What we're about

This is a group for anyone interested in Quantum Computing and Quantum Information in the Washington DC area. I started this group to find and meet the people around who will do events and participate in the discussion of the topics related to Quantum Computing.

Upcoming events (4)

Introduction to Hybrid Quantum-Classical Machine Learning with Applications

Topic : Introduction to Hybrid Quantum-Classical Machine Learning with Applications

Recent advances in machine learning (ML) and quantum computing (QC) hardware draw significant attention to building quantum machine learning (QML) applications. In this talk, Dr. Chen will first provide an overview of the hybrid quantum-classical machine learning paradigm. Important ideas such as calculating quantum gradients will be described. Then, Dr. Chen will present the recent progress of QML in various application fields such as classification, distributed or federated learning, speech recognition, natural language processing and reinforcement learning. Potential advantage and scalability in the NISQ era will be discussed as well. Finally, he will briefly discuss several promising research directions.

Dr. Samuel Yen-Chi Chen received the Ph.D. and B.S. degree in physics and the M.D. degree in medicine from National Taiwan University, Taipei City, Taiwan. He is now an assistant computational scientist in the Computational Science Initiative, Brookhaven National Laboratory. His research interests include building quantum machine learning algorithms as well as applying classical machine learning techniques to solve quantum computing problems. He was a recipient of the Theoretical Physics Fellowship from the National Taiwan University Center for Theoretical Physics, in 2015, and the First Prize In the Software Competition (Research Category) from Xanadu Quantum Technologies, in 2019.

Moderator: Pawel Gora, CEO of Quantum AI Foundation

Solving Unsolvable Problems: Taming Infinity with Quantum Measurements

Topic: Solving Unsolvable Problems: Taming Infinity with Quantum Measurements

According to Alan Turing, some problems cannot be solved in a finite amount of time. Turing described one such problem, the Halting Problem, in a landmark 1936 paper. Since then, dozens of problems have been shown to be unsolvable, including the problem of deciding whether certain equations can be solved using integers and even some air travel planning problems. A program to solve any of these might require infinitely many steps to run, so no known computer (not even quantum computers) can solve such problems.In 2015, three physicists studied the problem of computing a system's spectral gap -- the least possible energy difference between a system's ground state and its excited state. They showed that certain spectral gap problems are unsolvable. That is, solving such problems would require infinitely many steps. This opens both interesting questions and interesting possibilities.On a philosophical level, we may wonder what feature of nature allows it to do infinite-step calculations. On a more practical level, we can consider ways to convert hard problems into not-so-hard problems. Think about the Karate Kid trying to learn how to block punches. Instead of practicing punch-blocking, he practices car-waxing.Physicists can't compute every system's spectral gap. But when they encounter a physical system, they know how to measure its spectral gap. So, if we start with the air travel problem, we might be able to create a quantum-mechanical system whose gap mimics the travel problem's structure and then measure that system's gap.In this talk, Dr. Burd will discuss some of the details of Turing's original result and provide insight into the workings of the spectral gap problem.

Barry Burd received a Ph.D. in Mathematics at the University of Illinois. He teaches Quantum Computing in his role as a Professor of Mathematics and Computer Science at Drew University in Madison, New Jersey. He's the author of eleven books on technical topics such as Java programming and mobile application development. He's honored to have been named a Java Champion.

Optimized and hardware-aware solutions to quantum problems

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Title: Optimized and hardware-aware solutions to quantum problems: why they are important, and how to create them.

The Apollo 11 onboard computer had about 70 KB of ROM. Creating highly-efficient code is important not just for landing a man on the moon, but also to take maximum advantage of the current resource limitations of quantum computers. And unlike the space program, today's quantum users do have to plan to move their code from one hardware platform to another. Thus, quantum circuits not only need to be generically optimized but also take into account the particular characteristics of the quantum computer they run on. How does one create such circuits? How efficient can they become? Would a machine be able to perform this better than a human programmer? We'll discuss these questions and demonstrate practical applications in optimization, chemistry, and more.

Erik Garcell PhD – Technical Marketing Manager, Classiq
As Technical Marketing Manager, Erik works to articulate the value of quantum computing and how Classiq is revolutionizing the process of developing quantum algorithms.
Erik earned his PhD in Physics from the University of Rochester in 2019, as well as a Master of Science in Technical Entrepreneurship and Management in 2015. He pursued his research on the interactions of femtosecond laser pulses with metals at the University of Rochester’s Institute of Optics, resulting in six first authored publications in journals such as the Journal of Applied Physics and Optical Materials Express. His research and graduate education were supported by the U.S. Air Force Office of Scientific Research, the National Science Foundation, and the Bill & Melinda Gates Foundation.
Erik also has two patents from his time working at Kodak Alaris as an Innovation Research Scientist and IP Coordinator.

Yuval Boger (M.Sc, Physics) is the Chief Marketing Officer of Classiq Technologies (www.classiq.io), a company pioneering a new approach to designing quantum computing circuits. Boger served as CEO and CMO for technology companies from the seed stage to NASDAQ. He is now focused on quantum computing and its broad societal impact.

Pawel Gora, CEO of Quantum AI Foundation

Qiwi - A Quantum Programming Language

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Topic: Qiwi - A Quantum Programming Language


With the ever-growing quantum community, there is a need to make quantum programming easier and more accessible for the programmers at large. Thus we propose a quantum programming language that allows for high-level abstraction and simple and intuitive syntax. While still keeping space for direct construction of circuits. Being the early days of quantum computing even the fundamental operations like add and multiply find more optimal circuits for themselves sometimes with hard to decide trade-offs. Thus a key part of our language is easy modifiability.
Qiwi also comes with a scoring mechanism built into it to decide upon the most suitable definition of overloaded functions. By pre-calculating which variables are to be reused after the current statement and should preferably persist.
Quantum values in Qiwi are stored in data types of dynamic size to save the number of lines. The language also provides various other language constructs common in classical programming like importing other files, if-statements, logical operators and many more.

Speaker: Abhinandan Pal is a final year bachelor's student studying computer science and engineering at the Indian Institute of Information Technology Kalyani. His interests include formal verification, static analysis, programming languages and quantum computing.

Facilitators: Shadad Hussain, co-founder of Quantum Computing India;
Dr. Sebastian Zajac, board member of QPoland

Past events (94)

Quantum Engineering Workshops (May 25 - May 26)

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Photos (241)