Transition state theory bifurcations

Besides the two most well-known cases, the local bifurcations of the saddle-node and Hopf type, biochemical systems may show a variety of transitions between qualitatively different dynamic behavior [13, 17, 293, 294, 297 301]. Transitions between different regimes, induced by variation of kinetic parameters, are usually depicted in a bifurcation diagram. Within the chemical literature, a substantial number of articles seek to identify the possible bifurcation of a chemical system. Two prominent frameworks are Chemical Reaction Network Theory (CRNT), developed mainly by M. Feinberg [79, 80], and Stoichiometric Network Analysis (SNA), developed by B. L. Clarke [81 83]. An analysis of the (local) bifurcations of metabolic networks, as determinants of the dynamic behavior of metabolic states, constitutes the main topic of Section VIII. In addition to the scenarios discussed above, more complicated quasiperiodic or chaotic dynamics is sometimes reported for models of metabolic pathways [302 304]. However, apart from few special cases, the possible relevance of such complicated dynamics is, at best, unclear. Quite on the contrary, at least for central metabolism, we observe a striking absence of complicated dynamic phenomena. To what extent this might be an inherent feature of (bio)chemical systems, or brought about by evolutionary adaption, will be briefly discussed in Section IX. 

Dynamical Self-Organization. When the parameter X passes slowly through X (l),the bifurcation picture of the previous section accurateiy describes the system. However, in Fucus, and probably in many other examples, this time scale separation between the characteristic time on which X varies and the time to obtain the patterned state does not hold. Thus a dynamical theory allowing for the interplay of these two time scales is required to characterize the developmental scenario. A natural formalism to describe this process is that of time dependent Ginzburg-Landau (tdgl) equations used successfully in other contexts of nonequilibrium phase transitions (27). 

The solutions of these equations (the trajectories) will for long times (i.e., after transient effects associated with switching on the external parameters have decayed) approach so-called limit sets, which may be classified into fixed points (stationary states), limit cycles (periodic oscillations), mixedmode oscillations, quasiperiodic oscillations, and chaotic behavior. Transitions between these states may occur upon variation of the external parameters pk and are called bifurcations. Experimental evidence for these effects with the system CO + 02/Pt(110) will be briefly presented without going further into details of the underlying general theory (see 16, 17). 

On the other hand, the abundance of experimental material stimulates an evolution of the theories explaining non-linear phenomena. For example, as shown above, the transition in a chemical reaction from the stationary state to the state of periodical oscillations, the so-called Hopf bifurcation, is a certain elementary catastrophe. The transition in a chemical reaction to the chaotic state may be explained in terms of catastrophes associated with a loss of stability of a certain iterative process or by using the notion of a strange attractor (anyway, it turns out that both the systems are closely related). The equations of a chemical reaction with diffusion have been extensively studied lately. Based on the progress being made in this area, further interesting achievements in theory may be anticipated, particularly for the phenomena associated with catastrophes — the loss of stability by a non-linear system. 

Owing to the very simple and intuitively clear definition of the equation of state, the topology of the vapor-liquid-phase transition and critical point is examined easily using the methods of dynamic system and bifurcation theory. 

The transition from vortex motion to turbulence is accompanied by a corresponding sequence of instabilities or bifurcations, which results in a qualitative change of the domain pattern. Prom the theory of dynamical systems [127] the instability called Andronov-Hopf bifurcation [58] is well known. In this case, an oscillating regime appeared between two or more states having almost equal free energy. 

When a nonlinear system ewolwes under far-from-equilibrium conditions in the vicinity of a bifurcation point, a purely deterministic description often proved to be incomplete. The fluctuations of the dynamical variables can play an essential role and obstruct the observation of a transition expected by a deterministic analysis. In the framework of the deterministic approach, the stability of the different states according to the values of the control parameters is studied through a mathematical analysis of the velocity field. In particular, the theory of normal forms leads to the determination of the various kinds of attractors [l,2]. As far as we are concerned with the stochastic approach, the rrLa te.n. equation, has been widely used to analyze bifurcations of homogeneous or spatially ordered steady states or of limit cycles [3,4]. Our aim in the present contribution is to insist on the generality of the method to analyze various kinds of bifurcations in nonlinear nonequilibrium systems. The general procedure proposed to obtain a local description of the probability, which allows us to determine the system s attractors, turns out to display marked analogies with the theory of normal forms. 

In this section we discuss what happens when a pair of complex-conjugate characteristic exponents of an equilibrium state crosses over the imaginary axis. The loss of stability here is directly connected to the birth, or vice versa, the disappearance of a periodic orbit. This bifurcation is the simplest mechanism for transition from a stationary regime to oscillations, and it allows one to give a proper interpretation of numerous physical phenomena. For this reason this bifurcation has traditionally played a special role in the theory of bifurcations. 

The most relevant consequence of the change of interfacial chemistry for corrosion is undoubtedly the modification of the active-passive transition and the possible generation of self-sustained large-amplitude oscillations between active and passive states [163,164]. These phenomena were tightly associated with the manifestations of passivity from the earliest research, particularly in the case of iron in acid solutions. Theoretical investigations imply difficult nonlinear mathematics. A significant renewal of the field was observed in relation to the increasing interest in nonlinear phenomena and such concepts as bifurcation theory and chaos in chemistry [165-167]. 

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