Skip to main content Accessibility help
×
Hostname: page-component-7479d7b7d-jwnkl Total loading time: 0 Render date: 2024-07-11T04:29:44.593Z Has data issue: false hasContentIssue false

9 - Reaction-diffusion systems

from Part II - Scale invariance in non-equilibrium systems

Published online by Cambridge University Press:  05 June 2014

Uwe C. Täuber
Affiliation:
Virginia Polytechnic Institute and State University
Get access

Summary

This chapter addresses the stochastic dynamics of interacting particle systems, specifically reaction-diffusion models that, for example, capture chemical reactions in a gel such that convective transport is inhibited. Generic reaction-diffusion models are in fact utilized to describe a multitude of phenomena in various disciplines, ranging from population dynamics in ecology, competition of bacterial colonies in microbiology, dynamics of magnetic monopoles in the early Universe in cosmology, equity trading on the stock market in economy, opinion exchange in sociology, etc. More concrete physical applications systems encompass excitons kinetics in organic semconductors, domain wall interactions in magnets, and interface dynamics in growth models. Yet most of our current knowledge in this area stems from extensive computer simulations, and actual experimental realizations allowing accurate quantitative analysis are still deplorably rare. We begin with a brief review of mean-field and scaling arguments including Smoluchowski's self-consistent treatment of diffusion-limited binary annihilation. The main goal of this chapter is to demonstrate how one may systematically proceed from a microscopic master equation for interacting particles, which perhaps represents the most straightforward description of a system far from equilibrium, to a non-Hermitean bosonic ‘quantum’ many-body Hamiltonian, and thence to a continuum field theory representation that permits subsequent perturbative expansions and renormalization group treatment. The ensuing rich physics is illustrated with simple examples that include the annihilation reactions k Al A (l < k) and A + B ∅, their generalization to multiple particle species, as well as reversible recombination A + AB.

Type
Chapter
Information
Critical Dynamics
A Field Theory Approach to Equilibrium and Non-Equilibrium Scaling Behavior
, pp. 345 - 399
Publisher: Cambridge University Press
Print publication year: 2014

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Alcaraz, F. C., M., Droz, M., Henkel, and V., Rittenberg, 1994, Reaction-diffusion processes, critical dynamics, and quantum chains, Ann. Phys. (NY) 230, 250–302.Google Scholar
Allam, J., M. T., Sajjad, R., Sutton, et al., 2013, Measurement of a reaction-diffusion crossover in exciton–exciton recombination inside carbon nanotubes using femto-second optical absorption, Phys. Rev. Lett. 111, 197401-1–5.CrossRefGoogle Scholar
Andreanov, A., G., Biroli, J.-P., Bouchaud, and A., Lefèvre, 2006, Field theories and exact stochastic equations for interacting particle systems, Phys. Rev. E 74, 030101-1–4.CrossRefGoogle ScholarPubMed
Cardy, J., 1997, Renormalisation group approach to reaction-diffusion problems, in: Proceedings of Mathematical Beauty of Physics, ed. J.-B., Zuber, Adv. Ser. in Math. Phys. 24, 113–128.Google Scholar
Cardy, J., 2008, Reaction-diffusion processes, in:Non-equilibrium Statistical Mechanics and Turbulence, London Math. Soc. Lecture Note Ser. 355, Cambridge: Cambridge University Press, 108–161.CrossRefGoogle Scholar
Deloubriére, O., H. J., Hilhorst, and U. C., Täuber, 2002, Multispecies pair annihilation reactions, Phys. Rev. Lett. 89, 250601-1–4.CrossRefGoogle ScholarPubMed
Dobramysl, U. and U. C., Täuber, 2008, Spatial variability enhances species fitness in stochastic predator-prey interactions, Phys. Rev. Lett. l0l, 258102-1–4.Google Scholar
Dobramysl, U. and U. C., Täuber, 2013, Environmental versus demographic variability in two-species predator-prey models, Phys. Rev. Lett. 110, 048105-1–5.CrossRefGoogle ScholarPubMed
Doi, M., 1976a, Second quantization representation for classical many-particle systems, J. Phys. A: Math. Gen. 9, 1465–1477.CrossRefGoogle Scholar
Doi, M., 1976b, Stochastic theory of diffusion-controlled reactions, J. Phys. A: Math. Gen. 9, 1479–1495.CrossRefGoogle Scholar
Dornic, I., H., Chaté, and M. A., Muñoz, 2005, Integration of Langevin equations with multiplicative noise and the viability of field theories for absorbing phase transitions, Phys. Rev. Lett. 94, 100601-1–4.CrossRefGoogle ScholarPubMed
Elgart, V. and A., Kamenev, 2004, Rare event statistics in reaction-diffusion systems, Phys. Rev. E 70, 041106-1–12.CrossRefGoogle ScholarPubMed
Elgart, V. and A., Kamenev, 2006, Classification of phase transitions in reaction-diffusion models, Phys. Rev. E 74, 041101-1–16.CrossRefGoogle ScholarPubMed
Grassberger, P. and M., Scheunert, 1980, Fock–space methods for identical classical objects, Fortschr. Phys. 28, 547–578.CrossRefGoogle Scholar
Haken, H., 1983, Synergetics – an Introduction, Berlin: Springer, chapters 9, 10.CrossRefGoogle Scholar
Henkel, M., E., Orlandini, and J., Santos, 1997, Reaction-diffusion processes from equivalent integrable quantum chains, Ann. Phys. (NY) 259, 163–231.CrossRefGoogle Scholar
Hilhorst, H. J., O., Deloubrière, M. J., Washenberger, and U. C., Täuber, 2004, Segregation in diffusion-limited multispecies pair annihilation, J. Phys. A: Math. Gen. 37, 7063–7093.CrossRefGoogle Scholar
Hilhorst H., J., M. J., Washenberger, and U. C., Täuber, 2004, Symmetry and species segregation in diffusion-limited pair annihilation, J. Stat. Mech. P10002-1–19.CrossRefGoogle Scholar
Hinrichsen, H. and M., Howard, 1999, A model for anomalous directed percolation, Eur. Phys. J. B 7, 635–644.Google Scholar
Hofbauer, J. and K., Sigmund, 1998, Evolutionary Games and Population Dynamics, Cambridge: Cambridge University Press.CrossRefGoogle Scholar
Janssen, H. K., 2001, Directed percolation with colors and flavors, J. Stat. Phys. 103, 801–839.CrossRefGoogle Scholar
Kopelman, R., 1988, Fractal reaction kinetics, Science 241, 1620–1626.CrossRefGoogle ScholarPubMed
Krapivsky, P. K., S., Redner, and E., Ben-Naim, 2010, A Kinetic View of Statistical Physics, Cambridge: Cambridge University Press, chapters 12, 13.CrossRefGoogle Scholar
Kroon, R., H., Fleurent, and R., Sprik, 1993, Diffusion-limited exciton fusion reaction in one-dimensional tetramethylammonium manganese trichloride (TMMC), Phys. Rev. E 47, 2462–2472.CrossRefGoogle Scholar
Kuzovkov, V. and E., Kotomin, 1988, Kinetics of bimolecular reactions in condensed media: critical phenomena and microscopic self-organisation, Rep. Prog. Phys. 51, 1479–1523.CrossRefGoogle Scholar
Lee, B. P., 1994, Renormalization group calculation for the reaction kA → ∅, J. Phys. A: Math. Gen. 27, 2633–2652.CrossRefGoogle Scholar
Lee, B. P. and J., Cardy, 1994, Scaling of reaction zones in the A + B → ∅ diffusion-limited reaction, Phys. Rev. E 50, R3287–R3290.CrossRefGoogle Scholar
Lee, B. P. and J., Cardy, 1995, Renormalization group study of the A + B → ∅ diffusion-limited reaction, J. Stat. Phys. 80, 971–1007.CrossRefGoogle Scholar
Mattis, D. C. and M. L., Glasser, 1998, The uses of quantum field theory in diffusion-limited reactions, Rev. Mod. Phys. 70, 979–1002.CrossRefGoogle Scholar
Mobilia, M., I. T., Georgiev, and U. C., Täuber, 2007, Phase transitions and spatio-temporal fluctuations in stochastic lattice Lotka–Volterra models, J. Stat. Phys. 128, 447–483. [Various Monte Carlo simulation movies are accessible at http://www.phys.vt.edu/~tauber/PredatorPrey/movies/].CrossRefGoogle Scholar
Monson, E. and R., Kopelman, 2004, Nonclassical kinetics of an elementary A + B → C reaction-diffusion system showing effects of a speckled initial reactant distribution and eventual self-segregation: experiments, Phys. Rev. E 69, 021103-1–12.CrossRefGoogle Scholar
Murray, J. D., 2002, Mathematical Biology, Vols. I and II, New York: Springer, 3rd edn.Google Scholar
Ovchinnikov, A. A., S. F., Timashev, and A. A., Belyy, 1989, Kinetics of Diffusion-controlled Chemical Processes, New York: Nova Science.Google Scholar
Peliti, L., 1985, Path integral approach to birth-death processes on a lattice, J. Phys. (Paris) 46, 1469–1482.CrossRefGoogle Scholar
Peliti, L., 1986, Renormalisation of fluctuation effects in the A + A → A reaction, J. Phys. A: Math. Gen. 19, L365–367.CrossRefGoogle Scholar
Rey, P.-A. and J., Cardy, 1999, Asymptotic form of the approach to equilibrium in reversible recombination reactions, J. Phys. A: Math. Gen. 32, 1585–1603.CrossRefGoogle Scholar
Russo, R. M., E. J., Mele, C. L., Kane, I. V., Rubtsov, M. J., Therien, and D. E., Luzzi, 2006, One-dimensional diffusion-limited relaxation of photoexcitations in suspensions of single-walled carbon nanotubes, Phys. Rev. B 74, 041405(R)-1–4.CrossRefGoogle Scholar
Schütz, G., M., 2001, Exactly solvable models for many-body systems far from equilibrium, in: Phase Transitions and Critical Phenomena, Vol. 19, eds. C., Domb and J. L., Lebowitz, London: Academic Press.Google Scholar
Stinchcombe, R., 2001, Stochastic nonequilibrium systems, Adv. Phys. 50, 431–196.CrossRefGoogle Scholar
Täuber, U. C., 2012, Population oscillations in spatial stochastic Lotka–Volterra models: a field-theoretic perturbational analysis, J. Phys. A: Math. Theor. 45, 405002-1–34.CrossRefGoogle Scholar
Täuber, U. C., M. J., Howard, and B. P., Vollmayr-Lee, 2005, Applications of field-theoretic renormalization group methods to reaction-diffusion problems, J. Phys. A: Math. Gen. 38, R79–R131.CrossRefGoogle Scholar
Toussaint, D. and F., Wilczek, 1983, Particle-antiparticle annihilation in diffusive motion, J. Chem. Phys. 78, 2642–2647.CrossRefGoogle Scholar
van Wijland, F., 2001, Field theory for reaction-diffusion processes with hard-core particles, Phys. Rev. E 63, 022101-1–4.Google ScholarPubMed
Vernon, D., 2003, Long range hops and the pair annihilation reaction A + A → ∅: renormalization group and simulation, Phys. Rev. E 68, 041103-1–4.CrossRefGoogle Scholar
Washenberger, M. J., M., Mobilia, and U. C., Täuber, 2007, Influence of local carrying capacity restrictions on stochastic predator-prey models, J. Phys. Cond. Matt. 19, 065139-1–14.CrossRefGoogle Scholar
Barkema, G. T., M. J., Howard, and J. L., Cardy, 1996, Reaction-diffusion front for A + B → ∅ in one dimension, Phys. Rev. E 53, R2017–R2020.CrossRefGoogle Scholar
Cardy, J., 1995, Proportion of unaffected sites in a reaction-diffusion process, J. Phys. A: Math. Gen. 28, L19–L24.CrossRefGoogle Scholar
Cardy, J. and M., Katori, 2003, Families of vicious walkers, J. Phys. A: Math. Gen. 36 609–630.CrossRefGoogle Scholar
Chen, L. and M. W., Deem, 2002, Reaction, Lévy flights, and quenched disorder, Phys. Rev. E 65 011109-1–6.Google ScholarPubMed
Deem, M. W. and J.-M., Park, 1998a, Effect of static disorder and reactant segregation on the A + B → ∅ reaction, Phys. Rev. E 57, 2681–2685.CrossRefGoogle Scholar
Deem, M. W. and J.-M., Park, 1998b, Reactive turbulent flow in low-dimensional, disordered media, Phys. Rev. E 58, 3223–3228.CrossRefGoogle Scholar
Dobrinevski, A. and E., Frey, 2012, Extinction in neutrally stable stochastic Lotka–Volterra models, Phys. Rev. E 85, 051903-1–12.CrossRefGoogle ScholarPubMed
Droz, M. and L., Sasvári, 1993, Renormalization-group approach to simple reaction-diffusion phenomena, Phys. Rev. E 48, R2343–R2346.CrossRefGoogle ScholarPubMed
Emmerich, T., A., Bunde, and S., Havlin, 2012, Diffusion, annihilation, and chemical reactions in complex networks with spatial constraints, Phys. Rev. E 86, 046103-1–5.CrossRefGoogle ScholarPubMed
Hnatič, M. and J., Honkonen, 2000, Velocity-fluctuation-induced anomalous kinetics of the A + A → ∅ reaction, Phys. Rev. E 61, 3904–3911.Google Scholar
Hnatič, M., J., Honkonen, and T., Lučivjanský, 2013, Two-loop calculation of anomalous kinetics of the reaction A + A → ∅ in randomly stirred fluid, Eur. Phys. J. B 86, 214-1–16.CrossRefGoogle Scholar
Honkonen, J., 1991, Renormalization group analysis of superdiffusion in random velocity fields, J. Phys. A: Math. Gen. 24, L1235–L1242.CrossRefGoogle Scholar
Honkonen, J., 2012, Functional methods in stochastic systems, Lecture Notes in Computer Science 7125, 66–78.Google Scholar
Howard, M., 1996, Fluctuation kinetics in a multispecies reaction-diffusion system, J. Phys. A: Math. Gen. 29, 3437–3460.CrossRefGoogle Scholar
Howard, M. J. and G. T., Barkema, 1996, Shear flows and segregation in the reaction A + B → ∅, Phys. Rev. E 53, 5949–5956.CrossRefGoogle Scholar
Howard, M. and J., Cardy, 1995, Fluctuation effects and multiscaling of the reaction-diffusion front for A + B → ∅, J. Phys. A: Math. Gen. 28, 3599–3622.Google Scholar
Howard, M. and C., Godrèche, 1998, Persistence in the Voter model: continuum reaction-diffusion approach, J. Phys. A: Math. Gen. 31, L209–L216.CrossRefGoogle Scholar
Howard, M. J. and U. C., Täuber, 1997, ‘Real’ vs ‘imaginary’ noise in diffusion-limited reactions, J. Phys. A: Math. Gen. 30, 7721–7731.CrossRefGoogle Scholar
Itakura, K., J., Ohkubo, and S.-i., Sasa, 2010, Two Langevin equations in the Doi–Peliti formalism, J. Phys. A: Math. Theor. 43, 125001-1–14.CrossRefGoogle Scholar
Konkoli, Z., 2004, Application of Bogolyubov's theory of weakly nonideal Bose gases to the A + A, A + B, B + B reaction-diffusion system, Phys. Rev. E 69, 011106-1–16.CrossRefGoogle Scholar
Konkoli, Z., H., Johannesson, and B. P., Lee, 1999, Fluctuation effects in steric reaction-diffusion systems, Phys. Rev. E 59, R3787–R3790.CrossRefGoogle Scholar
Konkoli, Z. and H., Johannesson, 2000, Two-species reaction-diffusion system with equal diffusion constants: anomalous density decay at large times, Phys. Rev. E 62, 3276–3280.CrossRefGoogle ScholarPubMed
Krishnamurthy, S., R., Rajesh, and O., Zaboronski, 2003, Persistence properties of a system of coagulating and annihilating random walkers, Phys. Rev. E 68, 046103-1–12.CrossRefGoogle ScholarPubMed
Murthy, K. P. N. and G. M., Schütz, 1998, Aging in two- and three-particle annihilation processes, Phys. Rev. E 57, 1388–1394.CrossRefGoogle Scholar
Oerding, K., 1996, The A + B → ∅ annihilation reaction in a quenched random velocity field, J. Phys. A: Math. Gen. 29, 7051–7065.CrossRefGoogle Scholar
Ohkubo, J., 2012, One-parameter extension of the Doi–Peliti formalism and its relation with orthogonal polynomials, Phys. Rev. E 86, 042102-1–4.CrossRefGoogle ScholarPubMed
Park, J.-M. and M.W., Deem, 1998, Disorder-induced anomalous kinetics in the A + A → ∅ reaction, Phys. Rev. E 57, 3618–3621.CrossRefGoogle Scholar
Peruani, F. and C. F., Lee, 2013, Fluctuations and the role of collision duration in reaction-diffusion systems, EPL 102, 58001-1–6.CrossRefGoogle Scholar
Rajesh, R. and O., Zaboronski, 2004, Survival probability of a diffusing test particle in a system of coagulating and annihilating random walkers, Phys. Rev. E 70, 036111-1–9.CrossRefGoogle Scholar
Rey, P.-A. and M., Droz, 1997, A renormalization group study of a class of reaction-diffusion models, J. Phys. A: Math. Gen. 30, 1101–1114.CrossRefGoogle Scholar
Richardson, M. J. E. and J., Cardy, 1999, The reaction process A + A → ∅ in Sinai disorder, J. Phys. A: Math. Gen. 32 4035–4046.CrossRefGoogle Scholar
Santos R. V., dos, and R., Dickman, 2013, Survival of the scarcer in space, e-print arXiv:1304.5956.Google Scholar
Sasamoto, T., S., Mori, and M., Wadati, 1997, Universal properties of the mA + nB → ∅ diffusion-limited reaction, Physica A 247, 357–378.Google Scholar
Schütz,, G. M., 1995, Reaction-diffusion processes of hard-core particles, J. Stat. Phys. 79, 243–264.CrossRefGoogle Scholar
Schütz,, G. M., 1997, Diffusion-limited annihilation in inhomogeneous environments, Z. Phys. B Cond. Matt. 104, 583–590.CrossRefGoogle Scholar
Winkler, A. and E., Frey, 2012, Validity of the law of mass action in three-dimensional coagulation processes, Phys. Rev. Lett. 108, 108301-1–5.CrossRefGoogle ScholarPubMed
Winkler, A. and E., Frey, 2013, Long-range and many-body effects in coagulation processes, Phys. Rev. E 87, 022136-1–13.CrossRefGoogle ScholarPubMed
Zaboronski, O., 2001, Stochastic aggregation of diffusive particles revisited, Phys. Lett. A 281, 119–125.CrossRefGoogle Scholar

Save book to Kindle

To save this book to your Kindle, first ensure coreplatform@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

  • Reaction-diffusion systems
  • Uwe C. Täuber, Virginia Polytechnic Institute and State University
  • Book: Critical Dynamics
  • Online publication: 05 June 2014
  • Chapter DOI: https://doi.org/10.1017/CBO9781139046213.012
Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

  • Reaction-diffusion systems
  • Uwe C. Täuber, Virginia Polytechnic Institute and State University
  • Book: Critical Dynamics
  • Online publication: 05 June 2014
  • Chapter DOI: https://doi.org/10.1017/CBO9781139046213.012
Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

  • Reaction-diffusion systems
  • Uwe C. Täuber, Virginia Polytechnic Institute and State University
  • Book: Critical Dynamics
  • Online publication: 05 June 2014
  • Chapter DOI: https://doi.org/10.1017/CBO9781139046213.012
Available formats
×