Abstract
In the contemporary era we dwell in, every now and then, new technologies are developed by master brains such as researchers and scientists. This also paves the way to discover replacements to classical computers. One such progression among the great inventions is the essence of quantum computing. They are brought to light for the purpose of solving problems and scenarios solved by classical computers but in a more effective way and in the least span of time. The study of quantum computing focuses on finding new ways to compute by using quantum physics phenomena. A qubit, in contrast to a typical computer bit, can be either 0 or 1, or it can be a superposition of both 0 and 1. Quantum theory commemorates with automata theory, thereby formulating quantum finite automata. Quantum finite automaton, or basically a deterministic finite automaton, is one of the simplest models of computation, which is an input-driven model, which takes an input, and according to the input, we just read the machine, and it changes its state. This proves that any quantum finite automata are completely capable of recognizing languages like Tally with given cut point too. Such languages recognized by a cut point, by quantum finite automata, are called stochastic languages. It further collaborates with the chemical industry with its qubit power over molecular collide, interactive models, and collaborative string processing using nonregular languages.
| Original language | English |
|---|---|
| Title of host publication | Quantum Computing and Artificial Intelligence |
| Subtitle of host publication | Training Machine and Deep Learning Algorithms on Quantum Computers |
| Publisher | de Gruyter |
| Pages | 147-161 |
| Number of pages | 15 |
| ISBN (Electronic) | 9783110791402 |
| ISBN (Print) | 9783110791259 |
| DOIs | |
| Publication status | Published - 21-08-2023 |
All Science Journal Classification (ASJC) codes
- General Computer Science
- General Economics,Econometrics and Finance
- General Business,Management and Accounting