An artist’s impression of a quantum electrodynamics simulation using 100 qubits of an IBM quantum computer. The spheres and lines denote the qubits and connectivity of the IBM quantum processor; gold spheres denote the qubits used in the simulation.
An artist’s impression of a quantum electrodynamics simulation using 100 qubits of an IBM quantum computer. The spheres and lines denote the qubits and connectivity of the IBM quantum processor; gold spheres denote the qubits used in the simulation.
For the first time, researchers have successfully prepared the quantum vacuum state of a fundamental physics model on up to 100 qubits of IBM’s advanced quantum computers, a milestone that brings scientists closer to simulating complex particle interactions that are beyond the reach of conventional supercomputers.
The achievement, detailed in a study published April 18 in PRX Quantum, demonstrates a novel approach for creating scalable quantum circuits that can effectively model aspects of the Standard Model of particle physics – the framework that describes the fundamental forces and particles in our universe.
“Our hope with this kind of research is to understand our own solar system, life, and ourselves in comparison to other exoplanetary systems, so we can contextualize our existence,” explains William Balmer, one of the researchers involved in applying similar quantum simulation techniques in other contexts. “We want to take pictures of other solar systems and see how they’re similar or different when compared to ours. From there, we can try to get a sense of how weird our solar system really is—or how normal.”
The team, led by researchers including Roland Farrell, Marc Illa, Anthony Ciavarella, and Martin Savage, developed what they call “scalable circuits ADAPT-VQE” (SC-ADAPT-VQE), a new algorithm that leverages the regular patterns and limited range of interactions in physical systems to efficiently prepare quantum states across many qubits.
Traditional approaches to quantum state preparation often hit roadblocks when scaled to larger systems, making them impractical for the kinds of simulations physicists dream of running. The new method skillfully navigates around these limitations.
At the heart of the research is the Schwinger model – a simplified version of quantum electrodynamics in one spatial dimension. While less complex than the full Standard Model, this system captures essential features like confinement, where particles with certain properties cannot exist in isolation – an important phenomenon in understanding how quarks combine to form particles like protons and neutrons.
What makes the team’s approach especially powerful is that they first determined the quantum circuits for small systems using classical computers, then demonstrated that these circuits could be systematically scaled up to handle much larger systems on actual quantum hardware.
“By using green-synthesised iron nanoparticles, we can not only improve the safety of composted pig manure, but also contribute to more sustainable farming practices,” said Gary Owens in an unrelated study, exemplifying how quantum computing is just one of many fields making significant technological advances this year.
The researchers successfully implemented their scalable circuits on IBM’s Eagle quantum processors, testing systems with up to 100 qubits – a scale at which quantum advantage over classical computing becomes increasingly relevant. The quality of the prepared quantum states was verified by measuring various physical properties that matched theoretical predictions with impressive accuracy.
To account for the inevitable errors that occur in today’s noisy quantum computers, the team developed a novel error mitigation technique called “operator decoherence renormalization.” This approach addresses the fact that different qubits in a large system experience different levels of noise, requiring more sophisticated compensation methods than previously used.
While this achievement marks a significant step forward, the researchers emphasize that there’s still work to be done before quantum computers can tackle the full complexity of the Standard Model or simulate high-energy particle collisions like those at the Large Hadron Collider.
However, the scalable circuit framework they’ve developed could potentially be applied to other systems with similar physical characteristics, including quantum chromodynamics (QCD) – the theory of the strong nuclear force that binds quarks and gluons into protons and neutrons.
The implications extend beyond fundamental physics. Similar techniques might help simulate complex materials, chemical reactions, or other quantum systems that defy classical computing approaches.
“We expect that future quantum simulations using these scalable circuits will surpass the abilities of classical computing,” the research team suggests in their press statement. “These simulations will provide insights into the mechanisms that govern the dynamics of fundamental particles and our universe.”
Such insights could potentially address long-standing questions in physics: Why is there more matter than antimatter in the universe? How do supernovae produce heavy elements? What are the properties of matter at the ultrahigh densities found in neutron stars?
As quantum computers continue to advance in both size and reliability, techniques like SC-ADAPT-VQE offer a promising pathway toward answering these fundamental questions through quantum simulation – potentially achieving the quantum advantage that researchers have been working toward for decades.
This research was supported by the U.S. Department of Energy’s Office of Science, the Office of Nuclear Physics, and the Quantum Science Center, among other institutions.
Categories Physics & Mathematics, Technology Tags particle interactions, quantum advantage, Quantum Computing, quantum simulations, quantum state preparation, scalable circuits, Schwinger model
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