HSC 2016 MX2 Marathon (archive) (1 Viewer)

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leehuan

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Re: HSC 2016 4U Marathon

Is that second part really manageable by current 2016ers?
 

leehuan

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Re: HSC 2016 4U Marathon

Yes, just need to provide a counter-example.
Oh right.
But how would you go about proving a general case?

Also, in the context of maths what do we regard as convex and concave
 

InteGrand

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Re: HSC 2016 4U Marathon

Oh right.
But how would you go about proving a general case?
To disprove the statement's converse, one only needs a counter-example. What do you mean general case?
 

Paradoxica

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Re: HSC 2016 4U Marathon

Oh right.
But how would you go about proving a general case?

Also, in the context of maths what do we regard as convex and concave
There is no general case for the converse. All you have to show is that the converse does not hold true in general, as the converse statement is already generalised to all convex exponentials.

i.e the converse states:



which is not true, as counterexamples exist.
 

leehuan

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Re: HSC 2016 4U Marathon

Great, that's what I was thinking but I needed confirmation, since for some reason during the HSC I never came across that language.
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What I meant was, if you had g(x)=e^(f(x)) and you knew g"(x)>0 would it be possible to then work backwards and realise "but f"(x) isn't always > 0"

If the counterexample answer will suffice then I won't comment further.
 

glittergal96

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Re: HSC 2016 4U Marathon

i) Let g=e^f

g(tx+(1-t)y) =< e^(tf(x)+(1-t)f(y)) (convexity of f)
= (e^f(x))^t(e^f(y))^(1-t)
= g(x)^tg(y)^(1-t)
=< tg(x)+(1-t)g(t) (weighted AM-GM in two variables *)

for all 0 =< t =< 1.

ii) f(x)=log(x) is a counterexample, it is strictly concave as it's second derivative is negative, and e^f(x)=x is trivially convex.


Proof of weighted AM-GM in two variables:

log is a concave function because its second derivative is negative.

This implies that
tlog(x)+(1-t)log(y)=< log(tx+(1-t)y)
x^t y^(1-t) =< tx + (1-t)y (exponentiating both sides.)

Note that the proof of i) makes no assumption on the regularity of f. Convex functions need not be very smooth!
 

glittergal96

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Re: HSC 2016 4U Marathon

A followup question based on the second derivative test for convexity:

Given that f''(x)>0 for all a =< x =< b, show that f is convex on the interval [a,b].

That is, show that f(tx+(1-t)y) =< tf(x)+(1-t)f(y) for all x and y in [a,b], and all t in [0,1].

(This result is of course common sense, but should really be proved rigorously. Thankfully it is not too hard to do so.)
 

Paradoxica

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Re: HSC 2016 4U Marathon

i) Let g=e^f

g(tx+(1-t)y) =< e^(tf(x)+(1-t)f(y)) (convexity of f)
= (e^f(x))^t(e^f(y))^(1-t)
= g(x)^tg(y)^(1-t)
=< tg(x)+(1-t)g(t) (weighted AM-GM in two variables *)

for all 0 =< t =< 1.

ii) f(x)=log(x) is a counterexample, it is strictly concave as it's second derivative is negative, and e^f(x)=x is trivially convex.


Proof of weighted AM-GM in two variables:

log is a concave function because its second derivative is negative.

This implies that
tlog(x)+(1-t)log(y)=< log(tx+(1-t)y)
x^t y^(1-t) =< tx + (1-t)y (exponentiating both sides.)

Note that the proof of i) makes no assumption on the regularity of f. Convex functions need not be very smooth!
Wrong, linear functions are technically ambiguous in their convexity and concavity. A more rigorous counter-example would be f(x) = 2log(x)
 

glittergal96

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Re: HSC 2016 4U Marathon

Wrong, linear functions are technically ambiguous in their convexity and concavity. A more rigorous counter-example would be f(x) = 2log(x)
It is literally a matter of definition. My use of the word "convex" is exactly that in https://en.wikipedia.org/wiki/Convex_function (as well as most textbooks I have ever seen it in).

Using this terminology, x is a convex function, and log(x) is a strictly concave function. Strictly concave functions are not convex. Hence log(x) is a counterexample to your claim. If you meant something else by your use of the word "convex" you should have made that clear in the original question.
 

Sy123

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Re: HSC 2016 4U Marathon

A followup question based on the second derivative test for convexity:

Given that f''(x)>0 for all a =< x =< b, show that f is convex on the interval [a,b].

That is, show that f(tx+(1-t)y) =< tf(x)+(1-t)f(y) for all x and y in [a,b], and all t in [0,1].

(This result is of course common sense, but should really be proved rigorously. Thankfully it is not too hard to do so.)


















 

Sy123

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Re: HSC 2016 4U Marathon

Bringing it back to more familiar ground:

 

Ekman

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Re: HSC 2016 4U Marathon

Key word there is conventionally, however this isn't a conventional question, since when did integrand go to prison, come out, go to uni to only quit later and get hired by UPS, and still have time to answer questions on bos
 
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