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Analysis of the gluon distribution with next-to-leading order splitting function at small-x^(*)

Chinese Physics C 2024年第6期48卷 38-44页

作者：陈京萱王晓鹏蔡燕兵陈旭荣王倩 Key Laboratory of Atomic and Subatomic Structure and Quantum Control(MOE) Guangdong Basic Research Center of Excellence for Structure and Fundamental Interactions of MatterInstitute of Quantum MatterSouth China Normal UniversityGuangzhou 510006China Guangdong-Hong Kong Joint Laboratory of Quantum Matter Guangdong Provincial Key Laboratory of Nuclear ScienceSouthern Nuclear Science Computing CenterSouth China Normal UniversityGuangzhou 510006China Institute of Modern Physics Chinese Academy of SciencesLanzhou 730000China University of Chinese Academy of Sciences Beijing 100049China Lanzhou University Lanzhou 730000China School of Nuclear Science and Technology University of Chinese Academy of SciencesBeijing 100049China Guizhou Key Laboratory in Physics and Related Areas Guizhou University of Finance and EconomicsGuiyang 550025China Southern Center for Nuclear-Science Theory(SCNT) Institute of Modern PhysicsChinese Academy of SciencesHuizhou 516000China

An approximated solution for the gluon distribution from DGLAP evolution equations with the NLO splitting function in the small-x limit is *** first obtain simplified forms of the LO and NLO splitting functions in the small-x *** these approximated splitting functions,we obtain the analytical gluon distribution using the Mellin *** free parameters in the boundary conditions are obtained by fitting the CJ15 gluon distribution *** find that the asymptotic behavior of the gluon distribution is consistent with the CJ15 data;however,the NLO results considering the"ladder"structure of gluon emission are slightly better than the LO *** results indicate that the corrections from NLO have a significant influence on the behavior of the gluon distribution in the small-x *** addition,we investigate the DGLAP evolution of the proton structure function using the analytical solution of the gluon *** differential structure function reveals that our results have a similar tendency to the CJ15 data at small-x.

关键词： DGLAP equation gluon distribution small-x structure function

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Design of a Secure Machine Learning-Based Malware Detection and Analysis Scheme

Design of a Secure Machine Learning-Based Malware Detection ...

引用

Communications, computing, Cybersecurity, and Informatics (CCCI), International Conference on

作者： Pankaj Kumar Mohammad S. Obaidat Piyush Pandey Mohammad Wazid Ashok Kumar Das Devesh Pratap Singh Department of Computer Science and Engineering Graphic Era Deemed to be University Dehradun India King Abdullah II School of Information Technology The University of Jordan Amman Jordan School of Computing SRM University Jordan University of Science and Technology Beijing Beijing China School of Computing SRM University Kattankulathur TN India Center for Security Theory Algorithmic Research International Institute of Information Technology Hyderabad India

Today's world is rapidly growing towards the advanced concept of technology. technology nowadays is at its peak of development and has great advantages in all fields of work, whether it is in industrial automation, farming, weather forecasting, or disease detection and control. Despite its great advantages, it does have its negative side because a major population is using technology and general-purpose computing devices (i.e., desktops, laptops, smartphones, tablets, etc.). Therefore, most of their personal data is available online. The data is constantly in danger of getting stolen by malicious actors (i.e., hackers), who can find a way to get their hands on this data and then use it for their personal gain (i.e., money-making). The best-known technique to get this information is by using malware exploitation on the machine of the target. Malware is an executable or a binary that is malicious in nature. It may have various devastating effects, and in order to detect and make the system defensive, we need to propose a scheme to detect the malware in the system, analyze the particular file, and then mitigate it. In this paper, we propose a secure machine learning-based malware detection and analysis scheme (in short, SML-MDA). The conducted security analysis and formal security verification of the proposed SMLMDA prove its security against various types of potential attacks. The proposed SML-MDA is then compared with the other similar competing schemes, and its performance has been found to be better in terms of various performance metrics like accuracy and F1-score.

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Learning many-body Hamiltonians with Heisenberg-limited scaling

arXiv

引用

arXiv 2022年

作者： Huang, Hsin-Yuan Tong, Yu Fang, Di Su, Yuan Institute for Quantum Information and Matter California Institute of Technology United States Department of Mathematics University of California Berkeley United States Simons Institute for the Theory of Computing University of California Berkeley United States Microsoft Quantum

Learning a many-body Hamiltonian from its dynamics is a fundamental problem in physics. In this work, we propose the first algorithm to achieve the Heisenberg limit for learning an interacting N-qubit local Hamiltonian. After a total evolution time of O(∈−1), the proposed algorithm can efficiently estimate any parameter in the N-qubit Hamiltonian to ∈-error with high probability. The proposed algorithm is robust against state preparation and measurement error, does not require eigenstates or thermal states, and only uses polylog(∈−1) experiments. In contrast, the best previous algorithms, such as recent works using gradient-based optimization or polynomial interpolation, require a total evolution time of O(∈−2) and O(∈−2) experiments. Our algorithm uses ideas from quantum simulation to decouple the unknown N-qubit Hamiltonian H into noninteracting patches, and learns H using a quantum-enhanced divide-and-conquer approach. We prove a matching lower bound to establish the asymptotic optimality of our algorithm. © 2022, CC BY.

关键词： Hamiltonians

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SPECTRAL ALGORITHMS OPTIMALLY RECOVER PLANTED SUB-STRUCTURES

arXiv

引用

arXiv 2022年

作者： Dhara, Souvik Gaudio, Julia Mossel, Elchanan Sandon, Colin The Simons Institute for the Theory of Computing University of California Berkeley United States Department of Industrial Engineering and Management Sciences Northwestern University United States Department of Mathematics Massachusetts Institute of Technology United States

Spectral algorithms are an important building block in machine learning and graph algorithms. We are interested in studying when such algorithms can be applied directly to provide optimal solutions to inference tasks. Previous works by Abbe, Fan, Wang and Zhong (2020) and by Dhara, Gaudio, Mossel and Sandon (2022) showed the optimality for community detection in the Stochastic Block Model (SBM), as well as in a censored variant of the SBM. Here we show that this optimality is somewhat universal as it carries over to other planted substructures such as the planted dense subgraph problem and submatrix localization problem, as well as to a censored version of the planted dense subgraph problem. © 2022, CC BY.

关键词： Stochastic systems

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Training Multi-Layer Over-Parametrized Neural Network in Subquadratic Time

arXiv

引用

arXiv 2021年

作者： Song, Zhao Zhang, Lichen Zhang, Ruizhe Adobe Research United States Massachusetts Institute of Technology United States Simons Institute for the Theory of Computing United States

We consider the problem of training a multi-layer over-parametrized neural network to minimize the empirical risk induced by a loss function. In the typical setting of over-parametrization, the network width m is much larger than the data dimension d and the number of training samples n (m = poly(n, d)), which induces a prohibitive large weight matrix W ∈ Rm×m per layer. Naively, one has to pay O(m2) time to read the weight matrix and evaluate the neural network function in both forward and backward computation. In this work, we show how to reduce the training cost per iteration. Specifically, we propose a framework that uses m2 cost only in the initialization phase and achieves a truly subquadratic cost per iteration in terms of m, i.e., m2−Ω(1) per iteration. Our result has implications beyond standard over-parametrization theory, as it can be viewed as designing an efficient data structure on top of a pre-trained large model to further speed up the fine-tuning process, a core procedure to deploy large language models (LLM). © 2021, CC BY-NC-SA.

关键词： Matrix algebra

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Deconfined classical criticality in the anisotropic quantum spin-12 XY model on the square lattice

arXiv

引用

arXiv 2024年

作者： Mudry, Christopher Aksoy, Ömer M. Chamon, Claudio Furusaki, Akira Condensed Matter Theory Group PSI Center for Scientific Computing Theory and Data Villigen PSI5232 Switzerland Institut de Physique EPF Lausanne LausanneCH-1015 Switzerland Department of Physics Massachusetts Institute of Technology CambridgeMA02139 United States Department of Physics Boston University BostonMA02215 United States RIKEN Center for Emergent Matter Science Saitama Wako351-0198 Japan Condensed Matter Theory Laboratory RIKEN Saitama Wako351-0198 Japan

The anisotropic quantum spin-12 XY model on a linear chain was solved by Lieb, Schultz, and Mattis in 1961 [Ann. Phys. 16, 407 (1961)] and shown to display a continuous quantum phase transition at the O(2) symmetric point separating two gapped phases with competing Ising long-range order. For the square lattice, the following is known. The two competing Ising ordered phases extend to finite temperatures, up to a boundary where a transition to the paramagnetic phase occurs, and meet at the O(2) symmetric critical line along the temperature axis that ends at a tricritical point at the Berezinskii-Kosterlitz-Thouless transition temperature where the two competing phases meet the paramagnetic phase. We show that the first-order zero-temperature (quantum) phase transition that separates the competing phases as a function of the anisotropy parameter is smoothed by thermal fluctuations into deconfined classical criticality. © 2024, CC BY.

关键词： Paramagnetism

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Dynamical Hubbard approach to correlated materials: the case of transition-metal monoxides

arXiv

引用

arXiv 2025年

作者： Caserta, Mario Chiarotti, Tommaso Vanzini, Marco Marzari, Nicola École Polytechnique Fédérale de Lausanne LausanneCH-1015 Switzerland Department of Applied Physics and Materials Science California Institute of Technology PasadenaCA91125 United States College Champittet Pully Switzerland Belgium PSI Center for Scientific Computing Theory and Data PSI Villigen5232 Switzerland

Electronic correlations beyond static mean-field theories are of fundamental importance in describing the properties of complex materials - such as transition-metal oxides - where the low-energy physics is driven by localized d or f electrons. Here, we show that it is possible to capture these correlations with a local and dynamical self energy, extending to the spin-polarized and multi-site case our recently introduced dynamical Hubbard functional formulation. We apply this formalism to the prototypical transition-metal monoxide series of MnO, FeO, CoO, and NiO in their ground state, finding excellent agreement with experiments for the spectral properties. The results are comparable or improved with respect to state-of-the-art theories, both for the densities of states and for the spectral functions—including band renormalization and spectral weight transfer—in a numerically efficient and physically transparent treatment of correlations amenable to the study of realistic, complex materials. © 2025, CC BY.

关键词： Manganese oxide

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Parameterized Inapproximability Hypothesis under ETH

arXiv

引用

arXiv 2023年

作者： Guruswami, Venkatesan Lin, Bingkai Ren, Xuandi Sun, Yican Wu, Kewen Simons Institute for the Theory of Computing Departments of EECS and Mathematics UC Berkeley United States State Key Laboratory for Novel Software Technology Nanjing University China Department of EECS UC Berkeley United States School of Computer Science Peking University China

The Parameterized Inapproximability Hypothesis (PIH) asserts that no fixed parameter tractable (FPT) algorithm can distinguish a satisfiable CSP instance, parameterized by the number of variables, from one where every assignment fails to satisfy an ϵ fraction of constraints for some absolute constant ϵ > 0. PIH plays the role of the PCP theorem in parameterized complexity. However, PIH has only been established under Gap-ETH, a very strong assumption with an inherent gap. In this work, we prove PIH under the Exponential Time Hypothesis (ETH). This is the first proof of PIH from a gap-free assumption. Our proof is self-contained and elementary. We identify an ETH-hard CSP whose variables take vector values, and constraints are either linear or of a special parallel structure. Both kinds of constraints can be checked with constant soundness via a "parallel PCP of proximity" based on the Walsh-Hadamard code. © 2023, CC BY.

关键词： Parameterization

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Incommensurate gapless ferromagnetism connecting competing symmetry-enriched deconfined quantum phase transitions

arXiv

引用

arXiv 2025年

作者： Rey, Anthony Aksoy, Ömer M. Arovas, Daniel P. Chamon, Claudio Mudry, Christopher Condensed Matter Theory Group PSI Center for Scientific Computing Theory and Data Villigen PSI 5232 Switzerland Department of Physics Massachusetts Institute of Technology CambridgeMA02139 United States Department of Physics University of California at San Diego La Jolla CA92093 United States Department of Physics Boston University BostonMA02215 United States Institut de Physique EPF Lausanne LausanneCH-1015 Switzerland

Interpolating between distinct symmetry-enriched critical points is believed to require going through either a multicritical point or an intervening gapped phase. We present a scenario, in which a gapless extended phase serves as a "hub" connecting multiple symmetry-enriched deconfined quantum critical points. As a concrete example, we construct a lattice model with Z2×Z2×Z2 symmetry for quantum spin-1/2 degrees of freedom that realizes four distinct gapful phases supporting antiferromagnetic long-range order and one extended incommensurate gapless ferromagnetic phase. The quantum phase transition between any two of the four gapped and antiferromagnetic phases goes through either a (deconfined) quantum critical point, a quantum tricritical point, or the incommensurate gapless ferromagnetic phase. In this phase diagram, it is possible to interpolate between four deconfined quantum critical points by passing through the extended gapless ferromagnetic phase. We identify the phases in the model and the nature of the transitions between them through a combination of analytical arguments and density matrix renormalization group (DMRG) studies. Copyright © 2025, The Authors. All rights reserved.

关键词： Ferromagnetism

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Deep Learning Approaches for Image Captioning: Opportunities, Challenges and Future Potential

引用

IEEE Access 2024年 1-1页

作者： Jamil, Azhar Saif-Ur-Rehman Mahmood, Khalid Villar, Monica Gracia Prola, Thomas Diez, Isabel De La Torre Samad, Md Abdus Ashraf, Imran Department of Computer Science Barani Institute of Information Technology PMAS-Arid Agriculture University Rawalpindi Pakistan Department of Computer Science University Institute of Information Technology PMAS-Arid Agriculture University Rawalpindi Pakistan Institute of Computing and Information Technology Gomal University D.I.Khan Pakistan Universidad Europea del Atlántico. Isabel Torres 21 Santander Spain Department of Signal Theory Communications and Telematics Engineering Unviersity of Valladolid Paseo de Belén 15 Valladolid Spain Department of Information and Communication Engineering Yeungnam University Gyeongsan Republic of Korea

Generative intelligence relies heavily on the integration of vision and language. Much of the research has focused on image captioning, which involves describing images with meaningful sentences. Typically, when generating sentences that describe the visual content, a language model and a vision encoder are commonly employed. Because of the incorporation of object areas, properties, multi-modal connections, attentive techniques, and early fusion approaches like bidirectional encoder representations from transformers (BERT), these components have experienced substantial advancements over the years. This research offers a reference to the body of literature, identifies emerging trends in an area that blends computer vision as well as natural language processing in order to maximize their complementary effects, and identifies the most significant technological improvements in architectures employed for image captioning. It also discusses various problem variants and open challenges. This comparison allows for an objective assessment of different techniques, architectures, and training strategies by identifying the most significant technical innovations, and offers valuable insights into the current landscape of image captioning research. Authors

关键词： Feature extraction

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