What is quantum computing?


Quantum computing was first conceived of in the early 1980s by researchers including Paul Benioff, Richard Feynman and Yuri Manin. It aims to use the quantum behaviours of quantum objects (which includes photon which are not atomic of subatomic particles) to solve some problems faster and more easily than classical computers or even supercomputers can, and with less power.

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What is a quantum computer and how does it differ from today’s computer systems?

Quantum computing is an emerging technology that seeks to use the unique nature of the quantum realm – which exists at the scale of atoms and subatomic particles – to solve complex problems. In theory, large quantum computers could solve some types of problems, such as breaking cryptographic encryption or solve complex optimization problems, much faster than classical computers can. However, the current technology remains far from mature.

Quantum computers use quantum properties of elementary particles such as atoms, electrons or photons with qubits. These have the particularity of being able to manage states superimposing a 0 and a 1. Combined together, they make it possible to superimpose a large number of values.

So, what is a quantum computer and how does it differ from the computing systems we’re familiar with today?

Rather than using the binary system of 0s and 1s (bits) of classical computing, quantum computing uses qubits whose state at any moment in time can be represented by a complex number called an amplitude, which describes the probability of getting either 0 or 1 when reading out the state of the qubit. That complexity according to current thinking, could make quantum computers – especially large ones with many thousands or millions of qubits or more – better at solving difficult problems.

How does a quantum computer work, and what are potential quantum computing advantages? And what is a qubit?

A qubit can be any quantum-mechanical system which has two distinct and controllable quantum states, such as the polarization of a photon of light, the energy level of an atom or the spin of an electron. Because qubits can exist in more states than standard bits can, a quantum computer can handle much more information per qubit than a classical computer can per bit. For example, while 1024 bits provide 128 bytes of RAM, the same amount of data can be stored using just 10 qubits. A 1000-qubit quantum computer could manage 21000 different numbers.

What could quantum computers do?

So, what are quantum computers potentially capable of doing? Quantum computers are not expected to replace classical computers or supercomputers. They may perform better at certain kinds of computing tasks, but they will look and work very differently from the devices we use today. And, for many problems, conventional computers will remain the best option. But quantum computers might be able to deliver advantages for certain kinds of computing challenges, such as:

Cryptography

Developed by Peter Shor in 1994, Shor’s integer factoring algorithm is a quantum algorithm to identify the prime factors of any integer, or a whole number. That’s a problem that classical computers can’t solve in a practical timeframe today for large integers. Public-key cryptographic systems currently take advantage of this difficulty to create public keys used in data encryption for emails, online financial transactions and other secure communications like VPNs and SSH. The public key is a product of two very large prime numbers that are known only to the selected recipient. No one else in theory could calculate those primes to decrypt the message.

Shor’s algorithm shows that sufficiently powerful quantum computers could break today’s public-key cryptographic systems. This possibility has led to growing research into ways to provide stronger data security and privacy using quantum cryptography.

Optimisation problems

Beyond breaking cryptographic systems, what is a quantum computer potentially able to do? With the right amount of power, quantum computers could help to find optimal solutions to some kinds of problems with large numbers of potential outcomes. For example, they could be used to build models predicting the most likely paths for subatomic particles in high-energy physics research. Quantum computers could also solve the travelling sales person problem, which involves trying to find the shortest possible route between multiple destinations. Achieving this could bring great advances to big data technology.

Machine learning

With their optimisation capabilities, quantum computers could help create better models for machine learning and deep learning, with a lower error rate.

Other applications

There are many other potential applications for quantum computers, including developing new drugs or optimising finance. The key word is potential. While there are clear applications for which quantum computers would provide a powerful advantage over classical computers, the challenge is to build one that scales. Today’s technology isn’t yet advanced enough to be practical for real-world problems that regular computers can already solve, much less for tasks that today’s devices can’t handle.

What is the current state of quantum computing?

The field of quantum computing appeared to take a big step forward in 2019, when a leaked research paper indicated that Google’s quantum computer Sycamore had achieved quantum supremacy. That’s a term that describes when quantum computers can quickly solve a problem that no classical computer could within a feasible timeframe.

In November 2021, the announcement of a 127-qubit processor marked the first time a device achieved the milestone of more than 100 qubits.

What are the challenges for developing quantum computers?

The biggest obstacles are called noise and decoherence. When a quantum particle is not isolated from the surrounding environment, any unwanted interaction – even the act of taking a measurement – can cause it to collapse into a classical bit with a simple value of either 0 or 1. Noise and decoherence have a consequence: qubits have a very small lifetime, currently around 100 µs for superconducting qubits. Only a few quantum gates can be executed successfully during this amount of time.

Qubit noise and decoherence require the use of quantum error correction codes (QECC), which combines several physical qubits into logical qubits with an apparent much lower error rate and longer lifetime. While QECC concepts have been validated at small scale in labs, it is challenging to implement. First, scaling the number of qubits is complicated, whatever the type. Indeed, the number of physical qubits required to create a single logical qubit can be as large as a thousand. And we need at least 100 logical qubits to create a useful universal quantum computer. This equates to a 100,000 physical qubit system and today we’re only around 100.

Quantum computing hype vs. reality

Things behave in strange ways at the quantum level. Quantum objects act like both waves and particles at once. But measuring a quantum object collapses the wave function, so an observer sees it as a particle. Quantum objects can also exist in multiple states at once – something called superposition. And they can be entangled with other quantum objects.

What is quantum entanglement? It means that measuring one object also affects the entangled object, even if the two are far apart. Entangled quantum objects have correlated states, but random ones.

Because these behaviours are hard to understand and explain, they are often described in oversimplified ways. For example, it’s inaccurate to say a qubit is “both a 0 and a 1 at once”. And quantum computers are unlikely to always be better and faster than classical computers – for some types of problems, regular computers will remain the better option. Even where quantum computers could have an advantage, such as in breaking encryption, we are far from being able to build such a device.

Today’s quantum computers represent a significant advance over previous devices. But they have yet to prove effective at solving practical problems.

What is the future of quantum computing? Many researchers and industry vendors are working to achieve new milestones, and momentum is also growing to train the next generation of quantum computing experts and programmers. Advances in quantum computing technology will also likely drive demand for innovation in areas such as cloud storage, data mining and other technologies.

OVHcloud and quantum computing

OVHcloud is starting to provide developers with an access via the cloud to all the different technologies through partnerships with quantum startups like Pasqal and Quandela, but also with players such as Atos. Emulation, simulation and QPU will be deployed to offer a wide choice and help build a coherent European Quantum ecosystem.

“OVHcloud can help to build a coherent European quantum ecosystem”
Octave Klaba - Founder & Chairman, OVHcloud

Working in partnership with Atos, OVHcloud is making Atos’ quantum emulator available as a service to our users. Our goal is to make quantum emulation technologies more accessible to research laboratories, universities, startups and large companies looking to design quantum software and explore pioneering applications ahead of the quantum computing market.

Using Atos technology, OVHcloud will be able to offer quantum computation solutions through Jupyter Notebooks, offering easy access to developers and building on work by OVHcloud’s artificial intelligence teams.

To learn more, read the quantum computing announcement from Atos and OVHcloud.

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