Too Massive? New measurement of the W boson’s mass sparks intrigue

This is part one of our coverage of the CDF W mass result covering its implications. Read about the details of the measurement in a sister post here!

Last week the physics world was abuzz with the latest results from an experiment that stopped running a decade ago. Some were heralding this as the beginning of a breakthrough in fundamental physics, headlines read “Shock result in particle experiment could spark physics revolution” (BBC). So what exactly is all the fuss about?

The result itself is an ultra-precise measurement of the mass of the W boson. The W boson is one of the carriers of weak force and this measurement pegged its mass at 80,433 MeV with an uncertainty of 9 MeV. The excitement is coming because this value disagrees with the prediction from our current best theory of particle physics, the Standard Model. In theoretical structure of the Standard Model the masses of the gauge bosons are all interrelated. In the Standard Model the mass of the W boson can be computed based on the mass of the Z as well as few other parameters in the theory (like the weak mixing angle). In a first approximation (ie to the lowest order in perturbation theory), the mass of the W boson is equal to the mass of the Z boson times the cosine of the weak mixing angle. Based on other measurements that have been performed including the Z mass, the Higgs mass, the lifetime of muons and others, the Standard Model predicts that the mass of the W boson should be 80,357 (with an uncertainty of 6 MeV). So the two numbers disagree quite strongly, at the level of 7 standard deviations.

If the measurement and the Standard Model prediction are both correct, this would imply that there is some deficiency in the Standard Model; some new particle interacting with the W boson whose effects haven’t been unaccounted for. This would be welcome news to particle physicists, as we know that the Standard Model is an incomplete theory but have been lacking direct experimental confirmation of its deficiencies. The size of the discrepancy would also mean that whatever new particle was causing the deviation may also be directly detectable within our current or near future colliders.

If this discrepancy is real, exactly what new particles would this entail? Judging based on the 30+ (and counting) papers released on the subject in the last week, there are a good number of possibilities. Some examples include extra Higgs bosons, extra Z-like bosons, and vector-like fermions. It would take additional measurements and direct searches to pick out exactly what the culprit was. But it would hopefully give experimenters definite targets of particles to look for, which would go a long way in advancing the field.

But before everyone starts proclaiming the Standard Model dead and popping champagne bottles, its important to take stock of this new CDF measurement in the larger context. Measurements of the W mass are hard, that’s why it has taken the CDF collaboration over 10 years to publish this result since they stopped taking data. And although this measurement is the most precise one to date, several other W mass measurements have been performed by other experiments.

The Other Measurements

A plot summarizing the various W mass measurements performed to date
A summary of all the W mass measurements performed to date (black dots) with their uncertainties (blue bars) as compared to the the Standard Model prediction (yellow band). One can see that this new CDF result is in tension with previous measurements. (source)

Previous measurements of the W mass have come from experiments at the Large Electron-Positron collider (LEP), another experiment at the Tevatron (D0) and experiments at the LHC (ATLAS and LHCb). Though none of these were as precise as this new CDF result, they had been painting a consistent picture of a value in agreement with the Standard Model prediction. If you take the average of these other measurements, their value differs from the CDF measurement the level about 4 standard deviations, which is quite significant. This discrepancy seems large enough that it is unlikely to arise from purely random fluctuation, and likely means that either some uncertainties have been underestimated or something has been overlooked in either the previous measurements or this new one.

What one would like are additional, independent, high precision measurements that could either confirm the CDF value or the average value of the previous measurements. Unfortunately it is unlikely that such a measurement will come in the near future. The only currently running facility capable of such a measurement is the LHC, but it will be difficult for experiments at the LHC to rival the precision of this CDF one.

W mass measurements are somewhat harder at the LHC than the Tevatron for a few reasons. First of all the LHC is proton-proton collider, while the Tevatron was a proton-antiproton collider, and the LHC also operates at a higher collision energy than the Tevatron. Both differences cause W bosons produced at the LHC to have more momentum than those produced at the Tevatron. Modeling of the W boson’s momentum distribution can be a significant uncertainty of its mass measurement, and the extra momentum of W’s at the LHC makes this a larger effect. Additionally, the LHC has a higher collision rate, meaning that each time a W boson is produced there are actually tens of other collisions laid on top (rather than only a few other collisions like at the Tevatron). These extra collisions are called pileup and can make it harder to perform precision measurements like these. In particular for the W mass measurement, the neutrino’s momentum has to be inferred from the momentum imbalance in the event, and this becomes harder when there are many collisions on top of each other. Of course W mass measurements are possible at the LHC, as evidenced by ATLAS and LHCb’s already published results. And we can look forward to improved results from ATLAS and LHCb as well as a first result from CMS. But it may be very difficult for them to reach the precision of this CDF result.

A histogram of the transverse mass of the W from the ATLAS result. Showing how 50 MeV shifts in the W mass change the spectrum by extremely small amounts (a few tenths of a percent).
A plot of the transverse mass (one of the variables used in a measurement) of the W from the ATLAS measurement. The red and yellow lines show how little the distribution changes if the W mass changes by 50 MeV, which is around two and half times the uncertainty of the ATLAS result. These shifts change the distribution by only a few tenths of a percent, illustrating the difficulty involved. (source)

The Future

A future electron positron collider would be able to measure the W mass extremely precisely by using an alternate method. Instead of looking at the W’s decay, the mass could be measured through its production, by scanning the energy of the electron beams very close to the threshold to produce two W bosons. This method should offer precision significantly better than even this CDF result. However any measurement from a possible future electron positron collider won’t come for at least a decade.

In the coming months, expect this new CDF measurement to receive a lot buzz. Experimentalists will be poring over the details trying to figure out why it is in tension with previous measurements and working hard to produce new measurements from LHC data. Meanwhile theorists will write a bunch of papers detailing the possibilities of what new particles could explain the discrepancy and if there is a connection to other outstanding anomalies (like the muon g-2). But the big question of whether we are seeing the first real crack in the Standard Model or there is some mistake in one or more of the measurements is unlikely to be answered for a while.

If you want to learn about how the measurement actually works, check out this sister post!

Read More:

Cern Courier “CDF sets W mass against the Standard Model

Blog post on the CDF result from an (ATLAS) expert on W mass measurements “[Have we] finally found new physics with the latest W boson mass measurement?”

PDG Review “Electroweak Model and Constraints on New Physics

The Mini and Micro Boone Mystery, Part 1 Experiment

Title: “Search for an Excess of Electron Neutrino Interactions in MicroBooNE Using Multiple Final State Topologies”

Authors: The MiniBoone Collaboration

Reference: https://arxiv.org/abs/2110.14054

This is the first post in a series on the latest MicroBooNE results, covering the experimental side. Click here to read about the theory side. 

The new results from the MicroBoone experiment received a lot of excitement last week, being covered by several major news outlets. But unlike most physics news stories that make the press, it was a null result; they did not see any evidence for new particles or interactions. So why is it so interesting? Particle physics experiments produce null results every week, but what made this one newsworthy is that MicroBoone was trying to check the results from two previous experiments LSND and MiniBoone, that did see something anomalous with very high statistical evidence. If the LSND/MiniBoone result was confirmed, it would have been a huge breakthrough in particle physics, but now that it wasn’t many physicists are scratching their heads trying to make sense of these seemingly conflicting results. However, the MicroBoone experiment is not exactly the same as MiniBoone/LSND, and understanding the differences between the two sets of experiments may play an important role in unraveling this mystery.

Accelerator Neutrino Basics

All of these experiments are ‘accelerator neutrino experiments’, so lets first review what that means. Neutrino’s are ‘ghostly’ particles that are difficult to study (check out this post for more background on neutrinos).  Because they only couple through the weak force, neutrinos don’t like to interact with anything very much. So in order to detect them you need both a big detector with a lot of active material and a source with a lot of neutrinos. These experiments are designed to detect neutrinos produced in a human-made beam. To make the beam, a high energy beam of protons is directed at a target. These collisions produce a lot of particles, including unstable bound states of quarks like pions and kaons. These unstable particles have charge, so we can use magnets to focus them into a well-behaved beam.  When the pions and kaons decay they usually produce a muon and a muon neutrino. The beam of pions and kaons is pointed at an underground detector located a few hundred meters (or kilometers!) away, and then given time to decay. After they decay there will be a nice beam of muons and muon neutrinos. The muons can be stopped by some kind of shielding (like the earth’s crust), but the neutrinos will sail right through to the detector.

A diagram showing the basics of how a neutrino beam is made. Source

Nearly all of the neutrinos from the beam will still pass right through your detector, but a few of them will interact, allowing you to learn about their properties.

All of these experiments are considered ‘short-baseline’ because the distance between the neutrino source and the detector is only a few hundred meters (unlike the hundreds of kilometers in other such experiments). These experiments were designed to look for oscillation of the beam’s muon neutrinos into electron neutrinos which then interact with their detector (check out this post for some background on neutrino oscillations). Given the types of neutrinos we know about and their properties, this should be too short of a distance for neutrinos to oscillate, so any observed oscillation would be an indication something new (beyond the Standard Model) was going on.

The LSND + MiniBoone Anomaly

So the LSND and MiniBoone ‘anomaly’ was an excess of events above backgrounds that looked like electron neutrinos interacting with their detector. Both detectors were based on similar technology and were a similar distance from their neutrino source. Their detectors were essentially big tanks of mineral oil lined with light-detecting sensors.

An engineer styling inside the LSND detector. Source

At these energies the most common way neutrinos interact is to scatter against a neutron to produce a proton and a charged lepton (called a ‘charged current’ interaction). Electron neutrinos will produce outgoing electrons and muon neutrinos will produce outgoing muons.

A diagram of a ‘charged current’ interaction. A muon neutrino comes in and scatters against a neutron, producing a muon and a proton. Source

When traveling through the mineral oil these charged leptons will produce a ring of Cherenkov light which is detected by the sensors on the edge of the detector. Muons and electrons can be differentiated based on the characteristics of the Cherenkov light they emit. Electrons will undergo multiple scatterings off of the detector material while muons will not. This makes the Cherenkov rings of electrons ‘fuzzier’ than those of muons. High energy photons can produce electrons positron pairs which look very similar to a regular electron signal and are thus a source of background. 

A comparison of muon and electron Cherenkov rings from the Super-Kamiokande experiment. Electrons produce fuzzier rings than muons. Source

Even with a good beam and a big detector, the feebleness of neutrino interactions means that it takes a while to get a decent number of potential events. The MiniBoone experiment ran for 17 years looking for electron neutrinos scattering in their detector. In MiniBoone’s most recent analysis, they saw around 600 more events than would be expected if there were no anomalous electron neutrinos reaching their detector. The statistical significance of this excess, 4.8-sigma, was very high. Combining with LSND which saw a similar excess, the significance was above 6-sigma. This means its very unlikely this is a statistical fluctuation. So either there is some new physics going on or one of their backgrounds has been seriously under-estimated. This excess of events is what has been dubbed the ‘MiniBoone anomaly’.

The number of events seen in the MiniBoone experiment as a function of the energy seen in the interaction. The predicted number of events from various known background sources are shown in the colored histograms. The best fit to the data including the signal of anomalous oscillations is shown by the dashed line. One can see that at low energies the black data points lie significantly above these backgrounds and strongly favor the oscillation hypothesis.

The MicroBoone Result

The MicroBoone experiment was commissioned to verify the MiniBoone anomaly as well as test out a new type of neutrino detector technology. The MicroBoone is the first major neutrino experiment to use a ‘Liquid Argon Time Projection Chamber’ detector. This new detector technology allows more detailed reconstruction of what is happening when a neutrino scatters in the detector. The the active volume of the detector is liquid Argon, which allows both light and charge to propagate through it. When a neutrino scatters in the liquid Argon, scintillation light is produced that is collected in sensors. As charged particles created in the collision pass through the liquid Argon they ionize atoms they pass by. An electric field applied to the detector causes this produced charge to drift towards a mesh of wires where it can be collected. By measuring the difference in arrival time between the light and the charge, as well as the amount of charge collected at different positions and times, the precise location and trajectory of the particles produced in the collision can be determined. 

A beautiful reconstructed event in the MicroBoone detector. The colored lines show the tracks of different particles produced in the collision, all coming from a single point where the neutrino interaction took place. One can also see that one of the tracks produced a shower of particles away from the interaction vertex.

This means that unlike the MiniBoone and LSND, MicroBoone can see not just the lepton, but also the hadronic particles (protons, pions, etc) produced when a neutrino scatters in their detector. This means that the same type of neutrino interaction actually looks very different in their detector. So when they went to test the MiniBoone anomaly they adopted multiple different strategies of what exactly to look for. In the first case they looked for the type of interaction that an electron neutrino would have most likely produced: an outgoing electron and proton whose kinematics match those of a charged current interaction. Their second set of analyses, designed to mimic the MiniBoone selection, are slightly more general. They require one electron and any number of protons, but no pions. Their third analysis is the most general and requires an electron along with anything else. 

These different analyses have different levels of sensitivity to the MiniBoone anomaly, but all of them are found to be consistent with a background-only hypothesis: there is no sign of any excess events. Three out of four of them even see slightly less events than the expected background. 

A summary of the different MicroBoone analyses. The Y-axis shows the ratio of observed to expected number of events expected if there was only background present. The red lines show the excess predicted to be seen if the MiniBoone anomaly produced a signal in each channel. One can see that the black data points are much more consistent with the grey bands showing the background only prediction than amount predicted if the MiniBoone anomaly was present.

Overall the MicroBoone data rejects the hypothesis that the MiniBoone anomaly is due to electron neutrino charged current interactions at quite high significance (>3sigma). So if its not electron neutrinos causing the MiniBoone anomaly, what is it?

What’s Going On?

Given that MicroBoone did not see any signal, many would guess that MiniBoone’s claim of an excess must be flawed and they have underestimated one of their backgrounds. Unfortunately it is not very clear what that could be. If you look at the low-energy region where MiniBoone has an excess, there are three major background sources: decays of the Delta baryon that produce a photon (shown in tan), neutral pions decaying to pairs of photons (shown in red), and backgrounds from true electron neutrinos (shown in various shades of green). However all of these sources of background seem quite unlikely to be the source of the MiniBoone anomaly.

Before releasing these results, MicroBoone performed a dedicated search for Delta baryons decaying into photons, and saw a rate in agreement with the theoretical prediction MiniBoone used, and well below the amount needed to explain the MiniBoone excess.

Backgrounds from true electron neutrinos produced in the beam, as well as from the decays of muons, should not concentrate only at low energies like the excess does, and their rate has also been measured within MiniBoone data by looking at other signatures.

The decay of a neutral pions can produce two photons, and if one of them escapes detection, a single photon will mimic their signal. However one would expect that it would be more likely that photons would escape the detector near its edges, but the excess events are distributed uniformly in the detector volume.

So now the mystery of what could be causing this excess is even greater. If it is a background, it seems most likely it is from an unknown source not previously considered. As will be discussed in our part 2 post, its possible that MiniBoone anomaly was caused by a more exotic form of new physics; possibly the excess events in MiniBoone were not really coming from the scattering of electron neutrinos but something else that produced a similar signature in their detector. Some of these explanations included particles that decayed into pairs of electrons or photons. These sorts of explanations should be testable with MicroBoone data but will require dedicated analyses for their different signatures.

So on the experimental side, we now we are left to scratch our heads and wait for new results from MicroBoone that may help get to the bottom of this.

Click here for part 2 of our MicroBoone coverage that goes over the theory side of the story!

Read More

Is the Great Neutrino Puzzle Pointing to Multiple Missing Particles?” – Quanta Magazine article on the new MicroBoone result

“Can MiniBoone be Right?” – Resonaances blog post summarizing the MiniBoone anomaly prior to the the MicroBoone results

A review of different types of neutrino detectors – from the T2K experiment

How to find invisible particles in a collider

 You might have heard that one of the big things we are looking for in collider experiments are ever elusive dark matter particles. But given that dark matter particles are expected to interact very rarely with regular matter, how would you know if you happened to make some in a collision? The so called ‘direct detection’ experiments have to operate giant multi-ton detectors in extremely low-background environments in order to be sensitive to an occasional dark matter interaction. In the noisy environment of a particle collider like the LHC, in which collisions producing sprays of particles happen every 25 nanoseconds, the extremely rare interaction of the dark matter with our detector is likely to be missed. But instead of finding dark matter by seeing it in our detector, we can instead find it by not seeing it. That may sound paradoxical, but its how most collider based searches for dark matter work. 

The trick is based on every physicists favorite principle: the conservation of energy and momentum. We know that energy and momentum will be conserved in a collision, so if we know the initial momentum of the incoming particles, and measure everything that comes out, then any invisible particles produced will show up as an imbalance between the two. In a proton-proton collider like the LHC we don’t know the initial momentum of the particles along the beam axis, but we do that they were traveling along that axis. That means that the net momentum in the direction away from the beam axis (the ‘transverse’ direction) should be zero. So if we see a momentum imbalance going away from the beam axis, we know that there is some ‘invisible’ particle traveling in the opposite direction.

A sketch of what the signature of an invisible particle would like in a detector. Note this is a 2D cross section of the detector, with the beam axis traveling through the center of the diagram. There are two signals measured in the detector moving ‘up’ away from the beam pipe. Momentum conservation means there must have been some particle produced which is traveling ‘down’ and was not measured by the detector. Figure borrowed from here  

We normally refer to the amount of transverse momentum imbalance in an event as its ‘missing momentum’. Any collisions in which an invisible particle was produced will have missing momentum as tell-tale sign. But while it is a very interesting signature, missing momentum can actually be very difficult to measure. That’s because in order to tell if there is anything missing, you have to accurately measure the momentum of every particle in the collision. Our detectors aren’t perfect, any particles we miss, or mis-measure the momentum of, will show up as a ‘fake’ missing energy signature. 

A picture of a particularly noisy LHC collision, with a large number of tracks
Can you tell if there is any missing energy in this collision? Its not so easy… Figure borrowed from here

Even if you can measure the missing energy well, dark matter particles are not the only ones invisible to our detector. Neutrinos are notoriously difficult to detect and will not get picked up by our detectors, producing a ‘missing energy’ signature. This means that any search for new invisible particles, like dark matter, has to understand the background of neutrino production (often from the decay of a Z or W boson) very well. No one ever said finding the invisible would be easy!

However particle physicists have been studying these processes for a long time so we have gotten pretty good at measuring missing energy in our events and modeling the standard model backgrounds. Missing energy is a key tool that we use to search for dark matter, supersymmetry and other physics beyond the standard model.

Read More:

What happens when energy goes missing?” ATLAS blog post by Julia Gonski

How to look for supersymmetry at the LHC“, blog post by Matt Strassler

“Performance of missing transverse momentum reconstruction with the ATLAS detector using proton-proton collisions at √s = 13 TeV” Technical Paper by the ATLAS Collaboration

“Search for new physics in final states with an energetic jet or a hadronically decaying W or Z boson and transverse momentum imbalance at √s= 13 TeV” Search for dark matter by the CMS Collaboration

Measuring the Tau’s g-2 Too

Title : New physics and tau g2 using LHC heavy ion collisions

Authors: Lydia Beresford and Jesse Liu

Reference: https://arxiv.org/abs/1908.05180

Since April, particle physics has been going crazy with excitement over the recent announcement of the muon g-2 measurement which may be our first laboratory hint of physics beyond the Standard Model. The paper with the new measurement has racked up over 100 citations in the last month. Most of these papers are theorists proposing various models to try an explain the (controversial) discrepancy between the measured value of the muon’s magnetic moment and the Standard Model prediction. The sheer number of papers shows there are many many models that can explain the anomaly. So if the discrepancy is real,  we are going to need new measurements to whittle down the possibilities.

Given that the current deviation is in the magnetic moment of the muon, one very natural place to look next would be the magnetic moment of the tau lepton. The tau, like the muon, is a heavier cousin of the electron. It is the heaviest lepton, coming in at 1.78 GeV, around 17 times heavier than the muon. In many models of new physics that explain the muon anomaly the shift in the magnetic moment of a lepton is proportional to the mass of the lepton squared. This would explain why we are a seeing a discrepancy in the muon’s magnetic moment and not the electron (though there is a actually currently a small hint of a deviation for the electron too). This means the tau should be 280 times more sensitive than the muon to the new particles in these models. The trouble is that the tau has a much shorter lifetime than the muon, decaying away in just 10-13 seconds. This means that the techniques used to measure the muons magnetic moment, based on magnetic storage rings, won’t work for taus. 

Thats where this new paper comes in. It details a new technique to try and measure the tau’s magnetic moment using heavy ion collisions at the LHC. The technique is based on light-light collisions (previously covered on Particle Bites) where two nuclei emit photons that then interact to produce new particles. Though in classical electromagnetism light doesn’t interact with itself (the beam from two spotlights pass right through each other) at very high energies each photon can split into new particles, like a pair of tau leptons and then those particles can interact. Though the LHC normally collides protons, it also has runs colliding heavier nuclei like lead as well. Lead nuclei have more charge than protons so they emit high energy photons more often than protons and lead to more light-light collisions than protons. 

Light-light collisions which produce tau leptons provide a nice environment to study the interaction of the tau with the photon. A particles magnetic properties are determined by its interaction with photons so by studying these collisions you can measure the tau’s magnetic moment. 

However studying this process is be easier said than done. These light-light collisions are “Ultra Peripheral” because the lead nuclei are not colliding head on, and so the taus produced generally don’t have a large amount of momentum away from the beamline. This can make them hard to reconstruct in detectors which have been designed to measure particles from head on collisions which typically have much more momentum. Taus can decay in several different ways, but always produce at least 1 neutrino which will not be detected by the LHC experiments further reducing the amount of detectable momentum and meaning some information about the collision will lost. 

However one nice thing about these events is that they should be quite clean in the detector. Because the lead nuclei remain intact after emitting the photon, the taus won’t come along with the bunch of additional particles you often get in head on collisions. The level of background processes that could mimic this signal also seems to be relatively minimal. So if the experimental collaborations spend some effort in trying to optimize their reconstruction of low momentum taus, it seems very possible to perform a measurement like this in the near future at the LHC. 

The authors of this paper estimate that such a measurement with a the currently available amount of lead-lead collision data would already supersede the previous best measurement of the taus anomalous magnetic moment and further improvements could go much farther. Though the measurement of the tau’s magnetic moment would still be far less precise than that of the muon and electron, it could still reveal deviations from the Standard Model in realistic models of new physics. So given the recent discrepancy with the muon, the tau will be an exciting place to look next!

Read More:

An Anomalous Anomaly: The New Fermilab Muon g-2 Results

When light and light collide

Another Intriguing Hint of New Physics Involving Leptons

Machine Learning The LHC ABC’s

Article Title: ABCDisCo: Automating the ABCD Method with Machine Learning

Authors: Gregor Kasieczka, Benjamin Nachman, Matthew D. Schwartz, David Shih

Reference: arxiv:2007.14400

When LHC experiments try to look for the signatures of new particles in their data they always apply a series of selection criteria to the recorded collisions. The selections pick out events that look similar to the sought after signal. Often they then compare the observed number of events passing these criteria to the number they would expect to be there from ‘background’ processes. If they see many more events in real data than the predicted background that is evidence of the sought after signal. Crucial to whole endeavor is being able to accurately estimate the number of events background processes would produce. Underestimate it and you may incorrectly claim evidence of a signal, overestimate it and you may miss the chance to find a highly sought after signal.

However it is not always so easy to estimate the expected number of background events. While LHC experiments do have high quality simulations of the Standard Model processes that produce these backgrounds they aren’t perfect. Particularly processes involving the strong force (aka Quantum Chromodynamics, QCD) are very difficult to simulate, and refining these simulations is an active area of research. Because of these deficiencies we don’t always trust background estimates based solely on these simulations, especially when applying very specific selection criteria.

Therefore experiments often employ ‘data-driven’ methods where they estimate the amount background events by using control regions in the data. One of the most widely used techniques is called the ABCD method.

An illustration of the ABCD method. The signal region, A, is defined as the region in which f and g are greater than some value. The amount of background in region A is estimated using regions B C and D which are dominated by background.

The ABCD method can applied if the selection of signal-like events involves two independent variables f and g. If one defines the ‘signal region’, A,  (the part of the data in which we are looking for a signal) as having f  and g each greater than some amount, then one can use the neighboring regions B, C, and D to estimate the amount of background in region A. If the number of signal events outside region A is small, the number of background events in region A can be estimated as N_A = N_B * (N_C/N_D).

In modern analyses often one of these selection requirements involves the score of a neural network trained to identify the sought after signal. Because neural networks are powerful learners one often has to be careful that they don’t accidentally learn about the other variable that will be used in the ABCD method, such as the mass of the signal particle. If two variables become correlated, a background estimate with the ABCD method will not be possible. This often means augmenting the neural network either during training or after the fact so that it is intentionally ‘de-correlated’ with respect to the other variable. While there are several known techniques to do this, it is still a tricky process and often good background estimates come with a trade off of reduced classification performance.

In this latest work the authors devise a way to have the neural networks help with the background estimate rather than hindering it. The idea is rather than training a single network to classify signal-like events, they simultaneously train two networks both trying to identify the signal. But during this training they use a groovy technique called ‘DisCo’ (short for Distance Correlation) to ensure that these two networks output is independent from each other. This forces the networks to learn to use independent information to identify the signal. This then allows these networks to be used in an ABCD background estimate quite easily.

The authors try out this new technique, dubbed ‘Double DisCo’, on several examples. They demonstrate they are able to have quality background estimates using the ABCD method while achieving great classification performance. They show that this method improves upon the previous state of the art technique of decorrelating a single network from a fixed variable like mass and using cuts on the mass and classifier to define the ABCD regions (called ‘Single Disco’ here).

Using the task of identifying jets containing boosted top quarks, they compare the classification performance (x-axis) and quality of the ABCD background estimate (y-axis) achievable with the new Double DisCo technique (yellow points) and previously state of the art Single DisCo (blue points). One can see the Double DisCo method is able to achieve higher background rejection with a similar or better amount of ABCD closure.

While there have been many papers over the last few years about applying neural networks to classification tasks in high energy physics, not many have thought about how to use them to improve background estimates as well. Because of their importance, background estimates are often the most time consuming part of a search for new physics. So this technique is both interesting and immediately practical to searches done with LHC data. Hopefully it will be put to use in the near future!

Further Reading:

Quanta Magazine Article “How Artificial Intelligence Can Supercharge the Search for New Particles

Recent ATLAS Summary on New Machine Learning Techniques “Machine learning qualitatively changes the search for new particles

CERN Tutorial on “Background Estimation with the ABCD Method

Summary of Paper of Previous Decorrelation Techniques used in ATLAS “Performance of mass-decorrelated jet substructure observables for hadronic two-body decay tagging in ATLAS

The XENON1T Excess : The Newest Craze in Particle Physics

Paper: Observation of Excess Electronic Recoil Events in XENON1T

Authors: XENON1T Collaboration

Recently the particle physics world has been abuzz with a new result from the XENON1T experiment who may have seen a revolutionary signal. XENON1T is one of the world’s most sensitive dark matter experiments. The experiment consists of a huge tank of Xenon placed deep underground in the Gran Sasso mine in Italy. It is a ‘direct-detection’ experiment, hunting for very rare signals of dark matter particles from space interacting with their detector. It was originally designed to look for WIMP’s, Weakly Interacting Massive Particles, who used to be everyone’s favorite candidate for dark matter. However, given recent null results by WIMP-hunting  direct-detection experiments, and collider experiments at the LHC, physicists have started to broaden their dark matter horizons. Experiments like XENON1T, who were designed to look for heavy WIMP’s colliding off of Xenon nuclei have realized that they can also be very sensitive to much lighter particles by looking for electron recoils. New particles that are much lighter than traditional WIMP’s would not leave much of an impact on large Xenon nuclei, but they can leave a signal in the detector if they instead scatter off of the electrons around those nuclei. These electron recoils can be identified by the ionization and scintillation signals they leave in the detector, allowing them to be distinguished from nuclear recoils.

In this recent result, the XENON1T collaboration searched for these electron recoils in the energy range of 1-200 keV with unprecedented sensitivity.  Their extraordinary sensitivity is due to its exquisite control over backgrounds and extremely low energy threshold for detection. Rather than just being impressed, what has gotten many physicists excited is that the latest data shows an excess of events above expected backgrounds in the 1-7 keV region. The statistical significance of the excess is 3.5 sigma, which in particle physics is enough to claim ‘evidence’ of an anomaly but short of the typical 5-sigma required to claim discovery.

The XENON1T data that has caused recent excitement. The ‘excess’ is the spike in the data (black points) above the background model (red line) in the 1-7 keV region. The significance of the excess is around 3.5 sigma.

So what might this excess mean? The first, and least fun answer, is nothing. 3.5 sigma is not enough evidence to claim discovery, and those well versed in particle physics history know that there have been numerous excesses with similar significances have faded away with more data. Still it is definitely an intriguing signal, and worthy of further investigation.

The pessimistic explanation is that it is due to some systematic effect or background not yet modeled by the XENON1T collaboration. Many have pointed out that one should be skeptical of signals that appear right at the edge of an experiments energy detection threshold. The so called ‘efficiency turn on’, the function that describes how well an experiment can reconstruct signals right at the edge of detection, can be difficult to model. However, there are good reasons to believe this is not the case here. First of all the events of interest are actually located in the flat part of their efficiency curve (note the background line is flat below the excess), and the excess rises above this flat background. So to explain this excess their efficiency would have to somehow be better at low energies than high energies, which seems very unlikely. Or there would have to be a very strange unaccounted for bias where some higher energy events were mis-reconstructed at lower energies. These explanations seem even more implausible given that the collaboration performed an electron reconstruction calibration using the radioactive decays of Radon-220 over exactly this energy range and were able to model the turn on and detection efficiency very well.

Results of a calibration done to radioactive decays of Radon-220. One can see that data in the efficiency turn on (right around 2 keV) is modeled quite well and no excesses are seen.

However the possibility of a novel Standard Model background is much more plausible. The XENON collaboration raises the possibility that the excess is due to a previously unobserved background from tritium β-decays. Tritium decays to Helium-3 and an electron and a neutrino with a half-life of around 12 years. The energy released in this decay is 18.6 keV, giving the electron having an average energy of a few keV. The expected energy spectrum of this decay matches the observed excess quite well. Additionally, the amount of contamination needed to explain the signal is exceedingly small. Around 100 parts-per-billion of H2 would lead to enough tritium to explain the signal, which translates to just 3 tritium atoms per kilogram of liquid Xenon. The collaboration tries their best to investigate this possibility, but they neither rule out or confirm such a small amount of tritium contamination. However, other similar contaminants, like diatomic oxygen have been confirmed to be below this level by 2 orders of magnitude, so it is not impossible that they were able to avoid this small amount of contamination.

So while many are placing their money on the tritium explanation, there is the exciting possibility remains that this is our first direct evidence of physics Beyond the Standard Model (BSM)! So if the signal really is a new particle or interaction what would it be? Currently it it is quite hard to pin down exactly based on the data. The analysis was specifically searching for two signals that would have shown up in exactly this energy range: axions produced in the sun, and neutrinos produced in the sun interacting with electrons via a large (BSM) magnetic moment. Both of these models provide good fits to the signal shape, with the axion explanation being slightly preferred. However since this result has been released, many have pointed out that these models would actually be in conflict with constraints from astrophysical measurements. In particular, the axion model they searched for would have given stars an additional way to release energy, causing them to cool at a faster rate than in the Standard Model. The strength of interaction between axions and electrons needed to explain the XENON1T excess is incompatible with the observed rates of stellar cooling. There are similar astrophysical constraints on neutrino magnetic moments that also make it unlikely.

This has left door open for theorists to try to come up with new explanations for these excess events, or think of clever ways to alter existing models to avoid these constraints. And theorists are certainly seizing this opportunity! There are new explanations appearing on the arXiv every day, with no sign of stopping. In the roughly 2 weeks since the XENON1T announced their result and this post is being written, there have already been 50 follow up papers! Many of these explanations involve various models of dark matter with some additional twist, such as being heated up in the sun or being boosted to a higher energy in some other way.

A collage of different models trying to explain the XENON1T excess (center). Each plot is from a separate paper released in the first week and a half following the original announcement. Source

So while theorists are currently having their fun with this, the only way we will figure out the true cause of this this anomaly is with more data. The good news is that the XENON collaboration is already preparing for the XENONnT experiment that will serve as a follow to XENON1T. XENONnT will feature a larger active volume of Xenon and a lower background level, allowing them to potentially confirm this anomaly at the 5-sigma level with only a few months of data. If  the excess persists, more data would also allow them to better determine the shape of the signal; allowing them to possibly distinguish between the tritium shape and a potential new physics explanation. If real, other liquid Xenon experiments like LUX and PandaX should also be able to independently confirm the signal in the near future. The next few years should be a very exciting time for these dark matter experiments so stay tuned!

Read More:

Quanta Magazine Article “Dark Matter Experiment Finds Unexplained Signal”

Previous ParticleBites Post on Axion Searches

Blog Post “Hail the XENON Excess”

Listening for axions

If dark matter actually consists of a new kind of particle, then the most up-and-coming candidate is the axion. The axion is a consequence of the Peccei-Quinn mechanism, a plausible solution to the “strong CP problem,” or why the strong nuclear force conserves the CP-symmetry although there are no reasons for it to. It is a very light neutral boson, named by Frank Wilczek after a detergent brand (in a move that obviously dates its introduction in the ’70s).

Axion decay in a magnetic field: the result is a photon. (Source.)

Most experiments that try to directly detect dark matter have looked for WIMPs (weakly interacting massive particles). However, as those searches have not borne fruit, the focus started turning to axions, which make for good candidates given their properties and the fact that if they exist, then they exist in multitudes throughout the galaxies. Axions “speak” to the QCD part of the Standard Model, so they can appear in interaction vertices with hadronic loops. The end result is that axions passing through a magnetic field will convert to photons.

In practical terms, their detection boils down to having strong magnets, sensitive electronics and an electromagnetically very quiet place at one’s disposal. One can then sit back and wait for the hypothesized axions to pass through the detector as earth moves through the dark matter halo surrounding the Milky Way. Which is precisely why such experiments are known as “haloscopes.”

Now, the most veteran haloscope of all published significant new results. Alas, it is still empty-handed, but we can look at why its update is important and how it was reached.

ADMX (Axion Dark Matter eXperiment) of the University of Washington has been around for a quarter-century. By listening for signals from axions, it progressively gnaws away at the space of allowed values for their mass and coupling to photons, focusing on an area of interest:

ADMX_results_2020
Latest exclusion limits on the axion mass and coupling to photons.

Unlike higher values, this area is not excluded by astrophysical considerations (e.g. stars cooling off through axion emission) and other types of experiments (such as looking for axions from the sun). In addition, the bands above the lines denoted “KSVZ” and “DFSZ” are special. They correspond to the predictions of two models with favorable theoretical properties. So, ADMX is dedicated to scanning this parameter space. And the new analysis added one more year of data-taking, making a significant dent in this ballpark.

As mentioned, the presence of axions would be inferred from a stream of photons in the detector. The excluded mass range was scanned by “tuning” the experiment to different frequencies, while at each frequency step longer observation times probed smaller values for the axion-photon coupling.

Two things that this search needs is a lot of quiet and some good amplification, as the signal from a typical axion is expected to be as weak as the signal from a mobile phone left on the surface of Mars (around 10-23W). The setup is indeed stripped of noise by being placed in a dilution refrigerator, which keeps its temperature at a few tenths of a degree above absolute zero. This is practically the domain governed by quantum noise, so advantage can be taken of the finesse of quantum technology: for the first time ADMX used SQUIDs, superconducting quantum interference devices, for the amplification of the signal.

The heart of the experiment inside the refrigerator. The resonant frequency of the cavity is tuned to match the photons -hopefully- given off by axions. (Source.)




In the end, a good chunk of the parameter space which is favored by the theory might have been excluded, but the haloscope is ready to look at the rest of it. Just think of how, one day, a pulse inside a small device in a university lab might be a messenger of the mysteries unfolding across the cosmos.

References:

Publication by the ADMX collaboration. (arXiv)

Learn more:

  1. The theory behind axions.
  2. The hitchhiker’s guide to the dilution refrigerator.
  3. Intro to KSVZ and DFSZ axions (and more).
  4. Resonant cavities.

Three Birds with One Particle: The Possibilities of Axions

Title: “Axiogenesis”

Author: Raymond T. Co and Keisuke Harigaya

Reference: https://arxiv.org/pdf/1910.02080.pdf

On the laundry list of problems in particle physics, a rare three-for-one solution could come in the form of a theorized light scalar particle fittingly named after a detergent: the axion. Frank Wilczek coined this term in reference to its potential to “clean up” the Standard Model once he realized its applicability to multiple unsolved mysteries. Although Axion the dish soap has been somewhat phased out of our everyday consumer life (being now primarily sold in Latin America), axion particles remain as a key component of a physicist’s toolbox. While axions get a lot of hype as a promising dark matter candidate, and are now being considered as a solution to matter-antimatter asymmetry, they were originally proposed as a solution for a different Standard Model puzzle: the strong CP problem. 

The strong CP problem refers to a peculiarity of quantum chromodynamics (QCD), our theory of quarks, gluons, and the strong force that mediates them: while the theory permits charge-parity (CP) symmetry violation, the ardent experimental search for CP-violating processes in QCD has so far come up empty-handed. What does this mean from a physical standpoint? Consider the neutron electric dipole moment (eDM), which roughly describes the distribution of the three quarks comprising a neutron. Naively, we might expect this orientation to be a triangular one. However, measurements of the neutron eDM, carried out by tracking changes in neutron spin precession, return a value orders of magnitude smaller than classically expected. In fact, the incredibly small value of this parameter corresponds to a neutron where the three quarks are found nearly in a line. 

The classical picture of the neutron (left) looks markedly different from the picture necessitated by CP symmetry (right). The strong CP problem is essentially a question of why our mental image should look like the right picture instead of the left. Source: https://arxiv.org/pdf/1812.02669.pdf

This would not initially appear to be a problem. In fact, in the context of CP, this makes sense: a simultaneous charge conjugation (exchanging positive charges for negative ones and vice versa) and parity inversion (flipping the sign of spatial directions) when the quark arrangement is linear results in a symmetry. Yet there are a few subtleties that point to the existence of further physics. First, this tiny value requires an adjustment of parameters within the mathematics of QCD, carefully fitting some coefficients to cancel out others in order to arrive at the desired conclusion. Second, we do observe violation of CP symmetry in particle physics processes mediated by the weak interaction, such as kaon decay, which also involves quarks. 

These arguments rest upon the idea of naturalness, a principle that has been invoked successfully several times throughout the development of particle theory as a hint toward the existence of a deeper, more underlying theory. Naturalness (in one of its forms) states that such minuscule values are only allowed if they increase the overall symmetry of the theory, something that cannot be true if weak processes exhibit CP-violation where strong processes do not. This puts the strong CP problem squarely within the realm of “fine-tuning” problems in physics; although there is no known reason for CP symmetry conservation to occur, the theory must be modified to fit this observation. We then seek one of two things: either an observation of CP-violation in QCD or a solution that sets the neutron eDM, and by extension any CP-violating phase within our theory, to zero.

This term in the QCD Lagrangian allows for CP symmetry violation. Current measurements place the value of \theta at no greater than 10^{-10}. In Peccei-Quinn symmetry, \theta is promoted to a field.

When such an expected symmetry violation is nowhere to be found, where is a theoretician to look for such a solution? The most straightforward answer is to turn to a new symmetry. This is exactly what Roberto Peccei and Helen Quinn did in 1977, birthing the Peccei-Quinn symmetry, an extension of QCD which incorporates a CP-violating phase known as the \theta term. The main idea behind this theory is to promote \theta to a dynamical field, rather than keeping it a constant. Since quantum fields have associated particles, this also yields the particle we dub the axion. Looking back briefly to the neutron eDM picture of the strong CP problem, this means that the angular separation should also be dynamical, and hence be relegated to the minimum energy configuration: the quarks again all in a straight line. In the language of symmetries, the U(1) Peccei-Quinn symmetry is approximately spontaneously broken, giving us a non-zero vacuum expectation value and a nearly-massless Goldstone boson: our axion.

This is all great, but what does it have to do with dark matter? As it turns out, axions make for an especially intriguing dark matter candidate due to their low mass and potential to be produced in large quantities. For decades, this prowess was overshadowed by the leading WIMP candidate (weakly-interacting massive particles), whose parameter space has been slowly whittled down to the point where physicists are more seriously turning to alternatives. As there are several production-mechanisms in early universe cosmology for axions, and 100% of dark matter abundance could be explained through this generation, the axion is now stepping into the spotlight. 

This increased focus is causing some theorists to turn to further avenues of physics as possible applications for the axion. In a recent paper, Co and Harigaya examined the connection between this versatile particle and matter-antimatter asymmetry (also called baryon asymmetry). This latter term refers to the simple observation that there appears to be more matter than antimatter in our universe, since we are predominantly composed of matter, yet matter and antimatter also seem to be produced in colliders in equal proportions. In order to explain this asymmetry, without which matter and antimatter would have annihilated and we would not exist, physicists look for any mechanism to trigger an imbalance in these two quantities in the early universe. This theorized process is known as baryogenesis.

Here’s where the axion might play a part. The \theta term, which settles to zero in its possible solution to the strong CP problem, could also have taken on any value from 0 to 360 degrees very early on in the universe. Analyzing the axion field through the conjectures of quantum gravity, if there are no global symmetries then the initial axion potential cannot be symmetric [4]. By falling from some initial value through an uneven potential, which the authors describe as a wine bottle potential with a wiggly top, \theta would cycle several times through the allowed values before settling at its minimum energy value of zero. This causes the axion field to rotate, an asymmetry which could generate a disproportionality between the amounts of produced matter and antimatter. If the field were to rotate in one direction, we would see more matter than antimatter, while a rotation in the opposite direction would result instead in excess antimatter.

The team’s findings can be summarized in the plot above. Regions in purple, red, and above the orange lines (dependent upon a particular constant \xi which is proportional to weak scale quantities) signify excluded portions of the parameter space. The remaining white space shows values of the axion decay constant and mass where the currently measured amount of baryon asymmetry could be generated. Source: https://arxiv.org/pdf/1910.02080.pdf

Introducing a third fundamental mystery into the realm of axions begets the question of whether all three problems (strong CP, dark matter, and matter-antimatter asymmetry) can be solved simultaneously with axions. And, of course, there are nuances that could make alternative solutions to the strong CP problem more favorable or other dark matter candidates more likely. Like most theorized particles, there are several formulations of axion in the works. It is then necessary to turn our attention to experiment to narrow down the possibilities for how axions could interact with other particles, determine what their mass could be, and answer the all-important question: if they exist at all. Consequently, there are a plethora of axion-focused experiments up and running, with more on the horizon, that use a variety of methods spanning several subfields of physics. While these results begin to roll in, we can continue to investigate just how many problems we might be able to solve with one adaptable, soapy particle.

Learn More:

  1. A comprehensive introduction to the strong CP problem, the axion solution, and other potential solutions: https://arxiv.org/pdf/1812.02669.pdf 
  2. Axions as a dark matter candidate: https://www.symmetrymagazine.org/article/the-other-dark-matter-candidate
  3. More information on matter-antimatter asymmetry and baryogenesis: https://www.quantumdiaries.org/2015/02/04/where-do-i-come-from/
  4. The quantum gravity conjectures that axiogenesis builds upon: https://arxiv.org/abs/1810.05338
  5. An overview of current axion-focused experiments: https://www.annualreviews.org/doi/full/10.1146/annurev-nucl-102014-022120

LHCb’s Flavor Mystery Deepens

Title: Measurement of CP -averaged observables in the B0→ K∗0µ+µ− decay

Authors: LHCb Collaboration

Refference: https://arxiv.org/abs/2003.04831

In the Standard Model, matter is organized in 3 generations; 3 copies of the same family of particles but with sequentially heavier masses. Though the Standard Model can successfully describe this structure, it offers no insight into why nature should be this way. Many believe that a more fundamental theory of nature would better explain where this structure comes from. A natural way to look for clues to this deeper origin is to check whether these different ‘flavors’ of particles really behave in exactly the same ways, or if there are subtle differences that may hint at their origin.

The LHCb experiment is designed to probe these types of questions. And in recent years, they have seen a series of anomalies, tensions between data and Standard Model predictions, that may be indicating the presence of new particles which talk to the different generations. In the Standard Model, the different generations can only interact with each other through the W boson, which means that quarks with the same charge can only interact through more complicated processes like those described by ‘penguin diagrams’.

The so called ‘penguin diagrams’ describe how rare decays like bottom quark → strange quark can happen in the Standard Model. The name comes from both their shape and a famous bar bet. Who says physicists don’t have a sense of humor?

These interactions typically have quite small rates in the Standard Model, meaning that the rate of these processes can be quite sensitive to new particles, even if they are very heavy or interact very weakly with the SM ones. This means that studying these sort of flavor decays is a promising avenue to search for new physics.

In a press conference last month, LHCb unveiled a new measurement of the angular distribution of the rare B0→K*0μ+μ– decay. The interesting part of this process involves a b → s transition (a bottom quark decaying into a strange quark), where number of anomalies have been seen in recent years.

Feynman diagrams of the decay being studied. A B meson (composed of a bottom and a down quark) decays into a Kaon (composed of a strange quark and a down quark) and a pair of muons. Because this decay is very rare in the Standard Mode (left diagram) it could be a good place to look for the effects of new particles (right diagram). Diagrams taken from here

Rather just measuring the total rate of this decay, this analysis focuses on measuring the angular distribution of the decay products. They also perform this mesaurement in different bins of ‘q^2’, the dimuon pair’s invariant mass. These choices allow the measurement to be less sensitive to uncertainties in the Standard Model prediction due to difficult to compute hadronic effects. This also allows the possibility of better characterizing the nature of whatever particle may be causing a deviation.

The kinematics of decay are fully described by 3 angles between the final state particles and q^2. Based on knowing the spins and polarizations of each of the particles, they can fully describe the angular distributions in terms of 8 parameters. They also have to account for the angular distribution of background events, and distortions of the true angular distribution that are caused by the detector. Once all such effects are accounted for, they are able to fit the full angular distribution in each q^2 bin to extract the angular coefficients in that bin.

This measurement is an update to their 2015 result, now with twice as much data. The previous result saw an intriguing tension with the SM at the level of roughly 3 standard deviations. The new result agrees well with the previous one, and mildly increases the tension to the level of 3.4 standard deviations.

LHCb’s measurement of P’5, an observable describing one part of the angular distribution of the decay. The orange boxes show the SM prediction of this value and the red, blue and black point shows LHCb’s most recent measurement (a combination of its ‘Run 1’ measurement and the more recent 2016 data). The grey regions are excluded from the measurement because they have large backgrounds from the decays of other mesons.

This latest result is even more interesting given that LHCb has seen an anomaly in another measurement (the R_k anomaly) involving the same b → s transition. This had led some to speculate that both effects could be caused by a single new particle. The most popular idea is a so-called ‘leptoquark’ that only interacts with some of the flavors.

LHCb is already hard at work on updating this measurement with more recent data from 2017 and 2018, which should once again double the number of events. Updates to the R_k measurement with new data are also hotly anticipated. The Belle II experiment has also recent started taking data and should be able to perform similar measurements. So we will have to wait and see if this anomaly is just a statistical fluke, or our first window into physics beyond the Standard Model!

Read More:

Symmetry Magazine “The mystery of particle generations”

Cern Courier “Anomalies persist in flavour-changing B decays”

Lecture Notes “Introduction to Flavor Physcis”

Making Smarter Snap Judgments at the LHC

Collisions at the Large Hadron Collider happen fast. 40 million times a second, bunches of 1011 protons are smashed together. The rate of these collisions is so fast that the computing infrastructure of the experiments can’t keep up with all of them. We are not able to read out and store the result of every collision that happens, so we have to ‘throw out’ nearly all of them. Luckily most of these collisions are not very interesting anyways. Most of them are low energy interactions of quarks and gluons via the strong force that have been already been studied at previous colliders. In fact, the interesting processes, like ones that create a Higgs boson, can happen billions of times less often than the uninteresting ones.

The LHC experiments are thus faced with a very interesting challenge, how do you decide extremely quickly whether an event is interesting and worth keeping or not? This what the ‘trigger’ system, the Marie Kondo of LHC experiments, are designed to do. CMS for example has a two-tiered trigger system. The first level has 4 microseconds to make a decision and must reduce the event rate from 40 millions events per second to 100,000. This speed requirement means the decision has to be made using at the hardware level, requiring the use of specialized electronics to quickly to synthesize the raw information from the detector into a rough idea of what happened in the event. Selected events are then passed to the High Level Trigger (HLT), which has 150 milliseconds to run versions of the CMS reconstruction algorithms to further reduce the event rate to a thousand per second.

While this system works very well for most uses of the data, like measuring the decay of Higgs bosons, sometimes it can be a significant obstacle. If you want to look through the data for evidence of a new particle that is relatively light, it can be difficult to prevent the trigger from throwing out possible signal events. This is because one of the most basic criteria the trigger uses to select ‘interesting’ events is that they leave a significant amount of energy in the detector. But the decay products of a new particle that is relatively light won’t have a substantial amount of energy and thus may look ‘uninteresting’ to the trigger.

In order to get the most out of their collisions, experimenters are thinking hard about these problems and devising new ways to look for signals the triggers might be missing. One idea is to save additional events from the HLT in a substantially reduced size. Rather than saving the raw information from the event, that can be fully processed at a later time, instead the only the output of the quick reconstruction done by the trigger is saved. At the cost of some precision, this can reduce the size of each event by roughly two orders of magnitude, allowing events with significantly lower energy to be stored. CMS and ATLAS have used this technique to look for new particles decaying to two jets and LHCb has used it to look for dark photons. The use of these fast reconstruction techniques allows them to search for, and rule out the existence of, particles with much lower masses than otherwise possible. As experiments explore new computing infrastructures (like GPU’s) to speed up their high level triggers, they may try to do even more sophisticated analyses using these techniques. 

But experimenters aren’t just satisfied with getting more out of their high level triggers, they want to revamp the low-level ones as well. In order to get these hardware-level triggers to make smarter decisions, experimenters are trying get them to run machine learning models. Machine learning has become very popular tool to look for rare signals in LHC data. One of the advantages of machine learning models is that once they have been trained, they can make complex inferences in a very short amount of time. Perfect for a trigger! Now a group of experimentalists have developed a library that can translate the most popular types machine learning models into a format that can be run on the Field Programmable Gate Arrays used in lowest level triggers. This would allow experiments to quickly identify events from rare signals that have complex signatures that the current low-level triggers don’t have time to look for. 

The LHC experiments are working hard to get the most out their collisions. There could be particles being produced in LHC collisions already but we haven’t been able to see them because of our current triggers, but these new techniques are trying to cover our current blind spots. Look out for new ideas on how to quickly search for interesting signatures, especially as we get closer the high luminosity upgrade of the LHC.

Read More:

CERN Courier article on programming FPGA’s

IRIS HEP Article on a recent workshop on Fast ML techniques

CERN Courier article on older CMS search for low mass dijet resonances

ATLAS Search using ‘trigger-level’ jets

LHCb Search for Dark Photons using fast reconstruction based on a high level trigger

Paper demonstrating the feasibility of running ML models for jet tagging on FPGA’s