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We investigate a difference-of-convex (DC) formulation where the second term is allowed to be weakly convex. We examine the precise behavior of a single iteration of the difference-of-convex algorithm (DCA), providing a tight…

Optimization and Control · Mathematics 2026-01-23 Teodor Rotaru , Panagiotis Patrinos , François Glineur

The FORTRAN code POLRAD 2.0 for radiative correction calculation in inclusive and semi-inclusive deep inelastic scattering of polarized leptons by polarized nucleons and nuclei is described. Its theoretical basis, structure and algorithms…

High Energy Physics - Phenomenology · Physics 2008-11-26 I. Akushevich , A. Ilyichev , N. Shumeiko , A. Soroko , A. Tolkachev

Test-time adaptation (TTA) is a task that continually adapts a pre-trained source model to the target domain during inference. One popular approach involves fine-tuning model with cross-entropy loss according to estimated pseudo-labels.…

Machine Learning · Computer Science 2024-01-26 Guowei Wang , Changxing Ding , Wentao Tan , Mingkui Tan

Approximate methods have been considered as a means to the evaluation of discrete transforms. In this work, we propose and analyze a class of integer transforms for the discrete Fourier, Hartley, and cosine transforms (DFT, DHT, and DCT),…

Signal Processing · Electrical Eng. & Systems 2020-07-07 R. J. Cintra

Extremely large antenna arrays (ELAAs) operating in high-frequency bands have spurred the development of near-field communication, driving advancements in beam training and signal processing design. In this work, we present a low-complexity…

Signal Processing · Electrical Eng. & Systems 2025-06-27 Zijun Wang , Shawn Tsai , Rama Kiran , Rui Zhang

Fixed node diffusion quantum Monte Carlo (FN-DMC) is an increasingly used computational approach for investigating the electronic structure of molecules, solids, and surfaces with controllable accuracy. It stands out among equally accurate…

Computational Physics · Physics 2019-10-03 Andrea Zen , Jan Gerit Brandenburg , Angelos Michaelides , Dario Alfè

Language Models pretrained on large textual data have been shown to encode different types of knowledge simultaneously. Traditionally, only the features from the last layer are used when adapting to new tasks or data. We put forward that,…

Computation and Language · Computer Science 2024-05-08 Muhammad ElNokrashy , Badr AlKhamissi , Mona Diab

Convolutional neural networks (CNNs) have become increasingly popular for solving a variety of computer vision tasks, ranging from image classification to image segmentation. Recently, autonomous vehicles have created a demand for depth…

Computer Vision and Pattern Recognition · Computer Science 2018-11-28 Paden Tomasello , Sammy Sidhu , Anting Shen , Matthew W. Moskewicz , Nobie Redmon , Gayatri Joshi , Romi Phadte , Paras Jain , Forrest Iandola

Optical metasurfaces are planar substrates with custom-designed, nanoscale features that selectively modulate incident light with respect to direction, wavelength, and polarization. When coupled with photodetectors and appropriate…

Quantum low-density parity-check (qLDPC) codes are a promising construction for drastically reducing the overhead of fault-tolerant quantum computing (FTQC) architectures. However, all of the known hardware implementations of these codes…

ADF95 is a tool to automatically calculate numerical first derivatives for any mathematical expression as a function of user defined independent variables. Accuracy of derivatives is achieved within machine precision. ADF95 may be applied…

Mathematical Software · Computer Science 2007-05-23 Christian W. Straka

Despite the wide availability of density functional theory (DFT) codes, their adoption by the broader materials science community remains limited due to challenges such as software installation, input preparation, high-performance computing…

The Density Based Spatial Clustering of Applications with Noise (DBSCAN) is a topometric algorithm used to cluster spatial data that are affected by background noise. For the first time, we propose the use of this method for the detection…

Instrumentation and Methods for Astrophysics · Physics 2015-06-11 A. Tramacere , C. Vecchio

We present UDDSketch (Uniform DDSketch), a novel sketch for fast and accurate tracking of quantiles in data streams. This sketch is heavily inspired by the recently introduced DDSketch, and is based on a novel bucket collapsing procedure…

Data Structures and Algorithms · Computer Science 2020-04-21 Italo Epicoco , Catiuscia Melle , Massimo Cafaro , Marco Pulimeno , Giuseppe Morleo

Clustering is a fundamental task in machine learning. One of the most successful and broadly used algorithms is DBSCAN, a density-based clustering algorithm. DBSCAN requires $\epsilon$-nearest neighbor graphs of the input dataset, which are…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-09-12 Youguang Chen , William Ruys , George Biros

(Abridged.) This thesis investigates scalable fault-tolerant quantum computation through the development of bosonic quantum codes, quantum LDPC codes, and decoding protocols that connect continuous-variable and discrete-variable error…

Quantum Physics · Physics 2025-12-18 Timo Hillmann

An implementation of full self-consistency over the electronic density in the DFT+DMFT framework on the basis of a plane wave-projector augmented wave (PAW) DFT code is presented. It allows for an accurate calculation of the total energy in…

Strongly Correlated Electrons · Physics 2013-01-24 Bernard Amadon

DESP-C++ is a C++ discrete-event random simulation engine that has been designed to be fast, very easy to use and expand, and valid. DESP-C++ is based on the resource view. Its complete architecture is presented in detail, as well as a…

Databases · Computer Science 2016-11-29 Jérôme Darmont

The open source SKIRT Monte Carlo radiative transfer code has been used for more than 15 years to model the interaction between radiation and dust in various astrophysical systems. In this work, we present version 9 of the code, which has…

Astrophysics of Galaxies · Physics 2020-03-03 Peter Camps , Maarten Baes

Derivative computation is a key component of optimization, sensitivity analysis, uncertainty quantification, and nonlinear solvers. Automatic differentiation (AD) is a powerful technique for evaluating such derivatives, and in recent years,…

Mathematical Software · Computer Science 2025-07-18 Kim Liegeois , Brian Kelley , Eric Phipps , Sivasankaran Rajamanickam , Vassil Vassilev