Research co-authored by Mohamed Hibat Allah, assistant professor of applied mathematics, has received widespread media coverage, being featured on Phys.org, in Quantum Insider, and by IBM. The paper, “Variational benchmarks for quantum many-body problems,” was published in Science in October 2024.
The paper – the result of a collaboration by thirty researchers from around the world – proposes the “v-score” as a new metric to consistently compare different computational methods in the field of quantum many-body physics simulation. “The v-score can also allow scientists to identify the hardness of studying a specific quantum system,” Hibat Allah explains. “Additionally, this work with the v-score offers a solid benchmark for the future generation of quantum computers to compete with state-of-the-art computational methods based on classical computers.”
The collaboration builds on Hibat Allah’s existing research into the intersection of language modeling and many-body physics. “In particular,” he says, “my goal is to explore the frontiers of quantum systems simulation using language models (such as architecture used in ChatGPT). Exploring the power of these language models in the field of many-body physics could ignite breakthroughs in quantum systems simulation and quantum matter similar to the GenAI breakthroughs we experience nowadays in natural language processing.”
Hibat Allah is particularly grateful to his former PhD supervisor Juan Carrasquilla, for inviting him to collaborate on the project. “I would also like to thank Dian Wu, Giuseppe Carleo, and my other co-authors for the very nice collaboration,” he says. “Finally, I would like to acknowledge the invaluable support of the University of Waterloo, the Perimeter Institute, and the Vector Institute.”