A Blog About the Science and Sociology of Cosmology and Dark Matter
Author: tritonstation
Stacy McGaugh is an astrophysicist and cosmologist who studies galaxies, dark matter, and theories of modified gravity. He is an expert on low surface brightness galaxies, a class of objects in which the stars are spread thin compared to bright galaxies like our own Milky Way. He demonstrated that these dim galaxies appear to be dark matter dominated, providing unique tests of theories of galaxy formation and modified gravity.
Professor McGaugh is currently the chair of the Department of Astronomy at Case Western Reserve University in Cleveland, Ohio, and director of the Warner and Swasey Observatory. Previously he was a member of the faculty at the University of Maryland, having also held research fellowships at Rutgers, the Department of Terrestrial Magnetism of the Carnegie Institution of Washington, and the Institute of Astronomy at the University of Cambridge after earning his Ph.D. from the University of Michigan.
When I wrote about Nobel prizes a little while back, I did not expect to return to the subject. I assumed the prize this year would be awarded for some meritorious advance in laboratory physics, like last year’s prize “for experimental methods that generate attosecond pulses of light for the study of electron dynamics in matter.” Instead, we find that the 2024 prize has been awarded to John Hopfield and Geoffrey Hinton “for foundational discoveries and inventions that enable machine learning with artificial neural networks.” This is the Nobel prize in physics we’re talking about.
One small issue: that’s not physics.
I’ve been concerned for a long time with the interface between astronomy and physics – where they are distinct fields and where they overlap. One of the reasons I left physics as a grad student was because the string theorists were taking over. They were talking about phenomena that were tens of orders of magnitude beyond any conceivable experimental test. That sort of theoretical speculation is often fun, sometimes important, and very rarely relevant to physical reality. Lacking exposure to experimental tests or observational consequences, to my mind it was just that: speculation, not physics.
Nearly forty years on, my concerns about string theory have not been misplaced. And while, in the strictest sense, I don’t think it qualifies as physics – it’s more of a physics-adjacent branch of mathematics – it is at least attempting to be physical theory. But machine learning is not physics. It’s computer science. Computers are a useful tool, to be sure. But programming them is no more physics than teaching a horse to count.
I’m not sure we should even consider machine learning to be meritorious. It can be useful, but it is also a gateway drug to artificial intelligence (AI). I remember the more earnest proponents of early AI propounding on the virtues of LISP and how it would bring us AI – in the 1980s. All it brought us then was dystopian fantasies about killer robotsnuking the world. Despite the current hype, we have not now developed intelligent machines – what we’re calling AI is certainly artificial but not at all intelligent. It uses machine “learning” to reprocess existing information into repackaged forms. There is zero original thought, nothing resembling intelligence. Modern AI is, in essence, a bullshit generator. Now, we can all think of people who qualify as organic bullshit generators, but that begs the question:
Why is the Nobel prize in physics being awarded for something that is clearly not physics?
Maybe it has something to do with the hype around AI. I don’t know what the decision process was, but I do know that I am not the only scientist to have this reaction.
Myself, I’m not mad, just disappointed. I’m not unique in feeling that physics has lost its way. This just emphasizes how far it has strayed.
Apparently the Nobel committee is sensing the blow-back, as this poll currently appears on the award page:
I… don’t think this helps their case. Did you know that molecules are made of atoms? Ergo all of chemistry is just applied atomic physics. I mean, it is a long-standing trope that physicists think every other science is just a lesser, applied form of physics. At the level of being based on the equations of physics, that’s almost kinda if not really true. So asserting that machine learning models are based on physics equations comes nowhere near to making machine learning into physics. It’s fancy programming, not physics.
Well, there will be complaints about this one for a while, so I won’t pile on more. I guess if you give out 118 prizes since 1901, one of them has to rank 118th.
Who we give prizes to is more a matter of sociology than science. Good science is a prerequisite, but after that it is a matter of which results we value in the here and now. Results that are guaranteed to get a Nobel prize, like the detection of dark matter, attract many suitors who pursue them vigorously. Results that come as a surprise can be more important than the expected results, but it takes a lot longer to recognize and appreciate them.
When there are expected results with big stakes, sociology kicks into hyperdrive. Let’s examine the attitudes in some recent quotes:
If WIMPs were there, we have the sensitivity to have seen them
which is true. WIMP detection experiments have succeeded in failing. They have explored the predicted parameter space. But in the same paragraph, it is said that it is too early to “give up hope of detecting WIMPs.” That is a pretty vague assertion, and is precisely why I’ve been asking other scientists to define a criterion by which we could agree that enough was enough already. How do we know when to stop looking?
The same paragraph ends with
This is our first real foray into discovery territory
which is not true. We’ve explored the region in which WIMPs were predicted to reside over and over and over again. This was already excruciatingly old news when I wrote about it in 2008. The only way to spin this as a factual statement is to admit that the discovery territory is practically infinite, in which case we can assert that every foray is our first “real” foray because we’ll never get anywhere relative to infinity. It sounds bad when put that way, which is the opposite of the positivity the spokespeople for huge experiments are appointed to project.
And that’s where the sociology kicks in. The people who do the experiments want to keep doing the experiments until they discover dark matter and win the Nobel prize. It’s disappointing that this hasn’t happened already, but it is an expected result. It’s what they do, so it’s natural to want to keep at it.
On the one hand, I’d like to see these experiments continue until they reach the neutrino fog, at which point they will provide interesting astrophysical information. Says Michael Murra (in Science News, 25 July 2024)
It’s very cool to see that we can turn this detector into a neutrino observatory
Yes, it is. But that wasn’t the point, was it?
On the other hand, I do not expect these experiments to ever detect dark matter. That’s because I understand that the astronomical data contain self-contradictions to their interpretation in terms of dark matter. Any particle physicist will tell you that astronomical data require dark matter. But they’re not experts on that topic, I am. I’ve talked to enough of them at this point to conclude that the typical physicist working on dark matter has only a cartoonish understanding of the data that motivates their whole field. After all,
It is difficult to get a man to understand something, when his salary depends on his not understanding it.
The time is approaching when Nobel prizes are awarded. This inevitably leads to a lot of speculation and chattering rumor. Last year one publication, I think it was Physics Today, went so far as to publish a list of things various people thought should be recognized. This aspirational list was led, of course, by dark matter. It was even formatted the way prize awards are phrased, saying something like “the prize goes to [blank] for the discovery of dark matter.” This would certainly be a prize-worthy discovery, if made. So far it hasn’t been, and I expect it never will be: blank will remain blank forever. I’d be happy to be proved wrong, as forever is a long time to wait for corroboration of this prediction.
While the laboratory detection of dark matter is a slam-dunk for a Nobel prize, there are plenty of discoveries that drive the missing mass problem that are already worthy of this recognition. The issue is too big for a single prize. Laboratory detection would be the culmination of a search that has been motivated by astronomical observations. The Nobel prize in physics has sometimes been awarded for astronomical discoveries – and should be, for those that impact fundamental physics or motivate entire fields like the search for dark matter – so let’s think about what those might be.
An obvious historical example would be Kepler’s Laws. Kepler predates Nobel by a few centuries, but there is no doubt that his identification of the eponymous laws of planetary motion impacted fundamental physics, being one of the key set of facts that led Newton to his universal law of gravity. Whether Tycho Brahe should also be named as the person who made the observations on which Kepler’s work is based is the sort of question the prize committee has to wrestle with. I would say yes: the prize is for “the person who shall have made the most important discovery or invention within the field of physics.” In this case, the discovery that led to gravity was a set of rules – how the orbits of planets behave – that required both observational work (Brahe’s) and numerical analysis (Kepler’s) to achieve.
One could of course also give a prize to Newton some decades later, though theories are not generally considered discoveries. The line can be hazy. For example, the Nobel Prize in Physics 1921 was awarded to Albert Einstein “for his services to Theoretical Physics, and especially for his discovery of the law of the photoelectric effect.” The “especially” is reserved for the empirical law, not relativity, though I guess “services to theoretical physics” is doing a lot of work there.
Reading up on that I was mildly surprised to learn that the committee had a hard time finding deserving recipients, initially skipping 1918 and 1921 but awarding those prizes in the subsequent year to Planck and Einstein, respectively. I wonder if they struggled with the definition of discovery: need it be experimental? For many, the answer is yes. A theory by itself, untethered from experimental or observational corroboration, does not a discovery make.
I don’t think they need to skip years any more, as the list of plausible nominees has grown so long that deserving people die waiting to be recognized: the Nobel prize is not awarded posthumously. The story is that this is what happened to both Henrietta Leavitt (who discovered the Cepheid period-luminosity relation) and Edwin Hubble (who used Leavitt’s relation for Cepheids to measure distances to other galaxies, thereby changing the course of cosmology). There is also the issue of what counts as physics. At the time, these were very astronomical discoveries. In retrospect, it is obvious that the impact Hubble had on cosmology counts as physics as well.
The same can be said for the discovery of flat rotation curves. I have made the case before that Vera Rubin and Albert Bosma (and arguably others) deserve the Nobel prize for this discovery. Note that I do not say the discovery of dark matter, because (1) that’s not what they did*, and (2) flat rotation curves are enough. Flat rotation curves are a de facto law of nature. That’s enough, every bit as much as Einstein’s “discovery of the law of the photoelectric effect.” A laboratory detection of dark matter would be another discovery worthy of a Nobel prize, but we already missed out on recognizing Rubin for this one.
Conflating discoveries with their interpretation has precluded recognition of other important astronomical discoveries – discoveries that implicate basic physics regardless of their ultimate interpretation, be it cold dark matter or MOND or something else we have yet to figure out. So, what are some others?
Philip Mannheim pointed out to me that Milgrom deserves the prize for the discovery of the acceleration scale a0. This is a new constant of nature. That’s enough.
Milgrom went further, developing the whole MOND paradigm around this new scale. But that is extra credit material that needn’t be correct. Unfortunately, the controversial nature of MOND, deserved or not, serves to obscure that there is a new constant of nature whose discovery is analogous to Planck’s discovery of his eponymous constant. People argue over whether a0 is a single constant (it is) or whether it evolves over cosmic time (not so far as I can tell). The latter objection could be raised for Planck’s constant or Newton’s constant; these were established when it wasn’t possible to test whether their values might have varied over cosmic time. Now that we can, we do check! and so far, no: h, G, and a0 all appear to be constants of nature, to the extent we are able to perceive.
The above discoveries are all worthy of recognition by a Nobel prize. They are all connected by the radial acceleration relation, which is another worthy observational discovery in its own right. This is one that clearly transgresses the boundaries of physics and astronomy, as the early versions (Sanders 1990, McGaugh 1999, 2004) appeared in the astronomical literature, but more recent ones in the physics literature (McGaugh et al. 2016, Mistele et al. 2024). Sadly, the community seems perpetually stuck looping through the stages of Louis Agassiz‘s progression of responses to scientific discoveries. It shouldn’t be: this is an empirical relation that has long been well established and repeatedly confirmed. It suffers from association with MOND, but no reference to MOND is made in the construction of the observed relation. It’s right there in the data:
The radial acceleration relation as traced by both early (red) and late (cyan) type galaxies via both kinematics and gravitational lensing. The low acceleration behavior maps smoothly onto the Newtonian behavior seen in the solar system at higher accelerations. If Newton’s discovery of the inverse square force law would warrant a Nobel prize, as surely it would had the prize existed in Newton’s time, then so does the discovery of a systematically new behavior.
*Rubin and Bosma both argued, sensibly, that the interpretation of flat rotation curves required dark matter. That’s an interpretation, not a discovery. That rotation curves were flat, over and over again in every galaxy examined, to indefinitely large radii, was the observational discovery.
I have said I wasn’t going to attempt to teach an entire graduate course on galaxy dynamics in this forum, and I’m not. But I can give some pointers for those who want to try it for themselves. It also provides some useful context for fans of Deur’s approach.
The go-to textbook for this topic is Galactic Dynamics by Binney & Tremaine. The first edition was published in 1987, conveniently when I switched to grad school in astronomy. It was already a deep and well-developed field at that time; this is a compendium of considerable scientific knowledge.
Fun story: a colleague in a joint physics & astronomy department once complained to me that she wanted to develop a course in galaxy dynamics, which is a staple of graduate programs in astronomy & astrophysics. However, there was a certain senior colleague who objected, saying that since it was astronomy, it couldn’t possibly be a rigorous course worthy of a full semester graduate course. This is a casual bias that astronomers often encounter when talking to physicists, many of whom have attitudes about the subject that were trapped in amber sometime in the Jurassic. I suggested that she walk into his office and drop a copy of Galactic Dynamics on his desk from on high, as (1) it would make a hefty impact, and (2) no one who so much as skims this book could persist in this toxic attitude.
She later reported that she had done this, and it had worked.
Galactic Dynamics is not a starter book. It is the textbook we use when teaching the graduate course that this is not. A useful how-to guide for the specific material I’ll discuss here is provided by Federico Lelli. In brief, to model the gravitational potential of an observed distribution of matter, we can make one of the following series of approximations:
This is a slide I sometimes use to introduce mass modeling in science talks as a reminder for expert audiences.
All science is an approximation at some level. The most crude approximation we can employ here is to imagine that all of the mass resides at a central point. In this limit, the potential is simply
V2 = GM/R
where V is the orbital speed of a test particle on a circular orbit, G is Newton’s constant, M is the mass, and R is the distance from the point mass. Galaxies are not point masses, so this is a terrible approximation, as can be seen by the divergent V ~ R-1/2 behavior as R → 0 (the dotted line above).
The next bad approximation one can make is a spherical cow: assume the mass is distributed in a sphere that is projected as the image we see on the sky. This at least incorporates the fact that the mass is not all concentrated at a point, so
V2 = GM(R)/R
acknowledges that the mass M is spread out as a function of radius. This is a spherical cow. Since we cannot see dark matter, we almost always assume it to be a spherical cow.
For the luminous disk of a spiral galaxy, a common approximation is the so-called exponential disk:
Σ(R) = Σ0 e-R/Rd
where Σ0 is the central surface density of stars and Rd is the scale length of the disk – the characteristic size over which the surface brightness declines exponentially. This can be integrated by parts to obtain an expression for the enclosed mass M(R) which I leave as an exercise for the eager reader. This provides a handy analytic formula, the rotation curve of which is illustrated above by the dashed line.
Spiral galaxies are fairly thin when seen edge-on, so the spherical cow is not a great approximation. In a classic paper, Freeman (1970) solved the Poisson equation for the case of a razor-thin exponential disk, where one meets modified Bessel functions of the first and second kind (denoted “ikik” above). These must be solved numerically, but one can make a tabulation for use with any choice of disk mass and scale length. Such a thin disk is illustrated by the grey line above for a choice of stellar mass and scale length appropriate to NGC 6946.
The spiral galaxy NGC 6946, aka the fireworks galaxy.
Spiral galaxies are not razor thin of course. We only see a projected image on the sky, so for a galaxy like NGC 6946, we may have a good measurement of its azimuthally averaged light (and presumable stellar mass) distribution Σ(R) but we have no idea how thick it is. Here, we have to make an educated guess based on observations of edge-on galaxies. A ballpark average is R:z = 8:1, but some galaxies are thicker and others thinner, so this becomes an approximation with an associated uncertainty. This uncertainty cannot be unambiguously eliminated; it is one of the known unknowns that comprise the inevitable systematic errors in astronomy. Fortunately, allowing for a finite thickness only takes the harsh edge off of the thin disk case, and the assumption one chooses makes little difference to the result (compare the lines labeled thick and thin above).
The exponential disk formula Σ(R) is an azimuthal average over an image like that of NGC 6946. This approximation captures none of the spiral structure: it only tells us about the average rate at which the surface brightness falls off. It also imposes a smooth shape on that fall off that our eyes can see is not necessarily a great approximation. So the next level of approximation is to solve the Poisson equation numerically for the observed surface brightness profile, Σ(R), not just the exponential approximation thereto. This is the blue line in the bottom right graph above.
There are important differences between using the numerical solution for the observed light distribution and the exponential disk approximation. This has been known since the 1980s, but the analytic expression is so convenient that people need an occasional reminder not to trust it too much. Jerry Sellwood felt the need to provide this reminder in 1999:
Small apparent differences in the shape of the mass profile (left) correspond to pronounced differences in the rotation curve (right). I chose the example of NGC 6946 in part because the exponential approximation for it is pretty good. Nevertheless, the details matter, so the best practice is to build numerical mass models, as we did for SPARC.
Building numerical mass models is tractable for external galaxies, where we can see the entire light distribution. It is not possible for our own Milky Way, since we are located within it and cannot see it as a whole. Consequently, the vast majority of Milky Way models rely on the exponential approximation; so far as I’m aware, I’m the only one who has built a model that attempts to get beyond this.
Numerical mass models are still an approximation. We’re assuming that the gravitational potential is static and azimuthally symmetric. Taking the next step would require abandoning these assumptions to model the spiral arms. The Poisson equation can handle that, but it becomes dicey because the arms rotate with some pattern speed (generally unknown) and may grow or dissolve or reform on some unknown timescale. The potential at any given point is time variable even in equilibrium, so we need not just a numerical solution but a live numerical simulation to keep track of it. That can be done, but it has to be done on a case by case basis, and the answer will depend somewhat on additional assumptions that have to be introduced to run the simulation, like specifying a dark matter halo.
One can generalize further to consider the full 3D potential, e.g., to allow for asymmetry in the z-direction as well as in azimuth. One can further imagine non-equilibrium processes, such as an external perturbations. There is good evidence that the Milky Way suffers both of these effects, the passage of the Large Magellanic Cloud being one obvious and apparently large perturbation. So we are in the awkward position that the Gaia data now oblige us to consider the entire run of possible effects through non-equilibrium processes in a mass distribution that is not completely symmetric in any of the three spatial dimensions, but for the main mass component we are stuck with the inadequate approximation of an exponential disk.
Geometry appears to play a crucial role in the approach of Deur to the acceleration discrepancy problem. The essential claim is that the discrepancy correlates with flattening, with highly flattened systems like spirals evincing the classic discrepancy while spherical systems like E0 galaxies showing none. Big if true!
Some measure of the discrepancy as a function of apparent ellipticity.
This is the one example shown that goes into the plot of many determinations of the slope a on the following slide. It being the only one, it is the only thing I have to evaluate without chasing down every other case. Looking at this, I am not inclined to do so.
At first it looks persuasive: the best fit slope is clear. There is no reason why the discrepancy should depend on the projected ellipticity of a triaxial 3D blob of stars, so this must be telling us something important. I’d be on board with that if it were true, but I’ve seen too many non-correlations masquerading as correlations to believe this one. The fitted slope is strongly influenced by the one point at large ellipticity; absent that, a slope of zero works fine. Mostly what I see here is a lot of scatter, which is normal in extragalactic astronomy. Since there are only a few points at high and low ellipticity, we don’t know what would happen if we went out and got more data. But I bet that what would happen is that the high ellipticity points would wind up looking like those in the middle: a big blob of scatter, with no significant correlation.
I’d kinda like to be wrong about this one, so I won’t even get into the theory side, which I find sorta compelling but ultimately unpersuasive. Why are gravitons confined to a disk? What happens way far out? Surely the flatness of the disk at tens of kpc is not dictating the flatness at 1000 kpc.
The history of science is a decision tree. Vertices appear where we must take one or another branching. Sometimes, we take the wrong road for the right reasons.
A good example is the geocentric vs. heliocentric cosmology. The ancient Greeks knew that in many ways it made more sense for the earth to revolve around the sun than vice-versa. Yet they were very clever. Ptolemy and others tested for the signature of the earth’s orbit in the seasonal wobbling in the positions of stars, or parallax. If the earth is moving around the sun, nearby stars should appear to move on the sky as the earth moves from one side of the sun to the other. Try blinking back and forth between your left and right eyes to see this effect, noting how nearby objects appear to move relative to distant ones.
Problem is, Ptolemy did not find the parallax. Quite reasonably, he inferred that the earth stayed put. We know now that this was the wrong branch to choose, but it persisted as the standard world view for many centuries. It turns out that even the nearest stars are so distant that their angular parallax is tiny (the angle of parallax is inversely proportional to distance). Precision sufficient for measuring the parallax was not achieved until the 19th century, by which time astronomers were already convinced it must happen.
Ptolemy was probably aware of this possibility, though it must have seemed quite unreasonable to conjecture at that time that the stars could be so very remote. The fact was that parallax was not observed. Either the earth did not move, or the stars were ridiculously distant. Which sounds more reasonable to you?
So, science took the wrong branch. Once this happened, sociology kicked in. Generation after generation of intelligent scholars confirmed the lack of parallax until the opposing branch seemed so unlikely that it became heretical to even discuss. It is very hard to reverse back up the decision tree and re-assess what seems to be such a firm conclusion. It took the Copernican revolution to return to that ancient decision branch and try the other one.
Cosmology today faces a similar need to take a few steps back on the decision tree. The problem now is the issue of the mass discrepancy, typically attributed to dark matter. When it first became apparent that things didn’t add up when one applied the usual Law of Gravity to the observed dynamics of galaxies, there was a choice. Either lots of matter is present which happens to be dark, or the Law of Gravity has to be amended. Which sounds more reasonable to you?
Having traveled down the road dictated by the Dark Matter decision branch, cosmologists find themselves trapped in a web of circular logic entirely analogous to the famous Ptolemaic epicycles. Not many of them realize it yet, much less admit that this is what is going on. But if you take a few steps back up the decision branch, you find a few attempts to alter the equations of gravity. Most of these failed almost immediately, encouraging cosmologists down the dark matter path just as Ptolemy wisely chose a geocentric cosmology. However, one of these theories is not only consistent with the data, it actually predicts many important new results. This theory is known as MOND (MOdified Newtonian Dynamics). It was introduced in 1983 by Moti Milgrom of the Weizmann Institute in Israel.
MOND accurately describes the effective force law in galaxies based only on the observed stars and gas. What this means is unclear, but it clearly means something! It is conceivable that dark and luminous matter somehow interact to mimic the behavior stipulated by MOND. This is not expected, and requires a lot of epicyclic thinking to arrange. The more straightforward interpretation is that MOND is correct, and we took the wrong branch of the decision tree back in the ’70s.
MOND has dire implications for much modern cosmological thought which has developed symbiotically with dark matter. As yet, no one has succeeded in writing down a theory which encompasses both MOND and General Relativity. This leaves open many questions in cosmology that were thought to be solved, such as the expansion history of the universe. There is nothing a scientist hates to do more than unlearn what was thought to be well established. It is this sociological phenomenon that makes it so difficult to climb back up the decision tree to the faulty branching.
Once one returns and takes the correct branch, the way forward is not necessarily obvious. The host of questions which had been assigned seemingly reasonable explanations along the faulty branch must be addressed anew. And there will always be those incapable of surrendering the old world view irrespective of the evidence.
In my opinion, the newsuccesses of MOND can not occur by accident. They are a strong sign that we are barking up the wrong tree with dark matter. A grander theory encompassing both MOND and General Relativity must exist, even if no one has as yet been clever enough to figure it out (few have tried).
These all combine to make life as a cosmologist interesting. Sometimes it is exciting. Often it is frustrating. Most of the time, “interesting” takes on the meaning implied by the old Chinese curse:
MAY YOU LIVE IN INTERESTING TIMES
Like it or not, we do.
*I wrote this in 2000. I leave it to the reader to decide how much progress has been made since then.
I want to take another step back in perspective from the last post to say a few words about what the radial acceleration relation (RAR) means and what it doesn’t mean. Here it is again:
The Radial Acceleration Relation over many decades. The grey region is forbidden – there cannot be less acceleration than caused by the observed baryons. The entire region above the diagonal line (yellow) is accessible to dark matter models as the sum of baryons and however much dark matter the model prescribes. MOND is the blue line.
This information was not available when the dark matter paradigm was developed. We observed excess motion, like flat rotation curves, and inferred the existence of extra mass. That was perfectly reasonable given the information available at the time. It is not now: we need to reassess as we learn more.
There is a clear organization to the data at both high and low acceleration. No objective observer with a well-developed physical intuition would look at this and think “dark matter.” The observed behavior does not follow from one force law plus some arbitrary amount of invisible mass. That could do literally anything in the yellow region above, and beyond the bounds of the plot, both upwards and to the left. Indeed, there is no obvious reason why the data don’t fall all over the place. One of the lingering, niggling concerns is the 5:1 ratio of dark matter:baryons – why is it in the same ballpark, when it could be pretty much anything? Why should the data organize in terms of acceleration? There is no reason for dark matter to do this.
Plausible dark matter models have been predicted to do a variety of things – things other than what we observe. The problem for dark matter is that real objects only occupy a tiny line through the vast region available to them in the plot above. This is a fine-tuning problem: why do the data reside only where they do when they could be all over the place? I recognized this as a problem for dark matter before I became aware$ of MOND. That it turns out that the data follow the line uniquely predicted* by MOND is just chef’s kiss: there is a fine-tuning problem for dark matter because MOND is the effective force law.
The argument against dark matter is that the data could reside anywhere in the yellow region above, but don’t. The argument against MOND is that a small portion of the data fall a little off the blue line. Arguing that such objects, be they clusters of galaxies or particular individual galaxies, falsify MOND while ignoring the fine-tuning problem faced by dark matter is a case of refusing to see the forest for a few outlying trees.%
So to return to the question posed in the title of this post, I don’t know why it had to be MOND. That’s just what we observe. Pretending dark matter does the same thing is a false presumption.
$I’d heard of MOND only vaguely, and, like most other scientists in the field, had paid it no mind until it reared its ugly head in my own data.
*I talk about MOND here because I believe in giving credit where credit is due. MOND predicted this; no other theory did so. Dark matter theories did not predict this. Mydark matter-based galaxy formation theory did not predict this. Other dark matter-based galaxy formation theories (including simulations) continue to fail to explain this. Other hypotheses of modified gravity also did not predict what is observed. Who+ ordered this?
Modified Dynamics. Very dangerous. You go first.
Many people in the field hate MOND, often with an irrational intensity that has the texture of religion. It’s not as if I woke up one morning and decided to like MOND – sometimes I wish I had never heard of it – but disliking a theory doesn’t make it wrong, and ignoring it doesn’t make it go away. MOND and only MOND predicted the observed RAR a priori. So far, MOND and only MOND provides a satisfactory explanation of thereof. We might not like it, but there it is in the data. We’re not going to progress until we get over our fear of MOND and cope with it. Imagining that it will somehow fall out of simulations with just the right baryonic feedback prescription is a form of magical thinking, not science.
MOND. Why’d it have to be MOND?
+Milgrom. Milgrom ordered this.
%I expect many cosmologists would argue the same in reverse for the cosmic microwave background (CMB) and other cosmological constraints. I have some sympathy for this. The fit to the power spectrum of the CMB seems too good to be an accident, and it points to the same parameters as other constraints. Well, mostly – the Hubble tension might be a clue that things could unravel, as if they haven’t already. The situation is not symmetric – where MOND predicted what we observe a priori with a minimum of assumptions, LCDM is an amalgam of one free parameter after another after another: dark matter and dark energy are, after all, auxiliary hypotheses we invented to save FLRW cosmology. When they don’t suffice, we invent more. Feedback is single word that represents a whole Pandora’s box of extra degrees of freedom, and we can invent crazier things as needed. The results is a Frankenstein’s monster of a cosmology that we all agree is the same entity, but when we examine it closely the pieces don’t fit, and one cosmologist’s LCDM is not really the same as that of the next. They just seem to agree because they use the same words to mean somewhat different things. Simply agreeing that there has to be non-baryonic dark matter has not helped us conjure up detections of the dark matter particles in the laboratory, or given us the clairvoyance to explain# what MOND predicted a prioi. So rather than agree that dark matter must exist because cosmology works so well, I think the appearance of working well is a chimera of many moving parts. Rather, cosmology, as we currently understand it, works if and only if non-baryonic dark matter exists in the right amount. That requires a laboratory detection to confirm.
#I have a disturbing lack of faith that a satisfactory explanation can be found.
In the previous post, we discussed how lensing data extend the Radial Acceleration Relation (RAR) seen in galaxy kinematics to very low accelerations. Let’s zoom out now, and look at things at higher accelerations and from a historical perspective.
This all started with Kepler’s Laws of Planetary Motion, which are explained by Newton’s Universal Gravitation – the inverse square law gbar = GM/r2 is exactly what is needed to explain the observed centripetal acceleration, gobs = V2/r. It also explains the surface gravity of the Earth. Indeed, it was the famous falling apple that is reputed to have given Newton the epiphany that it was the same force that made the apple fall to the ground that made the Moon circle the Earth that made the planets revolve around the sun.
The inverse square law holds over more than six decades of observed acceleration in the solar system, from the one gee we feel here on the surface of the Earth to the outskirts patrolled by Neptune.
Planetary motion in the radial acceleration plane. The dotted line is Newton’s inverse square law of universal gravity.*
The inverse square force law is what it takes to make the planetary data line up. A different force law would give a line with a different slope in this plot. No force law at all would give chaos, with planets all over the place in this plot, if, say, the solar system were run by a series of deferents and epicycles as envisioned for Ptolemaic cosmologies. In such a system, there is no reason to expect the organization seen above. It would require considerable contrivance to make it so.
Newtonian gravity and General Relativity are exquisitely well-tested in the solar system. There are also some very precise tests at higher accelerations that GR passes with flying colors. The story to lower accelerations is another matter. The most remote solar system probes we’ve launched are the Voyger and Pioneer missions. These probe down to ~10-6 m/s/s; below that is uncharted territory.
The RAR extended from high solar system accelerations to much low accelerations typical of galaxies – not the change in scale. Some early rotation curves (of NGC 55, NGC 801, NGC 2403, NGC 2841, & UGC 2885) are shown as lines. These probed an entirely new regime of acceleration. The departure of these lines from the dotted line are the flat rotation curves indicating the acceleration discrepancy/need for dark matter. This discrepancy was clear by the end of the 1970s, but the amplitude of the discrepancy then was modest.
Galaxies (and extragalactic data in general) probe an acceleration range that is unprecedented from the perspective of solar system tests. General Relativity has passed so many precise tests that the usual presumption is that is applies at all scales. But it is an assumption that it applies to scales where it hasn’t been tested. Galaxies and cosmology pose such a test. That we need to invoke dark matter to save the phenomenon would be interpreted as a failure if we had set out to test the theory rather than assume it applied.
It was clear from flat rotation curves that something extra was needed. However, when we invented the dark matter paradigm, it was not clear that the data were organized in terms of acceleration. As the data continued to improve, it became clear that the vast majority of galaxies adhered to a single, apparently universal+radial acceleration relation. What had been a hint of systematic behavior in early data became clean and clear. The data did not exhibit the scatter that as was expected from a sum of a baryonic disk and a non-baryonic dark matter halo – there is no reason that these two distinct components should sum to the single effective force law that is observed.
The RAR with modern data for both early (red triangles) and late (cyan circles) morphological types. The blue line is the prediction of MOND: there is a transition at an acceleration scale to a force law that is universal but no longer inverse-square.
The observed force-law happened to already have a name: MOND. If it had been something else, then we could have claimed to discover something new. But instead we were obliged to admit that the unexpected thing we had found had in fact been predicted by Milgrom.
This predictive power now extends to much lower accelerations. Again, only MOND got this prediction right in advance.
The RAR as above, extended by weak gravitational lensing observations. These follow the prediction of MOND as far as they are credible.
The data could have done many different things here. It could have continued along the dotted line, in which case we’d have need for no dark matter or modified gravity. It could have scattered all over the place – this is the natural expectation of dark matter theories, as there is no reason to expect the gravitational potential of the dominant dark matter halo to be dictated by the distribution of baryons. One expects that not to happen. Yet the data evince the exceptional degree of organization seen above.
It requires considerable contrivance to explain the RAR with dark matter. No viable explanation yet exists, despite many unconvincing claims to this effect. I have worked more on trying to explain this in terms of dark matter than I have on MOND, and all I can tell you is what doesn’t work. Every explanation I’ve seen so far is a special case of a model I had previously considered and rejected as obviously unworkable. At this point, I don’t see how dark matter can ever plausibly do what the data require.
I worry that dark matter has become an epicycle theory. We’re sure it is right, so whatever we observe, no matter how awkward or unexpected, must be what it does. But what if it is wrong, and it does not exist? How do we ever disabuse ourselves of the notion that there is invisible mass once we’ve convinced ourselves that there has to be?
Of course, MOND has its own problems. Clusters of galaxies are systems$ for which it persistently fails to explain the amplitude of the observed acceleration discrepancy. So let’s add those to the plot as well:
So: do clusters violate the RAR, or follow it? I’d say yes and yes – the offset, thought modest in amplitude in this depiction, is statistically significant. But there is also a similar scaling with acceleration, only the amplitude is off. The former makes no sense in MOND; the latter makes no sense in terms of dark matter which did not predict a RAR at all.
Clusters are the strongest evidence against MOND. Just being evidence against MOND doesn’t automatically make it evidence in favor of dark matter. I often pose myself the question: which theory requires me to disbelieve the least amount of data? When I first came to the problem, I was shocked to find that the answer was clearly MOND. Since then, it has gone back and forth, but rather than a clear answer emerging, what has happened is more a divergence of different lines of evidence: that which favors the standard cosmology is incommensurate with that which favors MOND. This leads to considerable cognitive dissonance.
One way to cope with cognitive dissonance is to engage with a problem from different perspectives. If I put on a MOND hat, I worry about the offset seen above for clusters. If I put on a dark matter hat, I worry about the same kind of offset for every system that is not a rich cluster of galaxies. Most critics of MOND seem unconcerned about this problem for dark matter, so how much should a critic of dark matter worry about it in MOND?
*For the hyper-pedantic: the eccentricity of each orbit causes the exact location of each planet in the first plot to oscillate up and down along the dotted line. The extent of this oscillation is smaller than the size of each symbol with the exception of Mercury, which has a relatively high eccentricity (but nowhere near enough to reach Venus).
+There are a few exceptions, of course – there are always exceptions in astronomy. The issue is whether these are physically meaningful, or the result of systematic uncertainties or non-equilibrium processes. The claimed discrepancies range from dubious to unconvincing to obviously wrong.
$I’ve heard some people criticize MOND because the centroid of the lensing signal does not peak around the gas in the Bullet cluster. This assumes that the gas represents the majority of the baryons. We know the is not the case, and that there is some missing mass in clusters. Whatever it is, it is clearly more centrally concentrated than the gas, so we don’t expect the lensing signal to peak where the gas is. All the Bullet cluster teaches us is that whatever this stuff is, it is collisionless. So this particular complaint is a logical fallacy of the a red herring and/or straw man variety born of not understanding MOND well enough to criticize it accurately. Why bother to do that when you come to the problem already sure that MOND is wrong? I understand this line of thought extraordinarily well, because that’s the attitude I started with, and I’ve seen it repeated by many colleagues. The difference is that I bothered to educate myself.
A personal note – I will be on vacation next week, so won’t be quick to respond to comments.
Figure 2 from Mistele et al. (2024a).The RAR from weak lensing data (yellow diamonds) is shown together with the binned kinematic RAR from Lelli et al. (2017, gray circles). The solid line is Newtonian gravity without dark matter (gobs = gbar). The shaded region at gbar < 10−13 m/s2 indicates where the isolation criterion may be less reliable according to the estimate by Brouwer et al. (2021). Our results suggest that late type galaxies (LTGs) may be sufficiently isolated down to gbar ≈ 10−14 m/s2. We shade this region where LTGs may still be reliable in a lighter color.
The RAR of weak lensing extends the RAR from kinematics to much lower accelerations. How low we can trust we’ll come back to, but certainly to gbar ≈ 10−13 m/s2 and probably to gbar ≈ 10−14 m/s2. For the mass of the typical galaxy in the KiDS sample, this corresponds to a radius of 300 kpc and 1.1 Mpc, respectively. Hence our claim that the effective gravitational potentials of isolated galaxies are consistent with rotation curves that remain flat indefinitely far out: a million light years at least, and perhaps a million parsecs.
Note that the kinematic and lensing data overlap at log(gbar) = -11.5. These independent methods give the same result. Moreover, this region corresponds to the regions in galaxies where atomic gas rather than stars dominates the baryonic mass budget, which minimizes the systematic uncertainty due to stellar population mass estimates. The lensing results still depend on these, but they agree with the gas-dominated portion of the RAR, and merge smoothly into the star-dominated portion of the kinematic data when the same stellar pop models are used for both. To wit: the agreement is really good.
A flat rotation curve projects into the log(gobs)-log(gbar) plane as a line with slope 1/2. The data adhere closely to this slope, so I knew as soon as I saw the lensing RAR that the implied rotation curves remained flat indefinitely. How far, in radius, depends on galaxy mass, since for a point mass (a good approximation at radii beyond 100 kpc), gbar = GMbar/R2. We can split the lensing data into different mass bins, for which the RAR looks like
Figure 5 from Mistele et al. (2024a).The RAR implied by weak lensing for four baryonic mass bins. The dashed line has the slope a flat rotation curve has when projected into the acceleration plane. That different masses follow the same RAR implies the Baryonic Tully-Fisher relation.
Most dark matter models that I’ve seen or constructed myself predict a mass-dependent shift in the RAR, if they predict a RAR at all (many do not). We see no such shift. But the math is such that the flat rotation speed implied by the slope 1/2 RAR varies with mass in such a way that they only fall on the same RAR, as observed, if there is a Baryonic Tully-Fisher relation with slope 4. So I knew from examination of the above figure that the BTFR was sure to follow, but that’s because I’ve been working on these things for a long time. It isn’t necessarily obvious to everyone else, so it was worth explicitlyshowing.
Our result differs from the original of Brouwer et al. in two subtle but important ways. The first is that we use stellar population models that are the same as we use for the kinematic data. This self-consistency is important to the continuity of the data. We (especially Jim Schombert) took a deep dive into this, and the models used by Brouwer et al. are consistent with ours for late type (spiral) galaxies (LTGs). However, ours are somewhat heavier^ for early type galaxies (ETGs). That’s part of the reason that they find an offset in the RAR between morphological types and we do not.
Another important difference is the strictness of the isolation criterion. We are trying to ascertain the average gravitational potential of isolated galaxies, those with no big neighbors to compound the lensing signal. Brouwer et al. required that there be no galaxies more than a tenth of the luminosity of the primary within 3 Mpc. That seems reasonable, but we explored lots of variations on both aspects of that limit. It seems to be fine for LTGs, but insufficient for ETGs. That in itself is not surprising, as ETGs are known to be more strongly clustered than LTGs, so it is harder to find isolated examples.
To illustrate this, we show the deviation of the data from the kinematic RAR fit as a function of the isolation criterion:
Figure 4 from Mistele et al. (2024a). Top: the difference between the radial accelerations inferred from weak lensing and the RAR fitting function, measured in sigmas, as a function of how isolated the lenses are, quantified by Risol. We separately show the result for ETGs (red) and LTGs (blue) as well as for small (triangles with dashed lines) and large accelerations (diamonds with solid lines). LTGs are mostly unaffected by making the isolation criterion stricter. In contrast, ETGs do depend on Risol, but tend towards with increasing Risol. Middle and bottom: the accelerations behind these sigma values for Risol = 3 Mpc/h70 and Risol = 4 Mpc/h70.
The top panel shows that LTGs do not deviate from the RAR as we vary the radius of isolation. In contrast, ETGs deviate a lot for small Risol. This is what Brouwer et al. found, and it would be a problem for MOND if LTGs and ETGs genuinely formed different sequences: it would be as if they were both obeying their own version of a similar but distinct MOND-like force law rather than a single universal force law.
That said, the ETGs converge towards the same RAR as the LTGs as we make the isolation criterion more strict. The distinction between ETGs and LTGs that appears to be clear for the Risol = 3 Mpc/h70 used by Brouwer et al. (middle panel) goes away when Risol = 4 Mpc/h70 (bottom panel). The random errors grow because fewer galaxies+ meet the stricter criterion, but this seems a price well worth paying to be rid of the systematic variation seen in the top panel. This also dictates how far out we can trust the data, which show no clear deviation from the RAR until below the limit gbar = 10−14 m/s2.
Regardless of the underlying theory, the data paint a consistent picture. This can be summarized by threeempiricallaws of galactic rotation:
Rotation curves become approximately* flat at large radii and remain so indefinitely.
The amplitude of the flat rotation speed scales with the baryonic mass as Mbar ~ Vf4 (the BTFR).
The observed centripetal acceleration follows from that predicted by the baryons (the RAR).
These are the galactic analogs of Kepler’s Laws for planetary motion. There is no theory in these statements; their just a description of what the data do. That’s useful, as they provide an empirical touchstone that has to be satisfactorily explained by any theory for it to be considered viable. No dark matter-based theory currently does that.
^The difference is well within the expected variance for stellar population models. We can reproduce their numbers if we treat ETGs as if they were just red LTGs. I don’t know if that’s what they did, but it ain’t right.
+For the record, the isolated fraction of the entire sample is 16%: most galaxies have neighbors. As a function of mass, the isolation criterion leaves a fraction of 8%, 18%, 30%, and 42% of LTG lenses and 9%, 14%, and 22% of ETG lenses, respectively, in each mass bin. The fraction of isolated LTGs is generally higher than ETGs, as expected. There is also a trend for the isolation fraction to increase as mass decreases. In part this is real; more luminous galaxies are more clustered. It may also be that it is easier for objects that exceed 10% of the primary mass (really luminosity) to evade detection as the primaries get fainter so 10% of that is harder to reach.
*Some people take “flat” way too seriously in this context. While it is often true that rotation curves look pretty darn flat over an extended radial range, I say approximately flat because we never measure, and can never measure, exactly a slope of dV/dR = 0.000. As a practical matter, we have adopted a variation of < 5% from point to point as a working definition. The scatter in Tully-Fisher naturally goes up if one adopts a weaker criterion; what one gets for the scatter is all about data quality.
Last time, we discussed the remarkable result that gravitational lensing extends the original remarkable result of flat rotation curves much farther out, as far as the data credibly probe. This corroborates and extends the result of Brouwer et al. They did a thorough job, but one thing they did not consider was Tully-Fisher. If the circular speed inferred from gravitational lensing remains constant, does this flat velocity fall on the same Tully-Fisher relation that is seen in kinematic data?
We set out to answer this question. Along the way, we did three new things: 1. Dr. Mistele derived an improved method for doing the lensing analysis, extending the radial range over which the data were credible. 2. He explored the criteria by which galaxies were judged to be isolated, finding a morphological type dependence on how far out one had to exclude. 3. We reanalyzed the stellar masses of the KiDS sample to be consistent with those we used when analyzing the kinematic data of SPARC galaxies. The first two are connected, as how far out we can trust the data depends on how well we can define a clean sample of isolated galaxies. The third resolved an apparent offset between early type galaxies (ETGs, aka ellipticals) and late type galaxies (LTGs, aka spirals) seen by Brouwer et al. That appears to be an artifact of stellar population modeling, as I suspected when I first discussed their result. We don’t need to do any fitting of the mass-to-light ratio; the the apparent offset between types disappears when we use use the same population models for both kinematic and lensing data.
I could write a lot about each of these, but most of it is the stuff of technical details that would be dull to many people. If you’re into that sort of thing, go and read the long science paper which is where such details reside. Here I just want to describe the Tully-Fisher result. Spoiler alert: it is the same as that from kinematics.
First off, I’m talking strictly about the Baryonic Tully-Fisher relation: the scaling between baryonic mass and the flat rotation speed. To address this, we bin the lensing data by mass. The mass of each bin is well defined by the average of the many thousands of galaxies within the bin. By far the dominant uncertainty is the systematic in stellar mass caused by stellar population modeling. We went through this with a fine tooth comb, and I’m confident we have an internally self-consistent result. That doesn’t preclude it being wrong in an absolute sense – such is the nature of astronomy – but we can at least make a straight comparison between kinematic and lensing data using the same best-effort stellar mass estimates.
For the velocity, we estimate the average effective rotation curve for each mass bin from the lensing data. We also split the data into morphological types to look for differences. The statistics go down when one divvies up the data like this, so the uncertainties go up, but there are enough KiDS galaxies to define four mass bins. Here are their inferred rotation curves:
Figure 1 from Mistele et al. (2024). Circular velocities implied by weak lensing for four baryonic mass bins (most to least massive from the top row to the bottom) for the whole sample (left column), for LTGs (middle column), and for ETGs (right column). The lowest ETG mass bin is not shown because it contains too few lenses. Instead we show results for lenses with spectroscopic redshifts from GAMA, without splitting by mass or type due to the small sample size (gray and white symbols). For comparison, we also show results for KiDS without splitting by mass or type (small yellow symbols). Open symbols at small radii indicate where lenses are not yet effective point masses. Light-colored symbols (not-outlined) at large radii indicate data points that may still be reliable but where the isolation criterion is less certain. The error bars show the statistical errors. Horizontal lines and the corresponding shaded regions indicate the inferred Vflat values and uncertainties that we use for the BTFR. The extent of the horizontal lines indicates the radial range we consider when calculating Vflat.
Note that the average over all KiDS data shown in the lower right bin is the data shown in the press release image in the previous post, but the x-axis is logarithmic here. The GAMA data in that bin provide an important cross-check, as these galaxies have spectroscopic redshifts. They give the same answer as the larger KiDS sample, which relies on photometric redshifts. We need the larger sample to consider finer bins in mass, which is the rest of the plot.
Another thing to note here is that all the data in all the bins are consistent with remaining flat. There are some hints of a turn down at very large radii, particularly for LTGs in the second and third row, but these are not statistically significant, and only happen where the data start to become untrustworthy. Where exactly that happens is a judgement call.
Let’s take a closer look, with a comparison to radio data:
Figure 2 from Mistele et al. (2024).The circular velocities from weak lensing (circles) compared with those from gas kinematics (diamonds). The individual galaxies illustrated here have among the most extended 21 cm rotation curves in their mass bins; the lensing data continue to much larger radii still. The error bars show the statistical error, while the gray band indicates the systematic uncertainty in the radial accelerations. Symbol colors are as in Figure 1. Open symbols at large radii indicate where lenses are not sufficiently isolated. The solid green lines indicate the circular velocities of NFW halos and baryonic point masses appropriate for each mass bin. Green crosses indicate each NFW halo’s virial radius. The light green band adds a qualitative estimate of a two-halo term contribution to the NFW halo, which may become important at large radii in case our isolation criterion is imperfect there.
Again we see that the lensing data, averaged over many galaxies, extend much further out than the rotation curve of any one individual. The x-axis is again logarithmic, so the lensing data go way further out. They trace to 1 Mpc, which is crazy far beyond the observed ends of the most extended individual galaxies. A more conservative limit is the 300 kpc estimated by Brouwer et al. Surely we can go further than that, but how much further remains a judgement call.
What should we expect? The green lines show the rotation curve we’d expect for galaxy in an NFW halo with parameters specified by the stellar mass-halo mass relation of Kravtsov et al. (2018). Not all such relations agree well with kinematic data; this is the case that agrees most closely. We have intentionally cherry-picked the relation that makes LCDM look best. And it does look good up to a point, for example in the top two mass bins out to the virial radius of the halo (tick marks). Beyond that, not so much, and not at all for the two lower mass bins. The data extend far enough out that we should see the predicted decline. We do not.
The green line only represents the expected halo of the primary galaxy. When one gets so far out, one has to worry about all the other stuff out there. We’ve selected galaxies to be isolated, so there isn’t much that is luminous. But we can only exclude down to some sensitivity limit, there might be lots of tiny dwarf galaxies whose mass adds up and starts to affect the result. And of course there can be completely invisible dark matter. The green band attempts to account for this extra stuff in the so-called 2-halo term. This is hard to do, but we’ve made our best estimate based on the LCDM power spectrum. I’m sure the 2-halo term can be adjusted, but the shape is wrong. It will take some fine-tuning to get an effectively flat rotation curve out of the 1-halo+2 halo terms. They don’t naturally do that.
Something that is easy to do is define a flat value of the rotation speed. That’s just the average over the lensing data. We exclude the points at R < 50 kpc, as the assumption of a spherical mass that we make in the lensing analysis isn’t really valid at those comparatively small scales. We tried averaging over a bunch of different ranges, all of which gave pretty much the same answer. For illustration, we show two cases: a conservative one that only uses the data at R < 300 kpc, and another that goes out to 1 Mpc. Having measured Vflat over these ranges, we can plot Tully-Fisher:
Figure 3 from Mistele et al. (2024). The baryonic Tully–Fisher relation implied by weak lensing for the entire sample (yellow symbols, left column) and for ETGs and LTGs separately (red and blue symbols, right column). The Vflat values are weighted averages of the Vc values shown in Figure 1 for 50 kpc < R < 300 kpc (first row) and 50 kpc < R < 1000 kpc (second row). Vertical error bars represent a 0.1 dex systematic uncertainty on M*/L. For comparison, we also show the best fit to the kinematic data from Lelli et al. (2019; solid gray line) and the corresponding binned kinematic data (white diamonds).
Lo and behold, we find the same Baryonic Tully-Fisher relation from lensing data as we find with kinematics. This does not surprise me, but it didn’t have to be true. It shouldn’t be true in LCDM: if we can measure out to the virial radius, we should see some indication of a decline in velocity. We have and we don’t.
We also see no statistically significant separation between ETGs and LTGs. This is important, as a theory like MOND predicts that there should be no morphology dependence: only the baryonic mass matters. Brouwer et al. did see an indication of such a split, but it was small compared to the uncertainty in stellar population models. We don’t see it when we use our own stellar mass estimates. This is particularly true in the more conservative (300 kpc) case. There is a hint of a segregation when we average out to 1000 kpc, but the statistics say this isn’t significant. Since the lowest mass bin is most affected, I suspect this is a hint that the isolation criterion is failing first for the smallest galaxies. That makes sense, as the sensitivity limit on interlopers makes the lowest mass bin most susceptible to having its signal inappropriately boosted. It also makes sense that ETGs would be affected first, as ETGs are known to be more clustered than LTGs. It is really hard to define an isolated sample of ETGs, as discussed at length by Mistele et al.
That hasn’t prevented people from overlooking these basic facts in order to get to the apparent if statistically meaningless difference between ETGs and LTGs. Nevermind the successes! The slight offset between ETGs and LTGs falsify MOND! Seriously: other scientists have already made this argument to me while completely eliding the successes of MOND. It’s a case of refusing to see the forest for a tree that’s a little away from the others.
I think I said something about how this would happen when I first wrote about Brouwer et al‘s lensing result. Ah yes, here it is:
MOND predicted this behavior well in advance of the observation, so one would have to bend over backwards, rub one’s belly, and simultaneously punch oneself in the face to portray this as anything short of a fantastic success of MOND.
I say that because I’m sure people will line up to punch themselves in the face in exactly this fashion.
And so it has come to pass. Sometimes human behavior is as predictable as galaxy dynamics.
*There are many claims to explain limited portions of these results, but none are satisfactory. There is no LCDM model that matches the entire dynamic range of the radial acceleration relation. See, for example, Fig. 5 of Brouwer et al. (reproduced below), which shows the MICE and BAHAMAS simulations. Neither extend into the regime that is well-constrained by kinematic data; there is no reason to think they would successfully do so and good reason to think otherwise. MICE comes nowhere close to this regime and has no baryonic physics that would allow it do even address this question. BAHAMAS comes close but appears to turn away from the kinematic data before it gets there. We’ve built our own LCDM models; they don’t work either. We can make them come close, but only over a limited dynamic range, not over the full span of the data. It isn’t good enough to only explain a limited range of the data. One has to explain the full range, and the only theory that does that so far is MOND.
Fig. 5 from Brouwer et al. showing the radial acceleration relation inferred from the MICE (red band) and BAHAMAS (orange band) simulations. Not also that in our assessment of stellar masses, the lower acceleration points translate a bit to the right.
That rotation curves become flat at large radii is one of the most famous results in extragalactic astronomy. This had been established by Vera Rubin and her collaborators by the late 1970s. There were a few earlier anecdotal cases to this effect, but these seemed like mild curiosities until Rubin showed that the same thing was true over and over again for a hundred spiral galaxies. Flat rotation curves took on the air of a de facto natural law and precipitated the modern dark matter paradigm.
Optical and radio data
Rotation curves shouldn’t be flat. If what we saw was what we got, the rotation curve would reach a peak within the light distribution and decline further out. Perhaps an illustration is in order:
The rotation curve (data points, left) of NGC 6946 (right). The red line shows the expected rotation curve for the detected normal matter, which includes both the stars (yellow, from 2MASS) and atomic gas (blue, from THINGS). This provides a good description of the inner rotation curve but falls short further out. The excess observed rotation leads to the need for dark matter or MOND. Also noted is the extent of the rotation curve measured optically to the effective edge of the stars (Daigle et al. 2006; Epinat et al. 2008) and that measured with radio interferometric observations of the gas (Boomsma et al. 2008).
An obvious question is how far out rotation curves remain flat. In the rotation curves traced with optical observations by Rubin et al., the discrepancy was clear but modest – typically a factor of two in mass. It was possible to imagine that the mass-to-light ratios of stars increased with radius in a systematic way, bending the red line above to match the data out to the edge of the stars. This seemed unlikely, but neither did it seem like a huge ask.
Once one gets to the edge of the stellar distribution, most of the mass has been encompassed, and the rotation curve really should start to decline. Increasing the mass-to-light ratio of the stars ceases to be an option once we run out of stars*. Fortunately, the atomic gas typically extends to larger radii, so provides a tracer further out. Albert Bosma pursued this until there were again enough examples to establish that yes, flat rotation curves were the rule. They extended much further out, well beyond where the mass of the observed stars and gas could explain the data.
How much further out? It depends on the galaxy. A convenient metric is the scale length of the disk, which is a measure of the extent of the light distribution. Some galaxies are bigger than others. The peak of the contribution of the stars to the rotation curve occurs around 2.2 scale lengths. The rotation curve of NGC 6946 extends to about 7 scale lengths, far enough to make the discrepancy clear. For a long time, the record holder was NGC 2403, with a rotation curve that remains flat for 20 scale lengths.
Twenty scale lengths is a long way out. It is observations like this that demanded dark matter halos that are much larger than the galaxies they contain. They also posed a puzzle, since we were still nowhere near finding the edge of the mass distribution. Rotation curves seemed to persist in being flat indefinitely.
Postdoc Tobias Mistele worked out an elegant technique to improve the analysis of lensing data. His analysis corroborates the findings of Brouwer et al. It also provides the opportunity to push further out.
Weak gravitational lensing is a subtle effect – so subtle that one must coadd thousands of galaxies to get a signal. Beyond that, the limiting effect on the result is how isolated the galaxies are. Lensing is sensitive to all mass; if you go far enough out you start to run into other galaxies whose mass contributes to the signal. So one key is to identify isolated galaxies, and restrict the sample to them. KiDS is large enough to do this. Indeed, Mistele was able to show that while neighbors+ were a definite concern for elliptical galaxies, they were much less of a problem for spirals. Consequently, we can trace the implied rotation curve way far out.
How far out? In a new paper, Mistele shows that rotation curves continue way far out. Way way way far out. I mean, damn.
The average rotation curve of isolated galaxies (blue points) inferred from KiDS gravitational lensing data. This remains flat well beyond a million light-years with no end in sight. The width of the figure is the distance between the Milky Way and Andromeda. For comparison, the rotation curve of a single galaxy, UGC 6614, is shown in red. An image of the galaxy is shown to scale centered at the origin. UGC 6614 was selected for this illustration because it has a comparable rotation speed to the KiDS average and because it is one of the largest galaxies known: the red points are already a very extended rotation curve. Image credit: Mistele, Lelli, & McGaugh 2024.
Optical rotation curves typically extend to the edge of the stellar disk. That’s about 8 kpc in the example of NGC 6946 given above. Radio observations of the atomic gas of that galaxy extend to 17 kpc. That fits within the first two tick marks on the graph with the lensing rotation curve.
UGC 6614 is a massive galaxy with a very extended low surface brightness disk. Its rotation curve is traced by radio data to over 60 kpc. It is one of the most extended individual rotation curves known. The statistical lensing data push this out by a factor of ten, and more, with no end in sight. The flat rotation curves found by Rubin and Bosma and everyone else appear to persist indefinitely.
So what does it mean? First, flat rotation curves really are a law of nature, in the same sense of Kepler’s laws of planetary motion. Galaxies don’t obey those planetary rules, they have their own set of rules. This is what nature does.
In terms of dark matter halos, the extent of isolated galaxy rotation curves is surprisingly large. Just as we come to the edge of the stellar disk, then the gas disk, we should eventually hit the edge of the dark matter halo. In principle we can imagine this to be arbitrarily large, but in practice there are other galaxies in the universe so this cannot go one forever.
In the context of LCDM, we now have a pretty good idea of how extended halos should be from abundance matching. A galaxy of the mass of UGC 6614 should live in a halo with a virial radius of about 300 kpc or less. There is some uncertainty in this, of course, but we really should have hit the edge with the lensing data. There should be some sign of it, but we see none.
One complication is the so-called 2-halo term. In addition to the primary dark matter halo that hosts a galaxy, when you get very far out, you run into other halos. Isolated galaxies are selected to avoid this to the extent possible, but eventually there will be some extra mass that causes extra lensing signal that would cause an overestimate of the rotation speed. I’ll forgo a detailed discussion of this for now (see Mistele et al. if you’re eager), but the bottom line is that it would require some unnatural fine-tuning for the 1+2 halo terms to add up to such flat rotation curves. There ought to be a perceptible feature in the transition from the primary halo to the surrounding environment. We don’t see that.
In the context of MOND, a flat rotation curve that persists indefinitely is completely natural. That’s what an isolated galaxy should do. Even in MOND there should be an environmental effect: the mass of everything else in the universe should impose an external field effect that eventually limits the extent of the rotation curve. How this transition happens depends on the density of other galaxies; by selecting isolated galaxies this effect is put off as much as possible. Hopefully it will be detected as the data improve from projects like Euclid.
The primary prediction of MOND is an indefinitely extended rotation curve; the external field effect is a subtle detail. Yet again, that is what we see: MOND gets it right without really trying, and in a way that makes little sense in terms of dark matter. Sometimes I wish MOND had never been invented so we could claim to have discovered something profoundly new, or at least discuss the empirical result without concern that the data would get confused with the theory. MOND predictions keep being corroborated, yet the community persists in ignoring its implications, even in terms of dark matter. It’s gotta be telling us something.
We have a press release about this result, so perhaps you will see it kicking around your news feed.
*We could, of course, invoke dark stars, but that’s just an invisible horse of a different color.
+There is a well known correlation between morphology and density such that elliptical galaxies tend to live in the densest environments. This means that they are more likely to have neighbors that interfere with the lensing measurement, so finding that identifying isolated ellipticals with a clean lensing signal is more challenging that finding isolated spirals comes as no surprise. Isolated ellipticals do exist so it is possible, but one has to be very restrictive with the sample.
