Quantum Computing Applications:  What Is Hot And Why?

Discover the hotest uses for quantum computing in today's market.
Zuber Lawler

As quantum computing technology develops and evolves, there is tremendous buzz and excitement about a whole new array of potential possibilities for new applications to be run on quantum computers.

Quantum computing, of course, is not the answer for all computer applications. The vast majority of computer applications run – and will continue to run – perfectly well on conventional computers. Indeed, conventional computers will likely remain the superior choice for most applications. Nonetheless, there are many potential applications that will require quantum computers to run effectively. Two key questions are (1) what are those applications and (2) what makes quantum computers essential for running those applications?

These questions can be answered by understanding how quantum computers differ from conventional computers and what quantum computers can do that conventional computers cannot. Conventional computers implement an algorithm by executing program steps using binary states, branching to a particular subroutine when a specific condition is met or looping through a series of steps until a specific condition is met. They do this well. Sometimes, however, an algorithm requires evaluation of all possible permutations involving a number of factors and identification of the permutation having the best result. If there are a small number of factors to be evaluated, conventional computers can do this well. However, as the number of factors increases, there comes a point where conventional computers cannot effectively evaluate all of the possible permutations to determine the best answer within a reasonable time, if at all. That is where quantum computers come into play because their non-binary qubits simultaneously represent multiple states, enabling this type of analysis to be completed in a reasonable time.

Many applications have been proposed as good candidates for commercial implementation using quantum computers. Three particularly interesting candidates are cybersecurity, modeling of chemical behavior and financial modeling.

Cybersecurity may be the most interesting application proposed for quantum computers because of the interplay of technical, commercial and societal considerations. Cybersecurity is critically important today, as is evidenced by its continual high profile in the press. It has tremendous potential commercial significance as a quantum computing application. At bottom, breaking encryption algorithms involves evaluation of a large number of possibilities to determine how data has been encrypted – and how to decrypt the encrypted data to recover the underlying, unencrypted data. The required decryption algorithm may be beyond the capability of conventional computers, but could well be implemented using quantum computers. As quantum computers find their way into this application, a “cat and mouse” game will likely result, with quantum computers on the one hand becoming increasingly capable of breaking encryption, and on the other hand being increasingly used to create more robust encryption schemes to avoid being broken.

Political issues will likely arise from the impact of quantum computers on cybersecurity. It is plainly desirable for cybersecurity to protect business and government data from those who seek to steal secret information. In contrast, it is desirable for law enforcement to be able to circumvent encryption used by criminals and terrorists, particularly for those that seek to cause physical harm to innocent people. Between these polar extremes, it will be difficult to draw the line between what government access to private information is acceptable, and what access is not. As is invariably the case, technology evolves more quickly than the capacity to understand its implications and to respond to it politically, and quantum computing is no exception.

A second important application of quantum computing is modeling the chemical behavior of molecules.

Each atom and subatomic particle in a molecule affects each other atom and subatomic particle, not only within that molecule but also for any molecule that interacts with or is created from that molecule over time. It is necessary to understand fully what effects will result from these various interactions – both desirable and undesirable. For example, drug molecules typically include a relatively large number of atoms. Moreover, drug molecules often interact with complex protein molecules in a patient. Adding still further complication, these interactions are not static operations – drugs move within the body (for example, with blood flow) and change in concentration (for example, as a pill is digested). As these traveling drug molecules interact in varying concentrations with other molecules, they create new molecules having their own properties and effects. There is no way these interactions can be adequately modeled using conventional computers, leaving the determination of efficacy and adverse side effects almost entirely to a lengthy trial-and-error process of experimentation.

Another important application for quantum computing is financial modeling. The financial industry relies on predicting and evaluating things like arbitrage, risk assessment and hedging to maximize return on investment. Again, this involves analyzing a number of factors and identifying the permutation having the best result. As with cybersecurity and chemical modeling, there are a large number of factors and permutations, so conventional computers are unable to determine the best answer. Indeed, the number of potential permutations may be even greater for financial modeling because, unlike cryptography and chemistry – which are constrained respectively by laws of mathematics and science – financial modeling is subject to the vagaries of random human behavior and decision making.

These are but three of the more interesting, and commercially promising, applications of quantum computing. These applications – and other potential applications – may be fundamentally different from each other, but they all share a common need to evaluate a litany of permutations of data to arrive at an optimal solution. This requirement is, and will remain, beyond the capacity of conventional computers, but is in the exact sweet spot of quantum computers.

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