Welcome to our group website
We are working in quantum technologies with a focus in implementations of quantum computation and quantum simulation with quantum optical systems. Our research could be applied towards developing exotic high-performance quantum processors and simulators, and also for fundamental science in the area of strongly correlated quantum systems. read more.
October 2022: Our joint work with the leading group of Prof. JW Pan in China on quantum supremacy in many-body systems is out in the arXiv! Our theory prediction from last year that driven many-body systems can be shown to be hard to sample from, has been verified in a beautiful experiment with cold atoms in lattices!
July 2022: Congrats to Chee for putting his first paper on arXiv! We have shown how to go beyond Hartree Fock approximation in calculating molecular energies using NISQ quantum computers using only linear depth quantum circuits.
June 2022: Our collaboration with Alex Ling’s group here at CQT on implementing topological models in waveguide arrays is out on the arXiv!
May 2022: Our introductory review on applications of topological data analysis to physics and machine learning problems in physics including the detection of phase transition.
Apr 2022: Congratulations to our first years PhDs Harvey and Arthur for passing their first comprehensive qualifying exams!
Jan 2022: Arthur Strauss, from EPFL is joining us this month as a PhD student! Welcome Arthur!
Research Highlights
Jan 2023: Shallow quantum circuits for efficient preparation of Slater determinants and correlated states on a quantum computer
Shallow quantum circuits for efficient preparation of Slater determinants and correlated states on a quantum computer Chong Hian Chee, Daniel …
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October 2022: Efficiently Extracting Multi-Point Correlations of a Floquet Thermalized System
Efficiently Extracting Multi-Point Correlations of a Floquet Thermalized System Yong-Guang Zheng, Wei-Yong Zhang, Ying-Chao Shen, An Luo, Ying Liu, Ming-Gen …
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July 2022: Computing Electronic Correlation Energies using Linear Depth Quantum Circuits
Computing Electronic Correlation Energies using Linear Depth Quantum Circuits Chong Hian Chee, Adrian M. Mak, Daniel Leykam, Dimitris G. Angelakis …
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June 2022: Topological data analysis and machine learning
Topological data analysis and machine learning Daniel Leykam, Dimitris G. Angelakis arXiv:2206.15075 Topological data analysis refers to approaches for systematically …
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July 2021: Fock State-enhanced Expressivity of Quantum Machine Learning Models
Fock State-enhanced Expressivity of Quantum Machine Learning Models Beng Yee Gan, Daniel Leykam, Dimitris G. Angelakis EPJ Quantum Technology 9 …
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Jan 2021: Photonic band structure design using persistent homology
Photonic band structure design using persistent homology D. Leykam, D. G. Angelakis APL Photonics 6, 030802 (2021) The machine learning …
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