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Complexity Classes P & NP Video Lecture | Theory of Computation - Computer Science Engineering (CSE)
FAQs on Complexity Classes P & NP Video Lecture - Theory of Computation - Computer Science Engineering (CSE)
| 1. What is the complexity class P? |  |
Ans. The complexity class P consists of all decision problems that can be solved by a deterministic Turing machine in polynomial time. In other words, it includes problems for which there exists an algorithm that can solve them efficiently.
| 2. What is the complexity class NP? | |
Ans. The complexity class NP (nondeterministic polynomial time) consists of all decision problems for which a solution can be verified by a deterministic Turing machine in polynomial time. It includes problems that can be solved in polynomial time by a nondeterministic Turing machine, but not necessarily by a deterministic one.
| 3. What is the difference between the complexity classes P and NP? | |
Ans. The main difference between the complexity classes P and NP is that P represents problems that can be solved efficiently by a deterministic Turing machine in polynomial time, while NP represents problems for which a solution can be verified efficiently in polynomial time, but not necessarily solved by a deterministic machine in polynomial time.
| 4. Are all problems in P also in NP? | |
Ans. Yes, all problems in P are also in NP. This is because if a problem can be solved efficiently by a deterministic Turing machine in polynomial time, then its solution can also be verified efficiently by a deterministic Turing machine in polynomial time.
| 5. Is P equal to NP? | |
Ans. The question of whether P is equal to NP is one of the biggest open problems in computer science. It asks whether every problem for which a solution can be verified efficiently can also be solved efficiently. So far, no one has been able to prove whether P is equal to NP or not, and it remains an unsolved problem.
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