Boltzmann–Gibbs Random Fields with Mesh-free Precision Operators Based on Smoothed Particle Hydrodynamics
Author:
Dionissios T. Hristopulos
Journal:
Theor. Probability and Math. Statist. 107 (2022), 37-60
MSC (2020):
Primary 60G15, 62P12; Secondary 62P30, 62M40
DOI:
https://doi.org/10.1090/tpms/1180
Published electronically:
November 8, 2022
Full-text PDF
Abstract |
References |
Similar Articles |
Additional Information
Abstract: Boltzmann–Gibbs random fields are defined in terms of the exponential expression $\exp \left (-\mathcal {H}\right )$, where $\mathcal {H}$ is a suitably defined energy functional of the field states $x(\mathbf {s})$. This paper presents a new Boltzmann–Gibbs model which features local interactions in the energy functional. The interactions are embodied in a spatial coupling function which uses smoothed kernel-function approximations of spatial derivatives inspired from the theory of smoothed particle hydrodynamics. A specific model for the interactions based on a second-degree polynomial of the Laplace operator is studied. An explicit, mesh-free expression of the spatial coupling function (precision function) is derived for the case of the squared exponential (Gaussian) smoothing kernel. This coupling function allows the model to seamlessly extend from discrete data vectors to continuum fields. Connections with Gaussian Markov random fields and the Matérn field with $\nu =1$ are established.
References
- Denis Allard, Dionisios T. Hristopulos, and Thomas Opitz, Linking physics and spatial statistics: a new family of Boltzmann-Gibbs random fields, Electron. J. Stat. 15 (2021), no. 2, 4085–4116. MR 4308768, DOI 10.1214/21-ejs1879
- N. Aronszajn, Theory of reproducing kernels, Trans. Amer. Math. Soc. 68 (1950), 337–404. MR 51437, DOI 10.1090/S0002-9947-1950-0051437-7
- Salomon Bochner, Lectures on Fourier integrals. With an author’s supplement on monotonic functions, Stieltjes integrals, and harmonic analysis, Annals of Mathematics Studies, No. 42, Princeton University Press, Princeton, N.J., 1959. Translated by Morris Tenenbaum and Harry Pollard. MR 0107124
- Arsenia Chorti and Dionissios T. Hristopulos, Nonparametric identification of anisotropic (elliptic) correlations in spatially distributed data sets, IEEE Trans. Signal Process. 56 (2008), no. 10, 4738–4751. MR 2517209, DOI 10.1109/TSP.2008.924144
- Brian D. Ripley, Spatial statistics, Wiley Series in Probability and Mathematical Statistics, John Wiley & Sons, Inc., New York, 1981. MR 624436, DOI 10.1002/0471725218
- Lawrence C. Evans, Partial differential equations, 2nd ed., Graduate Studies in Mathematics, vol. 19, American Mathematical Society, Providence, RI, 2010. MR 2597943, DOI 10.1090/gsm/019
- Richard Franke, Scattered data interpolation: tests of some methods, Math. Comp. 38 (1982), no. 157, 181–200. MR 637296, DOI 10.1090/S0025-5718-1982-0637296-4
- James Glimm and Arthur Jaffe, Quantum physics, 2nd ed., Springer-Verlag, New York, 1987. A functional integral point of view. MR 887102, DOI 10.1007/978-1-4612-4728-9
- N. Goldenfeld, Lectures on phase transitions and the renormalization group, Frontiers in Physics, Addison-Wesley, Reading, MA, 1993.
- G. Gompper and M. Kraus, Ginzburg-Landau theory of ternary amphiphilic systems. i. Gaussian interface fluctuations, Phys. Rev. E 47 (1993), no. 6, 4289–4300.
- G. Gompper and M. Kraus, Ginzburg-Landau theory of ternary amphiphilic systems. ii. Monte Carlo simulations, Phys. Rev. E 47 (1993), no. 6, 4301–4314.
- T. L. Hayden, The extension of bilinear functionals, Pacific J. Math. 22 (1967), 99–108. MR 227736, DOI 10.2140/pjm.1967.22.99
- Dave Higdon, Space and space-time modeling using process convolutions, Quantitative methods for current environmental issues, Springer, London, 2002, pp. 37–56. MR 2059819
- Dionissios T. Hristopulos, Spartan Gibbs random field models for geostatistical applications, SIAM J. Sci. Comput. 24 (2003), no. 6, 2125–2162. MR 2005624, DOI 10.1137/S106482750240265X
- D. T. Hristopulos, Covariance functions motivated by spatial random field models with local interactions, Stoch. Environ. Res. Risk Assess. 29 (2015), no. 3, 739–754.
- D. T. Hristopulos, Stochastic local interaction (SLI) model: Bridging machine learning and geostatistics, Comput. Geosci. 85 (2015), 26–37.
- D. T. Hristopulos,Random fields for spatial data modeling: A primer for scientists and engineers, Springer, Dordrecht, the Netherlands, 2020.
- Dionissios T. Hristopulos and Vasiliki D. Agou, Stochastic local interaction model with sparse precision matrix for space-time interpolation, Spat. Stat. 40 (2020), 100403, 22. MR 4181140, DOI 10.1016/j.spasta.2019.100403
- Dionissios T. Hristopulos and Samuel N. Elogne, Analytic properties and covariance functions for a new class of generalized Gibbs random fields, IEEE Trans. Inform. Theory 53 (2007), no. 12, 4667–4679. MR 2446930, DOI 10.1109/TIT.2007.909163
- E. Ising, Contribution to the theory of ferromagnetism, Zeitschrift für Physik 31 (1925), no. 1, 253–258.
- Mehran Kardar, Statistical physics of fields, Cambridge University Press, Cambridge, 2007. MR 2374147, DOI 10.1017/CBO9780511815881
- Finn Lindgren, David Bolin, and Håvard Rue, The SPDE approach for Gaussian and non-Gaussian fields: 10 years and still running, Spat. Stat. 50 (2022), Paper No. 100599, 29. MR 4439328, DOI 10.1016/j.spasta.2022.100599
- Finn Lindgren, Håvard Rue, and Johan Lindström, An explicit link between Gaussian fields and Gaussian Markov random fields: the stochastic partial differential equation approach, J. R. Stat. Soc. Ser. B Stat. Methodol. 73 (2011), no. 4, 423–498. With discussion and a reply by the authors. MR 2853727, DOI 10.1111/j.1467-9868.2011.00777.x
- J. J. Monaghan, Smoothed particle hydrodynamics, Annu. Rev. Astron. Astrophys. 30 (1992), no. 1, 543–574.
- J. J. Monaghan, Smoothed particle hydrodynamics, Rep. Progr. Phys. 68 (2005), no. 8, 1703–1759. MR 2158506, DOI 10.1088/0034-4885/68/8/R01
- Giuseppe Mussardo, Statistical field theory, Oxford Graduate Texts, Oxford University Press, Oxford, 2010. An introduction to exactly solved models in statistical physics. MR 2559725
- Néel, M. L., Propriétés magnétiques des ferrites; ferrimagnétisme et antiferromagnétisme, Annales de Physique 12 (1948), no. 3, 137–198.
- M. Nica, Eigenvalues and eigenfunctions of the Laplacian, The Waterloo Mathematics Review 1 (2011), no. 2, 23–34.
- M. P. Petrakis and D. T. Hristopulos, Non-parametric approximations for anisotropy estimation in two-dimensional differentiable Gaussian random fields, Stoch. Environ. Res. Risk Assess. 31 (2017), no. 7, 1853–1870.
- Carl Edward Rasmussen and Christopher K. I. Williams, Gaussian processes for machine learning, Adaptive Computation and Machine Learning, MIT Press, Cambridge, MA, 2006. MR 2514435
- Ju. A. Rozanov, On the paper “Markov random fields, and stochastic partial differential equations” (Mat. Sb. (N.S.) 103(145) (1977), no. 4, 590–613), Mat. Sb. (N.S.) 106(148) (1978), no. 3, 484–492, 496 (Russian). MR 505113
- Yu. A. Rozanov, Markov random fields, Applications of Mathematics, Springer-Verlag, New York-Berlin, 1982. Translated from the Russian by Constance M. Elson. MR 676644, DOI 10.1007/978-1-4613-8190-7
- Håvard Rue and Leonhard Held, Gaussian Markov random fields, Monographs on Statistics and Applied Probability, vol. 104, Chapman & Hall/CRC, Boca Raton, FL, 2005. Theory and applications. MR 2130347, DOI 10.1201/9780203492024
- Bernhard Schölkopf, Ralf Herbrich, and Alex J. Smola, A generalized representer theorem, Computational learning theory (Amsterdam, 2001) Lecture Notes in Comput. Sci., vol. 2111, Springer, Berlin, 2001, pp. 416–426. MR 2042050, DOI 10.1007/3-540-44581-1_{2}7
- B. Schölkopf and A. J. Smola, Learning with kernels: Support vector machines, regularization, optimization, and beyond, MIT Press, Cambridge, MA, USA, 2002.
- Scott Sheffield, Gaussian free fields for mathematicians, Probab. Theory Related Fields 139 (2007), no. 3-4, 521–541. MR 2322706, DOI 10.1007/s00440-006-0050-1
- Lloyd N. Trefethen and Mark Embree, Spectra and pseudospectra, Princeton University Press, Princeton, NJ, 2005. The behavior of nonnormal matrices and operators. MR 2155029, DOI 10.1515/9780691213101
- Hermann Weyl, Das asymptotische Verteilungsgesetz der Eigenwerte linearer partieller Differentialgleichungen (mit einer Anwendung auf die Theorie der Hohlraumstrahlung), Math. Ann. 71 (1912), no. 4, 441–479 (German). MR 1511670, DOI 10.1007/BF01456804
- M. Ĭ. Yadrenko, Spectral theory of random fields, Translation Series in Mathematics and Engineering, Optimization Software, Inc., Publications Division, New York, 1983. Translated from the Russian. MR 697386
- A. M. Yaglom, Correlation theory of stationary and related random functions. Vol. II, Springer Series in Statistics, Springer-Verlag, New York, 1987. Supplementary notes and references. MR 915557
- M. Yaremchuk and S. Smith, On the correlation functions associated with polynomials of the diffusion operator, Q.J.R. Meteorol. Soc. 137 (2011), no. 660, 1927–1932.
References
- D. Allard, D. T. Hristopulos, and T. Opitz, Linking physics and spatial statistics: a new family of Boltzmann-Gibbs random fields, Electron. J. Stat. 15 (2021), no. 2, 4085–4116. MR 4308768
- N. Aronszajn, Theory of reproducing kernels, Trans. Amer. Math. Soc. 68 (1950), 337–404. MR 51437
- S. Bochner, Lectures on Fourier integrals, Annals of Mathematics Studies, No. 42, Princeton University Press, Princeton, N.J., 1959, Translated by Morris Tenenbaum and Harry Pollard. MR 0107124
- A. Chorti and D. T. Hristopulos, Nonparametric identification of anisotropic (elliptic) correlations in spatially distributed data sets, IEEE Trans. Signal Process. 56 (2008), no. 10, part 1, 4738–4751. MR 2517209
- N. Cressie, Spatial statistics, John Wiley and Sons, New York, 1993. MR 624436
- L. C. Evans, Partial differential equations, second ed., Graduate Studies in Mathematics, vol. 19, American Mathematical Society, Providence, RI, 2010. MR 2597943
- R. W. Franke, Scattered data interpolation: tests of some methods, Math. Comp. 38 (1982), no. 157, 181–200. MR 637296
- J. Glimm and A. Jaffe, Quantum physics: A functional integral point of view, second ed., Springer-Verlag, New York, 1987. MR 887102
- N. Goldenfeld, Lectures on phase transitions and the renormalization group, Frontiers in Physics, Addison-Wesley, Reading, MA, 1993.
- G. Gompper and M. Kraus, Ginzburg-Landau theory of ternary amphiphilic systems. i. Gaussian interface fluctuations, Phys. Rev. E 47 (1993), no. 6, 4289–4300.
- G. Gompper and M. Kraus, Ginzburg-Landau theory of ternary amphiphilic systems. ii. Monte Carlo simulations, Phys. Rev. E 47 (1993), no. 6, 4301–4314.
- T. Hayden, The extension of bilinear functionals, Pacific J. Math. 22 (1967), 99–108. MR 227736
- D. Higdon, Space and space-time modeling using process convolutions, Quantitative methods for current environmental issues, Springer, London, 2002, pp. 37–56. MR 2059819
- D. T. Hristopulos, Spartan Gibbs random field models for geostatistical applications, SIAM J. Sci. Comput. 24 (2003), no. 6, 2125–2162. MR 2005624
- D. T. Hristopulos, Covariance functions motivated by spatial random field models with local interactions, Stoch. Environ. Res. Risk Assess. 29 (2015), no. 3, 739–754.
- D. T. Hristopulos, Stochastic local interaction (SLI) model: Bridging machine learning and geostatistics, Comput. Geosci. 85 (2015), 26–37.
- D. T. Hristopulos,Random fields for spatial data modeling: A primer for scientists and engineers, Springer, Dordrecht, the Netherlands, 2020.
- D. T. Hristopulos and V. D. Agou, Stochastic local interaction model with sparse precision matrix for space–time interpolation, Spat. Stat. 40 (2020), 100403, 22. MR 4181140
- D. T. Hristopulos and S. Elogne, Analytic properties and covariance functions for a new class of generalized Gibbs random fields, IEEE Trans. Inform. Theory 53 (2007), no. 12, 4667–4679. MR 2446930
- E. Ising, Contribution to the theory of ferromagnetism, Zeitschrift für Physik 31 (1925), no. 1, 253–258.
- M. Kardar, Statistical physics of fields, Cambridge University Press, Cambridge, 2007. MR 2374147
- F. Lindgren, D. Bolin, and H. Rue, The SPDE approach for Gaussian and non-Gaussian fields: 10 years and still running, Spat. Stat. 50 (2022), Paper No. 100599. MR 4439328
- F. Lindgren, H. Rue, and J. Lindström, An explicit link between Gaussian fields and Gaussian Markov random fields: the stochastic partial differential equation approach, J. R. Stat. Soc. Ser. B Stat. Methodol. 73 (2011), no. 4, 423–498, With discussion and a reply by the authors. MR 2853727
- J. J. Monaghan, Smoothed particle hydrodynamics, Annu. Rev. Astron. Astrophys. 30 (1992), no. 1, 543–574.
- J. J Monaghan, Smoothed particle hydrodynamics, Rep. Progr. Phys. 68 (2005), no. 8, 1703–1759. MR 2158506
- G. Mussardo, Statistical field theory: An introduction to exactly solved models in statistical physics, Oxford Graduate Texts, Oxford University Press, Oxford, 2010. MR 2559725
- Néel, M. L., Propriétés magnétiques des ferrites; ferrimagnétisme et antiferromagnétisme, Annales de Physique 12 (1948), no. 3, 137–198.
- M. Nica, Eigenvalues and eigenfunctions of the Laplacian, The Waterloo Mathematics Review 1 (2011), no. 2, 23–34.
- M. P. Petrakis and D. T. Hristopulos, Non-parametric approximations for anisotropy estimation in two-dimensional differentiable Gaussian random fields, Stoch. Environ. Res. Risk Assess. 31 (2017), no. 7, 1853–1870.
- C. E. Rasmussen and C. K. I. Williams, Gaussian processes for machine learning, Adaptive Computation and Machine Learning, MIT Press, Cambridge, MA, 2006. MR 2514435
- J. A. Rozanov, Markov random fields and stochastic differential equations, Mathematics of the USSR-Sbornik 32 (1977), no. 4, 515–534. MR 505113
- Y. A. Rozanov, Markov random fields, Applications of Mathematics, Springer-Verlag, New York-Berlin, 1982, Translated from the Russian by Constance M. Elson. MR 676644
- H. Rue and L. Held, Gaussian Markov random fields: Theory and applications, Monographs on Statistics and Applied Probability, vol. 104, Chapman & Hall/CRC, Boca Raton, FL, 2005. MR 2130347
- B. Schölkopf, R. Herbrich, and A. J. Smola, A generalized representer theorem, Computational learning theory (Amsterdam, 2001), Lecture Notes in Comput. Sci., vol. 2111, Springer, Berlin, 2001, pp. 416–426. MR 2042050
- B. Schölkopf and A. J. Smola, Learning with kernels: Support vector machines, regularization, optimization, and beyond, MIT Press, Cambridge, MA, USA, 2002.
- S. Sheffield, Gaussian free fields for mathematicians, Probab. Theory Related Fields 139 (2007), no. 3-4, 521–541. MR 2322706
- L. N. Trefethen and M. Embree, Spectra and pseudospectra: The behavior of nonnormal matrices and operators, Princeton University Press, Princeton, NJ, 2005. MR 2155029
- H. Weyl, Das asymptotische Verteilungsgesetz der Eigenwerte linearer partieller Differentialgleichungen (mit einer Anwendung auf die Theorie der Hohlraumstrahlung), Math. Ann. 71 (1912), no. 4, 441–479. MR 1511670
- M. I. Yadrenko, Spectral theory of random fields, Translation Series in Mathematics and Engineering, Optimization Software, Inc., Publications Division, New York, 1983, Translated from the Russian. MR 697386
- A. M. Yaglom, Correlation theory of stationary and related random functions. Vol. II, Springer Series in Statistics, Springer-Verlag, New York, 1987, Supplementary notes and references. MR 915557
- M. Yaremchuk and S. Smith, On the correlation functions associated with polynomials of the diffusion operator, Q.J.R. Meteorol. Soc. 137 (2011), no. 660, 1927–1932.
Similar Articles
Retrieve articles in Theory of Probability and Mathematical Statistics
with MSC (2020):
60G15,
62P12,
62P30,
62M40
Retrieve articles in all journals
with MSC (2020):
60G15,
62P12,
62P30,
62M40
Additional Information
Dionissios T. Hristopulos
Affiliation:
School of Electrical and Computer Engineering, Technical University of Crete, Chania, 73100 Greece
Email:
dchristopoulos@tuc.gr
Keywords:
Random fields,
kernel functions,
precision matrix,
smoothed particle hydrodynamics
Received by editor(s):
July 30, 2021
Accepted for publication:
January 20, 2022
Published electronically:
November 8, 2022
Article copyright:
© Copyright 2022
Taras Shevchenko National University of Kyiv