If $f$ is in $L^p$, prove that $lim_lambda to 0 lambda ^p omega(lambda) = 0$

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Suppose that $E subseteq mathbbR$ is measurable and that the measurable functions $f: E to mathbbR$ satisfies $int_E |f| ^p < infty$. If $omega$ is the distribution function of $f$, prove that $lim_lambda to 0 lambda ^p omega(lambda) = 0$.
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real-analysis lebesgue-integral
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Suppose that $E subseteq mathbbR$ is measurable and that the measurable functions $f: E to mathbbR$ satisfies $int_E |f| ^p < infty$. If $omega$ is the distribution function of $f$, prove that $lim_lambda to 0 lambda ^p omega(lambda) = 0$.
I'm completely lost. How do I solve this problem?
real-analysis lebesgue-integral
By "distribution function of $f$", do you mean $omega(lambda) = mu left(left xin E : lvert f(x)rvert geqslant lambdarightright)$ where $mu$ is the measure under consideration (probably Lebesgue measure), or what?
â Daniel Fischerâ¦
Oct 30 '14 at 14:12
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Suppose that $E subseteq mathbbR$ is measurable and that the measurable functions $f: E to mathbbR$ satisfies $int_E |f| ^p < infty$. If $omega$ is the distribution function of $f$, prove that $lim_lambda to 0 lambda ^p omega(lambda) = 0$.
I'm completely lost. How do I solve this problem?
real-analysis lebesgue-integral
Suppose that $E subseteq mathbbR$ is measurable and that the measurable functions $f: E to mathbbR$ satisfies $int_E |f| ^p < infty$. If $omega$ is the distribution function of $f$, prove that $lim_lambda to 0 lambda ^p omega(lambda) = 0$.
I'm completely lost. How do I solve this problem?
real-analysis lebesgue-integral
asked Oct 30 '14 at 13:16
Johanna
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4,68941539
By "distribution function of $f$", do you mean $omega(lambda) = mu left(left xin E : lvert f(x)rvert geqslant lambdarightright)$ where $mu$ is the measure under consideration (probably Lebesgue measure), or what?
â Daniel Fischerâ¦
Oct 30 '14 at 14:12
add a comment |Â
By "distribution function of $f$", do you mean $omega(lambda) = mu left(left xin E : lvert f(x)rvert geqslant lambdarightright)$ where $mu$ is the measure under consideration (probably Lebesgue measure), or what?
â Daniel Fischerâ¦
Oct 30 '14 at 14:12
By "distribution function of $f$", do you mean $omega(lambda) = mu left(left xin E : lvert f(x)rvert geqslant lambdarightright)$ where $mu$ is the measure under consideration (probably Lebesgue measure), or what?
â Daniel Fischerâ¦
Oct 30 '14 at 14:12
By "distribution function of $f$", do you mean $omega(lambda) = mu left(left xin E : lvert f(x)rvert geqslant lambdarightright)$ where $mu$ is the measure under consideration (probably Lebesgue measure), or what?
â Daniel Fischerâ¦
Oct 30 '14 at 14:12
add a comment |Â
2 Answers
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We define $omega(lambda) = mu(f(x))$, then $lambda^p omega(lambda) to 0$ when $lambda to +infty$ is well known, since
$$lambda^p omega(lambda) leq int_E |f|^p1_geqlambda$$
It's interesting to see the convergence still holds when $lambda to 0$:
Take $lambda_n downarrow 0$, then we remark that
$$int_E |f|^p geq sum_n |lambda_n+1|^pleft(omega(lambda_n+1) - omega(lambda_n))right) = sum_n (lambda_n^p - lambda_n+1^p)omega(lambda_n)$$
Then for any $epsilon >0$, $exists N$ such that for all $k > N$ $$sum_n=k^infty (lambda_n^p - lambda_n+1^p)omega(lambda_n) < epsilon$$
Then remark that $omega(lambda_n) geq omega(lambda_k), forall n geq k$, so
$$sum_n=k^infty (lambda_n^p - lambda_n+1^p)omega(lambda_k) < epsilon$$
i.e. $$lambda_k^pomega(lambda_k)< epsilon, forall k > N$$
It's esay to complete the proof from here(suppose the conclusion is not true, then exists $lambda_n$ such that blabla, and $lambda_n$ has a decreasing subsequence, then apply what's above to get a contradiction.)
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Here is another proof, using the identity $$pint_0^infty lambda^p-1 omega(lambda) , d lambda = int_E |f|^p , dm$$ which one can prove with Fubini-Tonelli. If $fin L^p$, then the integral on the left converges; making the change of variables $lambda = 1/t$, we have $$int_0^infty lambda^p-1 omega(lambda) , d lambda = int_infty^0 frac1t^p-1 omegaleft(frac1t right) frac-1t^2 , dt = int_0^infty frac1t^p+1 omegaleft(frac1t right) , dt$$ Since this integral converges, and the function is nonnegative, we have $lim_c to infty int_c^infty t^-(p+1) omega(t^-1) , dt =0$.
On the other hand, we can bound $$int_c^infty t^-(p+1) omega(t^-1) > int_c^infty t^-(p+1), dt cdot omega(1/c) = frac1pc^-p omega(1/c)$$ Taking $ctoinfty$ gives the desired result by squeezing.
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2 Answers
2
active
oldest
votes
2 Answers
2
active
oldest
votes
active
oldest
votes
active
oldest
votes
up vote
1
down vote
accepted
We define $omega(lambda) = mu(f(x))$, then $lambda^p omega(lambda) to 0$ when $lambda to +infty$ is well known, since
$$lambda^p omega(lambda) leq int_E |f|^p1_geqlambda$$
It's interesting to see the convergence still holds when $lambda to 0$:
Take $lambda_n downarrow 0$, then we remark that
$$int_E |f|^p geq sum_n |lambda_n+1|^pleft(omega(lambda_n+1) - omega(lambda_n))right) = sum_n (lambda_n^p - lambda_n+1^p)omega(lambda_n)$$
Then for any $epsilon >0$, $exists N$ such that for all $k > N$ $$sum_n=k^infty (lambda_n^p - lambda_n+1^p)omega(lambda_n) < epsilon$$
Then remark that $omega(lambda_n) geq omega(lambda_k), forall n geq k$, so
$$sum_n=k^infty (lambda_n^p - lambda_n+1^p)omega(lambda_k) < epsilon$$
i.e. $$lambda_k^pomega(lambda_k)< epsilon, forall k > N$$
It's esay to complete the proof from here(suppose the conclusion is not true, then exists $lambda_n$ such that blabla, and $lambda_n$ has a decreasing subsequence, then apply what's above to get a contradiction.)
add a comment |Â
up vote
1
down vote
accepted
We define $omega(lambda) = mu(f(x))$, then $lambda^p omega(lambda) to 0$ when $lambda to +infty$ is well known, since
$$lambda^p omega(lambda) leq int_E |f|^p1_geqlambda$$
It's interesting to see the convergence still holds when $lambda to 0$:
Take $lambda_n downarrow 0$, then we remark that
$$int_E |f|^p geq sum_n |lambda_n+1|^pleft(omega(lambda_n+1) - omega(lambda_n))right) = sum_n (lambda_n^p - lambda_n+1^p)omega(lambda_n)$$
Then for any $epsilon >0$, $exists N$ such that for all $k > N$ $$sum_n=k^infty (lambda_n^p - lambda_n+1^p)omega(lambda_n) < epsilon$$
Then remark that $omega(lambda_n) geq omega(lambda_k), forall n geq k$, so
$$sum_n=k^infty (lambda_n^p - lambda_n+1^p)omega(lambda_k) < epsilon$$
i.e. $$lambda_k^pomega(lambda_k)< epsilon, forall k > N$$
It's esay to complete the proof from here(suppose the conclusion is not true, then exists $lambda_n$ such that blabla, and $lambda_n$ has a decreasing subsequence, then apply what's above to get a contradiction.)
add a comment |Â
up vote
1
down vote
accepted
up vote
1
down vote
accepted
We define $omega(lambda) = mu(f(x))$, then $lambda^p omega(lambda) to 0$ when $lambda to +infty$ is well known, since
$$lambda^p omega(lambda) leq int_E |f|^p1_geqlambda$$
It's interesting to see the convergence still holds when $lambda to 0$:
Take $lambda_n downarrow 0$, then we remark that
$$int_E |f|^p geq sum_n |lambda_n+1|^pleft(omega(lambda_n+1) - omega(lambda_n))right) = sum_n (lambda_n^p - lambda_n+1^p)omega(lambda_n)$$
Then for any $epsilon >0$, $exists N$ such that for all $k > N$ $$sum_n=k^infty (lambda_n^p - lambda_n+1^p)omega(lambda_n) < epsilon$$
Then remark that $omega(lambda_n) geq omega(lambda_k), forall n geq k$, so
$$sum_n=k^infty (lambda_n^p - lambda_n+1^p)omega(lambda_k) < epsilon$$
i.e. $$lambda_k^pomega(lambda_k)< epsilon, forall k > N$$
It's esay to complete the proof from here(suppose the conclusion is not true, then exists $lambda_n$ such that blabla, and $lambda_n$ has a decreasing subsequence, then apply what's above to get a contradiction.)
We define $omega(lambda) = mu(f(x))$, then $lambda^p omega(lambda) to 0$ when $lambda to +infty$ is well known, since
$$lambda^p omega(lambda) leq int_E |f|^p1_geqlambda$$
It's interesting to see the convergence still holds when $lambda to 0$:
Take $lambda_n downarrow 0$, then we remark that
$$int_E |f|^p geq sum_n |lambda_n+1|^pleft(omega(lambda_n+1) - omega(lambda_n))right) = sum_n (lambda_n^p - lambda_n+1^p)omega(lambda_n)$$
Then for any $epsilon >0$, $exists N$ such that for all $k > N$ $$sum_n=k^infty (lambda_n^p - lambda_n+1^p)omega(lambda_n) < epsilon$$
Then remark that $omega(lambda_n) geq omega(lambda_k), forall n geq k$, so
$$sum_n=k^infty (lambda_n^p - lambda_n+1^p)omega(lambda_k) < epsilon$$
i.e. $$lambda_k^pomega(lambda_k)< epsilon, forall k > N$$
It's esay to complete the proof from here(suppose the conclusion is not true, then exists $lambda_n$ such that blabla, and $lambda_n$ has a decreasing subsequence, then apply what's above to get a contradiction.)
edited Oct 30 '14 at 14:47
answered Oct 30 '14 at 13:47
Petite Etincelle
12.2k11946
12.2k11946
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Here is another proof, using the identity $$pint_0^infty lambda^p-1 omega(lambda) , d lambda = int_E |f|^p , dm$$ which one can prove with Fubini-Tonelli. If $fin L^p$, then the integral on the left converges; making the change of variables $lambda = 1/t$, we have $$int_0^infty lambda^p-1 omega(lambda) , d lambda = int_infty^0 frac1t^p-1 omegaleft(frac1t right) frac-1t^2 , dt = int_0^infty frac1t^p+1 omegaleft(frac1t right) , dt$$ Since this integral converges, and the function is nonnegative, we have $lim_c to infty int_c^infty t^-(p+1) omega(t^-1) , dt =0$.
On the other hand, we can bound $$int_c^infty t^-(p+1) omega(t^-1) > int_c^infty t^-(p+1), dt cdot omega(1/c) = frac1pc^-p omega(1/c)$$ Taking $ctoinfty$ gives the desired result by squeezing.
add a comment |Â
up vote
1
down vote
Here is another proof, using the identity $$pint_0^infty lambda^p-1 omega(lambda) , d lambda = int_E |f|^p , dm$$ which one can prove with Fubini-Tonelli. If $fin L^p$, then the integral on the left converges; making the change of variables $lambda = 1/t$, we have $$int_0^infty lambda^p-1 omega(lambda) , d lambda = int_infty^0 frac1t^p-1 omegaleft(frac1t right) frac-1t^2 , dt = int_0^infty frac1t^p+1 omegaleft(frac1t right) , dt$$ Since this integral converges, and the function is nonnegative, we have $lim_c to infty int_c^infty t^-(p+1) omega(t^-1) , dt =0$.
On the other hand, we can bound $$int_c^infty t^-(p+1) omega(t^-1) > int_c^infty t^-(p+1), dt cdot omega(1/c) = frac1pc^-p omega(1/c)$$ Taking $ctoinfty$ gives the desired result by squeezing.
add a comment |Â
up vote
1
down vote
up vote
1
down vote
Here is another proof, using the identity $$pint_0^infty lambda^p-1 omega(lambda) , d lambda = int_E |f|^p , dm$$ which one can prove with Fubini-Tonelli. If $fin L^p$, then the integral on the left converges; making the change of variables $lambda = 1/t$, we have $$int_0^infty lambda^p-1 omega(lambda) , d lambda = int_infty^0 frac1t^p-1 omegaleft(frac1t right) frac-1t^2 , dt = int_0^infty frac1t^p+1 omegaleft(frac1t right) , dt$$ Since this integral converges, and the function is nonnegative, we have $lim_c to infty int_c^infty t^-(p+1) omega(t^-1) , dt =0$.
On the other hand, we can bound $$int_c^infty t^-(p+1) omega(t^-1) > int_c^infty t^-(p+1), dt cdot omega(1/c) = frac1pc^-p omega(1/c)$$ Taking $ctoinfty$ gives the desired result by squeezing.
Here is another proof, using the identity $$pint_0^infty lambda^p-1 omega(lambda) , d lambda = int_E |f|^p , dm$$ which one can prove with Fubini-Tonelli. If $fin L^p$, then the integral on the left converges; making the change of variables $lambda = 1/t$, we have $$int_0^infty lambda^p-1 omega(lambda) , d lambda = int_infty^0 frac1t^p-1 omegaleft(frac1t right) frac-1t^2 , dt = int_0^infty frac1t^p+1 omegaleft(frac1t right) , dt$$ Since this integral converges, and the function is nonnegative, we have $lim_c to infty int_c^infty t^-(p+1) omega(t^-1) , dt =0$.
On the other hand, we can bound $$int_c^infty t^-(p+1) omega(t^-1) > int_c^infty t^-(p+1), dt cdot omega(1/c) = frac1pc^-p omega(1/c)$$ Taking $ctoinfty$ gives the desired result by squeezing.
answered Aug 29 at 4:41
Sameer Kailasa
5,37621743
5,37621743
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By "distribution function of $f$", do you mean $omega(lambda) = mu left(left xin E : lvert f(x)rvert geqslant lambdarightright)$ where $mu$ is the measure under consideration (probably Lebesgue measure), or what?
â Daniel Fischerâ¦
Oct 30 '14 at 14:12