# Computational complexity and statistical physics

• ## What is computational complexity and why do we need to study it?

Computational complexity theory is a mathematical research area in which the goal is to quantify the resources required to solve computational problems.
It is concerned with algorithms, which are computational methods for solving problems..

• ## What is meant by computational complexity?

In computer science, the computational complexity or simply complexity of an algorithm is the amount of resources required to run it.
Particular focus is given to computation time (generally measured by the number of needed elementary operations) and memory storage requirements..

• ## What is the theory of complexity in physics?

The concept of complexity has its origins in quantum information science, an area developed within the framework of quantum mechanics.
The general idea behind complexity is to quantify how difficult it is to reach a certain quantum state starting from another one..

• ## What subject is computational complexity?

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?.

• ## Why do we study computational physics?

Computational physics is the study of scientific problems using computational methods; it combines computer science, physics and applied mathematics to develop scientific solutions to complex problems.
Computational physics complements the areas of theory and experimentation in traditional scientific investigation..

• ## Why is computational complexity an essential topic in algorithm development?

Computer scientists use mathematical measures of complexity that allow them to predict, before writing the code, how fast an algorithm will run and how much memory it will require.
Such predictions are important guides for programmers implementing and selecting algorithms for real-world applications..

• Areas in the scope of computational physics include: large-scale quantum mechanical calculations in nuclear, atomic, molecular and condensed matter physics. large-scale calculations in fields like hydrodynamics, astrophysics, plasma physics, meteorology and geophysics.
• Automata-based computational complexity☆
The theory must go beyond the notion of computability and include some measure of the difficulty of the computation and how the difficulty is related to the organization of the machine that performs the computation.
• 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?
• Theoretical and computational physics provide the vision and the mathematical and computational framework for understanding and extending the knowledge of particles, forces, space-time, and the universe.
Dec 15, 2005Computational Complexity and Statistical Physics will serve as a standard reference and pedagogical aid to statistical physics methods in
Computer science and physics have been closely linked since the birth of modern computing. In recent years, an interdisciplinary area has blossomed at the junction of these fields, connecting insights from statistical physics with basic Google BooksOriginally published: 2006

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