- Open Access
Multiorbital dynamical mean-field theory with a complex-time solver
Phys. Rev. Research 8, 023142 – Published 11 May, 2026
DOI: https://doi.org/10.1103/yqv4-4vjx
Abstract
We present the combination of a complex-time tensor-network impurity solver with an analytic continuation scheme based on exponential fitting as an efficient framework for single and multiorbital dynamical mean-field calculations. By performing time evolution along a complex-time contour, the approach balances computational cost with the difficulty of spectral recovery, offering greater flexibility than methods confined to the real or imaginary axis. By complementing the complex-time evolution with an exponential fitting scheme, we faithfully extract real-time information at negligible cost. The resulting method obtains high-resolution spectra at a significantly lower computational cost than real-time evolution, offering a promising tool for ab initio studies of strongly correlated materials.
Physics Subject Headings (PhySH)
Article Text
References (82)
- W. Metzner and D. Vollhardt, Correlated lattice fermions in dimensions, Phys. Rev. Lett. 62, 324 (1989).
- A. Georges, G. Kotliar, W. Krauth, and M. J. Rozenberg, Dynamical mean-field theory of strongly correlated fermion systems and the limit of infinite dimensions, Rev. Mod. Phys. 68, 13 (1996).
- G. Kotliar, S. Y. Savrasov, K. Haule, V. S. Oudovenko, O. Parcollet, and C. A. Marianetti, Electronic structure calculations with dynamical mean-field theory, Rev. Mod. Phys. 78, 865 (2006).
- T. Pruschke, Perturbation theory of the Anderson model at finite , Physica B 163, 553 (1990).
- H. Keiter and J. C. Kimball, Perturbation technique for the Anderson Hamiltonian, Phys. Rev. Lett. 25, 672 (1970).
- T. Pruschke and N. Grewe, The Anderson model with finite Coulomb repulsion, Z. Phys. B 74, 439 (1989).
- A. N. Rubtsov, V. V. Savkin, and A. I. Lichtenstein, Continuous-time quantum Monte Carlo method for fermions, Phys. Rev. B 72, 035122 (2005).
- P. Werner, A. Comanac, L. de’ Medici, M. Troyer, and A. J. Millis, Continuous-time solver for quantum impurity models, Phys. Rev. Lett. 97, 076405 (2006).
- E. Gull, P. Werner, O. Parcollet, and M. Troyer, Continuous-time auxiliary-field Monte Carlo for quantum impurity models, Europhys. Lett. 82, 57003 (2008).
- E. Gull, A. J. Millis, A. I. Lichtenstein, A. N. Rubtsov, M. Troyer, and P. Werner, Continuous-time Monte Carlo methods for quantum impurity models, Rev. Mod. Phys. 83, 349 (2011).
- G. Cohen, E. Gull, D. R. Reichman, A. J. Millis, and E. Rabani, Numerically exact long-time magnetization dynamics at the nonequilibrium Kondo crossover of the Anderson impurity model, Phys. Rev. B 87, 195108 (2013).
- M. Caffarel and W. Krauth, Exact diagonalization approach to correlated fermions in infinite dimensions: Mott transition and superconductivity, Phys. Rev. Lett. 72, 1545 (1994).
- M. Capone, L. de’ Medici, and A. Georges, Solving the dynamical mean-field theory at very low temperatures using the Lanczos exact diagonalization, Phys. Rev. B 76, 245116 (2007).
- S. Iskakov and M. Danilov, Exact diagonalization library for quantum electron models, Comput. Phys. Commun. 225, 128 (2018).
- D. Zgid, E. Gull, and G. K.-L. Chan, Truncated configuration interaction expansions as solvers for correlated quantum impurity models and dynamical mean-field theory, Phys. Rev. B 86, 165128 (2012).
- A. Shee and D. Zgid, Coupled cluster as an impurity solver for Green’s function embedding methods, J. Chem. Theory Comput. 15, 6010 (2019).
- T. Zhu, C. A. Jiménez-Hoyos, J. McClain, T. C. Berkelbach, and G. K.-L. Chan, Coupled-cluster impurity solvers for dynamical mean-field theory, Phys. Rev. B 100, 115154 (2019).
- K. G. Wilson, The renormalization group: Critical phenomena and the Kondo problem, Rev. Mod. Phys. 47, 773 (1975).
- T. Pruschke, R. Bulla, and M. Jarrell, Low-energy scale of the periodic Anderson model, Phys. Rev. B 61, 12799 (2000).
- R. Bulla, T. A. Costi, and T. Pruschke, Numerical renormalization group method for quantum impurity systems, Rev. Mod. Phys. 80, 395 (2008).
- S. R. White, Density matrix formulation for quantum renormalization groups, Phys. Rev. Lett. 69, 2863 (1992).
- S. R. White, Density-matrix algorithms for quantum renormalization groups, Phys. Rev. B 48, 10345 (1993).
- U. Schollwöck, The density-matrix renormalization group in the age of matrix product states, Ann. Phys. 326, 96 (2011).
- R. Orús, Advances on tensor network theory: Symmetries, fermions, entanglement, and holography, Eur. Phys. J. B 87, 280 (2014).
- F. A. Wolf, A. Go, I. P. McCulloch, A. J. Millis, and U. Schollwöck, Imaginary-time matrix product state impurity solver for dynamical mean-field theory, Phys. Rev. X 5, 041032 (2015).
- Y. Núñez Fernández, M. Jeannin, P. T. Dumitrescu, T. Kloss, J. Kaye, O. Parcollet, and X. Waintal, Learning Feynman diagrams with tensor trains, Phys. Rev. X 12, 041018 (2022).
- A. J. Kim and P. Werner, Strong coupling impurity solver based on quantics tensor cross interpolation, Phys. Rev. B 111, 125120 (2025).
- S. Matsuura, H. Shinaoka, P. Werner, and N. Tsuji, Tensor cross interpolation approach for quantum impurity problems based on the weak-coupling expansion, Phys. Rev. B 111, 155150 (2025).
- L. Geng, A. J. Kim, and P. Werner, Third-order strong-coupling impurity solver for real-frequency dynamical mean field theory: Accurate spectral functions for antiferromagnetic and photodoped states, Phys. Rev. B 112, 245119 (2025).
- M. Jarrell and J. Gubernatis, Bayesian inference and the analytic continuation of imaginary-time quantum Monte Carlo data, Phys. Rep. 269, 133 (1996).
- A. W. Sandvik, Stochastic method for analytic continuation of quantum Monte Carlo data, Phys. Rev. B 57, 10287 (1998).
- H. J. Vidberg and J. W. Serene, Solving the Eliashberg equations by means of -point Padé approximants, J. Low Temp. Phys. 29, 179 (1977).
- J. Fei, C.-N. Yeh, and E. Gull, Nevanlinna analytical continuation, Phys. Rev. Lett. 126, 056402 (2021).
- Z. Huang, E. Gull, and L. Lin, Robust analytic continuation of Green’s functions via projection, pole estimation, and semidefinite relaxation, Phys. Rev. B 107, 075151 (2023).
- L. Ying, Pole recovery from noisy data on imaginary axis, J. Sci. Comput. 92, 107 (2022).
- L. Ying, Analytic continuation from limited noisy Matsubara data, J. Comput. Phys. 469, 111549 (2022).
- L. Zhang and E. Gull, Minimal pole representation and controlled analytic continuation of Matsubara response functions, Phys. Rev. B 110, 035154 (2024).
- K. A. Hallberg, Density-matrix algorithm for the calculation of dynamical properties of low-dimensional systems, Phys. Rev. B 52, R9827 (1995).
- P. E. Dargel, A. Honecker, R. Peters, R. M. Noack, and T. Pruschke, Adaptive Lanczos-vector method for dynamic properties within the density matrix renormalization group, Phys. Rev. B 83, 161104(R) (2011).
- P. E. Dargel, A. Wöllert, A. Honecker, I. P. McCulloch, U. Schollwöck, and T. Pruschke, Lanczos algorithm with matrix product states for dynamical correlation functions, Phys. Rev. B 85, 205119 (2012).
- O. Kovalska, J. von Delft, and A. Gleis, Tangent space Krylov computation of real-frequency spectral functions: Influence of density-assisted hopping on 2D Mott physics, arXiv:2510.07279.
- S. R. White and A. E. Feiguin, Real-time evolution using the density matrix renormalization group, Phys. Rev. Lett. 93, 076401 (2004).
- J. Haegeman, J. I. Cirac, T. J. Osborne, I. Pižorn, H. Verschelde, and F. Verstraete, Time-dependent variational principle for quantum lattices, Phys. Rev. Lett. 107, 070601 (2011).
- J. Haegeman, T. J. Osborne, and F. Verstraete, Post-matrix product state methods: To tangent space and beyond, Phys. Rev. B 88, 075133 (2013).
- J. Haegeman, C. Lubich, I. Oseledets, B. Vandereycken, and F. Verstraete, Unifying time evolution and optimization with matrix product states, Phys. Rev. B 94, 165116 (2016).
- L. Vanderstraeten, J. Haegeman, and F. Verstraete, Tangent-space methods for uniform matrix product states, SciPost Phys. Lect. Notes, 7 (2019).
- M. Ganahl, M. Aichhorn, H. G. Evertz, P. Thunström, K. Held, and F. Verstraete, Efficient DMFT impurity solver using real-time dynamics with matrix product states, Phys. Rev. B 92, 155132 (2015).
- D. Bauernfeind, M. Zingl, R. Triebl, M. Aichhorn, and H. G. Evertz, Fork tensor-product states: Efficient multiorbital real-time DMFT solver, Phys. Rev. X 7, 031013 (2017).
- X. Cao, Y. Lu, P. Hansmann, and M. W. Haverkort, Tree tensor-network real-time multiorbital impurity solver: Spin-orbit coupling and correlation functions in , Phys. Rev. B 104, 115119 (2021).
- X. Cao, Y. Lu, E. M. Stoudenmire, and O. Parcollet, Dynamical correlation functions from complex time evolution, Phys. Rev. B 109, 235110 (2024).
- M. Grundner, P. Westhoff, F. B. Kugler, O. Parcollet, and U. Schollwöck, Complex time evolution in tensor networks and time-dependent Green’s functions, Phys. Rev. B 109, 155124 (2024).
- K. Guther, W. Dobrautz, O. Gunnarsson, and A. Alavi, Time propagation and spectroscopy of fermionic systems using a stochastic technique, Phys. Rev. Lett. 121, 056401 (2018).
- Z. Wang, P. McClarty, D. Dankova, A. Honecker, and A. Wietek, Spectroscopy and complex-time correlations using minimally entangled typical thermal states, Phys. Rev. B 113, 024406 (2026).
- S. Paeckel, Spectral decomposition and high-accuracy Greens functions: Overcoming the Nyquist-Shannon limit via complex-time Krylov expansion, Phys. Rev. Lett. 136, 160401 (2026).
- L. Zhang, A. Erpenbeck, Y. Yu, and E. Gull, Minimal pole representation for spectral functions, J. Chem. Phys. 162, 214111 (2025).
- A. Erpenbeck, Y. Zhu, Y. Yu, L. Zhang, R. Gerum, O. Goulko, C. Yang, G. Cohen, and E. Gull, Compact representation and long-time extrapolation of real-time data for quantum systems, Phys. Rev. B 113, 115129 (2026).
- A. F. Kemper, C. Yang, and E. Gull, Denoising and extension of response functions in the time domain, Phys. Rev. Lett. 132, 160403 (2024).
- G. R. de Prony, Essai experimental et analytique: Sur les lois de la dilatabilite des fluides elastique et sur celles de la force expansive de la vapeur de l'eau et de la vapeur de l'alkool, a differentes temperatures, J. Polytech. ou Bull. du Trav. fait Ec. Cent. Trav. Publics 1, 24 (1795).
- R. Roy and T. Kailath, Esprit-estimation of signal parameters via rotational invariance techniques, IEEE Trans. Acoust. Speech Signal Process. 37, 984 (1989).
- Y. Hua and T. K. Sarkar, Matrix pencil method for estimating parameters of exponentially damped/undamped sinusoids in noise, IEEE Trans. Acoust. Speech Signal Process. 38, 814 (1990).
- T. Sarkar and O. Pereira, Using the matrix pencil method to estimate the parameters of a sum of complex exponentials, IEEE Antennas Propag. Mag. 37, 48 (1995).
- R. Schmidt, Multiple emitter location and signal parameter estimation, IEEE Trans. Antennas Propag. 34, 276 (1986).
- P. J. SCHMID, Dynamic mode decomposition of numerical and experimental data, J. Fluid Mech. 656, 5 (2010).
- D. Potts and M. Tasche, Parameter estimation for nonincreasing exponential sums by Prony-like methods, Linear Algebra Appl. 439, 1024 (2013).
- L. Zhang, Y. Yu, and E. Gull, Minimal pole representation and analytic continuation of matrix-valued correlation functions, Phys. Rev. B 110, 235131 (2024).
- Y.-Y. Shi, L.-M. Duan, and G. Vidal, Classical simulation of quantum many-body systems with a tree tensor network, Phys. Rev. A 74, 022320 (2006).
- V. Murg, F. Verstraete, O. Legeza, and R. M. Noack, Simulating strongly correlated quantum systems with tree tensor networks, Phys. Rev. B 82, 205105 (2010).
- Y. Lu, M. Höppner, O. Gunnarsson, and M. W. Haverkort, Efficient real-frequency solver for dynamical mean-field theory, Phys. Rev. B 90, 085102 (2014).
- Y. Lu, X. Cao, P. Hansmann, and M. W. Haverkort, Natural-orbital impurity solver and projection approach for Green’s functions, Phys. Rev. B 100, 115134 (2019).
- J. M. Luttinger, Fermi surface and some simple equilibrium properties of a system of interacting fermions, Phys. Rev. 119, 1153 (1960).
- J. M. Luttinger, Analytic properties of single-particle propagators for many-fermion systems, Phys. Rev. 121, 942 (1961).
- M. Karski, C. Raas, and G. S. Uhrig, Single-particle dynamics in the vicinity of the Mott-Hubbard metal-to-insulator transition, Phys. Rev. B 77, 075116 (2008).
- M. Karski, C. Raas, and G. S. Uhrig, Electron spectra close to a metal-to-insulator transition, Phys. Rev. B 72, 113110 (2005).
- D. Zgid and E. Gull, Finite temperature quantum embedding theories for correlated systems, New J. Phys. 19, 023047 (2017).
- P. Werner, E. Gull, M. Troyer, and A. J. Millis, Spin freezing transition and non-Fermi-liquid self-energy in a three-orbital model, Phys. Rev. Lett. 101, 166405 (2008).
- L. de’ Medici, J. Mravlje, and A. Georges, Janus-faced influence of Hund’s rule coupling in strongly correlated materials, Phys. Rev. Lett. 107, 256401 (2011).
- A. Georges, L. de’ Medici, and J. Mravlje, Strong correlations from hund’s coupling, Annu. Rev. Condens. Matter Phys. 4, 137 (2013).
- M. Vojta, Orbital-selective Mott transitions: Heavy fermions and beyond, J. Low Temp. Phys. 161, 203 (2010).
- A. Koga, N. Kawakami, T. M. Rice, and M. Sigrist, Orbital-selective Mott transitions in the degenerate Hubbard model, Phys. Rev. Lett. 92, 216402 (2004).
- R. Arita and K. Held, Orbital-selective Mott-Hubbard transition in the two-band Hubbard model, Phys. Rev. B 72, 201102(R) (2005).
- L. de’ Medici, A. Georges, and S. Biermann, Orbital-selective Mott transition in multiband systems: Slave-spin representation and dynamical mean-field theory, Phys. Rev. B 72, 205124 (2005).
- R. K. Bryan, Maximum entropy analysis of oversampled data problems, Eur. Biophys. J. 18, 165 (1990).