Overview of quantum computing
Submitted on Sat, 04/10/2021 - 10:31am
A quantum computer is a device that performs computation by controlling and measuring quantum states. Quantum computers were first proposed in the 1980s by several physicists, notably Paul Benioff, David Deutsch, Richard Feynman, and Yuri Manin. It is widely believed that quantum computers should be capable of performing computations that would not be feasible on a classical computer, particulary problems in computational chemistry which require the simulation of quantum states.
Quantum Algorithm Implementations for Beginners
Posted on 1 January 2021
Quantum Cryptography School for Young Students
Posted on 22 December 2020
QCSYS is a unique enrichment program for high school students that runs from Tuesday, August 3 to Friday, August 13, 2021. QCSYS will once again run virtually in 2021. This free online program offers a blend of expert lectures, small group discussions, problem solving, and opportunities for mentoring and networking with world-leading quantum researchers.
More information: https://uwaterloo.ca/institute-for-quantum-computing/programs/qcsys
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Quantum Techniques in Machine Learning 2020
Posted on 12 October 2020
There will be free online conference on quantum technology and machine learning. It will be held in November 2020 from the 9th to the 12th. Visit the conference website to register by November 5.
Quantum Techniques in Machine Learning (QTML) is an annual international conference focusing on the interdisciplinary field of quantum technology and machine learning. The goal of the conference is to gather leading academic researchers and industry players to interact through a series of scientific talks focussed on the interplay between machine learning and quantum physics.
QTML was first hosted in Verona, Italy (2017), then Durban, South Africa (2018), and was last held in Daejeon, South Korea (2019). This is the conference's fourth annual year, and will be held online.
Example topics at QTML include, but are not limited to:
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Quantum algorithms for machine learning tasks
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Quantum state reconstruction from data
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Minnesota's Quantum Impact
Posted on 25 August 2020
Over the next five to 10 years, quantum computing will have major impacts on a wide range of industries, including everything from finance, to healthcare - and even traffic.
To explore those upcoming changes, Microsoft released a YouTube series called Quantum Impact, which looked at how the agriculture, chemistry and education sectors will be benefit from quantum technology.
Because Minnesota has strengths in each of those areas, this is great news for us. Here's a look at why our state is in a strong position to take advantage of the upcoming changes:
Agriculture
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The Race is On: Launching a Quantum Computing Start-Up
How does the trajectory and pathway for a quantum computing start-up look? Is it the same as other start-ups? While the race will be on in the coming years as Quantum computing heats up, conventional start-up wisdom doesn’t apply straight across to entrepreneurs in science-based companies including Quantum. Join Aventurine partners Stan Hanks and Genevieve LeMarchal to dive into the nuts and bolts of what it takes to develop and launch a Quantum Computing start-up and take a look at the current market for start-ups in Quantum Computing.
MinneQuantum & the QED-C
Posted on 30 July 2020
MinneQuantum has great news to share, we've joined the Quantum Economic Development Consortium (QED-C)!
We're excited about the benefits that this brings to the Minnesota Quantum Computing Meetup and how this will help us further MinneQuantum's goals of advancing quantum computing and quantum technologies in Minnesota.
But before we dive into that, here's more information on the QED-C:
About the QED-C
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An Introduction to Quantum Computing Through Logic
Abstract: There's always room for one more introduction to quantum computing! This time, let's approach it by taking baby steps from basic boolean logic truth tables to alternate representations of classical logic, relaxing constraints until we arrive at superposition, entanglement, and quantum circuits. After a brief diversion into quantum advantage and the current state of the industry, we'll finish up by combining classical computer science and quantum algorithms for a seemingly simple task: setting a quantum state vector from a classical array of numbers, a foundational task for many algorithms in machine learning and more.
Bio: Vic Putz is the Head of Engineering at QCWare, a Palo Alto startup providing Quantum Computing as a Service. Prior to that, he spent 25 years as an officer in the US Air Force, in both physics and aviation, finishing his career as the Director of Research of the USAF Academy's physics department. He has a MS in Software Development and Management from the Rochester Institute of Technology, and a D. Phil in computational theoretical physics from Oxford University.