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At Fermilab, a new campus devoted to studying muons was being built.

That opened up a world of possibility, Dr. Polly recalled in his biographical article. By this time, Dr. Polly was working at Fermilab; he urged the lab to redo the g-2 experiment there. They put him in charge.

To conduct the experiment, however, they needed the 50-foot magnet racetrack from Brookhaven. And so in 2013, the magnet went on a 3,200-mile odyssey, mostly by barge, down the Eastern Seaboard, around Florida and up the Mississippi River, then by truck across Illinois to Batavia, home of Fermilab.

The magnet resembled a flying saucer, and it drew attention as it was driven south across Long Island at 10 miles per hour. I walked along and talked to people about the science we were doing, Dr. Polly wrote. It stayed over one night in a Costco parking lot. Well over a thousand people came out to see it and hear about the science.

The experiment started up in 2018 with a more intense muon beam and the goal of compiling 20 times as much data as the Brookhaven version.

Meanwhile, in 2020, a group of 170 experts known as the Muon g-2 Theory Initiative published a new consensus value of the theoretical value of the muons magnetic moment, based on three years of workshops and calculations using the Standard Model. That answer reinforced the original discrepancy reported by Brookhaven.

Reached by phone on Monday two days before the announcement, Aida X. El-Khadra, a physicist at the University of Illinois and a co-chair of the Muon g-2 Theory Initiative, said they had been waiting for this result for a long time.

I have not had the feeling of sitting on hot coals before, she said.

On the day of the Fermilab announcement another group, using a different technique known as a lattice calculation to compute the muons magnetic moment, got a different answer than Dr. El-Khadras group, adding a new note of uncertainty to the proceedings.

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A Tiny Particles Wobble Could Upend the Known Laws of Physics - The New York Times

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Quantum computing promises to harness the strange properties of quantum mechanics in machines that will outperform even the most powerful supercomputers of today. But the extent of their application, it turns out, isnt entirely clear.

To fully realize the potential of quantum computing, scientists must start with the basics: developing step-by-step procedures, or algorithms, for quantum computers to perform simple tasks, like the factoring of a number. These simple algorithms can then be used as building blocks for more complicated calculations.

Prasanth Shyamsundar, a postdoctoral research associate at the Department of Energys Fermilab Quantum Institute, has done just that. In a preprint paper released in February, he announced two new algorithms that build upon existing work in the field to further diversify the types of problems quantum computers can solve.

There are specific tasks that can be done faster using quantum computers, and Im interested in understanding what those are, Shyamsundar said. These new algorithms perform generic tasks, and I am hoping they will inspire people to design even more algorithms around them.

Shyamsundars quantum algorithms, in particular, are useful when searching for a specific entry in an unsorted collection of data. Consider a toy example: Suppose we have a stack of 100 vinyl records, and we task a computer with finding the one jazz album in the stack.

Classically, a computer would need to examine each individual record and make a yes-or-no decision about whether it is the album we are searching for, based on a given set of search criteria.

You have a query, and the computer gives you an output, Shyamsundar said. In this case, the query is: Does this record satisfy my set of criteria? And the output is yes or no.

Finding the record in question could take only a few queries if it is near the top of the stack, or closer to 100 queries if the record is near the bottom. On average, a classical computer would locate the correct record with 50 queries, or half the total number in the stack.

A quantum computer, on the other hand, would locate the jazz album much faster. This is because it has the ability to analyze all of the records at once, using a quantum effect called superposition.

With this property, the number of queries needed to locate the jazz album is only about 10, the square root of the number of records in the stack. This phenomenon is known as quantum speedup and is a result of the unique way quantum computers store information.

The quantum advantage

Classical computers use units of storage called bits to save and analyze data. A bit can be assigned one of two values: 0 or 1.

The quantum version of this is called a qubit. Qubits can be either 0 or 1 as well, but unlike their classical counterparts, they can also be a combination of both values at the same time. This is known as superposition, and allows quantum computers to assess multiple records, or states, simultaneously.

Qubits can be in a superposition of 0 and 1, while classical bits can be only one or the other. Image: Jerald Pinson

If a single qubit can be in a superposition of 0 and 1, that means two qubits can be in a superposition of four possible states, Shyamsundar said. The number of accessible states grows exponentially with the number of qubits used.

Seems powerful, right? Its a huge advantage when approaching problems that require extensive computing power. The downside, however, is that superpositions are probabilistic in nature meaning they wont yield definite outputs about the individual states themselves.

Think of it like a coin flip. When in the air, the state of the coin is indeterminate; it has a 50% probability of landing either heads or tails. Only when the coin reaches the ground does it settle into a value that can be determined precisely.

Quantum superpositions work in a similar way. Theyre a combination of individual states, each with their own probability of showing up when measured.

But the process of measuring wont necessarily collapse the superposition into the value we are looking for. That depends on the probability associated with the correct state.

If we create a superposition of records and measure it, were not necessarily going to get the right answer, Shyamsundar said. Its just going to give us one of the records.

To fully capitalize on the speedup quantum computers provide, then, scientists must somehow be able to extract the correct record they are looking for. If they cannot, the advantage over classical computers is lost.

Amplifying the probabilities of correct states

Luckily, scientists developed an algorithm nearly 25 years ago that will perform a series of operations on a superposition to amplify the probabilities of certain individual states and suppress others, depending on a given set of search criteria. That means when it comes time to measure, the superposition will most likely collapse into the state they are searching for.

But the limitation of this algorithm is that it can be applied only to Boolean situations, or ones that can be queried with a yes or no output, like searching for a jazz album in a stack of several records.

A quantum computer can amplify the probabilities of certain individual records and suppress others, as indicated by the size and color of the disks in the output superposition. Standard techniques are able to assess only Boolean scenarios, or ones that can be answered with a yes or no output. Illustration: Prasanth Shyamsundar

Scenarios with non-Boolean outputs present a challenge. Music genres arent precisely defined, so a better approach to the jazz record problem might be to ask the computer to rate the albums by how jazzy they are. This could look like assigning each record a score on a scale from 1 to 10.

New amplification algorithms expand the utility of quantum computers to handle non-Boolean scenarios, allowing for an extended range of values to characterize individual records, such as the scores assigned to each disk in the output superposition above. Illustration: Prasanth Shyamsundar

Previously, scientists would have to convert non-Boolean problems such as this into ones with Boolean outputs.

Youd set a threshold and say any state below this threshold is bad, and any state above this threshold is good, Shyamsundar said. In our jazz record example, that would be the equivalent of saying anything rated between 1 and 5 isnt jazz, while anything between 5 and 10 is.

But Shyamsundar has extended this computation such that a Boolean conversion is no longer necessary. He calls this new technique the non-Boolean quantum amplitude amplification algorithm.

If a problem requires a yes-or-no answer, the new algorithm is identical to the previous one, Shyamsundar said. But this now becomes open to more tasks; there are a lot of problems that can be solved more naturally in terms of a score rather than a yes-or-no output.

A second algorithm introduced in the paper, dubbed the quantum mean estimation algorithm, allows scientists to estimate the average rating of all the records. In other words, it can assess how jazzy the stack is as a whole.

Both algorithms do away with having to reduce scenarios into computations with only two types of output, and instead allow for a range of outputs to more accurately characterize information with a quantum speedup over classical computing methods.

Procedures like these may seem primitive and abstract, but they build an essential foundation for more complex and useful tasks in the quantum future. Within physics, the newly introduced algorithms may eventually allow scientists to reach target sensitivities faster in certain experiments. Shyamsundar is also planning to leverage these algorithms for use in quantum machine learning.

And outside the realm of science? The possibilities are yet to be discovered.

Were still in the early days of quantum computing, Shyamsundar said, noting that curiosity often drives innovation. These algorithms are going to have an impact on how we use quantum computers in the future.

This work is supported by the Department of Energys Office of Science Office of High Energy Physics QuantISED program.

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. For more information, visit science.energy.gov.

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New computing algorithms expand the boundaries of a quantum future - Fermi National Accelerator Laboratory

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Quantum information science is an on-the-rise field that merges quantum mechanics-based conceptsor those that hone in on how things operate at the subatomic levelwith theories on storing, transmitting, computing or measuring information.

Many argue it will lead to unprecedented breakthroughs across major industries, but QIS is still relatively young among other technology areas, and quantum-ready personnel remainrare and in demand.

The numbers that I could find said something like a total few thousand quantum experts worldwide. Worldwide, there is a shortage, Abiodun Ilumoka, a program director in the National Science Foundations Education and Human Resources Directorate told Nextgov recently. In the United States, there is definitely a shortage. And yes, there's definitely a diversity gap: a huge diversity gap.

Passed in late 2018, the National Quantum Initiative Act aims to spur the governments prioritization of this emerging realm. It incorporates federal mandates to help grow the QIS workforce pipeline. Over the last several months, Nextgov spoke to officials across U.S. public, private and academic sectors about the complexities of quantum career paths, and efforts to help deliberately diversify this up-and-coming talent pool on the front end, before the field is fully realized.

We're not talking about something like the world's 25 million classical developers. We're talking about a few thousand to tens of thousandsthats what we're seeing here. So when we say nascent, it really is a nascent technology, IBMs Global Lead of Quantum Education and Open Science Dr. Abe Asfaw noted. And so how do you take that opportunity, then, to build a community from the ground up that is diverse and inclusive?

Momentum Presents Opportunity

The roots of QIS trace back to the 20th century, and the field saw a real surge in the 1990s.

But today, the U.S. is confronting a need for qualified quantum scientists, engineers and technicians. People with such expertise essentially try to use bizarre features of subatomic phenomena and quantum mechanics that dont occur in standard physicslike the notion that a quantum system can exist in multiple states simultaneously until observedto their advantage. They arent united in one specific type of academic degree, though most have some science, technology, engineering and math-, or STEM-aligned expertise.

The way that the field of quantum information science has been approached has been very interdisciplinary, according to Isabella Bello Martinez, a quantum computing researcher at Booz Allen Hamilton. Colleagues on her team have studied biology, chemistry, psychology and more, while her own background includes some focus on engineering and entrepreneurship. In her current role, Martinez is passionate about assessing what quantum computing means nowand what it might mean for the future.

She said specific areas of study or universities attended matter less in hiring than applicants attitudes. Its about being willing to think about a field that is newthat we don't really know how things work, we will never understand how atoms work, probablyand looking to work with that uncertainty, she explained. So, those building quantum-centered teams can pick from a wide range of individuals who have studied different subsets of math and science regardless of their final degree.

However, those fields I'm thinking about, which are mostly physical sciences, are inherently white spaces, Martinez explained, also noting that there arent a lot of women who pursue these areas. She reflected on an experience in a professional setting that struck her personally, to shed a little light on what it can sometimes be like for those less represented in the field.

I was presenting at a conference, talking about what quantum computing is going to mean to the field of communications, Martinez noted. And I had a gentleman come up to me after the talk, and tell me something along the lines of I'm so impressed that a young Latina woman was able to give such a good presentation, or something to that effect. And I was like, OK, we're leaving, and left the conference for the rest of the day. It was awful.

She considers herself lucky to have not encountered the exact same icky situation again since then, but Martinez added, This also wasn't that long ago, and I think its representative of, not even looking at quantum yet, but just looking at physical sciences.

University of Chicagos Associate Professor in Computer Science and Director of Computer Science Education Diana Franklin told Nextgov that she, too, has seen how the technology communities that trickle out of these topics generally have a shortage of people of color and depending on the subject matter, less women.

I have definitely felt [the diversity gap]. I mean, there are very few women in my department and very few females in my classes. The ways that it plays outwell, it's interesting for me because in computer science education, actually that is not male-dominated, Franklin explained. So for me, it's very interesting because I have one community in which I'm normal, and I have another community where I'm very much a minority. And so you can definitely see the difference in just communication patterns and how I'm treated.

While the federal website quantum.gov emerged amid the Trump administration, it doesnt house one updated public source that captures comprehensive data reflecting or forecasting the U.S. quantum workforce. Whats become clear more recently, though, is that STEM disciplines with some of the lowest representation of women contribute to the strongest involvement in QIS.

According to the 2017 NSF Science and Engineering Indicators, women earned a smaller percentage of Bachelors degrees than men in the primary quantum-related disciplines: computer sciences (19%), engineering (22%), mathematics and statistics (42%), and physical sciences (40%), academics who participated in a 2019 symposium regarding the quantum information science and engineering, or QISE, talent pipeline wrote in a subsequent paper. Further, the quantum thinkers said those same indicators suggest students who identify as Hispanic, Latinx, Black or African American account for a much higher percentage of awarded degrees at the Associates level than at the Bachelors degree level.

While the QISE community is still nascent, emphasizing diversity upfront, rather than as an afterthought, is an essential step forward, they wrote.

NSF statistics informed those viewsand officials within that agency are aware of systemic issues around representation apparent in other technological fields seeping into this realm. As they work to help promote a robust channel for future quantum personnel, federal insiders are also making serious considerations around ensuring its more inclusive.

There are very, very few women and minorities in STEM nationwide, NSFs Ilumoka reiterated. Now, if you consider the quantum technologies emergingthen the diversity gap in quantum is even worse.

Ilumokas interests span complex systems design with artificial intelligence and engineering education. She works in NSFs Education and Human Resources directorate, which she noted focuses on getting folks educated in STEM, but also making sure that they're well-prepared for the workplace.

In December, officials in EHR released a Dear Colleague Letter, detailing existing funding opportunities for education-related research and development to prepare a diverse QISE workforce. Ilumoka said the move was meant to inspire NSFs community to craft projects that will inspire and support students interest in the spaceacross many ages and from many backgrounds. Its just one of several moves NSF made last year to help boost Americas quantum workforce, but together, the programs will account for hundreds of millions towardresearch.

Ilumokas colleague Tomasz Durakiewicz, a condensed matter physicist and program director in NSFs Division of Materials Research, noted that the letter came after the agency had been deliberately refocusing and renewing its approaches to education, broadening participation and workforce development. That work enabled officials across NSFs seemingly disparate realmslike physical sciences and educationto connect and share expertise across curriculum development and enable fundamental QIS research.

The quantum enthusiasm and momentum that is now happening in front of our eyes across this nation brings with it unique opportunities, Durakiewicz said. And this is how we want to look at that: There are challenges out there, but every single challenge is an opportunity.

Eyeing Early Exposure

IBMs Abe Asfaw went to high school in Ethiopia and was later trained as an electrical engineer. More recently, he completed a doctorate at Princeton, where he focused on quantum computinga topic Asfaw said he wasnt introduced to until roughly his senior year of college.

A barrier to entry I think, Asfaw noted, is that we haven't rethought our STEM education in a way that makes quantum mechanics an easy thing to learnand it's something you encounter very late.

His industry-based team is now supporting a government-steered effort to help make that happen.

In August, months before dropping the Dear Colleague letter, NSF partnered with the White House to launch the National Q-12 Education Partnership and Q2Work Program. The partnership is meant to bring together public, private and academic experts to ultimately foster the creation of first-of-a-kind materials for K-12 classrooms intended to spark students interests in quantum-aligned career fields while the program helps facilitate the community developing those resources. The entities involved collectively aim to support and grow a quantum workforce that is diverse and equitable, according to the partnerships website.

NSFs Durakiewicz is enthusiastically involved with Q-12 and Q2Work. He explained that they surfaced as the next steps following a virtual workshop the agency hosted earlier last year to produce what would become Key Concepts for Future Quantum Information Science Learners. Hours of heated debates unfolded among various stakeholders, he said, and after it was over, those involved made it very clear that they wanted the collaboration to continue on the path toward implementation. Durakiewicz noted that while the Office of Science and Technology Policy and NSF spearhead the partnership, theyre working jointly with industry partners, teachers and academics through it.

So then you have the full picture here in this project because you have a very strong tie to reality out there down in the trenchesthe industrial types, they know exactly what they need, with teachers who are supposed to deliver that but don't always have the right tools in handand academics who are developing those tools, he explained. And then on top of it, there is OSTP that provides the necessary anchors, so to speak, in this all-of-government approach.

Partners participating will help design and disseminate a foundation for classroom activities and curricula to spur students interest in QIS topics as early as grade school, and broaden access to such studies throughout K-12 education. Q2Work is a coordinating member of the partnership thatll lead the making of digital tools, collaborative exchanges and other outreach to amplify the resources.

University of Chicagos Franklin was tapped to co-lead Q2Work.

This idea that things that happen at the quantum level are so crazy and no one could understand itit's just not true, Franklin said. And so I'm trying to create the resources that connect these things to things you've already figured out in daily life.

She noted that those involved with Q2Work will host workshops to dive deeper into how NSFs foundational concepts for quantum learners might be applied for different audiences, and for students at different grade levels.

I would characterize our effort not as directly interacting with underserved communities and people of color starting outit's that we want to design for them from day one, instead of designing for people who are already successful, Franklin noted. A lot of early computer science outreach activities were people designing for what they wish they had when they were young, which of course, those were the people who already made it in computer science. And if we want to broaden participation, we have to do different types of activities than the ones that you wish you would have. That's been a big challenge to get people to understand in computer science. And so for quantum, we want to start with that.

Speaking from experience, Booz Allen Hamiltons Martinez said its very good that there is going to be a concerted unifying effort to increase early education in quantum topics. She recalled referencing being taught about the electron model of an atom in grade school in a recent conversation with a male colleague, whod responded that he wasnt introduced to the subject until college.

So that's the kicker, right? I went to a private school, Martinez noted, adding that her teachers empowered female students from an early age. She had access to and was placed into advanced classes, and had a support system and resources to pursue her interests.

And that is, by far, not the normal experience for someone whose parents are immigrants from Latin America, or someone who is Black growing up in a rural community, or even just communities that are poor, like Rust Belt communities, or communities in the Appalachian that don't have access to those resources, she said. And clearly, it didn't bother [my colleague] that he did not learn about quantum until undergrad. Clearly, it captivated his imagination. But I imagine that he had people telling him You are smart, you should pursue science, as a childthe same way I did.

To Martinez, children likely wont dwell on complicated topics unless they have an inherent interest in them or someone encourages them, and teachers in many of these communities are already too overburdened to learn such weedy topics independently.

So this is cool, this needs to be doneit can go further, she said. Like I would like to see, once this curriculum gets developed a bit more, very deliberate partnerships with the teachers to give them the time, the funds and the support that they need in order to give their students support that they need.

Theres More

Among the Q2Work programs various founding members was IBM. The company for years now has been rolling out quantum-centered educational activities that incorporate device access and events like hackathons to inspire its next generation of workers. Officials released an open-source quantum software platform known as Qiskit, and the Qiskit Textbook and Qiskit Global Summer School to help outsiders learn quantum computation using it. Those are essentially a collection of tools that allow almost anyone to write and run programs on quantum computers.

The goal of all these open-source efforts is to work with the community to build everythingincluding the quantum computing software and the educational materials. I am seeing 16-year-olds contributing to our open-source quantum computing textbook and just wondering how much times have changed because these resources were not accessible to me at that time, Asfaw said. And so that's one of the things that makes all of this education work rewarding is seeing things like that.

On top of other pursuits, the company aims to make its Quantum Educators program, which provides teachers and their students with prioritized use of IBM quantum systems via the cloud, available to K-12 schools through Q2Work.

It's one of these situations where the interests of the industry align with what I consider to be good for the world. So good for the world, I would consider it to be everyone is equipped and ready to do quantum computing and has access to quantum computers. The interest of the industry would be to see more people exploring the field and coming up with applications for quantum computing, Asfaw said. Both of them are aligned here, and we have a pretty good opportunity to make sure that we build this nascent technology from the ground up while being inclusive to everyone.

Beyond Q-12 and Q2Work, NSF, IBM and other major science players are also supporting some historically Black colleges and universities to expand students exposure and access to quantum opportunities, and embarking on other pursuits to meet this national initiative.

Imagine this fast train that is zooming through the countrythis is a quantum train. Everyone who wants a ticket should be able to get a ticket on this train to benefit from this revolution, NSFs Durakiewicz said. And inclusion here, it's not an obligation, it is an opportunity to do the right thing. If we fail in broadening participation in quantum, we will fail in quantumperiod. We cannot afford that.

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Officials Aim to Diversify the U.S. Quantum Workforce Early On - Nextgov

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Particle physicists use lattice quantum chromodynamics and supercomputers to search for physics beyond the Standard Model.

Peer deeper into the heart of the atom than any microscope allows and scientists hypothesize that you will find a rich world of particles popping in and out of the vacuum, decaying into other particles, and adding to the weirdness of the visible world. These subatomic particles are governed by the quantum nature of the Universe and find tangible, physical form in experimental results.

Some subatomic particles were first discovered over a century ago with relatively simple experiments. More recently, however, the endeavor to understand these particles has spawned the largest, most ambitious and complex experiments in the world, including those at particle physics laboratories such as the European Organization for Nuclear Research (CERN) in Europe, Fermilab in Illinois, and the High Energy Accelerator Research Organization (KEK) in Japan.

These experiments have a mission to expand our understanding of the Universe, characterized most harmoniously in the Standard Model of particle physics; and to look beyond the Standard Model for as-yet-unknown physics.

This plot shows how the decay properties of a meson made from a heavy quark and a light quark change when the lattice spacing and heavy quark mass are varied on the calculation. Credit: A. Bazavov (Michigan State U.), C. Bernard (Washington U., St. Louis), N. Brown (Washington U., St. Louis), C. DeTar (Utah U.), A.X. El-Khadra (Illinois U., Urbana and Fermilab) et al.

The Standard Model explains so much of what we observe in elementary particle and nuclear physics, but it leaves many questions unanswered, said Steven Gottlieb, distinguished professor of Physics at Indiana University. We are trying to unravel the mystery of what lies beyond the Standard Model.

Ever since the beginning of the study of particle physics, experimental and theoretical approaches have complemented each other in the attempt to understand nature. In the past four to five decades, advanced computing has become an important part of both approaches. Great progress has been made in understanding the behavior of the zoo of subatomic particles, including bosons (especially the long sought and recently discovered Higgs boson), various flavors of quarks, gluons, muons, neutrinos and many states made from combinations of quarks or anti-quarks bound together.

Quantum field theory is the theoretical framework from which the Standard Model of particle physics is constructed. It combines classical field theory, special relativity and quantum mechanics, developed with contributions from Einstein, Dirac, Fermi, Feynman, and others. Within the Standard Model, quantum chromodynamics, or QCD, is the theory of the strong interaction between quarks and gluons, the fundamental particles that make up some of the larger composite particles such as the proton, neutron and pion.

Carleton DeTar and Steven Gottlieb are two of the leading contemporary scholars of QCD research and practitioners of an approach known as lattice QCD. Lattice QCD represents continuous space as a discrete set of spacetime points (called the lattice). It uses supercomputers to study the interactions of quarks, and importantly, to determine more precisely several parameters of the Standard Model, thereby reducing the uncertainties in its predictions. Its a slow and resource-intensive approach, but it has proven to have wide applicability, giving insight into parts of the theory inaccessible by other means, in particular the explicit forces acting between quarks and antiquarks.

A plot of the Unitarity Triangle, a good test of the Standard Model, showing constraints on the , plane. The shaded areas have 95% CL, a statistical method for setting upper limits on model parameters. Credit: A. Ceccucci (CERN), Z. Ligeti (LBNL) and Y. Sakai (KEK)

DeTar and Gottlieb are part of the MIMD Lattice Computation (MILC) Collaboration and work very closely with the Fermilab Lattice Collaboration on the vast majority of their work. They also work with the High Precision QCD (HPQCD) Collaboration for the study of the muon anomalous magnetic moment. As part of these efforts, they use the fastest supercomputers in the world.

Since 2019, they have used Frontera at the Texas Advanced Computing Center (TACC) the fastest academic supercomputer in the world and the 9th fastest overall to propel their work. They are among the largest users of that resource, which is funded by the National Science Foundation. The team also uses Summit at the Oak Ridge National Laboratory (the #2 fastest supercomputer in the world); Cori at the National Energy Research Scientific Computing Center (#20), and Stampede2 (#25) at TACC, for the lattice calculations.

The efforts of the lattice QCD community over decades have brought greater accuracy to particle predictions through a combination of faster computers and improved algorithms and methodologies.

We can do calculations and make predictions with high precision for how strong interactions work, said DeTar, professor of Physics and Astronomy at the University of Utah. When I started as a graduate student in the late 1960s, some of our best estimates were within 20 percent of experimental results. Now we can get answers with sub-percent accuracy.

Frontera was the fifth most powerful supercomputer in the world and fastest academic supercomputer, according to the November 2019 rankings of the Top500 organization. Frontera is located at the Texas Advanced Computing Center and supported by National Science Foundation. Credit: TACC

In particle physics, physical experiment and theory travel in tandem, informing each other, but sometimes producing different results. These differences suggest areas of further exploration or improvement.

There are some tensions in these tests, said Gottlieb, distinguished professor of Physics at Indiana University. The tensions are not large enough to say that there is a problem here the usual requirement is at least five standard deviations. But it means either you make the theory and experiment more precise and find that the agreement is better; or you do it and you find out, Wait a minute, what was the three sigma tension is now a five standard deviation tension, and maybe we really have evidence for new physics.'

DeTar calls these small discrepancies between theory and experiment tantalizing. They might be telling us something.

Over the last several years, DeTar, Gottlieb and their collaborators have followed the paths of quarks and antiquarks with ever-greater resolution as they move through a background cloud of gluons and virtual quark-antiquark pairs, as prescribed precisely by QCD. The results of the calculation are used to determine physically meaningful quantities such as particle masses and decays.

One of the current state-of-the-art approaches that is applied by the researchers uses the so-called highly improved staggered quark (HISQ) formalism to simulate interactions of quarks with gluons. On Frontera, DeTar and Gottlieb are currently simulating at a lattice spacing of 0.06 femtometers (10-15 meters), but they are quickly approaching their ultimate goal of 0.03 femtometers, a distance where the lattice spacing is smaller than the wavelength of the heaviest quark, consequently removing a significant source of uncertainty from these calculations.

Each doubling of resolution, however, requires about two orders of magnitude more computing power, putting a 0.03 femtometers lattice spacing firmly in the quickly-approaching exascale regime.

The costs of calculations keeps rising as you make the lattice spacing smaller, DeTar said. For smaller lattice spacing, were thinking of future Department of Energy machines and the Leadership Class Computing Facility [TACCs future system in planning]. But we can make do with extrapolations now.

Among the phenomena that DeTar and Gottlieb are tackling is the anomalous magnetic moment of the muon (essentially a heavy electron) which, in quantum field theory, arises from a weak cloud of elementary particles that surrounds the muon. The same sort of cloud affects particle decays. Theorists believe yet-undiscovered elementary particles could potentially be in that cloud.

A large international collaboration called the Muon g-2 Theory Initiative recently reviewed the present status of the Standard Model calculation of the muons anomalous magnetic moment. Their review appeared in Physics Reports in December 2020. DeTar, Gottlieb and several of their Fermilab Lattice, HPQCD and MILC collaborators are among the coauthors. They find a 3.7 standard deviation difference between experiment and theory.

While some parts of the theoretical contributions can be calculated with extreme accuracy, the hadronic contributions (the class of subatomic particles that are composed of two or three quarks and participate in strong interactions) are the most difficult to calculate and are responsible for almost all of the theoretical uncertainty. Lattice QCD is one of two ways to calculate these contributions.

The experimental uncertainty will soon be reduced by up to a factor of four by the new experiment currently running at Fermilab, and also by the future J-PARC experiment, they wrote. This and the prospects to further reduce the theoretical uncertainty in the near future make this quantity one of the most promising places to look for evidence of new physics.

Gottlieb, DeTar and collaborators have calculated the hadronic contribution to the anomalous magnetic moment with a precision of 2.2 percent. This give us confidence that our short-term goal of achieving a precision of 1 percent on the hadronic contribution to the muon anomalous magnetic moment is now a realistic one, Gottlieb said. The hope to achieve a precision of 0.5 percent a few years later.

Other tantalizing hints of new physics involve measurements of the decay of B mesons. There, various experimental methods arrive at different results. The decay properties and mixings of the D and B mesons are critical to a more accurate determination of several of the least well-known parameters of the Standard Model, Gottlieb said. Our work is improving the determinations of the masses of the up, down, strange, charm and bottom quarks and how they mix under weak decays. The mixing is described by the so-called CKM mixing matrix for which Kobayashi and Maskawa won the 2008 Nobel Prize in Physics.

The answers DeTar and Gottlieb seek are the most fundamental in science: What is matter made of? And where did it come from?

The Universe is very connected in many ways, said DeTar. We want to understand how the Universe began. The current understanding is that it began with the Big Bang. And the processes that were important in the earliest instance of the Universe involve the same interactions that were working with here. So, the mysteries were trying to solve in the microcosm may very well provide answers to the mysteries on the cosmological scale as well.

Reference: The anomalous magnetic moment of the muon in the Standard Model by T. Aoyama, N. Asmussen, M. Benayoun, J. Bijnens, T. Blum, M. Bruno, I. Caprini, C. M. Carloni Calame, M. C, G. Colangelo, F. Curciarello, H. Czyz, I. Danilkin, M. Davier, C. T. H. Davies, M. Della Morte, S. I. Eidelman, A. X. El-Khadra, A. Grardin, D. Giusti, M. Golterman, StevenGottlieb, V. Glpers, F. Hagelstein, M. Hayakawa, G. Herdoza, D. W. Hertzog, A. Hoecker, M. Hoferichter, B.-L. Hoid, R. J. Hudspith, F. Ignatov, T. Izubuchi, F. Jegerlehner, L. Jin, A. Keshavarzi, T. Kinoshita, B. Kubis, A. Kupich, A. Kupsc, L. Laub, C. Lehner, L. Lellouch, I. Logashenko, B. Malaescu, K. Maltman, M. K. Marinkovic, P. Masjuan, A. S. Meyer, H. B. Meyer, T. Mibe, K. Miura, S. E. Mller, M. Nio, D. Nomura, A. Nyffeler, V. Pascalutsa, M. Passera, E. Perez del Rio, S. Peris, A. Portelli, M. Procura, C. F. Redmer, B. L. Roberts, P. Snchez-Puertas, S. Serednyakov, B. Shwartz, S. Simula, D. Stckinger, H. Stckinger-Kim, P. Stoffer, T. Teubner, R. Van de Water, M. Vanderhaeghen, G. Venanzoni, G. von Hippel, H. Wittig, Z. Zhang, M. N. Achasov, A. Bashir, N. Cardoso, B. Chakraborty, E.-H. Chao, J. Charles, A. Crivellin, O. Deineka, A. Denig, C. DeTar, C. A. Dominguez, A. E. Dorokhov, V. P. Druzhinin, G. Eichmann, M. Fael, C. S. Fischer, E. Gmiz, Z. Gelzer, J. R. Green, S. Guellati-Khelifa, D. Hatton, N. Hermansson-Truedsson, S. Holz, B. Hrz, M. Knecht, J. Koponen, A. S. Kronfeld, J. Laiho, S. Leupold, P. B. Mackenzie, W. J. Marciano, C. McNeile, D. Mohler, J. Monnard, E. T. Neil, A. V. Nesterenko, K. Ottnad, V. Pauk, A. E. Radzhabov, E. de Rafael, K. Raya, A. Risch, A. Rodrguez-Snchez, P. Roig, T. San Jos, E. P. Solodov, R. Sugar, K. Yu. Todyshev, A. Vainshtein, A. Vaquero Avils-Casco, E. Weil, J. Wilhelm, R. Williams and A. S. Zhevlakov, 14 August 2020, .DOI: 10.1016/j.physrep.2020.07.006

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Searching for New Physics in the Subatomic World - SciTechDaily

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