QuDPy: A Python-based tool for computing ultrafast non-linear optical responses
QuDPy: A Python-based tool for computing ultrafast non-linear optical responses
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QuDPy：基于 Python 的工具，用于计算超快非线性光学响应
DOI：
10.1016/j.cpc.2023.108891
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发表时间：
2023
影响因子：
6.3
通讯作者：
Piryatinski, Andrei
中科院分区：
文献类型：
--
作者：
Shah, S.A.;Li, Hao;Bittner, Eric R.;Silva, Carlos;Piryatinski, Andrei
摘要非线性光学光谱学是一个发展很快的领域，它的理论和实验进展使包括化学、生物和物理在内的多个学科受益。然而，为了准确地解释相应的多维光谱，需要基于模型哈密顿的精确的量子动力学模拟。在本文中，我们介绍了我们的代码的初始版本QuDPy(Python中的量子动力学)，它为基于模型系统(包括开放量子系统)进行量子动力学模拟提供了一个强大的数值平台。我们方法的一个显著特点是能够通过直接的输入语法以双面费曼图的形式指定各种高阶光学响应路径。该语法概述了作用于系统随时间演化的密度矩阵的面侧或半侧光学相互作用的时间顺序。我们利用QuTip的量子动力学能力来模拟复杂系统的光谱响应，使我们几乎可以计算模型系统的任何n阶光学响应。为了说明我们方法的实用性，我们提供了一系列的实例计算。计划摘要计划标题：QuDPy CPC库指向计划文件的链接：https://doi.Org/10.17632/5xm9pm24cz.1开发者资源库链接：https://github.Com/sa-shah/QuDPy许可条款：麻省理工学院许可编程语言：Python(v3.7)补充材料：可通过Google Colab Files获得。示例1：https://tinyurl.Com/y3j5jmmr示例2：https://tinyurl.COM/37vwntn5外部包：·QuTip(v4.7)和依赖项Numpy、Matplotlib(https://qutip.Org/)·UFSS自动图表生成器(https://github.问题的性质：为了理解和解释多维超快光谱信号，需要对复杂系统进行准确的量子模拟。该代码提供了一种开源/多平台的方法，该方法便于在给定模型输入哈密顿量和浴场模型的情况下，对任意分子或材料系统产生高阶非线性光学响应。求解方法：我们使用双面Feynman图法[1，2]来(象征性地)产生一组响应函数，对应于系统对一系列激光脉冲的n阶非线性响应，然后使用UFSS程序包[3]，然后使用QuTip程序包[4]进行一系列精确的量子动力学计算，以生成对应于特定实验条件的数值响应和谱。参考文献[1]S.Mukamel，牛津大学出版社，1995。[2]P.Hamm，M.Zanni，2D红外光谱的概念和方法，剑桥大学出版社，2011。[3]Peter A.Rose，Jacob J.Krich，J.Chem。太棒了。[4]J.Johansson，P.Nation，F.Nori，Comput.太棒了。交警。184(4)(2013)1234-1240。
Abstract Nonlinear Optical Spectroscopy is a well-developed field with theoretical and experimental advances that have benefited multiple disciplines, including chemistry, biology, and physics. However, for the accurate interpretation of the corresponding multi-dimensional spectra, there is a need for precise quantum dynamical simulations based on model Hamiltonians. In this article, we present the initial release of our code, QuDPy (Quantum Dynamics in Python), which provides a robust numerical platform for performing quantum dynamics simulations based on model systems, including open quantum systems. A distinguishing feature of our approach is the ability to specify various high-order optical response pathways in the form of double-sided Feynman diagrams through a straightforward input syntax. This syntax outlines the time-ordering of ket-sided or bra-sided optical interactions acting on the time-evolving density matrix of the system. We utilize the quantum dynamics capabilities of QuTip to simulate the spectral response of complex systems, allowing us to compute virtually any n-th order optical response of the model system. To illustrate the utility of our approach, we provide a series of example calculations. Program summary Program Title: QuDPy CPC Library link to program files: https://doi. org/10.17632/5xm9pm24cz. 1 Developer's repository link: https://github. com/sa-shah/QuDPy Licensing provisions: MIT License Programming language: Python (v3. 7) Supplementary material: Available as Google Colab Files. Example 1: https://tinyurl. com/y3j5jmmr Example 2: https://tinyurl. com/37vwntn5 External packages:• QuTip (v. 4.7) and dependencies ie Numpy, Matplotlib (https://qutip. org/)• UFSS Automatic Diagram Generator (https://github. com/peterarose/ufss) Nature of problem: Accurate quantum simulations of complex systems are required in order to understand and interpret multi-dimensional ultrafast spectroscopic signals. This code provides an open-source/multi-platform method that facilitates the generation of higher-order non-linear optical responses for an arbitrary molecular or material system given a model input Hamiltonian and bath model. Solution method: We use the double-sided Feynman diagram method [1, 2] to generate (symbolically) a set of response functions corresponding to the n t h order non-linear response of the system to a series of laser pulses using the UFSS package [3] We then perform a series of accurate quantum dynamics calculations using the QuTip package [4] to generate the numerical response and spectra which correspond to specific experimental conditions. References [1] S. Mukamel, Principles of Nonlinear Optics and Spectroscopy, Oxford University Press, 1995.[2] P. Hamm, M. Zanni, Concepts and Methods of 2D Infrared Spectroscopy, Cambridge University Press, 2011.[3] Peter A. Rose, Jacob J. Krich, J. Chem. Phys. 154 (2021) 034109.[4] J. Johansson, P. Nation, F. Nori, Comput. Phys. Commun. 184 (4)(2013) 1234–1240.
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发表时间：
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期刊：
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影响因子：
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