Formalizing Real-Valued Computable Functions

In summary, Li and Vitanyi's book on Kolmogorov complexity defines computable real-valued functions as those that can be computed by a Turing machine. This definition is extended to rational domains and ranges through a recursive bijection. They also introduce the concept of lower semicomputable functions, which are recursively approximable from below, and upper semicomputable functions, which are the negation of lower semicomputable functions. This definition is one approach to defining computability for real-valued functions, but there may be other definitions that could be more useful or accurate.
  • #1
kanima
7
0
Hi there, I'm currently reading Li and Vitanyi's book on Kolmogorov complexity. Unfortunately, I don't have a good background in computability/recursive function theory.

I have a question about their definition of a computable real-valued function. The authors first define recursive functions from the natural numbers to the natural numbers as those functions which are computable by a Turing machine. This definition is extended to rational domains and ranges by way of a recursive bijection [itex]\langle\cdot, \cdot\rangle : \mathbb{N} \times \mathbb{N} \to \mathbb{N}[/itex] by interpreting [itex]\langle p, q \rangle[/itex] as meaning [itex]p/q.[/itex]

Following a paper by http://www.mathnet.ru/php/archive.phtml?wshow=paper&jrnid=rm&paperid=5428&option_lang=eng", the authors define a lower semicomputable function as being a real-valued function which is recursively approximable from below.

More formally, a function [itex]f : \mathbb{Q} \to \mathbb{R}[/itex] is said to be lower semicomputable if there exists a partial recursive function [itex]\phi : \mathbb{Q} \times \mathbb{N} \to \mathbb{Q}[/itex] such that for all [itex]x,[/itex] [itex]\phi(x, k) \le \phi(x, k + 1)[/itex] and [itex]\lim_{k \to \infty} \phi(x, k) = f(x).[/itex]

Following this, [itex]f[/itex] is said to be upper semicomputable if [itex]-f[/itex] is lower semicomputable and computable if it is both upper and lower semicomputable (so it can be approximated to any desired degree of accuracy).

I'm just wondering how this definition compares to other formalizations of computability for real-valued functions. Is this a standard approach to defining computability?
 
Last edited by a moderator:
Physics news on Phys.org
  • #2
Are there any other definitions of computability for real-valued functions which might be more useful/accurate?
 

What is the definition of a formalized real-valued computable function?

A formalized real-valued computable function is a mathematical function that can be calculated by a computer using a finite sequence of precise, well-defined steps. It is a function that can be written in a formal language, such as a programming language, and can be executed by a computer to produce a result.

What is the importance of formalizing real-valued computable functions?

Formalizing real-valued computable functions is important because it allows us to precisely define and analyze mathematical functions that can be executed by a computer. This allows us to prove properties and theorems about these functions, as well as develop efficient algorithms for calculating them.

What is the difference between a formalized real-valued computable function and a regular mathematical function?

The main difference between a formalized real-valued computable function and a regular mathematical function is that a formalized function can be executed by a computer, while a regular mathematical function is typically just a conceptual representation. Formalized functions also have a precise, well-defined set of steps for calculation, while regular mathematical functions may be more abstract and open to interpretation.

What are some examples of formalized real-valued computable functions?

Some examples of formalized real-valued computable functions include addition, subtraction, multiplication, division, and exponentiation. These functions can be written in a formal language, such as a programming language, and executed by a computer to produce a result. Other examples include trigonometric functions, logarithms, and polynomials.

How can formalized real-valued computable functions be used in practical applications?

Formalized real-valued computable functions have a wide range of practical applications, such as in computer science, engineering, physics, and finance. They can be used to develop efficient algorithms for solving complex problems, simulate physical systems, and analyze data. They are also essential in the development of modern technology, such as artificial intelligence and machine learning.

Similar threads

Replies
2
Views
779
  • Math POTW for Graduate Students
Replies
1
Views
967
  • Programming and Computer Science
Replies
1
Views
1K
  • Set Theory, Logic, Probability, Statistics
Replies
1
Views
686
  • Set Theory, Logic, Probability, Statistics
Replies
5
Views
2K
  • Set Theory, Logic, Probability, Statistics
Replies
1
Views
1K
  • Set Theory, Logic, Probability, Statistics
Replies
28
Views
5K
  • Set Theory, Logic, Probability, Statistics
Replies
1
Views
2K
Replies
14
Views
3K
  • Set Theory, Logic, Probability, Statistics
Replies
5
Views
2K
Back
Top