Quantum Computers Explained – What are Qubits

Quantum physics in and of itself is no simple subject. Explaining how a quantum *computer *works is no different. But this video’s here by popular demand. I hope you enjoy.

Trusty white board here. In order to understand quantum computing, we’ve gotta run through binary computing. 1s and 0s. Only two possible outcomes. We have transistors in *on* and *off* states to control the flow of voltage; basically closing and opening circuits like valves control the flow of water through pipes. It’s always easier to picture circuits in this way.

If the circuit is open, then no pathway exists and current (or, in this case, water) does not flow. But if the circuit is closed, the pathway is completed and water flows unhindered. Transistors are these “valves” or “on/off” switches. For binary systems, like the computers and phones you’re using to watch this video, binary transistors open and close to indicate 1 and 0. I explain it a bit more in this video right here. For now, just know that, if threshold voltage is not reached, a gap in the current is created indicating a “0 for FALSE.” Whether it’s a 1 or 0 really depends on the algorithm being used. They’ll always be opposites. For our examples in this video, 1 = True = closed circuit, and 0 = False = open circuit.

This is how all data in modern computing systems is transmitted and processed. And you can imagine how billions of transistors opening and closing at billions of times per second can amount to some serious data computation. But quantum computers make PCs like *this one* behind me seem like basic calculators. They aren’t binary systems *per se*, although we often use 1 and 0 to denote the range of values quantum bits, or “qubits” can denote.

In a nutshell, “quantum,” in the term “quantum mechanics” defines the energy levels of small particles. And thanks to research done by Werner Heisenberg, Serge Haroche, and David Wineland, we now know that it also describes how an electron can be in two places at once. This is from where quantum *computing* is derived.

Instead of 1s and 0s, regular bits, qubits can represent an infinite range of values between 1 and 0. And unlike the classical counterpart, qubits can be physical objects like electrons and photons. Imagine a compass with one pole denoted 1 and the other pole denoted 0. The needle of the compass can swing wherever it wants within the system – but it can never point to anything higher than one and lower than zero. Instead, it can point to areas in-between the two poles and represent the likelihood of either *becoming* a 1 or 0 once the qubit is processed. This area in-between is what’s known as “superposition.”

When we read and interpret classical three-bit binary data streams, we understand that eight outcomes are possible. Since there are two possible states and 3 bits, 2 raised to n (where n is 3) = 8. So eight possible outcomes here; all probabilities of which must equal 1. So there’s a 100% chance that a three-bit binary system will yield one of these values (since they’re the only values possible with three digits and two numbers).

A quantum three-bit system works a bit different, however. Since each qubit can denote any complex number between 0 and 1, then the sum of the squares of each complex probability must equal 1 for a 100% probability. When we make a measurement of a 3-bit quantum system, the values of the particles in each orientation collapse to a classical state of binary. But the computational power of a three-bit quantum computer *far-exceeds* that of classical systems. Where binary systems require 2 raised to the power N bits, quantum computers can express the same amount of information in just *N* qubits.

For scale, just a 30-bit computer is capable of nearly 10 teraflops of floating point performance. That’s 10 trillion floating operations per second which, in the real world, would require *billions* of transistors.

But like I said in *this* video right here, quantum computers aren’t as practical for every-day users as you might think. Streaming, editing, and even gaming won’t benefit much from quantum PCs in the current state; and they get extremely hot. They have to be cryogenically cooled. They must also be shielded from the outside world, since even the smallest magnetic disturbances can offset a qubit’s reading and promote decoherence. They’re extremely large, expensive, and difficult to maintain, and are more-or-less used for large probability and research operations today.

The viability of these quantum computers will change as our technology and infrastructure does, but I expect we’ll still be relying on the binary system for *many* years to come. They just work. We don’t have to worry about quantum decoherence, overheating, and insane shielding. But much like early binary computers, quantum computers today are very large. Who knows? In fifty years, we may have shrunken an entire system to the size of *this*. If we had enough computational qubits in this as we do classical transistors, imagine the potential.