The consistent growth in computational power has been a major catalyst behind numerous technological and economic advancements over the recent decades. This growth, characterized by Moore’s Law, hinges on the continuous reduction in the size of electrical components within integrated circuits, resulting in a remarkable increase in processing power. However, we are rapidly approaching a point where transistors are so small that quantum effects will start to impede their performance. To sustain this growth, it is imperative that we explore new avenues of information processing. Quantum computation emerges as one of these new paradigms.
Unlike classical computation, which grapples with quantum limitations at these scales, quantum computation capitalizes on quantum mechanical phenomena such as superposition, entanglement, and interference. This enables exponential acceleration in the execution of various computational algorithms. By harnessing these quantum algorithms, we can delve into complex problems that are currently beyond the capabilities of classical computers, spanning domains like:
- Artificial intelligence
- Cybersecurity
- Pharmaceutical research
- Optimization of stock portfolios
- Discovery of novel materials
- Streamlined supply chain management
- Selection of optimal Pokémon teams
The exceptional speed of quantum computers allows them to accomplish tasks in mere minutes that would demand thousands of years from the mightiest supercomputers. It is highly likely that quantum computation will spearhead the forthcoming technological revolution. However, as with any swiftly advancing technology, we must be well-prepared for the advent of fully operational quantum computers. This readiness involves grasping the implications, adapting our infrastructure to accommodate this technology, and educating the upcoming workforce to effectively utilize its potential.
A) Humanities and social sciences
Requirements:
Understanding of probability, exponentials, and an active imagination.
Method of explanation:
I'll try to explain concepts by way of analogy. Understand that in doing so, we will be sacrificing accuracy in exchange for clarity. I'll try my best to explicitly state when the analogy breaks down.
Learning goals:
A fundamental understanding of how a quantum computer works. Definition of terms and notations that are often used in the quantum computing community.
B) STEM
Requirements:
Linear algebra, and complex numbers.
Method of explanation:
Linear algebra is the mathematical framework for quantum computing. Here I'll describe topics using notions such as vectors, vector spaces, dot products, and linear transformations.
Learning goals:
Understand how quantum bits can be described as vectors and logic operations can be thought of as transformations of those vectors.
C) Physics
Requirements:
Undergraduate level quantum mechanics. Dirac notation and Hilbert spaces.
Method of explanation:
Here we'll represent the qubit states as a two-level quantum mechanical system. We can understand logical operations as unitary operators acting on states within a Hilbert space.
Learning goals:
Understand how the underlying physical mechanisms of quantum superposition, entanglement, and interference can be leveraged for efficient computation.