Quantum computers possess the remarkable potential to revolutionize various fields, and one area that holds immense promise is the simulation of quantum chemistry. By utilizing the principles of quantum mechanics, quantum computers can model and understand complex molecular systems with incredible precision. However, due to the inherent fragility of quantum systems, it becomes crucial to implement fault-tolerant algorithms in quantum chemistry simulations. These algorithms ensure accurate and reliable computations while mitigating the adverse effects of errors and noise.
In a recent announcement, quantum computing company Quantinuum simulated a chemical molecule by using logical qubits to run a fault-tolerant algorithm on their quantum processor. The Quantinuum scientists, based in Japan, utilized three logical qubits on Quantinuum’s H1 quantum computer to calculate the hydrogen molecule’s ground state energy. To do this, the researchers used an algorithm called stochastic quantum phase estimation, which has already been run on early fault-tolerant devices.
“Today’s announcement turns a page for quantum chemistry on quantum computers, moving us towards the era of early fault tolerance,” stated Quantinuum CEO Dr. Raj Hazra in the press release. “This achievement is testament to the dedication of the hardware and software teams at Quantinuum, who consistently demonstrate their ability to achieve world-class results. It was made possible thanks to the H1 quantum computer which brings together high-fidelity gate operations, all-to-all connectivity and conditional logic, with the truly world-leading algorithms, methods and error handling techniques offered by our InQuanto chemistry platform.”
The Importance of Fault-Tolerance
Quantum systems are inherently sensitive to environmental noise and decoherence. Even the slightest disturbances can introduce errors that can propagate rapidly throughout the computation, rendering the results unreliable. Thus, the fragile nature of quantum systems necessitates developing and implementing fault-tolerant algorithms to ensure the accuracy and integrity of quantum chemistry simulations.
Fault-tolerant algorithms are specifically designed to mitigate the impact of errors and noise in quantum computations. These algorithms incorporate techniques to encode and manipulate quantum information redundantly, allowing error detection and correction. By employing sophisticated error-correcting codes, fault-tolerant algorithms can actively combat the detrimental effects of noise, enabling quantum systems to maintain their coherence and fidelity.
Moving Quantum Chemistry Toward Fault-Tolerance
In a preprint paper, “Demonstrating Bayesian Quantum Phase Estimation with Quantum Error Detection,” Quantinuum scientists, led by Dr. Kentaro Yamamoto, claim to have used logical qubits with a recently developed error correction code designed for Quantinuum’s H1 quantum computer to achieve error mitigation in their quantum chemistry computations. According to the press release: “The code saved quantum resources by immediately discarding a calculation if it detected qubits that had produced errors during the computation process.” Using this new code, the researchers produced more accurate quantum chemistry simulation results than without this code. “Simulating the hydrogen molecule and getting such good results with an early fault-tolerant algorithm on logical qubits is an excellent experimental result and reminds us how fast we continue to progress,” stated Yamamoto in the press release. “This result may reflect the start of a new chapter for quantum computing professionals, where we can begin to adopt early fault-tolerant algorithms on near-term devices, using all the techniques that will ultimately be required for future large-scale quantum computing.”
Kenna Hughes-Castleberry is a staff writer at Inside Quantum Technology and the Science Communicator at JILA (a partnership between the University of Colorado Boulder and NIST). Her writing beats include deep tech, quantum computing, and AI. Her work has been featured in Scientific American, Discover Magazine, Ars Technica, and more.