Min or max

Calculus Level 2

Let a a , b b , and c c be positive real numbers, then which of the following is equal to

lim p ( a p + b p + c p ) 1 p ? \lim_{p\to \infty}\left(a^p+b^p+c^p\right)^{\frac{1}{p}}?

Notations: max ( ) \max (\cdot) and min ( ) \min (\cdot) denote maximum and minimum functions respectively.

max ( a p , b p , c p ) \operatorname{max}(a^p,b^p,c^p) max ( a , b , c ) \operatorname{max}(a,b,c) min ( a b , b c , c a ) \operatorname{min}(a-b,b-c,c-a) max ( a b , b c , c a ) \operatorname{max}(ab,bc,ca)

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2 solutions

Chris Lewis
Oct 19, 2020

Without loss of generality, say the maximum of a , b , c a,b,c is a a . Then ( a p + b p + c p ) 1 p = a ( 1 + ( b a ) p + + ( c a ) p ) 1 p \left(a^p+b^p+c^p \right)^{\frac{1}{p}}=a\left(1+\left(\frac{b}{a}\right)^p+ +\left(\frac{c}{a}\right)^p \right)^{\frac{1}{p}}

Now, the (positive) quantity ε = ( b a ) p + ( c a ) p \varepsilon=\left(\frac{b}{a}\right)^p+ \left(\frac{c}{a}\right)^p

can be made arbitrarily small by choosing p p large enough.

So ( a p + b p + c p ) 1 p = a ( 1 + ε ) 1 p = a + 1 p a ε + O ( ε 2 ) a \left(a^p+b^p+c^p \right)^{\frac{1}{p}}=a(1+\varepsilon)^{\frac{1}{p}}=a+\frac{1}{p}a\varepsilon+\mathcal{O} \left( \varepsilon^2 \right) \to a

ie the quantity in the question tends to max ( a , b , c ) \max(a,b,c) as p p \to \infty .


Incidentally, this is a very useful identity and very common in analysis of dynamical systems (where you are often interested in long term behaviour of a differential equation near a fixed point).

For similar reasons, this is also why the n th n^{\text{th}} Fibonacci number is well approximated by φ n \varphi^n .

Nicely explained. Just sharing my thoughts on this. In literature, the quantity

( a p + b p + c p ) 1 / p \left(a^p + b^p+c^p\right)^{1/p}

is called the p p th norm of the vector:

[ a b c ] T \left[\begin{matrix} a & b& c \end{matrix}\right]^T

In the limit as p p tends to infinity, the norm is then known as the infinity norm of that vector. We are most familiar with the 2 2 -norm in which case p = 2 p=2 .

Karan Chatrath - 7 months, 3 weeks ago
Naren Bhandari
Oct 19, 2020

We shall in general show that, for λ i R n \lambda_i\in\mathbb R^n , i = 1 , 2 , 3 , , n i=1,2,3,\cdots, n max { λ 1 , λ 2 , , λ n } = lim p ( i = 1 n λ i p ) 1 / p \operatorname{max}\left\{|\lambda_1|,\lambda_2,\cdots,|\lambda_n| \right\}=\lim_{p\to\infty}\left(\sum_{i=1}^n|\lambda_i|^p\right)^{1/p}

Proof

Let A i = { λ 1 , λ 1 , , λ n } \mathcal{A}_i=\left\{|\lambda_1|,|\lambda_1|,\cdots ,|\lambda_n|\right\} be a finite set such that for i [ 1 , n ] i\in [1,n] , max { λ 1 , λ 1 , , λ n } = λ k \operatorname{max}\left\{|\lambda_1|,|\lambda_1|,\cdots ,|\lambda_n|\right\}= |\lambda_k| for any 1 k i n 1\leq k\leq i\leq n then we can write S ( n , k ) = i = 1 n λ i p = λ k p i = 1 n λ i λ k p = λ k p ( 1 + i = 1 , i k n λ i λ k p ) \mathcal{S}(n,k)=\sum_{i=1}^{n}|\lambda_i|^p=|\lambda_k|^p\sum_{i=1}^n\Bigg|\frac{\lambda_i}{\lambda_k}\Bigg|^p=|\lambda_k|^p\left(1+\sum_{i=1,i\neq k}^n\Bigg|\frac{\lambda_i}{\lambda_k}\Bigg|^p\right) now with pth root of S ( n , k ) \mathcal{S}(n,k) and by Bernoulli inequality we have for 0 < j < 1 0<j<1 λ k S ( n , k ) p λ k ( 1 + 1 p i = 1 , i k n λ i λ k p ) |\lambda_k|\leq \sqrt[p]{\mathcal{S}(n,k)}\leq |\lambda_k|\left(1+\frac{1}{p}\sum_{i=1,i\neq k}^n\Bigg|\frac{\lambda_i}{\lambda_k}\Bigg|^p\right) and hence as p p\to \infty , ( λ i λ k ) p = j p 0 \left(\frac{\lambda_i}{\lambda_k}\right)^p=j^p\to 0 as j < 1 j<1 and by Sandwich theorem we have λ k lim p S ( n , k ) p λ k |\lambda_k|\leq \lim_{p\to\infty}\sqrt[p]{\mathcal{S}(n,k)}\leq |\lambda_k| and hence max { A i } = lim p + ( i = 1 n A i p ) 1 / p \operatorname{max}\left\{A_i\right\}=\lim_{p\to \infty+}\left(\sum_{i=1}^n\mathcal{A}_i^p\right)^{1/p}

For our case we just set λ 1 = a , λ 2 = b |\lambda_1|=a ,|\lambda_2| =b and λ 3 = c |\lambda_3|=c and hence required answer is max ( a , b , c ) \operatorname{max}(a,b,c) .


Remark: It is interesting to note that for all x , y R n x,y\in\mathbb R^n d ( x , y ) = lim p d p ( x , y ) d_{\infty}(x,y)=\lim_{p\to \infty}d_p(x,y) where d ( x , y ) d_{\infty}(x,y) is called sup-norm metric and d p ( x , y ) = ( x 1 y 1 p + x 2 y 2 p ) 1 / p d_p(x,y)=\left(|x_1-y_1|^p+|x_2-y_2|^p\right)^{1/p} which is directly a implication of above result.

Nice problem on generalised vector norms.

Karan Chatrath - 7 months, 3 weeks ago

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