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Quantum Computing

Quantum computing is a rapidly advancing field of computer science that looks set to start entering mainstream commercial application by the late 2020s or early 2030s. By this time, quantum computers are anticipated to outperform traditional or 'classical' computers for specific applications that are likely to include molecular modelling and logistics optimization. Already many traditional companies -- including IBM, Google, Microsoft and Intel are engaged in quantum computing research, along with many pure-play quantum start-ups and academic institutions. So already some people are now employed as quantum computing programmers and hardware engineers.

This page provides a non-technical overview of quantum computing pioneers and developments, and provides support for the ExplainingComputers Quantum Computing Update videos published in 2023, 2022, 2021, 2020, 2019, 2018 and 2017.

Note that if you want to learn about quantum computing and its application, it is worth revisting the older videos -- particularly the 2017 video for detail on different quantum computing technologies, and the 2018, 2019 and 2020 videos for information on market developments and quantum computing applications.


Traditional or 'classical' computers are built from silicon chips that contain millions or billions of miniature transistors. Each of these can be turned 'on' or 'off' to represent a value of either '1' or '0'. Conventional computers subsequently store and process data using "binary digits" or "bits".

In contrast, quantum computers work with 'quantum bits' or 'qubits'. These can be represented in hardware in many ways. These include:

  • Superconducting qubits -- eg IBM creates transmon qubits using niobium and aluminium, patterned on a silicon substrate.
  • Trapped-ion qubits -- eg IonQ creates qubits using ionized ytterbium atoms.
  • Photonic qubits -- eg Xanadu creates qubits by squeezing laser light using ring resonators.
  • Silicon spin qubits -- eg Intel has fabricated silicon chips with spin qubits in gate-defined quantum dots.
  • Neutral atom spin qubits -- eg Atom Computing creates qubits using the nuclear spin of neutral atoms.
  • Topological qubits -- eg Microsoft is developing quantum hardware based on Majorana zero modes.

Due to the peculiar laws of quantum mechanics, qubits can exist in more than one state -- or 'superposition' -- at exactly the same point in time. This allows a qubit to assume a value of '1', ‘0', or both of these numbers simultaneously. However, when measured or 'observed', the state of a qubit will always collapse to a value of either '1' or '0'.

In quantum computation, qubits represent the probability that their observed state will be either '1' or '0'. And because there are an infinite range of decimal probability values between '1' and '0', this means that a qubit can represent a far larger range of data values than a classical bit.

The fact that qubits are more 'smears of probability' than definitive, black-and-white certainties is exceptionally weird. Flip a coin, and it cannot come up both heads and tails simultaneously. And yet the quantum state of a qubit can in some senses do just that. It is therefore hardly surprising that renowned nuclear physicist Niels Bohr once stated that 'anyone who is not shocked by quantum theory has not understood it!'

In addition to assuming superpositions, qubits can become 'entangled'. 'Entanglement' is another key quantum mechanical property, and means that the state of one qubit is tied to the state of another, regardless of how far apart the two qubits may be. This is useful and powerful, as it means that observing one qubit can reveal the state of its unobserved pair.

Creating and manipulating qubits is very hard indeed. Many of today's experimental quantum processors exploit the quantum phenomenon that occur in superconducting materials, and hence need to cooled to almost absolute zero (around minus 272 degrees celsius). Significant shielding against background noise is also required, and even then performing computation using qubits requires significant error correction. Indeed, a grand challenge in quantum computing is the creation of a truly fault-tolerant machine.


Companies currently developing quantum computer hardware include IBM, Alibaba, Microsoft, Google, Intel, D-Wave Systems, Quantum Circuits, IonQ, Xanadu and Rigetti. Many of these firms work in conjunction with major university research teams, and all continue to accrue significant progress. The following provides an overview of the work of these and many other quantum computing pioneers.


IBM has been working to develop a quantum computer for over 35 years. It is also making significant progress, with many operational machines. As a very significant milestone, in 2016 IBM made a 5 qubit quantum computer publicly available over the Internet. Since this time, more and more cloud-based 'quantum computing as a service' (QCaaS) hardware has been added, with IBM now offering cloud access to wide 'aviary' of online quantum hardware.

To help those wishing to learn about and develop quantum computing, IBM offers an open source quantum computing software framework called Qiskit. This is now available in a runtime version that executes on cloud hardware physically close to the quantum computer it controls, so reducing classical-to-quantum latency. This can speed up quantum computing simulations very significantly -- and indeed IBM has reported a 120x speed increase for simulating a lithium hydride molecule using the latest Qiskit runtime.

In January 2019, IBM unveilled a roadmap to chart its quantum computing plans and progress. This has since been updated on a number of occasions, and most recently in May 2022. In this latest update, IBM revealed its ambition to scale up its quantum computing offering by 'developing ways to link processors together into a modular system capable of scaling without physics limitations'. By 2024, this is anticipated to allow IBM to deliver 4158-qubit system that links together three multi-chip quantum processors called Kookaburra. In line with the roadmap, in November 2022 IBM announced a new 433 qubit processor called Osprey.

IBM's currently-stated endgoal is to create quantum-centric supercomputers. As it explains, 'the quantum-centric supercomputer will incorporate quantum processors, classical processors, quantum communication networks, and classical networks, all working together to completely transform how we compute'.


Another tech giant that is working hard to make quantum computing a reality is Google, which now has a Quantum AI campus that can be explored here. Google's early with in quantum computing involved the use of a machine from Canadian pioneer D-Wave Systems. However, the company is now developing its own hardware, and in March 2018, announced a 72 qubit quantum processor called 'Bristlecone'.

In October 2019, an engineering team from Google published a paper in Nature in which they claimed to have achieved quantum supremacy. Specifically, the Google scientists had used a quantum processor called Sycamore to sample the output of a pseudo-random quantum circuit. Sycamore took about 200 seconds to sample one instance of the circuit a million times. In comparison, the Google team estimated that a classical supercomputer would take about 10,000 years to perform the same calculations. As the team went on to conclude: "quantum processors based on superconducting qubits can now perform computations ... beyond the reach of the fastest classical supercomputers available today. To our knowledge, this experiment marks the first computation that can be performed only on a quantum processor. Quantum processors have thus reached the regime of quantum supremacy."

The Google announcement was big news, but soon controversial. Not least IBM published a blog post in which they stated that the computations in Google's experiment could be undertaken on a classical computer in two-and-half days, rather than 10,000 years. And as IBM went on to contend "Because the original meaning of the term 'quantum supremacy,' as proposed by John Preskill in 2012, was to describe the point where quantum computers can do things that classical computers can't, this threshold has not been met."

Since 2019, Google's quatum computing research and development has continued apace, and in February 2023 the company announced significant progress in quantum error correction.


As you may also expect, as the world's leading producer of microprocessors, Intel is working to develop quantum computing chips, and over the years worked on a number of qubit technologies. Most recently, Intel has reported progress based on a technology using 'spin qubit' that make use of quantum dots. This is a significant, as Intel's spin qubit chips can be manufactured using its traditional silicon fabrication methods.

In March 2022, Intel announced that, in collaboration with research partner QuTech, it had successfully managed to mass manufacture qubits using conventional optical lithographic and associated processes at its D1 manufacturing factory in Oregon. As scientists involved reported in Nature Electronics, 'the compatibility of silicon spin qubits with fully industrial processing demonstrated here highlights their potential for scaling and for creating a fault-tolerant full-stack quantum computer'.

D-Wave Systems

D-Wave Systems is a pure-play pioneer based in Canada, and way back in 2007 demonstrated a 16 qubit quantum computer. In 2011, it then sold a $10 million dollar, 128 qubit machine called the D-Wave One to Lockheed Martin. In 2013, D-Wave next sold a 512 Qubit D-Wave Two to NASA and Google. By 2015, D-Wave even broke the 1,000 qubit barrier with its D-Wave 2X. And in June 2022, D-Wave announced cloud access to a prototype of a next-generation system called Advantage2 that will eventually boast 7000 qubits.

Reading the above list of achievements, you may have concluded that D-Wave has to be the world's leading quantum computing pioneer. However, notwithstanding all of the aforementioned milestones, much of D-Wave's work remains controversial. This is because until very recently all of its hardware has been based on an 'adiabatic' process called 'quantum annealing' that other pioneers have dismissed as 'restrictive' and 'a dead end'. IBM, for example, uses a 'gate-based' approach to quantum computing that allows it to control qubits in a manner analygous to the manner in which a transistor controls the flow of electrons in a conventional microprocessor. But in a D-Wave system their is no such control.

Instead, a D-Wave quantum computer takes advantage of the fact that all physical systems tend toward minimum energy states. So, for example, if you make a cup of tea and leave it standing, when you come back it will be cold as it will have declined to a more minimal energy state. The qubits in a D-Wave system also do this, and so what D-Wave does is to use its hardware to solve optimization problems that can be expressed as 'energy minimization problems'. This is indeed restrictive, but still allows the hardware to run certain algorithms far faster than a classical computer. You can view a great video in which D-Wave explain their approach to quantum computing here.

In August 2016, this paper in Physical Review X reported that certain algorithms ran up to one hundred million times faster on a D-Wave 2X than on a single-core classical processor.

In October 2018, D-Wave launched a cloud-based, quantum application environment called Leap. And in October 2021, it revealed that it had plans to build a gate-based quantum computer. To this end, in September 2023, D-Wave reported that it has been achieving success with the development of gate-based fluxonium qubits.


As you may anticipate, Microsoft is also keen to get in on the quantum computing action, and now has an online offering called Azure Quantum. This brings together a range of services from other companies, and is indicative of Microsoft's approach to advance quantum computing by working with a wide range of partners and academic institutions.

A key element of Microsoft's strategy is the development of quantum computers based on 'topological qubits', which it believes will be less prone to errors (hence requring fewer final system resources to be devoted to error correction). Microsoft also believes that topological qubits will be easier to scale to commercial application.

In March 2022, Microsoft reported that its quantum scientists had managed to engineer hardware that has induced a topological superconducting phase bookended by a pair of Majorana zero nodes. Further, they’ve been able to quantify the stability of this phase, so removing the biggest obstacle to producing a topological qubit. In November 2022, Microsoft released more data from its experiments. On its website, Microsoft now subsequently explains how it is on the path to quantum at scale with its planned topological qubit hardware.

On the software side, Microsoft has now made freely available considerable quantum development resources and educational materials for use with its Azure Quantum cloud computing service. And if you are wondering, the later provides access to a portfolio of quantum hardware from other pioneers.


Over in China, the main web giant is Alibala, not Google. And in July 2015, Alibaba teamed up with the Chinese Academy of Sciences to form the 'CAS - Alibaba Quantum Computing Laboratory'. As its Professor Jianwei Pan explained at the time, this had the mission to 'undertake frontier research on systems that appear the most promising in realizing the practical applications of quantum computing . . . so as to break the bottlenecks of Moore's Law and classical computing'. You can visit the website for the lab here.

Like IBM, D-Wave and several other players, Alibaba has now made an experimental quantum computer available online. Specifically, in March 2018 the Chinese e-business giant launched its 'superconducting quantum computing cloud' to provide access to an 11 qubit quantum computer. This was developed with the Chinese Academy of Sciences, and allows users to run quantum programs and download the results.

University of Science and Technology of China

Also in China, the University of Science and Technology of China has created a 62-qubit superconducting quantum processor called Zuchongzhi. In June 2021, this was reported to have outperformed Google's Sycamore quantum processor by two-to-three times running similar sampling benchmarks. With Zuchongzhi running a sampling benchmark in about 1.2 hours that would have taken about 8 years on a classical supercomputer, the research team behind the system concluded that their "work establishes an unambiguous quantum computational advantage", and it hard to disagree. There is indeed no little doubt that we now have several quantum computers around the planet that are able to do certain things that are very hard to achieve in a reasonable frame of time on a classical computer.


Xanadu is developing photonic quantum computing by designing quantum silicon photonic chips. As the company notes, compared to other qubit technologies, "photons are very stable and are almost unaffected by random noise from heat. We use photonic chips to generate, control, and measure photons in ways that enable extremely fast computation'.

Xanadu's quantum hardware primarily operates at room temperature, which is a major advantage over other technologies. Within the company's processors, qubits are created by squeezing laser light using ring resonators. This creates superpositions of different numbers of photons, which enter a sequence of externally programmable quantum gates called an interferometer, within which they entangle. Finally, special transition edge sensors count the photons exiting the interferometer, which allows the quantum state representing the output of a quantum algorithm to be converted to a stream of numerical data. Xanadu has published a very cool video here that explains how their quantum photonic processors work.

In support of its hardware, Xanadu provides a quantum neural network Python library called Penny Lane, plus another called Strawberry Fields for for simulating and executing programs on quantum photonic hardware.

In September 2020, Xanadu launched the first cloud-based photonic quantum computing service, and in May 2021 it obtained an additional $100m in funding. There is therefore little doubt that Xanadu is a quantum computing pioneer to watch.

Atom Computing

Atom Computing is pioneering the creation quantum computers based on of neutral atom qubit. The company has a great Technical White Paper all about their technology that is very accessible and a great publication.


Also working on photonic quantum computing is PsiQuantum. The company is working with GLOBAL FOUNDARIES, and has set itself the goal to create 1 million qubit photonic quantum computers. Already PsiQuantum and GLOBAL FOUNDARIES claim to have the technical capability to manufacture photonic quantum processors, and in July 2021 PsiQuantum completed a $450m funding round. So once again, it is a photonic quantum computing pioneer to keep a close eye on.


Another pioneer of trapped-ion quantum computing is Honeywell, a company with a long heritage in business computing. The company was formed in 2021 via a merger of the quantum computing division of Honeywell (Honeywell Quantum Solutions), and Cambridge Quantum. In June 2021, Honeywell announced that this created "the world's most advanced quantum computing business".

Alpine Quantum Technologies

Alpine Quantum Technologies develops trapped-ion quantum computers that operate at room temperature, are installed in standard 19” racks, and are even powered from an ordinary wall-mounted power-plug!

Quantum Brilliance

Quantum Brilliance is developing quantum computers that work at room temperature that rely on the properties of the nitrogen-vacancy (NV) centre in diamonds . . .


QuTech is a research institute developing quantum computing hardware and software, as well as the "quantum Internet".


Seeqc is developing its DQM System-on-a-Chip for controlling quantum computing hardware


Toshiba is developing its Quantum Key Distribution (QKD) technology to help secure network communications.


Another quantum computing pure-play is a start-up called Rigetti. The company already has over 120 employees, and has made a 19 qubit quantum computer available online through its developer environment called Forest.

Quantum Circuits

Another quantum computing start-up is Quantum Circuits, which was established by leading quantum computing professor Robert Schoelkopf and other colleages from Yale University. The company has raised $18 million of venture capital, and plans to beat the computing industry giants in the race to make a viable quantum computer.


IonQ is a pure-play pioneer in trapped-ion quantum computing. The company claims that its technology 'combines unmatched physical performance, perfect qubit replication, optical networkability, and highly-optimized algorithms' in order to 'create a quantum computer that is as scalable as it is powerful and that will support a broad array of applications across a variety of industries'. If you want to learn more, IonQ's technology page is an excellent learning resource


IQM is a quantum computing hardware and software pioneer based in Finland.


Amazon has not announced that it is developing quantum computing hardware or software. However, on December 2nd 2019, it did launch a range AWS quantum services. These include Amazon Bracket, which allows scientists, researchers and developers to begin experimenting with quantum computers from multiple hardware providers. Specifically, customers can access hardware from Rigetti, Ion-Q and D-Wave Systems, which means that they can experiment with systems based on three different qubit technologies.

In addition to Bracket, Amazon also launched the Amazon Quantum Solutions Lab. This is intended to help companies to 'get ready for quantum computing' by allowing them to work with leading experts. So a key thing that Amazon is doing with its quantum computing offerings is to act as a cloud broker.


Even the best quantum computer hardware is no use without appropriate software, and many of the above quantum hardware pioneers are developing their own. However, there are also already a growing number of quantum computing software pioneers, as follows.


1QBit parters with large companies and "leading hardware providers to solve industry problems in the areas of optimization, simulation, and machine learning". The company develops software for both classical and quantum processors, although the name of the company indicates their primary focus.


Atos has created a quantum computing simulator which it calls its "quantum learning machine". This is a piece of hardware, but I have listed it here under "software" as it is not a quantum computer, but has the purpose of assisting with quantum computing software development.


Blueqat has created a quantum computing software library that is freely available on GitHub.

Multiverse Computing

Multiverse Computing develops quantum algorithms for the financial services industry.

QC Ware

QC Ware develops "enterprise software and services for quantum computing", with clients including Airbus, BMW and Goldman Sachs, and hardware partners including AWS,D-Wave Systems, Google, IBM, Microsoft and Rigetti, as detailed above.


QSimulate is developing software to "bring the power of quantitative simulations to solve pressing problems in the pharmaceutical and chemistry spaces".

QU & Co

QU & Co develops quantum algorithms and software.


Rahko is creating software that is intended to use quantum machine learning (quantum AI) to solve problems in quantum chemistry.


Riverlane develops quantum computing software, including the Deltaflow.OS quantum computing operating system.


Zapata Zapata works with its clients to develop quantum computing software to solve compulationally complex problems in fields including chemistry, finance, logistics, pharmaceuticals, engineering, and materials.


It is critical to understand that quantum computers are being developed to allow us to do new things in new ways, and not to run existing classical computing applications on a different kind of hardware. Quantum computing applications are expected to include molecular modelling (also known as molecular modelling or quantum chemistry), and this may well turn out to be their killer app. All physical systems are quantum in nature. And this means that if we really want to simulate them accurately, we need to use a quantum computer.

In June 2023, Microsoft made the above extremly explicit when it announced Azure Quantum Elements with the aim of compress 250 years of chemistry into the next 25. This recognizes the importance of quantum computing for improving our understanding of chemistry, not to mention physics and biology, and in turn our practice of material science, engineering and healthcare.

Maybe in the far future, quantum hardware will find general end-user application. But this is not the rearch goal or wider aspiration at the current time. For those wishing to read more, but not wishing to click on everything hyperlinked above(!), here are some selected top sources for more information:

Finally (again), you can read about quantum computing -- and many other and related future computing developments such as organic computing in my book Digital Genesis.

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Quantum computers store and process information using quantum-mechanical states.

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