IAS@NTU Discovery Science Seminar Webinar “Quantum Simplicity: A Tour of Complexity Science in a Quantum World
October 28, 2020 10:30 am - 11:30 am
Speaker: Mile Gu
Nanyang Assistant Professor Mile Gu leads the Quantum and Complexity Science Initiative at NTU. Prior to that, he was a faculty at the Institute of Interdisciplinary Information Sciences, Tsinghua University under China's one thousand talent program. He is a winner of the 2020 IBM Quantum Key to the Future Contest.
Complexity and quantum science appear to be two fields that bear little relation. Yet, there is growing evidence that in interfacing ideas from quantum and complexity science, we may unveil new perspective in both fields. NAP Mile Gu will introduce computational mechanics and illustrate how many processes that require complex classical models may be simulated by remarkably simple quantum devices. He will also discuss recent experiments to test this in laboratory conditions.
Quantum Machine Learning Journal Club Talks by José Ignacio Latorre, CQT
October 29, 2020 10:00 am - 11:00 am
Online via Zoom
Title: One qubit as a universal approximant
Abstract: The outcome probability of a single qubit quantum circuit can describe any function f(x), provided x is re-uploaded multiple times as parameter of the gates. This can be verified experimentally. I'll also discuss other ideas related to quantum singular value decomposition as well as quantum attacks to crypto protocols.
Register in advance for this meeting: https://nus-sg.zoom.us/meeting/register/tZAqd-usqzkvG9LKB9Dc0ZKPdaA9F-39I1jl
After registering, you will receive a confirmation email containing information about joining the meeting.
CQT Workshop: QTX-4 | Quantum Technologies in Space
October 30, 2020 3:00 pm - 6:00 pm
Venue: Online Event
Title: QTX-4 | Quantum Technologies in Space
The event is co-hosted by the Centre for Quantum Technologies, NUS, and the QTX research forum – led by Alexander Ling of NUS and Markus Krutzik of Humboldt. The forum has previously met in Singapore (2018), Germany (2018) and UK (2019).
The focus will be on quantum communications and the technologies that facilitate delivery from cubesats, and other specific technologies and system issues, e.g. SWaP constraints, and space qualification – from components to missions.
The workshop will take place on 30 October virtually:
Lecture Series: HPC Online Lectures on Quantum Computational Materials Science
November 16, 2020 3:30 pm - 6:30 pm
Venue: Online Event
Title: HPC Online Lectures on Quantum Computational Materials Science
The HPC School on Quantum Computational Materials Science was scheduled be held at the Nanyang Technological University (NTU) campus from 16-20 November 2020. Due to current travel restrictions, the organising committee has decided to replace the HPC school by online lectures to be held from 16-18 November 2020. The HPC school is itself postponed to November 2021. Details will be announced later.
You areinvited to register and join the online lectures https://sss-comp.quantumlah.org/program.phpby:
· Adam Shaffique, Yale-NUS andNational University of Singapore
· Michele Casula, CNRS and SorbonneUniversité
· Guo Chu , Henan Key Laboratory ofQuantum Information and Cryptography
· Martial Duchamp , NanyangTechnological University, Singapore
· Benjamin Lenz , Sorbonne Université
· Dario Poletti, Singapore Universityof Technology and Design
· Antonino Marco Saitta, SorbonneUniversité
· Mathieu Salanne, Sorbonne Université
· Laura Scalfi, CNRS and SorbonneUniversité
· Pinaki Sengupta, NanyangTechnological University, Singapore
· Ari Paavo Seitsonen, CNRS and ENS
· Fabio Pietrucci, Sorbonne Université
· Rodolphe Vuilleumier, SorbonneUniversité and ENS
Register here to attend: https://nus-sg.zoom.us/meeting/register/tZUsdOGhqTwtG9xKHnXJAkrd326tK6fpZ2Zu
CQT Colloquium by Giuseppe Carleo, EPFL
November 19, 2020 4:30 pm - 5:30 pm
Venue: Online Event
Title: Machine-Learning for Many-Body Quantum Physics
Machine-learning-based approaches, routinely adopted in cutting-edge industrial applications, are being increasingly embraced to study fundamental problems in science. Many-body physics is very much at the forefront of these exciting developments, given its intrinsic "big-data" nature. In this seminar I will present selected applications to the quantum realm. First, I will discuss how a systematic, and controlled machine learning of the many-body wave-function can be realized. This goal is achieved by a variational representation of quantum states based on artificial neural networks. I will then discuss applications in diverse domains, ranging from open problems in Condensed Matter physics to applications in Quantum Computing. Focusing on the latter case, I will show that there are relevant cases in which machine learning techniques can be already used to classically simulate useful quantum algorithms, using purely classical resources.
Please register to receive zoom details: http://bit.ly/cqtwebinar
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