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 level – are not exactly definitive. They are opaque clouds of possibilities, or rather: probabilities. When one observes a quantum system, it loses its quantum nature and ‘collapses’ into a final state.
Quantum phenomena are mysterious and often counterintuitive. This makes quantum computing difficult to understand. People naturally turn to the known to try to explain the unknown, and for quantum computing this usually means using traditional binary computing as a metaphor. But explaining quantum computing this way leads to major conceptual confusion, because at a basic level they are completely different animals.
This problem highlights the often incorrect belief that common metaphors are more useful than exotic ones in explaining new technologies. Sometimes the opposite approach is more useful. The freshness of the metaphor must match the novelty of the discovery.
The unique nature of quantum computers calls for an unusual metaphor. As a communications researcher who studies technology, I believe quantum computers are better understood as kaleidoscopes.
Digital security versus quantum opportunity
The gap between understanding classical computers and quantum computers is a wide one. Classical computers store and process information through transistors, which are electronic devices that assume binary, deterministic states: one or zero, yes or no. Quantum computers, on the other hand, process information probabilistically at the atomic and subatomic level.
Classical computers use the flow of electricity to open and close gates sequentially to capture or manipulate information. Information flows through circuits and triggers actions through a series of switches that register information as ones and zeros. Using binary math, bits form the basis of everything digital, from the apps on your phone to the account information at your bank and the Wi-Fi signals bouncing around your home.
Quantum computers, on the other hand, 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 quantum particle affect all the others. They then introduce interference patterns, such as multiple stones thrown into a pond at the same time. Some waves combine to create higher peaks, while some waves and troughs combine to cancel each other out. Carefully calibrated interference patterns guide the quantum computer to the solution of a problem.
Conceptually, realize a quantum leap
The term ‘bit’ is a metaphor. The word suggests that a computer can break down large values into small pieces of information during calculations – which electronic devices such as transistors can process more easily.
However, using metaphors like these comes at a price. They are not perfect. Metaphors are incomplete comparisons that transfer knowledge 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 types of different bits at once, as common sense might suggest. Instead, all bits are the same.
The smallest unit of a quantum computer is called the 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 weakens its effect.
The prevailing explanation for quantum computers is that while classical computers can store or process only a zero or one in a transistor or other computing unit, quantum computers supposedly simultaneously store and process both zero and one and other values in between. of superposition.
However, superposition does not store one, zero, or any other number at the same time. There is only an expectation that the values at the end of the calculation can be zero or one. This quantum probability is the opposite of the binary method of storing information.
Driven by the uncertainty principle of quantum science, the probability of a qubit storing a one or zero is comparable to Schroedinger’s cat, which can be dead or alive depending on when you observe it. But the two different values do not exist at the same time during superposition. They exist only as probabilities, and an observer cannot determine when or how many times these values existed before the observation ended the superposition.
Moving past these challenges in using traditional binary computing metaphors means embracing new metaphors to explain quantum computing.
Looking into kaleidoscopes
The kaleidoscope metaphor is particularly suitable for explaining quantum processes. Kaleidoscopes can create infinitely diverse yet orderly patterns using a limited number of colored glass beads, mirror separating walls and light. Rotating the kaleidoscope enhances the effect and generates an infinitely variable spectacle of fleeting colors and shapes.
Not only do the shapes change, but they cannot be reversed. If you turn the kaleidoscope in the opposite direction, the images will generally remain the same, but the exact composition of each shape or even their structures will vary as the beads randomly mix together. In other words, while the beads, light, and mirrors may mimic some patterns previously shown, they are never absolutely the same.
Using the kaleidoscope metaphor, the solution a quantum computer provides – the final pattern – depends on when you stop the computing process. Quantum computers are not about guessing the state of a particular particle, but about using mathematical models that show how the interaction between many particles in different states creates patterns called quantum correlations.
Each final pattern is the answer to a problem posed to the quantum computer, and what you get in a quantum computer operation is the probability that a particular configuration will result.
New metaphors for new worlds
Metaphors make the unknown manageable, approachable and discoverable. Approaching the meaning of a surprising object or phenomenon by expanding an existing metaphor is a method as old as calling the edge of an ax its “bit” and the flat end its “butt.” The two metaphors take something we understand very well from everyday life, and apply it to a technology that requires a specialized explanation of what it does. Calling the cutting edge of an ax a “bit” evocatively states what it does, and adds the nuance that it changes the object to which it is applied. When an ax shapes or splits a piece of wood, it takes a “bite” out of it.
However, metaphors do much more than provide useful labels and explanations for new processes. The words people use to describe new concepts change over time, expand, and take on a life of their own.
When dealing with dramatically different ideas, technologies, or scientific phenomena, it’s important to use fresh and eye-catching terms as windows to open minds and increase understanding. Scientists and engineers who want to explain new concepts would do well to look for originality and master metaphors – in other words, to think about words the way poets do.
This article is republished from The Conversation, an independent nonprofit organization providing facts and analysis to help you understand our complex world.
It was written by: Sorin Adam Matei, Purdue University.
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Sorin Adam Matei does not work for, consult with, own shares in, or receive funding from any company or organization that would benefit from this article, and has disclosed no relevant affiliations beyond their academic appointment.