Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
97 tokens/sec
GPT-4o
53 tokens/sec
Gemini 2.5 Pro Pro
44 tokens/sec
o3 Pro
5 tokens/sec
GPT-4.1 Pro
47 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

Schrödingerisation based computationally stable algorithms for ill-posed problems in partial differential equations (2403.19123v4)

Published 28 Mar 2024 in math.NA and cs.NA

Abstract: We introduce a simple and stable computational method for ill-posed partial differential equation (PDE) problems. The method is based on Schr\"odingerization, introduced in [S. Jin, N. Liu and Y. Yu, arXiv:2212.13969][S. Jin, N. Liu and Y. Yu, Phys. Rev. A, 108 (2023), 032603], which maps all linear PDEs into Schr\"odinger-type equations in one higher dimension, for quantum simulations of these PDEs. Although the original problem is ill-posed, the Schr\"odingerized equations are Hamiltonian systems and time-reversible, allowing stable computation both forward and backward in time. The original variable can be recovered by data from suitably chosen domain in the extended dimension. We will use the backward heat equation and the linear convection equation with imaginary wave speed as examples. Error analysis of these algorithms are conducted and verified numerically. The methods are applicable to both classical and quantum computers, and we also lay out quantum algorithms for these methods. Moreover, we introduce a smooth initialization for the Schr\"odingerized equation which will lead to essentially spectral accuracy for the approximation in the extended space, if a spectral method is used. Consequently, the extra qubits needed due to the extra dimension, if a qubit based quantum algorithm is used, for both well-posed and ill-posed problems, becomes almost $\log\log {1/\varepsilon}$ where $\varepsilon$ is the desired precision. This optimizes the complexity of the Schr\"odingerization based quantum algorithms for any non-unitary dynamical system introduced in [S. Jin, N. Liu and Y. Yu, arXiv:2212.13969][S. Jin, N. Liu and Y. Yu, Phys. Rev. A, 108 (2023), 032603].

Definition Search Book Streamline Icon: https://streamlinehq.com
References (29)
  1. A comparison of regularizations for an ill-posed problem. Math. Comput., 67:1451–1471, 1998.
  2. Introduction to inverse problems in imaging. CRC press, 2021.
  3. A two-stage numerical approach for the sparse initial source identification of a diffusion–advection equation. Inverse Problems, 39(9):095003, 2023.
  4. Convergence rates for tikhonov regularisation of non-linear ill-posed problems. Inverse problems, 5(4):523, 1989.
  5. L. C. Evans. Partial differential equations. American Mathematical Society, 2016.
  6. T. Funada and D. Joseph. Viscous potential flow analysis of kelvin–helmholtz instability in a channel. J. Fluid Mech., 445:263–283, 2001.
  7. D. N. Háo. A mollification method for ill-posed problems. Numerische Mathematik, 68(4):469–506, 1994.
  8. A. Hasegawa. Plasma instabilities and nonlinear effects, volume 8. Springer Science & Business Media, 2012.
  9. K. Höllig. Existence of infinitely many solutions for a forward backward heat equation. Trans. Amer. Math. Soc., 278(1):299–316, 1983.
  10. S. Jin and N. Liu. Analog quantum simulation of partial differential equations. arXiv:2308.00646, 2023.
  11. On schrödingerization based quantum algorithms for linear dynamical systems with inhomogeneous terms. arXiv:2402.14696v2, 2024.
  12. Quantum simulation of partial differential equations via schrodingerisation. arXiv preprint arXiv:2212.13969., 2022.
  13. Quantum simulation of partial differential equations: Applications and detailed analysis. Physical Review A, 108(3):032603, 2023.
  14. F. John. Numerical solution of the equation of heat conduction for preceding times. Ann. Mat. Pura Appl., 40:Ann. Mat. Pura Appl., 1955.
  15. M. Jourhmane and N. S. Mera. An iterative algorithm for the backward heat conduction problem based on variable relaxation factors. Inverse Problems in Engineering, 10(4):293–308, 2002.
  16. H. J. Kull. Theory of the rayleigh-taylor instability. Physics reports, 206(5):197–325, 1991.
  17. R. Lattès and J. L. Lions. Méthode de quasi-réversibilité et applications. English translation: R. Bellman, Elsevier, New York, 1969.
  18. F. Lin. Remarks on a backward parabolic problem. Methods Appl. Anal., 10(2):245–252, 2003.
  19. K. Miller. Stabilized quasireversibility and other nearly best possible methods for non-well-posed problems. in: Symposium on Non-Well-Posed Problems and Logarithmic Convexity, in: Lecture Notes in Math., 316:161–176, 1973.
  20. W. Miranker. A well posed problem for the backward heat equation. Proc. Amer. Math. Soc., 12:243–247, 1961.
  21. J. Nash. Continuity of solutions of parabolic and elliptic equations. Amer. J. Math., 80(4):931–954, 1958.
  22. Experimental verification and simulation of negative index of refraction using snell’s law. Phys. Rev. Lett., 90(10):107401, 2003.
  23. A modified method for a backward heat conduction problem. Appl. Math. Comput., 185:564–573, 2007.
  24. Experimental verification of a negative index of refraction. science, 292(5514):77–79, 2001.
  25. Spectral methods. Springer-Verlag Berliln Heidelberg, 2011.
  26. R.E. Showalter. The final value problem for evolution equations. J. Math. Anal. Appl., 47:563–572, 1974.
  27. Introduction to numerical analysis. New York: Springer-Verlag, 1980.
  28. G. Uhlmann. Inverse problems: seeing the unseen. Bulletin of Mathematical Sciences, 4:209–279, 2014.
  29. Two numerical methods for solving a backward heat conduction problem. Appl. Math. Comput., 179(1):370–377, 2006.
User Edit Pencil Streamline Icon: https://streamlinehq.com
Authors (3)
  1. Shi Jin (487 papers)
  2. Nana Liu (54 papers)
  3. Chuwen Ma (10 papers)

Summary

We haven't generated a summary for this paper yet.