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We compare approaches to evaluation of decoherence at low temperatures in two-state quantum systems weakly coupled to the environment. By analyzing an exactly solvable model, we demonstrate that a non-Markovian approximation scheme yields…

Mesoscale and Nanoscale Physics · Physics 2010-10-12 Dmitry Solenov , Vladimir Privman

We introduce a minimization formulation for the determination of a finite-dimensional, time-dependent, orthonormal basis that captures directions of the phase space associated with transient instabilities. While these instabilities have…

Computational Physics · Physics 2016-04-27 Hessam Babaee , Themistoklis Sapsis

Tiny Recursive Models (TRM) achieve strong results on reasoning tasks through iterative refinement of a shared network. We investigate whether these recursive mechanisms transfer to Quality Estimation (QE) for low-resource languages using a…

Computation and Language · Computer Science 2026-03-17 Umar Abubacar , Roman Bauer , Diptesh Kanojia

Anisotropic decompositions using representation systems such as curvelets, contourlet, or shearlets have recently attracted significantly increased attention due to the fact that they were shown to provide optimally sparse approximations of…

Functional Analysis · Mathematics 2015-03-17 Gitta Kutyniok

The purpose of this paper is to develop a model reduction theory for linear quantum stochastic systems that are commonly encountered in quantum optics and related fields, modeling devices such as optical cavities and optical parametric…

Quantum Physics · Physics 2013-08-29 Hendra I. Nurdin

We present a low-complexity algorithm to calculate the correlation energy of periodic systems in second-order M\o ller-Plesset perturbation theory (MP2). In contrast to previous approximation-free MP2 codes, our implementation possesses a…

Chemical Physics · Physics 2017-03-16 Tobias Schäfer , Benjamin Ramberger , Georg Kresse

Most of the existing multi-relational network embedding methods, e.g., TransE, are formulated to preserve pair-wise connectivity structures in the networks. With the observations that significant triangular connectivity structures and…

Social and Information Networks · Computer Science 2018-06-11 Xin Li , Huiting Hong , Lin Liu , William K. Cheung

Recent results show that Kochen-Specker (KS) sets of observables are fundamental to quantum information, computation, and foundations beyond previous expectations. Among KS sets, those that are unique up to unitary transformations (i.e.,…

Quantum Physics · Physics 2025-07-28 Stefan Trandafir , Adán Cabello

The Morse potential quantum system is a realistic model for studying vibrations of atoms in a diatomic molecule. This system is very close to the harmonic oscillator one. We thus propose a construction of squeezed coherent states similar to…

Mathematical Physics · Physics 2010-10-19 M. Angelova , V. Hussin

In non-equilibrium quantum many-body systems, the quantum Mpemba effect (QME) emerges as a counterintuitive phenomenon: systems exhibiting greater initial symmetry breaking restore symmetry faster than those with less. While theoretical…

Controller synthesis techniques for continuous systems with respect to temporal logic specifications typically use a finite-state symbolic abstraction of the system model. Constructing this abstraction for the entire system is…

Systems and Control · Computer Science 2017-08-10 Kaushik Mallik , Anne-Kathrin Schmuck , Sadegh Soudjani , Rupak Majumdar

This paper extends the high-order entropy stable (ES) adaptive moving mesh finite difference schemes developed in [14] to the two- and three-dimensional (multi-component) compressible Euler equations with the stiffened equation of state.…

Numerical Analysis · Mathematics 2022-08-10 Shangting Li , Junming Duan , Huazhong Tang

Reconstructing high-dimensional spatiotemporal fields from sparse point-sensor measurements is a central challenge in learning parametric PDE dynamics. Existing approaches often struggle to generalize across trajectories and parameter…

Machine Learning · Computer Science 2026-02-05 Yanjie Tong , Peng Chen

We establish an intriguing connection between quantum phase transitions and bifurcations in the reduced fidelity between two different reduced density matrices for quantum lattice many-body systems with symmetry-breaking orders. Our finding…

Strongly Correlated Electrons · Physics 2009-05-20 Jin-Hua Liu , Qian-Qian Shi , Jian-Hui Zhao , Huan-Qiang Zhou

We construct on the category of diffeological spaces a Quillen model structure having smooth weak homotopy equivalences as the class of weak equivalences.

Algebraic Topology · Mathematics 2024-07-19 Tadayuki Haraguchi , Kazuhisa Shimakawa

We propose a new approach to represent nonparametrically the linear dependence structure of a spatio-temporal process in terms of latent common factors. Though it is formally similar to the existing reduced rank approximation methods…

Methodology · Statistics 2018-03-20 Da Huang , Qiwei Yao , Rongmao Zhang

We construct the four-mode squeezed states and study their physical properties. These states describe two linearly-coupled quantum scalar fields, which makes them physically relevant in various contexts such as cosmology. They are shown to…

Quantum Physics · Physics 2022-01-04 Thomas Colas , Julien Grain , Vincent Vennin

Temporal Relation Extraction (TRE) requires identifying how two events or temporal expressions are related in time. Existing attention-based models often highlight globally salient tokens but overlook the pair-specific cues that actually…

Computation and Language · Computer Science 2026-03-25 Duy Dao Do , Anaïs Halftermeyer , Thi-Bich-Hanh Dao

The Transformer architecture, despite its widespread success, struggles with long-context scenarios due to quadratic computation and linear memory growth. While various linear attention variants mitigate these efficiency constraints by…

Machine Learning · Computer Science 2025-10-02 Yuqi Pan , Yongqi An , Zheng Li , Yuhong Chou , Ruijie Zhu , Xiaohui Wang , Mingxuan Wang , Jinqiao Wang , Guoqi Li

The recent framework of compressive statistical learning aims at designing tractable learning algorithms that use only a heavily compressed representation-or sketch-of massive datasets. Compressive K-Means (CKM) is such a method: it…

Machine Learning · Computer Science 2018-08-01 Vincent Schellekens , Laurent Jacques
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