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Numerical analysis demonstrates strong convergence and efficient preconditioning for space-time parabolic equations, highlighting robust solver performance.
We propose a least squares formulation for abstract parabolic equations in the natural L²(0,T;V^ )× H L 2 ( 0 , T ; V ⋆ ) × H norm which only relies on natural regularity assumptions on the data of the problem. The resulting bilinear form then is symmetric, coercive, and continuous and contains the V^ V ⋆ -norm. We propose a solution approach that uses a conforming Galerkin discretization of an equivalent saddle point problem to circumvent the evaluation of V^ V ⋆ -norms. We prove strong convergence of discrete solutions towards continuous solutions and provide a preconditioner for efficient numerical solution of the discrete saddle point problem. We illustrate our analytical findings by selected numerical experiments.
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Hinze et al. (2026) studied this question.
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