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It is believed that one of the first useful applications for a quantum computer will be the preparation of groundstates of molecular Hamiltonians. A crucial task involving state preparation and readout is obtaining physical observables of…

Many systems in biology, physics and engineering can be described by systems of ordinary differential equation containing many parameters. When studying the dynamic behavior of these large, nonlinear systems, it is useful to identify and…

Molecular Networks · Quantitative Biology 2016-04-13 Heather A. Harrington , Dhagash Mehta , Helen M. Byrne , Jonathan D. Hauenstein

The quark model was formulated in 1964 to classify mesons as bound states made of a quark-antiquark pair, and baryons as bound states made of three quarks. For a long time all known mesons and baryons could be classified within this scheme.…

Understanding hadronic interactions is crucial for investigating the properties of unstable hadrons, since measuring physical quantities for unstable hadrons including the resonance mass and decay width requires simultaneous calculations of…

High Energy Physics - Lattice · Physics 2015-03-31 Takeshi Yamazaki

We investigate the extent to which supervised machine learning techniques can distinguish between neutron-star matter models using macroscopic and oscillation-related quantities derived from theoretical stellar configurations. Four…

High Energy Astrophysical Phenomena · Physics 2026-05-26 Wasif Husain

The strongly repulsive core of the short-range nucleon-nucleon interaction leads to the existence of high-momentum nucleons in nuclei. Inclusive electron scattering can be used to probe these high-momentum nucleons and study the nature of…

High Energy Physics - Phenomenology · Physics 2009-11-10 J. Arrington

Accurate simulations of the Hubbard model are crucial to understanding strongly correlated phenomena, where small energy differences between competing orders demand high numerical precision. In this work, Neural Quantum States are used to…

Strongly Correlated Electrons · Physics 2025-10-14 Louis Sharma , Ahmedeo Shokry , Rajah Nutakki , Olivier Simard , Michel Ferrero , Filippo Vicentini

We investigate heavy quark symmetries for heavy meson hadronic molecules, and explore the consequences of assuming the X(3872) and $Z_b(10610)$ as an isoscalar $D\bar D^*$ and an isovector $B\bar B^*$ hadronic molecules, respectively. The…

High Energy Physics - Phenomenology · Physics 2014-09-16 F. -K. Guo , C. Hidalgo-Duque , J. Nieves , A. Ozpineci , M. Pavon Valderrama

Nonlinear dynamical systems such as Lorenz63 equations are known to be chaotic in nature and sensitive to initial conditions. As a result, a small perturbation in the initial conditions results in deviation in state trajectory after a few…

Dynamical Systems · Mathematics 2021-06-17 Megha Subramanian , Ramakrishna Tipireddy , Samrat Chatterjee

Despite being the main tool to visualize molecules at the atomic scale, AFM with CO-functionalized metal tips is unable to chemically identify the observed molecules. Here we present a strategy to address this challenging task using deep…

Materials Science · Physics 2025-09-03 Jaime Carracedo-Cosme , Carlos Romero-Muñiz , Pablo Pou , Rubén Pérez

Data-driven methods based on machine learning have the potential to accelerate computational analysis of atomic structures. In this context, reliable uncertainty estimates are important for assessing confidence in predictions and enabling…

Machine Learning · Computer Science 2021-11-04 Jonas Busk , Peter Bjørn Jørgensen , Arghya Bhowmik , Mikkel N. Schmidt , Ole Winther , Tejs Vegge

Inspired by the recent observation of $\chi_{c0}(3930)$, $X(4685)$ and $X(4630)$ by the LHCb Collaboration and some exotic resonances such as $X(4350)$, $X(4500)$, etc. by several experiment collaborations, the $cs\bar{c}\bar{s}$ tetraquark…

High Energy Physics - Phenomenology · Physics 2021-11-10 Xuejie Liu , Hongxia Huang , Jialun Ping , Dianyong Chen , Xinmei Zhu

We introduce a framework for reasoning about what meaning is captured by the neurons in a trained neural network. We provide a strategy for discovering meaning by training a second model (referred to as an observer model) to classify the…

Machine Learning · Computer Science 2021-03-16 Eric E. Allen

Neural networks are being used to improve the probing of the state spaces of many particle systems as approximations to wavefunctions and in order to avoid the recurring sign problem of quantum monte-carlo. One may ask whether the usual…

Machine Learning · Computer Science 2022-06-02 Andrei T. Patrascu

In chemical reaction network theory, ordinary differential equations are used to model the temporal change of chemical species concentration. As the functional form of these ordinary differential equations systems is derived from an…

Molecular Networks · Quantitative Biology 2025-02-27 Anna C. M. Thöni , William E. Robinson , Yoram Bachrach , Wilhelm T. S. Huck , Tal Kachman

Recently observed spectrum of $P_c$ states exhibits a strong link to $\Sigma_c \bar{D}^{(*)}$ thresholds. In spite of successful molecular interpretations, we still push forward to wonder whether there exist finer structures. Utilizing the…

High Energy Physics - Phenomenology · Physics 2020-04-01 Hao Xu , Qiang Li , Chao-Hsi Chang , Guo-Li Wang

The properties of the resonance X(3872) are discussed under the assumption that this resonance is dominantly a `molecular' $J^{PC}=1^{++}$ state of neutral $D$ and $D^*$ mesons. It is argued that in these properties should dominate the…

High Energy Physics - Phenomenology · Physics 2008-11-26 M. B. Voloshin

The binding system of a hadron and a nucleus is a topic of great interest for investigating the hadron properties. In the heavy-flavor region, the attraction between a $P(=\bar{D},B)$ meson and a nucleon $N$ can appear, where the $PN-P^\ast…

Nuclear Theory · Physics 2019-08-14 Yasuhiro Yamaguchi , Shigehiro Yasui

In this work, we first propose the isovector $nD^{*}_0(2400)^0$ molecular state to explain the enhancement structure around 3250 MeV ($X_c(3250)^0$) in the $\Sigma_c^{++}\pi^-\pi^-$ invariant mass spectrum newly observed by the BaBar…

High Energy Physics - Phenomenology · Physics 2012-08-21 Jun He , Dian-Yong Chen , Xiang Liu

Automated cooking machine is a goal for the future. The main aim is to make the cooking process easier, safer, and create human welfare. To allow robots to accurately perform the cooking activities, it is important for them to understand…

Computer Vision and Pattern Recognition · Computer Science 2021-06-01 Qi Zheng