Research
On-device research index

arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,695 papers · 148 categories

Trend · papers per month

1223 · Jun 202019922001200920172026
15 results for metamaterials

A framework uses deep generative modeling to design metamaterials efficiently.

problem Designing metamaterials with complex properties is challenging due to high-dimensional design space and high computational cost.
method A variational autoencoder (VAE) and a regressor are trained on a large database to map microstructures to a latent space, enabling interpolation and manipulation of microstructures.
result The latent space provides a distance metric for shape similarity and encoding meaningful patterns of variation, enabling efficient design of microstructures and multiscale systems.

Unified theory solves strain compatibility and elasticity of origami metamaterials.

problem Understanding and controlling the morphing paths of origami metamaterials.
method Unified theory for a wide array of origami tessellations, solving strain compatibility and elasticity.
result Origami metamaterials exhibit equal but opposite in-plane and out-of-plane Poisson's ratios and bending energy depends on strain gradient.

MetaNOR learns common nonlocal kernels for efficient metamaterial modeling.

problem Efficiently modeling wave propagation in new metamaterials.
method Meta-learns a common nonlocal kernel from existing tasks and transfers this knowledge to new tasks with minimal data.
result Substantial improvements in sampling efficiency for new metamaterials.

METASET selects diverse unit cells for efficient data-driven metamaterial design.

problem Imbalanced datasets in unit cells can bias data-driven metamaterial design.
method METASET uses similarity metrics and DPPs to select diverse subsets of unit cells.
result Smaller, diverse subsets improve search process and structural performance.

Enhances topology optimization with multiclass microstructures using latent variable Gaussian process.

problem Lack of an inherent ordering or distance measure between different classes of microstructures.
method Extended latent-variable Gaussian process (LVGP) models to multi-response LVGP (MR-LVGP) models for metamaterials.
result Improved performance through consistent load-transfer paths for micro- and macro-structures.

Bayesian-guided method selects optimal design from large candidate pool.

problem Optimizing complex structures with high-fidelity evaluations.
method Bayesian active learning with surrogate modeling.
result Optimal design identified with minimal oracle evaluations.

PIMA autoencoders discover shared features in multimodal scientific data.

problem Discovering shared information in high-throughput scientific datasets.
method Physics-informed multimodal autoencoders (PIMA) with Gaussian mixture prior and product of experts formulation.
result Accurate cross-modal inference between images and mechanical stress-strain response in lattice metamaterials.

Scalable GP model tackles big data, categorical factors, and multiple responses.

problem Handling big datasets, categorical inputs, and multiple responses in Gaussian processes.
method Latent variable Gaussian process (LVGP) with variational inference for scalability and interpretability.
result The method scales well for large datasets and outperforms state-of-the-art methods.

The point of the paper is to show some limitations of geometrical optics in the analysis of subwavelength focusing. We analyze the resolution of the image of a line source radiating in the Maxwell fisheye and the Veselago-Pendry slab lens. The former optical medium is deduced from the stereographic projection of a virt…

2009-12-01abs ↗pdf ↗