Journal Link: Science, 388, 180-185 (2025)

BYLINE: Michelle Alvarez

For Immediate Release_

March 23, 2026
Contact: Michelle Alvarez
malvarez@jlab.org

A Strong Case for Weak Interactions

Jefferson Lab physicist Ciprian Gal wins prestigious DOE award to search for cracks in physics’ best theory of the universe

Newswise — NEWPORT NEWS, VA – In fifth grade, Ciprian Gal received his physics textbook a year early. The book promised to explain everything, and young Gal believed it. “I was bragging to all my friends, look at this book. It tells you everything,” Gal said. “And I’m going to know everything about it.” Decades later, Gal, a staff scientist at the U.S. Department of Energy’s (DOE) Thomas Jefferson National Accelerator Facility, is still chasing answers. His work probing the fundamental forces that hold matter together earned him a DOE Office of Science Early Career Research Award. The five-year, $2.75 million award will fund personnel and research expenses related to Gal’s work on the Measurement of a Lepton-Lepton Electroweak Reaction (MOLLER) experiment. MOLLER aims to test whether the Standard Model of Particle Physics, scientists’ current best description of how particles interact, is actually complete. Measuring Weak Charge The Standard Model explains three of the four fundamental forces that govern the universe: electromagnetism, the strong force and the weak force. Gal’s research focuses on the measurement of the electron’s weak charge, a property that describes how electrons interact through the weak force. While physicists understand the weak force reasonably well, measuring its precise effects on electrons requires extraordinary precision. The MOLLER experiment will scatter electrons off other electrons in a hydrogen target. It will measure tiny differences in how they scatter depending on the electron’s spin direction. These differences are so tiny, estimated to be 35 parts per billion, that measuring them requires utmost accuracy and control over every aspect of the experiment. “It’s a precision measurement,” Gal said. “We need to know exactly what we’re measuring, down to very fine details.” The challenge extends beyond just taking measurements. Gal and his team must account for every possible source of uncertainty, from the quantum mechanics of how particles scatter to the precise geometry of their detector. Abhay Deshpande, who mentored Gal during his graduate studies at Stony Brook University and now collaborates with him on MOLLER, attributes this precision mindset to Gal’s fundamental approach to physics. “His penchant for precision and methodical approach makes him particularly suited to this exacting research,” said Deshpande, Brookhaven National Laboratory’s associate lab director for nuclear and particle physics and Stony Brook University distinguished professor of physics. The new measurements could indicate new particles or forces that physicists haven’t discovered yet. These deviations could help answer some of physics’ biggest mysteries: Why is there more matter than antimatter in the universe? What is dark matter made of? “Whether we confirm the Standard Model’s predictions or find something unexpected, this measurement will be a major step forward,” Gal said. “Either result will teach us something fundamental about how the universe works.” A Decade of Physics at Jefferson Lab Gal’s connection to Jefferson Lab began in 2014, long before he joined the staff. Immediately after earning his Ph.D., he came to the lab as a University of Virginia (UVA) postdoc, drawn by the facility’s unique capabilities for studying the internal structure of protons and neutrons. Over the next eight years, Gal worked at the lab through partnerships with UVA, Stony Brook University and Mississippi State University. Each position as a research assistant professor helped him develop his skills in precision measurements and experimental design. In 2023, he joined Jefferson Lab as a staff scientist in Experimental Halls A/C. Throughout his career, Gal worked closely with mentors who shaped his approach to physics and collaboration. “At this point, Cip is one of the leading mid-career experts on all things relevant to the MOLLER experiment,” said Krishna Kumar, a University of Massachusetts, Amherst professor of physics and MOLLER spokesperson. “As we pivot to data collection and physics analysis, I expect he will be one of the leaders of the team driving the analysis to accomplish the goals of the experiment.” For Gal, that leadership potential stems directly from his commitment to teamwork. “The research that I want to do and the things that I want to discover can’t be done without collaboration, not only with experimental and theoretical physicists here at the lab, but also at the universities,” Gal said.

Looking Forward The DOE Office of Science Early Career Research Program, established in 2010, supports outstanding scientists at a DOE national laboratory or Office of Science user facility within 12 years of having earned their doctorate degree across disciplines including nuclear physics. The program aims to support the vision, creativity and effort of early career faculty to drive innovation in the basic science enterprise. For Gal, the award provides resources and time to tackle MOLLER’s technical challenges and prepare for the experiment’s data collection phase. “Cip is a fantastic collaborator,” said Kumar. “He communicates effectively regardless of the audience, and the fact that he acknowledges the need for collaboration demonstrates his maturity and potential for leadership.” Beyond the immediate research, Gal sees the award as validation of his approach: combining precision measurement techniques with innovative detector design to push the boundaries of what physics can reveal about nature’s fundamental workings. It also validates something simpler: persistence. “I think for these very competitive awards, it matters a lot to be able to stand out, to have something that is unique on its own,” Gal said. He applied in 2024, received feedback, refined his proposal, and won on his second attempt in 2025. “Ciprian thrives on difficult tasks,” said Deshpande. “He understands not only the award’s value to his own career but, more importantly, the visibility this recognition brings to the MOLLER project and Jefferson Lab. His persistence therefore does not surprise me, and I am delighted by his success.” For researchers working at the frontier of nuclear physics, success often means spending years preparing for measurements that take only hours or days to complete. The payoff comes when those measurements reveal something unexpected, a crack in our understanding that points toward deeper truths. Gal’s work on MOLLER continues that tradition, using precision as a tool to probe whether the Standard Model tells the whole story or whether the universe has more secrets waiting to be discovered. For a scientist who once believed a single book could explain everything, the possibility of discovering something entirely new might be even better than having all the answers.

Further Reading

https://moller-docdb.physics.sunysb.edu/cgi-bin/DocDBTest/public/ShowDocument?docid=998

https://journals.aps.org/prc/abstract/10.1103/PhysRevC.109.024323

https://arxiv.org/abs/2411.10267

Contact: Michelle Alvarez, Jefferson Lab Communications Office, malvarez@jlab.org

-end-

Jefferson Science Associates, LLC, manages and operates the Thomas Jefferson National Accelerator Facility, or Jefferson Lab, for the U.S. Department of Energy’s Office of Science. JSA is a wholly owned subsidiary of the Southeastern Universities Research Association, Inc. (SURA).

DOE’s Office of Science is the single largest supporter of basic research in the physical sciences in the United States and is working to address some of the most pressing challenges of our time. For more information, visit

BYLINE: Ula Chrobak

Read this story in the SLAC News Center

Newswise — Researchers at the Department of Energy’s SLAC National Accelerator Laboratory and collaborating institutions recently built a generative AI model that can recreate molecular structures from the movement of the molecule’s ions after they are blasted apart by X-rays, a technique called Coulomb explosion imaging.

The research, published in Nature Communications, is an important step toward being able to take snapshots of molecules during chemical reactions – an advance that could have important impacts in medicine and industry. The machine learning model closely predicted the geometries of a range of different molecules made of less than ten atoms, paving the way for applying the technique to larger molecules. “We were pretty excited about this,” said Xiang Li, an associate scientist at SLAC’s Linac Coherent Light Source (LCLS) and lead author of the study. “It is the first AI model built for molecular structure reconstruction from Coulomb explosion imaging.”

A new way to see molecules

Currently, there are limited options available for imaging isolated gas phase molecules. With electron microscopy, for example, subjects must be fixed in place, making it impossible to image free-floating molecules. And for diffraction-based techniques to work, the sample of molecules needs to be dense enough to generate a strong signal in the detector. The resulting image is technically an average of many molecules, restricting researchers from studying details only visible when imaging isolated molecules.

In the paper, the researchers instead focused on Coulomb explosion imaging. In this technique, an X-ray pulse hits a single molecule in a vacuum chamber, ripping off the molecule’s electrons. This leaves behind positive ions that explosively repel away from each other and smash into a detector. The detector captures their momentum, which can be used to reconstruct the structure of the molecule. “This technique has the ability to isolate minor details that are chemically relevant,” said James Cryan, LCLS interim deputy director for science, research and development, associate professor of photon science at SLAC and coauthor of the paper.

But this reconstruction process has so far been largely infeasible due to computing constraints. After the X-ray pulse strips away electrons, the remaining ions do not explode apart instantly. During this brief delay, the atoms can shift slightly, making it difficult to reconstruct the original structure using Coulombs law for electrostatic forces. “It will not be accurate because a simple use of that law only works if the charge-up process is instantaneous,” explained Li.

Making things even messier, every additional atom in the molecule adds an exponential level of complexity. “It’s very challenging to work backwards to get the original structure,” said co-author Phay Ho, a physicist with DOE’s Argonne National Laboratory. “It’s kind of like breaking a glass and trying to put it back together from how the pieces flew apart. Many problems in modern physics and chemistry involve reconstructing hidden structures from indirect measurements. This work demonstrates how AI can help tackle such inverse problems.”

Machine learning for molecular structures

The research team set out to build a machine learning model that could overcome this computing constraint. They developed and trained the model at SLAC’s Shared Science Data Facility (S3DF). Generative AI models are well-suited for the task because they “think” differently than a standard computer simulation. Instead of working through a series of equations, they learn by finding patterns in training data. Then, they use those patterns to make statistical predictions. 

To gather training data, the team turned to a simulation built by Ho. The simulation analyzes molecular structures and calculates the momentum of their ions following a Coulomb explosion. After running for over a month, the computing-intensive simulation, using both quantum mechanics and classical physics equations, produced a dataset of 76,000 molecular samples.

Initially, the researchers trained the AI on this dataset alone, which is small by AI-training standards, and they found the model predicted inaccurate structures from explosion data. So, they re-did the training, adding in another dataset derived using only classical physics. The second set was less precise but about 100 times larger than the first one.

This two-step training was the trick for predicting precise structures.

The researchers tested the AI model by prompting it to predict molecular structures in a portion of the simulation data it had not seen in training. The model, which the team named MOLEXA (short for “molecular structure reconstruction from Coulomb explosion imaging”), took the ion momenta and calculated the most likely structures. “We found that this two-step training process suppressed the prediction error by a factor of two,” said Li.

The team then tested MOLEXA with experimental datasets recorded at the Small Quantum Systems (SQS) instrument of the European X-ray Free-Electron Laser facility (European XFEL) in Germany. The molecules they tested included water, tetrafluoromethane and ethanol. They entered the experimental ion momenta into the model, reconstructed the molecular structures, and then compared the reconstructions to known structures listed by the National Institute of Standards and Technology.

They found the predictions largely overlapped with the established structures. Overall, the bonds were in the right spots, with only slight variations in their angles. The errors in position were generally less than half the length of a typical chemical bond. “The model is actually, most of the time, doing better than that,” added Li. “It is only a starting point for future research, which will not only improve model accuracy but also extend its applicability to larger molecular systems.”

Expanding to larger molecules and chemical reactions

The paper is a major step in advancing Coulomb explosion imaging, which has long been limited by the challenge of reconstructing molecular structures from experimental measurements. In future work, the researchers plan to scale up the number of atoms the machine learning model can piece back together and apply the model to time-resolved experiments at the LCLS and European XFEL. That will help researchers to reconstruct snapshots of molecules in motion, creating flip-book-like molecular movies with insights into how chemical reactions unfold. It will also help with the interpretation of data collected at the high X-ray pulse rates delivered by SLAC’s superconducting X-ray laser, Cryan said.

The team is also now testing the model’s ability to reconstruct molecules from incomplete data. Much of the time, the detector misses an ion produced in the Coulomb explosion. Li wants to know, for example: Can the AI still reconstruct an ethanol molecule if one or more of its hydrogen ions are not registered in the detector?

If these challenges are resolved, the technique could become more applicable in biology and chemistry research. Proteins, for instance, can consist of thousands of atoms. “That’s really the goal,” said Li. “We will be able to study systems that are more biologically or industrially relevant.”

The team also included researchers from the Stanford PULSE Institute; Stanford University; Kansas State University; European XFEL, Germany; the Max Planck Institute for Nuclear Physics, Germany; Fritz Haber Institute, Germany; and Sorbonne University, France. Large parts of this work were funded by the Department of Energy’s Office of Science. LCLS is an Office of Science user facility.

About SLAC

SLAC National Accelerator Laboratory explores how the universe works at the biggest, smallest and fastest scales and invents powerful tools used by researchers around the globe. As world leaders in ultrafast science and bold explorers of the physics of the universe, we forge new ground in understanding our origins and building a healthier and more sustainable future. Our discovery and innovation help develop new materials and chemical processes and open unprecedented views of the cosmos and life’s most delicate machinery. Building on more than 60 years of visionary research, we help shape the future by advancing areas such as quantum technology, scientific computing and the development of next-generation accelerators.

SLAC is operated by Stanford University for the U.S. Department of Energy’s Office of Science. The Office of Science is the single largest supporter of basic research in the physical sciences in the United States and is working to address some of the most pressing challenges of our time.

BYLINE: Lauren Biron

Newswise — Although dark matter makes up most of the mass in our universe, it has never been directly observed. To hunt for lighter dark matter and other rare phenomena, researchers must solve a puzzle in their supersensitive detectors: an unexpected number of low-energy events, called the “low-energy excess” or LEE, that can obscure the rare signals they seek.

In a study published on Dec. 30, 2025, in Applied Physics Letters, researchers with the TESSERACT (Transition-Edge Sensors with Sub-EV Resolution And Cryogenic Targets) experiment identified one of the culprits behind the low-energy excess. They found that the noise comes not from the electronics or the surrounding environment, but from tiny bursts of vibrational energy within the silicon crystal of the detectors themselves. And the thicker the silicon, the more LEE events there are.

Since at least some LEE events come from tiny changes in the detector material itself, researchers estimate they also cause problems in superconducting qubits, the sensitive building blocks of quantum computers that are often made of silicon. The bursts of energy can create “quasiparticles” that disturb a qubit’s fragile quantum state, causing it to decohere or fail. So even in carefully shielded quantum systems, some errors could be coming from inside the house.

“Quantum computers could perform calculations our current systems can’t, but only if people can make qubits that are stable,” said Dan McKinsey, the director of TESSERACT and a scientist at the Department of Energy’s Lawrence Berkeley National Laboratory (Berkeley Lab), which leads the experiment. “Because the detectors we use for our dark matter experiment have a similar backbone to what is in qubits, by understanding a problem in particle physics, we’re also getting information on how to improve the quantum computing side.”

To pinpoint where LEE events were coming from, TESSERACT collaborators fabricated superconducting phonon sensors (which pick up quantum vibrations, or phonons) on two nearly identical silicon chips that were 1 and 4 millimeters thick. In both detectors, the number of events decreased over time as they were cooled, and the thicker chip saw four times as many low-energy events — pointing to the volume of silicon itself as the source, rather than outside causes.

Now that the scientific community knows the number of LEE events relates to how thick the silicon is, some groups will be able to improve their sensors simply by scaling back how much silicon they use. But it’s still just the first step in understanding exactly what causes the bursts of energy and finding an engineering solution to get rid of the background noise completely.

“Superconducting qubits for computers are designed to ignore the environment so that their quantum state survives,” said Matt Pyle, a TESSERACT collaborator, associate professor at UC Berkeley, and researcher at Berkeley Lab. “In contrast, our photon and phonon sensors use similar technology, but they’re designed to be incredibly sensitive to their environment so that they can sense dark matter. That makes our detectors unique and powerful tools for diagnosing environmental sources that cause decoherence and limit quantum computers.”

During the experiment, TESSERACT’s thinner detector also achieved a world-leading energy resolution of 258.5 millielectronvolts. That means it could distinguish between two events with energies differing by only a few hundredths of an electronvolt, several times smaller than the amount of energy carried by a single particle of visible light. That precision will allow scientists to distinguish extremely faint signals from background noise, essential for tracking down dark matter.

TESSERACT is currently in the prototype and construction phase, and will eventually be installed in France’s Modane Underground Laboratory. The TESSERACT collaboration also includes researchers at Argonne National Laboratory, Caltech, Florida State University, IJCLab (Laboratoire de Physique des 2 Infinis Iréne Joliot-Curie), IP2I (Institut de Physique des 2 Infinis de Lyon), LPSC (Laboratoire de Physique Subatomique et de Cosmologie), Texas A&M University, UC Berkeley, the University of Massachusetts Amherst, the University of Zürich, and QUP (the International Center for Quantum-field Measurement Systems for Studies of the Universe and Particles).

###

Lawrence Berkeley National Laboratory (Berkeley Lab) is committed to groundbreaking research focused on discovery science and solutions for abundant and reliable energy supplies. The lab’s expertise spans materials, chemistry, physics, biology, earth and environmental science, mathematics, and computing. Researchers from around the world rely on the lab’s world-class scientific facilities for their own pioneering research. Founded in 1931 on the belief that the biggest problems are best addressed by teams, Berkeley Lab and its scientists have been recognized with 17 Nobel Prizes. Berkeley Lab is a multiprogram national laboratory managed by the University of California for the U.S. Department of Energy’s Office of Science.

DOE’s Office of Science is the single largest supporter of basic research in the physical sciences in the United States, and is working to address some of the most pressing challenges of our time. For more information, please visit energy.gov/science.

BYLINE: Shannon Brescher Shea: Social media manager and senior writer/editor in the Office of Science’s Office of Communications and Public Affairs

Newswise — Scientists recognized by the Department of Energy Office of Science Distinguished Scientists Fellows Award are pursuing answers to science’s biggest questions. Mary Bishai is a senior physicist at DOE’s Brookhaven National Laboratory.

If it wasn’t for a magazine, I may have become a completely different type of scientist. 

In 1985, my uncle – who was a prominent marine biology professor – was tutoring me in high school biology. As a science lover, he had copies of National Geographic lying around. Intrigued, I convinced my parents to get me a subscription. One article caught my eye – “Worlds Within the Atom.” It described how physicists used massive particle accelerators to study the tiniest things in existence. 

Even though I was born in and living in Egypt, I was enthralled by the research in Europe and the United States. I decided I would one day work at CERN in Switzerland or the Tevatron collider at the Department of Energy’s (DOE) Fermilab.

Although my engineer parents wanted me to follow in their footsteps, I entered the American University of Cairo as a physics major instead. An exchange program later brought me to the United States.

Then nearly 13 years after I first read about the Tevatron at Fermilab, I was there. Fulfilling my dream, I delved into the interactions between the Standard Model of Particle Physics fundamental particles called Quarks and Gluons.

But that’s not the end of the story. Along the way, another type of physics caught my eye – neutrino physics. Since then, I’ve pursued the question – how can neutrinos help us answer some of the biggest questions about how our universe evolved?

The little neutral one

Neutrinos are a type of fundamental particle. They’re in a group called the leptons, which also includes electrons. However, neutrinos are much smaller than their familiar cousins.

Neutrinos are incredibly abundant. On the tip of your tongue right now, there are 300 neutrinos left over from the Big Bang. The sun, Supernovae, cosmic rays interacting with the atmosphere, and nuclear reactors also produce neutrinos. They’re the second most abundant particle in the universe, after photons (particles of light). Neutrinos are everywhere. 

Despite them being so common, neutrinos interact very little with other matter. Every second, 100 billion neutrinos produced by the sun move through your thumbnail and never leave a mark. A neutrino would have to travel 1.6 light years through lead – or 100,000 times the distance from the Earth to the sun – to interact with a single atom. Or as writer John Updike declared in the poem “Cosmic Gall,” “The earth is just a silly ball / To them, through which they simply pass, / Like dustmaids through a drafty hall / Or photons through a sheet of glass.” This lack of interaction inspired the nickname of “ghost particles.” 

Scientists are interested in neutrinos because of their ubiquity and the fact that they could hold the answers to some of physics’ biggest questions. One of those questions is the issue of why there is something in our universe rather than nothing. 

But none of that drew me to neutrino research. Wave-particle duality – or the idea that all matter can act like waves or particles – is a key concept in quantum mechanics. Scientists in the 1960’s stipulated that if neutrinos have non-zero mass, one type of neutrino could convert to another then back again. This would be a direct signature of quantum interference and wave-particle duality. In the late 1990s and early 2000s, experimental results confirmed the observation of neutrino “oscillations.” Hearing about one of the experiments, I said, “Oh my God, this is wave particle duality. It’s quantum mechanics and it’s just there. That’s cool, that’s what I want to do.” 

When I joined DOE’s Brookhaven National Laboratory in 2004 to study neutrinos, I joined a history of “ghostbuster” physicists.  

A history of ghostbusters

Our story starts in the 1930s. At that point, scientists were interested in how radioactive particles fall apart. Beta decay is when a nucleus emits an electron or its anti-matter partner, the positron. When a Nuclei nucleus undergoes beta decay, it transforms into another type of nucleus. When scientists looked at this process, they expected it to release a specific amount of energy. But it didn’t. It seemed like this result contradicted the Law of Energy Conservation, where energy can neither be created nor destroyed. 

Enter our first ghostbuster – Wolfgang Pauli. In a letter to fellow physicists attending a workshop, he proposed the idea of a yet-unknown particle that would carry away some of the energy. It would be neutral and have extremely small mass. While he valued his research enough to write the letter, it didn’t win out over a social obligation. In the same letter, he explained that he couldn’t have traveled to the workshop “since I am indispensable here in Zurich because of a ball.” Physicists do like to party. 

Now let’s jump ahead to the 1950s at DOE’s Los Alamos National Laboratory. Determined to track down these mysterious particles, Fred Reines and Clyde Cowan pursued the “poltergeist project.” While they first proposed detecting neutrinos from nuclear bomb testing, that idea was dismissed. Instead, they placed particle detectors near the Hanford and Savannah River nuclear reactors. The detectors sensed a telltale: two flashes of light from ghost-like neutrinos emitted by the reactors interacting with the material in the detectors. By counting these flashes, the scientists could count the neutrinos being captured by the detector. Developing the first neutrino detector netted Reines the Nobel Prize in 1995.

In addition to reactors, scientists realized that they could produce neutrinos in particle accelerators. From early on, Brookhaven was a leader in neutrino research. Physicists Leon Lederman, Melvin Schwartz, and Jack Steinberger used a proton beam from Brookhaven’s Alternating Gradient Synchrotron to slam protons into a target. A type of particle called a pi meson emerged, which then decayed into a neutrino and a Muons (another cousin of the electron). 

The scientists wanted to know if these were the same type of neutrinos as the ones from beta decay. The tracks the neutrinos left in their detector revealed mostly muon neutrinos and not electron neutrinos which are the type of neutrinos from beta decay. Another Nobel Prize-winning discovery. Later experiments at Fermilab confirmed a third type of neutrino called the tau neutrino – the neutral partner of the tau lepton, the heavier sibling of electrons and muons.

But both reactors and accelerators are made by humans. What about neutrinos from the sun? That was Ray Davis’s question. A chemist and physicist from Brookhaven, Davies began a long-standing physics experiment in 1967. He wanted to test the models that predicted how many solar neutrinos Earth receives. 

Davies installed a particle detector with 615 tons of cleaning fluid in the Homestead gold mine in South Dakota. The solar neutrinos interacted with the chlorine in the cleaning fluid to produce a unique isotope – argon-37. To track the interactions, he painstakingly counted the atoms of argon-37. He kept this up for almost 20 years! For demonstrating how to detect solar neutrinos, he also received a Nobel Prize. 

As these experiments revealed different types of neutrinos – called “flavors” – they also brought up new questions. From studying beta decay, scientists knew that neutrinos are extraordinarily light. In fact, they assumed that neutrinos didn’t have mass at all, like photons. But observations suggested that assumption was wrong. 

In the late 1950s to 1960s, scientists suggested that the different flavors of neutrinos were different mixes of quantum states. In highly relativistic particles like neutrinos, mass, energy, and momentum are all closely related. So when neutrinos act like waves and not particles, you can use their speed to understand their mass. If the different flavors had different speeds, neutrinos would have to have mass. One sign of neutrinos having mass would be one flavor of neutrino turning into another. 

While theory supported that idea, no one had observed that behavior – at least not until 1998 at the Super-Kamiokande (Super-K) detector. This experiment studied neutrinos created by cosmic rays smacking into the atmosphere. It identified if they were muon or electron neutrinos, as well as the direction they came from. The number of neutrinos that came from near the experiment matched well with estimates. In contrast, the ones from far away had a major deficit. The “disappearing” neutrinos were the first observations of neutrinos changing flavor, called oscillation. 

Later experiments confirmed the idea of neutrino oscillation. They also gave evidence of at least three different masses. The results won the leaders of the Super-K and Sudbury Neutrino Observatory experiments yet another Nobel Prize.

From not knowing that neutrinos existed to realizing that they change flavors over time, a lot changed in neutrino science in 60 years. But there was so much we still didn’t know.

Becoming a ghostbuster

This is where I come back into the story. The results from the KamLAND experiment following the Super-K project were so intriguing that I wanted to study this bizarre particle. 

One of the earliest projects I worked on was the Daya Bay experiment. This was an extremely difficult project. This experiment measured neutrinos from one of the most powerful nuclear reactors in the world. We had three detectors: one close to the reactor core, one a few hundred meters away, and a last one about a kilometer away. Spreading out the detectors allowed us to study the differences between them. Taking data over the course of 10 years, we detected 5 million anti-neutrino interactions! They were the most precise measurements in the world of antineutrinos from reactors. 

With these results, we knew there were three mass states and three flavors of neutrino. Each mass state is a different mix of flavors. The first mass state is dominated by the electron neutrino flavor. The second mass state has almost equal amounts of all three types. The third mass state is almost all muon and tao neutrino with a tiny amount of electron neutrinos. While we knew the second mass state was heavier than the first one, we didn’t know if the first mass state was heavier or lighter than the third one.

These flavors and mass states brought up a new question – could neutrinos explain why there is something rather than nothing? There is a fundamental principle called charge-parity symmetry. It states that if a particle is swapped with its anti-particle and left and right are swapped, the laws of physics will act in an identical way. However, if this law was universally true, there would have been equal amounts of matter and anti-matter at the beginning of the universe. As matter and anti-matter completely destroy each other and the universe is dominated by matter, we know there must be an exception. If neutrinos and anti-neutrinos demonstrate different mixing of neutrino flavors, this could be the exception. But to find out, we needed to better understand how neutrinos change flavor. 

The ultimate neutrino experiment

Exploring this issue was why we designed the Deep Underground Neutrino Experiment (DUNE). 

In the early 2000s, a multidisciplinary, multi-institutional team proposed the ultimate neutrino experiment. We picked two facilities with a long history of neutrino research – the former Homestake Mine and Fermilab. Where Ray Davies once studied solar neutrinos is now home to the Sanford Underground Research Facility. Fermilab has a particle accelerator that produces the most powerful neutrino beam in the world. The locations are 1,300 kilometers apart, enough space for us to capture plenty of oscillations.

Besides the sheer distance, DUNE is extremely large and complex. From the beam line to the shielding, everything must be extremely precise. The detectors use 17 kilotons of liquid argon that must be kept at -300 degrees F. Each of the two cryostats that keep the liquid cold is the size of a Boeing 787 plane. To fit the equipment, we had to massively expand the underground space of the former mine.

In addition to detecting neutrino oscillation, DUNE should also provide us with new insights into other issues. It will look for new particles, several types of proton decay, and neutrinos produced by supernovas. 

Recognizing the importance of this experiment, more partners joined the effort. Currently, we have 1,400 scientists from 209 institutions. Our international partners at CERN and elsewhere have made essential contributions to building and testing parts of the detectors.  

I have been involved with DUNE since early in its conception and served as DUNE project scientist from 2012 to 2015, leading the conceptual design of the project. I was also honored to serve as DUNE co-spokesperson from 2023 to 2025. In August 2024, we celebrated our biggest milestone yet – the ribbon cutting of the cavern expansion. The next milestone will be installing the first of four detectors underground. 

Looking forward, I hope that DUNE provides the next generation of scientists and engineers with the same opportunities I had. Working in experimental particle physics at the DOE National Labs has given me the incredible opportunity to study the fundamental science of our universe. I am lucky to study the worlds within the atom that I first read about in a magazine 40 years ago.