Classical computing has limitations because of the binary nature of the underlying system used to store and manipulate data, i.e., 0 and 1. Quantum computing can remove these limitations due to the fuzzy nature of the underlying quantum physics. In quantum theory, particles, such as electrons, can exist in multiple states at once: these are called quantum states. These quantum states can also be superimposed (known as ‘superposition’).
Superposition and multiple states are the principles behind quantum computing. The binary off/on (0/1) system of classical computing is replaced by the infinitely more expansive superposition states of the quantum computer. The quantum computing basic unit of memory is called a “quantum bit” or qubit. This increased number of states gives quantum computing its processing power: for each additional qubit, the power of a quantum computer doubles.
In physics, a phenomenon called ‘quantum entanglement’ is the basis of linking (associating) qubits together; in doing so, a qubit can represent different things simultaneously. The result is a mathematical power effect: two linked qubits perform 2 to the power of 2 (22); three linked qubits 23, and so on. The more qubits a quantum computer has, the more powerful it is. Consequently, 300 entangled qubits could be used to represent more numbers than there are atoms in the universe.
What is quantum supremacy?
Quantum supremacy, or alternatively, quantum primacy, is the number of qubits required to overtake the power of classical computing. In 2019, Google claimed quantum supremacy when it built a quantum computer with 53-qubits and named it ‘Sycamore.’ But in 2021, IBM made headlines with Eagle, a 127-qubit quantum computer. The race for quantum supremacy continues.
A note on quantum supremacy as a term
A seminal blog post from IBM quantum researchers, “On Quantum Supremacy,” outlined the issues in performing a direct comparison between quantum and classical computers. In the post, the authors talk about Google’s quantum research and how to benchmark any ‘quantum leap’ in computing. They also point out the fallibility of using the term ‘supremacy,’ saying that “it should not be viewed as proof that quantum computers are “supreme” over classical computers.”
What is quantum computing used for?
The speed and processing power of quantum computing lends well to various applications, including cryptography, logistics, drug discovery, and banking. The industry is backed by groups such as the Quantum Consortium, which works to build opportunities for the industry. Investments in quantum computing tripled in 2020. IonQ became the industry's first publicly traded quantum company with a valuation of $2 billion.
Use cases that stand to be enhanced or changed by quantum computing include:
The current encryption standards that help us interact safely across the internet may be at risk from quantum computing. Quantum computers could be used to break existing cryptographic schemes such as AES 256. Quantum cryptography is an emerging area that is exploring new encryption methods that are hardened against quantum attacks. The National Institute of Standards and Technology (NIST) works on quantum-proof encryption.
Quantum computing is being used in fraud detection and portfolio analysis, and optimization. In 2022, PayPal and IBM partnered to use quantum computing to detect financial fraud. The Monte Carlo simulation is a test that looks for an outcome that has a range of possible variables. Quantum algorithms based on the Monte Carlo method are being applied to financial markets to increase the speed of financial calculations.
Computing has been used in drug discovery and design for several decades, but quantum computing is being heralded as a fast way to simulate the structure, properties, and behavior of candidate molecules faster and more accurately.
Traffic prediction and supply chain optimization are just two areas that can benefit from quantum computing. Route optimization is another logistics area benefiting from quantum computing: quantum computers can swiftly calculate the fastest route in even the most complex situations.