Research, teaching and public engagement in Physics at UW–Madison
High Energy
In search of new particles like the Higgs Boson
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Could there be more particles like the Higgs boson? For the first time, the CMS experiment has searched for the decay of the Higgs boson into two more Higgs-boson-like particles with unequal masses.
Some theories suggest that the Higgs boson might occasionally decay into particles that have never been seen before and have Higgs-boson-like properties. These new particles are unstable and quickly decay to known Standard Model particles in the CMS detector. While past CMS results have explored scenarios where the Higgs boson decays to such short-lived particles of identical masses, in this study we searched for a new possibility: what if the Higgs boson decays into two different new particles instead of two identical ones?
Calling the new particles ɸ1 and ϕ2 (ϕ2 is the heavier one), we consider cases where one of the ɸ decays to two bottom quarks, and the other decays to two 𝜏 leptons. This final state is favourable, since it has a relatively large probability of occurring and can be used to select interesting signal-like events from our datasets.
If the ϕ2 particle is at least twice as heavy as ϕ1, it could decay into an intermediate state with two ϕ1 before these decay into Standard Model particles. “We call this ‘cascade’ decay,” says Ashling Quinn, a PhD student working on the analysis, “since the extra step makes it resemble a waterfall.” So the decays can look like: H→ ɸ1ϕ2 → 2𝜏2b (non-cascade) or H→ ɸ1ϕ2 → 2𝜏4b (cascade). These are shown in the figure below.
Schematic (Feynman) diagrams depicting cascade (left) and non-cascade (right) decays of the Higgs boson into new Higgs-boson-like particles.
The strategy of this search is to reconstruct the decay of the ɸ1 boson into two 𝜏 leptons and to obtain the ɸ1 mass distribution. The presence of the ɸ1 signal is expected to appear as a peak on top of a flat background distribution.
To enhance the separation between signal and background events, we trained a machine learning model with several kinematic distributions as input. Another PhD student, Anagha Aravind, describes how this works: “Since the ɸ bosons have relatively low mass, their final state will be collimated in a narrow cone. The machine learning model exploits this feature, along with other subtle differences, to classify events as either signal or background.”
No significant excess of events was observed in the mass distribution. Upper limits were extracted on the rates – or “cross section” – of the considered processes for a range of ɸ1, ϕ2 boson masses. These results provide valuable constraints on theoretical models predicting such signatures and help guide future theoretical and experimental efforts.
Upper limits on the rates – or “cross section” – of the considered processes. Mass of the lighter new particle ɸ1 on the x-axis and the heavier ɸ2 on the y-axis.
This was the first search within the CMS Collaboration for Higgs boson decays into two Higgs-boson-like particles with unequal masses. The results pave the way for a promising future: the dominant source of uncertainty was statistical, which means more data from Run 3 and the High-Luminosity LHC will improve the sensitivity. If we think of ourselves as detectives hunting for new particles, more data means more clues to solve the mystery.
WIPAC scientists observe a spectral change in the astrophysical neutrino flux
The IceCube Neutrino Observatory, embedded in a cubic kilometer of Antarctic ice, searches for weakly interacting particles called neutrinos that are able to travel undisturbed through the cosmos. Of interest are high-energy astrophysical neutrinos that can arise from cosmic ray interactions with matter or photons in astrophysical sources. Thus far, the dominant sources of the [...]
Congrats to UW–Madison physics Prof. Sau Lan Wu, who announced her retirement effective January 1, 2026. One of the first two women on the physics faculty when she joined as an assistant professor in 1977, her nearly 50-year career stands as one of the most consequential in modern experimental particle physics.
“Sau Lan is truly remarkable and irreplaceable,” says UW–Madison experimental particle physicist and department chair Kevin Black. “If I accomplish even one-third of what she has in her career, I will consider myself incredibly successful.”
Rising from humble beginnings in Hong Kong to becoming a central figure in high energy physics, Wu’s path began at Vassar College, where she graduated summa cum laude in 1963. She then earned her MA and PhD from Harvard, part of the first cohort of women ever awarded graduate degrees directly from the university. After a postdoctoral fellowship and research appointment at MIT, she joined UW–Madison as an assistant professor in 1977, was promoted to associate professor in 1980, and to full professor in 1983. She earned the UW–Madison titles of Enrico Fermi Professor, Hilldale Professor, and Vilas Professor.
From her earliest days in the field, Wu gravitated toward the biggest scientific frontiers. She played key roles in three landmark particle discoveries: the charm quark in 1974 as part of Samuel Ting’s MIT/Brookhaven team; the gluon in 1979 through her pioneering work identifying three-jet events at DESY; and the Higgs boson in 2012, where her ATLAS group helped lead analyses of the H→γγ and H→ZZ*→4ℓ decay channels. Each discovery reshaped the Standard Model, and collectively they earned her a reputation as one of particle physics’ most influential experimentalists.
The UW–Madison ATLAS group at CERN at the time of the Higgs discovery all celebrated with printouts of the data confirming 5sigma. | Provided by Sau Lan Wu
Wu is a Fellow of the American Physical Society and the American Academy of Arts & Sciences, a recipient of the European Physical Society Prize, and shared the 2025 Breakthrough Prize in Fundamental Physics with the LHC collaboration. In 2022, the International Astronomical Union named a minor planet, Saulanwu, in her honor.
Through all these achievements, Wu remained devoted to guiding the next generation of experimental physics. 65 doctoral students completed their PhDs in her group, on major experiments from PETRA to LEP, BaBar, and the LHC. Of her former students and postdocs, 40 now hold faculty positions worldwide, and 18 are permanent staff scientists at major laboratories. Many others have gone on to high-impact roles in national science policy and the technology sector.
Says Steve Ritz, distinguished professor of physics at the University of California Santa Cruz and the Santa Cruz Institute for Particle Physics and a former student with Wu:
“Sau Lan pointed the way toward the most interesting questions, and she made sure we had what we needed for success. We always knew that we could try new approaches to problems and that she had our backs if we hit a bump in the road. She also made sure we didn’t just bury ourselves in our own work: there seemed to be a constant flow of great physicists visiting the group, and Sau Lan introduced us to each one. We were encouraged to attend their seminars and we were invited to lunch and dinner discussions. I now understand that Sau Lan was helping us develop our own sense of belonging in the field, while also pushing us to reach our full potential.”
John Conway, distinguished professor in the Department of Physics and Astronomy at UC Davis and former postdoc in Wu’s group, adds:
“I worked with Sau Lan as a postdoc on the ALEPH experiment at CERN for over five years. It was a fantastic time — her group was super lively and carrying out a lot of different work on the experiment, and which was then brand new. Sau Lan instilled in me the hunger for discovery that I have carried through the rest of my career, and demonstrated what it meant to be truly dedicated to this work. She was an inspiring leader and had genuine concern for the lives and careers of everyone who worked for her. I’ve tried to pay that forward in my own career.”
Sau Lan Wu and other Higgs scientists were featured on the cover of the New York Times for a story about the chase for the Higgs boson.
Even in the later stages of her career, Wu remained at the forefront of innovation. She championed the integration of artificial intelligence and machine learning into experimental physics, leading ATLAS’s first event-level anomaly detection study and advancing GNN-based tracking, GAN-based simulation, and early quantum machine learning applications for high energy physics. These efforts have helped prepare the field for the data-intensive future of the HighLuminosity‑ LHC beginning later this decade.
Wu has been featured on the front page of The New York Times, profiled in Quanta and Wired, invited to write for Scientific American, and highlighted in seven books celebrating scientific trailblazers and women in STEM, many aimed at sharing the excitement of discovery with children. The UW–Madison alumni magazine, On Wisconsin, featured her in a lengthy profile in 2019. She has delivered Vassar’s 150th Commencement Address, appeared on the cover of the AIP History Newsletter, and continued to be a sought-after speaker, including keynotes at SLAC in 2024 commemorating the 50th anniversary of the J/ψ discovery.
“Sau Lan is a legend in the field of experimental particle physics,” says Sridhara Dasu, an experimental particle physics professor at UW–Madison. “Her experiences will be inspiring for generations to come.”
IceCube Neutrino Observatory gets a major upgrade beneath the ice
Interdisciplinary physicist Mariel Pettee uses techniques grounded in machine learning to study a range of topics that span high energy physics and astrophysics, with an ultimate goal of developing a better understanding of the fundamental physical building blocks of our Universe.
Originally from Dallas, TX, Pettee was a physics and mathematics undergraduate at Harvard University, a master’s student in physics at the University of Cambridge, and a PhD student in physics at Yale University. While pursuing a postdoc at Lawrence Berkeley National Lab, she also joined the Flatiron Institute in New York City as a guest researcher. She then joined the UW–Madison physics faculty as part of the RISE-AI initiative in August 2025.
Please give an overview of your research.
My background is in high energy physics, and that training has fundamentally shaped the way I approach my work. But over the past several years, I have become more of what you might call a “data physicist” — someone with physics expertise who works at the intersection of physics and data science. In particular, I’m interested in how machine learning can help us do interdisciplinary physics research and make discoveries using massive experimental datasets that would otherwise be out of our reach.
On a broad scale, my research touches on high energy particle physics and astrophysics through the lens of machine learning. Some of my work applies recent machine learning techniques to domain-specific problems such as anomaly detection, object reconstruction, and unfolding. Another part of my work explores core questions in machine learning in areas such as self-supervised learning and likelihood-free inference in a physics-driven way. I’m also interested in developing large-scale foundation models for broader scientific use.
What are one or two main projects you’ll have your group focus on first?
The field of scientific foundation models has been rapidly taking shape over the last couple of years, but there are still a lot of open questions to explore. By researching what might make training foundation models on fundamental physics data distinct from training on more common industry-standard data, I think there is significant potential to understand our data more deeply.
I’m interested in simultaneously incorporating information from multiple heterogeneous layers of a detector, e.g. time series, images, and point clouds, as well as across detectors. Early projects in this direction will develop a variety of self-supervised learning strategies on multimodal HEP and astrophysics data to understand how models can simultaneously incorporate many different types of measurements of the same physics objects.
I’m also interested in studying stellar streams, which are remnants of ancient galaxies or globular clusters being absorbed into the Milky Way and serve as interesting tracers of local dark matter. The first step is to simply detect more of them using unsupervised or weakly supervised anomaly detection: trying to learn with no labels or with imperfect or missing labels. We can use machine learning models to automatically detect resonant anomalies in data, and stellar streams emerge as resonant anomalies in velocity space due to their constituents’ shared origin.
I’m optimistic that we will also eventually be able to use aggregate stream information to better map local dark matter substructure. Beyond their immediate physics use cases, streams can also serve as a nice testbed for understanding the limits of domain transfer for foundation models due to their resonant properties: perhaps particle physics data, with its 3D point cloud structure and “bump”-like anomalies, has more shared information with streams from the perspective of a foundation model than one might initially expect.
What attracted you to Madison and the university?
I felt a strong fit with Madison and the university from my first visit. I think that’s a combination of the general spirit of the department, how warm and open it felt, and how much I admired the researchers that I met when I was here. Also, the nature of the position that I was offered gave me the kind of flexibility that I dreamed of — to work and move between these spaces of high energy physics, astrophysics, and machine learning with a lot of freedom.
What is your favorite element and/or elementary particle?
Well, I have to pick a particle! I got into physics because of the Higgs boson. I started my physics career as an undergraduate at CERN on July 1st, 2012, and then the discovery of the Higgs boson was announced three days later. So I think I have the Higgs to thank for really getting me energized about this field. Waking up so early that morning, witnessing those presentations, seeing hundreds of people buzzing with excitement, scribbling on chalkboards, popping champagne corks — it made me feel like I was in the center of the universe.
What hobbies and interests do you have?
I love the performing arts of all kinds—contemporary dance, theater, music. I’m a dancer, choreographer, and occasional actor and director. I’m also an amateur birdwatcher.
“Rival” neutrino experiments NOvA and T2K publish first joint analysis
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The combined results add to physicists’ understanding and validate the impressive collaborative effort between two competing — yet complementary — experiments.
This story was published by Fermilab
When the universe began, physicists expect there should have been equal amounts of matter and antimatter. But if that were so, the matter and antimatter should have perfectly canceled each other out, resulting in total annihilation.
And yet, here we are. Somehow, matter won out over antimatter — but we still don’t know how or why.
Physicists suspect the answer may lie in the mysterious behavior of abundant yet elusive particles called neutrinos. Specifically, learning more about a phenomenon called neutrino oscillation — in which neutrinos change types, or flavors, as they travel — could bring us closer to an answer.
The international collaborations representing two neutrino experiments, NOvA in the United States and T2K in Japan, recently combined forces to produce their first joint results, published October 22 in the journal Nature. This initial joint analysis provides some of the most precise neutrino-oscillation measurements in the field. The NOvA collaboration, centered at Fermilab, includes University of Wisconsin–Madison physicists in Brian Rebel’s group.
“These results are an outcome of a cooperation and mutual understanding of two unique collaborations, both involving many experts in neutrino physics, detection technologies and analysis techniques, working in very different environments, using different methods and tools,” says T2K collaborator Tomáš Nosek.
Caption: T2K in Japan and NOvA in the United States are both long-baseline experiments: they each shoot an intense beam of neutrinos that passes through both a near detector close to the neutrino source and a far detector hundreds of kilometers away. Both experiments compare data recorded in each detector to learn about neutrinos’ behavior and properties. | Credit: Fermilab
Different experiments, common goals
Despite their ubiquity, neutrinos are very difficult to detect and study. Even though they were first seen in the 1950s, the ghostly particles remain deeply enigmatic. Filling in gaps in our knowledge about neutrinos and their properties may reveal fundamental truths about the universe.
T2K and NOvA are both long-baseline experiments: they each shoot an intense beam of neutrinos that passes through both a near detector close to the neutrino source and a far detector hundreds of miles away. Both experiments compare data recorded in each detector to learn about neutrinos’ behavior and properties.
NOvA, the NuMI Off-axis νe Appearance experiment, sends a beam of neutrinos 810 kilometers from its source at the U.S. Department of Energy’s Fermi National Accelerator Laboratory near Chicago, Illinois, to a 14,000-ton liquid-scintillator detector in Ash River, Minnesota.
The T2K experiment’s neutrino beam travels 295 kilometers from Tokai to Kamioka — hence the name T2K. Tokai is home to the Japan Proton Accelerator Research Complex (J-PARC) and Kamioka hosts the Super-Kamiokande neutrino detector, an enormous tank of ultrapure water located a kilometer underground.
Since the experiments have similar science goals but different baselines and different neutrino energies, physicists can learn more by combining their data.
“By making a joint analysis, you can get a more precise measurement than each experiment can produce alone,” says NOvA collaborator Liudmila Kolupaeva. “As a rule, experiments in high-energy physics have different designs even if they have the same science goal. Joint analyses allow us to use complementary features of these designs.”
As long-baseline experiments, NOvA and T2K are ideal for studying neutrino oscillations, a phenomenon that can provide insight into open questions like charge-parity violation and the neutrino mass ordering. Two experiments with different baselines and energies have a better chance of disentangling the two effects than one experiment alone.
Interrogating neutrino oscillations
The mystery of neutrino mass ordering is the question of which neutrino is the lightest. But it isn’t as simple as placing particles on a scale. Neutrinos have miniscule masses that are made up of combinations of mass states. There are three neutrino mass states, but, confusingly, they don’t map to the three neutrino flavors. In fact, each flavor is made of a mix of the three mass states, and each mass state has a different probability of acting like each flavor of neutrino.
There are two possible mass orderings, called normal or inverted. Under the normal ordering, two of the mass states are relatively light and one is heavy, while the inverted ordering has two heavier mass states and one light.
In the normal ordering, there is an enhanced probability that muon neutrinos will oscillate to electron neutrinos but a lower probability that muon antineutrinos will oscillate to electron antineutrinos. In the inverted ordering, the opposite happens. However, an asymmetry in the neutrinos’ and antineutrinos’ oscillations could also be explained if neutrinos violate CP symmetry — in other words, if neutrinos don’t behave the same as their antimatter counterparts.
The combined results of NOvA and T2K do not favor either mass ordering. If future results show the neutrino mass ordering mass ordering is normal, NOvA’s and T2K’s results are less clear on CP symmetry, requiring additional data to clarify. However, if the neutrino mass ordering is found to be inverted, the results published today provide evidence that neutrinos violate CP symmetry, potentially explaining why the universe is dominated by matter instead of antimatter.
“Neutrino physics is a strange field. It is very challenging to isolate effects,” says Kendall Mahn, co-spokesperson for T2K. “Combining analyses allows us to isolate one of these effects, and that’s progress.”
The combined analysis does provide one of the most precise values of the difference in mass between neutrino mass states, a quantity called Δ . With an uncertainty below 2%, the new value will enable physicists to make precision comparisons with other neutrino experiments to test whether the neutrino oscillation theory is complete.
What’s next
These first joint results do not definitively solve any mysteries of neutrinos, but they do add to physicists’ knowledge about the particles. Plus, they validate the impressive collaborative effort between two competing — yet complementary — experiments.
The NOvA collaboration consists of more than 250 scientists and engineers from 49 institutions in eight countries. The T2K collaboration has more than 560 members from 75 institutions in 15 countries. The two collaborations began active work on this joint analysis in 2019; it combines six years of data from NOvA, which began collecting data in 2014, and a decade of data from T2K, which started up in 2010. Both experiments continue to take data, and efforts are already underway to update the joint analysis with the new data.
“The joint analysis work has benefited both collaborations,” says Patricia Vahle, co-spokesperson for NOvA. “We have a much better mutual understanding of the strengths and challenges of the different experimental setups and analysis techniques.”
NOvA and T2K are the only currently operating long-baseline neutrino experiments. Their initial combined results lay a foundation for forthcoming neutrino experiments that will answer the questions around neutrinos unambiguously.
The Fermilab-led Deep Underground Neutrino Experiment is under construction in Illinois and South Dakota in the U.S. With its longer baseline of 1,800 kilometers, DUNE will be more sensitive to neutrino mass ordering and could give physicists a conclusive answer shortly after it turns on in the early years of the next decade.
In Japan, Hyper-Kamiokande, a sequel to Super-Kamiokande located beneath a mountain in Hida City, will be more sensitive to CP violation. And a medium-baseline reactor neutrino experiment in China called JUNO recently began additional studies of antineutrinos and their behavior. Two experiments that use neutrinos generated in the atmosphere to study oscillations, KM3Net-Orca and IceCube, also continue to take data.
Many physicists hope these next-generation neutrino experiments can come together — as NOvA and T2K have already done — to make progress on their shared scientific goals to learn more about neutrinos and their unusual properties.
“As shown in this very analysis, there are no truly ‘rivaling’ experiments because they all share a common goal of scientific study of a phenomenon,” says Nosek. “Collaborating is naturally important for the transfer of knowledge, know-how and experience, and for sharing resources, ideas and tools. The T2K-NOvA collaboration is not merely a sum of T2K and NOvA collaborations. It is much, much more.”
Double the Higgs, Double the Mystery! The hunt for a new, heavy particle decaying to a pair of Higgs Bosons
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This story, written by physics grad student Ganesh Parida, was originally published by the CMS collaboration
CMS scientists are on the hunt for a new, heavy particle that decays into a pair of Higgs bosons. Using the final state with two bottom quarks and two tau leptons, the search sets the most stringent limits to date in the mass range 1.4–4.5 TeV.
Ganesh Parida
The CMS experiment is searching for signs of new, heavy particles that could decay into pairs of Higgs bosons – we call this an HH signature. These signatures are particularly exciting because they can give us clues about the stability of our universe and open a window to physics beyond our current understanding of fundamental particles and their interactions, the standard model.
In this search, we focus on a final state where one Higgs boson decays to two bottom quarks (H→bb) and the other decays to two tau leptons (H→ττ). This final state offers a promising balance: it has a relatively large probability of occurring, while also allowing us to separate signal events from background processes. Performing such a search is far from straightforward. If a new heavy particle were produced at the LHC, it would impart a large momentum, a “boost”, to its daughter Higgs bosons. The boost causes the decay products of each Higgs boson to be collimated and overlap in the detector, making their reconstruction quite challenging.
Diagram showing a new physics process explored in this search. Two protons collide and produce a new heavy particle X, which then decays into two standard model Higgs bosons , which in turn give two bottom quarks and two tau leptons in the final state. | Credit: CMS Collaboration
To meet this challenge, CMS uses advanced reconstruction and machine-learning techniques. For the H→bb decay, the bottom quarks form collimated sprays of particles, called jets, which overlap to a large extent. To identify them, a graph neural network, called ParticleNet, is trained to recognize the pattern of the two bottom quark jets inside a single, large jet.
Reconstructing the H→ττ is a two-step process: first, we untangle and reconstruct the two really close taus, and then we use a convolutional neural network, called Boosted DeepTau to figure out the characteristics of these reconstructed taus and tell them apart from background jets. Because tau leptons also produce invisible neutrinos, we apply a likelihood-based method to obtain the four-momentum of the parent Higgs boson.
Once both Higgs bosons are reconstructed, we can combine them to measure the mass of the system. If a new heavy particle exists, it would appear as a peak, or “bump,” on top of the smoothly falling background distribution. This strategy is often referred to as a “bump hunt” – a classic tool in the search for new particles at colliders.
Left: The sketch illustrates how we perform a “bump hunt.” Background processes fall smoothly with increasing mass, while a new particle would create a visible peak on top of this distribution. Right: We reconstruct the mass of Higgs boson pairs from collision data and compare it to standard model background predictions (shown in color). The black points show the recorded data, while the dashed lines illustrate how new heavy particles could appear. The data follow the standard model expectation, and CMS does not observe a significant excess. | Source: CMS Collaboration
After analyzing data from the full LHC Run 2 (2016–2018), CMS did not observe any significant deviation from the standard model prediction. While this means that no new particle was discovered in this final state yet, the analysis sets the most stringent upper limits to date on the possible production of heavy particles decaying into Higgs boson pairs in the bbττ final state in the mass range of 1.4 TeV to 4.5 TeV.
“The results may not yet show evidence of new physics, but they are paving the way,” says Ganesh Parida, a PhD student at the University of Wisconsin–Madison, who carried out this analysis together with Camilla Galloni and Deborah Pinna, both scientists at the University of Wisconsin–Madison and members of CMS. “It has been both exciting and rewarding to learn, develop, and apply sophisticated techniques to probe these challenging boosted regimes.”
The biggest challenge here is the sheer number of events we can collect for these difficult “boosted” scenarios. That is why the ongoing Run 3 and the upcoming High-Luminosity runs of the LHC are so important – they will give us the biggest datasets ever for a potential discovery!
Karle, Lu lead team awarded Research Forward funding
The Office of the Vice Chancellor for Research (OVCR) hosts the Research Forward initiative to stimulate and support highly innovative and groundbreaking research at the University of Wisconsin–Madison. The initiative is supported by the Wisconsin Alumni Research Foundation (WARF) and will provide funding for 1–2 years, depending on the needs and scope of the project.
Albrecht KarleLu Lu
Research Forward seeks to support collaborative, multidisciplinary, multi-investigator research projects that are high-risk, high-impact, and transformative. It seeks to fund research projects that have the potential to fundamentally transform a field of study as well as projects that require significant development prior to the submission of applications for external funding. Collaborative research proposals are welcome from within any of the four divisions (Arts & Humanities, Biological Sciences, Physical Sciences, Social Sciences), as are cross-divisional collaborations.
Nine projects were chosen for funding in Round 5 of Research Forward (2025), including one from Physics:
From radiation therapy to the high energy universe: Generative AI for particle tracking
Artificial intelligence is rapidly expanding across all fields of science, particularly in physics. The 2024 Nobel Prize in Physics was awarded for groundbreaking advancements in artificial intelligence that have led to significant discoveries in various physics applications. This project uses a specific type of AI, generative AI, to achieve breakthroughs in diverse particle physics research applications.
Analyzing and understanding the results of high-energy particle interactions using traditional methods requires immense computing resources. Even a single particle collision can involve billions of calculations. This research will enable substantial shortcuts in calculating the outcomes of particle interactions for fundamental physics and astrophysics.
The collaborative research between physicists and computer scientists will significantly improve data use, enabling discoveries that would otherwise be impossible. Medical physics applications, such as radiation therapy, are also envisioned.
PRINCIPAL INVESTIGATOR
Albrecht Karle, professor of physics
CO-PRINCIPAL INVESTIGATORS
Yong Jae, associate professor of computer science
Lu Lu, assistant professor of physics
CO-INVESTIGATOR
Benedikt Riedel, computing manager for WIPAC
Search for boosted Higgs advances our understanding of dark matter
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This story, featuring physics graduate student Shivani Lomte, was originally published by the CMS collaboration
The CMS Collaboration hunts for Higgs bosons recoiling against dark matter particles
Shivani Lomte
Dark matter is one of the most perplexing mysteries of our universe, accounting for roughly 27% of its total energy. Dark matter does not emit, absorb, or reflect light, and is thus invisible to telescopes. However, its effects on gravitation are unmistakable. Although dark matter’s elementary nature remains unknown, scientists hypothesize that it might be made up of weakly interacting massive particles (WIMPs) that rarely interact with ordinary matter.
In the CMS experiment, we use the fundamental law of momentum conservation to infer the possible presence of dark matter in the detector. In particular the momentum in the transverse plane should be conserved before and after the proton-proton (pp) collision – in other words, the sum of all particle momenta combined should balance out. If momentum is missing, then this suggests that an ‘invisible’ particle, for instance a dark matter particle, has carried that momentum away. Since dark matter doesn’t interact with the detectors, we can’t directly observe it. To detect its presence, we use a ‘visible’ known particle that recoils against the dark matter particle, providing a detectable signal in the experiment. An example of this type of process is shown in Fig. 1.
Figure 1: An event display from the transverse plane which illustrates a signal-like event: the orange cone corresponds to a jet that recoils against missing transverse energy, represented as a magenta arrow. | Credit: CMS collaboration
In pp collisions, a photon, ‘jet’, W or Z boson can be emitted from the initial quark within the proton, whereas radiating a Higgs boson is extremely rare given its small coupling to the quarks. Higgs bosons might be preferentially emitted through a new particle acting as a ‘mediator’ between the standard model and dark matter sector. There is a unique possibility at LHC to produce the mediator particle and study its interaction with the standard model and dark matter.
This analysis uses the “mono-Higgs” signature to search for dark matter particles, focusing on two scenarios that both involve Higgs bosons decaying to bottom quarks. If the Higgs boson is highly energetic (boosted), its decay products become collimated and can be reconstructed in a single large-radius ‘jet’. Alternatively, if the Higgs is not as energetic, we instead look for two small-radius jets, one from each bottom quark. The two scenarios are illustrated in Fig. 2.
Figure 2: Schematic depiction of the “mono-Higgs” → bb̄ production process. On the left, the Higgs decay products merge into a large-radius jet. On the right, the Higgs decay products are reconstructed as two small-radius jets. | Credit: CMS collaboration
“A key challenge in this search is that the dark matter signal is rare (at best) and well-known processes, as described in the standard model, produce very similar signatures. To reduce the backgrounds from known particles, we use distinguishing features like the momentum and energy distribution of the particles” says Shivani Lomte, a graduate student at the University of Wisconsin-Madison, leading this search. The precise estimation of the background is critical and is achieved using so called control regions in the data. Such control regions are dominated by background processes and this allows us to quantify the amount of backgrounds in the signal region where we search for dark matter.
In this analysis, once the backgrounds were well-understood, we looked for the dark matter signal by comparing the observed data distributions to the predicted backgrounds, looking for discrepancies. Unfortunately, the observed data agrees with the standard model predictions, and so we conclude that our result has no sign of dark matter. We can thus rule out those types of dark matter particles that would have been detected if they existed.
Regardless of the outcome, the search for dark matter is a journey that pushes the boundaries of human knowledge. Each step brings us closer to answering some of the most profound questions about the nature of the universe and our place within it.
