A deep dive into the building block of quantum computers.
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In honor of the International Year of Quantum Technology, I plan to write as many articles as possible about different aspects of the quantum field. However, to discuss deeper and more technical topics, I first need to explain the basics well enough so everyone can catch up later.
Quantum computers are systems that utilize the powers of quantum physics and mechanics to execute computations. In order for me (or anyone, really) to explain how quantum computers can be better at solving some problems or how they would solve these problems, we first need to discuss how they work.
Quantum computers are powerful because they can utilize interference, superposition, and entanglement. If you already know about these concepts, great; if not, keep an eye out for my next article, which will dive deep into them.
Let’s take a quick detour first and discuss why ML, AI, and software engineers may benefit from learning some quantum computing basics. For ML and AI engineers, Quantum Machine learning is a topic at the intersection of quantum mechanics and machine learning. Because of superposition, quantum can “enhance” ML models by allowing them to address different environmental inputs more efficiently. As for…