Podcast.init

Building Quantum Computing Algorithms In Python

Oct 29 '19

Summary

Quantum computers are the biggest jump forward in processing power that the industry has seen in decades. As part of this revolution it is necessary to change our approach to algorithm design. D-Wave is one of the companies who are pushing the boundaries in quantum processing and they have created a Python SDK for experimenting with quantum algorithms. In this episode Alexander Condello explains what is involved in designing and implementing these algorithms, how the Ocean SDK helps you in that endeavor, and what types of problems are well suited to this approach.

Announcements

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Your host as usual is Tobias Macey and today I’m interviewing Alex Condello about the Ocean SDK from D-Wave for building quantum algorithms in Python

Interview

Introductions
How did you get introduced to Python?
Can you start by giving a high-level overview of quantum computing?
What is the Ocean SDK and how does it fit into the business model for D-Wave?
What are some of the problem types that a quantum processor is uniquely well suited for?
- How does the overall system design for a quantum computer compare to that of the Von Neumann architecture that is common for the machines that we are all familiar with?
What are some of the differences in algorithm design when programming for a quantum processor?
- Is there any specialized background knowledge that is necessary for making effective use of the QPU’s capabilities?
- What are some of the common difficulties that you have seen users struggle with?
- How does the Ocean SDK assist the developer in implementing and understanding the patterns necessary for Quantum algorithms?
What was the motivation for choosing Python as the target language for an SDK to attract developers to experiment with quantum algorithms?
Can you describe how the SDK is implemented and some of the integrations that are necessary for being able to operate on a quantum processor?
- What have you found to be some of the most interesting, challenging, or unexpected aspects of your work on the Ocean software stack?
- How do you handle the abstraction of the execution context to allow for replicating the program behavior on CPU/GPU vs QPU
Is there any potential for quantum computing to impact research in previously intractable computer science research, such as the P vs NP problem?
What are your current scaling limits in terms of providing compute to customers for their problems?
What are some of the most interesting, innovative, or unexpected ways that you have seen developers use the Ocean SDK and quantum processors?
What are you most excited for as you look to the future capabilities of quantum systems?
- What are some of the upcoming challenges that you anticipate for the quantum computing industry?