Benefits and challenges for unleashing potential of quantum technologies – WS 02 2021
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The EU long-term vision is the development of the Quantum internet all over Europe: quantum computers, simulators and sensors would be interconnected via quantum networks distributing information and quantum resources. By 2030 the EU is expecting to have created quantum-safe networks for connecting all countries in Europe. However from infrastructure, algorithmic and even legal perspectives quantum computing introduces new challenges that require new theoretical frameworks and robust technical development. How can Europe ensure its Quantum vision? What are the potential benefits of Quantum internet for the society and the existing challenges to tackle?
Brief presentations to stimulate the discussion. Presentations will be non-technical for a broad audience by
- Dimitris Angelakis
- From Feynman’s quantum simulators to today’s emerging quantum software and hardware industry
In 1981, at a conference on physics and computation at the Massachusetts Institute of Technology, Richard Feynman suggested the use of controllable quantum systems, quantum simulators, to simulate physical systems. This was a solution to the fact that classical computers simply can not simulate realistic quantum systems, and thus can not be applied to any realistic applications such as the design of new materials, in chemistry or in developing new drugs.
Since then, a series of very important scientific discoveries in basic science, including several Nobel prizes in quantum physics, led to what is today an emerging quantum computing industry. Now numerous private and public institutions are entering a race for developing operational quantum software and hardware, and promise use cases in a variety of areas from healthcare, finance, AI, and the environment. I will briefly review the recent milestones in this journey both in terms of quantum software and hardware, as well as the challenges ahead to avoid a possible quantum winter.
- Massimo Palma
- When machine learning and quantum physics meet.
I will briefly overview how machine learning techniques are finding new applications in the field of quantum technologies while at the same time new paradigms of machine learning techniques are either inspired or make directly use of quantum mechanical features.
- Sabrina Maniscalco
- Emergent phenomena in complex quantum networks
The development of complex network theory, consequent and motivated by the availability of big data sets, has not only provided a theoretical framework to analyse emergent phenomena but, most importantly, has permitted to introduce models explaining their origin. In the quantum realm, however, a similar step has not yet been undertaken, despite the birth and rise of quantum machine learning. Indeed, although machine learning approaches are commonly associated with enormous predictive power in big data scenarios, they oftentimes lack descriptive power.
Until 20 May 2021.
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Links to relevant websites, declarations, books, documents:
At the invitation of the Commissioner for Digital Society and Economy, a working group of European scientists worked on the "Quantum Manifesto", with the aim of outlining a common strategy for Europe to continue to be at the forefront of the development of this so-called quantum revolution. This is among the largest investments that Europe has planned in research. This massive intervention is carried out on land made fertile by constant attention born in previous years. It can itself be seen as a second phase with respect to what was planned in the period starting around the beginning of the third millennium. A detailed description of the various actions connected to the Quantum Flagship can be found in https://qt.eu and https://iopscience.iop.org/article/10.1088/1367-2630/aad1ea.
Needless to say that all over the world there is a massive investment and attention to the future of quantum technologies. A quantum is forseen to be within reach over the next decade as analysed in this document of the US Department of Energy https://www.energy.gov/sites/prod/files/2020/07/f76/QuantumWkshpRpt20FINAL_Nav_0.pdf or from the roadmap illustrated in the website of the Quantum ICT Advanced Development Center in Japan https://www.nict.go.jp./en/quantum/roadmap.html.
A broad description on how a quantum Internet is getting closer to reality, through a series of key experimental results can be found in this article in Scientific American https://physicstoday.scitation.org/doi/10.1063/PT.3.4612.
In this world-wide race towards the realization of quantum information protocols, an important role is played by private companies. Over the last decade, the different roles played by the public and private sectors have emerged clearly. An interesting overview of this aspects together with a description of the current situation can be found here https://www.scientificamerican.com/article/the-quantum-internet-is-emerging-one-experiment-at-a-time/.
Until 20 May 2021.
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- Rosario Fazio
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- Polina Malaja
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- André Melancia
- Roberto Gaetano, EURALO
- Alessandro Tavecchio
- Amali De Silva-Mitchell, Dynamic Coalition on Data Driven Health Technologies / Futurist
- Velimira Nemiguentcheva-Grau
- Dimitris Angelakis, Centre for Quantum Technologies, Singapore
- is a Principal Investigator at Centre for Quantum Technologies at Singapore, leading the Quantum Computing and Simulation Group. He is also Assoc. Professor of Quantum Physics in the Technical University of Crete. He did his PhD at Imperial College supported by the Greek State Scholarship Foundation, and was then elected a research fellow in St Catharines College, University of Cambridge and the Cambridge Center for Quantum Computing. He is the recipient of the Google Quantum Innovation Award 2018, the Valerie Myerscough Award from University of London 2000, and UK Quantum Electronics and Photonics PhD Prize in 2002. He is serving at the QCN board of the EU Quantum Flagship Project in Quantum Technologies, and also as the Cloud Quantum Computing Coordinator of the Singapore Quantum Engineering Program. In parallel to his academic research, he consults different industries on the potential applications of quantum computing. He has recently founded AngelQ Quantum Computing, a consulting and quantum software startup in stealth mode, where he is the Chief Scientist.
- Sabrina Maniscalco, University of Helsinki
- is the Professor of Quantum Information, Computing and Logic at the University of Helsinki, an Adjunct Professor at Aalto University, the vice Director of the Finnish Centre of Excellence on Quantum Technology, and co-founder and CEO of Algorithmiq Ltd, a startup focussing on quantum algorithms for life sciences. She obtained her PhD from the University of Palermo in 2004 and subsequently worked as postdoctoral researcher in several groups around the world (Bulgaria, South Africa, Finland). In 2011 she was appointed as Associate Professor at Heriot-Watt University in Edinburg (UK) where she worked until 2014 when she moved back to Finland as the Chair of Theoretical Physics at the University of Turku. She has coordinated a number of European and national projects and is member of several scientific advisory boards of world-leading quantum institutions. She is also actively involved in several education, outreach, and science & art projects, such as the online platform QPlayLearn.
- Gioacchino Massimo Palma, University of Palermo, Italy
- Professor of Quantum Optics and Quantum Information Theory at the University of Palermo. Formerly research fellow at the Clarendon Laboratory, Oxford and associate professor at the University of Milan. Working in the field of Quantum Information and Quantum Technologies since the early 90s. Current research area: open quantum system dynamics, quantum thermodynamics, reservoir computing.
- Rosario Fazio, The Abdus Salam International Centre for Theoretical Physics, Trieste
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- Quantum technology will allow us to solve very complex problems. Possible applications include optimisation of operations, simulations in chemistry, biology and physics, design of advanced materials, machine learning, and complex quantum networks (‘quantum internet’), as well as breaking (traditional) encryption.
- There is increasing global competition and investment in developing quantum computing for practical use. Current state of the art technology is still very limited and there are no broadly useful applications yet.
- Classical machine learning can help solve complex quantum problems and describe quantum systems. Future steps could include hybrid quantum-classical machine learning, as well as quantum machine learning. Yet quantum supremacy is not so likely soon; to avoid quantum bubble burst (quantum hype), we need to identify the real areas where quantum machine learning outperforms classical machine learning.
- Social challenges due to quantum computing include geopolitical misuse and some sort of ‘armed race’, endangering privacy (due to high ability to break traditional encryption) and disrupting the job market. Society should ‘democratise’ access to quantum technology by all.
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