by 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 sub-atomic levels – are not certain, one thing or another. They are opaque clouds of possibility or, more accurately, probabilities. When one observes a quantum system, it loses its quantum and “falls” into a definite state.
Quantum phenomena are mysterious and often counter-intuitive. This makes quantum computing difficult to understand. People naturally turn to the familiar to try to explain the familiar, and for quantum computing this usually means using traditional binary computing as a metaphor. But explaining quantum computing in this way leads to great conceptual confusion, because the two animals are completely different at the basic level.
This problem highlights the often mistaken belief that common metaphors are more useful than exotic ones when explaining new technologies. Sometimes the opposite approach is more useful. The freshness of the metaphor should match the freshness of the discovery.
The singularity of quantum computers requires an unusual metaphor. As a communication researcher who studies technology, I believe that quantum computers can best be understood as kaleidoscopes.
Digital certainty vs. quantum probabilities
The gap between the understanding of classical and quantum computers is a wide chasm. Classical computers store and process information through transistors, which are electronic devices that take binary, deterministic states: one or zero, yes or no. In contrast, quantum computers reliably handle information at the atomic and subatomic levels.
Classical computers use the flow of electricity to sequentially open and close gates to record or manipulate information. Information flows through circuits, triggering actions through a series of switches that record information as ones and zeros. Using binary math, bits are the foundation of everything digital, from the apps on your phone to the account records at your bank and the Wi-Fi signals bouncing around your house.
In contrast, quantum computers use changes in the quantum states of atoms, ions, electrons or photons. Quantum computers link, or bind, multiple quantum particles so that changes in one affect the others. They then introduce interference patterns, like multiple stones thrown into a pond at the same time. Some waves come together to create higher peaks, and some waves and troughs come together to cancel each other out. Carefully calibrated interference patterns guide the quantum computer toward solving a problem.
Achieving a quantum leap, conceptually
The term “bit” is a metaphor. The word implies that, during calculations, a computer can break up large values into small bits – pieces of information – that can be more easily processed by electronic devices such as transistors.
However, metaphors like this come at a cost. They are not perfect. Metaphors are incomplete comparisons that transfer knowledge from something people know well to something they are working to understand. The bit metaphor ignores that the binary method does not deal with many different types of bits at the same time, as common sense might suggest. Instead, every bit is the same.
The smallest unit of a quantum computer is called the quantum bit, or qubit. But translating the metaphor to quantum computing is even less difficult than using it for classical computing. When a metaphor is transferred from one use to another, its effect is diluted.
The most widespread explanation of quantum computing is that, while classical computers can only store or process zero or one in a transistor or other computational unit, quantum computers are thought to store and manipulate values between zero and one and values other between them at the same time through the process. of superposition.
However, superposition does not store one number or zero or any other number simultaneously. It is only expected that the values may be zero or values at the end of the calculation. This quantum probability is the polar opposite of the binary method of storing information.
Driven by the uncertainty principle of quantum science, the probability that a qubit stores a one or a zero is like a Schroedinger’s cat, which can be dead or alive, depending on when you look at it. But the two different values do not exist simultaneously during superposition. They are only probabilities, and an observer cannot determine when or how often those values existed before the observation ended the superposition.
Leaving behind these challenges of using traditional binary metaphors of computing requires adopting a new metaphor to explain quantum computing.
Looking at kaleidoscopes
The kaleidoscope metaphor is particularly suitable for explaining quantum processes. Kaleidoscopes can create incredibly varied yet orderly patterns using a limited number of colored glass beads, dividing walls of mirrors and light. Rotating the kaleidoscope adds to the effect, generating endless shows of changing 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 usually remain the same, but the exact composition of each shape or even its structure will vary as the beads randomly mix with each other. In other words, although the beads, light and mirrors may replicate some patterns previously shown, these are never the same.
Using the kaleidoscope metaphor, the solution provided by a quantum computer – the final pattern – depends on when you stop the computing process. Quantum computing is not about measuring the state of any particular particle but using mathematical models of how the interaction between many particles in different states creates patterns, called quantum correlations.
Each final pattern is the answer to a quantum computer problem, and what you get in a quantum computer operation is the probability of a certain configuration.
New metaphors for new lives
Metaphors make the unknown tangible, approachable and discoverable. It is a method of approximating the meaning of a surprising object or phenomenon by extending an existing metaphor, as old as the edge of an ax “bit” and its flat end “butt.” Both metaphors take something we understand from everyday life very well, applying it to a technology that needs a definition of what it does. When the tip of the ax is called a “bit” it clearly shows what it does, adding to the nuance that it changes the object it is applied to. When an ax shapes or splits a piece of wood, it takes a “bit” from it.
Metaphors, however, do much more than provide convenient labels and explanations for new processes. The words people use to describe new concepts change over time, expanding and taking on a life of their own.
When different scientific ideas, technologies or phenomena are at stake, it is important to use fresh and striking terms as windows to open the mind and increase understanding. Scientists and engineers trying to explain new concepts would do well to look for originality and master metaphors – in other words, think of words as poets do.
This article is republished from The Conversation, a non-profit, independent news organization that brings you facts and analysis to help you make sense of our complex world.
It was written by: Sorin Adam Matei, Purdue University.
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Sorin Adam Matei does not work for any company or organization that would benefit from this article, does not consult with, own shares or receive funding from any company or organization that would benefit from this article, and He has disclosed no relevant affiliations beyond his academic appointment.
