A Similarity Between Quantum Computing and Classical Computing

Anyone exploring quantum computing should be aware that the same tradeoff exists between portability and performance that you find in classical computing. This is increasingly important to be aware of, as the industry is currently trending toward portability across vendors’ platforms. In fact, one of my earliest goals in quantum computing was to run one circuit on multiple platforms, comparing their performances.

This reminds me of when I first learned about the Java programming language. There was a lot of buzz about writing once and running everywhere. And, yet, not everyone transitioned to it.

Today, Python is the world’s most popular development language. Like Java, it’s everywhere. However, if you look at Python.org, you’ll find that performance-critical features are written in C. Along those lines, I recently saw a tweet about how Tesla writes initially in Python, but then translates their code into C++.

That’s the classical tradeoff, in a nutshell. Higher-level languages like Java and Python give you portability, but lower-level languages like C and C++ allow better performance.

The analogy with quantum computing stretches a bit here, but anyone who has been involved for a while knows that you can’t create one circuit and run it optimally everywhere. Yes…