IEEE Quantum Week 2022

Advancing Science and the Industry

September 19, 2022

The IEEE International Conference on Quantum Computing and Engineering – or IEEE Quantum Week -- begins this week, serendipitously located in Broomfield, Colorado this year, home to Quantinuum’s U.S. corporate headquarters.

At the conference, Quantinuum’s leadership in bridging the gap between the science of quantum computing and the development of a commercial industry will be on full display.

Quantinuum President and COO Tony Uttley will deliver a much-anticipated keynote address at IEEE Quantum Week titled, “A Measured Approach to Quantum Computing” on Thursday.  An additional 17 company engineers, physicists and other scientists will participate in four panels, three workshops and a mentorship session as well as deliver a tutorial and technical paper presentation at the conference this week.

Quantinuum team members will be participating in a variety of sessions vital to the growth of the quantum ecosystem, from educating students about the field and mapping out careers in the industry to explaining the science behind trapped ion quantum computers and describing the architectures of logical qubits. 

An important discussion about the UCSB NSF Quantum Foundry and its mission to develop materials and interfaces to power quantum-based electronics will be led by Dr. Bob Horning, Senior Technical Manager for Wafer Fabrication at Quantinuum. 

In addition to hosting sessions and speaking at the event, Quantinuum researchers will present the following posters during the conference:

  • Mitigating qubit leakage errors in quantum circuits with gadgets and post-selection  
  • High fidelity state preparation and measurement of ion qubits with spin I > ½
  • The Impact of the Sun on Trapped-Ion Quantum Computers

Quantinuum looks forward to connecting with the diverse community of quantum researchers, learners, and industry experts at IEEE Quantum Week who are all helping to pave the way forward in the field.

Please see the complete list of sessions featuring Quantinuum team members below.

Keynote: President and COO Tony Uttley, “A measured approach to quantum computing,” Thursday, Sept. 22, 5:30 pm.

Workshop: Principal Scientist Curtis Volin, “Careers in quantum computing: How to get started with quantum computing—A workshop for high schoolers,” Sunday, Sept. 18, 10:00 am. 

Technical paper: Jacob Johansen, Atomic, Molecular, and Optical Physicist; Brian Estey, Physicist; Mary Rowe, Research Scientist; and Anthony Ransford, Research Scientist, “Quantum hardware-1—Fast loading of a trapped ion quantum computer using a 2D magneto-optical trap,” Monday, Sept. 18, 1:00 pm. 

Mentorship program: R&D Manager Brian Mathewson, “Student mentorship breakfast,” Monday, Sept. 19, 9:30 am.

Workshop: Advanced Software Engineer Peter Campora, “Azure Quantum: A Platform for Quantum Computing Research, Education and Innovation,” Tuesday, Sept. 10:00 am. 

Workshop: Senior Director of Technology Development Steve Sanders, “Classical control systems for quantum computing,” Tuesday, Sept. 20, 10:00 am.

Panel: Senior Technical Manager for Wafer Fabrication Dr. Bob Horning, “The Quantum Foundry,” Sept. 20, 3:15 pm.

Panel: Senior Advanced Physicist Ciaran Ryan-Anderson, “Architectures for logical qubits,” Wednesday, Sept. 21, 10:00 am.

Tutorial: Daniel Mills, Research Scientist, and Cristina Cirstoiu, Research Scientist, “Developing and Executing Error-mitigated NISQ Algorithms across Devices and Simulators,” Thursday, Sept. 22, 10:00 am.

Workshop: Natalie Brown, Advanced Physicist, and Ciaran Ryan-Anderson, Senior Advanced Physicist, “Real-time decoding for fault-tolerant quantum computing,” Thursday, Sept. 22, 10:00 a.m.

Panel: Caroline Figgatt, Senior Atomic, Molecular and Optical Physicist; Liz Argueta, Software Engineer; and Tammie Borders, Senior Business Development Manager, “Being your authentic self: Promoting DEI in quantum computing,” Thursday, Sept. 22, 3:15 pm.

*All sessions are listed in Colorado time, Mountain Time Zone, or UTC-6

About Quantinuum

Quantinuum, the world’s largest integrated quantum company, pioneers powerful quantum computers and advanced software solutions. Quantinuum’s technology drives breakthroughs in materials discovery, cybersecurity, and next-gen quantum AI. With over 500 employees, including 370+ scientists and engineers, Quantinuum leads the quantum computing revolution across continents. 

Blog
May 12, 2025
Quantinuum Dominates the Quantum Landscape: New World-Record in Quantum Volume

Back in 2020, we made a promise to increase our Quantum Volume (QV), a measure of computational power, by 10x per year. 

Today, we’re pleased to share that we’ve followed through on our commitment: Our System Model H2 has reached a Quantum Volume of 2²³ = 8,388,608, proving not just that we always do what we say, but that our quantum computers are leading the world forward. 

The QV benchmark was developed by IBM to represent a machine’s performance, accounting for things like qubit count, coherence times, qubit connectivity, and error rates. In IBM's words

“the higher the Quantum Volume, the higher the potential for exploring solutions to real world problems across industry, government, and research."

Our announcement today is precisely what sets us apart from the competition. No one else has been bold enough to make a similar promise on such a challenging metric – and no one else has ever completed a five-year goal like this.

We chose QV because we believe it’s a great metric. For starters, it’s not gameable, like other metrics in the ecosystem. Also, it brings together all the relevant metrics in the NISQ era for moving towards fault tolerance, such as gate fidelity and connectivity. 

Our path to achieve a QV of over 8 million was led in part by Dr. Charlie Baldwin, who studied under the legendary Ivan H. Deutsch. Dr. Baldwin has made his name as a globally renowned expert in quantum hardware performance over the past decade, and it is because of his leadership that we don’t just claim to be the best, but that we can prove we are the best. 

Figure 1: All known published Quantum Volume measurements.
Sources: [1][2][3][4][5]

Alongside the world’s biggest quantum volume, we have the industry’s most benchmarked quantum computers. To that point, the table below breaks down the leading commercial specs for each quantum computing architecture. 

Table 1: Leading commercial spec for each listed architecture or demonstrated capabilities on commercial hardware.
Download Benchmarking Results

We’ve never shied away from benchmarking our machines, because we know the results will be impressive. It is our provably world-leading performance that has enabled us to demonstrate:

As we look ahead to our next generation system, Helios, Quantinuum’s Senior Director of Engineering, Dr. Brian Neyenhuis, reflects: “We finished our five-year commitment to Quantum Volume ahead of schedule, showing that we can do more than just maintain performance while increasing system size. We can improve performance while scaling.” 

Helios’ performance will exceed that of our previous machines, meaning that Quantinuum will continue to lead in performance while following through on our promises. 

As the undisputed industry leader, we’re racing against no one other than ourselves to deliver higher performance and to better serve our customers.

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Blog
May 1, 2025
GenQAI: A New Era at the Quantum-AI Frontier

At the heart of quantum computing’s promise lies the ability to solve problems that are fundamentally out of reach for classical computers. One of the most powerful ways to unlock that promise is through a novel approach we call Generative Quantum AI, or GenQAI. A key element of this approach is the Generative Quantum Eigensolver (GQE).

GenQAI is based on a simple but powerful idea: combine the unique capabilities of quantum hardware with the flexibility and intelligence of AI. By using quantum systems to generate data, and then using AI to learn from and guide the generation of more data, we can create a powerful feedback loop that enables breakthroughs in diverse fields.

Unlike classical systems, our quantum processing unit (QPU) produces data that is extremely difficult, if not impossible, to generate classically. That gives us a unique edge: we’re not just feeding an AI more text from the internet; we’re giving it new and valuable data that can’t be obtained anywhere else.

The Search for Ground State Energy

One of the most compelling challenges in quantum chemistry and materials science is computing the properties of a molecule’s ground state. For any given molecule or material, the ground state is its lowest energy configuration. Understanding this state is essential for understanding molecular behavior and designing new drugs or materials.

The problem is that accurately computing this state for anything but the simplest systems is incredibly complicated. You cannot even do it by brute force—testing every possible state and measuring its energy—because  the number of quantum states grows as a double-exponential, making this an ineffective solution. This illustrates the need for an intelligent way to search for the ground state energy and other molecular properties.

That’s where GQE comes in. GQE is a methodology that uses data from our quantum computers to train a transformer. The transformer then proposes promising trial quantum circuits; ones likely to prepare states with low energy. You can think of it as an AI-guided search engine for ground states. The novelty is in how our transformer is trained from scratch using data generated on our hardware.

Here's how it works:

  • We start with a batch of trial quantum circuits, which are run on our QPU.
  • Each circuit prepares a quantum state, and we measure the energy of that state with respect to the Hamiltonian for each one.
  • Those measurements are then fed back into a transformer model (the same architecture behind models like GPT-2) to improve its outputs.
  • The transformer generates a new distribution of circuits, biased toward ones that are more likely to find lower energy states.
  • We sample a new batch from the distribution, run them on the QPU, and repeat.
  • The system learns over time, narrowing in on the true ground state.

To test our system, we tackled a benchmark problem: finding the ground state energy of the hydrogen molecule (H₂). This is a problem with a known solution, which allows us to verify that our setup works as intended. As a result, our GQE system successfully found the ground state to within chemical accuracy.

To our knowledge, we’re the first to solve this problem using a combination of a QPU and a transformer, marking the beginning of a new era in computational chemistry.

The Future of Quantum Chemistry

The idea of using a generative model guided by quantum measurements can be extended to a whole class of problems—from combinatorial optimization to materials discovery, and potentially, even drug design.

By combining the power of quantum computing and AI we can unlock their unified full power. Our quantum processors can generate rich data that was previously unobtainable. Then, an AI can learn from that data. Together, they can tackle problems neither could solve alone.

This is just the beginning. We’re already looking at applying GQE to more complex molecules—ones that can’t currently be solved with existing methods, and we’re exploring how this methodology could be extended to real-world use cases. This opens many new doors in chemistry, and we are excited to see what comes next.

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Blog
April 11, 2025
Quantinuum’s partnership with RIKEN bears fruit

Last year, we joined forces with RIKEN, Japan's largest comprehensive research institution, to install our hardware at RIKEN’s campus in Wako, Saitama. This deployment is part of RIKEN’s project to build a quantum-HPC hybrid platform consisting of high-performance computing systems, such as the supercomputer Fugaku and Quantinuum Systems.  

Today, a paper published in Physical Review Research marks the first of many breakthroughs coming from this international supercomputing partnership. The team from RIKEN and Quantinuum joined up with researchers from Keio University to show that quantum information can be delocalized (scrambled) using a quantum circuit modeled after periodically driven systems.  

"Scrambling" of quantum information happens in many quantum systems, from those found in complex materials to black holes.  Understanding information scrambling will help researchers better understand things like thermalization and chaos, both of which have wide reaching implications.

To visualize scrambling, imagine a set of particles (say bits in a memory), where one particle holds specific information that you want to know. As time marches on, the quantum information will spread out across the other bits, making it harder and harder to recover the original information from local (few-bit) measurements.

While many classical techniques exist for studying complex scrambling dynamics, quantum computing has been known as a promising tool for these types of studies, due to its inherently quantum nature and ease with implementing quantum elements like entanglement. The joint team proved that to be true with their latest result, which shows that not only can scrambling states be generated on a quantum computer, but that they behave as expected and are ripe for further study.

Thanks to this new understanding, we now know that the preparation, verification, and application of a scrambling state, a key quantum information state, can be consistently realized using currently available quantum computers. Read the paper here, and read more about our partnership with RIKEN here.  

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