What we're about

The future of computing has come out of the labs. Software development for quantum computing is happening in the GTA, and this meetup aims at bringing people from this fledgling industry together with anybody who wants to learn about quantum computing technology, its disruptive potential, and its application in fields as far ranging as fintech and biology.

Upcoming events (3)

Genetic Optimization acceleration using a Quantum Annealer

Online event

This talk will aim at providing a basic understanding of how genetic algorithms work in solving simple logic problems. We will be discussing about the Turing completeness of machines required to solve optimization problems. For any practical application, Classical Genetic Algorithm/ Genetic optimization have been quite ineffective but after the advent of Quantum Computers, Genetic optimization seems like a problem that can be accelerated by Quantum Computers. We will also go through some interesting examples like creating Ion Thrust drives, solving annealing problems and a lot of other interesting things using Quantum Genetic optimization.


Vinay Phadnis is an online instructor on Udemy and has helped a lot of startups scale using various edge technologies like AI, Blockchain and Quantum Computing. He has given guest lectures in various Quantum Computing topics like Quantum Machine Learning, Quantum Drug Discovery, Quantum Annealing etc. He is currently working on his own venture to help businesses leverage the power of Quantum Computing and Blockchain.


Balaji Ramamurthy, Dr. Virendra Golatra

Quantum machine learning with PennyLane and Xanadu Quantum Codebook


The first part of this talk provides an introduction to quantum machine learning using the Python-based PennyLane software library, covering key concepts like variational circuits and hybrid models. We show how circuits can be constructed and trained in PennyLane on a variety of hardware devices and simulators.

The second part of this talk gives an introduction to the Xanadu Quantum Codebook, explaining both the motivation behind it and how to use it.


Thomas Bromley
Thomas is a Quantum Machine Learning Developer at Xanadu who works on PennyLane, the world’s leading quantum differentiable programming software library. Thomas holds an MSc in Physics from the University of Warwick and a PhD in Physics from the University of Nottingham. Thomas' background is in the measurement and quantification of quantum properties and he now focuses on making cutting edge quantum algorithms available through software and over the cloud.

Catalina Albornoz
Catalina holds a MSc. in Electronics from Los Andes University and Engineering Diploma from IMT Atlantique in France. She’s currently Quantum Community Manager at Xanadu, where she helps build the community around PennyLane. In the past Catalina has worked at IBM, where she was an IBM Quantum Ambassador, and at GreenYellow Colombia, where she was Project Manager for energy efficiency projects.


Pawel Gora , CEO of Quantum AI Foundation
Dr. Sebastian Zajac, board member of QPoland


Zoom link will be sent out an hour before the meetup

Held in partnership with the Washington QC Meetup

Quantum Computation for Predicting Electron and Phonon Properties of Solids


Quantum Computation for Predicting Electron and Phonon Properties of Solids


Dr. Kamal Choudhary


Quantum chemistry is one of the most promising near-term applications of quantum computers. Quantum algorithms such as variational quantum eigen solver (VQE) and variational quantum deflation (VQD) algorithms have been mainly applied for molecular systems and there is a need to implement such methods for periodic solids. Using Wannier tight-binding Hamiltonian (WTBH) approaches, we demonstrate the application of VQE and VQD to accurately predict both electronic and phonon band structure properties of several elemental as well as multi-component solid-state materials. We apply VQE–VQD calculations for 307 spin–orbit coupling based electronic WTBHs and 933 finite-difference based phonon WTBHs. Also, we discuss a workflow for using VQD with lattice Green's function that can be used for solving dynamical mean-field theory problems. The WTBH model solvers can be used for testing other quantum algorithms and models also.


Kamal Choudhary is a research scientist in the Materials measurement laboratory at the National Institute of Standards and Technology (NIST), Maryland, USA and Theiss Research, La Jolla, CA, USA. He received his PhD from University of Florida in 2015 and then joined NIST. His research interests are focused on atomistic materials design using classical, quantum, and machine learning methods. In particular, he has developed the JARVIS database and tools (https://jarvis.nist.gov/) that hosts publicly available datasets for millions of material properties. He has published more than 50 research articles in various reputed journals and is an active member of TMS, APS, and MRS societies.


Kareem El-Safty of QEgypt / Pawel Gora (CEO of Quantum AI Foundation) / Dr. Javier Orduz of QMexico/Baylor University


Another event hosted in partnership with the Washington DC QC Meetup Group!

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