《科学前沿报告会》第689期-北京大学现代光学研究所

《科学前沿报告会》第689期

发布日期：2026-05-06　　　　点击量：

报告题目:	Enhancing quantum information processing with neuromorphic approaches to data processing
报告专家:	Mauro Paternostro, University of Palermo
报告地点:	物理楼中215
报告时间:	2026年5月11日（周一）上午 10:00-11:00
联系人:	何琼毅（qiongyihe@pku.edu.cn）
专家介绍:	Mauro is Full Professor of Quantum Information Science at the Department of Physics and Chemistry, University of Palermo, and Professor of Quantum Optics at Queen’s University Belfast (QUB). He was awarded his PhD in 2005 (QUB) and was a Leverhulme Trust Early Career Fellow (2005-2008) at QUB and Universität Wien (Austria), a visiting Research Fellow at University of Queensland (Australia, 2008), and an EPSRC Career Acceleration Fellow at QUB (2008-2014). He became Lecturer at QUB in 2008, has been awarded an Alexander von Humboldt Fellowship for Senior Scientists in 2011. He has authored 300+ research papers published in top-tier journals, attracting 20000+ citations and € 20M+ of research funding. He has contributed extensively – through both theory and experimental endeavours – to the development of quantum frameworks for cavity optomechanics, the understanding of the thermodynamics of quantum systems and processes, the development of machine learning-assisted tools for quantum characterization and control, and the assessment of the quantum to classical transition.

I will illustrate how approaches to neuromorphic computing based on the use of uncontrolled reservoirs could help enhancing our ability to to validate quantum processes and states, thus characterising delicate features such as the entanglement between quantum systems in an resource-economic manner. I will show how the theoretical framework presented in this talk has been applied, quite successfully, to photonics-based quantum computers.

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