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arXiv 2025年

作者： Tang, Yingheng Xu, Wenbin Cao, Jie Gao, Weilu Farrell, Steven Erichson, Benjamin Mahoney, Michael W. Nonaka, Andy Yao, Zhi Applied Mathematics and Computational Research Division Lawrence Berkeley National Laboratory BerkeleyCA United States National Energy Research Scientific Computing Center Lawrence Berkeley National Laboratory BerkeleyCA United States NSF National AI Institute for Student-AI Teaming University of Colorado at Boulder Boulder United States Department of Electrical and Computer Engineering The University of Utah Salt Lake CityUT United States Scientific Data Division Lawrence Berkeley National Laboratory BerkeleyCA United States International Computer Science Institute BerkeleyCA United States Department of Statistics University of California at Berkeley BerkeleyCA United States

Understanding and predicting the properties of inorganic materials is crucial for accelerating advancements in materials science and driving applications in energy, electronics, and beyond. Integrating material structure data with language-based information through multi-modal large language models (LLMs) offers great potential to support these efforts by enhancing human–AI interaction. However, a key challenge lies in integrating atomic structures at full resolution into LLMs. In this work, we introduce MatterChat, a versatile structure-aware multi-modal LLM that unifies material structural data and textual inputs into a single cohesive model. MatterChat employs a bridging module to effectively align a pretrained universal machine learning interatomic potential with a pretrained LLM, reducing training costs and enhancing flexibility. Our results demonstrate that MatterChat significantly improves performance in material property prediction and human-AI interaction, surpassing general-purpose LLMs such as GPT-4. We also demonstrate its usefulness in applications such as more advanced scientific reasoning and step-by-step material synthesis. © 2025, CC BY.

关键词： Structure (composition)

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Enhanced Superconducting Qubit Performance Through Ammonium Fluoride Etch

arXiv

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arXiv 2024年

作者： Kopas, Cameron J. Goronzy, Dominic P. Pham, Thang Torres Castanedo, Carlos G. Cheng, Matthew Cochrane, Rory Nast, Patrick Lachman, Ella Zhelev, Nikolay Z. Vallières, André Murthy, Akshay A. Oh, Jin-Su Zhou, Lin Kramer, Matthew J. Cansizoglu, Hilal Bedzyk, Michael J. Dravid, Vinayak P. Romanenko, Alexander Grassellino, Anna Mutus, Josh Y. Hersam, Mark C. Yadavalli, Kameshwar Rigetti Computing BerkeleyCA United States Department of Materials Science and Engineering Northwestern University EvanstonIL United States Center for Applied Physics and Superconducting Technologies Northwestern University EvanstonIL United States Department of Physics and Astronomy Northwestern University EvanstonIL United States Department of Physics University of Oregon EugeneOR United States Graduate Program in Applied Physics Northwestern University EvanstonIL60208 United States Fermi National Accelerator Laboratory BataviaIL United States Ames Laboratory U.S. Department of Energy AmesIA United States Northwestern University EvanstonIL United States Department of Chemistry Northwestern University EvanstonIL United States Department of Electrical and Computer Engineering Northwestern University EvanstonIL United States

The performance of superconducting qubits is often limited by dissipation and two-level systems (TLS) losses. The dominant sources of these losses are believed to originate from amorphous materials and defects at interfaces and surfaces, likely as a result of fabrication processes or ambient exposure. Here, we explore a novel wet chemical surface treatment at the Josephson junction-substrate and the substrate-air interfaces by replacing a buffered oxide etch (BOE) cleaning process with one that uses hydrofluoric acid followed by aqueous ammonium fluoride. We show that the ammonium fluoride etch process results in a statistically significant improvement in median T1 by ∼ 22% (p = 0.002), and a reduction in the number of strongly-coupled TLS in the tunable frequency range. Microwave resonator measurements on samples treated with the ammonium fluoride etch prior to niobium deposition also show ∼ 33% lower TLS-induced loss tangent compared to the BOE treated samples. As the chemical treatment primarily modifies the Josephson junction-substrate interface and substrate-air interface, we perform targeted chemical and structural characterizations to examine materials’ differences at these interfaces and identify multiple microscopic changes that could contribute to decreased TLS. © 2024, CC BY-NC-ND.

关键词： Fluorine compounds

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A multimodal framework for extraction and fusion of satellite images and public health data

引用

Scientific Data 2024年第1期11卷 634页

作者： Moukheiber, Dana Restrepo, David Cajas, Sebastián Andrés Montoya, María Patricia Arbeláez Celi, Leo Anthony Kuo, Kuan-Ting López, Diego M. Moukheiber, Lama Moukheiber, Mira Moukheiber, Sulaiman Osorio-Valencia, Juan Sebastian Purkayastha, Saptarshi Paddo, Atika Rahman Wu, Chenwei Kuo, Po-Chih Laboratory for Computational Physiology Massachusetts Institute of Technology Cambridge MA United States Departamento de Telemática Universidad del Cauca Cauca Popayán Colombia John A. Paulson School of Engineering and Applied Sciences Harvard University Boston MA United States School of Computer Science University College Dublin Dublin Ireland Grupo de Epidemiología Facultad Nacional de Salud Pública Universidad de Antioquia Medellín Colombia Department of Biostatistics Harvard TH Chan School of Public Health Boston MA United States Department of Medicine Beth Israel Deaconess Medical Center Boston MA United States Department of Computer Science National Tsing Hua University Hsinchu Taiwan Department of Computer Science Worcester Polytechnic Institute Worcester MA United States ScienteLab Cundinamarca Bogota Colombia Department of BioHealth Informatics Indiana University Luddy School of Informatics Computing and Engineering Indianapolis IN United States Department of Electrical Engineering and Computer Science University of Michigan Ann Arbor MI United States

In low- and middle-income countries, the substantial costs associated with traditional data collection pose an obstacle to facilitating decision-making in the field of public health. Satellite imagery offers a potential solution, but the image extraction and analysis can be costly and requires specialized expertise. We introduce SatelliteBench, a scalable framework for satellite image extraction and vector embeddings generation. We also propose a novel multimodal fusion pipeline that utilizes a series of satellite imagery and metadata. The framework was evaluated generating a dataset with a collection of 12,636 images and embeddings accompanied by comprehensive metadata, from 81 municipalities in Colombia between 2016 and 2018. The dataset was then evaluated in 3 tasks: including dengue case prediction, poverty assessment, and access to education. The performance showcases the versatility and practicality of SatelliteBench, offering a reproducible, accessible and open tool to enhance decision-making in public health. © The Author(s) 2024.

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Advancing quantum imaging through learning theory

arXiv

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arXiv 2025年

作者： Wang, Yunkai Oh, Changhun Liu, Junyu Jiang, Liang Zhou, Sisi Perimeter Institute for Theoretical Physics WaterlooONN2L 2Y5 Canada Department of Applied Mathematics University of Waterloo ONN2L 3G1 Canada Institute for Quantum Computing University of Waterloo ONN2L 3G1 Canada Department of Physics Korea Advanced Institute of Science and Technology Daejeon34141 Korea Republic of Department of Computer Science The University of Pittsburgh PittsburghPA15260 United States Pritzker School of Molecular Engineering The University of Chicago ChicagoIL60637 United States Department of Physics and Astronomy University of Waterloo ONN2L 3G1 Canada

We quantify performance of quantum imaging by modeling it as a learning task and calculating the Resolvable Expressive Capacity (REC). Compared to the traditionally applied Fisher information matrix approach, REC provides a single-parameter interpretation of overall imaging quality for specific measurements that applies in the regime of finite samples. We first examine imaging performance for two-point sources and generally distributed sources, referred to as compact sources, both of which have intensity distributions confined within the Rayleigh limit of the imaging system. Our findings indicate that REC increases stepwise as the sample number reaches certain thresholds, which are dependent on the source’s size. Notably, these thresholds differ between direct imaging and superresolution measurements (e.g., spatial-mode demultiplexing (SPADE) measurement in the case of Gaussian point spread functions (PSF)). REC also enables the extension of our analysis to more general scenarios involving multiple compact sources, beyond the previously studied scenarios. For closely spaced compact sources with Gaussian PSFs, our newly introduced orthogonalized SPADE method outperforms the naively separate SPADE method, as quantified by REC. Copyright © 2025, The Authors. All rights reserved.

关键词： Fisher information matrix

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Loss tangent fluctuations due to two-level systems in superconducting microwave resonators

arXiv

引用

arXiv 2024年

作者： Vallières, André Russell, Megan E. You, Xinyuan Garcia-Wetten, David A. Goronzy, Dominic P. Walker, Mitchell J. Bedzyk, Michael J. Hersam, Mark C. Romanenko, Alexander Lu, Yao Grassellino, Anna Koch, Jens McRae, Corey Rae H. Graduate Program in Applied Physics Northwestern University EvanstonIL60208 United States Fermi National Accelerator Laboratory BataviaIL60510 United States Department of Physics and Astronomy Northwestern University EvanstonIL60208 United States Department of Materials Science and Engineering Northwestern University EvanstonIL60208 United States Department of Chemistry Northwestern University EvanstonIL60208 United States Department of Electrical and Computer Engineering Northwestern University EvanstonIL60208 United States Center for Applied Physics and Superconducting Technologies Northwestern University EvanstonIL60208 United States Electrical Computing and Energy Engineering Department University of Colorado BoulderCO80309 United States Department of Physics University of Colorado BoulderCO80309 United States National Institute of Standards and Technology BoulderCO80305 United States

Superconducting microwave resonators are critical to quantum computing and sensing technologies. Additionally, they are common proxies for superconducting qubits when determining the effects of performance-limiting loss mechanisms such as from two-level systems (TLS). The extraction of these loss mechanisms is often performed by measuring the internal quality factor Qi as a function of power or temperature. In this work, we investigate large temporal fluctuations of Qi at low powers over periods of 12 to 16 hours (relative standard deviation σQi/Qi = 13%). These fluctuations are ubiquitous across multiple resonators, chips and cooldowns. We are able to attribute these fluctuations to variations in the TLS loss tangent due to two main indicators. First, measured fluctuations decrease as power and temperature increase. Second, for interleaved measurements, we observe correlations between low- and medium-power Qi fluctuations and an absence of correlations with high-power fluctuations. Agreement with the TLS loss tangent mean is obtained by performing measurements over a time span of a few hours. We hypothesize that, in addition to decoherence due to coupling to individual near-resonant TLS, superconducting qubits are affected by these observed TLS loss tangent fluctuations. © 2024, CC BY.

关键词： Qubits

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Intelligent scaling for 6G IoE services for resource provisioning

引用

PeerJ computer science 2021年 7卷 e755页

作者： Alharbi, Abdullah Alyami, Hashem Poongodi, M. Rauf, Hafiz Tayyab Kadry, Seifedine Department of Information Technology College of Computers and Information Technology Taif University Taif Saudi Arabia Department of Computer Science College of Computers and Information Technology Taif University Taif Saudi Arabia College of Science and Engineering Hamad Bin Khalifa University Doha Qatar Department of Computer Science Faculty of Engineering & Informatics University of Bradford Bradford United Kingdom Faculty of Applied Computing and Technology Noroff University College Kristiansand Norway

The proposed research motivates the 6G cellular networking for the Internet of Everything’s (IoE) usage empowerment that is currently not compatible with 5G. For 6G, more innovative technological resources are required to be handled by Mobile Edge computing (MEC). Although the demand for change in service from different sectors, the increase in IoE, the limitation of available computing resources of MEC, and intelligent resource solutions are getting much more significant. This research used IScaler, an effective model for intelligent service placement solutions and resource scaling. IScaler is considered to be made for MEC in Deep Reinforcement Learning (DRL). The paper has considered several requirements for making service placement decisions. The research also highlights several challenges geared by architectonics that submerge an Intelligent Scaling and Placement module. Subjects Algorithms and Analysis of Algorithms, Artificial Intelligence, Data Mining and Machine Learning, World Wide Web and Web science © Copyright 2021 Alharbi et al.

关键词： Internet of Everything

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Positioning as service for 5G IoT networks

Positioning as service for 5G IoT networks

引用

2021 Telecoms Conference, ConfTELE 2021

作者： El Boudani, Brahim Kanaris, Loizos Kokkinis, Akis Chrysoulas, Christos Dagiuklas, Tasos Stavrou, Stavros London South Bank University Department of Computer Science and Informatics United Kingdom Sigint Solutions Ltd 10-12 Demokedous street 1 stfloor Nicosia2311 Cyprus School of Computing Edinburgh Napier University 10 Colinton Rd ScotlandEH10 5DT United Kingdom Faculty of Pure and Applied Sciences Open University of Cyprus Nicosia2220 Cyprus

ISBN: (纸本)9781665415880

Big Data and Artificial Intelligence are new technologies to improve indoor localization. It focuses on the use of machine learning probabilistic algorithms to extract, model and analyse live and historical signal data obtained from several sources. In this respect, the data generated by 5G network and the Internet of Things is quintessential for precise indoor positioning in complex building environments. In this paper, we present a new architecture for assets and personnel location management in 5G network with an emphasis on vertical sectors in smart cities. Moreover, we explain how Big Data and Machine learning can be used to offer positioning as service. Additionally, we implement a new deep learning model for 3D positioning using the proposed architecture. The performance of the proposed model is compared against other Machine Learning algorithms. © 2021 IEEE.

关键词： Internet of things

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Corrigendum to “A hybrid algorithm (BAPSO) for capacity configuration optimization in a distributed solar PV based microgrid” [Energy Rep. 7 (2021) 7906–7912]

引用

Energy Reports 2024年 12卷 5757-5757页

作者： Ahmad Almadhor Hafiz Tayyab Rauf Muhammad Attique Khan Seifedine Kadry Yunyoung Nam Department of Computer Engineering and Networks Jouf University Saudi Arabia Centre for Smart Systems AI and Cybersecurity Staffordshire University Stoke-on-Trent United Kingdom Department of Computer Science HITEC University Taxila Pakistan Faculty of Applied Computing and Technology Noroff University College Kristiansand Norway Department of Computer Science and Engineering Soonchunhyang University Asan South Korea

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Efficient implementation of modern entropy stable and kinetic energy preserving discontinuous Galerkin methods for conservation laws

arXiv

引用

arXiv 2021年

作者： Ranocha, Hendrik Schlottke-Lakemper, Michael Chan, Jesse Rueda-Ramírez, Andrés M. Winters, Andrew R. Hindenlang, Florian Gassner, Gregor J. Applied Mathematics University of Münster Germany High-Performance Computing Center Stuttgart University of Stuttgart Germany Computational and Applied Mathematics Rice University United States Department of Mathematics and Computer Science University of Cologne Germany Computational Mathematics Division of Applied Mathematics Linköping University Sweden Max Planck Institute for Plasma Physics NMPP division Garching Germany Department of Mathematics and Computer Science Center for Data and Simulation Science University of Cologne Germany

Many modern discontinuous Galerkin (DG) methods for conservation laws make use of summation by parts operators and flux differencing to achieve kinetic energy preservation or entropy stability. While these techniques increase the robustness of DG methods significantly, they are also computationally more demanding than standard weak form nodal DG methods. We present several implementation techniques to improve the efficiency of flux differencing DG methods that use tensor product quadrilateral or hexahedral elements, in 2D or 3D respectively. Focus is mostly given to CPUs and DG methods for the compressible Euler equations, although these techniques are generally also useful for GPU computing and other physical systems including the compressible Navier-Stokes and magnetohydrodynamics equations. We present results using two open source codes, *** written in Julia and FLUXO written in Fortran, to demonstrate that our proposed implementation techniques are applicable to different code bases and programming languages. Copyright © 2021, The Authors. All rights reserved.

关键词： Entropy

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List homomorphism problems for signed graphs 45

List homomorphism problems for signed graphs

引用

45th International Symposium on Mathematical Foundations of computer science, MFCS 2020

作者： Bok, Jan Brewster, Richard Feder, Tomás Hell, Pavol Jedličková, Nikola Computer Science Institute Charles University Prague Czech Republic Department of Mathematics and Statistics Thompson Rivers University Kamloops Canada Palo Alto CA United States School of Computing Science Simon Fraser University Burnaby Canada Department of Applied Mathematics Charles University Prague Czech Republic

ISBN: (纸本)9783959771597

We consider homomorphisms of signed graphs from a computational perspective. In particular, we study the list homomorphism problem seeking a homomorphism of an input signed graph (G, σ), equipped with lists L(v) ⊆ V (H), v ∈ V (G), of allowed images, to a fixed target signed graph (H, π). The complexity of the similar homomorphism problem without lists (corresponding to all lists being L(v) = V (H)) has been previously classified by Brewster and Siggers, but the list version remains open and appears difficult. Both versions (with lists or without lists) can be formulated as constraint satisfaction problems, and hence enjoy the algebraic dichotomy classification recently verified by Bulatov and Zhuk. By contrast, we seek a combinatorial classification for the list version, akin to the combinatorial classification for the version without lists completed by Brewster and Siggers. We illustrate the possible complications by classifying the complexity of the list homomorphism problem when H is a (reflexive or irreflexive) signed tree. It turns out that the problems are polynomial-time solvable for certain caterpillar-like trees, and are NP-complete otherwise. The tools we develop will be useful for classifications of other classes of signed graphs, and we mention some follow-up research of this kind;those classifications are surprisingly complex. © Nathalie Bertrand;licensed under Creative Commons License CC-BY 45th International Symposium on Mathematical Foundations of computer science (MFCS 2020).

关键词： Constraint satisfaction problems

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