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Quantum computers, once fully scaled, could lead to breakthroughs on many fronts — medicine, finance, architecture, logistics.
First, it’s important to understand why quantum computers are superior to the conventional ones we’ve been using for years:
In conventional electronic devices, memory consists of bits with only one value, either 0 or 1. In quantum computing, a quantum bit (qubit) exhibits both values in varying degrees at the same time. This is called quantum superposition. These ubiquitous states of each qubit are then used in complex calculations, which read like regular bits: 0 and 1.
Since qubits can store more information than regular bits, this also means quantum computers are capable of processing greater quantities of information. Having four bits enables 16 possibilities, but only one at a time. Four qubits in quantum superposition, however, let you calculate all 16 states at once. This means that four qubits equal 65,500 regular bits. Each qubit added to the quantum computing system increases its power exponentially.
To put things in perspective, a top supercomputer can currently accomplish as much as a five- to 20-qubit computer, but it’s estimated that a 50-qubit quantum computer will be able to solve computational problems no other conventional device can in any feasible amount of time.
This “quantum supremacy” has been achieved many times so far. It’s important to mention that this doesn’t mean the quantum computer can beat a traditional one in every task — rather, it shines only in a limited set of tasks specially tailored to outline its strengths. Also, a quantum computer still needs to overcome many obstacles before it can become a mainstream device.
But once it does, its computational power will boost science and industries that profit from it.
Large companies working on quantum computing in their respective industries include AT&T
Google holding company Alphabet
Here are a few industries that could benefit the most:
Quantum chemistry, also called molecular quantum mechanics, is a branch of chemistry focused on the application of quantum mechanics to chemical systems. Here, quantum computers help in molecule modeling, taking into account all of their possible quantum states — a feat that is beyond the power of conventional computing.
That, in turn, helps us understand their properties, which is invaluable for new material and medicine research.
Quantum cryptography, also known as quantum encryption, employs principles of quantum mechanics to facilitate encryption and protection of encrypted data from tampering. Using the peculiar behavior of subatomic particles, it enables the reliable detection of tampering or eavesdropping (via the Quantum Key Distribution method).
Quantum encryption is also used for secure encryption key transfer, which is based on the entanglement principle. Both methods are currently available, but due to their complexity and price, only governments and institutions handling delicate data (most notably in China and the U.S.) can afford them for the time being.
Quantum finance is an interdisciplinary research field that applies theories and methods developed by quantum physicists and economists to solve problems in finance. This especially includes complex calculations, such as the pricing of various financial instruments and other computational finance problems.
Some scientists argue that quantum pricing models will provide more accuracy than classical ones because they’re able to take into account market inefficiency, which is something classical models disregard.
Quantum computing will also enhance analysis of large and unstructured data sets, which will improve decision making across different areas — from better-timed offers to risk assessment. Many of these calculations will require a quantum computer with thousands of qubits to resolve, but the way things have been progressing recently, it’s not unrealistic to see quantum computers reach this processing potential in a matter of years, rather than decades.
Quantum artificial intelligence
Although still in the domain of conceptual research, principles of quantum mechanics will help quantum computers achieve a markedly greater speed and efficiency than what is currently possible on classical computers when executing AI algorithms — this goes especially for machine learning.
Current computational models used in weather forecasting employ dynamic variables, from air temperature, pressure and density to historic data and other factors that go into creating climate prediction models. Due to limited available processing power, classical computers and even conventional supercomputers are the bottlenecks that limit the speed and efficacy of forecasting calculations.
To predict extreme weather events and limit the loss of life and property, we need faster and more robust forecasting models. By harnessing the power of qubits, quantum computing is capable of providing necessary the raw processing power to make that happen. Furthermore, machine learning provided by the quantum AI can additionally improve these forecasting models.
Despite its rapid progress, quantum computing is still in its infancy, but it’s clearly a game changer, capable of solving problems previously deemed insurmountable for classical computers.
This power will provide most benefits not only to science and medicine, but also to businesses and industries where fast processing of large datasets is paramount.
As a marketing specialist, I can see a huge advantage for my industry, but others, especially finance and cryptography, will undoubtedly find the quantum boost to their decision-making processes and quality of their final product hugely beneficial.
The real question is who will be the first to harness this power and use quantum computing as a part of their unique value proposition and competitive advantage? The race is on.