“Quantum computers will be able to perform complex calculations, quickly,” said Pierre Dulon, deputy CEO for I.T. and operations at Credit Agricole in Paris, presenting at the Singapore Fintech Festival this week. “Our commercial and investment bank needs to make intense calculations every day.”
When people think about quantum physics – if they think about it at all – they probably aren’t thinking about banks. They might think about a cat inside a box.
This was the famous thought experiment of Erwin Schrödinger, who conceived of a cat inside a box that might be alive, or dead, and what we know about the cat’s status without opening the lid. The idea was to illustrate that the fundamental reality of nature can not be measured in a binary fashion, but a series of probabilities based in the relationships between objects and observers.
Quantum mechanics is concerned with the interactions of atoms and their components, and its weirdness has necessitated stories like cats in a box. But the science explains natural phenomena very well. So well, in fact, that some scientists now describe the universe in terms of being a giant computer.
“If nature is one big universal computer,” said Bob Sutor, chief quantum exponent at IBM in the U.S., “then electrons are the data and the applications are us – our chemistry, every physical reaction we have. Nature itself is the biggest computer that can solve these. Can we imitate how nature works as a way of computing?”
Mathematicians and engineers have been working for years to do exactly that: develop the hardware for quantum computers and the algorithms they can carry out.
Today we have prototype quantum computers in operation, although they can’t do anything useful. Not yet. Bu that utility is just around the corner, which is why banks like Credit Agricole are so keen to use them.
“The magnitude of change will be high,” said Valerie Sauvage, managing director and head of I.T. for Asia Pacific in Singapore. She oversees a new team developing use cases for quantum computing in risk management and capital markets.
More mathematicians!
Banks are looking at the technology to optimize portfolios, price complex products, simulate market conditions, and upgrade cybersecurity.
Aside from the fact that quantum computers are still embryonic, the biggest hurdle banks face is a dearth of talent.
“Quantum computing needs skills different from traditional programming,” Dulon said. “It requires some knowledge of quantum physics and a solid background in mathematics.” Credit Agricole is looking to partner with fintechs and universities with such people.
Computing au naturale
Ilyas Khan, CEO of Cambridge Quantum in the U.K., said (rather optimistically), “There’s no reason to be mystified by quantum computing.”
Quantum computers use sub-atomic particles to carry information, just as a classical computer operates a transistor to manipulate electrical signals to do the same. But a transistor and its heir, the microprocessor, are “contrived items”, as Khan put it. They are human contraptions meant to manipulate nature, and so they come with limits. Quantum computing is based on natural phenomena. It’s the “real McCoy”. Therefore it doesn’t face limitations on what it can compute, at least in theory.
The trick is to make the machines actually work.
The hardware we have today is sensitive and jangly. Errors occur at the most basic level of the hardware: the qubit, which is to say, the quantum bit.
In classic computing, a bit is the most basic unit of information, either zero or one, and a byte is thousand bits. DigFin is writing this on a Mac laptop with 500 gigabytes of storage. That’s a lot of ones and zeros zipping around the laptop’s microprocessors. As amazing as the Mac is, it can still only run relatively simple programs. That’s because its microchips are “contrived items” and therefore limited.
The quantum computing world has turned bits into qubits, or quantum bits. These process far more information than a bit: instead of zero and one, a qubit measures the potential of a bit being either one – in other words, is the cat inside the box dead or alive? The uncertainty is calculated in probabilities rather than a binary relationship, creating a huge field of possibilities for a computer to crunch.
The revolutionary qubit
The trick is that, as per quantum mechanics, you can’t actually observe the position of sub-atomic particles without yielding nonsense results. In other words, trying to monitor the output from quantum computers has a tendency to crash the system. But as engineers build ever-bigger arrays of qubits, they’re learning how to harness their power.
John Martinis, professor of physics at University of California at Santa Barbara, says scaling the use of qubits is one way to benchmark progress. For example, Google and other companies say it will take about 1 million qubits to maintain operations despite errors – in other words, to run software programs.
Right now the biggest quantum computer has only 64 qubits. That makes it sound like the industry is far away from reach 1 million qubits, but progress may be exponential.
With that in mind, experts believe it will require a 50 million-qubit computer to crack most encryption protocols. That sounds even further away, but the reality is that governments and companies will need to either develop quantum cyber defenses right away, or assume all their secrets will be unraveled in as few as ten years.
“This represents an industrial revolution that we are all living through,” Kahn said. “This revolution is more fundamental than any that’s taken place in history.”
Bigger than the internet?
“This as big as the adoption of classical computers in the 1980s,” said Sauvage at Credit Agricole.
“This is bigger,” Khan said.
Sooner than you think
Quantum computing hasn’t attracted the hype of artificial intelligence. But governments such as the U.S., China, U.K., Singapore, Germany, and others are pursuing quantum computing as national priorities.
The world’s biggest technology companies are also in the race: Google, for example, has declared it will have a fault-tolerant computer running by 2029. Fintechs and universities are trying out a variety of hardware and physical systems. Add it up and there is now a growing and diverse ecosystem.
This means the impact of quantum computing will be felt before 2029. Kahn likens today’s situation to the introduction of the first mobile phones, which were big and clunky and used only by a few rich people. But those early adopters drove innovation. Similarly, the internet existed as obscure domains among science and defense research labs before the World Wide Web knitted it together so it could be commercialized.
The World Wide Web was an early example of open-source development, which made the internet accessible to anyone with a computer and a modem. The same is already happening with quantum computing: IBM operates a 25-qubit quantum computer in the cloud, so that anyone can use the hardware online.
From cyber to A.I.
Experts agree that quantum computing is about to begin to influence cybersecurity. Within five years it will be used to address big questions in chemistry. Its ability to calculate scenarios and optimizations will begin to improve risk management in finance and other fields.
The biggest impact, though, will be adopting quantum computing in artificial intelligence.
“You can’t skip over A.I. and machine learning if you want quantum,” IBM’s Sutor said. “Deep down, all of A.I. is math; it’s heavy calculations. Quantum will enable us to do this faster for A.I. so we can find better patterns and better insights.”
For example, in the financial services world, a big concern about A.I. is “explainability”. A neural network provides results that humans can’t understand, even if the output works.
This is a problem for the industry, however. Trading desks need to explain their strategies, investors need to explain their portfolios, and credit officers need to explain why they approved or rejected a loan application (including reasons of human bias that gets cooked into the coding). Quantum computing has the power to unlock the mysteries of machine learning.
Can we do better this time?
From encryption to explainability, though, quantum computing will pose similar questions about ethics and good governance – questions that went ignored in the rise of classical computing and the internet, which is why we are inundated with deep fakes, adversarial networks, data breaches, and data harvesting by big tech platforms.
“We were asleep at the wheel in the 1990s,” said Khan from Cambridge Quantum. “We’re paying the price today. We need to start talking about this now.”
The state of quantum computing is therefore a lot like Schrödinger’s cat in the box. Will it be a force of good – or a threat? We can’t lift the lid to see, and so the answer is a probability field. It’s vital that banks, among other organizations, prepare for whatever changes are in store, ideally in partnership with regulators and the public.