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Consider the differential dλ of the matrix λ over an infinitesimal increments of two independent real variables x Reλac and y Imλac [see Eqs. (7) and (9)]: dλ=Θac(dx+idy) +Θac†(dx-idy).To develop the notion of the matrix gradient (similar to the usual gradient) we first calculate the Euclidean norm ||dλ|| of dλ: ||dλ2||=(dx2+dy2)[tr(A2)nx2+tr(B2)ny2+2tr(AB)nxny],where AΘac+Θac†, Bi(Θac-Θac†) and where (nx,ny)=(dx,dy)/dx2+dy2is the normal vector over the direction of the small increment. The (modulus of) matrix gradient is defined by maximizing over n(nx,ny): 14maxn||dλ2||=12(dx2+dy2)[tr(ΘacΘac†) +||tr(Θac2)||].As follows from tr(AB)≤tr(A2)tr(B2), the quantity maxn||dλ2||4(dx2+dy2)is limited from above by tr(ΘacΘ ac†)=||Θac2||, and from below by12tr(ΘacΘac†).
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Consider the differential dλ of the matrix λ over an infinitesimal increments of two independent real variables x Reλac and y Imλac [see Eqs. (7) and (9)]: dλ=Θac(dx+idy) +Θac†(dx-idy).To develop the notion of the matrix gradient (similar to the usual gradient) we first calculate the Euclidean norm ||dλ|| of dλ: ||dλ2||=(dx2+dy2)[tr(A2)nx2+tr(B2)ny2+2tr(AB)nxny],where AΘac+Θac†, Bi(Θac-Θac†) and where (nx,ny)=(dx,dy)/dx2+dy2is the normal vector over the direction of the small increment. The (modulus of) matrix gradient is defined by maximizing over n(nx,ny): 14maxn||dλ2||=12(dx2+dy2)[tr(ΘacΘac†) +||tr(Θac2)||].As follows from tr(AB)≤tr(A2)tr(B2), the quantity maxn||dλ2||4(dx2+dy2)is limited from above by tr(ΘacΘ ac†)=||Θac2||, and from below by 12tr(ΘacΘac†). Thus, ||Θac2|| can be taken as an adequate characteristics of the matrix gradient.
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