Roger Melko

Professor, University of Waterloo; Associate Faculty, Perimeter Institute for Theoretical Physics

[Sofia Gonzalez Garcia @sofiagonga]

Very happy to finally share my work in collaboration with the @GoogleQuantumAI team, where we developed a new variant of the DMRG algorithm and used it to perform spectroscopy of transmon arrays: https://t.co/qTuPDc1Rnv

[Juan Felipe Carrasquilla Álvarez @carrasqu]

Apply to this nice program at ETH

[Zlatko Minev @zlatko_minev]

Kicking off the AI+Quantum, ACP 2025 great workshop, organized by Eun-Ah Kim, Xiaoliang Qi, Victor Galitsky, and Michael Brenner, with:

Machine learning for practical #quantum error mitigation

Slides: https://t.co/6ChaU3ayJb

#ai #ml

[Waterloo Region Record @WR_Record]

Waterloo startup launches open source platform for making a quantum computer https://t.co/pz1cEaLDGs

[Xanadu @XanaduAI]

We are excited to announce our partnership with Open Quantum Design (@OpenQuantumDes).

Together, we aim to democratize quantum computing, accelerate research and fuel industry applications.

Read more🔗👇

[Roger Melko @rgmelko]

Thrilled to announce Open Quantum Design and its four founding partners - building the world's first open source quantum computer https://t.co/dLX0sc0hP4

[Will Zeng @wjzeng]

Single qubit gates with errors below 10^-6!

https://t.co/VwkCsdsonM

Impressive result on ions

[Michael Albergo @msalbergo]

Come to Cambridge! There is a tenure-track position at Kempner and Harvard CS. Please share around:

https://t.co/bPfCzIFsxN

[Juan Felipe Carrasquilla Álvarez @carrasqu]

We are organizing a workshop on ML for quantum matter in Dresden in February 2025. Amazing speaker lineup. The application deadline is Nov. 30, apply! https://t.co/mYTGLde38x

[Roger Luo 罗秀哲 @rogerluorl18]

we have a full-time opening on compiler engineer at QuEra Computing Inc.! https://t.co/eJWswYIl7K is an exciting moment to work on the this new direction of software and algorithm, if you know a talent compiler engineer, quantum compilation researcher, please forward to them!

[Jan Olle @jolle_ag]

It was a pleasure to organize last week's workshop on AI for quantum tech @MPI_Light !

Thank you to all our attendees for the lots of inspiring works presented and the very insightful discussions.

The future of AI x quantum tech is looking great! 🚀

[Christian Weedbrook @_cweedbrook]

Happy BDay @PennyLaneAI!

[Marin Bukov @MarinBukov]

hoping to see many of you at this upcoming machine learning 4 quantum matter workshop @mpi_pks in Dresden (Feb 24-28, '25):

https://t.co/J1MvHT9HTL

application *deadline* is _Nov 30_ !

[Debanjan Chowdhury @debch_veritas]

Please help spread the word for next year’s Boulder School for Condensed Matter and Materials Physics, with an incredible lineup of speakers. Please encourage your students and postdocs to apply (Deadline: January 15). https://t.co/mQoD2pgsPL @NSF @CUBoulder @Yale

[Michael Albergo @msalbergo]

This was a years-long effort pushed forward by @aavishkar_patel and Peter. Later we will share a companion paper on improving the computational methods.

[Perimeter Institute @Perimeter]

PI’s Postdoctoral Program is accepting 2025 applications!
Join a unique research environment with the freedom to focus on physics problems that drive your passion.

The deadline for applying is November 8, 2024.
Apply here: https://t.co/Jo6MTYybey

[Perimeter Institute @Perimeter]

John J. Hopfield and Geoffrey E. Hinton win the 2024 Nobel Prize in Physics for their groundbreaking work in machine learning with neural networks. Hinton is the fourth Canadian laureate in a decade! PI congratulates both on their achievement!
Read more: https://t.co/kPITP3jGpO

[Isaac De Vlugt @DeVlugtIsaac]

Oh yeah, forgot to mention that you can fiddle around with Hinton's *prized* algorithm, the restricted Boltzmann machine, with QuCumber!

https://t.co/4xgIn54TRy

pip install qucumber

It's an RBM that does quantum state reconstruction.

Carry on.

[The Nobel Prize @NobelPrize]

This year’s #NobelPrize laureate in physics John Hopfield created an associative memory that can store and reconstruct images and other types of patterns in data.

The Hopfield network can store patterns and has a method for recreating them. When the network is given an incomplete or slightly distorted pattern, the method can find the stored pattern that is most similar.

Read more about the research that led to this year’s physics prize: https://t.co/QuIdxRvuEP

[The Nobel Prize @NobelPrize]

The 2024 #NobelPrize laureates in physics used tools from physics to construct methods that helped lay the foundation for today’s powerful machine learning.

John Hopfield created a structure that can store and reconstruct information. Geoffrey Hinton invented a method that can independently discover properties in data and which has become important for the large artificial neural networks now in use.

Although computers cannot think, machines can now mimic functions such as memory and learning. This year’s physics laureates have helped make this possible. Using fundamental concepts and methods from physics, they have developed technologies that use structures in networks to process information.