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When was the last time you knowingly encountered helium, the gas that makes balloons float and children�OK, adults too�giggle and talk in high, squeaky voices after inhaling it? ��Likely at a birthday party, wedding, or another celebration, right? ��

Helium, however, has many applications beyond party balloons. Pure, high-quality helium is critical to several industries and technologies, including quantum computing.

�Many quantum computing technologies use helium,� said Steve Sanders, director of engineering at ���Ͽ�, which develops trapped-ion quantum computing technologies. �We use it to keep our ion traps very cold because they operate better below 50 degrees Kelvin. The helium also has the effect of lowering the gas pressure inside our physics packages and keeping the few remaining gas atoms cold. ��Fewer gas atoms mean fewer collisions with our ions. ��And cold gas atoms have far less energy, so even if they collide with our ions, they don�t disturb them.�

Found among the stars, helium is one of the most abundant elements in the universe, second only to hydrogen. On earth, where it formed from alpha-particles of radioactive elements decaying beneath the surface, helium is a finite resource. And that why ���Ͽ� has significantly invested in staff and infrastructure to reuse as much helium as possible.

�We recognize the physical and socioeconomic impacts of both limited natural resources and climate change, so it crucial for us to operate as sustainably as possible,� said Tony Uttley, president and chief operating officer at ���Ͽ�. ��

Andy Miller, an engineer at ���Ͽ�, spends his days managing and maintaining the extensive helium recovery system at the company Colorado campus. (���Ͽ� has a smaller system at its laboratory space in Minnesota.)

�Our helium liquefaction system is a process plant that converts helium from a gas into a liquid. That liquid is then moved into the labs where it provides cooling to the quantum computing application. As it provides cooling, it becomes a gas again and then is transported into our recovery pipeline, which is installed throughout the facility, and the recovery piping leads to a big gasbag,� Miller explains.

his gasbag is a giant balloon that fills up with gaseous helium. And as that balloon fills up with helium, it is monitored by a level sensor that measures the size of the gas bag. Once the bag inflates to a certain volume, it turns on a high-pressure compressor. The high-pressure compressor then pulls helium from the gas bag and sends the helium over to high-pressure storage. The helium is stored in high-pressure cylinders which are 20 feet in length and two feet in diameter. It's stored as a high-pressure gas until it's ready to be liquefied again and sent back to the labs to continue the cooling and recycle process.� ��

This process enables the team to recover and reuse large amounts of helium.

�Helium is an absolutely 100% nonrenewable resource,� Miller emphasizes. �Once we pull helium out of the ground, it is so light that it will float up out of the atmosphere. It important we recover and reuse as much of it as possible.�

Cambridge Quantum (CQ), the global leader in quantum software, and a wholly owned subsidiary of ���Ͽ�, the world leading integrated quantum computing company, is pleased to announce the continuation of its expansion across Europe with the opening of its new office in Munich, Germany.

The creation and rapid expansion of the new company, CQ Deutschland (CQD), underlines ���Ͽ� commitment to the ambitious project of the German government in supporting and promoting quantum technologies and quantum computing. Cambridge Quantum already has a scientific team in Munich that complements its existing work in ab-initio Quantum Chemistry with a model-based perspective from Condensed Matter Physics. The goal of the Condensed Matter Group in Munich is to develop algorithms and software that will be the driver of strongly correlated systems research and the commercialization of quantum materials. Cambridge Quantum will continue to expand its collaboration with enterprise, government and academic partners in Germany on chemistry, optimization, finance, cybersecurity, and quantum machine learning and natural language processing in order to grow the industry's quantum computing ecosystem.

he next milestone in quantum computation is delivering useful applications for the rapidly improving quantum hardware. Achieving this requires a combined effort in the fields of quantum software, quantum algorithms, and quantum hardware,� said Dr. Henrik Dreyer, Cambridge Quantum Deutschland Scientific Lead, he German quantum computing ecosystem is exceptionally well positioned in these areas. We look forward to joining the community, in which our team of expert scientists can continue to develop applications for quantum computing in collaboration with industry, government and academic partners.�

This week, the System Model H1-2 doubled its performance to become the first commercial quantum computer to pass Quantum Volume 4096, a benchmark introduced by IBM in 2019 to measure the overall capability and performance of quantum computers.

It marks the sixth time in two years that ���Ͽ� H-Series hardware, Powered by Honeywell, has set an industry record for measured quantum volume.

The achievement also fulfills a March 2020 promise made by Honeywell Quantum Solutions, which combined with Cambridge Quantum in late 2021 to form ���Ͽ�, to increase the performance of its trapped ion technologies by an order of magnitude each year for the next five years.��

his is the second consecutive year we�ve delivered on that promise and our commitment to developing the highest performing quantum hardware available,� said Tony Uttley, president and chief operating officer at ���Ͽ�.

Continuous upgrades

This week marks the second time in four months that the System Model H1-2, which came online late last year, has achieved a quantum volume milestone. It set a record in December 2021 when it passed Quantum Volume 2048.

Uttley attributed the doubling of performance to the consistent upgrades that are made.��

���Ͽ� currently operates two commercial quantum computers, the H1-1 and H1-2, which run projects for customers and then are taken offline for upgrades.��

his approach provides the opportunity for us to continuously add new updates and features to our systems, which enables us to improve performance,� he said. �We learn a lot about our machines by running projects and can make small upgrades or tweaks that keep our fidelities high.���

The data

The average single-qubit gate fidelity for this milestone was 99.994(3)%, the average two-qubit gate fidelity was 99.81(3)% with fully-connected qubits, and measurement fidelity was 99.72(5)%.��The ���Ͽ� team ran 200 circuits with 100 shots each, using standard QV optimization techniques to yield an average of 152.97 two-qubit gates per circuit.

The System Model H1-2 successfully passed the quantum volume 4096 benchmark, outputting heavy outcomes 69.04% of the time, which is above the 2/3 threshold with greater than 99.99% confidence.��

The team used a , Dr. Charlie Baldwin and Dr. Karl Mayer, to calculate the confidence interval.��

The plot above shows the individual heavy output probability for each circuit in the Quantum Volume 4096 test. The blue line is the cumulative average heavy output probability and the green regions are the cumulative two-sigma confidence interval calculated by the new method. The heavy output probability crosses the 2/3 threshold with two-sigma confidence after 100 circuits.

The plot above shows the growth of measured quantum volume by ���Ͽ�. For each test, the heavy output probability �h� is listed and the system is identified by the marker type. The dashed grey line shows our target scaling of increasing QV × 10 yearly.��

What next?

Uttley said the next step is to increase the number of qubits on both ���Ͽ� machines and to continue to improve gate fidelities.

he System Model H1-2 used all 12 of its fully connected qubits to pass Quantum Volume 4096,� he said. �We have reached the limit of what we can do with 12 qubits.��To continue to improve performance, we need to add qubits. So keep watching what happens soon.�

���Ͽ�'s quantum chemistry team, in collaboration with TotalEnergies, has presented a detailing a potential use of quantum computers in mitigating climate change. The team has paved the way for the use of quantum computing to model materials, as a part of the materials discovery process, for use in carbon capture and sequestration.

In this work, the research team brought together the worlds of carbon capture and quantum computing. They developed a quantum computing methodology describing the binding of molecular carbon dioxide with a material being actively researched for carbon capture, called a Metal-Organic Framework, or MOF. This family of materials is of great scientific interest because they are capable of absorbing carbon dioxide with low energy requirements.

These synthetic materials are porous, which gives them their ability to bind to carbon dioxide molecules. MOFs can be compared to "molecular LEGO", as they can take many different configurations, which result in specific pore sizes and reactivity. They can in principle be used to design materials with specific properties.

Using classical computers to model these systems often yields imprecise solutions. Using a novel quantum method, the team opens a door to potentially overcoming some of the limitations of classical approaches. Due to the natural way in which many-body interactions can be treated, as well as the sheer size of the computational space, quantum computing is a natural future alternative for modeling such systems.

Today quantum computers (noisy, intermediate-scale quantum machines, or NISQ machines) are constrained by the number of qubits available for computation, and the tendency for calculations to be overwhelmed by errors. Modeling complex materials like MOFs is therefore challenging. The breakthrough represented by this paper is the use of fragmentation strategies to break down the computational task, providing a robust and versatile approach that combines quantum and classical computing methods.

The work revealed the way today quantum computers modeling complex many-body interactions can increase our understanding of MOF-CO2 systems. It potentially accelerates our ability to use quantum computers to solve challenges that could play an important role in tackling climate change.

�Ilyas Khan, CEO of ���Ͽ�, commented: "The publication of this paper in partnership with TotalEnergies, one of the world's leading developers of carbon capture and storage technologies, marks an important milestone in the much anticipated area of quantum chemistry. The mixed team of TotalEnergies and ���Ͽ� scientists has demonstrated a way to use today's quantum computers to conduct materials science research in a space that the Intergovernmental Panel on Climate Change says will play a vital role in stabilizing atmospheric greenhouse gas concentrations. This is the sort of work quantum computers have the potential to accelerate in the future."

By Amy Wolff For ���Ͽ�

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 ���Ͽ�, 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 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 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.�

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

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

����Ͽ� 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 award is for the design of the two-state rodeo algorithm,� said Dr. Lee. he 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 ���Ͽ� theory group regularly and is looking forward to implementing his algorithm soon on the company 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. he 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 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.�

���Ͽ� 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 �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.��

his is a major step forward for the ���Ͽ� team and our high-performing trapped-ion quantum hardware,� said Tony Uttley, ���Ͽ� president and chief operating officer.�� he 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 ���Ͽ� 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 ���Ͽ� 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 next

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

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