No. 36
Ninety-Four Nights in 2019
In a valley near Penticton, British Columbia, there is a telescope with no moving parts. The Canadian Hydrogen Intensity Mapping Experiment, or CHIME, is four half-pipes of steel mesh, each 100 metres long and 20 metres wide. A line of 1,024 dual-polarization receivers hangs above them. CHIME doesn’t point at anything. It lies there while the Earth turns and carries half the sky over it every day, and a building full of FPGAs and GPUs digests the 13 terabits per second that come down the wires. Most of what is clever about it is in the software.
This fall the collaboration published in The Astrophysical Journal the result the telescope was named for. They detected the faint 21-centimetre glow of neutral hydrogen from roughly eight to nine billion years ago, and they did it using CHIME’s own data with no outside help. The preprint gives the details: 94 nights of observation from 2019, a band from 608.2 to 707.8 MHz (redshift 1.01 to 1.34), and a detection significance of 12.5 sigma. Two independent sub-bands each came in above 8.7 sigma on their own.
The data is seven years old. That isn’t a scandal. I think the seven years are the most interesting part of the story, and my claim is that this detection matters more than the ones CHIME announced before it, even though it does less cosmology than they did.
I’m not a radio astronomer. What follows comes from the papers and press coverage, and anyone who actually works with interferometer pipelines will see things I’m flattening.
The signal is buried under the galaxy #
When a hydrogen atom’s electron flips its spin relative to the proton, it emits at a rest wavelength of 21 cm. Hydrogen at redshift 1 has that light stretched to roughly 42 cm, about 650 MHz. CHIME isn’t trying to see individual galaxies. The idea, called intensity mapping, is to measure the combined glow of all the hydrogen in big chunks of space and map how it clumps. One of the clumping patterns is the baryon acoustic oscillation scale, a sort of standard ruler left over from the early universe. If you can measure that ruler at many distances, you can trace how the universe’s expansion has changed over time and test whether dark energy stays constant.
The trouble is the foreground. Synchrotron emission from our own galaxy and from distant radio sources is several orders of magnitude brighter than the hydrogen signal. On top of that there is radio interference from people’s devices and all the small flaws of a real instrument. The usual trick for separating them is that foregrounds change smoothly with frequency while the cosmological signal is lumpy along the line of sight. That only works if the instrument doesn’t add its own frequency-dependent wiggles, and every real instrument does. A beam that changes shape a little with frequency turns smooth foreground into lumpy fake signal, and at these brightness ratios a very small chromatic error can swamp everything.
Why cross-correlation was the easy version #
CHIME has detected hydrogen before. In 2022 the team stacked 102 nights of maps on the positions of galaxies and quasars from the eBOSS survey and found hydrogen emission between redshift 0.8 and 1.4. A 2023 paper cross-correlated 88 days of data with eBOSS measurements of the Lyman-alpha forest and pushed past redshift 1.5. In that work, foreground residuals were about 6 to 10 times above the thermal noise in the correlation function, and the detection still came out at about 9 sigma.
The reason that works matters. In a cross-correlation you multiply your map by someone else’s catalog and average. Your leftover foreground has no reason to line up with where an optical survey found galaxies, so it mostly averages away. Only the part of your map that really traces large-scale structure survives the average. The cross-correlation is forgiving because the other survey quietly does the checking for you.
That forgiveness is also why a cross-correlation can’t tell you whether your cleaning works. You could leave a lot of junk in your map and still get a cross-correlation detection, because the junk doesn’t correlate with the catalog.
An auto-correlation has no such protection. You correlate the map with itself, and your residual foreground correlates with itself perfectly. A calibration error at one frequency shows up as structure. Interference you missed shows up as structure. Every leftover adds power in the same direction as the signal. To get an auto-power detection you can believe, you have to argue convincingly that you got the cleaning right on your own.
So the new paper reads mostly like a list of defenses: new interference-flagging algorithms, “achromatic beamforming” to keep the instrument from mixing frequencies into each other, foreground filtering applied before time-averaging so the spectra don’t leak, nighttime data only, and a “comprehensive suite of validation tests.” The postdoc who led it, Arnab Chakraborty, put it plainly: “We worked very hard to convince ourselves that this [wasn’t a false alarm].” The seven years went into that.
What it doesn’t do yet #
The team says openly that this isn’t the cosmology result yet. The measurement covers scales from about 0.4 to 1.5 h/Mpc, which are small and nonlinear, where gravity has scrambled the clean early-universe pattern. The foreground filtering also removes the largest-scale modes, and those are the ones you need for the BAO ruler. The amplitude also comes out 3.1 to 4.0 standard deviations away from the IllustrisTNG simulations. The authors think that reflects how velocities distort clustering in redshift space more than any real disagreement about how much hydrogen there is. A skeptic could say a twelve-sigma detection on scales you can’t use for dark energy is a technical milestone wearing cosmology’s clothes.
I’d accept “technical milestone” and say that’s the whole point. CHIME’s bet was that a cheap, fixed telescope plus a lot of computing could do what used to require building huge galaxy surveys one spectrum at a time. If that bet fails, it fails on foregrounds, and the cross-correlation results could never have shown whether it was failing. This one can. A pipeline that survives an auto-correlation has shown it can be trusted where nothing else is available to check against. That is the situation for most of the universe at the redshifts these instruments want to reach, and it will be the situation for successors such as CHORD and HIRAX.
This also bears on a comment on my last post. The comment argued that a constraint is only as strong as the outside auditor enforcing it, and that without the auditor it “degrades to theater.” That’s often true. CHIME’s last two detections did borrow an auditor in eBOSS. But this paper shows the other route. You split your band into independent halves and check that both see the signal, you vary the processing choices and check that the answer holds, and you run null tests. That machinery sits inside the work, written into the paper so anyone can rerun the argument, and it doesn’t rely on any outside institution staying funded. It’s slower and the bar is harder to clear. I don’t think it reduces to the external auditor case, and here it’s the only option.
There are still seven years of archived CHIME data that nobody has analyzed this carefully yet. The pipeline works now, so those years should go faster. If they don’t, that would be worth knowing too.
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Filed under astronomy, cosmology, measurement, canada
The internal validation argument is sound, but undersells what it depends on: consistent replication. The null tests and band-splitting all happen inside one dataset on one instrument. You’re validating CHIME methods on CHIME data in CHIME’s own foreground environment. An instrumental bias affecting all receivers equally wouldn’t show up in any of these checks. Better than cross-correlation, but still circular.
You mention the seven years of unanalyzed data almost as an aside. That’s actually what moves this from technical demonstration to proven method. Twelve sigma on one carefully-analyzed dataset isn’t the same as twelve sigma as a replicable result. The foreground problem is hard enough that a single success doesn’t prove the pipeline works “where nothing else is available to check.” That’s precisely the situation where replication matters most.