Quantum computing

By exploiting the weird phenomena of quantum mechanics, a quantum computer could perform loads of calculations simultaneously – enough to solve problems far beyond the reach of today’s, and tomorrow’s, most capable supercomputers. ​

The power is in the qubit​

The anticipated advantage of quantum computers over regular computers lies in the basic building blocks. In regular computers, the smallest information carrier is the bit which can take either the value 0 or 1. Generally, 1 is represented by an electrical voltage (typically 5 volts) being on, and 0 by no voltage.  

By contrast, a quantum computer uses quantum bits – qubits for short – which can be both 0 and 1 at once, due to the quantum property known as superposition​

Because each qubit can represent two values at once, the total number of possible simultaneous states doubles with each added qubit. Two qubits can represent four values at once, three qubits gives eight possible values, and so on. It starts slow, but grows faster and faster. Already 300 qubits could represent more values at once than there are particles in the entire universe. And it only takes 50–60 well-functioning qubits to exceed the computing power in today’s supercomputers.

The story begins

Optical LatticeRichard Feynman, the famous physicist, and Yuri Manin came up with the idea of using quantum systems for calculations in the 1980’s. More precisely, they saw that it could be useful for simulations in physics research.  

But at that time, nobody knew how to correct the errors that would inevitably occur in a quantum computer and there were no useful algorithms for quantum computers. 

The situation changed drastically in 1994, when mathematician Peter Shor published a quantum algorithm which rapidly finds the prime factors of a given large number – the key to breaking today’s encryption codes. A year later, he showed how a special error correction code can deal with the errors arising in a quantum computer. This sparked a strong interest in realising a quantum computer. Today, great efforts are made all over the world, at universities as well as companies.

How to build a quantum computer

Unfortunately, there is no simple guide on how to build a quantum computer as it is a very difficult and complex task. But at least, this guide provides a rough overview of the very basics:

1. Select hardware
Pick a controllable quantum system with two (or more) states, for example, an ion having two different energy levels, a superconducting circuit with two different oscillating states, or a tiny semiconductor particle – a quantum dot – with different charge or spin states. Other alternatives are for example, Majorana particles, implanted ions, and photons.

The most promising and developed techniques this far are superconducting circuits and ions. Superconducting circuits are fabricated on a microchip, whereas ions are suspended by electromagnetic fields in a so-called ion trap.

2. Isolate from surroundings
Quantum states are extremely sensitive, and superpositions collapse if they are exposed to disturbances. Therefore, the qubits need to be thoroughly isolated from the surroundings, in order to not “forget” their value immediately. For many types of hardware, this means placing the qubits in an isolated vacuum chamber cooled to just above absolute zero temperature, colder than outer space. Also, take other actions you can think of to reduce disturbances, such as shielding from radiation and magnetic fields. 

3. Control the qubits
To make the qubits work for you, you need a way to manipulate them to put them in the desired input states, put pairs of qubits in entanglement (Einstein's "spooky action at a distance"), perform quantum-logic gate operations, and read out the results. In superconducting quantum computers, this is done using microwave pulses. In ion trap computers, it is done using pulses of laser light with specific wavelengths.

4. Improve and practice
Try running a quantum algorithm. Probably, you will find that the qubits forget their values long before the end of the algorithm. Go back to step 1 and try to remove any imperfections in your quantum hardware. Repeat step 2 and take every action you can think of to eliminate disturbances. Then go back to step 3 and remove all possible imperfections in the control equipment. Also, work on increasing the speed in all operations on the qubits. With better qubits and faster operations, you should now be in a better position to run your quantum algorithm.​

At the front

As mentioned before, superconducting circuits and ion traps are the most developed techniques for building a quantum computer.

In October 2019, Google was first to demonstrate a quantum computer solving a problem that is beyond the reach of a regular computer. This is a major milestone in quantum computing, generally referred to as quantum advantage or quantum supremacy. Google's quantum computer is a 53-qubit superconducting device named Sycamore. Read more in our news article Big breakthrough for quantum computers and in Nature.

A few other companies have built quantum computers, with up to 53 qubits, and made them available for commercial and research activity via the cloud. None of these have yet been reported to have outperformed a classical computer​.

From WACQT’s point of view, it’s not yet time to go for large-scale systems. First, one has to construct a small-scale system that works extremely well. Going directly for large systems, without having good-enough qubits and inter-connections, will inevitably result in large error rates.

Picture: Google A.I. Quantum’s Sycamore processor. Credit: Erik Lucero/Google​

Comparing different quantum computers

News articles often focus on the number of qubits in a quantum computer. However, this number alone tells very little about its performance. There are several other useful metrics to take into account:

  • the connectivity between qubits – the number of other qubits that couple to each qubit,
  • the types of quantum-logic gates that can be implemented, 
  • the reliability, often referred to as fidelity, of the gate operations,
  • the number of parallel operations that can be implemented, and
  • the circuit depth, that is the number of gates in sequence that can be applied to all the qubits before the fidelity has decayed too much during the course of an algorithm.

Coming next

The demonstration of quantum advantage or quantum supremacy, announced in 2019 by Google, is certainly impressive. Their Sycamore quantum processor outperformed a conventional supercomputer in solving a specific problem – but a useless problem chosen only because it is easy on a quantum computer but very hard on a conventional computer. ​

“The next big milestone in quantum computing is to find a useful problem that is beyond the reach of regular computers, but which a quantum computer with fifty to a hundred qubits can solve. We work intensively on this in collaboration with our industry partners. Probably, it will be within logistics or simulation of large molecules,” says WACQT principal investigator Göran Johansson.

Quantum computers are predicted to be particularly suitable for solving problems that involve a large number of possibilities, such as optimisation problems in logistics or machine learning, and the calculation of properties of large molecules. Breaking today’s encryption codes is further away, since running Shor’s famous algorithm requires thousands of well-functioning qubits.

Quantum computers will most likely be part of hybrid computing systems, where a quantum computer operates as a subroutine or co-processor to a conventional supercomputer. The conventional processors will do most of the work, whereas the quantum processor performs the specific calculations that a quantum computer is significantly better at.

Optical Lattice, credit: NIST Image Gallery
Google AI Quantum’s Sycamore processor, credit: Erik Lucero/Google
iStock by Getty Images and Chalmers 


Page manager Published: Fri 18 Dec 2020.