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The higher-order guaranteed lower eigenvalue bounds of the Laplacian in the recent work by Carstensen et al. (Numer Math 149(2):273–304, 2021) require a parameter $$C_{\text {st},1}$$ C st , 1 that is found not robust as the polynomial degree p increases. This is related to the $$H^1$$ H 1 stability bound of the $$L^{2}$$ L 2 projection onto polynomials of degree at most p and its growth $$C_{\textrm{st, 1}}\propto (p+1)^{1/2}$$ C st, 1 ∝ ( p + 1 ) 1 / 2 as $$p \rightarrow \infty $$ p → ∞ . A similar estimate for the Galerkin projection holds with a p-robust constant $$C_{\text {st},2}$$ C st , 2 and $$C_{\text {st},2} \le 2$$ C st , 2 ≤ 2 for right-isosceles triangles. This paper utilizes the new inequality with the constant $$C_{\text {st},2}$$ C st , 2 to design a modified hybrid high-order eigensolver that directly computes guaranteed lower eigenvalue bounds under the idealized hypothesis of exact solve of the generalized algebraic eigenvalue problem and a mild explicit condition on the maximal mesh-size in the simplicial mesh. A key advance is a p-robust parameter selection. The analysis of the new method with a different fine-tuned volume stabilization allows for a priori quasi-best approximation and improved $$L^{2}$$ L 2 error estimates as well as a stabilization-free reliable and efficient a posteriori error control. The associated adaptive mesh-refining algorithm performs superior in computer benchmarks with striking numerical evidence for optimal higher empirical convergence rates.
The higher-order guaranteed lower eigenvalue bounds of the Laplacian in the recent work by Carstensen et al. (Numer Math 149(2):273–304, 2021) require a parameter $$C_{\text {st},1}$$ C st , 1 that is found not robust as the polynomial degree p increases. This is related to the $$H^1$$ H 1 stability bound of the $$L^{2}$$ L 2 projection onto polynomials of degree at most p and its growth $$C_{\textrm{st, 1}}\propto (p+1)^{1/2}$$ C st, 1 ∝ ( p + 1 ) 1 / 2 as $$p \rightarrow \infty $$ p → ∞ . A similar estimate for the Galerkin projection holds with a p-robust constant $$C_{\text {st},2}$$ C st , 2 and $$C_{\text {st},2} \le 2$$ C st , 2 ≤ 2 for right-isosceles triangles. This paper utilizes the new inequality with the constant $$C_{\text {st},2}$$ C st , 2 to design a modified hybrid high-order eigensolver that directly computes guaranteed lower eigenvalue bounds under the idealized hypothesis of exact solve of the generalized algebraic eigenvalue problem and a mild explicit condition on the maximal mesh-size in the simplicial mesh. A key advance is a p-robust parameter selection. The analysis of the new method with a different fine-tuned volume stabilization allows for a priori quasi-best approximation and improved $$L^{2}$$ L 2 error estimates as well as a stabilization-free reliable and efficient a posteriori error control. The associated adaptive mesh-refining algorithm performs superior in computer benchmarks with striking numerical evidence for optimal higher empirical convergence rates.
We establish an a priori error analysis for the lowest-order Raviart–Thomas finite element discretization of the nonlinear Gross-Pitaevskii eigenvalue problem. Optimal convergence rates are obtained for the primal and dual variables as well as for the eigenvalue and energy approximations. In contrast to conforming approaches, which naturally imply upper energy bounds, the proposed mixed discretization provides a guaranteed and asymptotically exact lower bound for the ground state energy. The theoretical results are illustrated by a series of numerical experiments.
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