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[Licence| Download | New Version Template] aewq_v1_0.tar.gz(5139 Kbytes)
Manuscript Title: iQIST: An open source continuous-time quantum Monte Carlo impurity solver toolkit
Authors: Li Huang, Yilin Wang, Zi Yang Meng, Liang Du, Philipp Werner, Xi Dai
Program title: iQIST
Catalogue identifier: AEWQ_v1_0
Distribution format: tar.gz
Journal reference: Comput. Phys. Commun. 195(2015)140
Programming language: Fortran 2008 and Python.
Computer: Desktop PC, laptop, high performance computing cluster.
Operating system: Unix, Linux, Mac OS X, Windows.
Has the code been vectorised or parallelized?: Yes, it is parallelized by MPI and OpenMP
RAM: Depends on the complexity of the problem
Keywords: Quantum impurity model, Continuous-time quantum Monte Carlo algorithm, Dynamical mean-field theory.
Classification: 7.3.

External routines: BLAS, LAPACK, Latex is required to build the user manual.

Nature of problem:
Quantum impurity models were originally proposed to describe magnetic impurities in metallic hosts. In these models, the Coulomb interaction acts between electrons occupying the orbitals of the impurity atom. Electrons can hop between the impurity and the host, and in an action formulation, this hopping is described by a time-dependent hybridization function. Nowadays quantum impurity models have a broad range of applications, from the description of heavy fermion systems, and Kondo insulators, to quantum dots in nano-science. They also play an important role as auxiliary problems in dynamical mean-field theory and its diagrammatic extensions [1-3], where an interacting lattice model is mapped onto a quantum impurity model in a self-consistent manner. Thus, the accurate and efficient solution of quantum impurity models becomes an essential task.

Solution method:
The quantum impurity model can be solved by the numerically exact continuous-time quantum Monte Carlo method, which is the most efficient and powerful impurity solver for finite temperature simulations. In the iQIST software package, we implemented the hybridization expansion version of continuous-time quantum Monte Carlo algorithm. Both the segment representation and general matrix formalism are supported. The key idea of this algorithm is to expand the partition function diagrammatically in powers of the impurity-bath hybridization, and to stochastically sample these diagrams to all relevant orders using the Metropolis Monte Carlo algorithm. For a detailed review of the continuous-time quantum Monte Carlo algorithms, please refer to [4].

Running time:
Depends on the complexity of the problem. The sample run supplied in the distribution takes about 1.5 minutes.

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[2] G. Kotliar, S. Y. Savrasov, K. Haule, V. S. Oudovenko, O. Parcollet, and C. A. Marianetti, Rev. Mod. Phys. 78, 865 (2006)
[3] T. Maier, M. Jarrell, T. Pruschke, and M. H. Hettler, Rev. Mod. Phys. 77, 1027 (2005)
[4] E. Gull, A. J. Millis, A. I. Lichtenstein, A. N. Rubtsov, M. Troyer, and Philipp Werner, Rev. Mod. Phys. 83, 349 (2011)