Description: NISQ, which stands for ‘Noisy Intermediate-Scale Quantum’, refers to a class of quantum computers that are capable of performing quantum calculations but have not yet achieved full fault tolerance. These machines operate with an intermediate number of qubits, typically between 50 and 1000, and are subject to significant errors due to decoherence and quantum noise. Unlike fully functional quantum computers, which are expected to perform complex calculations reliably, NISQ devices are more limited in their processing capabilities. However, their development is crucial as they represent an intermediate step towards scalable and practical quantum computing. NISQ devices are particularly relevant in the current context of quantum research, where algorithms and applications are being explored that can leverage their capabilities despite inherent limitations. In this sense, NISQ computers are seen as valuable tools for research and the development of new quantum technologies, as well as for exploring problems that are difficult or impossible to solve with classical computers.
History: The term NISQ was introduced in 2018 by John Preskill, a theoretical physicist in quantum computing, in a paper discussing the future of quantum computing and its potential to solve problems that classical computers could not. Since then, the concept has gained attention in the scientific and technological community, driving research into quantum algorithms that can be executed on these intermediate machines.
Uses: NISQ computers are primarily used in the research of quantum algorithms and in the simulation of quantum systems. They are valuable tools for exploring problems in quantum chemistry, optimization, and machine learning, where approaches that could be more efficient than classical methods can be tested.
Examples: An example of NISQ computer usage is the work done by IBM with its IBM Quantum platform, which allows researchers to run quantum algorithms on their NISQ devices. Another example is the use of NISQ in simulating complex molecules for drug development.
