Measuring distance in the Universe is very challenging—you can't simply run a tape measure out to the Cosmic Microwave Background. What astronomers have done instead is find classes of objects that have a consistent brightness. By measuring how much dimmer than the expected value an object is, you can infer its distance. These objects have been termed "standard candles."

The most useful object for measuring great distances is the type Ia supernova. These supernovae are created when a white dwarf star reaches a specific mass, which triggers a thermonuclear explosion. Since the explosions always happen through the same process, it's thought that the light output is always more or less the same. Type Ia supernova have thus been used to measure the expansion of the Universe out to great distances. They're what were used to spot the apparent acceleration of the expansion, which led to the recognition that much of the Universe is composed of dark energy, a feature we know extremely little about.

Recently, however, a paper was published that suggests that these distance estimates may not be entirely reliable. The supernovae, it seems, are not quite as standard as we thought.

To an extent, we already knew this. When astronomers build collections of these distant objects, they already throw out a few well-described anomalous events, termed things like "narrow-peaked" supernovae or supernova type Iax. They also throw out anything that looks unusual. What they're left with is a set of events that all look similar, which makes it more likely for them to behave as standard candles.

But even then, the authors of the new paper point out, there may be differences among the population. We can't necessarily discriminate between events triggered by mass accumulating on the surface of a white dwarf and explosions that occur when two white dwarfs collide. There are also several different explosive mechanism (such as delayed detonation and double detonation). Finally, the exact composition of the star that's exploding—the different elements that were present in the star itself or in the nearby environment—could influence the light released when it explodes.

In other words, every supernova is probably unique. The question is whether their properties vary in some systematic way with distance. If not, then the randomness can cancel itself out, and our distance measurements will, on average, be reliable.

The key point of the new paper is that the properties actually vary with distance. In this case, the specific property that the authors looked at is the luminosity in the UV portion of the spectrum. There appear to be two types of supernova Ia in the UV: in one case, which the researchers call Near UV-red, the peaks on the red side of the UV spectrum are somewhat higher. For NUV-blue, the opposite is true: peaks at the blue-end are a bit higher. By examining these objects closely, the authors were able to determine that NUV-red events eject debris at a higher velocity than NUV-blue ones, suggesting they are slightly different events.

They then went on to show that the frequency of these two events varies with distance. In the relatively nearby portion of the Universe, nearly 70 percent of the type Ia supernovae are NUV-red. At greater distances, the fractions shift until roughly 90 percent of the explosions are NUV-blue.

This doesn't directly affect how we measure the distance, but it does affect how we measure how much dust the light from these explosions passes through. Since this dust dims the light a bit, it's compensated for when we calculate the final distance measurement. So it's this compensation that may be a bit off. The authors created a model population of supernovae and showed that the calculated distance started off being slightly high and then gradually decreased.

Does this mean that we can get rid of dark energy? Absolutely not. The authors recognize that their analysis was pretty limited and only contained simulated explosions. But they argue that there's enough cause here to go back and look carefully at the real thing to see if the potential problems they've identified turn out to exist in the real data sets used for these studies. Only when we know that will we be in a position to judge whether the data is off by enough to modify some of the earlier work.

The Astrophysical Journal, 2015. DOI: 10.1088/0004-637X/803/1/20 (About DOIs).