Direct algorithms sample codon sequences from Boltzmann distributions using tensor-based secondary structure free energy models for RNA design under codon constraints.
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Rank-adaptive tensor decompositions enable memory-efficient dynamical simulations of Schrödinger's equation by compressing partially entangled quantum states while controlling truncation error via SVD thresholds.
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Direct RNA sequence design under codon constraints using expressive tensor-based secondary structure models
Direct algorithms sample codon sequences from Boltzmann distributions using tensor-based secondary structure free energy models for RNA design under codon constraints.
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Dynamical Simulations of Schr\"odinger's Equation via Rank-Adaptive Tensor Decompositions
Rank-adaptive tensor decompositions enable memory-efficient dynamical simulations of Schrödinger's equation by compressing partially entangled quantum states while controlling truncation error via SVD thresholds.