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arXiv 2024年

作者： Muthusivarajan, Rajarajeswari Celaya, Adrian Farhat, Maguy Talpur, Wasif Langshaw, Holly White, Victoria Elliott, Andrew Thrower, Sara Schellingerhout, Dawid Fuentes, David Chung, Caroline Department of Imaging Physics University of Texas MD Anderson Cancer Center HoustonTX77030 United States Department of Radiation Oncology University of Texas MD Anderson Cancer Center HoustonTX77030 United States Department of Neuroradiology Division of Diagnostic Imaging University of Texas MD Anderson Cancer Center HoustonTX77030 United States Department of Computational Applied Mathematics and Operations Research Rice University HoustonTX77005 United States

Precise automated delineation of post-operative gross tumor volume in glioblastoma cases is challenging and time-consuming owing to the presence of edema and the deformed brain tissue resulting from the surgical tumor resection. The pre-operative glioma segmentation models that have been developed to date struggle to define the post-operative cavity and any residual tumor;however, the postoperative tumor and cavity are what are tracked to assess treatment response. To develop a model for automated delineation of post-operative gross tumor volumes in glioblastoma, we proposed a novel 3D double pocket U-Net architecture that has two parallel pocket U-Nets. Both U-Nets were trained simultaneously with two different subsets of MRI sequences and the output from the models was combined to do the final prediction. We strategically combined the MRI input sequences (T1, T2, T1C, FL) for model training to achieve improved segmentation accuracy. The dataset comprised 82 postoperative studies collected from 23 glioblastoma patients who underwent maximal safe tumor resection. All had gross tumor volume (GTV) segmentations performed by human experts, and these were used as a reference standard. The results of 3D double pocket U-Net were compared with baseline 3D pocket U-Net models and the ensemble of 3D pocket U-Net models. All the models were evaluated with fivefold cross-validation in terms of the Dice similarity coefficient and Hausdorff distance. Our proposed double U-Net model trained with input sequences [T1, T1C, FL + T2, T1C] achieved a better mean Dice score of 0.8585 and Hausdorff distance of 4.1942 compared to all the baseline models and ensemble models trained. The presence of infiltrating tumors and vasogenic edema in the post-operative MRI scans tends to reduce segmentation accuracy when considering the MRI sequences T1, T2, T1C, and FL together for model training. The double U-Net approach of combining subsets of the MRI sequences as distinct inputs for model trai

关键词： Convolutional neural networks

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Efficient First-Principles Framework for Overdamped Phonon Dynamics and Anharmonic Electron-Phonon Coupling in Superionic Materials

arXiv

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arXiv 2025年

作者： Wang, Yuxuan Zacharias, Marios Zhang, Xiao Pant, Nick Even, Jacky Poudeu, Pierre F.P. Kioupakis, Emmanouil Department of Materials Science and Engineering University of Michigan Ann ArborMI48109 United States Univ Rennes INSA Rennes CNRS Institut FOTON - UMR 6082 RennesF-35000 France Applied Physics Program University of Michigan Ann ArborMI48109 United States Oden Institute for Computational Engineering and Sciences The University of Texas at Austin AustinTX78712 United States

Relying on the anharmonic special displacement method, we introduce an ab initio quasistatic polymorphous framework to describe local disorder, anharmonicity, and electron-phonon coupling in superionic conductors. Using the example of cubic Cu2Se, we show that positional polymorphism yields extremely overdamped anharmonic vibrations while preserving transverse acoustic phonons, consistent with experiments. We also demonstrate well-defined electronic band structures with large band gap openings due to polymorphism of 1.0 eV and calculate anharmonic electron-phonon renormalization, yielding band gap narrowing with increasing temperature in agreement with previous measurements. Our approach opens the way for efficient ab initio electronic structure calculations in superionic crystals to elucidate their compelling high figure-of-merit. © 2025, CC BY-NC-ND.

关键词： Energy gap

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Cross sections for the electron-impact excitations Ã1B1 and B̃1A1 of H2O determined by high-energy electron scattering

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Physical Review A 2021年第3期103卷 032808-032808页

作者： Wei-Qing Xu Zi-Ru Ma Yi-Geng Peng Xiao-Jiao Du Yuan-Chen Xu Li-Han Wang Bo Li Hao-Ran Zhang Bei-Yuan Zhang Jian-Hui Zhu Shu-Xing Wang Yong Wu Jian-Guo Wang Lin-Fan Zhu School of Physical Science and Technology ShanghaiTech University Shanghai 201210 China Hefei National Laboratory for Physical Sciences at Microscale and Department of Modern Physics University of Science and Technology of China Hefei Anhui 230026 China Department of Applied Physics Nanjing University of Science and Technology Nanjing 210094 China Institute of Applied Physics and Computational Mathematics Beijing 100088 China

Understanding the role of inelastic electron scattering in water is of fundamental importance in various fields ranging from atmospheric chemistry to radiation biology. The lack of accurate excitation cross sections for water results in a large uncertainty, for example, in the track structure simulation for modeling radiation damage to DNA. The large differences of the integral cross sections (ICSs) for the optical-allowed excitations Ã1B1 and B̃1A1 of H2O among experiments and theories have been maintaining for decades. To resolve this issue, by combining the ab initio calculation with the electron correlation being taken into account accurately, we compare the ICSs determined by high-energy electron scattering with the existing experiments at low and intermediate energies and theories, where the present experiment eliminated the errors from the spectral deconvolution in low-energy measurements. Our work provides a recommendation for the ICSs of the two excitations from thresholds up to several keV, and suggests the existing selected ICSs for H2O be revised for accurate modeling radiation effects in biological matter and describing the transport properties of electrons in aqueous systems.

关键词： Atomic & molecular collisions Electron & positron scattering Electronic excitation & ionization Electronic structure of atoms & molecules Electronic transitions Molecular spectra Molecules Configuration interaction High-resolution electron energy loss spectroscopy

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A program for 3D nuclear static and time-dependent density-functional theory with full Skyrme energy density functional: hit3d

arXiv

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arXiv 2024年

作者： Shi, Yue Stevenson, Paul D. Hinohara, Nobuo Department of Physics Harbin Institute of Technology Harbin150001 China School of Mathematics and Physics University of Surrey GuildfordGU2 7XH United Kingdom Center for Computational Sciences University of Tsukuba Tsukuba305-8577 Japan Faculty of Pure and Applied Sciences University of Tsukuba Tsukuba35-8571 Japan Facility for Rare Isotope Beams Michigan State University East LansingMI48824 United States

This work presents a computer program that performs symmetry-unrestricted 3D nuclear time-dependent density function theory (DFT) calculations. The program features the augmented Lagrangian constraint in the static calculation. This allows for the calculation of the potential energy surface. In addition, the code includes the full energy density functionals derived from the Skyrme interaction, meaning that the time-even and time-odd tensor parts are included for the time-dependent calculations. The results of the hit3d code are carefully compared with the Sky3D and Ev8 programs. The testing cases include unconstrained DFT calculations for doubly magic nuclei, the constrained DFT + BCS calculations for medium-heavy nucleus 110Mo, and the dynamic applications for harmonic vibration and nuclear reactions. © 2024, CC BY.

关键词： Nuclear reactions

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Global optical model potential describing 12C-nucleus elastic scattering

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Chinese physics C 2020年第12期44卷 123-132页

作者： Yong-Li Xu Yin-Lu Han Xin-Wu Su Xiao-Jun Sun Hai-Ying Liang Hai-Rui Guo Chong-Hai Cai College of Physics and Electronic Science Shanxi Datong UniversityDatong 037009China Key Laboratory of Nuclear Data China Institute of Atomic EnergyP.O.BOX(275-41)Beijing 102413China College of Physics Guangxi Normal UniversityGuilin 541004China Institute of Applied Physics and Computational Mathematics Beijing 100094China Department of Physics Nankai UniversityTianjin 300071China

We construct a new global optical model potential to describe the elastic scattering of *** experimental data of elastic-scattering angular distributions and total reaction cross sections for targets from 24Mg to 209Bi are considered below 200 MeV within the framework of the optical *** results calculated using the derived global optical potential are then compared with the existing experimental *** reliability of the global optical potential is further tested by predicting the elastic scattering data out of the mass and energy ranges,within which the global potential parameters are determined,and reasonable results are also obtained.

关键词： optical model potential elastic-scattering angular distribution reaction cross section

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Observation of giant quadrupole plasmon resonance in C60 in fast ion collisions

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Physical Review A 2022年第1期106卷 012820-012820页

作者： S. Kasthurirangan C.-Z. Gao P. M. Dinh L. Gulyás E. Suraud L. C. Tribedi Department of Nuclear and Atomic Physics Tata Institute of Fundamental Research Colaba Mumbai 400005 India Department of Physics Institute of Chemical Technology Matunga Mumbai 400019 India Institute of Applied Physics and Computational Mathematics Beijing 100088 China Laboratoire de Physique Théorique Université de Toulouse CNRS UPS F-31062 Toulouse Cedex France Institute of Nuclear Research of the Hungarian Academy of Sciences (ATOMKI) H-4001 Debrecen Hungary School of Mathematics and Physics Queen's University Belfast University Road Belfast BT7 1NN Northern Ireland

Strong perturbation caused due to the Coulomb interaction with fast highly charged ions has been used to probe the quadrupole plasmon excitation in C60 fullerene. The electron-emission spectrum arising from a free C60 molecule reveals a double-peak structure due to the decay of the giant plasmon resonance. Using a state-of-the-art theoretical approach describing the electron dynamics by time-dependent density functional theory, with an explicit ionic background these two peaks are unambiguously identified as arising from the dipole and quadrupole modes of the plasmon. Furthermore, the electron angular distribution clearly shows a double-well-type distribution which is well reproduced by quadrupole and plasmon resonances. The dipole and quadrupole excitations combined with a long-range postcollisional Coulomb interaction shows excellent agreement with the observed anisotropic angular distribution. The present paper serves as an independent confirmation of the presence of a substantial quadrupole plasmon contribution in molecular systems.

关键词： Atomic & molecular clusters Electronic excitation & ionization

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A Universal Description of Stochastic Oscillators

arXiv

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arXiv 2023年

作者： Pérez-Cervera, Alberto Gutkin, Boris Thomas, Peter J. Lindner, Benjamin Universidad Complutense de Madrid Instituto de Matemática Inderdisciplinar Madrid Spain Group for Neural Theory LNC2 INSERM U960 DEC Ecole Normale Supérieure - PSL University Paris France Department of Mathematics Applied Mathematics and Statistics Case Western Reserve University ClevelandOH United States Department of Physics Bernstein Center for Computational Neuroscience Humboldt University Berlin Germany

Many systems in physics, chemistry and biology exhibit oscillations with a pronounced random component. Such stochastic oscillations can emerge via different mechanisms, for example linear dynamics of a stable focus with fluctuations, limit-cycle systems perturbed by noise, or excitable systems in which random inputs lead to a train of pulses. Despite their diverse origins, the phenomenology of random oscillations can be strikingly similar. Here we introduce a nonlinear transformation of stochastic oscillators to a new complex-valued function Q∗1(x) that greatly simplifies and unifies the mathematical description of the oscillator’s spontaneous activity, its response to an external time-dependent perturbation, and the correlation statistics of different oscillators that are weakly coupled. The function Q∗1(x) is the eigenfunction of the Kolmogorov backward operator with the least negative (but non-vanishing) eigenvalue λ1 = µ1 + iω1. The resulting power spectrum of the complex-valued function is exactly given by a Lorentz spectrum with peak frequency ω1 and half-width µ1;its susceptibility with respect to a weak external forcing is given by a simple one-pole filter, centered around ω1;and the cross-spectrum between two coupled oscillators can be easily expressed by a combination of the spontaneous power spectra of the uncoupled systems and their susceptibilities. Our approach makes qualitatively different stochastic oscillators comparable, provides simple characteristics for the coherence of the random oscillation, and gives a framework for the description of weakly coupled oscillators. Copyright © 2023, The Authors. All rights reserved.

关键词： Power spectrum

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Emulating Complex Synapses Using Interlinked Proton Conductors

arXiv

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arXiv 2024年

作者： Zhang, Lifu Li, Ji-An Hu, Yang Jiang, Jie Lai, Rongjie Benna, Marcus K. Shi, Jian Department of Materials Science and Engineering Rensselaer Polytechnic Institute TroyNY12180 United States Neurosciences Graduate Program University of California San Diego La Jolla CA92093 United States Department of Mathematics Purdue University West LafayetteIN47907 United States Department of Neurobiology School of Biological Sciences University of California at San Diego La Jolla CA92093 United States Department of Physics Applied Physics and Astronomy Rensselaer Polytechnic Institute TroyNY12180 United States

In terms of energy efficiency and computational speed, neuromorphic electronics based on non-volatile memory devices is expected to be one of most promising hardware candidates for future artificial intelligence (AI). However, catastrophic forgetting, networks rapidly overwriting previously learned weights when learning new tasks, remains as a pivotal hurdle in either digital or analog AI chips for unleashing the true power of brain-like computing. To address catastrophic forgetting in the context of online memory storage, a complex synapse model (the Benna-Fusi model) has been proposed recently[1], whose synaptic weight and internal variables evolve following a diffusion dynamics. In this work, by designing a proton transistor with a series of charge-diffusion-controlled storage components, we have experimentally realized the Benna-Fusi artificial complex synapse. The memory consolidation from coupled storage components is revealed by both numerical simulations and experimental observations. Different memory timescales for the complex synapse are engineered by the diffusion length of charge carriers, the capacity and number of coupled storage components. The advantage of the demonstrated complex synapse in both memory capacity and memory consolidation is revealed by neural network simulations of face familiarity detection. Our experimental realization of the complex synapse suggests a promising approach to enhance memory capacity and to enable continual learning. Copyright © 2024, The Authors. All rights reserved.

关键词： computational efficiency

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THE COMPLEX INTERPLAY BETWEEN RISK TOLERANCE AND THE SPREAD OF INFECTIOUS DISEASES

arXiv

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arXiv 2024年

作者： Nguyen, Maximilian Freedman, Ari Cheung, Matthew Saad-Roy, Chadi Espinoza, Baltazar Grenfell, Bryan Levin, Simon Lewis-Sigler Institute Princeton University PrincetonNJ08544 United States Department of Ecology and Evolutionary Biology Princeton University PrincetonNJ United States Program in Applied and Computational Mathematics Princeton University PrincetonNJ United States Miller Institute for Basic Research in Science Department of Integrative Biology University of California Berkeley BerkeleyCA United States Biocomplexity Institute University of Virginia CharlottesvilleVA United States

Risk-driven behavior provides a feedback mechanism through which individuals both shape and are collectively affected by an epidemic. We introduce a general and flexible compartmental model to study the effect of heterogeneity in the population with regards to risk tolerance. The interplay between behavior and epidemiology leads to a rich set of possible epidemic dynamics. Depending on the behavioral composition of the population, we find that increasing heterogeneity in risk tolerance can either increase or decrease the epidemic size. We find that multiple waves of infection can arise due to the interplay between transmission and behavior, even without the replenishment of susceptibles. We find that increasing protective mechanisms such as the effectiveness of interventions, the number of risk-averse people in the population, and the duration of intervention usage reduces the epidemic overshoot. When the protection is pushed past a critical threshold, the epidemic dynamics enter an underdamped regime where the epidemic size exactly equals the herd immunity threshold. Lastly, we can find regimes where epidemic size does not monotonically decrease with a population that becomes increasingly risk-averse. Copyright © 2024, The Authors. All rights reserved.

关键词： Epidemiology

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Predicting nonequilibrium Green’s function dynamics and photoemission spectra via nonlinear integral operator learning

arXiv

引用

arXiv 2024年

作者： Zhu, Yuanran Yin, Jia Reeves, Cian C. Yang, Chao Vlček, Vojtěch Applied Mathematics and Computational Research Division Lawerence Berkeley National Laboratory Berkeley94720 United States School of Mathematical Sciences Fudan University Shanghai200437 China Department of Physics University of California Santa Barbara Santa Barbara93117 United States Department of Chemistry and Biochemistry University of California Santa Barbara Santa Barbara93117 United States Department of Materials University of California Santa Barbara Santa Barbara93117 United States

Understanding the dynamics of nonequilibrium quantum many-body systems is an important research topic in a wide range of fields across condensed matter physics, quantum optics, and high-energy physics. However, numerical studies of large-scale nonequilibrium phenomena in realistic materials face serious challenges due to intrinsic high-dimensionality of quantum many-body problems and the absence of time-invariance. The nonequilibrium properties of many-body systems can be described by the dynamics of the correlator, or the Green’s function of the system, whose time evolution is given by a high-dimensional system of integro-differential equations, known as the Kadanoff-Baym equations (KBEs). The time-convolution term in KBEs, which needs to be recalculated at each time step, makes it difficult to perform long-time numerical simulation. In this paper, we develop an operator-learning framework based on Recurrent Neural Networks (RNNs) to address this challenge. We utilize RNNs to learn the nonlinear mapping between Green’s functions and convolution integrals in KBEs. By using the learned operators as a surrogate model in the KBE solver, we obtain a general machine-learning scheme for predicting the dynamics of nonequilibrium Green’s functions. Besides significant savings per each time step, the new methodology reduces the temporal computational complexity from O(Nt3) to O(Nt) where Nt is the number of steps taken in a simulation, thereby making it possible to study large many-body problems which are currently infeasible with conventional KBE solvers. Through various numerical examples, we demonstrate the effectiveness of the operator-learning based approach in providing accurate predictions of physical observables such as the reduced density matrix and time-resolved photoemission spectra. Moreover, our framework exhibits clear numerical convergence and can be easily parallelized, thereby facilitating many possible further developments and applications. Copyright © 2024

关键词： Quantum optics

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