Equivalent Norms: Proving $\|A\| \leq \|A\|_{Eucl} \leq \sqrt{n}\|A\|$

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Discussion Overview

The discussion revolves around proving the inequalities involving norms of a real matrix \( A \), specifically \(\|A\| \leq \|A\|_{\text{Eucl}} \leq \sqrt{n}\|A\|\). The focus is on mathematical reasoning and exploration of the properties of matrix norms.

Discussion Character

  • Mathematical reasoning
  • Exploratory
  • Technical explanation

Main Points Raised

  • One participant establishes the first inequality \(\|A\| \leq \|A\|_{\text{Eucl}}\) using the Cauchy–Schwarz inequality and provides a detailed derivation.
  • Another participant suggests using the trace of \(A^TA\) to approach the second inequality, indicating a potential method for proving \(\|A\|_{\text{Eucl}} \leq \sqrt{n}\|A\|\).
  • A participant proposes a series of transformations involving the Euclidean norm and the standard basis vectors \(e_j\) to explore the relationship between \(\|A\|_{\text{Eucl}}\) and \(\|A\|_2\), questioning whether this leads to \(\|A\|\).
  • Further clarification is provided on the properties of supremum and the relationship between the norms, emphasizing that \(\|Ae_j\|_2^2 \leq \|A\|^2\) for each basis vector.

Areas of Agreement / Disagreement

Participants generally agree on the validity of the first inequality and the approach to the second inequality, but the discussion remains unresolved regarding the specific steps to prove \(\|A\|_{\text{Eucl}} \leq \sqrt{n}\|A\|\).

Contextual Notes

The discussion includes various mathematical assumptions and transformations that may depend on the definitions of the norms involved. Some steps in the reasoning are not fully resolved, particularly in connecting \(\|A\|_2\) to \(\|A\|\).

mathmari
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Hey! :o

Let $A=(a_{i,j})$ a real matrix with $m$ rows and $n$ columns, $x\in \mathbb{R}^n$ and \begin{equation*}\|A\|:=\sup_{\|x\|_2\leq 1}\|Ax\|_2, \ \ \|A\|_{\text{Eucl}}:=\sqrt{\sum_{i=1}^m\sum_{j=1}^n|a_{i,j}|^2}\end{equation*}

I want to show that $$\|A\|\leq \|A\|_{\text{Eucl}} \leq \sqrt{n}\|A\|$$ I have already shown the first inequality:

Since $\displaystyle{(Ax)_i=\sum_{j=1}^na_{i,j}x_j}$, we get $\displaystyle{\|Ax\|_2^2=\sum_{i=1}^m\left (\sum_{j=1}^n|a_{i,j}x_j|\right )^2=\sum_{i=1}^m\left (\sum_{j=1}^n|a_{i,j}||x_j|\right )^2}$.

From the Cauchy–Schwarz inequality we get \begin{equation*}\left (\sum_{j=1}^n|a_{i,j}||x_j|\right )^2\leq \left (\sum_{j=1}^n{|a_{i,j}|^2}\right )\left (\sum_{j=1}^n|x_j|^2\right )=\left (\sum_{j=1}^n{|a_{i,j}|^2}\right )\|x\|_2^2\end{equation*}

Sp we get\begin{equation*}\|Ax\|_2^2=\sum_{i=1}^n\left (\sum_{j=1}^n|a_{i,j}||x_j|\right )^2\leq \sum_{i=1}^m\sum_{j=1}^n|a_{i,j}|^2\|x\|_2^2=\|A\|_{\text{Eucl}}^2\,\|x\|_2^2 \end{equation*}

Therefore we have that \begin{equation*}\|Ax\|_2\leq \|A\|_{\text{Eucl}}\,\|x\|_2\Rightarrow \sup_{\|x\|_2\leq 1}\|Ax\|_2\leq \sup_{\|x\|_2\leq 1}\|A\|_{\text{Eucl}}\,\|x\|_2=\|A\|_{\text{Eucl}}\end{equation*}

From that it implies that $\|A\|\leq \|A\|_{\text{Eucl}}$. Is everything correct? (Wondering)
Could you give me a hint for the second inequality? (Wondering)
 
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mathmari said:
Hey! :o

Let $A=(a_{i,j})$ a real matrix with $m$ rows and $n$ columns, $x\in \mathbb{R}^n$ and \begin{equation*}\|A\|:=\sup_{\|x\|_2\leq 1}\|Ax\|_2, \ \ \|A\|_{\text{Eucl}}:=\sqrt{\sum_{i=1}^m\sum_{j=1}^n|a_{i,j}|^2}\end{equation*}

I want to show that $$\|A\|\leq \|A\|_{\text{Eucl}} \leq \sqrt{n}\|A\|$$ I have already shown the first inequality:
.
.
.
Is everything correct? (Wondering)
Yes!

mathmari said:
Could you give me a hint for the second inequality? (Wondering)
You could use the fact that $\|A\|_{\text{Eucl}}^2 = \text{tr}\,(A^TA)$ (where tr denotes the trace and $A^T$ is the transpose of $A$).
 
Opalg said:
You could use the fact that $\|A\|_{\text{Eucl}}^2 = \text{tr}\,(A^TA)$ (where tr denotes the trace and $A^T$ is the transpose of $A$).

What do we get from that? I got stuck right now. (Wondering) Could we do also something like the following?
\begin{align*}\|A\|_{\text{Eucl}}^2=\sum_{i=1}^m\sum_{j=1}^n|a_{i,j}|^2=\sum_{j=1}^n\sum_{i=1}^m|a_{i,j}|^2=\sum_{j=1}^n\|a_j\|_2^2=\sum_{j=1}^n\|Ae_j\|_2^2\leq \sum_{j=1}^n\|A\|_2^2\|e_j\|_2^2=n\|A\|_2^2\end{align*} But instead of $\|A\|$ we have $\|A\|_2$. Is the above correct? If yes, can we get to $\|A\|$ ? (Wondering)
 
Hi mathmari,

mathmari said:
Could we do also something like the following?
\begin{align*}\|A\|_{\text{Eucl}}^2=\sum_{i=1}^m\sum_{j=1}^n|a_{i,j}|^2=\sum_{j=1}^n\sum_{i=1}^m|a_{i,j}|^2=\sum_{j=1}^n\|a_j\|_2^2=\sum_{j=1}^n\|Ae_j\|_2^2\leq \sum_{j=1}^n\|A\|_2^2\|e_j\|_2^2=n\|A\|_2^2\end{align*} But instead of $\|A\|$ we have $\|A\|_2$. Is the above correct? If yes, can we get to $\|A\|$ ? (Wondering)

This idea will work, we just need to note two small things:

1) For a set $S$ of non-negative numbers -- which $S=\{\|Ax\|_{2} : \|x\|_{2}\leq 1\}$ is -- $\sup_{x\in S} x^{2}=\left(\sup_{x\in S} x\right)^{2}.$ This follows from the continuity and monotonicity of the squaring function $x\mapsto x^{2}$ on the non-negative half-line.

2) For each $e_{j}$, $\|Ae_{j}\|_{2}^{2}\leq \|A\|^{2}$, because, using point (1) above,
$$\|A\|^{2}=\left(\sup_{\|x\|_{2}\leq 1}\|Ax\|_{2} \right)^{2}=\sup_{\|x\|_{2}\leq 1}\|Ax\|^{2}_{2}\geq \|Ae_{j}\|^{2}_{2}.$$
 
Last edited:
GJA said:
This idea will work, we just need to note two small things:

1) For a set $S$ of non-negative numbers -- which $S=\{\|Ax\|_{2} : \|x\|_{2}\leq 1\}$ is -- $\sup_{x\in S} x^{2}=\left(\sup_{x\in S} x\right)^{2}.$ This follows from the continuity and monotonicity of the squaring function $x\mapsto x^{2}$ on the non-negative half-line.

2) For each $e_{j}$, $\|Ae_{j}\|_{2}^{2}\leq \|A\|^{2}$, because, using point (1) above,
$$\|A\|^{2}=\left(\sup_{\|x\|_{2}\leq 1}\|Ax\|_{2} \right)^{2}=\sup_{\|x\|_{2}\leq 1}\|Ax\|^{2}_{2}\geq \|Ae_{j}\|^{2}_{2}.$$

Ah I see! Thank you so much! (Yes)
 

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