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.
November 2020: Dimitris was interviewed on Deutsch Welle News Asia on the recent quantum supremacy experiment in China. Check out the interview here.
September 2020: Two new PhD students and a Senior Research Fellow join us. Chee, Beng Yee and Daniel. Welcome guys!
July 2020: New work on qubit efficient algorithms for solving binary optimization problems is out as preprint! We propose and analyze a set of variational quantum algorithms for solving quadratic unconstrained binary optimization problems where a problem consisting of n classical variables can be implemented on O(log(n))number of qubits.
May 2020: Our new work on analog quantum processors for machine learning is out as a preprint! We discuss how the interplay between external driving and disorder in quantum many-body systems can dictate their trainability and expressibility and apply it to solve a generative modelling problem.
March 2020: Our work on “Quantum supremacy in driven quantum many-body systems” using complexity theory arguments is out as a preprint! We hope it will open the path for a large number of existing analog quantum simulators to showcase quantum supremacy and motivate further works in the field!
December 2019: Some of our group’s PhD and Final Year Diploma Theses are now available online. You can find them here.
Research Highlights
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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December 2020: Quantum supremacy and quantum phase transitions
Quantum supremacy and quantum phase transitions S. Thanasilp, J. Tangpanitanon, M. A. Lemonde, N. Dangniam, D. G. Angelakis Phys. Rev …
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July 2020: Qubit efficient algorithms for binary optimization problems
Qubit efficient algorithms for binary optimization problems B. Tan, M. A. Lemonde, S. Thanasilp, J. Tangpanitanon, D. G. Angelakis Quantum …
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