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arXiv 2025年

作者： Tang, Yingheng Xu, Wenbin Cao, Jie Ma, Jianzhu Gao, Weilu Farrell, Steve 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 Institute for AI Industry Research Tsinghua University Beijing China 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 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： Materials properties

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Modular Autonomous Virtualization System for Two-Dimensional Semiconductor Quantum Dot Arrays

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Physical Review X 2025年第2期15卷 021034-021034页

作者： Anantha S. Rao Donovan Buterakos Barnaby van Straaten Valentin John Cécile X. Yu Stefan D. Oosterhout Lucas Stehouwer Giordano Scappucci Menno Veldhorst Francesco Borsoi Justyna P. Zwolak Joint Center for Quantum Information and Computer Science University of Maryland College Park Maryland 20742 USA Department of Physics University of Maryland College Park Maryland 20742 USA National Institute of Standards and Technology Gaithersburg Maryland 20899 USA QuTech and Kavli Institute of Nanoscience Delft University of Technology P.O. Box 5046 2600 GA Delft The Netherlands QuTech and Netherlands Organisation for Applied Scientific Research (TNO) Delft The Netherlands Present address: NNF Quantum Computing Programme Niels Bohr Institute University of Copenhagen Blegdamsvej 17 2100 Copenhagen Denmark.

Arrays of gate-defined semiconductor quantum dots are among the leading candidates for building scalable quantum processors. High-fidelity initialization, control, and readout of spin qubit registers require exquisite and targeted control over key Hamiltonian parameters that define the electrostatic environment. However, due to the tight gate pitch, capacitive crosstalk between gates hinders independent tuning of chemical potentials and interdot couplings. While virtual gates offer a practical solution, determining all the required cross-capacitance matrices accurately and efficiently in large quantum dot registers is an open challenge. Here, we establish a modular automated virtualization system (MAViS)—a general and modular framework for autonomously constructing a complete stack of multilayer virtual gates in real time. Our method employs machine learning techniques to rapidly extract features from two-dimensional charge stability diagrams. We then utilize computer vision and regression models to self-consistently determine all relative capacitive couplings necessary for virtualizing plunger and barrier gates in both low- and high-tunnel-coupling regimes. Using MAViS, we successfully demonstrate accurate virtualization of a dense two-dimensional array comprising ten quantum dots defined in a high-quality Ge/SiGe heterostructure. Our work offers an elegant and practical solution for the efficient control of large-scale semiconductor quantum dot systems.

关键词： Semiconductor quantum dots

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MAP-based Problem-Agnostic Diffusion Model for Inverse Problems

arXiv

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arXiv 2025年

作者： Tao, Pingping Liu, Haixia Su, Jing Yang, Xiaochen Tan, Hongchen Shandong University Library No. 180 West Culture Road Shandong Weihai264209 China School of Mathematics and Statistics Hubei Key Laboratory of Engineering Modeling and Scientific Computing Institute of Interdisciplinary Research for Mathematics and Applied Science Huazhong University of Science and Technology No. 1037 Luoyu road Hubei Wuhan430074 China Dapartment of Basic Sciences Dalian University of Science and Technology No. 999-26 Harbor Road Liaoning Dalian116052 China School of Computer Science and Technology Harbin Institute of Technology No. 2 West Culture Road Shandong Weihai264209 China Institute of Future Technology Dalian University of Technology No. 2 Lingong Road Liaoning Dalian116081 China

Diffusion models have indeed shown great promise in solving inverse problems in image processing. In this paper, we propose a novel, problem-agnostic diffusion model called the maximum a posteriori (MAP)-based guided term estimation method for inverse problems. To leverage unconditionally pretrained diffusion models to address conditional generation tasks, we divide the conditional score function into two terms according to Bayes’ rule: an unconditional score function (approximated by a pretrained score network) and a guided term, which is estimated using a novel MAP-based method that incorporates a Gaussian-type prior of natural images. This innovation allows us to better capture the intrinsic properties of the data, leading to improved performance. Numerical results demonstrate that our method preserves contents more effectively compared to state-of-the-art methods—for example, maintaining the structure of glasses in super-resolution tasks and producing more coherent results in the neighborhood of masked regions during inpainting. Our numerical implementation is available at https://***/liuhaixias1/ MAP-DIFFUSION-IP. Copyright © 2025, The Authors. All rights reserved.

关键词： Inverse problems

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Foundation Models for Atomistic Simulation of Chemistry and Materials

arXiv

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arXiv 2025年

作者： Yuan, Eric C.-Y. Liu, Yunsheng Chen, Junmin Zhong, Peichen Raja, Sanjeev Kreiman, Tobias Vargas, Santiago Xu, Wenbin Head-Gordon, Martin Yang, Chao Blau, Samuel M. Cheng, Bingqing Krishnapriyan, Aditi Head-Gordon, Teresa Kenneth S. Pitzer Theory Center Department of Chemistry United States Department of Chemical and Biomolecular Engineering United States Electrical Engineering and Computer Science United States Bakar Institute of Digital Materials for the Planet University of California BerkeleyCA94720 United States Chemical Sciences Division United States Applied Mathematics and Computational Research Division United States Energy Technologies Area United States National Energy Research Scientific Computing Center Lawrence Berkeley National Laboratory BerkeleyCA94720 United States

Given the power of large language and large vision models, it is of profound and fundamental interest to ask if a foundational model based on data and parameter scaling laws and pre-training strategies is possible for learned simulations of chemistry and materials. The scaling of large and diverse datasets and highly expressive architectures for chemical and materials sciences should result in a foundation model that is more efficient and broadly transferable, robust to out-of-distribution challenges, and easily fine-tuned to a variety of downstream observables, when compared to specific training from scratch on targeted applications in atomistic simulation. In this Perspective we aim to cover the rapidly advancing field of machine learned interatomic potentials (MLIP), and to illustrate a path to create chemistry and materials MLIP foundation models at larger scale. © 2025, CC BY-SA.

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Ensuring numerical quality in grid computing

Ensuring numerical quality in grid computing

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12th GAMM-IMACS International Symposium on scientific computing, computer Arithmetic and Validated Numerics, SCAN 2006

作者： Frommer, Andreas Hüsken, Matthias Bergische Universität Wuppertal Applied Computer Science and Scientific Computing D-42097 Wuppertal Germany

ISBN: (纸本)076952821X

Certain numerically intensive applications executed within a grid computing environment crucially depend on the properties of floating-point arithmetic implemented on the respective platform. Differences in these properties may have drastic effects. This paper identifies the central problems related to this situation. We propose an approach which gives the user valuable information on the various platforms available in a grid computing environment in order to assess the numerical quality of an algorithm run on each of these platforms. In this manner, the user will at least have very strong hints whether a program will perform reliably in a grid before actually executing it. Our approach extends the existing IeeeCC754 test suite by two "grid-enabled" modes: The first mode calculates a "numerical checksum" on a specific grid host and executes the job only if the checksum is identical to a locally generated one. The second mode provides the user with information on the reliability and IEEE 754-conformity of the underlying floating-point implementation of various platforms. Furthermore, it can help to find a set of compiler options to optimize the application's performance while retaining numerical stability.

关键词： Digital arithmetic

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Integrable discretization of soliton equations via bilinear method and Backlund transformation

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science China Mathematics 2015年第2期58卷 279-296页

作者： ZHANG Ying Nan CHANG Xiang Ke HU Juan HU Xing Biao TAM Hon-Wah Institute of Computational Mathematics and Scientific Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences School of Mathematical Sciences University of Chinese Academy of Sciences Department of Applied Mathematics Zhejiang University of Technology Department of Computer Science Hong Kong Baptist University

We present a systematic procedure to derive discrete analogues of integrable PDEs via Hirota’s bilinear *** approach is mainly based on the compatibility between an integrable system and its B¨acklund *** apply this procedure to several equations,including the extended Korteweg-deVries(Kd V)equation,the extended Kadomtsev-Petviashvili(KP)equation,the extended Boussinesq equation,the extended Sawada-Kotera(SK)equation and the extended Ito equation,and obtain their associated semidiscrete *** the continuum limit,these differential-difference systems converge to their corresponding smooth *** these new integrable systems,their B¨acklund transformations and Lax pairs are derived.

关键词： integrable discretization bilinear method Backlund transformation

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Early experiences with the OpenMP accelerator model

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9th International Workshop on OpenMP in the Era of Low Power Devices and Accelerators, IWOMP 2013

作者： Liao, Chunhua Yan, Yonghong De Supinski, Bronis R. Quinlan, Daniel J. Chapman, Barbara Center for Applied Scientific Computing Lawrence Livermore National Laboratory United States Department of Computer Science University of Houston United States

ISBN: (纸本)9783642406973

A recent trend in mainstream computer nodes is the combined use of general-purpose multicore processors and specialized accelerators such as GPUs and DSPs in order to achieve better performance and to reduce power consumption. To support this trend, the OpenMP Language Committee has approved a set of extensions to OpenMP (referred to as the OpenMP accelerator model). The initial version is the subject of Technical Report 1 (TR1) while OpenMP 4.0 Release Candidate 2 (RC2) further refines the extensions. In this paper, we examine the newly released accelerator directives and create an initial reference implementation, referred to as HOMP (Heterogeneous OpenMP). Focused on targeting NVIDIA GPUs, our work is based on an existing OpenMP implementation in the ROSE source-to-source compiler infrastructure. HOMP includes extensions to parse the new constructs and to represent them in the AST and other compiler translation details. Further we provide initial runtime support. For our evaluation, we have adapted a few existing OpenMP codes to use the accelerator model directives and present preliminary performance results. Finally, we critique the accelerator model in terms of its impact on developers and compiler writers and suggest possible improvements. © 2013 Springer-Verlag.

关键词： Application programming interfaces (API)

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An OpenMP analyzer for detecting concurrency errors

An OpenMP analyzer for detecting concurrency errors

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41st International Conference on Parallel Processing Workshops, ICPPW 2012

作者： Ma, Hongyi Chen, Qichang Wang, Liqiang Liao, Chunhua Quinlan, Daniel Department of Computer Science University of Wyoming United States Center for Applied Scientific Computing Lawrence Livermore National Laboratory United States

ISBN: (纸本)9780769547954

With the increasing popularity of multi-core machines, more and more sequential programs are being parallelized using OpenMP. However, it is not easy for programmers to write parallel programs correctly. Concurrency errors, such as data races and deadlocks. This paper presents a novel technique to detect data races and deadlocks using hybrid program analysis. © 2012 IEEE.

关键词： Application programming interfaces (API)

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DieT Transformer model with PCA-ADE integration for advanced multi-class brain tumor classification

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Intelligence-Based Medicine 2025年 11卷 100192-100192页

作者： Amin, Mohammad Nahar, Khalid M.O. Gharaibeh, Hasan Nasayreh, Ahmad Alsalmanc, Neda'a Alomar, Alaa Malkawi, Majd Alqasem, Noor Smerat, Aseel Zitar, Raed Abu Nusier, Shawd Ezugwu, Absalom E. Abualigah, Laith Department of Information Technology and Computer Sciences Yarmouk University Irbid 211633 Jordan Faculty of Computer Studies Arab Open University P.O.Box 84901 Riyadh 11681 Saudi Arabia Department of Computer Science Faculty of Information Technology Jordan University of Science and Technology Irbid 22110 Jordan Department of Medicine Faculty of Medicine Jordan University of Science and Technology Irbid 22110 Jordan Department of Biomedical Systems and Informatics Engineering Hijjawi Faculty for Engineering Technology Yarmouk University Irbid 21163 Jordan Centre for Research Impact & Outcome Chitkara University Institute of Engineering and Technology Chitkara University Punjab Rajpura 140401 India Department of Biosciences Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai 602105 India Artificial Intelligence and Sensing Technologies (AIST) Research Center University of Tabuk Tabuk 71491 Saudi Arabia Faculty of Engineering and Computing Liwa College Abu Dhabi United Arab Emirates Department of Health and Clinical Outcomes Research Saint Louis University St. Louis MO United States Unit for Data Science and Computing North-West University 11 Hofman Street Potchefstroom 2520 South Africa Computer Science Department Al al-Bayt University Mafraq 25113 Jordan Hourani Center for Applied Scientific Research Al-Ahliyya Amman University Amman 19328 Jordan

Early and accurate diagnosis of brain tumors is crucial to improving patient outcomes and optimizing treatment strategies. Long-term brain injury results from aberrant proliferation of either malignant or nonmalignant tissues in the brain. MRIs, or magnetic resonance imaging, are one of the most used approaches for detecting brain tumors. Professionals physically evaluate people after they have had MRI filtering, the process of enhancing MRI scans for radiologist interpretation, to establish if they have a brain tumor. Because different specialists use different frames to make judgments on the same MRI image, their analyses may yield contradictory results. Furthermore, simply detecting a tumor is insufficient. Inconsistent diagnoses can lead to delays in treatment, impacting survival rates and quality of care. It is also crucial to diagnose the patient's tumor so that treatment can begin as soon as possible. In this research, we investigate the multi-class classification of brain tumors utilizing a cutting-edge methodology that includes feature extraction from pictures using the DieT Transformer model, dimensionality reduction with PCA, and feature selection using the ADE algorithm. The proposed model, known in the publication as ADE_DieT, obtained an accuracy of 96.09 %. In addition, this article analyzes the performance of various pre-trained models, including MobileNetV3, NasNet, ResNet50, VGG16, VGG19, and DeiT. The proposed approach shortens the time required for manual diagnosis by clinicians by assisting in the rapid and accurate identification of brain tumors using MRI data. In oncology, this is important since it allows for early treatment. Integrating ADE_DieT into clinical workflows can support radiologists by reducing diagnosis time and enhancing diagnostic consistency. © 2024 The Authors

关键词： Brain tumor Medical image analysis MRI Vision Transformer

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Extracting logical structure and identifying stragglers in parallel execution traces 14

Extracting logical structure and identifying stragglers in p...

引用

2014 19th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, PPoPP 2014

作者： Isaacs, Katherine E. Gamblin, Todd Bhatele, Abhinav Bremer, Peer-Timo Schulz, Martin Hamann, Bernd Department of Computer Science University of California Davis United States Center for Applied Scientific Computing Lawrence Livermore National Laboratory United States

ISBN: (纸本)9781450326568

We introduce a new approach to automatically extract an idealized logical structure from a parallel execution trace. We use this structure to define intuitive metrics such as the lateness of a process involved in a parallel execution. By analyzing and illustrating traces in terms of logical steps, we leverage a developer's understanding of the happened-before relations in a parallel program. This technique can uncover dependency chains, elucidate communication patterns, and highlight sources and propagation of delays, all of which may be obscured in a traditional trace visualization.

关键词： Visualization

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