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How is computational complexity measured?

Posted on April 6, 2020 by Author

Table of Contents

  • 1 How is computational complexity measured?
  • 2 What is complexity theory in automata?
  • 3 What is computational complexity analysis?
  • 4 Which the the worst case occur in linear search algorithm?
  • 5 What is the BQP of a quantum computer?
  • 6 What is computational complexity theory?

How is computational complexity measured?

In some algorithms, the complexity can be measured by the time that the CPU needs to run the algorithm, others consider the computational complexity as the number of nested loops (for loops and others) per run and can be written as O(x), where x is your nested loops.

What is complexity theory in automata?

Complexity Theory aims to make general conclusions of the resource requirements of decidable problems (languages). Henceforth, we only consider decidable languages and deciders. Our computational model is a Turing Machine. Time: the number of computation steps a TM machine makes to decide on an input of size n.

What are different types of complexities that are considered?

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There are different types of time complexities, so let’s check the most basic ones.

  • Constant Time Complexity: O(1)
  • Linear Time Complexity: O(n)
  • Logarithmic Time Complexity: O(log n)
  • Quadratic Time Complexity: O(n²)
  • Exponential Time Complexity: O(2^n)

What is computational complexity analysis?

In computer science, the computational complexity or simply complexity of an algorithm is the amount of resources required to run it. The study of the complexity of explicitly given algorithms is called analysis of algorithms, while the study of the complexity of problems is called computational complexity theory.

Which the the worst case occur in linear search algorithm?

The worst case occurs in the Linear Search Algorithm when the item to be searched is in end of the Array.

What is a BQP-complete problem?

Similar to the notion of NP-completeness and other complete problems, we can define a BQP-complete problem as a problem that is in BQP and that every problem in BQP reduces to it in polynomial time. Here is an intuitive BQP-complete problem, which stems directly from the definition of BQP.

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What is the BQP of a quantum computer?

This class is defined for a quantum computer and its natural corresponding class for an ordinary computer (or a Turing machine plus a source of randomness) is BPP. Just like P and BPP, BQP is low for itself, which means BQP BQP = BQP. Informally, this is true because polynomial time algorithms are closed under composition.

What is computational complexity theory?

Computational complexity theory is a subfield of theoretical computer science one of whose primary goals is to classify and compare the practical difficulty of solving problems about finite combinatorial objects – e.g. given two natural numbers n and m, are they relatively prime?

What does BQP stand for?

In computational complexity theory, bounded-error quantum polynomial time ( BQP) is the class of decision problems solvable by a quantum computer in polynomial time, with an error probability of at most 1/3 for all instances. It is the quantum analogue to the complexity class BPP .

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