Safe Zeroth-Order Convex Optimization Using Quadratic Local Approximations

We address black-box convex optimization problems, where the objective and constraint functions are not explicitly known but can be sampled within the feasible set. The challenge is thus to generate a sequence of feasible points converging towards an optimal solution. By leveraging the knowledge of the smoothness properties of the objective and constraint functions, we propose a novel zeroth-order method, SZO-QQ, that iteratively computes quadratic approximations of the constraint functions, constructs local feasible sets and optimizes over them. We prove convergence of the sequence of the objective values generated at each iteration to the minimum. Through experiments, we show that our method can achieve faster convergence compared with state-of-the-art zeroth-order approaches to convex optimization

Safe Zeroth-Order Optimization Using Quadratic Local Approximations

This paper addresses black-box smooth optimization problems, where the objective and constraint functions are not explicitly known but can be queried. The main goal of this work is to generate a sequence of feasible points converging towards a KKT primal-dual pair. Assuming to have prior knowledge on the smoothness of the unknown objective and constraints, we propose a novel zeroth-order method that iteratively computes quadratic approximations of the constraint functions, constructs local feasible sets and optimizes over them. Under some mild assumptions, we prove that this method returns an $\eta$-KKT pair (a property reflecting how close a primal-dual pair is to the exact KKT condition) within $O({1}/{\eta^{2}})$ iterations. Moreover, we numerically show that our method can achieve faster convergence compared with some state-of-the-art zeroth-order approaches. The effectiveness of the proposed approach is also illustrated by applying it to nonconvex optimization problems in optimal control and power system operation.Comment: arXiv admin note: text overlap with arXiv:2211.0264

Topological Surface States in a Gyroid Acoustic Crystal

The acoustic properties of an acoustic crystal consisting of acoustic channels designed according to the gyroid minimal surface embedded in a 3D rigid material are investigated. The resulting gyroid acoustic crystal is characterized by a spin-1 Weyl and a charge-2 Dirac degenerate points that are enforced by its nonsymmorphic symmetry. The gyroid geometry and its symmetries produce multi-fold topological degeneracies that occur naturally without the need for ad hoc geometry designs. The non-trivial topology of the acoustic dispersion produces chiral surface states with open arcs, which manifest themselves as waves whose propagation is highly directional and remains confined to the surfaces of a 3D material. Experiments on an additively manufactured sample validate the predictions of surface arc states and produce negative refraction of waves at the interface between adjoining surfaces. The topological surface states in a gyroid acoustic crystal shed light on nontrivial bulk and edge physics in symmetry-based compact continuum materials, whose capabilities augment those observed in ad hoc designs. The continuous shape design of the considered acoustic channels and the ensuing anomalous acoustic performance suggest this class of phononic materials with semimetal-like topology as effective building blocks for acoustic liners and load-carrying structural components with sound proofing functionality. &nbsp;</p

Hierarchical Masked 3D Diffusion Model for Video Outpainting

Video outpainting aims to adequately complete missing areas at the edges of video frames. Compared to image outpainting, it presents an additional challenge as the model should maintain the temporal consistency of the filled area. In this paper, we introduce a masked 3D diffusion model for video outpainting. We use the technique of mask modeling to train the 3D diffusion model. This allows us to use multiple guide frames to connect the results of multiple video clip inferences, thus ensuring temporal consistency and reducing jitter between adjacent frames. Meanwhile, we extract the global frames of the video as prompts and guide the model to obtain information other than the current video clip using cross-attention. We also introduce a hybrid coarse-to-fine inference pipeline to alleviate the artifact accumulation problem. The existing coarse-to-fine pipeline only uses the infilling strategy, which brings degradation because the time interval of the sparse frames is too large. Our pipeline benefits from bidirectional learning of the mask modeling and thus can employ a hybrid strategy of infilling and interpolation when generating sparse frames. Experiments show that our method achieves state-of-the-art results in video outpainting tasks. More results are provided at our https://fanfanda.github.io/M3DDM/.Comment: ACM MM 2023 accepte

Shifts in Soil Microbial Community Composition, Function, and Co-occurrence Network of Phragmites australis in the Yellow River Delta

Soil microorganisms play vital roles in regulating biogeochemical processes. The composition and function of soil microbial community have been well studied, but little is known about the responses of bacterial and fungal communities to different habitats of the same plant, especially the inter-kingdom co-occurrence pattern including bacteria and fungi. Herein, we used high-throughput sequencing to investigate the bacterial and fungal communities of five Phragmites australis habitats in the Yellow River Delta and constructed their inter-kingdom interaction network by network analysis. The results showed that richness did not differ significantly among habitats for either the bacterial or fungal communities. The distribution of soil bacterial community was significantly affected by soil physicochemical properties, whereas that of the fungal community was not. The main functions of the bacterial and fungal communities were to participate in the degradation of organic matter and element cycling, both of which were significantly affected by soil physicochemical properties. Network analysis revealed that bacteria and fungi participated in the formation of networks through positive interactions; the role of intra-kingdom interactions were more important than inter-kingdom interactions. In addition, rare species acted as keystones played a critical role in maintaining the network structure, while NO3−−N likely played an important role in maintaining the network topological properties. Our findings provided insights into the inter-kingdom microbial co-occurrence network and response of the soil microbial community composition and function to different P. australis habitats in coastal wetlands, which will deepen our insights into microbial community assembly in coastal wetlands

Moire-Driven Topological Transitions and Extreme Anisotropy in Elastic Metasurfaces

The twist angle between a pair of stacked 2D materials has been recently shown to control remarkable phenomena, including the emergence of flat-band superconductivity in twisted graphene bilayers, of higher-order topological phases in twisted moir&eacute; superlattices, and of topological polaritons in twisted hyperbolic metasurfaces. These discoveries, at the foundations of the emergent field of twistronics, have so far been mostly limited to explorations in atomically thin condensed matter and photonic systems, with limitations on the degree of control over geometry and twist angle, and inherent challenges in the fabrication of carefully engineered stacked multilayers. Here, this work extends twistronics to widely reconfigurable macroscopic elastic metasurfaces consisting of LEGO pillar resonators. This work demonstrates highly tailored anisotropy over a single-layer metasurface driven by variations in the twist angle between a pair of interleaved spatially modulated pillar lattices. The resulting quasi-periodic moir&eacute; patterns support topological transitions in the isofrequency contours, leading to strong tunability of highly directional waves. The findings illustrate how the rich phenomena enabled by twistronics and moir&eacute; physics can be translated over a single-layer metasurface platform, introducing a practical route toward the observation of extreme phenomena in a variety of wave systems, potentially applicable to both quantum and classical settings without multilayered fabrication requirements. &nbsp;</p