When is it possible to find necessary and sufficient conditions linking two concepts?
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Status of this question: The notion I'm after is vague in my mind. I hope someone can clarify whether there is an exact version of the question I'm asking.
It seems to me that one of the most important reason why a mathematician would be interested in trying to find "necessary and sufficient conditions" for some notion $A$ (please tell me if you disagree), is to find computable or "easily recognizable" conditions for a notion $A$. In this case, there are two notions:
A notion $A$ that we are interested in, but which is not "directly" easily checkable (e.g. to "directly" check whether $x$ is a local extremum we'd need to check an uncountable number of points)
A notion $B$ that is "directly" easily checkable (e.g. checking the first derivative of $x$ is easy, and allows us to indirectly check $A$).
But the notion of "local optimum" does not seem to have generally applicable satisfying necessary and sufficient conditions (only for differentiable functions, but not for arbitrary functions).
So it seems that it is not always possible to find necessary and sufficient conditions for some notion.
My questions are:
Is there some kind of metamathematical analysis of when it is possible to formulate necessary and sufficient conditions for some mathematical notion?
(My understanding of my question is too vague to say definitively, but I presume this has to do with computability, and maybe kolmogorov-complexity?)The main motivation behind the previous question: When you're doing research and would like to have necessary and sufficient conditions for some notion $X$, is it possible to make good educated guesses about whether such conditions are even theoretically possible?
research
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up vote
0
down vote
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Status of this question: The notion I'm after is vague in my mind. I hope someone can clarify whether there is an exact version of the question I'm asking.
It seems to me that one of the most important reason why a mathematician would be interested in trying to find "necessary and sufficient conditions" for some notion $A$ (please tell me if you disagree), is to find computable or "easily recognizable" conditions for a notion $A$. In this case, there are two notions:
A notion $A$ that we are interested in, but which is not "directly" easily checkable (e.g. to "directly" check whether $x$ is a local extremum we'd need to check an uncountable number of points)
A notion $B$ that is "directly" easily checkable (e.g. checking the first derivative of $x$ is easy, and allows us to indirectly check $A$).
But the notion of "local optimum" does not seem to have generally applicable satisfying necessary and sufficient conditions (only for differentiable functions, but not for arbitrary functions).
So it seems that it is not always possible to find necessary and sufficient conditions for some notion.
My questions are:
Is there some kind of metamathematical analysis of when it is possible to formulate necessary and sufficient conditions for some mathematical notion?
(My understanding of my question is too vague to say definitively, but I presume this has to do with computability, and maybe kolmogorov-complexity?)The main motivation behind the previous question: When you're doing research and would like to have necessary and sufficient conditions for some notion $X$, is it possible to make good educated guesses about whether such conditions are even theoretically possible?
research
add a comment |Â
up vote
0
down vote
favorite
up vote
0
down vote
favorite
Status of this question: The notion I'm after is vague in my mind. I hope someone can clarify whether there is an exact version of the question I'm asking.
It seems to me that one of the most important reason why a mathematician would be interested in trying to find "necessary and sufficient conditions" for some notion $A$ (please tell me if you disagree), is to find computable or "easily recognizable" conditions for a notion $A$. In this case, there are two notions:
A notion $A$ that we are interested in, but which is not "directly" easily checkable (e.g. to "directly" check whether $x$ is a local extremum we'd need to check an uncountable number of points)
A notion $B$ that is "directly" easily checkable (e.g. checking the first derivative of $x$ is easy, and allows us to indirectly check $A$).
But the notion of "local optimum" does not seem to have generally applicable satisfying necessary and sufficient conditions (only for differentiable functions, but not for arbitrary functions).
So it seems that it is not always possible to find necessary and sufficient conditions for some notion.
My questions are:
Is there some kind of metamathematical analysis of when it is possible to formulate necessary and sufficient conditions for some mathematical notion?
(My understanding of my question is too vague to say definitively, but I presume this has to do with computability, and maybe kolmogorov-complexity?)The main motivation behind the previous question: When you're doing research and would like to have necessary and sufficient conditions for some notion $X$, is it possible to make good educated guesses about whether such conditions are even theoretically possible?
research
Status of this question: The notion I'm after is vague in my mind. I hope someone can clarify whether there is an exact version of the question I'm asking.
It seems to me that one of the most important reason why a mathematician would be interested in trying to find "necessary and sufficient conditions" for some notion $A$ (please tell me if you disagree), is to find computable or "easily recognizable" conditions for a notion $A$. In this case, there are two notions:
A notion $A$ that we are interested in, but which is not "directly" easily checkable (e.g. to "directly" check whether $x$ is a local extremum we'd need to check an uncountable number of points)
A notion $B$ that is "directly" easily checkable (e.g. checking the first derivative of $x$ is easy, and allows us to indirectly check $A$).
But the notion of "local optimum" does not seem to have generally applicable satisfying necessary and sufficient conditions (only for differentiable functions, but not for arbitrary functions).
So it seems that it is not always possible to find necessary and sufficient conditions for some notion.
My questions are:
Is there some kind of metamathematical analysis of when it is possible to formulate necessary and sufficient conditions for some mathematical notion?
(My understanding of my question is too vague to say definitively, but I presume this has to do with computability, and maybe kolmogorov-complexity?)The main motivation behind the previous question: When you're doing research and would like to have necessary and sufficient conditions for some notion $X$, is it possible to make good educated guesses about whether such conditions are even theoretically possible?
research
asked Aug 16 at 6:14
Programmer2134
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As an interesting bit of trivia, there are proofs of arbitrarily large minimum complexity, hence there are arbitrarily large minimal necessary and sufficient conditions. You're effectively (approximately) asking the meta question "Are there necessary and sufficient conditions for determining if there are necessary and sufficient conditions for a given problem", and no such thing could exist without solving the Halting Problem (at least, I'm pretty sure of that).
As to your actual main motivation, it is absolutely possible to make good educated guesses about whether such conditions are even theoretically possible. To work with an analogy that hopefully fits into your math/programming background somewhere, take the chromatic number of a graph as an example. Actually computing such a thing is an NP-Complete problem, but we have many excellent heuristics both for approximating it and for bounding it.
Many non-trivial facts have a similar property. It takes an obscene amount of work to prove them from a cold start, but with enough background they are so trivial you no longer need to even go through the mechanics of a proof. The more you know, the more approaches and facts you'll be able to trivially rule out (with the approximations, bounds, and heuristics you develop while learning about mathematics) without ever "wasting" time actually attempting them.
Tangentially to that, in addition to heuristics which rule out research areas we also have heuristics which allow one to hone in on other research areas. Over time, I've found that I tend to have success improving seemingly discrete algorithms by finding a way to work a derivative into the picture. I have a rough idea of what a successful proof in that style looks like, and given a new problem/question I can gauge whether or not I think incorporating derivatives is worth my time.
As to the metamathematical analysis you are looking for, I'm really not certain if any necessary conditions or any sufficient conditions are readily available for such use. The general vein of study would be proof complexity, and I think you're on the right track, but I don't know enough to answer or help any further.
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1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
up vote
1
down vote
As an interesting bit of trivia, there are proofs of arbitrarily large minimum complexity, hence there are arbitrarily large minimal necessary and sufficient conditions. You're effectively (approximately) asking the meta question "Are there necessary and sufficient conditions for determining if there are necessary and sufficient conditions for a given problem", and no such thing could exist without solving the Halting Problem (at least, I'm pretty sure of that).
As to your actual main motivation, it is absolutely possible to make good educated guesses about whether such conditions are even theoretically possible. To work with an analogy that hopefully fits into your math/programming background somewhere, take the chromatic number of a graph as an example. Actually computing such a thing is an NP-Complete problem, but we have many excellent heuristics both for approximating it and for bounding it.
Many non-trivial facts have a similar property. It takes an obscene amount of work to prove them from a cold start, but with enough background they are so trivial you no longer need to even go through the mechanics of a proof. The more you know, the more approaches and facts you'll be able to trivially rule out (with the approximations, bounds, and heuristics you develop while learning about mathematics) without ever "wasting" time actually attempting them.
Tangentially to that, in addition to heuristics which rule out research areas we also have heuristics which allow one to hone in on other research areas. Over time, I've found that I tend to have success improving seemingly discrete algorithms by finding a way to work a derivative into the picture. I have a rough idea of what a successful proof in that style looks like, and given a new problem/question I can gauge whether or not I think incorporating derivatives is worth my time.
As to the metamathematical analysis you are looking for, I'm really not certain if any necessary conditions or any sufficient conditions are readily available for such use. The general vein of study would be proof complexity, and I think you're on the right track, but I don't know enough to answer or help any further.
add a comment |Â
up vote
1
down vote
As an interesting bit of trivia, there are proofs of arbitrarily large minimum complexity, hence there are arbitrarily large minimal necessary and sufficient conditions. You're effectively (approximately) asking the meta question "Are there necessary and sufficient conditions for determining if there are necessary and sufficient conditions for a given problem", and no such thing could exist without solving the Halting Problem (at least, I'm pretty sure of that).
As to your actual main motivation, it is absolutely possible to make good educated guesses about whether such conditions are even theoretically possible. To work with an analogy that hopefully fits into your math/programming background somewhere, take the chromatic number of a graph as an example. Actually computing such a thing is an NP-Complete problem, but we have many excellent heuristics both for approximating it and for bounding it.
Many non-trivial facts have a similar property. It takes an obscene amount of work to prove them from a cold start, but with enough background they are so trivial you no longer need to even go through the mechanics of a proof. The more you know, the more approaches and facts you'll be able to trivially rule out (with the approximations, bounds, and heuristics you develop while learning about mathematics) without ever "wasting" time actually attempting them.
Tangentially to that, in addition to heuristics which rule out research areas we also have heuristics which allow one to hone in on other research areas. Over time, I've found that I tend to have success improving seemingly discrete algorithms by finding a way to work a derivative into the picture. I have a rough idea of what a successful proof in that style looks like, and given a new problem/question I can gauge whether or not I think incorporating derivatives is worth my time.
As to the metamathematical analysis you are looking for, I'm really not certain if any necessary conditions or any sufficient conditions are readily available for such use. The general vein of study would be proof complexity, and I think you're on the right track, but I don't know enough to answer or help any further.
add a comment |Â
up vote
1
down vote
up vote
1
down vote
As an interesting bit of trivia, there are proofs of arbitrarily large minimum complexity, hence there are arbitrarily large minimal necessary and sufficient conditions. You're effectively (approximately) asking the meta question "Are there necessary and sufficient conditions for determining if there are necessary and sufficient conditions for a given problem", and no such thing could exist without solving the Halting Problem (at least, I'm pretty sure of that).
As to your actual main motivation, it is absolutely possible to make good educated guesses about whether such conditions are even theoretically possible. To work with an analogy that hopefully fits into your math/programming background somewhere, take the chromatic number of a graph as an example. Actually computing such a thing is an NP-Complete problem, but we have many excellent heuristics both for approximating it and for bounding it.
Many non-trivial facts have a similar property. It takes an obscene amount of work to prove them from a cold start, but with enough background they are so trivial you no longer need to even go through the mechanics of a proof. The more you know, the more approaches and facts you'll be able to trivially rule out (with the approximations, bounds, and heuristics you develop while learning about mathematics) without ever "wasting" time actually attempting them.
Tangentially to that, in addition to heuristics which rule out research areas we also have heuristics which allow one to hone in on other research areas. Over time, I've found that I tend to have success improving seemingly discrete algorithms by finding a way to work a derivative into the picture. I have a rough idea of what a successful proof in that style looks like, and given a new problem/question I can gauge whether or not I think incorporating derivatives is worth my time.
As to the metamathematical analysis you are looking for, I'm really not certain if any necessary conditions or any sufficient conditions are readily available for such use. The general vein of study would be proof complexity, and I think you're on the right track, but I don't know enough to answer or help any further.
As an interesting bit of trivia, there are proofs of arbitrarily large minimum complexity, hence there are arbitrarily large minimal necessary and sufficient conditions. You're effectively (approximately) asking the meta question "Are there necessary and sufficient conditions for determining if there are necessary and sufficient conditions for a given problem", and no such thing could exist without solving the Halting Problem (at least, I'm pretty sure of that).
As to your actual main motivation, it is absolutely possible to make good educated guesses about whether such conditions are even theoretically possible. To work with an analogy that hopefully fits into your math/programming background somewhere, take the chromatic number of a graph as an example. Actually computing such a thing is an NP-Complete problem, but we have many excellent heuristics both for approximating it and for bounding it.
Many non-trivial facts have a similar property. It takes an obscene amount of work to prove them from a cold start, but with enough background they are so trivial you no longer need to even go through the mechanics of a proof. The more you know, the more approaches and facts you'll be able to trivially rule out (with the approximations, bounds, and heuristics you develop while learning about mathematics) without ever "wasting" time actually attempting them.
Tangentially to that, in addition to heuristics which rule out research areas we also have heuristics which allow one to hone in on other research areas. Over time, I've found that I tend to have success improving seemingly discrete algorithms by finding a way to work a derivative into the picture. I have a rough idea of what a successful proof in that style looks like, and given a new problem/question I can gauge whether or not I think incorporating derivatives is worth my time.
As to the metamathematical analysis you are looking for, I'm really not certain if any necessary conditions or any sufficient conditions are readily available for such use. The general vein of study would be proof complexity, and I think you're on the right track, but I don't know enough to answer or help any further.
answered Aug 16 at 6:48
Hans Musgrave
1,484111
1,484111
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