代码空间


摘要(Abstract)

GULP最初设计的目的是拟合立场，现在已经逐步发展成为模拟凝聚态物质的通用代码，可以模拟无机固体、团聚体、缺陷、表面、界面以及聚合物等。gulp 外文名 General Utility Lattice Program 模拟的类型 （各维的都能模拟） 能量最小化 GULP里面比较出色的1 Quench your thirst for knowledge 2 GULP(General Utility Lattice Program )GULP的功能如下： 模拟的类型-（各维的都能模拟）0-D (clusters and embedded defects) 1-D (polymers) 2-D (slabs and surfaces) 3-D (bulk materials) 能量最小化-（GULP里面比较出色的，方法也比较多） constant pressure / constant volume / unit cell only / isotropic （恒压/恒容/单位晶胞/各向同性） thermal/optical calculations （热/光学计算） application of external pressure （应用外部压力） user specification of degrees of freedom for relaxation （可以指定那些自由度要驰豫）r elaxation of spherical region about a given ion or point （给定离子或质点的球形区域的驰豫） symmetry constrained relaxation （对称性限制驰豫） unconstrained relaxation （无限制驰豫） constraints for fractional coordinates and cell strains （可对分数坐标和晶胞应力加限制） Newton/Raphson, conjugate gradients or Rational Function optimisers （几种最小化算法）


主题(Topic)
interactive gulp
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reinforcement-learning reinforcement-learning- interactive-learning adversarial-reinforcement-learning applied-reinforcement-learning berkeley-reinforcement-learning carla-reinforcement-learning causal-reinforcement-learning checkers-reinforcement-learning constrained-reinforcement-learning continuous-reinforcement-learning coursera-reinforcement-learning curriculum-reinforcement-learning deep-reinforcement-learning dissecting-reinforcement-learning distributed-reinforcement-learning feudal-reinforcement-learning hierachical-reinforcement-learning hierarchical-reinforcement-learning inverse-reinforcement-learning meta-reinforcement-learning minecraft-reinforcement-learning multiagent-reinforcement-learning munchausen-reinforcement-learning practical-reinforcement-learning pytorch-reinforcement-learning recurrent-reinforcement-learning reinforcement-learning-agent reinforcement-learning-agents reinforcement-learning-alberta reinforcement-learning-algorithm reinforcement-learning-algorithms reinforcement-learning-analysis reinforcement-learning-books reinforcement-learning-bot reinforcement-learning-bots reinforcement-learning-cartpole reinforcement-learning-concepts reinforcement-learning-datasets reinforcement-learning-environ reinforcement-learning-environment reinforcement-learning-environments reinforcement-learning-examples reinforcement-learning-excercises reinforcement-learning-exercises reinforcement-learning-frame reinforcement-learning-options reinforcement-learning-papers reinforcement-learning-playground
项目(Project)
tzuhsial/ISCR-DRL zyxue/rljs awjuliani/DeepRL-Agents awesome-reinforcement-learning-zh Spandana-K-R/Interactive-Reinforcement-Learning konichuvak/rl_experiments IEEE-NITK/Interactive-Multi-Agent-Reinforcement-Learning Yashwanthv21/Reinforcement-Learning sergeLabo/balance singhgaurav2323/reinforcement simerplaha/reinforcement-learning levimcclenny/Reinforcement_Learning Issuenate/RL-Policy-Gradient-Actor-Critic knightron0/cartpole-openAI cbalkig/DL-RL-Gamer mtimjones/QLearning ChengshuLi/HRL4IN zyxue/sutton-barto-rl-exercises aprimadi/deep-rl-imitation vdthatte/OpenAI-Cartpole zhongruiwang/memristor_RL soroosh-rz/Deep-Reinforcement-Learning camandmum22/gridworld_mdp makototakamatsu/reinforcement_learning sarthak-chakraborty/RL-assgn tims457/RL_Agent_Notebooks aquib1011/RL-Cartpole kochlisGit/Reinforcement-Learning nazariinyzhnyk/2048RL Ctiely/RL_example 全部项目