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The Role of Quantum Computers in Future Society and Challenges to Overcome

This article explores the basic concepts of quantum computers, their advantages over classical computers, and their expected roles in the future. It also considers the necessity for Korea to prepare in advance for the era of quantum computing. This essay was written by the author when they were in their second year of high school.

Posted Updated
By Yunseo Kim
views 8 min read

For decades since the 1960s, the computational power of computers has increased exponentially. This development has been achieved by miniaturizing transistors, components inside computer processors, to integrate more of them into the same area. As a striking example of the rapid progress in computer performance, the latest smartphones we use today outperform the most powerful supercomputers of the 1990s. Given that it’s virtually impossible to find a field that doesn’t use computers today, computer performance is a crucial factor determining the overall pace of technological advancement in modern society. However, the problem is that as individual transistors become extremely small, this method of improving computer processing power is now reaching its physical limits. This is why scientists are focusing on quantum computers. In this article, we will discuss the characteristics of quantum computers, their advantages over existing computers, their expected roles in future society, and the challenges that need to be addressed to realize these roles.

A quantum computer is a computer that processes data using quantum mechanical phenomena such as entanglement and superposition, a concept first proposed by American theoretical physicist Richard Feynman in 1982. The unique characteristic of quantum computers is that they read information in units of qubits (quantum bits). Unlike bits used by conventional computers, which have a single value of either 0 or 1, qubits can have values of both 0 and 1 simultaneously using the quantum superposition phenomenon. Therefore, when using n qubits, the number of possible states that can be represented at once is theoretically 2^n, and thanks to this characteristic of qubits, quantum computers can effectively perform parallel data processing.

Before discussing the potential applications of quantum computers in future society, it’s important to note that because quantum computers operate on entirely different principles from existing computers, even when commercialized, they will differ from what people commonly imagine. The fundamental difference between quantum computers and existing computers is not simply the number of possibilities created by qubits. The most important feature that distinguishes quantum computers from existing computers is that quantum computers process operations non-deterministically. To understand what this means, we need to know the concepts of deterministic Turing machines and non-deterministic Turing machines.

First, a deterministic Turing machine is a machine that processes a given set of instructions one at a time sequentially. Common computers we use today fall into this category. Easy problems that a deterministic Turing machine can solve in polynomial time are called P problems, such as sorting problems. On the other hand, a non-deterministic Turing machine is a machine that can calculate multiple answers to a problem simultaneously, that is, a machine that finds the optimal solution among numerous possibilities. For example, in an optimal path finding problem, when there are numerous paths from A to B, a non-deterministic Turing machine simultaneously simulates all paths to the destination and presents the path that arrives fastest as the optimal path. Problems that a non-deterministic Turing machine can solve in polynomial time are called NP problems. NP problems are complex problems that need to consider various causes and factors while lacking standardized solutions that can be applied like formulas. Examples include optimal path finding, integer factorization, discrete logarithms, analysis of complex systems such as fluids, and natural language processing.

Now you should understand what it means when we say that quantum computers process operations non-deterministically. When a conventional computer, a deterministic Turing machine that can only calculate one path at a time, tries to solve an NP problem, the time taken increases exponentially as the complexity of the problem increases. However, for a quantum computer, which is a non-deterministic Turing machine, the time increases only arithmetically even as the problem complexity increases. This is why people say that quantum computers can perform calculations that existing computers cannot. In particular, integer factorization and discrete logarithm problems are important parts of public key cryptography algorithms, which is why discussions about encryption always come up whenever quantum computers are mentioned. However, this doesn’t mean that quantum computers are omnipotent and superior to existing computers in all aspects. Rather, it would be more accurate to understand that existing computers and quantum computers are good at different things. While quantum computers can certainly demonstrate very powerful capabilities in certain areas, they may perform poorly depending on the type of operation. In other words, even if quantum computers are commercialized, existing computers will still be needed. Existing computers will continue to be used for deterministic calculation tasks, while quantum computers will excel in solving complex problems that are difficult for existing computers to handle. Quantum computers and existing computers are not in a competitive relationship, but rather in a complementary one.

Keeping this in mind, let’s look at what quantum computers might be able to do in the future. The areas where quantum computers are most likely to excel in the future are undoubtedly nanotechnology and data analysis. First, in the case of nanotechnology, quantum computers can demonstrate tremendous ability in analyzing the microscopic motion of particles. In fact, Richard Feynman first proposed the concept of quantum computers in a paper arguing that a computer based on the Schrödinger equation was needed to analyze the motion of the microscopic world. Today’s computers take a long time and are not sufficiently accurate in predicting the structure of large molecules like proteins or complex biochemical reaction processes. This is why drug development cannot rely solely on computer simulations and must always go through several stages of animal testing and clinical trials. However, using quantum computers, we can predict biochemical reaction processes where numerous factors interact, quickly and accurately analyze various molecular structures, and use the results to accelerate new drug or new material development while reducing side effects. The main reason it takes a long time to develop new drugs is because of clinical trials, but with quantum computers, we could dramatically shorten the time to develop new drugs in response to new diseases like COVID-19 to just a few weeks by simplifying the clinical trial stage based on highly reliable simulations.

Quantum computers can also be useful in big data analysis. Through quantum superposition, quantum computers can quickly and accurately analyze complex and vast data where various elements interact. Thanks to this characteristic, more accurate weather forecasts than now will be possible by tracking the flow of the atmosphere and the movement of clouds, and they can play a key role in autonomous driving by identifying the movement of vehicles on the road in real-time and finding optimal routes.

However, to utilize quantum computers in industry like this, several challenges need to be addressed. First, we need to find ways to stably implement and maintain qubits, as well as quantum error correction methods. Qubits easily collapse with small environmental changes, so controlling them stably is a big challenge in commercializing quantum computers. Also, current quantum computers have a problem of somewhat lower computational accuracy due to quantum errors, so we need to find ways to correct these errors. Various methods such as ion traps, superconducting loops, and topological qubits are being researched for qubit implementation, each with its own advantages and disadvantages. At the same time, there is a need to train professionals who can write quantum algorithms and maintain, repair, and operate quantum computers. Existing software cannot run on quantum computers, so completely new types of software suitable for quantum computers will be needed.

Although AI started to receive full-fledged attention from the 2010s, technologies like perceptrons that form the basis of today’s AI have been researched for decades. To be competitive when quantum computers receive attention like today’s AI in the future, we need to prepare in advance from now. According to Professor Lee Jun-koo of the School of Electrical and Electronic Engineering at KAIST (Korea Advanced Institute of Science and Technology), Korea’s quantum computer technology is currently 5-10 years behind other advanced countries. Before the gap widens further and becomes irreversible, we need to establish related policies with a long-term perspective, increase investment scale, and strive to secure software-related intellectual property rights while conducting quantum computer demonstration research through consistent and steady government support. This will require sufficient information exchange and smooth cooperation between industry, basic science researchers, and government policy makers.

References

Engineering Physics, Quantum Computing
Quantum Computing
This post is licensed under CC BY-NC 4.0 by the author.

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