Does Newton’s Constant Vary?

This title is an example of what has come to be called Betteridge’s law. This is a relatively recent name for an old phenomenon: if a title is posed as a question, the answer is no. This is especially true in science, whether the authors are conscious of it or not.

Pengfei Li completed his Ph.D. recently, fitting all manner of dark matter halos as well as the radial acceleration relation (RAR) to galaxies in the SPARC database. For the RAR, he found that galaxy data were consistent with a single, universal acceleration scale, g₊. There is of course scatter in the data, but this appears to us to be consistent with what we expect from variation in the mass-to-light ratios of stars and the various uncertainties in the data.

This conclusion has been controversial despite being painfully obvious. I have my own law for data interpretation in astronomy:

Obvious results provoke opposition. The more obvious the result, the stronger the opposition.
S. McGaugh, 1997

The constancy of the acceleration scale is such a case. Where we do not believe we can distinguish between galaxies, others think they can – using our own data! Here it is worth contemplating what all is involved in building a database like SPARC – we were the ones who did the work, after all. In the case of the photometry, we observed the galaxies, we reduced the data, we cleaned the images of foreground contaminants (stars), we fit isophotes, we built mass models – that’s a very short version of what we did in order to be able to estimate the acceleration predicted by Newtonian gravity for the observed distribution of stars. That’s one axis of the RAR. The other is the observed acceleration, which comes from rotation curves, which require even more work. I will spare you the work flow; we did some galaxies ourselves, and took others from the literature in full appreciation of what we could and could not believe — which we have a deep appreciation for because we do the same kind of work ourselves. In contrast, the people claiming to find the opposite of what we find obtained the data by downloading it from our website. The only thing they do is the very last step in the analysis, making fits with Bayesian statistics the same as we do, but in manifest ignorance of the process by which the data came to be. This leads to an underappreciation of the uncertainty in the uncertainties.

This is another rule of thumb in science: outside groups are unlikely to discover important things that were overlooked by the group that did the original work. An example from about seven years ago was the putative 126 GeV line in Fermi satellite data. This was thought by some at the time to be evidence for dark matter annihilating into gamma rays with energy corresponding to the rest mass of the dark matter particles and their anti-particles. This would be a remarkable, Nobel-winning discovery, if true. Strange then that the claim was not made by the Fermi team themselves. Did outsiders beat them to the punch with their own data? It can happen: sometimes large collaborations can be slow to move on important results, wanting to vet everything carefully or warring internally over its meaning while outside investigators move more swiftly. But it can also be that the vetting shows that the exciting result is not credible.

I recall the 126 GeV line being a big deal. There was an entire session devoted to it at a conference I was scheduled to attend. Our time is valuable: I can’t go to every interesting conference, and don’t want to spend time on conferences that aren’t interesting. I was skeptical, simply because of the rule of thumb. I wrote the organizers, and asked if they really thought that this would still be a thing by the time the conference happened in few months’ time. Some of them certainly thought so, so it went ahead. As it happened, it wasn’t. Not a single speaker who was scheduled to talk about the 126 GeV line actually did so. In a few short months, if had gone from an exciting result sure to win a Nobel prize to nada.

What 126 GeV line? Did I say that? I don’t recall saying that.

This happens all the time. Science isn’t as simple as a dry table of numbers and error bars. This is especially true in astronomy, where we are observing objects in the sky. It is never possible to do an ideal experiment in which one controls for all possible systematics: the universe is not a closed box in which we can control the conditions. Heck, we don’t even know what all the unknowns are. It is a big friggin’ universe.

The practical consequence of this is that the uncertainty in any astronomical measurement is almost always larger than its formal error bar. There are effects we can quantify and include appropriately in the error assessment. There are things we can not. We know they’re there, but that doesn’t mean we can put a meaningful number on them.

Indeed, the sociology of this has evolved over the course of my career. Back in the day, everybody understood these things, and took the stated errors with a grain of salt. If it was important to estimate the systematic uncertainty, it was common to estimate a wide band, in effect saying “I’m pretty sure it is in this range.” Nowadays, it has become common to split out terms for random and systematic error. This is helpful to the non-specialist, but it can also be misleading because, so stated, the confidence interval on the systematic looks like a 1 sigma error even though it is not likely to have a Gaussian distribution. Being 3 sigma off of the central value might be a lot more likely than this implies — or a lot less.

People have become more careful in making error estimates, which ironically has made matters worse. People seem to think that they can actually believe the error bars. Sometimes you can, but sometimes not. Many people don’t know how much salt to take it with, or realize that they should take it with a grain of salt at all. Worse, more and more folks come over from particle physics where extraordinary accuracy is the norm. They are completely unprepared to cope with astronomical data, or even fully process that the error bars may not be what they think they are. There is no appreciation for the uncertainties in the uncertainties, which is absolutely fundamental in astrophysics.

Consequently, one gets overly credulous analyses. In the case of the RAR, a number of papers have claimed that the acceleration scale isn’t constant. Not even remotely! Why do they make this claim?

Below is a histogram of raw acceleration scales from SPARC galaxies. In effect, they are claiming that they can tell the difference between galaxies in the tail on one side of the histogram from those on the opposite side. We don’t think we can, which is the more conservative claim. The width of the histogram is just the scatter that one expects from astronomical data, so the data are consistent with zero intrinsic scatter. That’s not to say that’s necessarily what Nature is doing: we can never measure zero scatter, so it is always conceivable that there is some intrinsic variation in the characteristic acceleration scale. All we can say is that if is there, it is so small that we cannot yet resolve it.

Histogram of the acceleration scale in individual galaxies g₊ relative the characteristic value a₀.

Posed as a histogram like this, it is easy to see that there is a characteristic value – the peak – with some scatter around it. The entire issue it whether that scatter is due to real variation from galaxy to galaxy, or if it is just noise. One way to check this is to make quality cuts: in the plot above, the gray-striped histogram plots every available galaxy. The solid blue one makes some mild quality cuts, like knowing the distance to better than 20%. That matters, because the acceleration scale is a quantity that depends on distance – a notoriously difficult quantity to measure accurately in astronomy. When this quality cut is imposed, the width of the histogram shrinks. The better data make a tighter histogram – just as one would expect if the scatter is due to noise. If instead the scatter is a real, physical effect, it should, if anything, be more pronounced in the better data.

This should not be difficult to understand. And yet – other representations of the data give a different impression, like this one:

Best-fit accelerations from Marra et al. (2020).

This figure tells a very different story. The characteristic acceleration does not just scatter around a universal value. There is a clear correlation from one end of the plot to the other. Indeed, it is a perfectly smooth transition, because “Galaxy” is the number of each galaxy ordered by the value of its acceleration, from lowest to highest. The axes are not independent, they represent identically the same quantity. It is a plot of x against x. If properly projected it into a histogram, it would look like the one above.

This is a terrible way to plot data. It makes it look like there is a correlation where there is none. Setting this aside, there is a potential issue with the most discrepant galaxies – those at either extreme. There are more points that are roughly 3 sigma from a constant value than there should be for a sample this size. If this is the right assessment of the uncertainty, then there is indeed some variation from galaxy to galaxy. Not much, but the galaxies at the left hand side of the plot are different from those on the right hand side.

But can we believe the formal uncertainties that inform this error analysis? If you’ve read this far, you will anticipate that the answer to this question obeys Betteridge’s law. No.

One of the reasons we can’t just assign confidence intervals and believe them like a common physicist is that there are other factors in the analysis – nuisance parameters in Bayesian verbiage – with which the acceleration scale covaries. That’s a fancy way of saying that if we turn one knob, it affects another. We assign priors to the nuisance parameters (e.g., the distance to each galaxy and its inclination) based on independent measurements. But there is still some room to slop around. The question is really what to believe at the end of the analysis. We don’t think we can distinguish the acceleration scale from one galaxy to another, but this other analysis says we should. So which is it?

It is easy at this point to devolve into accusations of picking priors to obtain a preconceived result. I don’t think anyone is doing that. But how to show it?

Pengfei had the brilliant idea to perform the same analysis as Marra et al., but allowing Newton’s constant to vary. This is Big G, a universal constant that’s been known to be a constant of nature for centuries. It surely does not vary. However, G appears in our equations, so we can test for variation therein. Pengfei did this, following the same procedure as Mara et al., and finds the same kind of graph – now for G instead of g₊.

Best fit values of Newton’s constant from Li et al (2021).

You see here the same kind of trend for Newton’s constant as one sees above for the acceleration scale. The same data have been analyzed in the same way. It has also been plotted in the same way, giving the impression of a correlation where there is none. The result is also the same: if we believe the formal uncertainties, the best-fit G is different for the galaxies at the left than from those to the right.

I’m pretty sure Newton’s constant does not vary this much. I’m entirely sure that the rotation curve data we analyze are not capable of making this determination. It would be absurd to claim so. The same absurdity extends to the acceleration scale g₊. If we don’t believe the variation in G, there’s no reason to believe that in g₊.

So what is going on here? It boils down to the errors on the rotation curves not representing the uncertainty in the circular velocity as we would like for them to. There are all sorts of reasons for this, observational, physical, and systematic. I’ve written about this at great lengths elsewhere, and I haven’t the patience to do so again here. it is turgidly technical to the extent that even the pros don’t read it. It boils down to the ancient, forgotten wisdom of astronomy: you have to take the errors with a grain of salt.

Here is the cumulative distribution (CDF) of reduced chi squared for the plot above.

Cumulative distribution of reduced chi-squared for different priors on Newton’s constant.

Two things to notice here. First, the CDF looks the same regardless of whether we let Newton’s constant vary or not, or how we assign the Bayesian priors. There’s no value added in letting it vary – just as we found for the characteristic acceleration scale in the first place. Second, the reduced chi squared is rarely close to one. It should be! As a goodness of fit measure, one claims to have a good fit when chi squared equal to one. The majority of these are not good fits! Rather than the gradual slope we see here, the CDF of chi squared should be a nearly straight vertical line. That’s nothing like what we see.

If one interprets this literally, there are many large chi squared values well in excess of unity. These are bad fits, and the model should be rejected. That’s exactly what Rodrigues et al. (2018) found, rejecting the constancy of the acceleration scale at 10 sigma. By their reasoning, we must also reject the constancy of Newton’s constant with the same high confidence. That’s just silly.

One strange thing: the people complaining that the acceleration scale is not constant are only testing that hypothesis. Their presumption is that if the data reject that, it falsifies MOND. The attitude is that this is an automatic win for dark matter. Is it? They don’t bother checking.

We do. We can do the same exercise with dark matter. We find the same result. The CDF looks the same; there are many galaxies with chi squared that is too large.

CDF of rotation curve fits with various types of dark matter halos. None provide a satisfactory fit (as indicated by chi squared) to all galaxies.

Having found the same result for dark matter halos that we found for the RAR, if we apply the same logic, then all proposed model halos are excluded. There are too many bad fits with overly large chi squared.

We have now ruled out all conceivable models. Dark matter is falsified. MOND is falsified. Nothing works. Look on these data, ye mighty, and despair.

But wait! Should we believe the error bars that lead to the end of all things? What would Betteridge say?

Here is the rotation curve of DDO 170 fit with the RAR. Look first at the left box, with the data (points) and the fit (red line). Then look at the fit parameters in the right box.

RAR fit to the rotation curve of DDO 170 (left) with fit parameters at right.

Looking at the left panel, this is a good fit. The line representing the model provides a reasonable depiction of the data.

Looking at the right panel, this is a terrible fit. The reduced chi squared is 4.9. That’s a lot larger than one! The model is rejected with high confidence.

Well, which is it? Lots of people fall into the trap of blindly trusting statistical tests like chi squared. Statistics can only help your brain. They can’t replace it. Trust your eye-brain. This is a good fit. Chi squared is overly large not because this is a bad model but because the error bars are too small. The absolute amount by which the data “miss” is just a few km/s. This is not much by the standards of galaxies, and could easily be explained by a small departure of the tracer from a purely circular orbit – a physical effect we expect at that level. Or it could simply be that the errors are underestimated. Either way, it isn’t a big deal. It would be incredibly naive to take chi squared at face value.

If you want to see a dozen plots like this for all the various models fit to each of over a hundred galaxies, see Li et al. (2020). The bottom line is always the same. The same galaxies are poorly fit by any model — dark matter or MOND. Chi squared is too big not because all conceivable models are wrong, but because the formal errors are underestimated in many cases.

This comes as no surprise to anyone with experience working with astronomical data. We can work to improve the data and the error estimation – see, for example, Sellwood et al (2021). But we can’t blindly turn the crank on some statistical black box and expect all the secrets of the universe to tumble out onto a silver platter for our delectation. There’s a little more to it than that.

Oh… you don’t want to look in there

This post is a recent conversation with David Garofalo for his blog.

Today we talk to Dr. Stacy McGaugh, Chair of the Astronomy Department at Case Western Reserve University.

David: Hi Stacy. You had set out to disprove MOND and instead found evidence to support it. That sounds like the poster child for how science works. Was praise forthcoming?

Stacy: In the late 1980s and into the 1990s, I set out to try to understand low surface brightness galaxies. These are diffuse systems of stars and gas that rotate like the familiar bright spirals, but whose stars are much more spread out. Why? How did these things come to be? Why were they different from brighter galaxies? How could we explain their properties? These were the problems I started out working on that inadvertently set me on a collision course with MOND.

I did not set out to prove or disprove either MOND or dark matter. I was not really even aware of MOND at that time. I had head of it only on a couple of occasions, but I hadn’t payed any attention, and didn’t really know anything about it. Why would I bother? It was already well established that there had to be dark matter.

I worked to develop our understanding of low surface brightness galaxies in the context of dark matter. Their blue colors, low metallicities, high gas fractions, and overall diffuse nature could be explained if they had formed in dark matter halos that are themselves lower than average density: they occupy the low concentration side of the distribution of dark matter halos at a given mass. I found this interpretation quite satisfactory, so gave me no cause to doubt dark matter to that point.

This picture made two genuine predictions that had yet to be tested. First, low surface brightness galaxies should be less strongly clustered than brighter galaxies. Second, having their mass spread over a larger area, they should shift off of the Tully-Fisher relation defined by denser galaxies. The first prediction came true, and for a period I was jubilant that we had made an important new contribution to out understanding of both galaxies and dark matter. The second prediction failed badly: low surface brightness galaxies adhere to the same Tully-Fisher relation that other galaxies follow.

I tried desperately to understand the failure of the second prediction in terms of dark matter. I tried what seemed like a thousand ways to explain this, but ultimately they were all tautological: I could only explain it if I assumed the answer from the start. The adherence of low surface brightness galaxies to the Tully-Fisher relation poses a serious fine-tuning problem: the distribution of dark matter must be adjusted to exactly counterbalance that of the visible matter so as not to leave any residuals. This makes no sense, and anyone who claims it does is not thinking clearly.

It was in this crisis of comprehension in which I became aware that MOND predicted exactly what I was seeing. No fine-tuning was required. Low surface brightness galaxies followed the same Tully-Fisher relation as other galaxies because the modified force law stipulates that they must. It was only at this point (in the mid-’90s) at which I started to take MOND seriously. If it had got this prediction right, what else did it predict?

I was still convinced that the right answer had to be dark matter. There was, after all, so much evidence for it. So this one prediction must be a fluke; surely it would fail the next test. That was not what happened: MOND passed test after test after test, successfully predicting observations both basic and detailed that dark matter theory got wrong or did not even address. It was only after this experience that I realized that what I thought was evidence for dark matter was really just evidence that something was wrong: the data cannot be explained with ordinary gravity without invisible mass. The data – and here I mean ALL the data – were mostly ambiguous: they did not clearly distinguish whether the problem was with mass we couldn’t see or with the underlying equations from which we inferred the need for dark matter.

So to get back to your original question, yes – this is how science should work. I hadn’t set out to test MOND, but I had inadvertently performed exactly the right experiment for that purpose. MOND had its predictions come true where the predictions of other theories did not: both my own theory and those of others who were working in the context of dark matter. We got it wrong while MOND got it right. That led me to change my mind: I had been wrong to be sure the answer had to be dark matter, and to be so quick to dismiss MOND. Admitting this was the most difficult struggle I ever faced in my career.

David: From the perspective of dark matter, how does one understand MOND’s success?

Stacy: One does not.

That the predictions of MOND should come true in a universe dominated by dark matter makes no sense.

Before I became aware of MOND, I spent lots of time trying to come up with dark matter-based explanations for what I was seeing. It didn’t work. Since then, I have continued to search for a viable explanation with dark matter. I have not been successful. Others have claimed such success, but whenever I look at their work, it always seems that what they assert to be a great success is just a specific elaboration of a model I had already considered and rejected as obviously unworkable. The difference boils down to Occam’s razor. If you give dark matter theory enough free parameters, it can be adjusted to “predict” pretty much anything. But the best we can hope to do with dark matter theory is to retroactively explain what MOND successfully predicted in advance. Why should we be impressed by that?

David: Does MOND fail in clusters?

Stacy: Yes and no: there are multiple tests in clusters. MOND passes some and flunks others – as does dark matter.

The most famous test is the baryon fraction. This should be one in MOND – all the mass is normal baryonic matter. With dark matter, it should be the cosmic ratio of normal to dark matter (about 1:5).

MOND fails this test: it explains most of the discrepancy in clusters, but not all of it. The dark matter picture does somewhat better here, as the baryon fraction is close to the cosmic expectation — at least for the richest clusters of galaxies. In smaller clusters and groups of galaxies, the normal matter content falls short of the cosmic value. So both theories suffer a “missing baryon” problem: MOND in rich clusters; dark matter in everything smaller.

Another test is the mass-temperature relation. Both theories predict a relation between the mass of a cluster and the temperature of the gas it contains, but they predict different slopes for this relation. MOND gets the slope right but the amplitude wrong, leading to the missing baryon problem above. Dark matter gets the amplitude right for the most massive clusters, but gets the slope wrong – which leads to it having a missing baryon problem for systems smaller than the largest clusters.

There are other tests. Clusters continue to merge; the collision velocity of merging clusters is predicted to be higher in MOND than with dark matter. For example, the famous bullet cluster, which is often cited as a contradiction to MOND, has a collision speed that is practically impossible with dark matter: there just isn’t enough time for the two components of the bullet to accelerate up to the observed relative speed if they fall together under the influence of normal gravity and the required amount of dark mass. People have argued over the severity of this perplexing problem, but the high collision speed happens quite naturally in MOND as a consequence of its greater effective force of attraction. So, taken at face value, the bullet cluster both confirms and refutes both theories!

I could go on… one expects clusters to form earlier and become more massive in MOND than in dark matter. There are some indications that this is the case – the highest redshift clusters came as a surprise to conventional structure formation theory – but the relative numbers of clusters as a function of mass seems to agree well with current expectations with dark matter. So clusters are a mixed bag.

More generally, there is a widespread myth that MOND fits rotation curves, but gets nothing else right. This is what I expected to find when I started fact checking, but the opposite is true. MOND explains a huge variety of data well. The presumptive superiority of dark matter is just that – a presumption.

David: At a physics colloquium two decades ago, Vera Rubin described how theorists were willing and eager to explain her data to her. At an astronomy colloquium a few years later, you echoed that sentiment in relation to your data on velocity curves. One concludes that theorists are uniquely insightful and generous people. Is there anyone you would like to thank for putting you straight?

Stacy: So they perceive themselves to be.

MOND has made many successful a priori predictions. This is the golden standard of the scientific method. If there is another explanation for it, I’d like to know what it is.

As your questions supposes, many theorists have offered such explanations. At most one of them can be correct. I have yet to hear a satisfactory explanation.

David: What are MOND people working on these days?

Stacy: Any problem that is interesting in extragalactic astronomy is interesting in the context of MOND. Outstanding questions include planes of satellite dwarf galaxies, clusters of galaxies, the formation of large scale structure, and the microwave background. MOND-specific topics include the precise value of the MOND acceleration constant, predicting the velocity dispersions of dwarf galaxies, and the search for the predicted external field effect, which is a unique signature of MOND.

The phrasing of this question raises a sociological issue. I don’t know what a “MOND person” is. Before now, I have only heard it used as a pejorative.

I am a scientist who has worked on many topics. MOND is just one of them. Does that make me a “MOND person”? I have also worked on dark matter, so am I also a “dark matter person”? Are these mutually exclusive?

I have attended conferences where I have heard people say ‘“MOND people” do this’ or ‘“MOND people” fail to do that.’ Never does the speaker of these words specify who they’re talking about: “MOND people” are a nameless Other. In all cases, I am more familiar with the people and the research they pretend to describe, but in no way do I recognize what they’re talking about. It is just a way of saying “Those People” are Bad.

There are many experts on dark matter in the world. I am one of them. There are rather fewer experts on MOND. I am also one of them. Every one of these “MOND people” is also an expert on dark matter. This situation is not reciprocated: many experts on dark matter are shockingly ignorant about MOND. I was once guilty of that myself, but realized that ignorance is not a sound basis on which to base a scientific judgement.

David: Are you tired of getting these types of questions?

Stacy: Yes and no.

No, in that these are interesting questions about fundamental science. That is always fun to talk about.

Yes, in that I find myself having the same arguments over and over again, usually with scientists who remain trapped in the misconceptions I suffered myself a quarter century ago, but whose minds are closed to ideas that threaten their sacred cows. If dark matter is a real, physical substance, then show me a piece already.

Cosmology, then and now

I have been busy teaching cosmology this semester. When I started on the faculty of the University of Maryland in 1998, there was no advanced course on the subject. This seemed like an obvious hole to fill, so I developed one. I remember with fond bemusement the senior faculty, many of them planetary scientists, sending Mike A’Hearn as a stately ambassador to politely inquire if cosmology had evolved beyond a dodgy subject and was now rigorous enough to be worthy of a 3 credit graduate course.

Back then, we used transparencies or wrote on the board. It was novel to have a course web page. I still have those notes, and marvel at the breadth and depth of work performed by my younger self. Now that I’m teaching it for the first time in a decade, I find it challenging to keep up. Everything has to be adapted to an electronic format, and be delivered remotely during this damnable pandemic. It is a less satisfactory experience, and it has precluded posting much here.

Another thing I notice is that attitudes have evolved along with the subject. The baseline cosmology, LCDM, has not changed much. We’ve tilted the power spectrum and spiked it with extra baryons, but the basic picture is that which emerged from the application of classical observational cosmology – measurements of the Hubble constant, the mass density, the ages of the oldest stars, the abundances of the light elements, number counts of faint galaxies, and a wealth of other observational constraints built up over decades of effort. Here is an example of combining such constraints, and exercise I have students do every time I teach the course:

Observational constraints in the mass density-Hubble constant plane assembled by students in my cosmology course in 2002. The gray area is excluded. The open window is the only space allowed; this is LCDM. The box represents the first WMAP estimate in 2003. CMB estimates have subsequently migrated out of the allowed region to lower H0 and higher mass density, but the other constraints have not changed much, most famously H0, which remains entrenched in the low to mid-70s.

These things were known by the mid-90s. Nowadays, people seem to think Type Ia SN discovered Lambda, when really they were just icing on a cake that was already baked. The location of the first peak in the acoustic power spectrum of the microwave background was corroborative of the flat geometry required by the picture that had developed, but trailed the development of LCDM rather than informing its construction. But students entering the field now seem to have been given the impression that these were the only observations that mattered.

Worse, they seem to think these things are Known, as if there’s never been a time that we cosmologists have been sure about something only to find later that we had it quite wrong. This attitude is deleterious to the progress of science, as it precludes us from seeing important clues when they fail to conform to our preconceptions. To give one recent example, everyone seems to have decided that the EDGES observation of 21 cm absorption during the dark ages is wrong. The reason? Because it is impossible in LCDM. There are technical reasons why it might be wrong, but these are subsidiary to Attitude: we can’t believe it’s true, so we don’t. But that’s what makes a result important: something that makes us reexamine how we perceive the universe. If we’re unwilling to do that, we’re no longer doing science.

Two fields divided by a common interest

Britain and America are two nations divided by a common language.

attributed to George Bernard Shaw

Physics and Astronomy are two fields divided by a common interest in how the universe works. There is a considerable amount of overlap between some sub-fields of these subjects, and practically none at all in others. The aims and goals are often in common, but the methods, assumptions, history, and culture are quite distinct. This leads to considerable confusion, as with the English language – scientists with different backgrounds sometimes use the same words to mean rather different things.

A few terms that are commonly used to describe scientists who work on the subjects that I do include astronomer, astrophysicist, and cosmologist. I could be described as any of the these. But I also know lots of scientists to whom these words could be applied, but would mean something rather different.

A common question I get is “What’s the difference between an astronomer and an astrophysicist?” This is easy to answer from my experience as a long-distance commuter. If I get on a plane, and the person next to me is chatty and asks what I do, if I feel like chatting, I am an astronomer. If I don’t, I’m an astrophysicist. The first answer starts a conversation, the second shuts it down.

Flippant as that anecdote is, it is excruciatingly accurate – both for how people react (commuting between Cleveland and Baltimore for a dozen years provided lots of examples), and for what the difference is: practically none. If I try to offer a more accurate definition, then I am sure to fail to provide a complete answer, as I don’t think there is one. But to make the attempt:

Astronomy is the science of observing the sky, encompassing all elements required to do so. That includes practical matters like the technology of telescopes and their instruments across all wavelengths of the electromagnetic spectrum, and theoretical matters that allow us to interpret what we see up there: what’s a star? a nebula? a galaxy? How does the light emitted by these objects get to us? How do we count photons accurately and interpret what they mean?

Astrophysics is the science of how things in the sky work. What makes a star shine? [Nuclear reactions]. What produces a nebular spectrum? [The atomic physics of incredibly low density interstellar plasma.] What makes a spiral galaxy rotate? [Gravity! Gravity plus, well, you know, something. Or, if you read this blog, you know that we don’t really know.] So astrophysics is the physics of the objects astronomy discovers in the sky. This is a rather broad remit, and covers lots of physics.

With this definition, astrophysics is a subset of astronomy – such a large and essential subset that the terms can and often are used interchangeably. These definitions are so intimately intertwined that the distinction is not obvious even for those of us who publish in the learned journals of the American Astronomical Society: the Astronomical Journal (AJ) and the Astrophysical Journal (ApJ). I am often hard-pressed to distinguish between them, but to attempt it in brief, the AJ is where you publish a paper that says “we observed these objects” and the ApJ is where you write “here is a model to explain these objects.” The opportunity for overlap is obvious: a paper that says “observations of these objects test/refute/corroborate this theory” could appear in either. Nevertheless, there was a clearly a sufficient need to establish a separate journal focused on the physics of how things in the sky worked to launch the Astrophysical Journal in 1895 to complement the older Astronomical Journal (dating from 1849).

Cosmology is the study of the entire universe. As a science, it is the subset of astrophysics that encompasses observations that measure the universe as a physical entity: its size, age, expansion rate, and temporal evolution. Examples are sufficiently diverse that practicing scientists who call themselves cosmologists may have rather different ideas about what it encompasses, or whether it even counts as astrophysics in the way defined above.

Indeed, more generally, cosmology is where science, philosophy, and religion collide. People have always asked the big questions – we want to understand the world in which we find ourselves, our place in it, our relation to it, and to its Maker in the religious sense – and we have always made up stories to fill in the gaping void of our ignorance. Stories that become the stuff of myth and legend until they are unquestionable aspects of a misplaced faith that we understand all of this. The science of cosmology is far from immune to myth making, and often times philosophical imperatives have overwhelmed observational facts. The lengthy persistence of SCDM in the absence of any credible evidence that Ω_m = 1 is a recent example. Another that comes and goes is the desire for a Phoenix universe – one that expands, recollapses, and is then reborn for another cycle of expansion and contraction that repeats ad infinitum. This is appealing for philosophical reasons – the universe isn’t just some bizarre one-off – but there’s precious little that we know (or perhaps can know) to suggest it is a reality.

battlestar_galactica-last-supper — This has all happened before, and will all happen again.

Nevertheless, genuine and enormous empirical progress has been made. It is stunning what we know now that we didn’t a century ago. It has only been 90 years since Hubble established that there are galaxies external to the Milky Way. Prior to that, the prevailing cosmology consisted of a single island universe – the Milky Way – that tapered off into an indefinite, empty void. Until Hubble established otherwise, it was widely (though not universally) thought that the spiral nebulae were some kind of gas clouds within the Milky Way. Instead, the universe is filled with millions and billions of galaxies comparable in stature to the Milky Way.

We have sometimes let our progress blind us to the gaping holes that remain in our knowledge. Some of our more imaginative and less grounded colleagues take some of our more fanciful stories to be established fact, which sometimes just means the problem is old and familiar so boring if still unsolved. They race ahead to create new stories about entities like multiverses. To me, multiverses are manifestly metaphysical: great fun for late night bull sessions, but not a legitimate branch of physics.

So cosmology encompasses a lot. It can mean very different things to different people, and not all of it is scientific. I am not about to touch on the world-views of popular religions, all of which have some flavor of cosmology. There is controversy enough about these definitions among practicing scientists.

I started as a physicist. I earned an SB in physics from MIT in 1985, and went on to the physics (not the astrophysics) department of Princeton for grad school. I had elected to study physics because I had a burning curiosity about how the world works. It was not specific to astronomy as defined above. Indeed, astronomy seemed to me at the time to be but one of many curiosities, and not necessarily the main one.

There was no clear department of astronomy at MIT. Some people who practiced astrophysics were in the physics department; others in Earth, Atmospheric, and Planetary Science, still others in Mathematics. At the recommendation of my academic advisor Michael Feld, I wound up doing a senior thesis with George W. Clark, a high energy astrophysicist who mostly worked on cosmic rays and X-ray satellites. There was a large high energy astrophysics group at MIT who studied X-ray sources and the physics that produced them – things like neutron stars, black holes, supernova remnants, and the intracluster medium of clusters of galaxies – celestial objects with sufficiently extreme energies to make X-rays. The X-ray group needed to do optical follow-up (OK, there’s an X-ray source at this location on the sky. What’s there?) so they had joined the MDM Observatory. I had expressed a vague interest in orbital dynamics, and Clark had become interested in the structure of elliptical galaxies, motivated by the elegant orbital structures described by Martin Schwarzschild. The astrophysics group did a lot of work on instrumentation, so we had access to a new-fangled CCD. These made (and continue to make) much more sensitive detectors than photographic plates.

Empowered by this then-new technology, we embarked on a campaign to image elliptical galaxies with the MDM 1.3 m telescope. The initial goal was to search for axial twists as the predicted consequence of triaxial structure – Schwarzschild had shown that elliptical galaxies need not be oblate or prolate, but could have three distinct characteristic lengths along their principal axes. What we noticed instead with the sensitive CCD was a wonder of new features in the low surface brightness outskirts of these galaxies. Most elliptical galaxies just fade smoothly into obscurity, but every fourth or fifth case displayed distinct shells and ripples – features that were otherwise hard to spot that had only recently been highlighted by Malin & Carter.

Arp227_crop — A modern picture (courtesy of Pierre-Alain Duc) of the shell galaxy Arp 227 (NGC 474). Quantifying the surface brightness profiles of the shells in order to constrain theories for their origin became the subject of my senior thesis. I found that they were most consistent with stars on highly elliptical orbits, as expected from the shredded remnants of a cannibalized galaxy. Observations like this contributed to a sea change in the thinking about galaxies as isolated island universes that never interacted to the modern hierarchical view in which galaxy mergers are ubiquitous.

At the time I was doing this work, I was of course reading up on galaxies in general, and came across Mike Disney’s arguments as to how low surface brightness galaxies could be ubiquitous and yet missed by many surveys. This resonated with my new observing experience. Look hard enough, and you would find something new that had never before been seen. This proved to be true, and remains true to this day.

I went on only two observing runs my senior year. The weather was bad for the first one, clearing only the last night during which I collected all the useful data. The second run came too late to contribute to my thesis. But I was enchanted by the observatory as a remote laboratory, perched in the solitude of the rugged mountains, themselves alone in an empty desert of subtly magnificent beauty. And it got dark at night. You could actually see the stars. More stars than can be imagined by those confined to the light pollution of a city.

It hadn’t occurred to me to apply to an astronomy graduate program. I continued on to Princeton, where I was assigned to work in the atomic physics lab of Will Happer. There I mostly measured the efficiency of various buffer gases in moderating spin exchange between sodium and xenon. This resulted in my first published paper.

In retrospect, this is kinda cool. As an alkali, the atomic structure of sodium is basically that of a noble gas with a spare electron it’s eager to give away in a chemical reaction. Xenon is a noble gas, chemically inert as it already has nicely complete atomic shells; it wants neither to give nor receive electrons from other elements. Put the two together in a vapor, and they can form weak van der Waals molecules in which they share the unwanted valence electron like a hot potato. The nifty thing is that one can spin-polarize the electron by optical pumping with a laser. As it happens, the wave function of the electron has a lot of overlap with the nucleus of the xenon (one of the allowed states has no angular momentum). Thanks to this overlap, the spin polarization imparted to the electron can be transferred to the xenon nucleus. In this way, it is possible to create large amounts of spin-polarized xenon nuclei. This greatly enhances the signal of MRI, and has found an application in medical imaging: a patient can breathe in a chemically inert [SAFE], spin polarized noble gas, making visible all the little passageways of the lungs that are otherwise invisible to an MRI. I contributed very little to making this possible, but it is probably the closest I’ll ever come to doing anything practical.

The same technology could, in principle, be applied to make dark matter detection experiments phenomenally more sensitive to spin-dependent interactions. Giant tanks of xenon have already become one of the leading ways to search for WIMP dark matter, gobbling up a significant fraction of the world supply of this rare noble gas. Spin polarizing the xenon on the scales of tons rather than grams is a considerable engineering challenge.

Now, in that last sentence, I lapsed into a bit of physics arrogance. We understand the process. Making it work is “just” a matter of engineering. In general, there is a lot of hard work involved in that “just,” and a lot of times it is a practical impossibility. That’s probably the case here, as the polarization decays away quickly – much more quickly than one could purify and pump tons of the stuff into a vat maintained at a temperature near absolute zero.

At the time, I did not appreciate the meaning of what I was doing. I did not like working in Happer’s lab. The windowless confines kept dark but for the sickly orange glow of a sodium D laser was not a positive environment to be in day after day after day. More importantly, the science did not call to my heart. I began to dream of a remote lab on a scenic mountain top.

I also found the culture in the physics department at Princeton to be toxic. Nothing mattered but to be smarter than the next guy (and it was practically all guys). There was no agreed measure for this, and for the most part people weren’t so brazen as to compare test scores. So the thing to do was Be Arrogant. Everybody walked around like they were too frickin’ smart to be bothered to talk to anyone else, or even see them under their upturned noses. It was weird – everybody there was smart, but no human could possible be as smart as these people thought they were. Well, not everybody, of course – Jim Peebles is impossibly intelligent, sane, and even nice (perhaps he is an alien, or at least a Canadian) – but for most of Princeton arrogance was a defining characteristic that seeped unpleasantly into every interaction.

It was, in considerable part, arrogance that drove me away from physics. I was appalled by it. One of the best displays was put on by David Gross in a colloquium that marked the take-over of theoretical physics by string theory. The dude was talking confidently in bold positivist terms about predictions that were twenty orders of magnitude in energy beyond any conceivable experimental test. That, to me, wasn’t physics.

More than thirty years on, I can take cold comfort that my youthful intuition was correct. String theory has conspicuously failed to provide the vaunted “theory of everything” that was promised. Instead, we have vague “landscapes” of 10⁵⁰⁰ possible theories. Just want one. 10⁵⁰⁰ is not progress. It’s getting hopelessly lost. That’s what happens when brilliant ideologues are encouraged to wander about in their hyperactive imaginations without experimental guidance. You don’t get physics, you get metaphysics. If you think that sounds harsh, note that Gross himself takes exactly this issue with multiverses, saying the notion “smells of angels” and worrying that a generation of physicists will be misled down a garden path – exactly the way he misled a generation with string theory.

So I left Princeton, and switched to a field where progress could be made. I chose to go to the University of Michigan, because I knew it had access to the MDM telescopes (one of the M’s stood for Michigan, the other MIT, with the D for Dartmouth) and because I was getting married. My wife is an historian, and we needed a university that was good in both our fields.

When I got to Michigan, I was ready to do research. I wanted to do more on shell galaxies, and low surface brightness galaxies in general. I had had enough coursework, I reckoned; I was ready to DO science. So I was somewhat taken aback that they wanted me to do two more years of graduate coursework in astronomy.

Some of the physics arrogance had inevitably been incorporated into my outlook. To a physicist, all other fields are trivial. They are just particular realizations of some subset of physics. Chemistry is just applied atomic physics. Biology barely even counts as science, and those parts that do could be derived from physics, in principle. As mere subsets of physics, any other field can and will be picked up trivially.

After two years of graduate coursework in astronomy, I had the epiphany that the field was not trivial. There were excellent reasons, both practical and historical, why it was a separate field. I had been wrong to presume otherwise.

Modern physicists are not afflicted by this epiphany. That bad attitude I was guilty of persists and is remarkably widespread. I am frequently confronted by young physicists eager to mansplain my own field to me, who casually assume that I am ignorant of subjects that I wrote papers on before they started reading the literature, and who equate a disagreement with their interpretation on any subject with ignorance on my part. This is one place the fields diverge enormously. In physics, if it appears in a textbook, it must be true. In astronomy, we recognize that we’ve been wrong about the universe so many times, we’ve learned to be tolerant of interpretations that initially sound absurd. Today’s absurdity may be tomorrow’s obvious fact. Physicists don’t share this history, and often fail to distinguish interpretation from fact, much less cope with the possibility that a single set of facts may admit multiple interpretations.

Cosmology has often been a leader in being wrong, and consequently enjoyed a shady reputation in both physics and astronomy for much of the 20th century. When I started on the faculty at the University of Maryland in 1998, there was no graduate course in the subject. This seemed to me to be an obvious gap to fill, so I developed one. Some of the senior astronomy faculty expressed concern as to whether this could be a rigorous 3 credit graduate course, and sent a neutral representative to discuss the issue with me. He was satisfied. As would be any cosmologist – I was teaching LCDM before most other cosmologists had admitted it was a thing.

At that time, 1998, my wife was also a new faculty member at John Carroll University. They held a welcome picnic, which I attended as the spouse. So I strike up a conversation with another random spouse who is also standing around looking similarly out of place. Ask him what he does. “I’m a physicist.” Ah! common ground – what do you work on? “Cosmology and dark matter.” I was flabbergasted. How did I not know this person? It was Glenn Starkman, and this was my first indication that sometime in the preceding decade, cosmology had become an acceptable field in physics and not a suspect curiosity best left to woolly-minded astronomers.

This was my first clue that there were two entirely separate groups of professional scientists who self-identified as cosmologists. One from the astronomy tradition, one from physics. These groups use the same words to mean the same things – sometimes. There is a common language. But like British English and American English, sometimes different things are meant by the same words.

“Dark matter” is a good example. When I say dark matter, I mean the vast diversity of observational evidence for a discrepancy between measurable probes of gravity (orbital speeds, gravitational lensing, equilibrium hydrostatic temperatures, etc.) and what is predicted by the gravity of the observed baryonic material – the stars and gas we can see. When a physicist says “dark matter,” he seems usually to mean the vast array of theoretical hypotheses for what new particle the dark matter might be.

To give a recent example, a colleague who is a world-reknowned expert on dark matter, and an observational astronomer in a physics department dominated by particle cosmologists, noted that their chairperson had advocated a particular hiring plan because “we have no one who works on dark matter.” This came across as incredibly disrespectful, which it is. But it is also simply clueless. It took some talking to work through, but what we think he meant was that they had no one who worked on laboratory experiments to detect dark matter. That’s a valid thing to do, which astronomers don’t deny. But it is a severely limited way to think about it.

To date, the evidence for dark matter to date is 100% astronomical in nature. That’s all of it. Despite enormous effort and progress, laboratory experiments provide 0%. Zero point zero zero zero. And before some fool points to the cosmic microwave background, that is not a laboratory experiment. It is astronomy as defined above: information gleaned from observation of the sky. That it is done with photons from the mm and microwave part of the spectrum instead of the optical part of the spectrum doesn’t make it fundamentally different: it is still an observation of the sky.

And yet, apparently the observational work that my colleague did was unappreciated by his own department head, who I know to fancy himself an expert on the subject. Yet existence of a complementary expert in his own department didn’t ever register him. Even though, as chair, he would be responsible for reviewing the contributions of the faculty in his department on an annual basis.

To many physicists we astronomers are simply invisible. What could we possibly teach them about cosmology or dark matter? That we’ve been doing it for a lot longer is irrelevant. Only what they [re]invent themselves is valid, because astronomy is a subservient subfield populated by people who weren’t smart enough to become particle physicists. Because particle physicists are the smartest people in the world. Just ask one. He’ll tell you.

To give just one personal example of many: a few years ago, after I had published a paper in the premiere physics journal, I had a particle physics colleague ask, in apparent sincerity, “Are you an astrophysicist?” I managed to refrain from shouting YES YOU CLUELESS DUNCE! Only been doing astrophysics for my entire career!

As near as I can work out, his erroneous definition of astrophysicist involved having a Ph.D. in physics. That’s a good basis to start learning astrophysics, but it doesn’t actually qualify. Kris Davidson noted a similar sociology among his particle physics colleagues: “They simply declare themselves to be astrophysicsts.” Well, I can tell you – having made that same mistake personally – it ain’t that simple. I’m pleased that so many physicists are finally figuring out what I did in the 1980s, and welcome their interest in astrophysics and cosmology. But they need to actually learn the subject, just not assume they’ll pick it up in a snap without actually doing so.

Shameless commercialism

I haven’t written here since late January, which not coincidentally was early in the Spring semester. Let’s just say it was… eventful. Mostly in an administrative way, which is neither a good way, nor an interesting way.

Not that plenty interesting hasn’t happened. I had a great visit to Aachen for the conference Dark Matter & Modified Gravity. Lots of emphasis on the philosophy of science, as well as history and sociology. Almost enough to make me think there is hope for the future. Almost. From there I visited CP3 in Odense where I gave both a science talk and a public talk at the Anarkist beer & food lab. It was awesome – spoke to a packed house in a place that was clearly used as a venue for rock concerts most of the time. People actually came out on a crappy night in February and paid a cover to hear about science!

I’d love to simply write my Aachen talk here, or the public Odense talk, and I should, but – writing takes a lot longer than talking. I’m continually amazed at how inefficient human communication is. Writing is painfully slow, and while I go to great lengths to write clearly and compellingly, I don’t always succeed. Even when I do, reading comprehension does not seem to be on an upward trajectory in the internet age. I routinely get accused of ignoring this or that topic by scientists too lazy to do a literature search wherein they would find I had written a paper on that. This has gotten so bad that it is currently a fad to describe as natural a phenomenon I explicitly showed over 20 years ago was the opposite of natural in LCDM. Faith in dark matter overpowers reason.

So many stories to tell, so little time to tell them. Some are positive. But far too many are the sordid sort of human behavior overriding the ideals of science. Self awareness is in short supply, and objectivity seems utterly forgotten as a concept, let alone a virtue. Many scientists no longer seem to appreciate the distinction between an a priori prediction and a post-hoc explanation pulled out of one’s arse when confronted with confounding evidence.

Consequently, I have quite intentionally refrained from ranting about bad scientific behavior too much, mostly in a mistaken but habitual “if you can’t say anything nice” sort of way. Which is another reason I have been quiet of late: I really don’t like to speak ill of my colleagues, even when they deserve it. There is so much sewage masquerading as science that I’m holding my nose while hoping it flows away under the bridge.

So, to divert myself, I have been dabbling in art. I am not a great artist by any means, but I’ve had enough people tell me “I’d buy that!” that I finally decided to take them at their word (silly, I know) and open a Zazzle store. Which immediately wants me to add links to it, which I find myself unprepared to do. I have had an academic website for a long time (since 1996, which is forever in internet years) but it seems really inappropriate to put them there. So I’m putting them here because this is the only place I’ve got readily available.

So the title “shameless commercialism” is quite literal. I hadn’t meant to advertise it here at all. Just find I need a web page, stat! It ain’t like I’ve even had time to stock the store – it is a lot more fun to do science than write it up; similarly, it is a lot more fun to create art than it is to market it. So there is only the one inaugural item so far, an Allosaurus on a T-shirt. Seems to fit the mood of the past semester.

A personal recollection of how we learned to stop worrying and love the Lambda

There is a tendency when teaching science to oversimplify its history for the sake of getting on with the science. How it came to be isn’t necessary to learn it. But to do science requires a proper understanding of the process by which it came to be.

The story taught to cosmology students seems to have become: we didn’t believe in the cosmological constant (Λ), then in 1998 the Type Ia supernovae (SN) monitoring campaigns detected accelerated expansion, then all of a sudden we did believe in Λ. The actual history was, of course, rather more involved – to the point where this oversimplification verges on disingenuous. There were many observational indications of Λ that were essential in paving the way.

Modern cosmology starts in the early 20th century with the recognition that the universe should be expanding or contracting – a theoretical inevitability of General Relativity that Einstein initially tried to dodge by inventing the cosmological constant – and is expanding in fact, as observationally established by Hubble and Slipher and many others since. The Big Bang was largely considered settled truth after the discovery of the existence of the cosmic microwave background (CMB) in 1964.

The CMB held a puzzle, as it quickly was shown to be too smooth. The early universe was both isotropic and homogeneous. Too homogeneous. We couldn’t detect the density variations that could grow into galaxies and other immense structures. Though such density variations are now well measured as temperature fluctuations that are statistically well described by the acoustic power spectrum, the starting point was that these fluctuations were a disappointing no-show. We should have been able to see them much sooner, unless something really weird was going on…

That something weird was non-baryonic cold dark matter (CDM). For structure to grow, it needed the helping hand of the gravity of some unseen substance. Normal matter matter did not suffice. The most elegant cosmology, the Einstein-de Sitter universe, had a mass density Ω_m= 1. But the measured abundances of the light elements were only consistent with the calculations of big bang nucleosynthesis if normal matter amounted to only 5% of Ω_m = 1. This, plus the need to grow structure, led to the weird but seemingly unavoidable inference that the universe must be full of invisible dark matter. This dark matter needed to be some slow moving, massive particle that does not interact with light nor reside within the menagerie of particles present in the Standard Model of Particle Physics.

CDM and early universe Inflation were established in the 1980s. Inflation gave a mechanism that drove the mass density to exactly one (elegant!), and CDM gave us hope for enough mass to get to that value. Together, they gave us the Standard CDM (SCDM) paradigm with Ω_m = 1.000 and H₀ = 50 km/s/Mpc.

elrondwasthere — I was there when SCDM failed.

It is hard to overstate the ferver with which the SCDM paradigm was believed. Inflation required that the mass density be exactly one; Ω_m < 1 was inconceivable. For an Einstein-de Sitter universe to be old enough to contain the oldest stars, the Hubble constant had to be the lower of the two (50 or 100) commonly discussed at that time. That meant that H₀ > 50 was Right Out. We didn’t even discuss Λ. Λ was Unmentionable. Unclean.

SCDM was Known, Khaleesi.

Λ had attained unmentionable status in part because of its origin as Einstein’s greatest blunder, and in part through its association with the debunked Steady State model. But serious mention of it creeps back into the literature by 1990. The first time I personally heard Λ mentioned as a serious scientific possibility was by Yoshii at a conference in 1993. Yoshii based his argument on a classic cosmological test, N(m) – the number of galaxies as a function of how faint they appeared. The deeper you look, the more you see, in a way that depends on the intrinsic luminosity of galaxies, and how they fill space. Look deep enough, and you begin to trace the geometry of the cosmos.

At this time, one of the serious problems confronting the field was the faint blue galaxies problem. There were so many faint galaxies on the sky, it was incredibly difficult to explain them all. Yoshii made a simple argument. To get so many galaxies, we needed a big volume. The only way to do that in the context of the Robertson-Walker metric that describes the geometry of the universe is if we have a large cosmological constant, Λ. He was arguing for ΛCDM five years before the SN results.

gold_hat_portrayed_by_alfonso_bedoya — Lambda? We don’t need no stinking Lambda!

Yoshii was shouted down. NO! Galaxies evolve! We don’t need no stinking Λ! In retrospect, Yoshii & Peterson (1995) looks like a good detection of Λ. Perhaps Yoshii & Peterson also deserve a Nobel prize?

Indeed, there were many hints that Λ (or at least low Ω_m) was needed, e.g., the baryon catastrophe in clusters, the power spectrum of IRAS galaxies, the early appearance of bound structures, the statistics of gravitational lenses, and so on. Certainly by the mid-90s it was clear that we were not going to make it to Ω_m = 1. Inflation was threatened – it requires Ω_m = 1 – or at least a flat geometry: Ω_m+Ω_Λ = 1.

SCDM was in crisis.

A very influential 1995 paper by Ostriker & Steinhardt did a lot to launch ΛCDM. I was impressed by the breadth of data Ostriker & Steinhardt discussed, all of which demanded low Ω_m. I thought the case for Λ was less compelling, as it hinged on the age problem in a way that might also have been solved, at that time, by simply having an open universe (low Ω_m with no Λ). This would ruin Inflation, but I wasn’t bothered by that. I expect they were. Regardless, they definitely made that case for ΛCDM three years before the supernovae results. Their arguments were accepted by almost everyone who was paying attention, including myself. I heard Ostriker give a talk around this time during which he was asked “what cosmology are you assuming?” to which he replied “the right one.” Called the “concordance” cosmology by Ostriker & Steinhardt, ΛCDM had already achieved the status of most-favored cosmology by the mid-90s.

omhannotated — A simplified version of the diagram of Ostriker & Steinhardt (1995) illustrating just a few of the constraints they discussed. Direct measurements of the expansion rate, mass density, and ages of the oldest stars excluded SCDM, instead converging on a narrow window – what we now call ΛCDM.

Ostriker & Steinhardt neglected to mention an important prediction of Λ: not only should the universe expand, but that expansion rate should accelerate! In 1995, that sounded completely absurd. People had looked for such an effect, and claimed not to see it. So I wrote a brief note pointing out the predicted acceleration of the expansion rate. I meant it in a bad way: how crazy would it be if the expansion of the universe was accelerating?! This was an obvious and inevitable consequence of ΛCDM that was largely being swept under the rug at that time.

I mean[t], surely we could live with Ω_m < 1 but no Λ. Can’t we all just get along? Not really, as it turned out. I remember Mike Turner pushing the SN people very hard in Aspen in 1997 to Admit Λ. He had an obvious bias: as an Inflationary cosmologist, he had spent the previous decade castigating observers for repeatedly finding Ω_m < 1. That’s too little mass, you fools! Inflation demands Ω_m = 1.000! Look harder!

By 1997, Turner had, like many cosmologists, finally wrapped his head around the fact that we weren’t going to find enough mass for Ω_m = 1. This was a huge problem for Inflation. The only possible solution, albeit an ugly one, was if Λ made up the difference. So there he was at Aspen, pressuring the people who observed supernova to Admit Λ. One, in particular, was Richard Ellis, a great and accomplished astronomer who had led the charge in shouting down Yoshii. They didn’t yet have enough data to Admit Λ. Not.Yet.

By 1998, there were many more high redshift SNIa. Enough to see Λ. This time, after the long series of results only partially described above, we were intellectually prepared to accept it – unlike in 1993. Had the SN experiments been conducted five years earlier, and obtained exactly the same result, they would not have been awarded the Nobel prize. They would instead have been dismissed as a trick of astrophysics: the universe evolves, metallicity was lower at earlier times, that made SN then different from now, they evolve and so cannot be used as standard candles. This sounds silly now, as we’ve figured out how to calibrate for intrinsic variations in the luminosities of Type Ia SN, but that is absolutely how we would have reacted in 1993, and no amount of improvements in the method would have convinced us. This is exactly what we did with faint galaxy counts: galaxies evolve; you can’t hope to understand that well enough to constrain cosmology. Do you ever hear them cited as evidence for Λ?

Great as the supernovae experiments to measure the metric genuinely were, they were not a discovery so much as a confirmation of what cosmologists had already decided to believe. There was no singular discovery that changed the way we all thought. There was a steady drip, drip, drip of results pointing towards Λ all through the ’90s – the age problem in which the oldest stars appeared to be older than the universe in which they reside, the early appearance of massive clusters and galaxies, the power spectrum of galaxies from redshift surveys that preceded Sloan, the statistics of gravitational lenses, and the repeated measurement of 1/4 < Ω_m < 1/3 in a large variety of independent ways – just to name a few. By the mid-90’s, SCDM was dead. We just refused to bury it until we could accept ΛCDM as a replacement. That was what the Type Ia SN results really provided: a fresh and dramatic reason to accept the accelerated expansion that we’d already come to terms with privately but had kept hidden in the closet.

Note that the acoustic power spectrum of temperature fluctuations in the cosmic microwave background (as opposed to the mere existence of the highly uniform CMB) plays no role in this history. That’s because temperature fluctuations hadn’t yet been measured beyond their rudimentary detection by COBE. COBE demonstrated that temperature fluctuations did indeed exist (finally!) as they must, but precious little beyond that. Eventually, after the settling of much dust, COBE was recognized as one of many reasons why Ω_m ≠ 1, but it was neither the most clear nor most convincing reason at that time. Now, in the 21st century, the acoustic power spectrum provides a great way to constrain what all the parameters of ΛCDM have to be, but it was a bit player in its development. The water there was carried by traditional observational cosmology using general purpose optical telescopes in a great variety of different ways, combined with a deep astrophysical understanding of how stars, galaxies, quasars and the whole menagerie of objects found in the sky work. All the vast knowledge incorporated in textbooks like those by Harrison, by Peebles, and by Peacock – knowledge that often seems to be lacking in scientists trained in the post-WMAP era.

Despite being a late arrival, the CMB power spectrum measured in 2000 by Boomerang and 2003 by WMAP did one important new thing to corroborate the ΛCDM picture. The supernovae data didn’t detect accelerated expansion so much as exclude the deceleration we had nominally expected. The data were also roughly consistent with a coasting universe (neither accelerating nor decelerating); the case for acceleration only became clear when we assumed that the geometry of the universe was flat (Ω_m+Ω_Λ = 1). That didn’t have to work out, so it was a great success of the paradigm when the location of the first peak of the power spectrum appeared in exactly the right place for a flat FLRW geometry.

The consistency of these data have given ΛCDM an air of invincibility among cosmologists. But a modern reconstruction of the Ostriker & Steinhardt diagram leaves zero room remaining – hence the tension between H₀ = 73 measured directly and H₀ = 67 from multiparameter CMB fits.

omhannotated_cmb — Constraints from the acoustic power spectrum of the CMB overplotted on the direct measurements from the plot above. Initially in great consistency with those measurement, the best fit CMB values have steadily wandered away from the most-favored region of parameter space that established ΛCDM in the first place. This is most apparent in the tension with H₀.

In cosmology, we are accustomed to having to find our way through apparently conflicting data. The difference between an expansion rate of 67 and 73 seems trivial given that the field was long riven – in living memory – by the dispute between 50 and 100. This gives rise to the expectation that the current difference is just a matter of some subtle systematic error somewhere. That may well be correct. But it is also conceivable that FLRW is inadequate to describe the universe, and we have been driven to the objectively bizarre parameters of ΛCDM because it happens to be the best approximation that can be obtained to what is really going on when we insist on approximating it with FLRW.

Though a logical possibility, that last sentence will likely drive many cosmologists to reach for their torches and pitchforks. Before killing the messenger, we should remember that we once endowed SCDM with the same absolute certainty we now attribute to ΛCDM. I was there, 3,000 internet years ago, when SCDM failed. There is nothing so sacred in ΛCDM that it can’t suffer the same fate, as has every single cosmology ever devised by humanity.

Today, we still lack definitive knowledge of either dark matter or dark energy. These add up to 95% of the mass-energy of the universe according to ΛCDM. These dark materials must exist.

It is Known, Khaleesi.

It Must Be So. But which Must?

In the last post, I noted some of the sociological overtones underpinning attitudes about dark matter and modified gravity theories. I didn’t get as far as the more scientifically interesting part, which illustrates a common form of reasoning in physics.

About modified gravity theories, Bertone & Tait state

“the only way these theories can be reconciled with observations is by effectively, and very precisely, mimicking the behavior of cold dark matter on cosmological scales.”

Leaving aside just which observations need to be mimicked so precisely (I expect they mean power spectrum; perhaps they consider this to be so obvious that it need not be stated), this kind of reasoning is both common and powerful – and frequently correct. Indeed, this is exactly the attitude I expressed in my review a few years ago for the Canadian Journal of Physics, quoted in the image above. I get it. There are lots of positive things to be said for the standard cosmology.

This upshot of this reasoning is, in effect, that “cosmology works so well that non-baryonic dark matter must exist.” I have sympathy for this attitude, but I also remember many examples in the history of cosmology where it has gone badly wrong. There was a time, not so long ago, that the matter density had to be the critical value, and the Hubble constant had to be 50 km/s/Mpc. By and large, it is the same community that insisted on those falsehoods with great intensity that continues to insist on conventionally conceived cold dark matter with similarly fundamentalist insistence.

I think it is an overstatement to say that the successes of cosmology (as we presently perceive them) prove the existence of dark matter. A more conservative statement is that the ΛCDM cosmology is correct if, and only if, dark matter exists. But does it? That’s a separate question, which is why laboratory searches are so important – including null results. It was, after all, the null result of Michelson & Morley that ultimately put an end to the previous version of an invisible aetherial medium, and sparked a revolution in physics.

Here I point out that the same reasoning asserted by Bertone & Tait as a slam dunk in favor of dark matter can just as accurately be asserted in favor of MOND. To directly paraphrase the above statement:

“the only way ΛCDM can be reconciled with observations is by effectively, and very precisely, mimicking the behavior of MOND on galactic scales.”

This is a terrible problem for dark matter. Even if it were true, as is often asserted, that MOND only fits rotation curves, this would still be tantamount to a falsification of dark matter by the same reasoning applied by Bertone & Tait.

Lets look at just one example, NGC 1560:

ngc1560mond — The rotation curve of NGC 1560 (points) together with the Newtonian expectation (black line) and the MOND fit (blue line). Data from Begeman et al. (1991) and Gentile et al. (2010).

MOND fits the details of this rotation curve in excruciating detail. It provides just the right amount of boost over the Newtonian expectation, which varies from galaxy to galaxy. Features in the baryon distribution are reflected in the rotation curve. That is required in MOND, but makes no sense in dark matter, where the excess velocity over the Newtonian expectation is attributed to a dynamically hot, dominant, quasi-spherical dark matter halo. Such entities cannot support the features commonly seen in thin, dynamically cold disks. Even if they could, there is no reason that features in the dominant dark matter halo should align with those in the disk: a sphere isn’t a disk. In short, it is impossible to explain this with dark matter – to the extent that anything is ever impossible for the invisible.

NGC 1560 is a famous case because it has such an obvious feature. It is common to dismiss this as some non-equilibrium fluke that should simply be ignored. That is always a dodgy path to tread, but might be OK if it were only this galaxy. But similar effects are seen over and over again, to the point that they earned an empirical moniker: Renzo’s Rule. Renzo’s rule is known to every serious student of rotation curves, but has not informed the development of most dark matter theory. Ignoring this information is like leaving money on the table.

MOND fits not just NGC 1560, but very nearly* every galaxy we measure. It does so with excruciatingly little freedom. The only physical fit parameter is the stellar mass-to-light ratio. The gas fraction of NGC 1560 is 75%, so M*/L plays little role. We understand enough about stellar populations to have an idea what to expect; MOND fits return mass-to-light ratios that compare well with the normalization, color dependence, and band-pass dependent scatter expected from stellar population synthesis models.

MLBV_MOND — The mass-to-light ratio from MOND fits (points) in the blue (left panel) and near-infrared (right panel) pass-bands plotted against galaxy color (blue to the left, red to the right). From the perspective of stellar populations, one expects more scatter and a steeper color dependence in the blue band, as observed. The lines are stellar population models from Bell et al. (2003). These are completely independent, and have not been fit to the data in any way. One could hardly hope for better astrophysical agreement.

One can also fit rotation curve data with dark matter halos. These require a minimum of three parameters to the one of MOND. In addition to M*/L, one also needs at least two parameters to describe the dark matter halo of each galaxy – typically some characteristic mass and radius. In practice, one finds that such fits are horribly degenerate: one can not cleanly constrain all three parameters, much less recover a sensible distribution of M*/L. One cannot construct the plot above simply by asking the data what it wants as one can with MOND.

The “disk-halo degeneracy” in dark matter halo fits to rotation curves has been much discussed in the literature. Obsessed over, dismissed, revived, and ultimately ignored without satisfactory understanding. Well, duh. This approach uses three parameters per galaxy when it takes only one to describe the data. Degeneracy between the excess fit parameters is inevitable.

From a probabilistic perspective, there is a huge volume of viable parameter space that could (and should) be occupied by galaxies composed of dark matter halos plus luminous galaxies. Two identical dark matter halos might host very different luminous galaxies, so would have rotation curves that differed with the baryonic component. Two similar looking galaxies might reside in rather different dark matter halos, again having rotation curves that differ.

The probabilistic volume in MOND is much smaller. Absolutely tiny by comparison. There is exactly one and only one thing each rotation curve can do: what the particular distribution of baryons in each galaxy says it should do. This is what we observe in Nature.

The only way ΛCDM can be reconciled with observations is by effectively, and very precisely, mimicking the behavior of MOND on galactic scales. There is a vast volume of parameter space that the rotation curves of galaxies could, in principle, inhabit. The naive expectation was exponential disks in NFW halos. Real galaxies don’t look like that. They look like MOND. Magically, out of the vast parameter space available to galaxies in the dark matter picture, they only ever pick the tiny sub-volume that very precisely mimics MOND.

The ratio of probabilities is huge. So many dark matter models are possible (and have been mooted over the years) that it is indefinably huge. The odds of observing MOND-like phenomenology in a ΛCDM universe is practically zero. This amounts to a practical falsification of dark matter.

I’ve never said dark matter is falsified, because I don’t think it is a falsifiable concept. It is like epicycles – you can always fudge it in some way. But at a practical level, it was falsified a long time ago.

That is not to say MOND has to be right. That would be falling into the same logical trap that says ΛCDM has to be right. Obviously, both have virtues that must be incorporated into whatever the final answer may be. There are some efforts in this direction, but by and large this is not how science is being conducted at present. The standard script is to privilege those data that conform most closely to our confirmation bias, and pour scorn on any contradictory narrative.

In my assessment, the probability of ultimate success through ignoring inconvenient data is practically zero. Unfortunately, that is the course upon which much of the field is currently set.

*There are of course exceptions: no data are perfect, so even the right theory will get it wrong once in a while. The goof rate for MOND fits is about what I expect: rare, but more frequent for lower quality data. Misfits are sufficiently rare that to obsess over them is to refuse to see the forest for a few outlying trees.

Here’s a residual plot of MOND fits. See the peak at right? That’s the forest. See the tiny tail to one side? That’s an outlying tree.

rcresid_mondfits — Residuals of MOND rotation curve fits from Famaey & McGaugh (2012).

The arrogance of ignorance

A colleague points out to me a recent preprint by Bertone & Tait titled A New Era in the Quest for Dark Matter. Most of the narrative is a conventionalist response to the failure of experimental dark matter searches, posing a legitimate question in this context. Where do we take it from here?

bloomccountyrocktakeitwhere — From *Bloom County* by Berkley Breathed.

There is one brief paragraph mentioning and dismissing the possibility that what we call the dark matter problem might instead be some form of new dynamics. This is completely pro forma, and I wouldn’t have given it a second thought had my colleague not griped to me about it. It contains the following gem:

“The success of these efforts however remained limited at most to rotation curves of galaxies, and it is today clear that the only way these theories can be reconciled with observations is by effectively, and very precisely, mimicking the behavior of cold dark matter on cosmological scales.”

This is enormously revealing about the sociological attitudes in the field. Specifically, the attitude common among particle physicists who work on dark matter. Now, that’s a lot of people, and there are many individual exceptions to the general attitude I’m about to describe. But these are exceedingly common themes, so lets break it down.

There are two distinct issues packed into this one sentence. The first amounts to the oft-repeated talking point, “MOND fits rotation curves but does nothing else.”

“…these efforts however remained limited at most to rotation curves of galaxies…”

(emphasis added.) This is simply incorrect.

Nevertheless, this sentiment has been asserted so many times by so many otherwise reasonable and eminent scientists that the innocent bystander may be forgiven for thinking there is some truth to this statement. There is not. Indeed, it is a perfect example of the echo chamber effect – someone said it without checking their facts, then someone else repeated it, and so on until everyone knows this to be true. Everyone says so!

To be sure, I shared the same concern initially. Difference is, I did the fact checking. It surprised the bejeepers out of me to find that the vast majority of observations that we usually ascribe to dark matter could just as well be explained by MOND. Often better, and with less effort. This is not to say that MOND is always better, of course. But there is so much more to it that I’m not going to review it yet again here.

f4b760cf-7f29-4e5b-a5d4-3b674a705c7c_screenshot — I’m shocked – SHOCKED – to find MOND going on in this universe!

If only there were some way for scientists to communicate. In writing. Preserved in archival journals. Reviews, even…

A Tale of Two Paradigms: the Mutual Incommensurability of ΛCDM and MOND

The Third Law of Galactic Rotation

Modified Newtonian Dynamics (MOND): Observational Phenomenology and Relativistic Extensions

Modified Newtonian Dynamics as an Alternative to Dark Matter

Testing the Hypothesis of Modified Dynamics with Low Surface Brightness Galaxies and Other Evidence

Testing the Dark Matter Hypothesis with Low Surface Brightness Galaxies and Other Evidence

or if those are too intimidating, review talks at conferences

Extended Theories of Gravity

The Trials and Tribulations of Modern Cosmology: The Good, the Bad, and the Just Plain Ugly

Observational Constraints on the Acceleration Discrepancy Problem

Dynamical Constraints on Disk Galaxy Formation

How Galaxies Don’t Form

ETC.

The world has many experts on dark matter. I am one of them. It has rather fewer experts on MOND. I happen to be one of those, because I made the effort to learn about it. Being an expert on dark matter does not make one an expert on MOND – it’s painful to realize you’re at the wrong peak in the Dunning-Kruger curve. Becoming an expert is hard and time consuming, so I appreciate why many people don’t want to invest their time that way – MOND is a fringe idea, after all. Or so I thought, until I bothered to learn about it. The more I learned, the more I realized it could not so easily be dismissed.

But MOND can easily be dismissed if you remain ignorant of it! This attitude is what I call the arrogance of ignorance. Many scientists who are experts on dark matter don’t know what MOND is really, or what all it does and does not do successfully. They don’t need to! (arrogance). It can’t possibly be true! (ignorance).

The result is a profoundly unscientific status quo. If you hear someone assert something to the effect that “MOND fits rotation curves and nothing else” then you know they simply don’t know what they’re talking about.

I haven’t yet broken down the second part of statement above, but I’ve probably outraged enough people for one post. That’s OK – the shoe deserves to be on the other foot. Being outraged is what is to be an astronomer listening to particle physicists opine about dark matter. Their general attitude is that astronomers can’t possibly have anything to teach them about the subject. Never mind that 100% of the evidence is astronomical in nature, and will remain so until we get a laboratory detection. Good luck with that.

Yes, Virginia, there is a Dark Matter

Virginia, your little friends are wrong. They have been affected by the skepticism of a skeptical age. They do not believe except they see. They think that nothing can be which is not comprehensible by their little minds. All minds, Virginia, whether they be men’s or children’s, are little. In this great universe of ours man is a mere insect, an ant, in his intellect, as compared with the boundless world about him, as measured by the intelligence capable of grasping the whole of truth and knowledge.

Yes, Virginia, there is a Dark Matter. It exists as certainly as squarks and sleptons and Higgsinos exist, and you know that they abound and give to your life its highest beauty and joy. Alas! how dreary would be the world if there were no Dark Matter. It would be as dreary as if there were no supersymmetry. There would be no childlike faith then, no papers, no grants to make tolerable this existence. We should have no enjoyment, except in observation and experiment. The eternal light with which childhood fills the world would be extinguished.

Not believe in Dark Matter! You might as well not believe in Dark Energy! You might get the DOE to hire men to watch in all the underground laboratories to catch Dark Matter, but even if they did not see Dark Matter coming down, what would that prove? Nobody sees Dark Matter, but that is no sign that there is no Dark Matter. The most real things in the world are those that neither children nor men can see. Did you ever see fairies dancing on the lawn? Of course not, but that’s no proof that they are not there. Nobody can conceive or imagine all the wonders there are unseen and unseeable in the world.

You may tear apart the baby’s rattle and see what makes the noise inside, but there is a veil covering the unseen world which not the best experiment, nor even the united efforts of all the keenest experiments ever conducted, could tear apart. Only faith, fancy, poetry, love, romance, can push aside that curtain and view and picture the supernal beauty and glory beyond. Is it all real? Ah, Virginia, in all this world there is nothing else real and abiding.

No Dark Matter! Thank God! It exists, and it exists forever. A thousand years from now, Virginia, nay, ten times ten thousand years from now, it will continue to make glad the coffers of science.

Paraphrased from the famous letter Yes, Virginia, there is a Santa Claus.

The kids are all right, but they can’t interpret a graph

I have not posted here in a while. This is mostly due to the fact that I have a job that is both engaging and demanding. I started this blog as a way to blow off steam, but I realized this mostly meant ranting about those fools at the academy! of whom there are indeed plenty. These are reality based rants, but I’ve got better things to do.

As it happens, I’ve come down with a bug that keeps me at home but leaves just enough energy to read and type, but little else. This is an excellent recipe for inciting a rant. Reading the Washington Post article on delayed gratification in children brings it on.

It is not really the article that gets me, let alone the scholarly paper on which it is based. I have not read the latter, and have no intention of doing so. I hope its author has thought through the interpretation better than is implied by what I see in the WaPo article. That is easy for me to believe; my own experience is that what academics say to the press has little to do with what eventually appears in the press – sometimes even inverting its meaning outright. (At one point I was quoted as saying that dark matter experimentalists should give up, when what I had said was that it was important to pursue these experiments to their logical conclusion, but that we also needed to think about what would constitute a logical conclusion if dark matter remains undetected.)

So I am at pains to say that my ire is not directed at the published academic article. In this case it isn’t even directed at the article in the WaPo, regardless of whether it is a fair representation of the academic work or not. My ire is directed entirely at the interpretation of a single graph, which I am going to eviscerate.

The graph in question shows the delay time measured in psychology experiments over the years. It is an attempt to measure self-control in children. When presented with a marshmallow but told they may have two marshmallows if they wait for it, how long can they hold out? This delayed gratification is thought to be a measure of self-control that correlates positively with all manners of subsequent development. Which may indeed be true. But what can we learn from this particular graph?

The graph plots the time delay measured from different experiments against the date of the experiment. Every point (plotted as a marshmallow – cute! I don’t object to that) represents an average over many children tested at that time. Apparently they have been “corrected” to account for the age of the children (one gets better at delayed gratification as one matures) which is certainly necessary, but it also raises a flag. How was the correction made? Such details can matter.

However, my primary concern is more basic. Do the data, as shown, actually demonstrate a trend?

To answer this question for yourself, the first thing you have to be able to do is mentally remove the line. That big black bold line that so nicely connects the dots. Perhaps it is a legitimate statistical fit of some sort. Or perhaps it is boldface to [mis]guide the eye. Doesn’t matter. Ignore it. Look at the data.

The first thing I notice about the data are the outliers – in this case, 3 points at very high delay times. These do not follow the advertised trend, or any trend. Indeed, they seem in no way related to the other data. It is as if a different experiment had been conducted.

When confronted with outlying data, one has a couple of choices. If we accept that these data are correct and from the same experiment, then there is no trend: the time of delayed gratification could be pretty much anything from a minute to half an hour. However, the rest of the data do clump together, so the other option is that these outliers are not really representing the same thing as the rest of the data, and should be ignored, or at least treated with less weight.

The outliers may be the most striking part of the data set, but they are usually the least important. There are all sorts of statistical measures by which to deal with them. I do not know which, if any, have been applied. There are no error bars, no boxes representing quartiles or some other percentage spanned by the data each point represents. Just marshmallows. Now I’m a little grumpy about the cutesy marshmallows. All marshmallows are portrayed as equal, but are some marshmallows more equal than others? This graph provides no information on this critical point.

In the absence of any knowledge about the accuracy of each marshmallow, one is forced to use one’s brain. This is called judgement. This can be good or bad. It is possible to train the brain to be a good judge of these things – a skill that seems to be in decline these days.

What I see in the data are several clumps of points (disregarding the outliers). In the past decade there are over a dozen points all clumped together around an average of 8 minutes. That seems like a pretty consistent measure of the delayed gratification of the current generation of children.

Before 2007, the data are more sparse. There are a half a dozen points on either side of 1997. These have a similar average of 7 or 8 minutes.

Before that there are very little data. What there is goes back to the sixties. One could choose to see that as two clumps of three points, or one clump of six points. If one does the latter, the mean is around 5 minutes. So we had a “trend” of 5 minutes circa 1970, 7 minutes circa 1997, and 8 minutes circa 2010. That is an increase over time, but it is also a tiny trend – much less persuasive than the heavy solid line in the graph implies.

If we treat the two clumps of three separately – as I think we should, since they sit well apart from each other – then we have to choose which to believe. They aren’t consistent. The delay time in 1968 looks to have an average of two minutes; in 1970 it looks to be 8 minutes. So which is it?

According to the line in the graph, we should believe the 1968 data and not the 1970 data. That is, the 1968 data fall nicely on the line, while the 1970 data fall well off it. In percentage terms, the 1970 data are as far from the trend as the highest 2010 point that we rejected as an outlier.

When fitting a line, the slope of the line can be strongly influence by the points at its ends. In this case, the earliest and the latest data. The latest data seem pretty consistent, but the earliest data are split. So the slope depends entirely on which clump of three early points you choose to believe.

If we choose to believe the 1970 clump, then the “trend” becomes 8 minutes in 1970, 7 minutes in 1997, 8 minutes in 2010. Which is to say, no trend at all. Try disregarding the first three (1968) points and draw your own line on this graph. Without them, it is pretty flat. In the absence of error bars and credible statistics, I would conclude that there is no meaningful trend present in the data at all. Maybe a formal fit gives a non-zero slope, but I find it hard to believe it is meaningfully non-zero.

None of this happens in a vacuum. Lets step back and apply some external knowledge. Have people changed over the 5 decades of my life?

The contention of the WaPo article is that they have. Specifically, contrary to the perception that iPhones and video games have created a generation with a cripplingly short attention span (congrats if you made it this far!), in fact the data show the opposite. The ability of children to delay gratification has improved over the time these experiments have been conducted.

What does the claimed trend imply? If we take it literally, then extrapolating back in time, the delay time goes to zero around 1917. People in the past must have been completely incapable of delaying gratification for even an instant. This was a power our species only developed in the past century.

I hope that sounds implausible. If there is no trend, which is what the data actually show, then children a half century ago were much the same as children a generation ago are much the same as the children of today. So the more conservative interpretation of the graph would be that human nature is rather invariant, at least as indicated by the measure of delayed gratification in children.

Sadly, null results are dull. There well may be a published study reporting no trend, but it doesn’t get picked up by the Washington Post. Imagine the headline: “Children today are much the same as they’ve always been!” Who’s gonna click on that? In this fashion, even reputable news sources contribute to the scourge of misleading science and fake news that currently pollutes our public discourse.

ghostbusters-columbia — They expect results!

This sort of over-interpretation of weak trends is rife in many fields. My own, for example. This is why I’m good at spotting them. Fortunately, screwing up in Astronomy seldom threatens life and limb.

Then there is Medicine. My mother was a medical librarian; I occasionally browsed their journals when waiting for her at work. Graphs for the efficacy of treatments that looked like the marshmallow graph were very common. Which is to say, no effect was in evidence, but it was often portrayed as a positive trend. They seem to be getting better lately (which is to say, at some point in the not distant past some medical researchers were exposed to basic statistics), but there is an obvious pressure to provide a treatment, even if the effect of the available course of treatment is tiny. Couple that to the aggressive marketing of drugs in the US, and it would not surprise me if many drugs have been prescribed based on efficacy trends weaker than seen in the marshmallow graph. See! There is a line with a positive slope! It must be doing some good!

Another problem with data interpretation is in the corrections applied. In the case of marshmallows, one must correct for the age of the subject: an eight year old can usually hold out longer than a toddler. No doubt there are other corrections. The way these are usually made is to fit some sort of function to whatever trend is seen with age in a particular experiment. While that trend may be real, it also has scatter (I’ve known eight year olds who couldn’t out wait a toddler), which makes it dodgy to apply. Do all experiments see the same trend? It is safe to apply the same correction to all of them? Worse, it is often necessary to extrapolate these corrections beyond where they are constrained by data. This is known to be dangerous, as the correction can become overlarge upon extrapolation.

It would not surprise me if the abnormally low points around 1968 were over-corrected in some way. But then, it was the sixties. Children may have not changed much since then, but the practice of psychology certainly has. Lets consider the implications that has for comparing 1968 data to 2017 data.

The sixties were a good time for psychological research. The field had grown enormously since the time of Freud and was widely respected. However, this was also the time when many experimental psychologists thought psychotropic drugs were a good idea. Influential people praised the virtues of LSD.

My father was a grad student in psychology in the sixties. He worked with swans. One group of hatchlings imprinted on him. When they grew up, they thought they should mate with people – that’s what their mom looked like, after all. So they’d and make aggressive displays towards any person (they could not distinguish human gender) who ventured too close.

He related the anecdote of a colleague who became interested in the effect of LSD on animals. The field was so respected at the time that this chap was able to talk the local zoo into letting him inject an elephant with LSD. What could go wrong?

Perhaps you’ve heard the expression “That would have killed a horse! Fortunately, you’re not a horse.” Well, the fellow in question figured elephants were a lot bigger than people. So he scaled up the dose by the ratio of body mass. Not, say, the ratio of brain size, or whatever aspect of the metabolism deals with LSD.

That’s enough LSD to kill an elephant.

Sad as that was for the elephant, who is reputed to have been struck dead pretty much instantly – no tripping rampage preceded its demise – my point here is that these were the same people conducting the experiments in 1968. Standards were a little different. The difference seen in the graph may have more to do with differences in the field than with differences in the subjects.

That is not to say we should simply disregard old data. The date on which an observation is made has no bearing on its reliability. The practice of the field at that time does.

The 1968 delay times are absurdly low. All three are under four minutes. Such low delay times are not reproduced in any of the subsequent experiments. They would be more credible if the same result were even occasionally reproduced. It ain’t.

Another way to look at this is that there should be a comparable number of outliers on either side of the correct trend. That isn’t necessarily true – sometimes systematic errors push in a single direction – but in the absence of knowledge of such effects, one would expect outliers on both the high side and the low side.

In the marshmallow graph, with the trend as drawn, there are lots of outliers on the high side. There are none on the low side. [By outlier, I mean points well away from the trend, not just scattered a little to one side or the other.]

If instead we draw a flat line at 7 or 8 minutes, then there are three outliers on both sides. The three very high points, and the three very low points, which happen to occur around 1968. It is entirely because the three outliers on the low side happen at the earliest time that we get even the hint of a trend. Spread them out, and they would immediately be dismissed as outliers – which is probably what they are. Without them, there is no significant trend. This would be the more conservative interpretation of the marshmallow graph.

Perhaps those kids in 1968 were different in other ways. The experiments were presumably conducted in psychology departments on university campuses in the late sixties. It was OK to smoke inside back then, and not everybody restricted themselves to tobacco in those days. Who knows how much second hand marijuana smoke was inhaled just to getting to the test site? I jest, but the 1968 numbers might just measure the impact on delayed gratification when the subject gets the munchies.

Triton Station

A Blog About the Science and Sociology of Cosmology and Dark Matter

Category: Sociology