References

Research papers on the DCA++ code and the underlying algorithms

DCA++

• DCA++: A software framework to solve correlated electron problems with modern quantum cluster methods
  U. R. Hähner, G. Alvarez, T. A. Maier, R. Solcà, P. Staar, M. S. Summers, and T. C. Schulthess,
  Comput. Phys. Commun. 246, 106709 (2020).

• Accelerating DCA++ (Dynamical Cluster Approximation) Scientific Application on the Summit Supercomputer
  G. Balduzzi, A. Chatterjee, Y. W. Li, P. W. Doak, U. R. Hähner, E. F. D'Azevedo, T. A. Maier and T. C. Schulthess
  Proc. 28th Int. Conf. on Parallel Architectures and Compilation Techniques (PACT), 433-444 (2019).

• DCA++ project: Sustainable and scalable development of a high-performance research code
  U. R. Hähner, G. Balduzzi, P. W. Doak, T. A. Maier, R. Solcà and T. C. Schulthess
  J. Phys.: Conf. Ser. 1290, 012017 (2019).

• Taking a Quantum Leap in Time to Solution for Simulations of High-Tc Superconductors
  P. Staar, T. A. Maier, M. S. Summers, G. Fourestey, R. Solca, and T. C. Schulthess,
  Proc. Int. Conf. on High Performance Computing, Networking, Storage and Analysis (SC13), 1:1-1:11 (2013).

Dynamical cluster approximation (DCA)

• Interlaced coarse-graining for the dynamic cluster approximation
  P. Staar, M. Jiang, U. R. Hähner, T. C. Schulthess, and T. A. Maier,
  Phys. Rev. B 93, 165144 (2016).

• Quantum cluster theories
  T. Maier, M. Jarrell, T. Pruschke, and M. H. Hettler,
  Rev. Mod. Phys. 77, 1027-80 (2005).

• Quantum Monte Carlo algorithm for nonlocal corrections to the dynamical mean-field approximation
  M. Jarrell, T. Maier, C. Huscroft, and S. Moukouri,
  Phys. Rev. B 64, 195130 (2001).

• Dynamical cluster approximation: Nonlocal dynamics of correlated electron systems
  M. H. Hettler, M. Mukherjee, M. Jarrell, and H. R. Krishnamurthy,
  Phys. Rev. B 61, 12739 (2000).

DCA⁺

• Two-particle correlations in a dynamic cluster approximation with continuous momentum dependence: Superconductivity in the two-dimensional Hubbard model
  P. Staar, T. Maier, and T. C. Schulthess,
  Phys. Rev. B 89, 195133 (2014).

• Dynamical cluster approximation with continuous lattice self-energy
  P. Staar, T. Maier, and T. C. Schulthess,
  Phys. Rev. B 88, 115101 (2013).

Quantum Monte Carlo (QMC) methods

• Efficient non-equidistant FFT approach to the measurement of single- and two-particle quantities in continuous time Quantum Monte Carlo methods
  P. Staar, T. A. Maier, and T. C. Schulthess,
  J. Phys.: Conf. Ser. 402, 012015 (2012).

• Continuous-time Monte Carlo methods for quantum impurity models
  E. Gull, A. J. Millis, A. I. Lichtenstein, A. N. Rubtsov, M. Troyer, and P. Werner,
  Rev. Mod. Phys. 83, 349-404 (2011).

Continuous-time auxiliary-field QMC

• Submatrix updates for the continuous-time auxiliary-field algorithm
  E. Gull, P. Staar, S. Fuchs, P. Nukala, M. S. Summers, T. Pruschke, T. C. Schulthess, and T. Maier,
  Phys. Rev. B 83, 075122 (2011)

• Continuous-time auxiliary-field Monte Carlo for quantum impurity models
  E. Gull, P. Werner, O. Parcollet, and M. Troyer,
  Europhys. Lett. 82, 57003 (2008).

Continuous-time hybridization expansion QMC

• Hybridization expansion impurity solver: General formulation and application to Kondo lattice and two-orbital models
  P. Werner and A. J. Millis,
  Phys. Rev. B 74, 155107 (2006).

• Continuous-Time Solver for Quantum Impurity Models
  P. Werner, A. Comanac, L. de’ Medici, M. Troyer, and A. J. Millis,
  Phys. Rev. Lett. 97, 076405 (2006).