From Feynman to the freezing: the history of quantum computing

From Feynman to the freezing: the history of quantum computing

3D Hardware quantum form
Shutterstock/Dmitriy Rybin

A classical computer uses binary digits with the two possible states of 1 or 0, a quantum computer uses qubits that can exist in multiple states simultaneously. Linking qubits together holds the potential to increase processing power exponentially, which in turn would have a huge impact on the world in a number of ways.

From speeding up the process of developing effective cancer medicines to aiding the advance of other emerging technologies, a range of exciting applications of the technology have been predicted.  One example would be a drastic reduction in the time it takes to create and train artificial intelligence, which would make the technology far more accessible than it currently is.

Spurred on by ambitions to make this revolutionary technology a reality, the likes of Google and IBM have made long, high-profile strides in the last five years, with scientists and engineers closing in on targets of creating 100 qubit systems. Though the world has seen rapid quantum computing progress in recent years, the foundations for this progress were laid in the midst of the previous century.

1965: Feynman

Having already played an important role in the development of the atomic bomb, the famous physicist, Richard Feynman, turned his attention to quantum electrodynamics in the mid-nineteen sixties. This field relates to the way that electrons interact with one another, governed by photons and electromagnetic forces. His research into this area prompted the important prediction that antiparticles are just normal particles moving backwards in time.

This theoretical work from Feynman marks an important foothold at the beginning of the journey toward the developments in quantum computing today, with Einstein himself having doubted the use of Quantum Theory, preferring solid predictions and observation as a basis for exploring physics. It was this thinking from Feynman that would eventually expand to explore the relationship between binary numbers and quantum systems.

1980 – 1985: The universal quantum computer

It was in 1982 that Feynman started lecturing on the advantages of computing with quantum systems, raising awareness to the subject significantly. He famously said that: "Nature isn’t classical, damnit, and if you want to make a simulation of nature, you’d better make it quantum mechanical, and by golly it’s a wonderful problem, because it doesn’t look so easy."

Feynman’s trailblazing was then followed in 1985 by British physicist, David Deutsch, who produced a paper on the concept of a ‘universal quantum computer’, building on the idea of the Turing machine by applying quantum theory. A Turing machine is a mathematical model that uses symbols on a strip of tape that relate to a set of rules, which could be used to simulate any given computer algorithm. By setting out this quantum theory, Deutsch "laid the foundations of the quantum theory of computation and participated in many of the most important advances in the field," according to his Fellow of the Royal Society nomination in 2008.

1994 – 2000: New algorithms

As the end of the 20th century was coming into view, Peter Shor, an American professor of applied mathematics at MIT presented a new algorithm that could find the factors of large numbers much more efficiently than the best classical algorithm. It was so effective that it theoretically put modern encryption at risk. Shor’s algorithm is another of the most significant milestones in the journey towards modern quantum computing.

Next came Grove’s search algorithm in 1996, brought forth by Indian American computer scientist, Lov Grover. This new algorithm for quantum computers proved to be more efficient for the purpose of searching databases. In the same year, Seth Lloyd, a professor of mechanical engineering at MIT, presented a quantum algorithm capable of simulating quantum-mechanical systems

In 1999, D-Wave Systems was founded by Geordie Rose, becoming the world’s first company to sell computers based on quantum computing, with early customers including NASA, Google and Lockheed Martin. The arrival of D-Wave cleared a path for the likes of IBM and Google that now lead the way.

2000 – 2020: Quantum Supremacy

Just after the turn of the century in 2001, scientists at the IBM Almaden Research Center performed the world’s most complicated quantum-computer calculation to date. This effort was carried out by IBM and Stanford University, together publishing the first implementation of Shor’s algorithm by factoring 15 into its prime factors on a 7-qubit processor.

In 2010, D-Wave Systems launched the D-Wave One, marking the first commercial release of a quantum computer. Then in 2016, IBM made quantum computing available via IBM Cloud for the first time. These events have been part of a wave of progress seen from a number of teams in the years leading up to today, with the world now familiar with photos of quantum computers housed in freezing chambers at -273.15 Celsius.

The development of quantum computers has come to look like a race, starting with Google claiming Quantum Supremacy in 2019. While it has not yet become clear who will deliver the first scalable system, we are beginning to see detailed roadmaps spanning the coming years which give an idea of the rate of progress. IBM plans to debut a 127-qubit processor in 2021, with 433 and 1,121-qubit systems following in 2022 and 2023.

A spotlight on Enterprise applications

While there is still a way to go before a commercially useful, scalable system is available, tech companies developing quantum processors are already beginning to partner with businesses to identify applications and key use cases.

The reason quantum systems are set to have a major impact on industry is the capability they have to address complex problems and enhance value chains. Quantum computing is likely to have its biggest industrial impact where problem solving is a major challenge, with AI, finance and healthcare being prime examples.

Supply chains, logistics and transport are other key areas that quantum computing has the power to disrupt, given its ability to process vast quantities of data so quickly. Because of this power, quantum-based systems could enhance efficiency in terms of both time and cost. This could be done by producing more accurate, informed scheduling, taking various conditions or unexpected changes into account and recalibrating accordingly. This would have a significant global impact, given that many existing supply chains are overly complex and operating with outdated, paper reliant systems.