Spreading the Word About Quantum Computing
Senior Quantum Evangelist
Mark Jackson is a man on a mission. As Quantinuum’s senior quantum evangelist, Mark’s job is to create awareness and understanding about quantum computing and its world-changing potential. Based in New York, Mark holds a Ph.D. in theoretical physics from Columbia University with a background in mathematical modeling and computational physics. In 2017 he joined Cambridge Quantum, which combined with Honeywell Quantum Solutions to form Quantinuum in 2021. He has an academic background and remains an adjunct faculty member at Singularity University. He sat down earlier this month to talk about his unique job and the future of quantum computing.
Senior Quantum Evangelist is such a unique title. What does your job entail?
A lot of my job is speaking at conferences, doing interviews, participating in podcasts, and posting on social media. I focus on creating awareness and excitement for quantum computing, letting people know what we do at Quantinuum, and educating them about the ways this amazing technology will help solve complex problems and improve people’s lives.
Most people just don’t know much about quantum computing, or they have misunderstandings or reservations about the technology and its potential impact on society.
Half the people don’t believe quantum computers really exist yet. They think it’s some sort of science fiction idea that we’ve cooked up and, if it happens at all, it’ll be 20 years from now. They just can’t believe we have these computers today. The other half think quantum computers are just really fast computers. They believe we can take all our existing software and run it on a quantum computer, and it will be a million times faster. Neither is true, and it’s my job to educate people about what quantum computers can actually do to make the world better.
Over the past few years my role at Quantinuum has evolved a bit, and about a year ago they changed my title to “evangelist.” Technically, I’m now the “senior evangelist” because we recently added several other people to the team, which will help us do an even better job of spreading the word.
How will the use of quantum computers benefit society?
We anticipate we’re only 3–5 years away from being able to do things on a quantum computer that are truly valuable to society. That time will pass very quickly, which is why we’re encouraging companies to work with us right now to develop projects so that in a few years, when technology catches up, they’ll be in a good position to take advantage of opportunities.
The two nearest-term commercial applications for quantum computers are in chemistry and optimization, such as supply chain and logistics.
In chemistry, we have known the equations for 100 years. If you give me a molecule, I know exactly what the molecule is made of — I know how many electrons, protons and neutrons are in it, and I know the equations governing all their interactions. But, solving those equations and actually figuring out the behavior of the molecule is very difficult because, as a molecule gets bigger, there are so many interactions that tracking them quickly overwhelms a conventional computer. Quantum computers are expected to one day solve these chemical equations easier and faster.
For example, pharmaceutical companies could use this technology to design medicine. Right now, there is a lot of guesswork in developing a drug. Scientists can do a little preliminary work on a computer, but then they must synthesize a lot of trial drugs followed by testing on humans.
Developing drugs this way is expensive, time consuming, and risky. In general, it takes about 10 years and $1 billion dollars to bring a drug to market. It would be ideal if scientists could do more work on a computer up front, which will save time and money and be less risky for patients.
Additionally, quantum computing will be invaluable for the machine-learning industry. Artificial intelligence is used everywhere. Your Netflix recommendations use AI machine-learning, and while this may not be lifechanging, advanced autopilot technology on an airplane or in a driverless car will be. Quantum computers one day could have the power, speed, and capacity to take machine-learning to a whole new level.
How did you end up working for Quantinuum?
I started hearing about quantum computing in 2017 and thought it sounded amazing. This field of study didn’t even exist when I was a student.
My background is in theoretical physics. For 15 years I worked in string theory and cosmology. Several years ago, I decided to leave academia and pursue other interests. I was very fortunate to be introduced to Ilyas Khan, founder of Cambridge Quantum and now CEO of Quantinuum, and he asked me to join the team about five years ago.
I was the first American hire at Cambridge Quantum, which was then a small start-up company with only about 30 people. The organization was comprised of all scientists until I joined. I was the first person to be hired whose main objective was business development.
Why is your job as an evangelist important to Quantinuum?
We can have the most amazing technology in the world, but if no one knows about it, then it doesn’t do anyone much good. There is a lot of misunderstanding and unfamiliarity that surrounds this industry currently, which is why my job of creating awareness is so important.
I get to talk to university students and researchers and let them know we have software they can use for free to help them code better. I am very lucky to have an academic background in physics because when I speak at these universities, the professors sometimes let me take over the class for a day. I don’t think they would grant the same access to a salesperson. I love to talk about the cool things we have done and are doing with these students and share ways we can partner and collaborate both now and in the future.
We want to build our hiring pipeline with the smartest and most creative young minds available. Hiring is a top priority, and job candidates may not know there are such amazing job opportunities at Quantinuum and throughout this exciting industry.
How has the industry changed in the last five years?
When I started, there were 8–10 credible quantum computing startups, including us. We were all pretty small with just a few dozen employees at the time.
Now, it seems like there’s a new company forming, a new investment, or a technical breakthrough in hardware or software every week. There are quantum information sciences degrees and programs in college now including quantum computing and closely related sciences. It’s dizzying to keep up with everything.
Today, there are roughly 400 quantum companies, building quantum products all over the world. Companies are also increasing in size. Our company currently has 400 employees, but we’re hiring like crazy and anticipate adding 200 people in 2022.
The U.S. government also is investing. During the last administration, they had a Quantum Initiative Act (QIA) where $1.2 billion was allocated for quantum funding. Other countries also are investing. China, for example, has spent at least $30 billion in quantum technology over the last few years.
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.
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.
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.
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:
- Quantum Supremacy via Random Circuit Sampling
- Quantum Magnetism at the Frontier of Classical Simulations
- Encoded Memory that Outperforms All Previous Implementations
- Quantum Supremacy for Certified Randomness
- High Fidelity Teleportation of Logical Qubits
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.
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.
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.