Today, many people are familiar with the term “quantum computing”. But what is it exactly? How is it different from classical computing, and how can it be used to solve certain problems more efficiently? In this article, we’ll answer these questions and more by looking at the history of quantum computing, its role in modern technology, its applications, its risks, and much more.
What is quantum computing?
Quantum computing is a branch of mathematics that aims to create computers based on the laws of quantum physics. The term “quantum computing” was coined in the early 2000s by researchers at the University of California, Berkeley. The idea is to build a computer using qubits — the mathematical state that can exist in two states at the same time — as the basic building blocks. The idea is to use computers to solve calculations that would take classical computer millions of times longer to perform.
What problems can be solved with quantum computing?
Quantum computers can perform complex mathematical calculations that would take classical computers millions of times longer to perform. They can also be used to solve problems that would take regular computers years or even decades to solve. These are some of the hardest problems facing modern technology:
– Decryption of encryption algorithms
– Decimator synthesis
– Identifying patterns in large amounts of data
– Recognizing voiceprints
– Numerical analysis
– Image/video signal processing
– AI and AR/VR
– Game theory
– Predictive analysis
– Deep learning
– IoT
– Blockchain
– Global trade simulation
– Face detection
– 3D facial mapping
– Neuro-imaging
– Document analysis
– Genome sequencing
– Cloning
– Material testing
– Genome analytics
– Prosthetics
– Nanotechnology
– Solar panels
– Windmills
– Stocks/ETFs
– Forecasting
– Food safety
– Aviation
How Quantum Computers Work
The modern quantum computer uses a quantum device to solve difficult mathematical problems. The most famous one is the entanglement machine, which was invented in the 1950s. It uses two spectroscopic devices, one that measures vibrations and another that measures the momentum of the waves, to create a 3D map of the quantum device.
The map reveals the state of each qubit, which is the basic building block of a computer. A quantum computer is a highly complex device that works on a scale that is much smaller than the typical desktop computer. It uses quantum technology to solve complex problems that would take conventional computers hundreds of thousands of times longer to solve.
The Heart of a Quantum Computer
At the heart of a quantum computer is a quantum device. Unlike a regular computer, which has a central processing unit (CPU) and an associated memory, a quantum computer has no physical location — it is a quantum system. The qubits, which make up most of a quantum computer, are the most valuable real estate in the device.
The qubits can be in two states at the same time, which is what allows them to perform complex mathematical functions such as cracking encryption algorithms or creating new molecules. This makes the qubits extremely difficult to solve and verify, making them ideal for cryptography.
How Big Is a Quantum Computer?
The size of a quantum computer can’t be determined exactly because it depends on the size of the problem and the computer model used to solve it. A large-scale implementation would have many, if not most, of the benefits of a quantum computer but much larger computer model requirements. Using a quantum computer to solve advanced physics problems would require a very large computer — one that is much larger than a conventional computer.
The largest computer in the world, the World Data Center in Taos, New Mexico, has a computer model that is 2.2 times larger than the largest computer in the U.S. that can be used for specialized functions, including quantum computing.
Risks of Using a Quantum Computer
The most significant risk of using a quantum computer is that of communication transmission. Once the information is in the system, it is extremely difficult to extract without any loss of information. This security depends on the robustness of the hardware and the software that runs on the computer. A less significant risk is that of the hardware itself.
A hardware design that is not reliable or error-prone will result in a substandard computer. Bad hardware can result in sub-optimal performance, incorrect answers, and security breaches. An example of hardware failure is a faulty thermal shutdown that can shut down the computer during a calculation. Bad software can result in incorrect answers, incorrect models of reality, and unproven claims. Bad communication results in unreliable data and erroneous claims.
Key Takeaways
- The concept of a quantum computer dates back decades and was first proposed in the 1950s. It is based on using two optical devices — one that measures vibrations and another that measures the momentum of the waves — to create a 3D map of the quantum device.
- The largest computer in the world is the World Data Center in Taos, New Mexico, with a computer model that is 2.2 times larger than the largest computer in the U.S.
- A robust computer that can communicate securely and precisely with other computers is a key factor in the success of a quantum computer. A poor design can result in sub-optimal performance, incorrect answers, and security breaches.
- The greatest risk of using a quantum computer is that of communication transmission — once the information is in the system, it is extremely difficult to extract without any loss of information. This security depends on the robustness of the hardware and the software that runs on the computer.
- A key advantage of a quantum computer is the ability to solve very difficult problems that would take conventional computers millions of times longer to solve. These include encryption and material identification.
- Because a quantum computer is much more powerful than a conventional computer, it has the potential to be used for many more tasks, including building a quantum computer that can solve the most complex problems in AI and computer vision.