Numerical analytic continuation


In many-body physics, the problem of analytic continuation is that of numerically extracting the spectral density of a Green function given its values on the imaginary axis. It is a necessary post-processing step for calculating dynamical properties of physical systems from Quantum Monte Carlo simulations, which often compute Green function values only at imaginary times or Matsubara frequencies.

Mathematically, the problem reduces to solving a Fredholm integral equation of the first kind with an ill-conditioned kernel. As a result, it is an ill-posed inverse problem with no unique solution and where a small noise on the input leads to large errors in the unregularized solution. There are different methods for solving this problem including the maximum entropy method,[1][2][3][4] the average spectrum method[5][6][7][8] and Pade approximation methods.[9][10]



A common analytic continuation problem is obtaining the spectral function   at real frequencies   from the Green function values   at Matsubara frequencies   by numerically inverting the integral equation


where   for fermionic systems or   for bosonic ones and   is the inverse temperature. This relation is an example of Kramers-Kronig relation.

The spectral function can also be related to the imaginary-time Green function   be applying the inverse Fourier transform to the above equation


with  . Evaluating the summation over Matsubara frequencies gives the desired relation


where the upper sign is for fermionic systems and the lower sign is for bosonic ones.

Another example of the analytic continuation is calculating the optical conductivity   from the current-current correlation function values   at Matsubara frequencies. The two are related as following



  • The Maxent Project: Open source utility for performing analytic continuation using the maximum entropy method.
  • Spektra: Free online tool for performing analytic continuation using the average spectrum Method.
  • SpM: Sparse modeling tool for analytic continuation of imaginary-time Green’s function.

See also



  1. ^ Silver, R. N.; Sivia, D. S.; Gubernatis, J. E. (1990-02-01). "Maximum-entropy method for analytic continuation of quantum Monte Carlo data". Physical Review B. 41 (4): 2380–2389. Bibcode:1990PhRvB..41.2380S. doi:10.1103/PhysRevB.41.2380. PMID 9993975.
  2. ^ Jarrell, Mark; Gubernatis, J. E. (1996-05-01). "Bayesian inference and the analytic continuation of imaginary-time quantum Monte Carlo data". Physics Reports. 269 (3): 133–195. Bibcode:1996PhR...269..133J. doi:10.1016/0370-1573(95)00074-7. ISSN 0370-1573.
  3. ^ Reymbaut, A.; Bergeron, D.; Tremblay, A.-M. S. (2015-08-27). "Maximum entropy analytic continuation for spectral functions with nonpositive spectral weight". Physical Review B. 92 (6): 060509. arXiv:1507.01956. Bibcode:2015PhRvB..92f0509R. doi:10.1103/PhysRevB.92.060509. S2CID 56385057.
  4. ^ Burnier, Yannis; Rothkopf, Alexander (2013-10-31). "Bayesian Approach to Spectral Function Reconstruction for Euclidean Quantum Field Theories". Physical Review Letters. 111 (18): 182003. arXiv:1307.6106. Bibcode:2013PhRvL.111r2003B. doi:10.1103/PhysRevLett.111.182003. PMID 24237510.
  5. ^ White, S. R. (1991). "The Average Spectrum Method for the Analytic Continuation of Imaginary-Time Data". In Landau, David P.; Mon, K. K.; Schüttler, Heinz-Bernd (eds.). Computer Simulation Studies in Condensed Matter Physics III. Springer Proceedings in Physics. Vol. 53. Berlin, Heidelberg: Springer. pp. 145–153. doi:10.1007/978-3-642-76382-3_13. ISBN 978-3-642-76382-3.
  6. ^ Sandvik, Anders W. (1998-05-01). "Stochastic method for analytic continuation of quantum Monte Carlo data". Physical Review B. 57 (17): 10287–10290. Bibcode:1998PhRvB..5710287S. doi:10.1103/PhysRevB.57.10287.
  7. ^ Ghanem, Khaldoon; Koch, Erik (2020-02-10). "Average spectrum method for analytic continuation: Efficient blocked-mode sampling and dependence on the discretization grid". Physical Review B. 101 (8): 085111. arXiv:1912.01379. Bibcode:2020PhRvB.101h5111G. doi:10.1103/PhysRevB.101.085111. S2CID 208548627.
  8. ^ Ghanem, Khaldoon; Koch, Erik (2020-07-06). "Extending the average spectrum method: Grid point sampling and density averaging". Physical Review B. 102 (3): 035114. arXiv:2004.01155. Bibcode:2020PhRvB.102c5114G. doi:10.1103/PhysRevB.102.035114. S2CID 214775183.
  9. ^ Beach, K. S. D.; Gooding, R. J.; Marsiglio, F. (2000-02-15). "Reliable Pad\'e analytical continuation method based on a high-accuracy symbolic computation algorithm". Physical Review B. 61 (8): 5147–5157. arXiv:cond-mat/9908477. Bibcode:2000PhRvB..61.5147B. doi:10.1103/PhysRevB.61.5147. S2CID 17880539.
  10. ^ Östlin, A.; Chioncel, L.; Vitos, L. (2012-12-06). "One-particle spectral function and analytic continuation for many-body implementation in the exact muffin-tin orbitals method". Physical Review B. 86 (23): 235107. arXiv:1209.5283. Bibcode:2012PhRvB..86w5107O. doi:10.1103/PhysRevB.86.235107. S2CID 8434964.