The field of quantum computation will bring competitive advantages to innovative companies, even before efficient quantum computers are available. How is that possible?
Quantum computers exploit quantum effects to enhance their performance in certain computational tasks. They are not simply faster but they actually follow a radically different computational paradigm than conventional devices. Programming a quantum computer is the fine art of designing algorithms that take advantage of the unique features of the quantum world.
In the last 25 years, physicists have been learning how to encode practical problems into the language of quantum algorithms. In their quest for practical applications of quantum computers, they have discovered different ways of efficiently encoding and reading quantum information. Physicists have also developed numerical methods that allow them to benchmark and design quantum computer prototypes. Those methods rely on the efficient encoding of quantum information on special mathematical structures, such as tensor networks, that mimic the structure of the quantum world. All that theoretical knowledge is a technology of its own that can also be exploited in conventional, non-quantum, computers.
Take for example, optimization problems which are ubiquitous in areas like finance or logistics and for which quantum computers are particularly promising. Here, one is interested in finding the best choice amongst an enormous amount of possibilities, for example when designing an investment fund or a distribution route. In the last years, quantum researchers have investigated how to encode practical optimization problems into quantum circuits. They have also developed numerical simulation methods to predict when and how quantum computers show an advantage in optimization. Now, it turns out that one can build on that theoretical research to design so-called quantum-inspired algorithms that are executed in conventional devices, while offering some of the advantages of quantum algorithms!
Beyond optimization, quantum-inspired algorithms can be used in other tasks like simulation and machine learning, and in areas such as quantitative finance, engineering or material science. We know that in many practical applications, the full power of a quantum computer is not really needed—here is where quantum-inspired algorithms may be the ultimate solution. In other applications, they will provide a preliminary solution until quantum hardware becomes cost-effective.
In a digital economy that is thirsty for computational capabilities, quantum-inspired algorithms can be key for innovative companies to keep a competitive advantage. To the inherent complexity of growing data structures, we have to add the need to address environmental and sustainability goals, which will add an extra level of difficulty in planning and decision-making. Quantum-inspired algorithms can offer solutions that are cost-effective, not only for large corporations, but also mid-size companies that cannot afford the access to quantum hardware. Actually, the quantum-inspired approach has the added value of reducing the entry cost into the quantum computing ecosystem, by allowing companies to get ready for the moment in which quantum hardware becomes widely available.
As the quest for large-scale quantum computers goes on, stay tuned for more innovations from the quantum-inspired front, since a virtual quantum leap may be about to be implemented on your classical workstation.