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A generalization of the Drude model is studied. On the one hand, the free motion of the particles is allowed to be sub- or superdiffusive; on the other hand, the distribution of the time delay between collisions is allowed to have a long…

Condensed Matter · Physics 2009-10-30 Hermann Schulz-Baldes

Density functional theory (DFT) is an essential building block for modern theoretical physics, chemistry, and engineering, especially those concerning electronic properties. Through decades of development, various program packages for…

Materials Science · Physics 2022-11-21 Yusuke Nomura , Ryosuke Akashi

Conceiving a molecule as composed of smaller molecular fragments, or subunits, is one of the pillars of the chemical and physical sciences, and leads to productive methods in quantum chemistry. Using a fragmentation scheme, efficient…

Chemical Physics · Physics 2015-04-14 Martín A. Mosquera , Adam Wasserman

The angular and frequency correlation functions of the transmission coefficient for light propagation through a strongly scattering amplifying medium are considered. It is found that just as in the case of an elastic scattering medium the…

Mesoscale and Nanoscale Physics · Physics 2009-10-31 A. A. Burkov , A. Yu. Zyuzin

We propose to describe the dynamics of phase transitions in terms of a non-stationary Generalized Langevin Equation for the order parameter. By construction, this equation is non-local in time, i.e.~it involves memory effects whose…

Statistical Mechanics · Physics 2021-02-10 Hugues Meyer , Fabian Glatzel , Wilkin Wöhler , Tanja SChilling

Phenomena involving multiple scattering, despite having attracted considerable attention in physics for decades, continue to generate unexpected and counterintuitive behaviours prompting further studies. For optical scattering, the memory…

We present an application of our new theoretical formulation of quantum dynamics, moment propagation theory (MPT) (Boyer et al., J. Chem. Phys. 160, 064113 (2024)), for employing machine-learning techniques to simulate the quantum dynamics…

Chemical Physics · Physics 2024-12-09 Nicholas J. Boyer , Christopher Shepard , Ruiyi Zhou , Jianhang Xu , Yosuke Kanai

Time-dependent density functional theory (TDDFT) is a widely used method to investigate electron dynamics under external time-dependent perturbations such as laser fields. In this work, we present a machine learning approach to accelerate…

Materials Science · Physics 2025-12-02 Karan Shah , Attila Cangi

We theoretically analyse D.C. resistivity($\rho$) in the Kondo-lattice model using the powerful memory function approach. The complete temperature evolution of $\rho$ is investigated using the W\"{o}lfle-G\"{o}tze expansion of the memory…

Strongly Correlated Electrons · Physics 2021-01-11 Komal Kumari , Raman Sharma , Navinder Singh

Atom scattering is becoming recognized as a sensitive probe of the electron-phonon interaction parameter $\lambda$ at metal and metal-overlayer surfaces. Here, the theory is developed linking $\lambda$ to the thermal attenuation of atom…

Superconductivity · Physics 2020-05-20 G. Benedek , J. R. Manson , S. Miret-Artés

An electron density functional approach for the calculation of the nuclear multipole moments is presented. The electronic matrix elements entering the experimentally observed hyperfine electron-nucleus interaction constants in atoms are…

Nuclear Theory · Physics 2007-05-23 R. L. Pavlov , P. P. Raychev , V. P. Garistov , M. Dimitrova-Ivanovich , J. Maruani

The effects of the deuteron breakup are estimated for the $\Lambda$-deuteron momentum correlation function. Faddeev amplitudes in calculating low-energy $\Lambda$-deuteron scattering can provide not only the elastic scattering part but also…

Nuclear Theory · Physics 2025-10-23 M. Kohno , H. Kamada

We propose to verify relations between quantities which characterize scaling properties of high energy density fluctuations in terms of factorial moments and newly introduced associated frequency moments. Typical examples are presented in…

High Energy Physics - Phenomenology · Physics 2014-11-17 Mikulaas Blazek

The embedding method for the calculation of the conductance through interacting systems connected to single channel leads is generalized to obtain the full complex transmission amplitude that completely characterizes the effective…

Mesoscale and Nanoscale Physics · Physics 2015-06-04 Rafael A. Molina , Peter Schmitteckert , Dietmar Weinmann , Rodolfo A. Jalabert , Philippe Jacquod

We propose a constructive approach to building temporal point processes that incorporate dependence on their history. The dependence is modeled through the conditional density of the duration, i.e., the interval between successive event…

Methodology · Statistics 2025-10-31 Xiaotian Zheng , Athanasios Kottas , Bruno Sansó

Geometric moments and moment invariants of image artifacts have many uses in computer vision applications, e.g. shape classification or object position and orientation. Higher order moments are of interest to provide additional feature…

Computer Vision and Pattern Recognition · Computer Science 2020-09-22 William Diggin , Michael Diggin

Optical memory effects are well-known types of amplitude-domain wave correlation enabling control over light scattered through diffusive materials or multimode fibers. In this letter, we report the phenomenon of random polarization memory…

Optics · Physics 2025-09-09 Gauri Arora , Lyubov V. Amitonova

Starting from the magnetic total-moment sum rule of neutron scattering, we derive an explicit connection between ordered-moment reduction and the long-time limit of the intermediate scattering function. We show that this time-domain…

Strongly Correlated Electrons · Physics 2026-03-04 Fanjun Xu

Memory effects play a key role in the dynamics of strongly correlated systems driven out of equilibrium. In the present study, we explore the nature of memory in the nonequilibrium Anderson impurity model. The Nakajima--Zwanzig--Mori…

Strongly Correlated Electrons · Physics 2013-01-28 Guy Cohen , Eran Rabani

We conduct a systematic study of the approximation properties of Transformer for sequence modeling with long, sparse and complicated memory. We investigate the mechanisms through which different components of Transformer, such as the…

Machine Learning · Computer Science 2024-10-31 Mingze Wang , Weinan E
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