اشترك بالحزمة الذهبية واحصل على وصول غير محدود شمرا أكاديميا
تسجيل مستخدم جديدThe Python-based Simulations of Chemistry Framework (PySCF)
52
0
0.0
(
0
)
اسأل ChatGPT حول البحث
ﻻ يوجد ملخص باللغة العربية
PySCF is a general-purpose electronic structure platform designed from the ground up to emphasize code simplicity, both to aid new method development, as well as for flexibility in computational workflow. The package provides a wide range of tools to support simulations of finite size systems, extended systems with periodic boundary conditions, low dimensional periodic systems, and custom Hamiltonians, using mean-field and post-mean-field methods with standard Gaussian basis functions. To ensure easy of extensibility, PySCF uses the Python language to implement almost all its features, while computationally critical paths are implemented with heavily optimized C routines. Using this combined Python/C implementation, the package is as efficient as the best existing C or Fortran based quantum chemistry programs. In this paper we document the capabilities and design philosophy of the current version of the PySCF package.
قيم البحث
اقرأ أيضاً
PYSCF is a Python-based general-purpose electronic structure platform that both supports first-principles simulations of molecules and solids, as well as accelerates the development of new methodology and complex computational workflows. The present
paper explains the design and philosophy behind PYSCF that enables it to meet these twin objectives. With several case studies, we show how users can easily implement their own methods using PYSCF as a development environment. We then summarize the capabilities of PYSCF for molecular and solid-state simulations. Finally, we describe the growing ecosystem of projects that use PYSCF across the domains of quantum chemistry, materials science, machine learning and quantum information science.
Fanpy is a free and open-source Python library for developing and testing multideterminant wavefunctions and related ab initio methods in electronic structure theory. The main use of Fanpy is to quickly prototype new methods by making it easier to tr
ansfer the mathematical conception of a new wavefunction ans{a}tze to a working implementation. Fanpy uses the framework of our recently introduced Flexible Ansatz for N-electron Configuration Interaction (FANCI), where multideterminant wavefunctions are represented by their overlaps with Slater determinants of orthonormal spin-orbitals. In the simplest case, a new wavefunction ansatz can be implemented by simply writing a function for evaluating its overlap with an arbitrary Slater determinant. Fanpy is modular in both implementation and theory: the wavefunction model, the systems Hamiltonian, and the choice of objective function are all independent modules. This modular structure makes it easy for users to mix and match different methods and for developers to quickly try new ideas. Fanpy is written purely in Python with standard dependencies, making it accessible for most operating systems; it adheres to principles of modern software development, including comprehensive documentation, extensive testing, and continuous integration and delivery protocols. This article is considered to be the official release notes for the Fanpy library.
Quantum chemistry simulations of four industrially relevant molecules are reported. Dissociation curves and dipole moments are reported for lithium hydride (LiH), hydrogen sulfide (H2S), lithium hydrogen sulfide (LiSH) and lithium sulfide (Li2S). Her
ein, we demonstrate the ability to calculate dipole moments using up to 21 qubits on a quantum simulator for a lithium sulfur salt molecule, and demonstrate the ability to calculate the dipole moment of the LiH molecule on the IBM Q Valencia device using four qubits. This is the first example to the best of our knowledge of dipole moment calculations being performed on quantum hardware.
As quantum computing hardware systems continue to advance, the research and development of performant, scalable, and extensible software architectures, languages, models, and compilers is equally as important in order to bring this novel coprocessing
capability to a diverse group of domain computational scientists. For the field of quantum chemistry, applications and frameworks exists for modeling and simulation tasks that scale on heterogeneous classical architectures, and we envision the need for similar frameworks on heterogeneous quantum-classical platforms. Here we present the XACC system-level quantum computing framework as a platform for prototyping, developing, and deploying quantum-classical software that specifically targets chemistry applications. We review the fundamental design features in XACC, with special attention to its extensibility and modularity for key quantum programming workflow interfaces, and provide an overview of the interfaces most relevant to simulations of chemistry. A series of examples demonstrating some of the state-of-the-art chemistry algorithms currently implemented in XACC are presented, while also illustrating the various APIs that would enable the community to extend, modify, and devise new algorithms and applications in the realm of chemistry.
Several chemical reactions catalyzed by plasmonic nanoparticles show enhanced rates under visible-light-excitation of the localized surface plasmon resonance of the nanoparticles. But it has been argued that there is an associated photothermal effect
that can complicate the analysis and/or interpretation of the nature of the role played by plasmon excitation. This Viewpoint discusses this dilemma and provides some best practices for accounting for photothermal contributions in plasmon-excitation-driven chemistry. A classification of plasmonic chemistry into plasmonic photocatalysis and plasmonic photosynthesis is also proposed. It is argued that photosynthetic reactions, which require a Gibbs free energy input, constitute an ultimate test of the non-thermal, photochemical action of plasmon excitation.
سجل دخول لتتمكن من نشر تعليقات
التعليقات
جاري جلب التعليقات
سجل دخول لتتمكن من متابعة معايير البحث التي قمت باختيارها
