D-Wave Quantum Inc., a leader in quantum computing systems, software, and services—and the only provider building both annealing and gate-model quantum computers—today published a peer-reviewed milestone paper showing the performance of its 5,000 qubit Advantage™ quantum computer is significantly faster than classical compute on 3D spin glass optimization problems, an intractable class of optimization problems. This paper also represents the largest programmable quantum simulation reported to date.
The paper—a collaboration between scientists from D-Wave and Boston University—entitled “Quantum critical dynamics in a 5,000-qubit programmable spin glass,” was published in the peer-reviewed journal Nature today. Building upon research conducted on up to 2,000 qubits last September, the study shows that the D-Wave quantum processor can compute coherent quantum dynamics in large-scale optimization problems. This work was done using D-Wave’s commercial-grade annealing-based quantum computer, which is accessible for customers to use today.
With immediate implications to optimization, the findings show that coherent quantum annealing can improve solution quality faster than classical algorithms. The observed speedup matches the theory of coherent quantum annealing and shows a direct connection between coherence and the core computational power of quantum annealing.
“This research marks a significant achievement for quantum technology, as it demonstrates a computational advantage over classical approaches for an intractable class of optimization problems,” said Dr. Alan Baratz, CEO of D-Wave. “For those seeking evidence of quantum annealing’s unrivaled performance, this work offers definitive proof.
This work supports D-Wave’s ongoing commitment to relentless scientific innovation and product delivery, as the company continues development on its future annealing and gate model quantum computers. To date, D-Wave has brought to market five generations of quantum computers and launched an experimental prototype of its sixth-generation machine, the Advantage2™ system, in June 2022. The full Advantage2 system is expected to feature 7,000+ qubits, 20-way connectivity, and higher coherence to solve even larger and more complex problems.
Paper’s Authors and Leading Industry Voices Echo Support
“This is an important advance in the study of quantum phase transitions on quantum annealers. It heralds a revolution in experimental many-body physics and bodes well for practical applications of quantum computing,” said Wojciech Zurek, theoretical physicist at Los Alamos National Laboratory and leading authority on quantum theory. Dr. Zurek is widely renowned for his groundbreaking contribution to our understanding of the early universe as well as condensed matter systems through the discovery of the celebrated Kibble-Zurek mechanism. This mechanism underpins the physics behind the experiment reported in this paper. “The same hardware that has already provided useful experimental proving ground for quantum critical dynamics can be also employed to seek low-energy states that assist in finding solutions to optimization problems.”
"Disordered magnets, such as spin glasses, have long functioned as model systems for testing solvers of complex optimization problems,” said Gabriel Aeppli, professor of physics at ETH Zürich and EPF Lausanne, and head of the Photon Science Division of the Paul Scherrer Institut. Professor Aeppli coauthored the first experimental paper demonstrating advantage of quantum annealing over thermal annealing in reaching ground state of disordered magnets. “This paper gives evidence that the quantum dynamics of a dedicated hardware platform are faster than for known classical algorithms to find the preferred, lowest energy state of a spin glass, and so promises to continue to fuel the further development of quantum annealers for dealing with practical problems."
“As a physicist who has built my career on computer simulations of quantum systems, it has been amazing to experience first-hand the transformative capabilities of quantum annealing devices,” said Anders Sandvik, professor of physics at Boston University and a coauthor of the paper. “This paper already demonstrates complex quantum dynamics on a scale beyond any classical simulation method, and I'm very excited about the expected enhanced performance of future devices. I believe we are now entering an era when quantum annealing becomes an essential tool for research on complex systems."
"This work marks a major step towards large-scale quantum simulations of complex materials,” said Hidetoshi Nishimori, professor at the Institute of Innovative Research, Tokyo Institute of Technology, and one of the original inventors of quantum annealing. “We can now expect novel physical phenomena to be revealed by quantum simulations using quantum annealing, ultimately leading to the design of materials of significant societal value.”
“This represents some of the most important experimental work ever performed in quantum optimization,” said Dr. Andrew King, director of performance research at D-Wave. “We’ve demonstrated a speedup over simulated annealing, in strong agreement with theory, providing high-quality solutions for large-scale problems. This work shows clear evidence of quantum dynamics in optimization, which we believe paves the way for even more complex problem-solving using quantum annealing in the future. The work exhibits a programmable realization of lab experiments that originally motivated quantum annealing 25 years ago.”
"Not only is this the largest demonstration of quantum simulation to date, but it also provides the first experimental evidence, backed by theory, that coherent quantum dynamics can accelerate the attainment of better solutions in quantum annealing,” said Mohammad Amin, fellow, quantum algorithms and systems at D-Wave. “The observed speedup can be attributed to complex critical dynamics during quantum phase transition, which cannot be replicated by classical annealing algorithms, and the agreement between theory and experiment is remarkable. We believe these findings have significant implications for quantum optimization, with practical applications in addressing real-world problems."