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  "body": "\n## Summary\n\nThe Frobenius norm of a matrix is the square root of the sum of the squares of the absolute values of its entries.\nIt is the Euclidean length of the matrix seen as a long vector, and it comes from the inner product $\\ip{A}{B} = \\tr(B^* A)$.\nIt is a submultiplicative [[matrix norm|54T6Y6DSY4]] that is easy to compute.\nIt equals the square root of the sum of the squares of the [[singular values|09VMDSRXWJ]].\n\n## Explanations\n\n### L1 human\n\nWrite all entries of a matrix in one long row and measure the length of that row as in the theorem of Pythagoras.\nThat length is the Frobenius norm.\nFor $\\begin{pmatrix} 1 \u0026 2 \\\\ 3 \u0026 4 \\end{pmatrix}$ it is $\\sqrt{1 + 4 + 9 + 16} = \\sqrt{30}$.\nIt is used to measure how far one matrix is from another, for example in least squares fitting and low rank approximation.\n",
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