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.
May 2024: Another new work was recently put out onto the arXiv by our PhD student Chee and collaborators. In this work, we integrate concepts based on the classical combination of quantum states into existing fault-tolerant algorithms for Hamiltonian simulation.
March 2024: We are excited to share our latest paper on “Nonlinear Quantum Dynamics in Superconducting NISQ Processors”, a collaborative effort by postdoc Muhammad and others from the Technical University of Crete. We tackle the ground state problem of the nonlinear Schrödinger equation and gain insights into the practical implementation and robustness of QCFD algorithms against hardware-induced noise.
April 2024: Check out our recent paper published to Advanced Quantum Technologies, part of our QEP project in collaboration with ExxonMobil! Using our unique qubit compression quantum optimization algorithms, we solve a route optimization problem, for instances ranging from 11 to 3964 routes constructed with data provided by researchers from ExxonMobil. State of the art so far was maximum 20-30 routes!
Jan 2024: Another new work was recently put out onto the arXiv by our PhD student Harvey, who shows how dimensionality reduction techniques from machine learning can be used to distinguish between thermal and non-thermal phases in quantum many-body scar systems!
July 2023: A new work from our research assistant Elias building up on our qubit compression algorithms for solving QUBO problems and applications in finance. We solve the transaction settlement problem and boost the performance by almost two orders of magnitude compared to the state of the art!
July 2023: Another paper was recently put up onto arXiv by PhD student Benjamin and others in the group. We show how the localization landscape can form the basis for hardware-efficient quantum algorithms for solving binary optimization problems, which is competitive with standard QAOA circuits of similar depth!
Research Highlights
June 2023: Qubit efficient quantum algorithms for the vehicle routing problem on quantum computers of the NISQ era
Qubit efficient quantum algorithms for the vehicle routing problem on quantum computers of the NISQ era Ioannis D. Leonidas, Alexander …
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 …
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 …
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, Panagiotis Kl Barkoutsos, …
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 …
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 …