Source authenticatedSettles the "if it exists" part for every p: a finite size-independent constant Cp exists exactly when 1<p<∞. The proof gives some constant, not the best one, for complex matrices of every size, square or rectangular.
At p=1 no constant exists, already for 2×2 matrices, turning Audenaert and Kittaneh's numerical C1≥40 into C1=∞. At p=∞ none exists on 3×3 matrices, as they already knew.
For diagonal matrices and p≥256 the best constant is an explicit Kp, the maximum of a ratio over the family (−t,1,1),(1,−t,1),(1,1,−t), t∈[1/2,2], with 939p/2000<Kp≤p. Since diagonal matrices are matrices, 939p/2000<Cp<∞ for p≥256.
Open: the best Cp for general matrices (except C2=1) and the best diagonal constant for 1<p<256; the cutoff 256 is not claimed optimal. All of this is in Lean except the one-line step from diagonal to general matrices.
Settles the "if it exists" part for every p: a finite size-independent constant Cp exists exactly when 1<p<∞. The proof gives some constant, not the best one, for complex matrices of every size, square or rectangular.
At p=1 no constant exists, already for 2×2 matrices, turning Audenaert and Kittaneh's numerical C1≥40 into C1=∞. At p=∞ none exists on 3×3 matrices, as they already knew.
For diagonal matrices and p≥256 the best constant is an explicit Kp, the maximum of a ratio over the family (−t,1,1),(1,−t,1),(1,1,−t), t∈[1/2,2], with 939p/2000<Kp≤p. Since diagonal matrices are matrices, 939p/2000<Cp<∞ for p≥256.
Open: the best Cp for general matrices (except C2=1) and the best diagonal constant for 1<p<256; the cutoff 256 is not claimed optimal. All of this is in Lean except the one-line step from diagonal to general matrices.