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arXiv 2018年

作者： Andrzejewski, K. Brihaye, Y. Gonera, C. Gonera, J. Nski, P. Kosi Slanka, P. Ma Department of Computer Science Faculty of Physics and Applied Informatics University of Lodz Poland Physique-Mathématique Université de Mons-Hainaut Mons Belgium

The quasiclassical theory of massless chiral fermions is considered. The effective action is derived using time-dependent variational principle which provides a clear interpretation of relevant canonical variables. As a result their transformation properties under the action of Lorentz group are derived from first principles. Copyright © 2018, The Authors. All rights reserved.

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Detecting lithium plating dynamics in a solid-state battery with operando X-ray computed tomography using machine learning

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npj Computational Materials 2023年第1期9卷 1402-1410页

作者： Ying Huang David Perlmutter Andrea Fei-Huei Su Jerome Quenum Pavel Shevchenko Dilworth Y.Parkinson Iryna V.Zenyuk Daniela Ushizima Department of Materials Science&Engineering University of California IrvineIrvineCaliforniaUSA National Fuel Cell Research Center University of California IrvineIrvineCaliforniaUSA Applied Math and Computational Research Division Lawrence Berkeley National LaboratoryBerkeleyCaliforniaUSA Department of Chemical&Biomolecular Engineering University of California IrvineIrvineCaliforniaUSA Department of Electrical Engineering and Computer Sciences College of EngineeringUniversity of California BerkeleyBerkeleyCaliforniaUSA Advanced Photon Source Argonne National Laboratory9700 South Cass AvenueLemontIllinoisUSA Advanced Light Source Lawrence Berkeley National LaboratoryBerkeleyCaliforniaUSA Berkeley Institute for Data Science University of California BerkeleyBerkeleyCaliforniaUSA

Operando X-ray micro-computed tomography(µCT)provides an opportunity to observe the evolution of Li structures inside pouch *** is an essential step to quantitatively analyzingµCT datasets but is challenging to achieve on operando Li-metal battery datasets due to the low X-ray attenuation of the Li metal and the sheer size of the ***,we report a computational approach,batteryNET,to train an Iterative Residual U-Net-based network to detect Li *** resulting semantic segmentation shows singular Li-related component changes,addressing diverse morphologies in the *** addition,visualizations of the dead Li are provided,including calculations about the volume and effective thickness of electrodes,deposited Li,and redeposited *** also report discoveries about the spatial relationships between these *** approach focuses on a method for analyzing battery performance,which brings insight that significantly benefits future Li-metal battery design and a semantic segmentation transferrable to other datasets.

关键词： battery lithium state

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The immune system and other cognitive systems

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Complexity 2001年第5期6卷 14-21页

作者： Hershberg, Uri Efroni, Sol Interdisciplinary Center for Neuronal Computation Hebrew University Jerusalem Israel Computer Science and Applied Math Department Immunology Department Weizmann Institute of Science Rehovot Israel

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Expansion of High-Dimensional Cubical Complexes: with Application to Quantum Locally Testable Codes

Expansion of High-Dimensional Cubical Complexes: with Applic...

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Annual IEEE Symposium on Foundations of computer science

作者： Irit Dinur Ting-Chun Lin Thomas Vidick Department of Applied Math and Computer Science The Weizmann Institute of Science Rehovot Israel Department of Physics University of California at San Diego San Diego USA Hon Hai Research Institute Taipei Taiwan

ISBN: (数字)9798331516741

ISBN: (纸本)9798331516758

We introduce a high-dimensional cubical complex, for any dimension $t \in \mathbb{N}$ , and apply it to the design of quantum locally testable codes. Our complex is a natural generalization of the constructions by Panteleev and Kalachev and by Dinur et. al of a square complex (case $t=2$ ), which have been applied to the design of classical locally testable codes (LTC) and quantum low-density parity check codes (qLDPC) respectively. We turn the geometric (cubical) complex into a chain complex by relying on constant-sized local codes $h_{1}, \ldots,h_{t}$ as gadgets. A recent result of Panteleev and Kalachev on existence of tuples of codes that are product expanding enables us to prove lower bounds on the cycle and co-cycle expansion of our chain complex. For $t=4$ our construction gives a new family of “almost-good” quantum LTCs - with constant relative rate, inverse-polylogarithmic relative distance and soundness, and constant-size parity checks. Both the distance of the quantum code and its local testability are proven directly from the cycle and co-cycle expansion of our chain complex.

关键词： computer science Parity check codes

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Crystallography of honeycomb formation under geometric frustration

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Proceedings of the National Academy of sciences of the United States of America 2022年第48期119卷 e2205043119-e2205043119页

作者： Fard, Golnar Gharooni Zhang, Daisy Jiménez, Francisco López Peleg, Orit Department of Computer Science University of Colorado Boulder 80309 CO United States Department of Computer Science Princeton University 08544 NJ United States Ann and H.J. Smead Department of Aerospace Engineering Sciences University of Colorado Boulder 80309 CO United States Department of Physics University of Colorado Boulder 80309 CO United States Department of Applied Math University of Colorado Boulder 80309 CO United States Department of Ecology and Evolutionary Biology University of Colorado Boulder 80309 CO United States BioFrontiers Institute University of Colorado Boulder 80309 CO United States Santa Fe Institute Santa Fe 87501 NM United States

As honeybees build their nests in preexisting tree cavities, they must deal with the presence of geometric constraints, resulting in nonregular hexagons and topological defects in the comb. In this work, we study how bees adapt to their environment in order to regulate the comb structure. Specifically, we identify the irregularities in honeycomb structure in the presence of various geometric frustrations. We 3D-print experimental frames with a variety of constraints imposed on the imprinted foundations. The combs constructed by the bees show clear evidence of recurring patterns in response to specific geometric frustrations on these starter frames. Furthermore, using an experimental-modeling framework, we demonstrate that these patterns can be successfully modeled and replicated through a simulated annealing process, in which the minimized potential is a variation of the Lennard-Jones potential that considers only first-neighbor interactions according to a Delaunay triangulation. Our simulation results not only confirm the connection between honeycomb structures and other crystal systems such as graphene, but also show that irregularities in the honeycomb structure can be explained as the result of analogous interactions between cells and their immediate surroundings, leading to emergent global order. Additionally, our computational model can be used as a first step to describe specific strategies that bees use to effectively solve geometric mismatches while minimizing cost of comb building. Copyright © 2022 the Author(s). Published by PNAS.

关键词： behavioral assays collective behavior honey bees honeycomb mathematical modelling

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Shape reconstruction of 3D bilaterally symmetric surfaces

Shape reconstruction of 3D bilaterally symmetric surfaces

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International Conference on Image Analysis and Processing

作者： I. Shimshoni Y. Moses M. Lindenbaumlpr Department of Industrial Engineering & Management Technion-Israel Institute of Technology Haifa Israel Department of Applied Math Weizmann Institute of Science Rehovot Israel Department of Computer Science Technion-Israel Institute of Technology Haifa Israel

The paper presents a new approach for shape recovery based on integrating geometric and photometric information. We consider 3D objects which are symmetric with respect to a plane (e.g., faces) and their reconstruction from a single image. Both the viewpoint and the illumination are not necessarily frontal. In principle, no correspondence between symmetric points is required, but knowledge about a few corresponding pairs accelerates the process. The basic idea is that an image taken from a general, non-frontal viewpoint, under non-frontal illumination can be regarded as a pair of images of half of the object, taken from two different viewing positions and two different lighting directions. We show that integrating the photometric and geometric information yields the unknown lighting and viewing parameters, as well as dense correspondence between pairs of symmetric points. As a result, a dense shape recovery of the object is computed. The method has been implemented and tested experimentally on simulated and real data.

关键词： Shape Surface reconstruction Electrical capacitance tomography Image reconstruction Photometry Lighting computer science Programmable logic arrays Read only memory Neutron spin echo

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Max-Information, Differential Privacy, and Post-selection Hypothesis Testing

Max-Information, Differential Privacy, and Post-selection Hy...

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Annual IEEE Symposium on Foundations of computer science

作者： Ryan Rogers Aaron Roth Adam Smith Om Thakkar Applied Math and Computational Sciences University of Pennsylvania Philadelphia PA USA Computer and Information Science University of Pennsylvania Philadelphia PA USA Computer Science and Engineering Department Pennsylvania State University University Park PA USA

ISBN: (纸本)9781509039340

In this paper, we initiate a principled study of how the generalization properties of approximate differential privacy can be used to perform adaptive hypothesis testing, while giving statistically valid p-value corrections. We do this by observing that the guarantees of algorithms with bounded approximate max-information are sufficient to correct the p-values of adaptively chosen hypotheses, and then by proving that algorithms that satisfy (∈,δ)-differential privacy have bounded approximate max information when their inputs are drawn from a product distribution. This substantially extends the known connection between differential privacy and max-information, which previously was only known to hold for (pure) (∈,0)-differential privacy. It also extends our understanding of max-information as a partially unifying measure controlling the generalization properties of adaptive data analyses. We also show a lower bound, proving that (despite the strong composition properties of max-information), when data is drawn from a product distribution, (∈,δ)-differentially private algorithms can come first in a composition with other algorithms satisfying max-information bounds, but not necessarily second if the composition is required to itself satisfy a nontrivial max-information bound. This, in particular, implies that the connection between (∈,δ)-differential privacy and max-information holds only for inputs drawn from product distributions, unlike the connection between (∈,0)-differential privacy and max-information.

关键词： Privacy Algorithm design and analysis Testing Data analysis Probability Data privacy computer science

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Solving the Families In the Wild Kinship Verification Challenge by Program Synthesis

arXiv

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arXiv 2021年

作者： Huang, Junyi Strome, Maxwell Benjamin Jenkins, Ian Williams, Parker Feng, Bo Wang, Yaning Wang, Roman Bagri, Vaibhav Cheng, Newman Drori, Iddo Department of Mathematics Columbia University United States Department of Computer Science Columbia University United States Department of Applied Physics and Math Columbia University United States Department of Electrical Engineering Columbia University United States Department of Electrical Engineering and Computer Science MIT United States

Kinship verification is the task of determining whether a parent-child, sibling, or grandparent-grandchild relationship exists between two people and is important in social media applications, forensic investigations, finding missing children, and reuniting families. We demonstrate high quality kinship verification by participating in the 2021 Recognizing Families in the Wild challenge which provides the largest publicly available dataset in the field. Our approach is among the top 3 winning entries in the competition. We ensemble models written by both human experts and a foundation model, OpenAI Codex, trained on text and code. We use Codex to generate model variants, and also demonstrate its ability to generate entire running programs for kinship verification tasks of specific relationships. © 2021, CC BY.

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RAIN: Reinforcement Algorithms for Improving Numerical Weather and Climate Models

arXiv

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arXiv 2024年

作者： Nath, Pritthijit Moss, Henry Shuckburgh, Emily Webb, Mark Department of Applied Math and Theoretical Physics University of Cambridge United Kingdom Department of Computer Science and Technology University of Cambridge United Kingdom Met Office Hadley Centre United Kingdom

This study explores integrating reinforcement learning (RL) with idealised climate models to address key parameterisation challenges in climate science. Current climate models rely on complex mathematical parameterisations to represent sub-grid scale processes, which can introduce substantial uncertainties. RL offers capabilities to enhance these parameterisation schemes, including direct interaction, handling sparse or delayed feedback, continuous online learning, and long-term optimisation. We evaluate the performance of eight RL algorithms on two idealised environments: one for temperature bias correction, another for radiative-convective equilibrium (RCE) imitating real-world computational constraints. Results show different RL approaches excel in different climate scenarios with exploration algorithms performing better in bias correction, while exploitation algorithms proving more effective for RCE. These findings support the potential of RL-based parameterisation schemes to be integrated into global climate models, improving accuracy and efficiency in capturing complex climate dynamics. Overall, this work represents an important first step towards leveraging RL to enhance climate model accuracy, critical for improving climate understanding and predictions. Code accessible at https://***/p3jitnath/climate-rl. © 2024, CC BY-NC-SA.

关键词： Digital elevation model

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Fairness in scheduling 95

Fairness in scheduling

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Proceedings of the sixth annual ACM-SIAM symposium on Discrete algorithms

作者： Miklos Ajtai James Aspnes Moni Naor Yuval Rabani Leonard J. Schulman Orli Waarts IBM Research Division Almaden Research Center Dept. of Computer Science Yale University Dept. of Applied Math and Computer Science Weizmann Institute Israel Department of Computer Science University of Toronto Toronto Ontario M5S 1A4 Computer Science Division U.C. Berkeley

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