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Let $s_1,s_2: \mathbb{R}^{2\times 2} \mapsto \mathbb{R}_+$, $s_{1}\left(\cdot\right)\ge s_{2}\left(\cdot\right)\ge 0$, be the singular values of a $2\times2$ matrix. Is it true that $$\left|s_{1}\left(M+N\right)-s_{1}\left(N\right)\right|+\left|s_{2}\left(M+N\right)-s_{2}\left(N\right)\right|\leq s_{1}\left(M\right)+s_{2}\left(M\right)$$ for any two $2\times2$ real matrices $M$ and $N$?

Thanks in advance for any helpful answers.

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The paper is possibly relevant. – Neil Strickland Oct 6 '11 at 8:43

Here is a more general result.

Let $A$ and $B$ be arbitrary $n \times n$ complex matrices. Then, we have the weak-majorization:

$$ |s(A) - s(B)|\quad \prec_w\quad s(A-B)$$

This result implies your alleged inequality as a special case.

The above result follows from a famous theorem of Lidskii, which states that for Hermitian matrices $A$ and $B$,

$$ \lambda^\downarrow(A) - \lambda^\downarrow(B) \prec \lambda(A-B),$$ where $\lambda^\downarrow(A)$ lists eigenvalues of $A$ is decreasing order (notice that here the majorization is strict)

For more details, see for example, Exercise IV.3.1 in Matrix Analysis by R. Bhatia.

Alternatively, you can have a look (for the singular value majorization result) at Theorem 3.4.5 in Topics in Matrix Analysis by Horn and Johnson.

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Watch out, though, for the fact that Bhatia and Horn & Johnson use opposite conventions in the definiton of majorization. – Mark Meckes Oct 6 '11 at 13:31
@Mark: Really? Seems like Def. 3.2.8 in HJ is the same as condition (II.2) in Bhatia's book (considering only weak majorization). – Suvrit Oct 6 '11 at 13:57
Actually, I was thinking of Matrix Analysis by Horn and Johnson. It looks like they switched conventions between volumes. – Mark Meckes Oct 11 '11 at 21:49

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