Quantum computation utilizes quantum mechanical effects such as superposition, entanglement, and interference to perform computation. Classical computation relies on the ability to store and manipulate binary integers (bits) generally made from silicon transistors. Instead, quantum computers make use of quantum bits (qubits) that can have the value 0, 1, or a superposition of these 2 states. Leveraging superposition and entanglement to create states that scale exponentially with the number of qubits offers the potential for dramatic improvements in computation power compared to classical computers.
A quantum mechanical model of a computer was first conceived by physicist Paul Benioff in 1980, inspired by an Alan Turing paper written in 1936. Richard Feynman, then a professor at Caltech, described how quantum computers could be used to simulate physical systems in a paper published in 1982, entitled "Simulating Physics with Computers". These ideas were developed by David Deutsch in 1985, describing the concept of a universal quantum computer to understand the mathematical potential that was possible. In 1994 Peter Shor developed “Shor’s algorithm” allowing a quantum computer to perform factorization of large numbers significantly faster than the best classical algorithms.
Development continued through the 90s and 2000s with significant contributions from scientists David Wineland, Christopher Monroe, and Lov Grover, companies and institutions such as the Technical University of Munich, Los Alamos National Laboratory, IBM, D-Wave, and Google. On October 23rd, 2019 researchers at Google published a paper claiming they had achieved quantum supremacy using the Sycamore quantum computer. Quantum supremacy refers to solving a problem that could not be solved by a classical computer in a reasonable amount of time. Although some disagreed whether Google had achieved true quantum supremacy it is seen as a significant breakthrough in quantum computation.
Current quantum computers struggle with errors in the form of noise and loss of quantum coherence as well as engineering challenges. However, they have found applications in fields such as cryptography and drug development.
A Qubit (quantum bit) is the quantum computing analog of a classical bit. Unlike classical bits (which have the value 0 or 1), qubits are two-level quantum systems that can have the value 0, 1, or a linear combination of both states caused by quantum superposition.
Quantum computing hardware requires qubits that can scale to the numbers required to demonstrate computing advantages compared to classical machines (>10,000 qubits). A number of qubit systems are under research for use as quantum computers. These include:
- Neutral atom qubits
- Superconducting qubits
- Quantum dot qubits (spin qubit quantum computing)
- Trapped ion qubits
- Photonic qubits (Linear optical quantum computing)
- Quantum machine learning
- Quantum Memory
- Quantum information
- Quantum photonics
- Integrated quantum photonics
Applications of quantum computing include:
- Drug development
- Financial Modeling
- Better Batteries
- Cleaner Fertilization
- Traffic Optimization
- Weather Forecasting and Climate Change
- Artificial Intelligence
- Solar Capture
- Electronic Materials Discovery
Quantum Computing Companies (Hardware and Software)
Quantum Computing Hardware Companies
Quantum Computing Software Companies
Creator Neven's Law
July 1, 2019
Simulating Physics with Computers
May 7, 1981