Quantum computing is like Forrest Gump’s box of chocolates: You never know what you’re going to get. Quantum phenomena (the behavior of matter and energy at the atomic and subatomic levels) are not certain one way or another. These are vague clouds of possibility, or rather probabilities. When someone observes a quantum system, the system loses its quantum property and “collapses” into a certain state.
Quantum phenomena are mysterious and often counterintuitive. This makes quantum computing difficult to understand. People naturally turn to the familiar to try to explain the unfamiliar, and for quantum computing this often means using traditional binary computing as a metaphor. But explaining quantum computing this way leads to great conceptual confusion because, at a fundamental level, the two are completely different animals.
This problem underscores the often mistaken belief that common metaphors are more useful than exotic metaphors when explaining new technologies. Sometimes the opposite approach is more useful. The freshness of the metaphor must match the novelty of the discovery.
The uniqueness of quantum computers requires an unusual metaphor. As a communication researcher working on technology, I believe that quantum computers can be better understood as a kaleidoscope.
Digital precision and quantum possibilities
The gap between understanding classical and quantum computers is a huge one. Classical computers store and process information through transistors, which are electronic devices that take on binary, deterministic states: one or zero, yes or no. Quantum computers, on the other hand, process information probabilistically at the atomic and subatomic levels.
Classical computers use the flow of electricity to sequentially open and close gates to save or modify information. Information flows through circuits and triggers actions through a series of switches that record information as ones and zeros. Using binary mathematics, bits are the basis of everything digital, from the apps on your phone to account records at your bank to the Wi-Fi signals traveling through your home.
In contrast, quantum computers use changes in the quantum states of atoms, ions, electrons or photons. Quantum computers connect or entangle multiple quantum particles so that changes in one affect the others. They then reveal interference patterns, like multiple stones thrown into a pool at the same time. Some waves merge to form higher crests, while some waves and troughs merge to cancel each other out. Carefully calibrated interference patterns guide a quantum computer toward the solution of a problem.
Achieving a quantum leap conceptually
The term “lice” is a metaphor. The word suggests that during calculations, a computer can break large values into smaller pieces (bits of information) that electronic devices such as transistors can process more easily.
But using metaphors like this comes at a cost. They are not perfect. Metaphors are incomplete comparisons that transfer information from something people know well to something they are trying to understand. The bit metaphor ignores that the binary method does not deal with many different types of bits simultaneously, as common sense suggests. Instead all bits are the same.
The smallest unit of a quantum computer is called a quantum bit or qubit. But transferring the bit metaphor to quantum computing is even less adequate than using it for classical computing. Transferring a metaphor from one use to another blunts its impact.
The common explanation for quantum computing is that classical computers can only store or process a zero or a one in a transistor or other computational unit, while quantum computers can simultaneously store and process both a zero and a one and other values in between throughout the process. superposition
But superposition does not store one or zero or any other number at the same time. There is only an expectation that the values may be zero or one at the end of the calculation. This quantum possibility is the exact opposite of the binary method of storing information.
Based on the uncertainty principle of quantum science, the probability of a qubit storing a one or a zero is like Schroedinger’s cat; The cat may be dead or alive depending on when you observe it. However, during superposition, two different values do not exist at the same time. These exist only as probabilities, and an observer cannot determine when or how often these values exist before the superposition ends.
Leaving behind these difficulties in using traditional binary computing metaphors means adopting new metaphors to describe quantum computing.
looking into kaleidoscopes
The kaleidoscope metaphor is particularly suitable for explaining quantum processes. Kaleidoscopes can create an infinite variety of yet regular patterns using a limited number of colored glass beads, walls dividing the mirror, and light. Rotating the kaleidoscope enhances the effect, creating an infinitely variable display of ephemeral colors and shapes.
Not only can the shapes change, they are also irreversible. If you turn the kaleidoscope in the opposite direction, the image generally remains the same, but the exact composition of each shape and even their structure will change as the beads randomly mix together. In other words, although beads, light, and mirrors can replicate some of the patterns shown previously, they are never exactly the same.
Using the kaleidoscope metaphor, the solution (final model) provided by the quantum computer depends on when you stop the computational process. Quantum computing is not about predicting the state of any particle; It is about using mathematical models of how interactions between many particles in various states form patterns called quantum correlations.
Each final pattern is an answer to a question posed to the quantum computer, and what you get in the quantum computing process is the probability of a particular configuration emerging.
New metaphors for new worlds
Metaphors make the unknown manageable, attainable and discoverable. Approaching the meaning of a surprising object or phenomenon by extending an existing metaphor is as old as calling the edge of an ax “piece” and the flat end “ass.” The two metaphors take something we understand very well from everyday life and apply it to a technology that requires a specific explanation of what it does. Calling an axe’s cutting edge “a little” meaningfully indicates what it does, adding the nuance that it changes the object it is applied to. When the ax shapes or splits a piece of wood, it takes a “bite” out of it.
But metaphors do much more than provide convenient labels and explanations for new processes. The words people use to describe new concepts change, expand and gain a life of their own over time.
When faced with significantly different ideas, technologies, or scientific facts, it is important to use new and compelling terms as windows to open the mind and increase understanding. Scientists and engineers trying to explain new concepts must seek originality and master metaphors—in other words, think about words the way poets do.
This article is republished from The Conversation, an independent, nonprofit news organization providing facts and analysis to help you understand our complex world.
Written by: Sorin Adam Matei, Purdue University.
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Sorin Adam Matei does not work for, consult, own shares in, or receive funding from any company or organization that would benefit from this article, and has disclosed no relevant affiliations beyond his academic duties.