Quantum Computing Comes. What Can It Do?

Digital computing has limitations in relation to an important category of computation called combinatorics, in which the order of data is important to the optimal solution. These complex, repetitive calculations can take even the fastest computers a long time to process. Computers and software that are based on the assumptions of quantum mechanics have the ability to do combinatorics and other calculations much faster, and as a result many companies are already exploring the technology whose known and likely applications already include cybersecurity, bioengineering, AI. , finance, and complex manufacturing.

Quantum technology is approaching the mainstream. Goldman Sachs recently announced that they could introduce quantum algorithms at the price of financial instruments in just five years. Honeywell is expected to make up $ 1 trillion in industry in the coming decades. But why are companies like Goldman making the leap – especially with commercial quantum computers perhaps years away?

To understand what is going on, it is helpful to take a step back and examine what exactly computers do.

Let’s start with today’s digital technology. At its core, the digital computer is an arithmetic machine. It is cheap to perform mathematical calculations and its impact on society has been huge. Advances in both hardware and software have enabled the application of all computing to products and services. Today’s cars, dishwashers and boilers all have some sort of computer embedded in them – and that’s before we even get to smartphones and the internet. Without computers we would never reach the moon or put satellites into orbit.

These computers use binary signals (the famous 1s and 0s of code) that are measured in “bits” or bytes. The more complicated the code, the more processing power required and the longer the processing takes. What this means is that for all their progress – from self-driving cars to beating grandmasters at Chess and Go – there are still tasks that traditional computing devices struggle with, even when the task is spread across millions of machines.

A particular problem they struggle with is a category of calculus called combinatorics. These calculations involve finding an arrangement of items that optimizes some goal. As the number of items increases, the number of possible arrangements increases exponentially. To find the best solution, today’s digital computers basically have to repeat each swap to find a result and then identify which one best achieves the goal. In many cases this may require a huge number of calculations (think about breaking passwords, for example). The challenge of combinatorial calculations, as we shall see in a minute, applies to many important fields, from finance to pharmaceuticals. It is also a critical issue in the development of AI.

And here come quantum computers. Just as classical computers have reduced the cost of arithmetic, quantum presents a similar cost reduction to calculating frightening combinatorial problems.

The Value of Quantity

Quantum computers (and quantum software) are based on a completely different model of how the world works. In classical physics, an object exists in a well-defined state. In the world of quantum mechanics, objects occur only in a well-defined state after we observe them. Before our observation, two states of objects and how they are related are matters of probability. From a computational perspective, this means that data is recorded and stored differently – through non-binary quits of information rather than binary bits, reflecting the multiplicity of states in the quantum world. This multiplicity can enable faster and lower cost calculation for combinatorial arithmetic.

If that sounds like a lie, it’s because it is. Even particle physicists struggle to think about quantum mechanics and the many extraordinary properties of the subatomic world it describes, and this is not the place to try a full explanation. But what we can say is that quantum mechanics does a better job of explaining many aspects of the natural world than classical physics, and it accepts almost all the theories that classical physics has produced.

Quantum translates, in the world of business computing, to machines and software that can basically do many of the things that classic digital computers can do and also do one big thing that classic computers can’t: do combinatorial calculations quickly. As we describe in our article, Business Applications of Quantum Computing, that will be an important issue in some important domains. In some cases, the importance of combinatorics may already be central to the domain.

  • Chemical and biological engineering. Chemical and biological engineering involves the discovery and manipulation of molecules. Doing so involves the movement and interaction of subatomic particles. In other words, it involves quantum mechanics. The simulation of quantum mechanics was an essential incentive in Richard Feynman’s initial proposal to build a quantum computer. As molecules become more complex, the number of possible configurations grows exponentially. It becomes a combinatorial calculus, suitable for a quantum computer. For example, programmable quantum computers have already shown successful simulations of simple chemical reactions, paving the way for increasingly complex chemical simulations in the near future. With the emerging feasibility of quantum simulations, which helps predict the properties of new molecules, engineers will be able to consider molecular configurations that would otherwise be difficult to model. This capability means that quantum computers will play an important role in accelerating current efforts in material discovery and drug development.
  • Cybersecurity. Combinatorics was central to encryption for more than a thousand years. The 8 of Al-Khalilth century Book of Crypt Messages looked at permutations and combinations of words. Today’s encryption is still built on combinatorics, emphasizing the assumption that combinatorial calculations are essentially unmanageable. With quantum computing, however, cracking encryption becomes much easier, posing a threat to data security. A new industry is growing that is helping companies prepare for future vulnerabilities in their cybersecurity.

As more people turn their attention to the potential of quantum computing, applications beyond quantum simulation and encryption are emerging:

  • Artificial intelligence. Quantum computing may open up new opportunities in artificial intelligence, which often involves the combined processing of very large amounts of data to make better predictions and decisions (think face recognition or fraud detection). Growing research field in quantum machine learning identifies ways that quantum algorithms can enable faster AI. The current restrictions on technology and software make quantum artificial general intelligence quite a distant possibility – but it certainly makes thinking machines more than a subject for science fiction.
  • Financial services. Finance was one of the earliest domains to embrace Big Data. And much of the science behind the price of complex assets – such as stock options – involves combinatorial calculation. When Goldman Sachs, for example, prices derivatives, it applies a very computer-intensive calculation known as Monte Carlo simulation, which makes projections based on simulated market movements. Computer speed has long been a source of advantage in financial markets (where hedge funds compete for millisecond advantages in obtaining price information). Quantum algorithms can increase speed for a significant set of financial calculations.
  • Complex manufacturing. Quantum computing can be used in taking large production data sets on functional failures and translating them to combinatorial challenges that, when paired with a quantum-inspired algorithm, can identify which part of a complex production process has contributed to events of product failure. For products such as microchips, where this production process can take thousands of steps, quantum can help reduce costly failures.

The opportunity for quantum computing to solve large-scale combinatorial problems faster and cheaper has prompted billions of dollars of investment in recent years. The greatest opportunity may be to find newer applications that benefit from the solutions offered by quantum. As a professor and entrepreneur Alan Aspuru-Guzik saidthere is “a role for imagination, intuition and adventure. It may not be about how many kits we have; it may be about how many hackers we have.”

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