In this episode of our Entangled Things podcast, we address why Quantum Computing (QC) is needed after all. Our discussion revolves around two fundamental ideas:
We address what is probably the biggest problem of CC - complexity. We also show how this problem impacts real-life areas like materials science. And, of course, this discussion cannot ignore a little bit of introduction into concepts related to computational complexity (we do a gentle introduction to P and NP complexity classes). Another interesting topic that we cover is data. We discuss this when we dive into why QC is not going to replace CC. We show that "data" in QC is radically different from "data" in CC, as it refers to the state of systems of qubits.
One cannot discuss the need for QC without addressing the problem of accessibility. Today, QC is cutting edge, and there is a limited number of people that can grasp and understand its fundamental concepts. We discuss how we expect this to change and how QC is supposed to follow CC's same trajectory.
We dedicate the rest of the podcast to a discussion about fields where QC applies. We detail the two major QC approaches: universal QC and quantum annealing (aka quantum optimization).
At some point, Patrick also challenges me to tell the story about the early stages of my journey into understanding quantum concepts. That evolves into an exciting discussion about grasping the "why" question when dealing with QC.
We end the podcast concluding that the future of QC seems tied in many ways to humanity's future. In addition to the significant technological hurdles, we need solutions for human resources' potential limitations. In this context, we mention Microsoft's quantum initiative that revolves around the Quantum SDK, the Q# language, simulation capabilities, and a healthy growing ecosystem of software and hardware partners.
Enjoy our new Entangled Things episode!