Every few decades, the world witnesses technological revolutions that profoundly change our lives. This happened when we first invented computers, when we created the Internet and most recently when artificial intelligence (AI) emerged.
Today, experts frequently speculate that the next revolution will involve technologies grounded in the principles of quantum mechanics. One such technology is quantum computing. Harnessing the unique properties of quantum mechanics, quantum computers promise to achieve superior computational power, solving certain tasks that are beyond the reach of classical computers.
Quantum computers can potentially transform many sectors, from defense and finance to education, logistics and medicine. However, we are currently in a quantum age reminiscent of the pre-silicon era of classical computers. Back then, state-of-the-art computers like ENIAC ran on vacuum tubes, which were large, clunky, and required a lot of power. During the 1950s, experts investigated various platforms to develop the most efficient and effective computing systems. This journey eventually led to the widespread adoption of silicon semiconductors, which we still use today.
Similarly, todays quantum quest involves evaluating different potential platforms to produce what the industry commonly calls a fault-tolerant quantum computer quantum computers that are able to perform reliable operations despite the presence of errors in their hardware.
Tech giants, including Google and IBM, are adapting superconductors materials that have zero resistance to electrical current to build their quantum computers, claiming that they might be able to build a reasonably large quantum computer by 2030. Other companies and startups dedicated to quantum computing, such as QuEra, PsiQuantum and Alice & Bob, are experimenting with other platforms and even occasionally declaring that they might be able to build one before 2030.
Until the so-called fault-tolerant quantum computer is built, the industry needs to go through an era commonly referred to as the Noisy Intermedia-Scale Quantum (NISQ) era. NISQ quantum devices contain a few hundred quantum bits (qubits) and are typically prone to errors due to various quantum phenomena.
NISQ devices serve as early prototypes of fault-tolerant quantum computers and showcase their potential. However, they are not expected to clearly demonstrate practical advantages, such as solving large scale optimization problems or simulating sufficiently complex chemical molecules.
Researchers attribute the difficulty of building such devices to the significant amount of errors (or noise) NISQ devices suffer from. Nevertheless, this is not surprising. The basic computational units of quantum computers, the qubits, are highly sensitive quantum particles easily influenced by their environment. This is why one way to build a quantum computer is to cool these machines to near zero kelvin a temperature colder than outer space. This reduces the interaction between qubits and the surrounding environment, thus producing less noise.
Another approach is to accept that such levels of noise are inevitable and instead focus on mitigating, suppressing or correcting any errors produced by such noise. This constitutes a substantial area of research that must advance significantly if we are to facilitate the construction of fault-tolerant quantum computers.
As the construction of quantum devices progresses, research advances rapidly to explore potential applications, not just for future fault-tolerant computers, but also possibly for todays NISQ devices. Recent advances show promising results in specialized applications, such as optimization, artificial intelligence and simulation.
Many speculate that the first practical quantum computer may appear in the field of optimization. Theoretical demonstrations have shown that quantum computers will be capable of solving optimization problems more efficiently than classical computers. Performing optimization tasks efficiently could have a profound impact on a broad range of problems. This is especially the case where the search for an optimized solution would usually require an astronomical number of trials.
Examples of such optimization problems are almost countless and can be found in major sectors such as finance (portfolio optimization and credit risk analysis), logistics (route optimization and supply chain optimization) and aviation (flight gate optimization and flight path optimization).
AI is another field in which experts anticipate quantum computers will make significant advances. By leveraging quantum phenomena, such as superposition, entanglement and interference which have no counterparts in classical computing quantum computers may offer advantages in training and optimizing machine learning models.
However, we still do not have concrete evidence supporting such claimed advantages as this would necessitate larger quantum devices, which we do not have today. That said, early indications of these potential advantages are rapidly emerging within the research community.
Simulating quantum systems was the original application that motivated the idea of building quantum computers. Efficient simulations will likely drastically impact many essential applications, such as material science (finding new material with superior properties, like for better batteries) and drug discovery (development of new drugs by more accurately simulating quantum interactions between molecules).
Unfortunately, with the current NISQ devices, only simple molecules can be simulated. More complex molecules will need to wait for the advent of large fault-tolerant computers.
There is uncertainty surrounding the timeline and applications of quantum computers, but we should remember that the killer application for classical computers was not even remotely envisioned by their inventors. A killer application is the single application that contributed the most to the widespread use of a certain technology. For classical computers, the killer application, surprisingly, turned out to be spreadsheets.
For quantum computers, speculation often centers around simulation and optimization being the potential killer applications of this technology, but a definite winner is still far from certain. In fact, the quantum killer application may be something entirely unknown to us at this time and it may even arise from completely uncharted territories.
[Will Sherriff edited this piece.]
The views expressed in this article are the authors own and do not necessarily reflect Fair Observers editorial policy.
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