Quantum Many-Body & Numerics

A collaboration between Mr. Ting-Tung Wang, Mr. Menghan Song, and Professor Zi Yang Meng from the Department of Physics at The University of Hong Kong (HKU) together with their collaborators Liuke Lyu and William WITCZAK-KREMPA from the University of Montreal has recently developed a novel algorithm in quantum physics known as ‘entanglement microscopy’ that enables visualization and mapping of this extraordinary phenomenon at a microscopic scale. Their study was published in a recent issue of Nature Communications. Using the algorithm, one can uncover the hidden structures of quantum matter, revealing insights that could transform technology and deepen the understanding of the universe. Continue reading

In this interview with HKU science editor, Dr Pavel Toropov, Professor Meng explains why AI is now indispensable in quantum physics research ­– by allowing us to circumvent the need for enormous computational complexity, AI can help to make breakthroughs and in the process help us to understand better of mother nature and ourselves. This leads to discoveries of quantum materials whose properties, such as superconductivity and entanglement, can change the world. The technology may be cutting edge, but the principles involved, says Prof Meng, go back to ancient greek maxim - know thyself, and the whole thing is similar to playing mahjong. Click here for the interview.

In 2024, Artificial Intelligence (AI) achieved a remarkable milestone by winning the Nobel Prizes in both Physics and Chemistry. This unprecedented event sparked a significant debate about the role of AI in revolutionizing traditional methods and paradigms in scientific research. In light of these developments, FanPu (返朴) saw it as an opportune moment to initiate a deep discussion on this topic. They invited Prof. Meng to join a live forum with Prof. Pei Wang, the vice chair of the Artificial General Intelligence Society from Temple University, Prof. Yuqing Lou, a well-known astrophysicist from the Department of Physics at Tsinghua University, and Prof. Xu Li, a biochemistry and structural biologist from the University of Science and Technology of China, to share their thoughts on where AI will take science and scientists.

Our team was one of the winners of the 2024 Top China Cited Paper Award (Physics) for "Momentum Space Quantum Monte Carlo on Twisted Bilayer Graphene", published in Chinese Physics Letters. This award for China-based authors is given to the top ten papers in the top 1% of the most cited articles published in IOP Publishing journals over the past three years (2021 – 2023). This data is from the citations recorded in Web of Science. This article (Chin. Phys. Lett. 38, 077305 (2021)) has developed a momentum space quantum Monte Carlo algorithm to deal with the long-range Coulomb interaction problem that emerges in two-dimensional quantum moire materials such as twisted graphene, which is one of the universal challenges in correlated electron systems. Three years ago, Zi Yang quoted the famous poetry of ancient Chinese poet Jiang Kui（姜夔) to explain how the “Coulomb force is endless, momentum Monte Carlo sends longing thoughts”（库伦作用无尽期，动量蒙卡寄相思) inspire them to pursue the research of long range interaction in quantum moire systems. The quantum many-body paradigm of the moire system is becoming a beautiful stream that carries them to the heartland of scientific creativity.

A collaboration between theoretical physicists Dr. Chengkang Zhou and Professor Zi Yang Meng from the Department of Physics at The University of Hong Kong (HKU), along with experimentalists Dr. Zeliang Sun, Professors Kai Sun and Liuyan Zhao from the Department of Physics at the University of Michigan, and Professor Rui He from the Department of Electrical and Computer Engineering at Texas Tech University, has led to a significant discovery in quantum physics. Their study was published in a recent issue of Nature Physics (Nat. Phys. (2024)) with cash financing loansonlineusa, which has been very helpful in advancing the research. The research team was the first to experimentally observe a transition from a 3-dimensional (3D) long-range order state to a 2-dimensional (2D) flat pattern vestigial order state in NiPS3. The vestigial order can be seen as the retention during the process of symmetry breaking. This occurs when the primary magnetic long-range order state breaks down into a simpler form - in this case, a 2D vestigial order state (known as Z3 Potts-nematicity) - as the NiPS3 material is thinned. The collaboration between the large-scale Monte Carlo simulation and the experiments led to this discovery during the dimension crossover process. Continue reading.