Particle Physics Powers Quantum Computing’s Future at Fermilab
In the race for advancing technology, time, funding, and attention are often dedicated to immediately monetizable applications. While industry roadmaps certainly drive technological advancement, basic science, which forwards our fundamental understanding of the universe, can create breakthrough findings with wide-reaching applications and effects.
My recent conversation with Silvia Zorzetti from Fermilab and Solidigm’s Jeniece Wnorowski revealed how such research into the convergence of high-energy physics and quantum technology is creating outstanding developments for quantum computing.
From Colliders to Qubits
As a U.S. particle accelerator laboratory, Fermilab has spent decades perfecting superconducting cavities that accelerate particle beams to near light speed. Through years of study, researchers at the lab have identified several sources of noise that can make these superconducting cavities less efficient, and they have worked to eliminate those sources of loss.
In 2017, researchers began studying these same cavities at the quantum level. As Silvia explained, at this single photon level, the energy is much lower, which means there are new potential sources of loss compared to the higher energy levels. “We can focus on the basic science and the basic understanding of those mechanisms,” Silvia explained.
At the same time, Fermilab is finding ways to transform superconducting cavities to be efficient for quantum computing. By placing qubits inside the cavities, Fermilab has achieved 20 milliseconds of coherence. That coherence time represents a critical advance in the typical rapid decay time of quantum information. “And we know that it is possible to achieve more coherence,” Silvia said.
Quantum Computing’s Sweet Spot
Quantum computers won’t replace classical computers for all tasks. The technology excels at specific problems, including the Shor algorithm for prime number factorization and Grover’s algorithm, a quantum algorithm for unstructured search. As the threats to digital security grow, the Shor algorithm is of extreme interest because of its efficient ability to factorize prime numbers, a process that is very important for cryptography. “This means that we can have systems that are very secure because they cannot be broken by someone else with a more advanced cryptography system, let’s say an alien, because here on Earth, we all have to comply with the quantum mechanics rule,” she explained.
Beyond these practical applications, quantum computing excels for quantum simulations for field theories, which involve many interacting components. “We have these huge many body problems in which there are so many entities. We know how to describe them if they are alone,” Silvia explained. “But then when they start to interact to each other, it becomes a very complex model. So, we know that quantum computing is very good for those kinds of applications.”
Roadmap Challenges
While quantum computing has seen great progress, challenges remain to realizing its full potential. Silvia identified two types of hurdles to be overcome: “engineering problems,” where technical challenges are understood and need to be addressed, and problems where more fundamental research is required.
“Those are mainly between the interconnects,” she said. “The interconnects are needed for scaling quantum computing…and in particular, interconnects with very low losses.” Quantum information is a weak signal, so research to find solutions that will prevent the loss of this information remains a priority.
Quantum error correction presents another major hurdle. Quantum states are inherently fragile, and errors can arise in quantum information due to decoherence and other issues. The community is developing algorithmic techniques that make computations more robust to noise, while simultaneously working on hardware improvements.
The Promise of Quantum Sensing
The environmental sensitivity that creates problems for quantum computing is actually an advantage for quantum sensing, which is already delivering results. Fermilab is leveraging this sensitivity to detect dark matter, dark photons, and axions. It is also studying radiation, like the gamma ray, to understand better how these affect quantum computers, and how quantum computers could be built that are robust to radiation.
The TechArena Take
Fermilab’s approach to quantum computing demonstrates how domain expertise from one field can catalyze breakthrough innovations in another. By leveraging decades of superconducting cavity development for particle accelerators, the laboratory has achieved amazing quantum coherence times. The pursuit of fundamental knowledge about how materials behave at the quantum level has yielded practical breakthroughs that are now accelerating the entire field forward.
For those interested in learning more, Fermilab hosts regular symposiums and outreach programs, including their Quantum 101 track designed for non-experts. Learn more about Fermilab’s quantum research at fnal.gov.
In the race for advancing technology, time, funding, and attention are often dedicated to immediately monetizable applications. While industry roadmaps certainly drive technological advancement, basic science, which forwards our fundamental understanding of the universe, can create breakthrough findings with wide-reaching applications and effects.
My recent conversation with Silvia Zorzetti from Fermilab and Solidigm’s Jeniece Wnorowski revealed how such research into the convergence of high-energy physics and quantum technology is creating outstanding developments for quantum computing.
From Colliders to Qubits
As a U.S. particle accelerator laboratory, Fermilab has spent decades perfecting superconducting cavities that accelerate particle beams to near light speed. Through years of study, researchers at the lab have identified several sources of noise that can make these superconducting cavities less efficient, and they have worked to eliminate those sources of loss.
In 2017, researchers began studying these same cavities at the quantum level. As Silvia explained, at this single photon level, the energy is much lower, which means there are new potential sources of loss compared to the higher energy levels. “We can focus on the basic science and the basic understanding of those mechanisms,” Silvia explained.
At the same time, Fermilab is finding ways to transform superconducting cavities to be efficient for quantum computing. By placing qubits inside the cavities, Fermilab has achieved 20 milliseconds of coherence. That coherence time represents a critical advance in the typical rapid decay time of quantum information. “And we know that it is possible to achieve more coherence,” Silvia said.
Quantum Computing’s Sweet Spot
Quantum computers won’t replace classical computers for all tasks. The technology excels at specific problems, including the Shor algorithm for prime number factorization and Grover’s algorithm, a quantum algorithm for unstructured search. As the threats to digital security grow, the Shor algorithm is of extreme interest because of its efficient ability to factorize prime numbers, a process that is very important for cryptography. “This means that we can have systems that are very secure because they cannot be broken by someone else with a more advanced cryptography system, let’s say an alien, because here on Earth, we all have to comply with the quantum mechanics rule,” she explained.
Beyond these practical applications, quantum computing excels for quantum simulations for field theories, which involve many interacting components. “We have these huge many body problems in which there are so many entities. We know how to describe them if they are alone,” Silvia explained. “But then when they start to interact to each other, it becomes a very complex model. So, we know that quantum computing is very good for those kinds of applications.”
Roadmap Challenges
While quantum computing has seen great progress, challenges remain to realizing its full potential. Silvia identified two types of hurdles to be overcome: “engineering problems,” where technical challenges are understood and need to be addressed, and problems where more fundamental research is required.
“Those are mainly between the interconnects,” she said. “The interconnects are needed for scaling quantum computing…and in particular, interconnects with very low losses.” Quantum information is a weak signal, so research to find solutions that will prevent the loss of this information remains a priority.
Quantum error correction presents another major hurdle. Quantum states are inherently fragile, and errors can arise in quantum information due to decoherence and other issues. The community is developing algorithmic techniques that make computations more robust to noise, while simultaneously working on hardware improvements.
The Promise of Quantum Sensing
The environmental sensitivity that creates problems for quantum computing is actually an advantage for quantum sensing, which is already delivering results. Fermilab is leveraging this sensitivity to detect dark matter, dark photons, and axions. It is also studying radiation, like the gamma ray, to understand better how these affect quantum computers, and how quantum computers could be built that are robust to radiation.
The TechArena Take
Fermilab’s approach to quantum computing demonstrates how domain expertise from one field can catalyze breakthrough innovations in another. By leveraging decades of superconducting cavity development for particle accelerators, the laboratory has achieved amazing quantum coherence times. The pursuit of fundamental knowledge about how materials behave at the quantum level has yielded practical breakthroughs that are now accelerating the entire field forward.
For those interested in learning more, Fermilab hosts regular symposiums and outreach programs, including their Quantum 101 track designed for non-experts. Learn more about Fermilab’s quantum research at fnal.gov.
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