Dimitris G. Angelakis Group

Classical computers require enormous computing power and memory to simulate even the most modest quantum systems. That makes it difficult to model, for example, why certain materials are insulators and others are conductors or even superconductors. R. Feynman had grasped this since the 1980s and suggested to use instead another more controllable and perhaps artificial quantum system as a "quantum simulator". Beyond applications in the quantum regime, quantum computers and simulators are expected to be able to solve difficult classical problems too in the area of machine learning and optimization. Recent advances in quantum technologies are paving the way as we speak for a second revolution where operational quantum devices are now within reach.

In our group, we are working on all aspects of quantum computing, from the basic science behind them to developing quantum algorithms and software for real world applications. We are theorists but keep close collaborations with all experimentalists in superconducting quantum circuits, room temperature light-matter systems, cold atoms and ions, and integrated photonic chips. We have recently edited two books, two special issues and written a review in our work. Examples of our basic science work include the quantum simulation of exotic phenomena thought to exist only in strongly interacting electronic systems with interacting photons: Mott transitions, spin-charge separation, interacting relativistic theories and many-body localization (the latter with the Google group). More recently we are interested to showcase useful quantum supremacy with analog many-body systems merging complexity theory to thermalization concepts as well as NISQ hybrid digital-analog algorithms for quantum machine learning, chemistry and QUBO problems. Finally, in addition to the "many-body stuff", we are also interested in the "few body" quantum effects found in nano-structures systems interfaced with light, topological physics, and quantum systems in general.

Beyond basic science, we are quite active in industry engangement and outreach, trying to spread the quantum gospel beyond the academic laboratories. Examples of our work include quantum machine learning algorithms for market research, quantum optimization for banking and supply chain.

For further information on collaborations, openings at internships, PhD or Postdoc level, or if you just want to talk to us, please email the group leader.

More information at our homepage: http://dimitrisangelakis.org/

Dimitris G. Angelakis joined CQT in 2009 as a Principal Investigator after being a regular visitor and collaborator of the quantum group since 2003. He was born and raised in a small farm in Chania, Crete, Greece, where his childhood curiosity for the wonders of nature led him to study physics in the University of Crete in Heraklion. In 1998 he was offered a PhD position in quantum optics to work with Sir Peter Knight FRS at Imperial College London supported by the Greek State Scholarship Foundation. His PhD work in quantum light-matter interactions received the Valerie Myerscough prize in 2000, and also the Institute of Physics UK prize in 2002. In 2001 and at age 25 he was elected college research Fellow at University of Cambridge (St Catharine's JRF) and worked in the Department of Applied Mathematics and Theoretical Physics until 2007. A year after his move to Cambridge, the Centre for Quantum Computation in Cambridge was initiated by Artur Ekert, where he joined to work in implementations of quantum simulation and computation. In 2008 he took over a faculty appointment at his hometown Technical University of Crete, where he in now a tenured associate professor of Quantum Physics at the School of Electrical and Computer Engineering (part time since 2012). He is known among others for his pioneering work in quantum simulators using light-matter systems. He received the Google Quantum Innovation Prize in 2018.

Group Members

Recent papers

  • Daniel Leykam, D.G. Angelakis. Topological data analysis and machine learning.
  • Angelina Frank, Daniel Leykam, Daria A. Smirnova, D.G. Angelakis, A. Ling. Boosting Topological Zero Modes Using Elastomer Waveguide Arrays.
  • Aleksandra Maluckov, Ekaterina Smolina, Daniel Leykam, Sinan Gundogdu, D.G. Angelakis, Daria A. Smirnova. (2022). Nonlinear signatures of Floquet band topology. Phys. Rev. B 105 115133
  • Daria A. Smirnova, Lev A. Smirnov, Ekaterina O. Smolina, D.G. Angelakis, Daniel Leykam. (2021). Gradient catastrophe of nonlinear photonic valley-Hall edge pulses. Physical Review Research 3 043027
  • Daniel Leykam, Irving Rondon, D.G. Angelakis. (2022). Dark soliton detection using persistent homology. Chaos: An Interdisciplinary Journal of Nonlinear Science 32 073133
  • B.Y. Gan, Daniel Leykam, D.G. Angelakis. (2022). Fock State-enhanced Expressivity of Quantum Machine Learning Models. EPJ Quantum Technology 9 16
  • Daniel Leykam, D.G. Angelakis. (2021). Photonic band structure design using persistent homology. APL Photonics 6 030802
more preprints > more publications >

We are hiring


Find out more about our PhD Positions on the Join us page.

go to Join Us >