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Quantum computers are the most advanced form of computing technology. They have the potential to revolutionise the way we process large amounts of data, as well as solve complex problems that traditional, ‘classical’ computers cannot. But what is a quantum computer?
How does a quantum computer work?
At its core, a quantum computer uses the principles of quantum mechanics – the study of how particles behave at the subatomic level – to crunch numbers and solve problems. Unlike traditional computers, which use binary bits (ones and zeros) to aid in the storage and computation of data, quantum machines use quantum bits, known in shorthand as‘qubits.’
Qubits are different from traditional bits because they can exist in multiple states at the same time. This allows them to process and store more data than a traditional computer in the same amount of time. For example, a single qubit can store two numbers at the same time, while two qubits can store four numbers and three qubits can store six numbers.
To take advantage of this phenomenon, quantum computers use a process called quantum entanglement. This is where two qubits become linked and their states become intertwined, which allows them to work together to perform calculations. This means that a quantum computer can operate much faster than a traditional one.
Are quantum computers more efficient than classical computers?
Quantum computers are also powerful because they can compute algorithms that would take traditional computers much longer to solve. For example, quantum computers are the most practical vehicle for cracking the codes used in cryptography using Shor’s Algorithm – a mathematical formula that would take a conventional computer 2,000 CPU years to solve.
As such, quantum computers offer immense potential for the future of computing. They could revolutionise the way we process data, allowing us to solve complex problems in a fraction of the time.
When would you use a quantum computer?
Quantum computers could be used for a wide variety of applications. This includes the development of new artificial intelligence programs, where researchers predict that quantum computers could be used to create new and more powerful machine learning algorithms, capable of accurately analysing millions, if not billions, of data points at significantly faster speeds than their classically built cousins.
Pharmaceutical research is another promising growth area. Industry giants often spend tens of millions of dollars in the search for new medicines using classical computers only capable of analysing molecules of a particular size. The leap in processing power offered by a quantum computer, however, would allow pharma companies to significantly reduce the time and cost involved in developing medications.
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Quantum computers could also be used to break conventional encryption standards. As such, international standards-setting bodies such as the US National Institute of Standards and Technology have inaugurated new methods of encryption capable of resisting the immense processing power offered by quantum computers.
How long before we see quantum computers everywhere?
While quantum computers themselves have been around since 1998, up until now researchers have struggled to harness the processing power of anything more than a handful of qubits. This has, consequently, limited the number of practical applications they can be used for at present, and prompted concerns among some that the sector’s potential is being overhyped.
Nevertheless, recent years have seen qubit numbers rise – and with this, the emergence of the first niche applications for quantum computers. These include topological data analysis, financial modelling and the development of new lighting technologies. While it remains unclear as to when quantum computers capable of discovering new medicines or breaking conventional encryption methods will be built, these early applications demonstrate the vast, untapped potential of these exotic and powerful machines.
The author generated this text in part with GPT-3, OpenAI’s large-scale language-generation model. Upon generating draft language, the author reviewed, edited, and revised the language to their own liking and takes ultimate responsibility for the content of this publication.
