What Are the Implications of the P = NP Problem for Math and Science?

  • Thread starter Thread starter Jimmy84
  • Start date Start date
  • Tags Tags
    Science
Click For Summary

Discussion Overview

The discussion revolves around the P = NP problem, exploring its implications for mathematics and science. Participants express curiosity about the problem's significance and the fields of study necessary to understand it, touching on theoretical computer science and its applications.

Discussion Character

  • Exploratory
  • Technical explanation
  • Conceptual clarification

Main Points Raised

  • Some participants highlight that a proof of P = NP could lead to efficient solutions for NP-complete problems, impacting fields like operations research and biology.
  • Others note that a proof showing P ≠ NP would advance computational complexity theory and guide future research by clarifying which problems cannot be solved efficiently.
  • Several participants suggest that understanding the P vs NP problem requires knowledge of automata theory and complexity theory, often covered in fundamental computer science courses.
  • One participant recommends specific textbooks, such as Papadimitriou's "Computational Complexity" and Kleinberg & Tardos' "Algorithm Design," as resources for learning about the problem.
  • Another participant mentions Scott Aaronson's "Quantum Computing Since Democritus" series as a valuable introduction to complexity classes and their relevance to the P vs NP problem.

Areas of Agreement / Disagreement

Participants generally agree on the significance of the P = NP problem and the fields of study necessary to understand it, but there is no consensus on the implications of the problem or the best resources for learning about it.

Contextual Notes

Some participants express uncertainty about their knowledge of computer science and the specific areas they should focus on to understand the P vs NP problem better.

Jimmy84
Messages
190
Reaction score
0
I was reading about the P = NP problem, and it seems very interesting because it has deep implications for math and for all of science if proven true.


(Quote)
http://en.wikipedia.org/wiki/P_=_NP_problem#Consequences_of_proof"

One of the reasons the problem attracts so much attention is the consequences of the answer.

A proof of P = NP could have stunning practical consequences, if the proof leads to efficient methods for solving some of the important problems in NP. Various NP-complete problems are fundamental in many fields. There are enormous positive consequences that would follow from rendering tractable many currently mathematically intractable problems. For instance, many problems in operations research are NP-complete, such as some types of integer programming, and the traveling salesman problem, to name two of the most famous examples. Efficient solutions to these problems would have enormous implications for logistics. Many other important problems, such as some problems in Protein structure prediction are also NP-complete;[11] if these problems were efficiently solvable it could spur considerable advances in biology.

But such changes may pale in significance compared to the revolution an efficient method for solving NP-complete problems would cause in mathematics itself. According to Stephen Cook,[12]

...it would transform mathematics by allowing a computer to find a formal proof of any theorem which has a proof of a reasonable length, since formal proofs can easily be recognized in polynomial time. Example problems may well include all of the CMI prize problems.

Research mathematicians spend their careers trying to prove theorems, and some proofs have taken decades or even centuries to find after problems have been stated – for instance, Fermat's Last Theorem took over three centuries to prove. A method that is guaranteed to find proofs to theorems, should one exist of a "reasonable" size, would essentially end this struggle.

A proof that showed that P ≠ NP, while lacking the practical computational benefits of a proof that P = NP, would also represent a massive advance in computational complexity theory and provide guidance for future research. It would allow one to show in a formal way that many common problems cannot be solved efficiently, so that the attention of researchers can be focused on partial solutions or solutions to other problems. Due to widespread belief in P ≠ NP, much of this focusing of research has already taken place.
(EndQuote)

I don't know much about computer science, I was wondering which fields of computer science and mathematics do I have to learn in order to get aquainted with the problem? I by no means would attempt to solve it but I am very curious about it because of its vast implications.
 
Last edited by a moderator:
Technology news on Phys.org
Jimmy84 said:
I don't know much about computer science, I was wondering which fields of computer science and mathematics do I have to learn in order to get aquainted with the problem? I by no means would attempt to solve it but I am very curious about it because of its vast implications.

There are two particular branches of theoretical computer science you will need to understand in order to seriously think about the P vs NP problem. The first one is often called "automata theory". The second one is called "complexity theory". The first one will be often taught in a "fundamental computer science" class, although not all learning institutions offer these. Complexity theory can be taught as an extension of basic automata theory, however you will more often see it taught alone-- actually it will be covered in this way in any algorithms class (if you have ever encountered "Big O Notation", this is complexity theory).

If you want to really jump headfirst into this, I suggest Papadimitriou's "Computational Complexity" textbook, which really seems to be the gold standard on the subject.

If you want just an introduction to the subject, I cannot highly enough recommend Scott Aaronson's "Quantum Computing Since Democritus" series. Go to the site I linked there and look on the sidebar for that title, there are transcripts of about 20 lectures listed. The first half will be the ones that will mostly be of interest to you. This series is wide-ranging in subject and its ultimate goal is to introduce you to quantum computing (a subject which not only will be relatable to you if you have a physics background, but also actually does have interesting relevance to the P vs NP problem for several reasons) but on the way to his goal he gives a great, readable introduction to complexity classes and some relevant introduction to automata.
 
Jimmy84 said:
I don't know much about computer science, I was wondering which fields of computer science and mathematics do I have to learn in order to get aquainted with the problem? I by no means would attempt to solve it but I am very curious about it because of its vast implications.

This would typically be covered in "algorithms / analysis of algorithms." An example course textbook is Kleinberg & Tardos' "Algorithm Design."
 
Thanks a lot guys, I appreciate it.
 

Similar threads

Replies
52
Views
4K
  • · Replies 6 ·
Replies
6
Views
3K
Replies
4
Views
5K
  • · Replies 13 ·
Replies
13
Views
16K
  • · Replies 4 ·
Replies
4
Views
2K
  • · Replies 8 ·
Replies
8
Views
2K
  • · Replies 4 ·
Replies
4
Views
1K
  • · Replies 0 ·
Replies
0
Views
1K
  • · Replies 2 ·
Replies
2
Views
2K
  • · Replies 2 ·
Replies
2
Views
3K