Realistic modelling of Majorana devices

George Winkler
Friday, October 15, 2021 - 12:15pm

A CMU MSE seminar

Abstract: One of the largest obstacles to scalable quantum computing are errors caused by decoherence. Topological quantum computing uses materials with topological properties limiting errors by their very nature. In this seminar I will give a brief introduction on how to engineer topological superconductor nanowires, a crucial building block of topological quantum computers. To understand and optimally design such nanowire devices sophisticated modelling of their physics is required. I will discuss how to simulate  nanowire devices and compare...

Matthias Troyer, Microsoft (ISC2021 Keynote)

Matthias Troyer
Tuesday, June 29, 2021 - 11:30am

Quantum Computing: From Academic Research to Real-World Applications
Register and learn more here!
Read Matthias Troyer's interview with HPCwire here!

Abstract: Still in early development, quantum computing is already overturning our contemporary notions of computational methods and devices. Using new concepts of computing based in quantum physics,  these computers will be able to solve certain problems that are completely intractable on any imaginable classical computer, such as accurate simulations of molecules and materials, or breaking public key encryption. While this potential is real, quantum computers are best viewed as special purpose accelerators for specific problem classes.

In an effort to bring clarity to the fast-growing field of quantum computing, I will describe the hardware and software architecture of quantum computers and discuss how they differ from conventional classical high performance computers. Based on this, I will also attempt to dispel myths and hype surrounding the field and present a realistic assessment of the potential of these devices and the specific application areas on which they are expected to have a large impact. I will end by showing that quantum computing already generates value today, through quantum inspired approaches. These are quantum approaches implemented on classical HPC hardware that outperform the state of the art of classical methods known before, with applications  in health care, logistics, chemistry and other areas.

Bio: Matthias Troyer is a Distinguished Scientist at Microsoft and affiliate faculty at the University of Washington. He is a Fellow of the American Physical Society and Vice President of the Aspen Center for Physics. Troyer is a recipient of the Rahman Prize for Computational Physics of the American Physical Society for “pioneering numerical work in many seemingly intractable areas of quantum many body physics and for providing efficient sophisticated computer codes to the community.” He is also a recipient of the Hamburg Prize for Theoretical Physics. He received his PhD in 1994 from ETH Zurich in Switzerland and spent three years as a postdoctoral researcher at the University of Tokyo. Later, Troyer was professor of Computational Physics at ETH Zurich until joining Microsoft’s quantum computing program at the beginning of 2017. At Microsoft he works on quantum architecture and leads the development of applications for quantum computers. His broader research interests span high performance computing, and quantum computing, as well as simulations of quantum devices and island ecosystems.

Nathaniel Rosi, Pitt (JACS In Session Webinar)

Nathaniel Rosi, Multiple Speakers
Tuesday, June 8, 2021 - 12:00pm

Metal-Organic Frameworks: Outlooks and Opportunities

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As Metal-Organic Frameworks enter their third decade, new fundamental insights are still being uncovered even as applications spread through every branch of chemistry and commercial products hit the market.

JACS in...

Hassan Halataei, Institute for Research in Fundamental Sciences (PQI Seminar)

Hassan Halataei
Thursday, May 13, 2021 - 9:00am

Pure dephasing effects in superconducting flux qubits and classical simulation of entanglement


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Advancements in the technology of quantum bits invoke more precise calculations of decoherence and dissipative effects. Such noise effects are a result of entanglement of qubits with their surrounding environment. It is interesting to see if the entanglement can be simulated by classical noises...

Stefano Sanvito, Trinity College (CMU MSE seminar)

Dr. Stefano Sanvito
Friday, May 7, 2021 - 11:30pm

From the periodic table to new magnets: climbing the inverse design mountain

Abstract: The development of novel materials is a fundamental enabler for any technology, to the point that often technology and materials innovation cannot be separated. Unfortunately the process of finding new materials, optimal for a given application, is lengthy, often unpredictable, and has a low throughput. Here I will describe a systematic pathway to the discovery of novel compounds, which demonstrates an unprecedented throughput and discovery speed. The method can...

Alba Cervera-Lierta, University of Toronto (SciML Webinar)

Dr. Alba Cervera-Lierta
Thursday, May 6, 2021 - 11:00am

Learning Energy Profiles of Parameterized Hamiltonians for Quantum Simulation Using Meta-VQE

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Abstract: Alba will present the meta-VQE, an algorithm capable to learn the ground state energy profile...

Lilo Pozzo, University of Washington (CMU Chemistry)

Dr. Lilo Pozzo
Wednesday, May 5, 2021 - 4:30pm

Understanding Nanoscale and Molecular Processes in Emulsions Systems

See CMU Chemistry departmental email or contact the host, Olexandr Isayev, at for zoom link.

Abstract: Emulsions are dynamic and complex systems with several physical mechanisms possibly leading to the formation, destruction and transformation of their interfacial and bulk structures. Simultaneously, emulsions are increasingly being used in consumer products (creams, cosmetics), for the synthesis of...

Andrea Skolik, Leiden University (SciML Webinar)

Dr. Andrea Skolik
Thursday, April 29, 2021 - 11:00am

Reinforcement Learning With Quantum Neural Networks

Zoom link 


Abstract: Quantum machine learning has been identified as one of the key fields that could reap advantages from near-term quantum devices, next to optimization and quantum chemistry. Research in this area has focused primarily on variational quantum algorithms, and several proposals to enhance supervised, unsupervised and reinforcement learning algorithms with quantum computing have been put forward. Out of the three, RL is the least studied and it is still an open question whether near-term quantum algorithms can be competitive with state-of-the-art classical approaches based on neural networks even on simple benchmark tasks. In this talk, I will introduce a variational quantum algorithm for deep Q-learning and explain which architectural choices of the quantum model are crucial to make it competitive with its classical counterpart on a benchmark learning task.

Dr. Konstantinos Vogiatzis, University of Tennessee (CMU Chemistry Seminar)

Dr. Konstantinos Vogiatzis
Wednesday, April 14, 2021 - 4:30pm

Coupling Electronic Structure Theory with Machine Learning for Chemical Applications

Abstract: Our recent efforts on the development of new computational methods that couple quantum chemistry with machine learning will be discussed. First, a novel molecular fingerprinting method based on persistent homology, an applied branch of topology, that can encode the geometric and electronic structure of molecules for chemical applications will be presented. We have demonstrated its applicability on studies on non-covalent interactions between functional...