If you’re familiar with quantum physics, it may bring to mind physicist Erwin Schrödinger's thought experiment of a cat, trapped in a box with poison, that is neither alive nor dead. Or, you might think of physicist Eugene Wigner's extrapolation of that experiment with quantum phenomena: a human friend closed in a lab, measuring a quantum system and living in a state of superposition.^{1} Although these concepts may seem to be the beginnings of the most brilliant theoretical physicists and purveyors of “quantum woo,” they’ve recently found more practical quantum computing applications in computer science.^{2}

Here, we'll take a closer look at the basics of quantum computing, including quantum theory, quantum entanglement, quantum bits, and the ongoing evolution of quantum computers.

## Quantum Mechanics Primer

Quantum computing uses the properties of quantum mechanics to process information in ways that classical computers can’t. It differs from classical computing in terms of the basic units of information and how they operate. The elements of quantum computing include the following:

### Quantum Bits (Qubits) and Superposition

In classical computing, the smallest unit of data is the bit, which can be either a 0 or a 1. In quantum computing, the fundamental unit is the qubit. Qubits can exist in a state of 0, 1, or any superposition of these states. This means a qubit can be both 0 and 1 simultaneously, a property that allows quantum computers to process a vast amount of data much more efficiently than classical computers.^{3}

This principle is what allows a qubit to be in multiple states at once. It's akin to spinning a coin; while it’s in the air, the coin is in a superposition of states of heads and tails. Only when it lands—or is measured, in the case of a qubit—does it assume a definite state. This superposition enables quantum computers to perform many calculations and produce more efficient algorithms all at once.^{4}

### Quantum Entanglement and Quantum States

Another key principle of quantum computing is entanglement, a strong correlation that exists between quantum particles. When two qubits are entangled, the state of one qubit is directly related to the state of another, no matter the distance between them. This property is used in quantum computing to link qubits in a way that amplifies quantum computing speed and power exponentially as more qubits are entangled.^{5}

### Quantum Gates and Circuits

In classical computing, logical operations are performed using logic gates. Quantum computing also uses gates, but these quantum gates manipulate an operation on a qubit or a set of qubits. These operations are reversible, which is a fundamental requirement in quantum computation. Quantum circuits are sequences of these gates, which are fundamental in designing algorithms for quantum computers.^{6}

## Quantum Computing Use Cases

Although you’re not likely to be carrying around a laptop quantum computer anytime soon, some promising applications of quantum computing may be on the horizon, depending on the progress of quantum computing advancements.

### Cryptography and Security

Quantum computers can potentially break many of the cryptographic systems currently in use. However, they also enable the development of new types of cryptographic systems, known as quantum cryptography. This field includes quantum key distribution, which offers a theoretically unbreakable encryption method, fundamentally changing the nature of data security.^{7}

### Optimization Problems

The Traveling Salesman Problem is a classic problem in optimization and supply chain logistics. It involves finding the shortest possible route through different cities and returning to the original city. With each additional city, the number of possible routes increases exponentially.

Because quantum computers work with qubits that can exist in several states simultaneously, they can evaluate multiple route options. This computational power allows quantum computers to solve optimization problems far faster and more efficiently than classical computers.^{8}

### Machine Learning

Quantum computing could significantly boost the field of AI and machine learning. Quantum computing algorithms can process and analyze large datasets much more efficiently than classical algorithms, potentially leading to new insights and advancements in machine learning models.^{9}

## Current State of Quantum Computing

In 2019, Google claimed its quantum computer outperformed the fastest state-of-the-art supercomputer by completing a calculation that would have taken the supercomputer 10,000 years in only three minutes and 20 seconds.^{10} As is often the case with over-hyped, futuristic tech, this accomplishment turned out to be quite a bit less impressive than originally touted.

However, it did signal that quantum computing research, a field still very much in its infancy, has the potential to transform computing—so much so that global consulting firm McKinsey & Co. has identified it as one of the next big trends in tech.^{11}

Google is currently claiming supremacy in the quantum computing race with a newer version of its quantum computer, Sycamore. But, Google isn't the only organization working on quantum computers and quantum computing hardware. IBM, Microsoft, Amazon, Intel, and other small startups are working on quantum computers, quantum computing hardware, and quantum algorithms, although it could easily be a decade or more before they're fully realized.^{12}

## Future Prospects and Implications

At this point, quantum computers are still a hopeful, distant probability. Google has laid out a six-step roadmap to building functioning quantum computers, including the following milestones:^{13}

- Beyond classical computer performance
- Logical qubit prototype
- One long-lived logical qubit
- Logical gate
- Scaled-up engineering
- Quantum computer that’s error-corrected

So far, Google has achieved the first two milestones on its roadmap. Yet it's important to note that even when there are functioning quantum computers, they won’t replace classical computers. Aside from the physical properties that make them difficult to use (e.g., size, amount of energy needed), classic computers are much more accessible, user friendly, and cost effective. Developing quantum algorithms is difficult, and they aren’t ideal for every problem. However, for complex problems that classical computers can’t handle, quantum computers will be a powerful tool.

- Retrieved on November 10, 2023, from scientificamerican.com/article/this-twist-on-schroedingers-cat-paradox-has-major-implications-for-quantum-theory/
- Retrieved on November 10, 2023, from alanjones.blog/p/the-rise-of-quantum-quackery
- Retrieved on November 10, 2023, from learn.microsoft.com/en-us/azure/quantum/concepts-the-qubit
- Retrieved on November 10, 2023, from builtin.com/software-engineering-perspectives/superposition
- Retrieved on November 10, 2023, from medium.com/@madali.nabil97/entanglement-and-its-role-in-quantum-computing-2cbb1ff74e77
- Retrieved on November 10, 2023, from towardsdatascience.com/demystifying-quantum-gates-one-qubit-at-a-time-54404ed80640
- Retrieved on November 10, 2023, from ibm.com/thought-leadership/institute-business-value/en-us/report/quantumsecurity
- Retrieved on November 10, 2023, from linkedin.com/pulse/using-quantum-computing-solve-travelling-salesman-problem-cammidge/
- Retrieved on November 10, 2023, from forbes.com/sites/sap/2023/03/21/if-you-think-ai-is-hot-wait-until-it-meets-quantum-computing/
- Retrieved on November 10, 2023, from science.org/content/article/ordinary-computers-can-beat-google-s-quantum-computer-after-all
- Retrieved on November 10, 2023, from mckinsey.com/capabilities/mckinsey-digital/our-insights/the-top-trends-in-tech
- Retrieved on November 10, 2023, from nextplatform.com/2023/07/18/google-gives-a-peek-at-what-a-quantum-computer-can-do
- Retrieved on November 10, 2023, from ai.google/static/documents/approach-quantum-computing.pdf