Friday, 30 June 2017
Conference concert
Conference concert in the Rudolphinium. And guess who got to sit dead centre in the third row from the front ? Me, that's who. I win, bitches.
And with that I withdraw once more for one final day of non-stop astronomy...
[I found out later that this was entirely down to luck, as the seats were given out completely at random]
Sunday, 25 June 2017
EWASS begins
EWASS. the European Week of Astronomy and Space Science, has now commenced. For the next week I'll be fighting off the invading horde of 1100 barbarous astronomers and the week after that will be spent recovering. I'll be online, but intermittently.
http://eas.unige.ch/EWASS2017/about.jsp
http://eas.unige.ch/EWASS2017/about.jsp
In Theory
Alternative title : Ten Times Scientists Didn't Use The Word Theory To Mean A Well-Tested Model That's Almost A Fact Because That's Not What The Damn Thing Means So Just Get Over It Already.
Admittedly, I do keep flip-flopping on whether "theory" means, "incredibly well-tested" model or something else. This post should definitively clear that up by making it abundantly clear than everything is much more complicated than that.
Clearly there are some theories which do extraordinarily well - sometimes so well that theory and fact are indistinguishable. It might be fair to start to describe these as laws, not theories - the law of gravity, the law of evolution. Both of these things are established factual processes. Yet even these are like Russian dolls : within them we find detailed theoretical models of how they occur, and within those we find competing hypotheses as to how particular aspects proceed and even rivals to the theory - but not the laws. Gravity is a thing. Evolution happens. It's the mechanisms by which these things occur that's open to debate (at least a little bit), not their very existence.
Even if we were to insist that hypothesis only means, "explanation with little or no testing" (which it does) and theory only means, "well-tested explanation" (which it doesn't), then it wouldn't be easy to distinguish between the two. No strict criteria of what "well tested" means exists. It's probably impossible anyway, given the incredibly diverse nature of theories. You can't equate cat emotions with the distortion of spacetime around a black hole, or at least you shouldn't.
The reality is, though, that the vast majority of theories fall somewhere between these two extremes. They aren't just speculations based on limited data, and they aren't so convincing that no other explanations are plausible. They've had some testing and they generally work, but they have room for improvement. Some of them might turn out to be completely wrong, others just need tweaking.
I'm all for rigorous definitions wherever that's possible and appropriate. But in the case of "theory" I think that neither is the case. The simple truth of the matter is that science isn't always purely objective. It's a murky, messy business of turning facts into models, testing those models, rejecting some while provisionally tolerating others. Pretending that it's more objective than it actually is won't work, because it simply isn't true. Would it be nice if it was ? Sure ! But that's not what it's like, and that murkiness is sometimes what makes it fun.
No definition will stop the most ardent from bullshitting about science, because these people simply do not care - and you can't argue with someone who doesn't care, you can only have shouting matches. But for the rest, let's not set ourselves up for disaster by pretending we know things we do not. Simply admit the plain truth of it - that we know hardly anything for certain, but we're far, far more confident about some things than others. If this leaves people feeling lost and insecure, then that would be a good start. Perhaps (and I say this cautiously, knowing how damaging bullshit and stupidity can be) then they'd stop the chest-thumping for a moment, begin to realise that not everything can be quantified, and actually learn how to think.
https://astrorhysy.blogspot.com/2017/06/in-theory.html https://astrorhysy.blogspot.com/2017/06/in-theory.html
Admittedly, I do keep flip-flopping on whether "theory" means, "incredibly well-tested" model or something else. This post should definitively clear that up by making it abundantly clear than everything is much more complicated than that.
Clearly there are some theories which do extraordinarily well - sometimes so well that theory and fact are indistinguishable. It might be fair to start to describe these as laws, not theories - the law of gravity, the law of evolution. Both of these things are established factual processes. Yet even these are like Russian dolls : within them we find detailed theoretical models of how they occur, and within those we find competing hypotheses as to how particular aspects proceed and even rivals to the theory - but not the laws. Gravity is a thing. Evolution happens. It's the mechanisms by which these things occur that's open to debate (at least a little bit), not their very existence.
Even if we were to insist that hypothesis only means, "explanation with little or no testing" (which it does) and theory only means, "well-tested explanation" (which it doesn't), then it wouldn't be easy to distinguish between the two. No strict criteria of what "well tested" means exists. It's probably impossible anyway, given the incredibly diverse nature of theories. You can't equate cat emotions with the distortion of spacetime around a black hole, or at least you shouldn't.
The reality is, though, that the vast majority of theories fall somewhere between these two extremes. They aren't just speculations based on limited data, and they aren't so convincing that no other explanations are plausible. They've had some testing and they generally work, but they have room for improvement. Some of them might turn out to be completely wrong, others just need tweaking.
I'm all for rigorous definitions wherever that's possible and appropriate. But in the case of "theory" I think that neither is the case. The simple truth of the matter is that science isn't always purely objective. It's a murky, messy business of turning facts into models, testing those models, rejecting some while provisionally tolerating others. Pretending that it's more objective than it actually is won't work, because it simply isn't true. Would it be nice if it was ? Sure ! But that's not what it's like, and that murkiness is sometimes what makes it fun.
No definition will stop the most ardent from bullshitting about science, because these people simply do not care - and you can't argue with someone who doesn't care, you can only have shouting matches. But for the rest, let's not set ourselves up for disaster by pretending we know things we do not. Simply admit the plain truth of it - that we know hardly anything for certain, but we're far, far more confident about some things than others. If this leaves people feeling lost and insecure, then that would be a good start. Perhaps (and I say this cautiously, knowing how damaging bullshit and stupidity can be) then they'd stop the chest-thumping for a moment, begin to realise that not everything can be quantified, and actually learn how to think.
https://astrorhysy.blogspot.com/2017/06/in-theory.html https://astrorhysy.blogspot.com/2017/06/in-theory.html
Saturday, 17 June 2017
Monday, 12 June 2017
Crowdsourced reviewing
Interesting and novel approach. Via Sakari Maaranen.
I am not proposing what is sometimes referred to as crowdsourced reviewing, in which anyone can comment on an openly posted manuscript. I believe that anonymous feedback is more candid, and that confidential submissions give authors space to decide how to revise and publish their work. I envisioned instead a protected platform whereby many expert reviewers could read and comment on submissions, as well as on fellow reviewers’ comments. This, I reasoned, would lead to faster, more-informed editorial decisions.
I recruited just over 100 highly qualified referees, mostly suggested by our editorial board. We worked with an IT start-up company to create a closed online forum and sought authors’ permission to have their submissions assessed in this way. Conventional peer reviewers evaluated the same manuscripts in parallel. After an editorial decision was made, authors received reports both from the crowd discussion and from the conventional reviewers.
This January, we put up two manuscripts simultaneously and gave the crowd 72 hours to respond. Each paper received dozens of comments that our editors considered informative. Taken together, responses from the crowd showed at least as much attention to fine details, including supporting information outside the main article, as did those from conventional reviewers.
So far, we have tried crowd reviewing with ten manuscripts. In all cases, the response was more than enough to enable a fair and rapid editorial decision. Compared with our control experiments, we found that the crowd was much faster (days versus months), and collectively provided more-comprehensive feedback.
https://www.nature.com/news/crowd-based-peer-review-can-be-good-and-fast-1.22072
I am not proposing what is sometimes referred to as crowdsourced reviewing, in which anyone can comment on an openly posted manuscript. I believe that anonymous feedback is more candid, and that confidential submissions give authors space to decide how to revise and publish their work. I envisioned instead a protected platform whereby many expert reviewers could read and comment on submissions, as well as on fellow reviewers’ comments. This, I reasoned, would lead to faster, more-informed editorial decisions.
I recruited just over 100 highly qualified referees, mostly suggested by our editorial board. We worked with an IT start-up company to create a closed online forum and sought authors’ permission to have their submissions assessed in this way. Conventional peer reviewers evaluated the same manuscripts in parallel. After an editorial decision was made, authors received reports both from the crowd discussion and from the conventional reviewers.
This January, we put up two manuscripts simultaneously and gave the crowd 72 hours to respond. Each paper received dozens of comments that our editors considered informative. Taken together, responses from the crowd showed at least as much attention to fine details, including supporting information outside the main article, as did those from conventional reviewers.
So far, we have tried crowd reviewing with ten manuscripts. In all cases, the response was more than enough to enable a fair and rapid editorial decision. Compared with our control experiments, we found that the crowd was much faster (days versus months), and collectively provided more-comprehensive feedback.
https://www.nature.com/news/crowd-based-peer-review-can-be-good-and-fast-1.22072
Monday, 29 May 2017
Attack of the flying space whotsits
After two days, my screen is finally filled with orange stringy sausage thingies. Hurrah for science !
I've been re-examining an old data set, searching for hydrogen streams that may have gone unnoticed. Some known streams are very long indeed - these can't have been missed, because they'd be extremely obvious in the data. But shorter features could be hiding. Bright galaxies are a lot like bright light sources in ordinary photographs - they appear much larger than they actually are. One way to limit this is to plot contours, which show the structure much more clearly than intensity maps. As long as the galaxies aren't too bright, non-circular features in the contours generally show up much more easily than having to carefully try and adjust the contrast of a flux map.
The reason the galaxies look like these long cigar-like blobs is because the third dimension is velocity. We don't have great spatial resolution so generally the galaxies only appear as a circularish blob at any given velocity, occasionally just about resolved into something more interesting. But we have great velocity resolution. Because the galaxies are rotating, this means we detect them at many different velocity channels.
This method seems to be working pretty well : there are 2-3 nice examples of streams that are almost certainly real and maybe a dozen other weaker candidates. None of these would have shown up very clearly in standard maps. And I couldn't have made this figure back when the data first came in - I could have plotted the contours for all 93 galaxies here but it would probably have taken closer to two weeks rather than days.
Falsification just isn't that important
With all this stuff going around about some angry scientists writing a letter to some other angry scientists about how their science isn't really science, I thought I'd take a look at the popular topic of falsification. Being able to disprove your theory is certainly a good thing. You never make a theory worse if it's possible to disprove it. But is it absolutely essential ? I argue, "no" - and we're already in a era when in insisting on the possibility of falsification does more harm than good, at least in astronomy. "That's all there is to it" is, alas, woefully inadequate.
A simplified example : galaxies in very dense regions tend to have smooth, elliptical shapes, while those in less dense regions tend to be spirals and irregulars. We know there are varying processes which can act to change a galaxy's shape, but which one dominates ? We don't even want to try to falsify which ones happen - because we know they all do - it's just a case of establishing which one has the biggest effect. The effects of the different mechanisms are so complex (and observational errors so large) it's possible we could make any of them work, with enough effort. So which method gives the results closest to reality with the least amount of tweaking ? That's the question we try to answer, which has little or nothing to do with falsifying anything.
Here's another example - a computer claims to have proved an obscure mathematical theorem but its proof is far too long for any human to ever read. By necessity, this proof must be based on logical deductions, but if it's too long to check then is it really a proof ? This isn't really all that novel either - throughout history, stupid people have stubbornly refused to accept the proofs that cleverer people have come up with. Does that mean that clever people aren't being scientific if they can't explain their ideas to the mentally deficient ? With science becoming increasingly complex and requiring increasing amounts of time to fully understand, this is a real problem. And if scientists don't even fully understand their results, well...
Really extreme proponents of falsification often tend to be those of the anti-science ilk. Geology, astronomy and anything else which involves deep time, they say, are not really sciences because we can't actually prove anything - no-one left records for billions of years ago for us to check, and we can't wait around to see how galaxies evolve. In a very strict sense, the evolutionary history of life on Earth and the behaviour of stars over cosmic time really can't be falsified.
Such a way of thinking has many parallels with conspiracy theories. It's not that everyone is lying, exactly, it's just that they are demanding impossibly high standards from the evidence which can never be met. By demanding ludicrously high levels of confidence, by refusing to make even the most basic assumptions and give the data some rudimentary level of trust, in short by refusing to even entertain hypothesis for the sake of it, they prevent themselves from learning anything. And they rarely say why they have such confidence in their own senses, which is bizarre given the complexities and many, many demonstrable fallibilities of the human brain.
https://astrorhysy.blogspot.com/2017/05/i-told-you-he-was-tricksy.html
A simplified example : galaxies in very dense regions tend to have smooth, elliptical shapes, while those in less dense regions tend to be spirals and irregulars. We know there are varying processes which can act to change a galaxy's shape, but which one dominates ? We don't even want to try to falsify which ones happen - because we know they all do - it's just a case of establishing which one has the biggest effect. The effects of the different mechanisms are so complex (and observational errors so large) it's possible we could make any of them work, with enough effort. So which method gives the results closest to reality with the least amount of tweaking ? That's the question we try to answer, which has little or nothing to do with falsifying anything.
Here's another example - a computer claims to have proved an obscure mathematical theorem but its proof is far too long for any human to ever read. By necessity, this proof must be based on logical deductions, but if it's too long to check then is it really a proof ? This isn't really all that novel either - throughout history, stupid people have stubbornly refused to accept the proofs that cleverer people have come up with. Does that mean that clever people aren't being scientific if they can't explain their ideas to the mentally deficient ? With science becoming increasingly complex and requiring increasing amounts of time to fully understand, this is a real problem. And if scientists don't even fully understand their results, well...
Really extreme proponents of falsification often tend to be those of the anti-science ilk. Geology, astronomy and anything else which involves deep time, they say, are not really sciences because we can't actually prove anything - no-one left records for billions of years ago for us to check, and we can't wait around to see how galaxies evolve. In a very strict sense, the evolutionary history of life on Earth and the behaviour of stars over cosmic time really can't be falsified.
Such a way of thinking has many parallels with conspiracy theories. It's not that everyone is lying, exactly, it's just that they are demanding impossibly high standards from the evidence which can never be met. By demanding ludicrously high levels of confidence, by refusing to make even the most basic assumptions and give the data some rudimentary level of trust, in short by refusing to even entertain hypothesis for the sake of it, they prevent themselves from learning anything. And they rarely say why they have such confidence in their own senses, which is bizarre given the complexities and many, many demonstrable fallibilities of the human brain.
https://astrorhysy.blogspot.com/2017/05/i-told-you-he-was-tricksy.html
Thursday, 13 April 2017
Plato's groupthink
An early example of groupthink ? You could be forgiven for thinking that Plato is here not only describing groupthink, where individuals tend to want to agree with the group because they're part of a group, but supporting it. In context, it's more subtle than that. He's actually suggesting something profoundly, deceptively tautologous - which sounds crazy, but such is the way of Plato.
What he's saying is that people who agree with each other... agree with each other ! That is, when people disagree, it isn't because they think the other person is correct, it's that they think they're wrong... that in that one, specific instant, they think the other person is less intelligent than they are (or is simply mistaken for some other reason). After all, if you thought that both their reasoning and their information was perfect, you could never disagree with them.
So intelligent, knowledgeable people can and do try to outdo each other because they believe the others are mistaken in some specific regard; merely respecting the overall knowledge and intelligence of others in a similar field does not automatically lead to groupthink at all. Indeed, however flawed the academic system is, its system of competitive collaborations is very good at preventing this. It's perfectly possible to agree and disagree with people on different issues. You don't have to think that someone who believes a single different thing to you is inherently and unconditionally stupid.
Yet the wilfully ignorant insist on believing some absurd absolute version of this : we're all desperately trying to agree with each other while simultaneously dismissing external ideas as crackpottery; that we can attack external ideas but not the group's own. Nothing could be further from the truth - the reason a scientific consensus emerges at all is because it's endured a damn good mauling. If your idea can't stand up to that, then you're asking for double standards. And that's not going to happen.
Which is why if you're reading Plato expecting simple, unquestionable conclusions, you're doing it really wrong.
Tuesday, 4 April 2017
A 3D spiral from ALMA
A little evening's diversion. A few weeks ago there was this ALMA press release (which I came across again today) about observations of the gas around the star LL Pegasi (). It was already fairly famous from Hubble observations thanks to its remarkably neat spiral pattern. The ALMA observations add velocity information and I wanted to see what this would look like in 3D. Actually I've been wondering about this for a while since there was a similar-ish press release about another sort-of similar object some time ago.
For those who aren't familiar with these types of observations, have a look at the gif in the press release first. There you see the data in a slightly more usual format, as a series of images. Each one shows the gas at some particular velocity along our line of sight. What I've done here is use each image as the slice of a 3D cube - it's fun to look at (maybe even useful) but it doesn't show you the true 3D structure of the object.
The last time something similar like this was doing the rounds I couldn't find the original FITS data I needed to display it. This time I didn't bother. I took the gif, converted it into a sequence of png images, then wrote a Python script to convert the image sequence into a FITS cube and then ran it through FRELLED (what else ? http://www.rhysy.net/frelled-1.html). Oh, and I interpolated extra velocity channels because there weren't very many in the gif (there might be more in the original data, I don't know). So there's a fair amount of extra processing for this one, but probably nothing that would result in any serious differences from the raw data.
What does it all mean ? Haven't got a clue, I just thought it would be nice to look at.
Subscribe to:
Posts (Atom)