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Quantum Algorithm for Nonlinear and Stochastic Homogenization via a Young-Measure based Linear Programming Formulation
Announce Type: new Abstract: We study quantum algorithms for nonlinear and stochastic homogenization via a Young-measure based linear programming (LP) formulation, which lifts the nonlinear problem to a linear one in higher dimensions by treating the microscale, the gradient, and possible random variables as independent variables, thereby capturing effective macroscopic quantities without directly resolving fine-scale oscillations. The resulting LP is large but structured, and its...
Young Measure Based Quantum Linear Programming Algorithms for Nonlinear/Stochastic Multiscale Partial Differential Equations and Homogenization
arXiv:2606.06165v2 Announce Type: replace Abstract: We study quantum algorithms for nonlinear and stochastic homogenization via a Young-measure based linear programming (LP) formulation, which lifts the nonlinear problem to a linear one in higher dimensions by treating the microscale, the gradient, and possible random variables as independent variables, thereby capturing effective macroscopic quantities without directly resolving fine-scale oscillations. The resulting LP is large but...
Parameter Tuning with Generalization Guarantees for GPU-Accelerated Linear Programming
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Show HN: Solving complex optimization problems with Google OR-Tools in browser
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High-Order Schemes for Hyperbolic Conservation Laws Using Young Measures
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Structure-preserving Optimal Kron-based Reduction of Radial Distribution Networks
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Scalable Joint Resource Allocation for SLO-Constrained LLM Inference in Heterogeneous GPU Clouds
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Clustering-enhanced adaptive Benders decomposition for energy systems planning optimization
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Effect of Demographic Bias on Skin Lesion Classification
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