We had an enlightening conversation about quantum computing with Silvia Zorzetti, senior engineer at the Fermi National Accelerator Laboratory.
She is deputy head of the co-design department at the National Quantum Information Science Research Center: Superconducting Quantum Materials and Systems Division.
The SQMS, led by Fermilab, collaborates with national laboratories, academia, and industry to make groundbreaking quantum computing and sensing progress. Her journey into quantum computing began with the goal of creating quantum systems that are as efficient and noise-free as possible.
Silvia Zorzetti’s significant contributions are further recognized with the DOE Early Career Research Award 2023.
What is your vision for the future of quantum computing, and what are your main goals in your role at the SQMS Center?
Quantum computing is a disruptive technology. About 40 years ago, there was an idea to use quantum mechanics for computing. The goal is to use properties like superposition and entanglement to gain an advantage in computing. In quantum mechanics, there’s the uncertainty principle, which says you can’t know a particle’s position and speed with infinite precision.
You have to give up some certainty about one to know the other.
Heisenberg’s uncertainty principle is counterintuitive but applies to tiny particles like electrons.
So, when we say we don’t know when a particle is, it can simultaneously be in multiple states. It’s like tossing a coin – while in the air, it can be both heads and tails. But when it lands, it’s in one state. This creates a challenge in quantum computing. After 40 years, Feynman suggested using quantum computers to simulate complex things in nature that might take classical computers years or even a century. Quantum computers leverage superposition, making them much faster.
We’re in a quantum computing industrial revolution, with industries working on it and quantum computers available to the public. The issue is these quantum computers are noisy, and efforts are ongoing to make computations more robust to noise.
The goal for the next decade is to make quantum computers less sensitive to noise and scalable, fitting many logical units on a single chip.
As for my role at Fermilab, we work on both devices and algorithms.
Quantum computing is an evolving field with unique challenges. Can you discuss some of the main challenges you’ve faced in your work, and how you’ve addressed them?
Quantum computing is rapidly advancing. Researchers are tackling numerous issues daily, aiming for more efficient solutions. One major challenge is the frustration of turning ideas into working solutions, especially at very low energies where everything, even sunlight, introduces noise.
To overcome these challenges in quantum computing, we focus on materials, drawing inspiration from particle accelerators. We work on understanding and addressing sources of losses and errors, like removing oxide layers that naturally form during device creation. Interfaces between different devices and even small components like screws contribute to noise, so we work on solving these daily problems.
Quantum computing has the potential to revolutionize various industries. Which industries do you believe will be most significantly impacted by quantum computing in the near future, and what transformative changes can we expect?
When we discuss the benefits of quantum computing, we’re mainly talking about its computing capabilities. This is crucial for solving complex problems that require many inputs, especially those classical computers struggle with or can’t handle efficiently in a short time. Quantum computers excel in such scenarios. A prominent area benefiting from this is drug research, involving applications in chemistry and drug discovery, particularly in synthesizing complex proteins more efficiently. Another exciting application we’re working on is quantum computing, enhancing magnetic resonance MRI signals. MRIs involve intricate computations, and we aim to leverage quantum computers to increase resolution, detecting anomalies at earlier stages.
However, the full impact of quantum computing may take longer because we’ll need millions of qubits for logical units to perform these computations. On the other hand, in the short term, we can expect advancements in quantum sensors and networks. Quantum sensors, sensitive to tiny radiations, can operate in various conditions. They could detect soil vibrations and have applications like monitoring nuclear reactors, natural gas pipelines, magnetometers, Yukes, flux qubits for GPS, and secure communication for national security.
Quantum computing is often seen as an emerging technology. How far along are we in democratizing this innovation and making it accessible to a broader audience? What steps are necessary to scale quantum computing effectively?
So it’s emerging technology, but it’s also kind of well-established. There are a few technologies that we are working on right now. For example, this superconducting technology traps ions that do exist, and we know the potential, and we also know the challenges of them. And so we are working to make it more effective and more efficient. The main challenges, as I said, are the noise and the scalability, but industries, including our work in basic science, are developing a roadmap to overcome these challenges. In the next decades, we anticipate seeing significant quantum advantages.
One thing that I can add there is how to make it accessible to the broader audience. While these computers require specialized facilities, companies, including ours, are placing devices on the cloud. This enables anyone using specific programming languages to access and encode quantum states into the cloud-based quantum device located elsewhere. Some companies also provide programming languages to simulate quantum computers, making them accessible for educational and training purposes, even if the physical device isn’t directly available.
What sets Fermilab’s quantum computing apart from the quantum computing technologies developed by industry leaders like IBM and Google?
The role of national laboratories is different. While we address similar problems as industries, our focus is unique. We don’t concentrate on scaling up or mass production but rather on solving specific challenges. At the end of a project, we might have a few highly performing devices, aiming to transfer the technology to industries for scaling up and commercialization.
Regarding our technology, Fermilab specializes in high-energy physics and houses a particle accelerator, supported by the Department of Energy. We use superconducting cavities, initially developed for accelerators worldwide, for quantum computing. This differs from the industry’s focus on 2D devices; our 3D technology, proven successful in accelerators, offers advantages. We’ve demonstrated its longevity against irradiation, addressing a key quantum computing challenge: noise. This sets us apart, utilizing superconducting 3D technology developed over the years for particle accelerators.
How is quantum computing reshaping the landscape of artificial intelligence and machine learning? Will Quantum AI become a reality?
Quantum AI exists, and again, maybe right now, it exists mostly from a theory point of view. There are algorithms that do this quantum machine learning and artificial intelligence programs in general. In the landscape of artificial intelligence, we know that artificial intelligence is another of these problems. That is what you want to do with AI. You receive a lot of input, and then the machine learns from it and gives results. If you have a quantum computer, then that means that you can scale up your ability to process this information also for artificial intelligence and machine learning.
In the era of quantum computing, how are ethical and regulatory considerations evolving in the tech world?
So this is something I had to think about. Of course, we are a national lab, and our main focus is to offer equal opportunities for all.
We offer a lot of educational workforce development opportunities that are accessible to a variety of students with very different backgrounds.
If we talk about some sort of ethical and regulatory considerations, I think it has to be sought in particular for the quantum communication part, in which we want to establish a very secure channel, quantum channel and transfer the information far away in a very secure way.
So this is, of course, something that requires policy and also requires exact protocols to be deployed. But one thing I want to say is that our main mission is to work on technology and make it efficient and also free for the public. But one thing that I want to say is that the technology does what the men tell the technology to do; it is not an independent, free-thinking entity.
Coming to space exploration, many claim that quantum computing will be crucial for communications. Is this true? What other applications could quantum computing have in the space economy?
Okay, yes. The answer is yes, it is true. If we aim to establish a highly secure channel, like the classic example of Alice and Bob transmitting information, we use quantum key distribution. This method ensures that only Alice and Bob, who know how to encrypt and decrypt the information, can create a secure channel. If a third person tries to interfere, their attempt triggers a readout operation. As mentioned earlier, when a readout is attempted on quantum information, it immediately collapses, and the information is generally destroyed if the key is unknown. If a malicious party tries to enter the channel, Alice and Bob will detect it because the information is destroyed, and the intruder, like Charlie, can’t do anything without the key. This Alice, Bob, and Charlie example illustrates why this communication channel is highly secure.
Transitioning to space, projects are working on sending quantum information into space, possibly using drones initially and later satellites. These projects represent some of the most promising applications in the space economy.
Could you share your advice for individuals interested in pursuing a career in quantum computing? What skills and knowledge do you believe are essential for success in this field?
Quantum computing and sensing is one of these fields in which you need to know a little bit of everything in order to enter it. So, most of us have a background in physics but also know about engineering. And then, in our case, you have to deal with the cryogenics, and then you have to deal with very technical details like putting together two devices that are made with different materials, and then you want to know about the algorithm part and the computing part. So, of course, you cannot be specialized in all of these aspects. But what happened is that usually you have an understanding of several of these aspects, and then you specialize in one specific field. So for us, in fact, it’s one of the main challenges to hire, for example, postdocs or graduate students who have the ambition and also have the knowledge of that, but it’s also one of the main challenges for engineers and technicians.
When they come to work with us, then they are in this world in which they also have to learn some parts of quantum mechanics that perhaps are very new to them.
So my advice for people would be, of course, you need to specialize in physics, engineering or one aspect of the quantum world, but I would say be curious and read technical notes and papers.