Quantum technology is approaching the mainstream. Goldman Sachs recently announced that it could introduce quantum algorithms for pricing financial instruments in as little as five years. Honeywell, an American publicly traded, multinational conglomerate corporation believes that quantum technology will form a trillion-dollar industry in the coming decades. But why are companies like Goldman daring to take this step, especially since commercial quantum computing may still be years away?

In order to understand what’s going on, let’s step back and examine what exactly computers are doing. We will start with today’s digital technology. At its core, the digital computer is a calculating machine. It made mathematical calculations inexpensive to perform and had a tremendous impact on society. Advances in both hardware and software have enabled all types of computing to be applied to products and services. Today’s days, cars, dishwashers, and boilers are all equipped with some kind of computer, and that’s before we even get to smartphones and the internet. Without computers, we would never have reached the moon or put satellites into orbit.

These computers use binary signals (the famous ones and zeros of the code) measured in bits or bytes. The more complicated the code, the more computing power is required and the longer it takes to process. This means that for all their advancements, from self-driving cars to defeating 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 computation called combinatorics. These calculations are about finding an arrangement of elements that optimizes a specific goal. As the number of items increases, the number of possible arrangements grows exponentially.

In order to find the best arrangement, today’s digital computers basically have to go through each permutation to find a result and then figure out which one achieves the goal best. In many cases, this can require an enormous amount of calculations (for example, think about cracking passwords). The challenge of combinatorial computation, as you will see shortly, applies to many important fields, from finance to pharmaceuticals. It also represents a critical bottleneck in the development of artificial intelligence, and this is where quantum computing comes in. Just as traditional computers have reduced the cost of arithmetic, quantum computers represent a similar cost reduction in computing massive combinatorial problems.

**The value of quantum**

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 do not appear in a well-defined state until the user observes them. Before observation, the states of two objects and their relationship are a matter of probability. Computationally, this means that data is recorded and stored in a different way by non-binary information qubits than by binary bits, reflecting the multitude of states in the quantum world. This variety can allow faster and cheaper computation of combinatorial arithmetic.

It has been noted that even particle physicists have difficulty becoming familiar with quantum mechanics and the many extraordinary properties of the subatomic world it describes. However, it is said that quantum mechanics can explain many aspects of the natural world better than classical physics and that it takes into account almost all the theories that classical physics has produced. Quantum, in the world of commercial computing, means machines and software that can, in principle, do many of the things that traditional digital computers can do, plus one great thing that traditional or classic computers can’t: perform combinatorial computations quickly.

In a paper called ‘Commercial Applications of Quantum Computing’, experts described, this is going to be a big deal in a few important areas. In some cases, it is already known that the importance of combinatorics is central to the subject. The paper has described various aspects that go with quantum which includes chemical and biological engineering sciences, cybersecurity, artificial intelligence, financial services, and complex manufacturing.

Chemical and biological engineering is about the discovery and manipulation of molecules. This requires the movement and interaction of subatomic particles. In other words, it’s quantum mechanics. The simulation of quantum mechanics was a central motivation in Richard Feynman’s original proposal to build a quantum computer. The more complex the molecules become, the greater the number of possible configurations. The result is a combinatorial calculation that is suitable for a quantum computer. For example, programmable quantum computers have already demonstrated successful simulations of simple chemical reactions, paving the way for increasingly complex chemistry simulations in the near future. With the increasing feasibility of quantum simulations, which help predict the properties of new molecules, engineers will be able to account for molecular configurations that would otherwise be difficult to model. This capability means that quantum computing will play an important role in accelerating current efforts in materials research and drug development.

Another aspect is cybersecurity in quantum computing. Combinatorics has been central to encryption for over a thousand years. Al-Khalil’s 8th-century book of cryptographic messages dealt with permutations and combinations of words. Today’s encryptions are still based on combinatorics, which underlines the assumption that combinatorial calculations are fundamentally unmanageable. However, with quantum computers, cracking encryption becomes much easier, which poses a threat to data security. A new industry is emerging to help organizations prepare for upcoming cybersecurity vulnerabilities.

As more and more people turn to the potential of quantum computing, applications are emerging that go beyond quantum simulation and encryption. Quantum computing potentially opens up new possibilities in artificial intelligence, which often involves the combinatorial processing of very large amounts of data to make better predictions and decisions (think facial recognition or fraud detection). A growing field of research in quantum machine learning is identifying ways in which quantum algorithms can enable faster AI. Due to the current limitations of technology and software, the possibility of quantum artificial general intelligence is slim, but it certainly makes thinking machines more than just a science fiction topic.

Another area where quantum computing can potentially open up is Financial services. Finance was one of the first areas to use big data. And much of the science behind the pricing of complex assets like stock options is based on combinatorial calculations. For example, when Goldman Sachs prices derivatives, it applies a very computationally intensive calculation called Monte Carlo simulation, which creates forecasts based on simulated market movements. Computational 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 the speed of important financial calculations.

Also, with quantum computing, large manufacturing datasets on operational failures can be captured and turned into combinatorial challenges that are combined with a quantum-inspired algorithm and can determine which part of a complex manufacturing process contributed to product failures. For products like microchips, where this production process can involve thousands of steps, quantum technology can help reduce costly failures.

Quantum computing’s ability to solve large-scale combinatorial problems faster and cheaper has led to billions of dollars in investment in recent years. Perhaps the biggest opportunity is finding more new applications that benefit from the solutions offered by Quanta. As professor and entrepreneur Alan Aspuru-Guzik said, “Imagination, intuition and adventure come into play. Maybe it’s not about how many qubits we have; Maybe it’s about how many hackers we have.”

**The quantum race is underway**

Governments around the world have allocated more than $25 billion to quantum research and development. Tech giants like IBM, Google, Alibaba, Microsoft, Amazon and others are competing to mainstream quantum computing as an everyday tool for businesses. For example, IBM announced its plans to build a 1,000-qubit quantum computer by 2024, a first in the tech industry, and broke new ground in November 2022 with the unveiling of Eagle, a cutting-edge processor that appears to be the most remarkable of quantum computing. The processor developed by IBM could thus embark on a remarkable new path in IT. The developers assembled a 54-qubit Sycamore processor and demonstrated its quantum quality by performing the task of generating an irregular number in 200 seconds, which would take the supercomputer 10,000 years to complete.

The company also unveiled its latest 72-qubit quantum computer, the Bristlecone. Alibaba’s cloud management service provider Aliyun and the Chinese Academy of Sciences have jointly developed an 11-qubit quantum program available to the general public on its quantum computing cloud platform. Not only big technology companies, but also well-funded startups have developed the quantum computing room to develop hardware, algorithms and security applications. Some of these are Rigetti, Xanadu, 1Qbit, IonQ, ISARA, Q-CTRL and QxBranch.

One of the main goals that companies are currently advancing towards is the supposed quantum incomparability, when a quantum computer applies the estimate that no conventional computer can function in a reasonable time frame. In October 2019, Google also claimed it had achieved unprecedented quantum quality, but this case has been disputed. Some experts, including Intel’s head of quantum hardware, Jim Clarke, believe the ultimate goal should be quantum practicality, he told IEEE, alluding to the moment when quantum computers can truly achieve something new and unique. Additionally, researchers accept that quantum computing will gradually enter the enterprise space and do things that would have been generally unthinkable.

**An ocean of opportunities for enterprises**

The varied analysis and advances in quantum computing by major technology companies and other organizations are opening an ocean of open doors for CIOs and IT offices to transform the innovation into the current reality. As Prashanth Kaddi, Partner at Deloitte India, notes, quantum computing is undeniably suited to handling complex optimizations and searching unstructured data quickly. They can bring about potentially problematic changes in all areas, including research, drug discovery, the distributed branch network and traffic flow, energy optimization, and more. In addition, quantum computing significantly reduces time to market and helps improve customer satisfaction.

For example, a drug organization may significantly limit the ability to introduce new drugs. In finance, it could enable faster and more complicated Monte Carlo stimuli such as trading, price optimization, market instability, value appreciation techniques, and more. Once again, JP Morgan Chase and co., together with IBM, are developing advanced philosophies for financial demonstration, including decision estimation and risk analysis. Another company, ExxonMobil, plans to work with IBM Quantum to solve the strategic challenge of shipping the world’s cleanest fuel, LPG, around the world.