English
Same kernel equality as in the transpose case, possibly with A^T.
Русский
Та же равенство ядер для варианта с транспонированием.
LaTeX
$$$ \ker\big(A^{T} A\big) \cdot \mathrm{mulVecLin} = \ker\big(A\, \mathrm{mulVecLin}\big). $$$
Lean4
theorem ker_mulVecLin_transpose_mul_self (A : Matrix m n R) :
LinearMap.ker (Aᵀ * A).mulVecLin = LinearMap.ker (mulVecLin A) :=
by
ext x
simp only [LinearMap.mem_ker, mulVecLin_apply, ← mulVec_mulVec]
constructor
· intro h
replace h := congr_arg (dotProduct x) h
rwa [dotProduct_mulVec, dotProduct_zero, vecMul_transpose, dotProduct_self_eq_zero] at h
· intro h
rw [h, mulVec_zero]