Workshop on Quantum Computing

The recent advances in quantum information, and in particular the continuous developments with quantum computers have the potential to revolutionise the theory of computation and communication. These recent developments inspired the increase of fertile scientific connections between quantum computing, machine learning and network science. The use of tensor networks, quantum machine learning and quantum complex networks have demonstrated that quantum information theory can be a valuable resource for classical machine learning, and vice versa.

The workshop will take place over two days and will bring together researchers in the above fields to further explore grounds for collaboration and to address the big questions in the field. An important goal of the workshop is to train the new generation of scientists.

Wednesday 1st April and Thursday 2nd April 2020

Invited Speakers for Quantum Computing Workshop

Gerardo Adesso, 'Quantum resources and how to use them'

Abstract: The quirky features of the quantum realm have puzzled scientists for a century. Microscopic particles can be in superpositions of two states at once -- say heads and tails -- and share entanglement, a correlation that defies their separation in space and time. Efforts in unmasking and controlling these and other signature traits of quantum mechanics triggered a technological overhaul currently rivalling last century’s industrial revolutions. This talk will explore the boundaries of the quantum world and investigate the operational significance of its most elusive manifestations, adopting the guiding formalism of resource theories. We will show in particular that every (convex) quantum resource yields an advantage in a channel discrimination task, enabling a strictly greater success probability than what is achievable by any state without the given resource. This may be seen to provide a universal framework to define and quantify "quantum supremacy" in practical applications.

Jacob Biamonte

Sougato Bose

Leigh Chase

Jens Eisert

Jonathan Oppenheim

Valentina Parigi, 'Quantum Complex Networks In Continuous Variables Quantum Optics'

Abstract: The study of quantum complex structures is crucial for choosing the best strategies to use in future multi-scales complex quantum technologies. Multimode quantum optics processes offer scalable platforms for implementing large networks of continuous variables entanglement correlation and emulating networks of harmonic oscillators with physical interactions. The strategy offers totally reconfigurable topology from regular to complex shapes. In particular, I’m going to discuss continuous variables entangled networks for quantum routing protocols, the emergence of complex network structures in quantum networks under non-Gaussian operations, and machine learning techniques for their experimental characterization.

Jyrki Piilo, 'Complex quantum networks and open quantum systems'

Abstract: Complex networks became a major research area about 20 years ago though their use in quantum physics is still in early stage. We describe complex quantum networks of coupled harmonic oscillators in the context of open quantum systems and demonstrate the possibilities they provide for reservoir engineering, experimental realizations, and quantum probing.

Roberta Zambrini

Gilles Zemor, 'Recent progress on quantum LDPC codes'

Abstract: it is commonly assumed that quantum computers will eventually have to rely on error correcting codes of LDPC type,hence the interest into their research, among other motivations. Many mysteries surround our current knowledge, among them whether we have hit a fundamental limit for the minimum distance of LDPC codes or whether we just don't know how to go beyond. We shall discuss recent constructions of quantum LDPC codes that achieve a minimum distance slightly above the square root of the block length and that rely on higher-dimensional simplicial complexes. Based on joint work with Shai Evra and Tali Kaufman.

The programme for the workshop will be available at a later date.