In this blog post, we’ll start with the uncertainty principle—a core principle of the microscopic world—and explore how qubits and quantum computers process information.
Interest in the “small world” is growing by the day. It’s been a long time since terms like “micro” and “nano” became familiar to us through science-related news. Various fields—including chemical and biological engineering, materials science, and mechanical engineering—are exploring the world at the nanoscale and, furthermore, at the atomic level. Electrical engineering is no exception. Due to the nature of the field, it focuses primarily on electrons, which carry a negative charge, and photons, which are particles of light. The branch of science that treats such tiny quanta as both particles and waves and interprets the results in terms of probability is called quantum mechanics. The uncertainty principle is a core principle of quantum mechanics. It is based on the idea that “the product of the uncertainty in position and the uncertainty in momentum is always greater than a certain constant.” No matter how precise the measuring device, the product of the uncertainty in position and the uncertainty in momentum is always greater than ℏ and can never be less than this value. Let Δx be the uncertainty in position and Δp be the uncertainty in momentum (which is the product of mass and velocity); then the following equation holds: Δx × Δp ≧ ℏ (ℏ = 1.055 × 10⁻³⁴ J·s).
To aid understanding, let’s consider the following example. Suppose we have a microscope capable of observing an electron. In order for us to see an electron, light must strike the electron and then reach our eyes. To accurately measure the position of the light, we must use light with a short wavelength; however, since a short wavelength corresponds to high energy, the error in momentum increases when the light strikes the electron. Conversely, to accurately measure the momentum of the light, we must use light with low energy; however, low energy results in a long wavelength, which in turn increases the error in position. It is impossible to measure both of these physical quantities with precision. This hypothetical measuring device, also known as the “Heisenberg microscope,” was frequently cited by Bohr to explain the uncertainty principle. The uncertainty principle is not observed in everyday life because, as can be seen from the equation, the product of the two uncertainties is extremely small—10⁻³⁴ J·s. For objects commonly seen in daily life—such as a moving car or a ball thrown by a pitcher—the position and momentum are so large that even a slight change in position or velocity is not visible to the naked eye. However, in fields dealing with the microscopic world, such as semiconductor manufacturing, the uncertainty principle is a critical consideration. “How much information can be stored within a limited space?” has always been a key question in the semiconductor industry. The quest to store terabytes (TB) of information within a space just a few square centimeters wide has led to a focus on a world even smaller than the micron or nanometer scale. In this context, the effects of the uncertainty principle could not be ignored.
When entering the sub-nanometer realm, transistors—which process bits (0s and 1s)—must also become correspondingly smaller; in this tiny world, however, the uncertainty of particles prevents 0s and 1s from being clearly distinguished. This leads to ambiguity in information. Semiconductor engineers are still grappling with the limitations of integrating such devices. Recently, other engineers have introduced the concept of a “qubit” and are researching ways to transmit large amounts of information more quickly. Since the bits used in conventional computers represent only the difference between whether an electric current is flowing or not, they have only two possible states: 0 and 1. However, qubits take advantage of the fact that, due to positional uncertainty, a particle can exist in both the 0 and 1 states simultaneously.
This is described as the particle being in a state of “superposition.” By utilizing quantum superposition, quantum computers can perform larger and faster calculations than conventional computers, which process information using only 0s and 1s. While bits reach their limit as they approach atomic scale—at which point the distinction between 0 and 1 becomes unclear—qubits operate in the opposite manner.
A quantum computer is a new type of computer that uses these qubits as its basic unit of information. Its computational power is immense. If a quantum computer with a processing capacity of 32 qubits existed, it would reportedly be capable of performing approximately 4 billion different operations simultaneously. Assuming each operation takes one second, the time required for a conventional computer to perform 4 billion operations would be 4 billion seconds—approximately 100 years. However, a 32-qubit quantum computer could perform the same operations in just one second. Yet, there are many hurdles to overcome before they can be used in the real world. The biggest problem is “quantum coherence.” For quantum properties—such as the uncertainty principle—to manifest properly, particles must be in a “pure state,” which is referred to as quantum coherence. The higher the level of coherence, the fewer disturbances there are, allowing for more accurate computations; however, achieving this is no easy task. Currently, many engineers are researching methods to create and maintain coherence. If a few more issues like this can be resolved, the day when we use quantum computers will come before long.
