Quantum computing is still far from widespread application, but the potential it brings is undeniable.
In recent years, technology giants like Google, IBM, and numerous startups have invested billions of dollars into quantum computing, even though this technology is still quite a distance from practical application. Many experts believe that once quantum computers are fully developed, they will have the potential to completely transform the technology landscape. However, the question remains: “What will quantum computers be used for, and why are they so highly anticipated?”
The idea of a type of computer capable of harnessing the strange phenomena of quantum mechanics has been around since the 1980s, but it is only in the last few decades that scientists have come closer to creating large-scale devices. Today, with the advent of quantum processing units (QPUs) and simple quantum computers, researchers are striving to make this technology reliable and capable of tackling complex problems that far exceed the capabilities of current supercomputers.
Quantum computers can handle tasks that classical computers cannot.
Quantum computers are fundamentally different from classical computers. Their uniqueness lies in the ability to process vast amounts of information through the phenomenon of quantum superposition, where a qubit can exist simultaneously in both states of 0 and 1.
This allows quantum computers to represent and process a large number of solutions concurrently, vastly outperforming the sequential processing of classical computers. According to Norbert Lütkenhaus, director of the Institute for Quantum Computing at the University of Waterloo, quantum computers can handle tasks that classical computers “simply cannot perform.”
Current quantum computing still faces many limitations, particularly regarding the number of qubits and their stability. The largest quantum computer today can reach up to 1,000 qubits, but most commercial systems only have a few dozen to a few hundred qubits. The sensitivity of qubits to external noise, such as temperature or magnetic field fluctuations, means that current quantum computers cannot run programs long enough to solve complex problems.
Quantum computers have the potential to solve problems across various fields.
Despite these challenges, William Oliver, director of the Quantum Engineering Center at MIT, believes that current quantum computers are not useless. These machines are still being used for experimentation, learning how to build larger quantum computers, and developing new algorithms to leverage quantum computing in the future.
Although still in the development stage, quantum computers have the potential to solve problems in many fields. One significant application is simulating complex physical systems in chemistry and materials science, where quantum phenomena play a crucial role. The ability to simulate quantum systems could help scientists achieve breakthroughs in the development of batteries, superconductors, catalysts, and pharmaceuticals.
Additionally, quantum computers could potentially break the current encryption methods of the internet. An algorithm developed by mathematician Peter Shor could crack RSA encryption – the security foundation for most online transactions. This raises concerns about cybersecurity, prompting many organizations to research and develop “post-quantum” encryption standards to protect data in the future.
However, so far, quantum optimization algorithms have only shown a small speed advantage.
Another exciting potential of quantum computing is its optimization capability, where quantum computers can find the best solutions among a range of possibilities. This opens up opportunities for optimization in fields such as transportation, logistics, and financial portfolio management. However, to date, quantum optimization algorithms have only shown a minor speed advantage, not yet reaching the exponential speed improvements over classical computers.
Quantum computers are also expected to advance progress in the field of machine learning; however, this poses a significant challenge due to the need to convert large amounts of data from classical to quantum forms, which can easily negate the computational performance advantages.
Quantum computers are also expected to advance progress in the field of machine learning.
According to experts like William Oliver and Norbert Lütkenhaus, quantum computing is still in its early stages and requires extensive research to fully understand how to develop quantum algorithms. Specifically, researchers must develop fundamental mathematical procedures, referred to as quantum “primitives”, to build more complex algorithms. The development of quantum computing heavily relies on the ability to discover new “primitives” and integrate them effectively to solve real-world problems.
Oliver emphasizes that companies should invest in research to promote advancements in quantum applications while simultaneously addressing fundamental design issues in quantum computers. Lütkenhaus agrees that specific problems are not the immediate priority. Instead, companies should focus on common challenges, paving the way for potential applications in the future.
