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By Amy Wolff For �ԹϺ�����

For most high school students, summers are for hanging out, playing video games, and staying up too late. Well, most high-schoolers are not Max Bee-Lindgren, a senior at Decatur High School in Decatur, Georgia. In 2021, Max spent his summer calculating transition matrix elements, the rate at which atoms, molecules, and other quantum-mechanical systems change states when interacting with their environments.

One important calculation is the emission of light from an excited electron in an atom. This state change is difficult to model accurately on current (classical) computers. Quantum computers, like those being developed by �ԹϺ�����, hold great promise for modeling quantum systems but require new algorithms to make efficient use of their capabilities in a way that is robust to noise.

“I’ve always wanted to know how things worked — more specifically — why things happen,” said Max. “When I was a kid, I would endlessly ask my parents ‘why.’ When they answered, it would just trigger more and more questions down an endless chain until eventually the answer would end up being ‘it’s a complicated physics thing we can’t explain.’ So, I figured if I wanted to actually know why things happen, I should probably learn physics.”��

For several months last summer, Max had the chance to collaborate online with other physics fanatics, including his mentor, , and Kenneth Choi, a freshman at MIT who created the original rodeo algorithm during his apprenticeship with Dr. Lee in 2020. They were also joined by MSU students Zhengrong Qian, Jacob Watkins, Gabriel Given and Joey Bonitati.��

The team met several times a week to discuss new developments in the rodeo algorithm research, collaborate about next steps, and get any big news updates on the project. The time spent paid off when Max was notified that he, along with 39 other high schoolers from across the U.S., was a finalist in the for high school seniors.

Like many people, when a call from an unknown number came in on his phone, Max declined the call. But when the Washington, D.C., number called back a second time, he picked up and was “shocked” to discover he had made the competition’s top 40.��

“Being a part of this intensive summer program has driven me to complete the project in the best way possible,” Max said. “Without the support of Dr. Lee and his team, I would still be researching, but not fully applying myself nor putting my experience into practice. It is nice to have a direct and present force driving me to succeed, and thanks to the STS program and my experiences, I’ve met a lot of amazing people who are as focused on physics as I am.”

�ԹϺ����� is an integral partner in the success of this research project.

��“The purpose of this collaboration is one of mutual benefits,” said Dr. David Hayes, a principal theorist at �ԹϺ�����. “Professor Lee and his students get to test their theories on real hardware and identify any weaknesses in the proposal. �ԹϺ����� benefits by helping the world get a little closer to identifying quantum algorithms that yield a computational advantage over classical algorithms.”��

“�ԹϺ����� is well served by the world-wide effort to advance these algorithms, so we try to identify the most promising ones and provide testbeds for them,” Hayes added. “Professor Lee's proposal caught our eye last year as a new idea for simulating quantum materials, which we believe to be the most promising avenue toward a near-term quantum advantage.”����

The 2022 Regeneron Science Talent Search finalists were selected from more than 1,800 highly qualified entrants based on their projects’ scientific rigor and their potential to become world-changing scientists and leaders. Each finalist is awarded at least $25,000, and the top 10 awards range from $40,000 to $250,000.

“Max’s award is for the design of the two-state rodeo algorithm,” said Dr. Lee. “The potential promise of the rodeo algorithm lies in its ability to be robust against noise and exponentially more efficient than other well-known methods for quantum state preparation.”��

Max shares his notebook with the �ԹϺ����� theory group regularly and is looking forward to implementing his algorithm soon on the company’s System Model H1 quantum technologies, Powered by Honeywell.��

“In the next few months, we’ll get a chance to run the two-state rodeo algorithm on the H1, which is very exciting,” Max stated. “The H1 is a good bit less error prone than other available systems, by an order of magnitude, so the results should be interesting as they unfold.”����

“Max was a great person to work with,” noted Professor Lee. “No matter what I gave him, he never got really stuck on anything. Max truly loves his work, and he’s very humble. He has a maturity beyond his years, which will serve him well in future endeavors.”����

While Max is unsure about his college choice for next year, he is certain of one thing, “I can’t wait to get to college to just study more physics.”

�ԹϺ����� researchers have set a record for the number of times they were able to place qubits into a quantum state and then measure the results, beating the previously stated best in class many times over.

The team led by Alex An, Tony Ransford, Andrew Schaffer, Lucas Sletten, John Gaebler, James Hostetter, and Grahame Vittorini achieved a state preparation and measurement, or SPAM, fidelity of 99.9904 percent — the highest of any quantum technology to date — using qubits formed from non-radioactive barium-137. The results, which are detailed here, have been submitted to arXiv.

This work has major implications for the quantum industry and trapped-ion technologies.��

Improving SPAM fidelity helps reduce errors that accumulate in today’s “noisy” quantum machines, which is critical for moving to “fault-tolerant” systems that prevent errors from cascading through a system and corrupting circuits.

In addition, being able to form qubits from barium-137 and place them into a quantum state with high fidelity is advantageous for scaling trapped-ion hardware systems.�� Researchers can use lasers in the visible spectrum, a more mature and readily available technology, to initialize and manipulate qubits.��

“This is a major step forward for the �ԹϺ����� team and our high-performing trapped-ion quantum hardware,” said Tony Uttley, �ԹϺ����� president and chief operating officer.�� “The advancement of the quantum computing industry as a whole is going to come from lots of individual technological achievements like this one, paving the way for future fault-tolerant systems.”

What is SPAM?

For most people, the word “spam” conjures images of unwanted emails flooding an inbox or of chopped pork in a can.��

In quantum computing, SPAM stands for identified by theoretical physicist David DiVincenzo as necessary for the operation of quantum computer. It refers to initializing qubits (placing them in a quantum state) and then measuring the output. SPAM is measured in terms of fidelity, or the ability to complete these tasks at a high rate of success. The higher the fidelity the better because it means a quantum computer is performing these critical tasks with fewer errors.��

Researchers at �ԹϺ����� believe to reach the point at which the logical error rate beats the leading order physical error rate.

Why barium?

Neutral ytterbium atoms have long been a source of ions in trapped-ion quantum computers. Charged by lasers, ytterbium ions are transformed into qubits. But using ytterbium presents challenges. Expensive ultraviolet lasers are needed to manipulate ytterbium ions and the results can be difficult to measure.

Barium ions, however, are easier to measure and can be manipulated with less expensive and more stable lasers in the green range. But until this work with non-radioactive barium-137, researchers have only been able to achieve low SPAM errors with barium-133 atoms, which are radioactive and require special handling.��

“Nobody thought you could do quick, robust SPAM with non-radioactive barium-137,” said Dr. Anthony Ransford, a �ԹϺ����� physicist and technical lead. “We were able to devise a scheme that enabled us to initialize the qubits and measure them better than any other qubits. We are the first to do it.”

What’s next

Being able to initialize non-radioactive barium-137 ions is just the first step.�� The goal is to incorporate these ions into future �ԹϺ����� hardware technologies.��

“We believe using non-radioactive barium-137 ions as qubits is an attractive path to increasingly robust, scalable, quantum hardware,” Uttley said.��

‍By Kevin Jackson for �ԹϺ�����

Some might view games as merely entertainment but for Professor Emanuele Dalla Torre at and his team, playing games is useful for measuring the effectiveness of today’s commercial quantum computers.

In a recent study published in , Dalla Torre and two of his students, Meron Sheffer and Daniel Azses, describe how they ran a collaborative, mathematical game on different technologies to evaluate 1) whether the systems demonstrated quantum mechanical properties and 2) how often the machines delivered the correct results. The team then compared the results to those generated by a classical computer.

Of the technologies tested, only the �ԹϺ����� System Model H1-1, Powered by Honeywell, outperformed the classical results. Dalla Torre said classical computers return the correct answer only 87.5 percent of the time. The H1-1 returned the correct answer 97 percent of the time. (The team also tested the game on the now-retired System Model H0, which achieved 85 percent.)

“What we see in the H1 is that the probability is not 100 percent, so it's not a perfect machine, but it is still significantly above the classical threshold. It's behaving quantum mechanically,” Dalla Torre said.

Playing the game

The mathematical game Dalla Torre and his team played requires non-local correlations. In other words, it’s a collaborative game in which parts of the system can’t communicate to solve challenges or score points.

“It's a collaborative game based on some mathematical rules, and the players score a point if they can satisfy all of them,” said Dalla Torre. “The key challenge is that during the game, the players cannot communicate among themselves. If they could communicate, it would be easy – but they can’t. Think of building something without being able to talk to each other. So, there is a limit to how much you can do. For the machines in this game, this is the classical threshold.”

Quantum computers are uniquely suited to solve such problems because they follow quantum mechanical properties, which allow for non-local effects. According to quantum mechanics, something that is in one place can instantaneously affect something else that is in a different place.

“What this experiment demonstrates is that there is a non-local effect, meaning that when you measure one of the qubits, you are actually affecting the others instantaneously,” Dalla Torre said.

Less noise, higher performance

Dalla Torre attributes the performance of the �ԹϺ����� technology to their low level of “noise”.

All commercial quantum computers operating today experience noise or interference from a variety of sources. Eliminating or suppressing such noise is essential to scaling the technology and achieving fault tolerant systems, a design principle that prevents errors from cascading throughout a system and corrupting circuits.

“Noise in this context just means an imperfection – it’s like a typo,” Dalla Torre said “So, a quantum computer does a computation and sometimes it gives you the wrong answer. The technical term is NISQ, noisy intermediate scale quantum computing. This is the general name of all the devices that we have right now. These are devices that are quantum, but they are not perfect ones. They make some mistakes.”

For Dr. Brian Neyenhuis, Commercial Operations Group Leader at �ԹϺ�����, projects such as Dalla Torre's are useful benchmarks of early quantum computers and, also help demonstrate and more clearly understand the difference between classical and quantum computation.

After seeing the initial results from the H0 system, he worked with Dalla Torre to run it again on the upgraded H1 system (still only using six qubits).

"We knew from a large number of standard benchmarks that the H1 system was a big step forward for us, but it was still nice to see such a clear signal that the improvements that we had made translated directly to better performance on this non-local game,” Dr. Neyenhuis said.

What’s next

Dalla Torre and his students completed the experiment through the platform. “Being able to do this kind of work on the cloud is vital for the growth of quantum experimentation,” he said. “The fact that I was sitting in Israel at and I could connect to the computers and use them using on the internet, that's something amazing.”

Dalla Torre and his team would like to expand this sort of research in the future, especially as commercial quantum computers add qubits and reduce noise.

By Kevin Jackson for �ԹϺ�����

The world is a lot smaller than it was in the previous century – or even in the previous decade.��

Customers are now accustomed to a wide variety of products that can be delivered from distributors all over the globe. While this is a great opportunity for suppliers, it also presents a challenge in the form of supply chain, logistics, routing, and optimization.��

How can distribution companies continue to serve the needs of their customers in the most efficient and effective way possible? This may seem like a simple question, but it becomes a complex computational problem when trying to account for all the variables that can occur within a distribution network.��

What’s more, classical computers simply cannot adequately perform this optimization calculation in real-world scenarios. Because of the number of variables, the math just runs too slow.��

That said, new work in quantum computing has shown promise in applications within the optimization field. To that end, we interviewed �ԹϺ�����’s and to better understand how quantum computing could to optimized logistics and supply chains.

Kohagen and Fiorentini are participating in a panel about quantum computing at this week in Las Vegas, Nevada.

Beyond classical computing

When it comes to optimization it is all about maximizing or minimizing an objective.�� A good example is a company that delivers goods and products but owns a limited number of trucks. To improve efficiency and minimize costs, the company needs to maximize the number of objects its trucks carry and identify the shortest routes between deliveries.

“You have all these constraints, you have your objective, and you’ve got to make decisions,” said Kohagen, an optimization researcher. “The decisions end up being things like how many goods you are going to send between your distribution centers and your stores? Each of these optimization problems, even if you consider them separately, are hard problems. The technical term is that they’re (non-deterministic polynomial)-hard because you’re dealing with discrete things. For example, I can’t send half a T-shirt to my customer. I can only operate with whole integers.”��

Fiorentini expands on this: “In logistics, we cannot leave anyone behind. If we need to deliver medicine, we cannot decide ‘the villages with less than 1,000 people – we don’t supply them. There are too many, and not enough people live there’. That’s not an option in today’s world.”

Today’s computers struggle to solve these NP-hard optimization problems because of the number of ever-changing variables.�� Consider the much-studied Traveling Salesperson Problem, which is often used to illustrate the complexity of managing logistics, routing, and supply chains.����

This is a theoretical problem where a machine is tasked with finding the shortest route between an identified list of cities that a “salesperson” must visit before returning to the point of origin. This problem is simple enough with only a few cities, but it becomes exponentially harder as more locations are added, and other factors such as multiple salespeople, weather conditions, and unforeseen events arise.��

Classical computers can solve this theoretical problem for a single salesperson traveling to thousands of cities. But this scenario is not realistic, and this is where classical computers begin to struggle.

“The Traveling Salesperson Problem is not very representative of what happens in the real world,” Kohagen said. “For example, with online ordering so prevalent, a retailer has orders coming in constantly. They must determine how to efficiently retrieve those items from the warehouse, pack them into the trucks, and then transport them to the customers.”

Today, the reality of an extended supply chain or distribution network is beyond what the best classical computer can solve. Quantum computers harness unique properties of quantum physics that enable them to examine all possible answers simultaneously and then concentrate the probable output of the computation onto the best option.

“Classical is a great technology, but it doesn’t cut it here,” said Fiorentini, who develops and tests quantum algorithms for optimization. “Quantum is the best alternative to classical computing that we have.“

The quantum computing opportunity

Optimization problems have long been viewed as “killer applications” for quantum computing and research conducted by Fiorentini, Kohagen and others has begun to prove that.��

Fiorentini believes it is time for decision makers to explore and invest in quantum-enabled solutions for optimization problems. “There are two decisions here for decision makers,” he said. “We either give up on the problem and say, ‘we’ll just do the best we can with a classical solution, or we start allocating a budget for really developing quantum technology.”

Quantum computing is expanding rapidly and is poised to disrupt markets such as optimization.�� A similar situation is the power sector, which is experiencing major disruptions due to innovations in renewable energy resources, energy storage, and regulatory reform.��

Every technology has a tipping point, and all signs point to a current trend in quantum computing moving rapidly to real-world applications in optimization.

“There are a lot of algorithms being developed for optimization right now,” said Kohagen. “If you really want to advance your business with quantum methods for logistics or supply chain, this is the moment to start. Decision makers must act quickly. Those that seize the opportunity before others will have a major advantage over those who lag.”

“As quantum computers continue to scale in computational power, they’ll be able to handle increasingly complex calculations to deliver more robust and optimized supply chain solutions,” said Tony Uttley, President and COO of �ԹϺ�����.

“We’re excited by the acceleration of our System Model H1 technologies, Powered by Honeywell. Measured in terms of qubit number as well as quantum volume, we’re meeting our commitment to increase performance by a factor of 10X each year,” he said. “Alongside other revolutionary advances such as real-time error correction, we look forward to supporting the commercialization of quantum applications that will change the way logistical challenges are met. In fact, within the coming few months we’ll be sharing more exciting news regarding our latest technological achievements.”

Want to learn about our work to develop quantum-enabled optimization solutions for companies? Contact our experts

Since 1851, the World’s Fairs, now known as World Expos, have brought people together to innovate, collaborate and solve important problems.��

The theme for this year’s World Expo, currently taking place in Dubai in the United Arab Emirates, is “Connecting Minds, Creating the Future.” �ԹϺ�����’s trapped-ion quantum computing technology, Powered by Honeywell, is one of a handful of breakthrough technologies chosen to showcase American innovation at the global event.��

Honeywell’s quantum computing division recently combined with Cambridge Quantum to form �ԹϺ�����. Honeywell is majority owner of the new company, which aims to accelerate the development of this disruptive technology and deliver real-world, quantum solutions faster.

Here are some things to know about the World Expo, quantum computing and our involvement in the global event:

1. This is the first World Expo to showcase quantum computing. Visitors to the take a 25-minute journey along a moving walkway and experience an immersive exhibit about how American ingenuity is shaping the future. Themed “The Sky is No Longer the Limit,” the exhibit showcases the System Model H1 quantum computing technology and its potential to help humans solve problems considered too complex for classical computers.
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2. The United Arab Emirates is the first Middle Eastern country to host the World Expo.��The first World’s Fair took place in London in 1851. It is held every five years and much like the Olympics, countries vie to host the event. In 2013, the United Arab Emirates became the first country in the Middle East, Africa, and South Asia (MEASA) region) selected to host a World Expo.
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3. The World Expo site in Dubai covers more than 1,000 acres.��The USA Pavilion boasts more than 20,000 square feet of indoor and outdoor exhibition space.��
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4. There are expected to be 25 million visits to the Expo during its six-month run. More than 4 million are expected to visit the USA Pavilion.
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5. Honeywell is an official sponsor of the USA Pavilion, which is also equipped with some of the company’s advanced security and access control systems.
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“We are proud to showcase quantum computing technology at what has been the world’s premier event for innovation for more than 170 years,” said Tony Uttley, president of �ԹϺ�����.��“Quantum computing will disrupt our world and enable us to solve critical challenges that we can’t with today’s technology. It is an honor that our trapped-ion quantum computing technology, which has led to our release of the highest performing commercial quantum computers in the world, has been included in momentous event.”��

�ԹϺ�����’s H-Series quantum computers, Powered by Honeywell, continue to deliver on exponential performance gains

Over the course of 2021, �ԹϺ�����’s customers and collaborators were the beneficiaries of a deliberate, strategic approach to quantum computing design. Namely, that it is possible to release a generation of quantum computers that can be quickly and systematically upgraded in parallel with commercial usage, allowing customers immediate access to the latest upgrades.

With the release of the System Model H1, Powered by Honeywell, in fall 2020, �ԹϺ����� began a real-time demonstration of its design approach. The first System Model H1, referred to as the H1-1, launched in October 2020 with a measured quantum volume of 128. Quantum volume is a metric introduced by IBM to measure the overall capability and performance of a quantum computing system regardless of technology. (Calculating requires running a series of complex random circuits and performing a statistical test on the results.)��

During 2021, �ԹϺ�����, under its trapped-ion hardware group, previously known as Honeywell Quantum Solutions, made multiple upgrades to the H1-1 achieving and the 1,024 in July 2021. During that same period, �ԹϺ����� was quietly releasing its second H1 generation quantum computer to customers and collaborators, called the H1-2. The System Model H1-2 uses the same ion-trap architecture, control system design, integrated optics, and photonics as the H1-1.��

“Our H1 generation of quantum computers are nearly identical copies, with the ongoing exception that at any given time one computer might have received upgrades prior to the other,” said Dr. Russ Stutz, Head of Commercial Products for the hardware team.��“Our goal is to provide users with the highest performing hardware as they work on solving real world problems."

Upgrades to both H1 quantum computers over the course of 2021 included improved gate and measurement fidelities, reduced memory errors, faster circuit compilation, inclusion of real-time classical computing resources and quantum operations using 12 qubits, versus the 10 qubits available at initial release.

What has been remarkable about the approach, is the ability to deliver near-continuous capability upgrades while being consistent on performance.��

“Our customers frequently comment about their ability to reliably get expected results, including when running deep circuits and using sophisticated features like mid-circuit measurement, qubit reuse and conditional logic,” said Dr. Brian Neyenhuis, Head of Commercial Operations for the hardware team.

Just this past week, H1-2 measured a Quantum Volume of 2,048 (2¹¹), setting a new bar on the highest quantum volume ever measured on a quantum computer. The performance of the H1 generation of quantum computers continues to achieve the 10X per year increase that was announced in March 2020.

The Data

The average single-qubit gate fidelity for this milestone was 99.996(2)%, the average two-qubit gate fidelity was 99.77(9)%, and state preparation and measurement (SPAM) fidelity was 99.61(2)%. We ran 2,000 randomly generated quantum volume circuits with 5 shots each, using standard optimization techniques to yield an average of 122 two-qubit gates per circuit.

The System Model H1-2 successfully passed the quantum volume 2,048 benchmark, returning heavy outputs 69.76% of the time, which is above the 2/3 threshold with 99.87% confidence.

The plot above shows the heavy outputs for �ԹϺ�����’s tests of quantum volume and the dates when each test passed. All tests are above the 2/3 threshold to pass the respective quantum volume benchmark. Circles indicate heavy output averages and the violin plots show the histogram distributions. Data colored in blue show system performance results and red points correspond to modeled, noise-included simulation data. White markers are the lower two-sigma error bounds.

The plot above shows the individual heavy outputs for each quantum volume 2,048 circuit. The blue line is an average of heavy outputs and the orange line is the lower two-sigma error bar which crosses the 2/3 threshold after 818 circuits, which corresponds to passing.

This is the latest in a string of accomplishments for �ԹϺ�����, which recently announced the completion of its combination between Honeywell Quantum Solutions and Cambridge Quantum Computing to form the largest stand-alone integrated quantum computing company in the world. This news also falls on the heels of the release of �ԹϺ�����’s flagship product, Quantum Origin, the world’s first quantum-enhanced cryptographic key generation platform.��

“We look forward to continued momentum in 2022 with expected advances in multiple application areas as well as further advances in the H-Series quantum computers”, said Tony Uttley, President and Chief Operating Officer of �ԹϺ�����.

* The Honeywell trademark is used under license from Honeywell International Inc.��Honeywell makes no representations or warranties with respect to this product or service.