P≠NP: Simplicity of Exponential Functions

  • Thread starter Adel Makram
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In summary: Note that the number of steps required to solve a particular problem in a particular class is always an integer. It is never transcendental.In summary, we discussed the relationship between exponential functions and polynomial algebraic forms, and how this relates to the question P=NP. We learned that P is the class of problems solvable in polynomial time, while NP is the class of problems verifiable in polynomial time. It is possible for a problem in EXPTIME to be verified in NP, but we don't know if NP=EXPTIME. Additionally, we clarified that every problem in P is also in EXPTIME, and the number of steps required to solve a problem is
  • #1
Adel Makram
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If exponential functions are transcendental functions, then they can not be expressed in a polynomial algebraic form. If so, then P≠NP. Is that so simple?
 
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  • #2
No. It is not that simple. Can you please elaborate for us in your words what the question P=NP means?
 
  • #3
jbriggs444 said:
No. It is not that simple. Can you please elaborate for us in your words what the question P=NP means?
P means means the processing time of a computer algorithm is represented by a polynomial function of time.
NP means processing time of a computer algorithm is represented by an exponential function of time.
 
  • #4
Adel Makram said:
P means means the processing time of a computer algorithm is represented by a polynomial function of time.
NP means processing time of a computer algorithm is represented by an exponential function of time.

No, P is the class of all mathematical problems which can be solved by an algorithm which runs in polynomial time.
NP is the class of all mathematical problems whose solution can be verified by an algorithm which runs in polynomial time.
 
  • #5
pwsnafu said:
No, P is the class of all mathematical problems which can be solved by an algorithm which runs in polynomial time.
NP is the class of all mathematical problems whose solution can be verified by an algorithm which runs in polynomial time.
However, the solution of all mathematical problems in NP class are solved by an algorithm which runs in exponential time, isn't it?
 
  • #6
Adel Makram said:
However, the solution of all mathematical problems in NP class are solved by an algorithm which runs in exponential time, isn't it?

Yes, but we don't know if the converse is true. There may be problems which can be solved in exponential time whose solution verification also require exponential time.
 
  • #7
pwsnafu said:
Yes, but we don't know if the converse is true. There may be problems which can be solved in exponential time whose solution verification also require exponential time.
But I guess this contradicts your definition of NP:
pwsnafu said:
NP is the class of all mathematical problems whose solution can be verified by an algorithm which runs in polynomial time.
.
So how NP which is supposed by definition to be verified in polynomial time, now require exponential time?
 
  • #8
Adel Makram said:
But I guess this contradicts your definition of NP:
.
So how NP which is supposed by definition to be verified in polynomial time, now require exponential time?

No it doesn't. There's the class P (solvable in polynomial time). There is NP (verifiable in polynomial time). There is EXPTIME (solvable in exponential time). And lastly NEXPTIME (verifiable in exponential time). We know that
##P \subset NP \subset EXPTIME \subset NEXPTIME##
and also that ##P \neq EXTIME ##and ##NP \neq NEXTIME##. At least one of the inclusions is strict, we don't know which one.

If I pick a problem from EXPTIME the solution might be verifiable in polynomial time, or maybe not. It could be true that ##NP = EXPTIME##, in which case your definition is fine. But we don't know that.
 
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  • #9
For me it is all about mutual exclusion. Please look at the attached 2x2 table which I just made.
pwsnafu said:
If I pick a problem from EXPTIME the solution might be verifiable in polynomial time, or maybe not. It could be true that NP=EXPTIMENP = EXPTIME, in which case your definition is fine. But we don't know that.
If you do so, the verification of the solution in polynomial time will not invalidate that P is mutually exclusive with EXPTIME.
 

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  • #10
Please look at the attached 2x2 table which I just made now.
pwsnafu said:
If I pick a problem from EXPTIME the solution might be verifiable in polynomial time, or maybe not. It could be true that NP=EXPTIMENP = EXPTIME, in which case your definition is fine. But we don't know that.

If you do so, it won`t invalidate that both P and EXPTIME are mutually exclusive. So if the problem is solvable in exponential time (EXPTIME) but verified in polynomial (NP), it won`t be transformed one day to be solvable in polynomial (P) because it can`t be solvable in polynomial and exponential time at the same time.
 

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  • #11
Adel Makram said:
If you do so, it won`t invalidate that both P and EXPTIME are mutually exclusive. So if the problem is solvable in exponential time (EXPTIME) but verified in polynomial (NP), it won`t be transformed one day to be solvable in polynomial (P) because it can`t be solvable in polynomial and exponential time at the same time.

I have no idea what you are arguing now. "Mutually exclusive" means both cannot be true at the same time, i.e. there does not exist a problem which is both in P and in EXPTIME. That's nonsense, every problem in P is also in EXPTIME.
 
  • #12
pwsnafu said:
I have no idea what you are arguing now. "Mutually exclusive" means both cannot be true at the same time, i.e. there does not exist a problem which is both in P and in EXPTIME. That's nonsense, every problem in P is also in EXPTIME.
Good starting point now, so how come that every problem in P is a problem in EXPTIME? This again bring us back to the first post, that exponential function is transcendental ones!
 
  • #13
Adel Makram said:
Good starting point now, so how come that every problem in P is a problem in EXPTIME? This again bring us back to the first post, that exponential function is transcendental ones!

A problem class is solvable in "exponential time" if the solution to every problem in that class whose size is n takes no more than ken steps for some constant k.

A problem class is solvable in "polynomial time" if the solution to every problem in that class whose size is n takes no more than knj for some constants k and j.

Note that the number of steps required to solve a particular problem in a particular class is always an integer. It is never transcendental.
 
  • #14
jbriggs444 said:
A problem class is solvable in "exponential time" if the solution to every problem in that class whose size is n takes no more than ken steps for some constant k.

A problem class is solvable in "polynomial time" if the solution to every problem in that class whose size is n takes no more than knj for some constants k and j.

Note that the number of steps required to solve a particular problem in a particular class is always an integer. It is never transcendental.
But ken can not be expressed in a finite terms of knj. Also, if you put "verified" instead of "solvable" in the your statement, then quotes from pwsnafu becomes true. namely, the solution of a problem which can be verified in a polynomial time can not be verified in exponential time, if i understood i correctly.
pwsnafu said:
NP≠NEXTIMENP
 
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  • #15
Adel Makram said:
But ken can not be expressed in a finite steps of knj.

So? Exponentials grow faster than any ##n^j## (provided j is fixed). That's all that matters.

Also, if you put "verified" instead of "solvable" in the your statement, then quotes from pwsnafu becomes true.

The statements you quoted are true. It's called the time heirachy theorem.
We know that ##P \neq EXPTIME## and ##NP \neq NEXPTIME##.
We don't known if ##P \neq NP## or if ##NP \neq EXPTIME##.

namely, the solution of a problem which can be verified in a polynomial time can not be verified in exponential time, if i understood i correctly.

You did not understand correctly. ##NP \neq NEXPTIME## means that there exists at least one problem which can be verified in exponential time but not in polynomial time. Remember, ##NP \subset NEXPTIME##.
 
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  • #16
OK that is more clear for me now. So if we can prove that there exists at least one problem which is solvable in exponential time but can not be verified in polynomial time, then we prove that NP≠EXPTIME.
 
  • #17
Adel Makram said:
OK that is more clear for me now. So if we can prove that there exists at least one problem which is solvable in exponential time but can not be verified in polynomial time, then we prove that NP≠EXPTIME.
Correct.
 

1. What is the concept of P≠NP?

The concept of P≠NP is a hypothesis in computer science that suggests certain mathematical problems are inherently more difficult to solve than others. P stands for "polynomial time," which means that a problem can be solved in a reasonable amount of time, while NP stands for "nondeterministic polynomial time," which means that a problem can be verified in a reasonable amount of time. The hypothesis posits that there are problems in NP that cannot be solved in polynomial time, but this has not been proven or disproven.

2. What is the significance of P≠NP in the field of computer science?

The P≠NP hypothesis has significant implications in the field of computer science. If it is proven to be true, it would mean that there are problems that cannot be efficiently solved by computers, which would have major impacts on areas such as cryptography and data encryption. It would also have implications for the development of efficient algorithms and the understanding of the complexity of various problems.

3. How does the concept of P≠NP relate to exponential functions?

The concept of P≠NP is closely related to exponential functions because many problems in NP are believed to have an exponential time complexity. This means that the time it takes to solve these problems increases exponentially as the size of the problem increases. The P≠NP hypothesis suggests that there are no efficient algorithms for solving these problems, and therefore, exponential functions cannot be simplified or approximated in polynomial time.

4. What evidence supports the P≠NP hypothesis?

There is currently no conclusive evidence that supports or refutes the P≠NP hypothesis. However, there have been many attempts to solve NP-complete problems in polynomial time, and all have failed so far. Additionally, there are many problems that are believed to be in NP but have not been proven to be in NP. These factors provide some support for the hypothesis, but it remains unproven.

5. Can the P≠NP hypothesis ever be proven or disproven?

It is currently unknown if the P≠NP hypothesis can be proven or disproven. Some experts believe that it may be possible to prove the hypothesis by showing that certain NP-complete problems are inherently unsolvable in polynomial time. Others argue that it may be impossible to prove or disprove the hypothesis due to its complexity and the limitations of current technology. The debate on this topic is ongoing, and it remains a challenging problem in computer science.

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