mathematics Article Mathematical Analysis of a Thermostatted Equation with a Discrete Real Activity Variable Carlo Bianca 1,2 and Marco Menale 1,3,* 1 Laboratoire Quartz EA 7393, École Supérieure d’Ingénieurs en Génie Électrique, Productique et Management Industriel, 95092 Cergy Pontoise CEDEX, France; [email protected] 2 Laboratoire de Recherche en Eco-innovation Industrielle et Energétique, École Supérieure d’Ingénieurs en Génie Électrique, Productique et Management Industriel, 95092 Cergy Pontoise CEDEX, France 3 Dipartimento di Matematica e Fisica, Università degli Studi della Campania “L. Vanvitelli”, Viale Lincoln 5, I-81100 Caserta, Italy * Correspondence: [email protected] Received: 28 November 2019; Accepted: 17 December 2019; Published: 2 January 2020 Abstract: This paper deals with the mathematical analysis of a thermostatted kinetic theory equation. Specifically, the assumption on the domain of the activity variable is relaxed allowing for the discrete activity to attain real values. The existence and uniqueness of the solution of the related Cauchy problem and of the related non-equilibrium stationary state are established, generalizing the existing results. Keywords: real activity variable; thermostat; nonlinearity; complex systems; Cauchy problem 1. Introduction The mathematical analysis of a differential equation is usually based on the existence and uniqueness of a positive solution of the related Cauchy problem and on the dependence on the initial data (well-posed problem) [1,2]. The well-posed problem is analyzed under some (usually strongly) assumptions. However, if the differential equation is proposed as a general paradigm for the derivation of a mathematical model for a complex system [3,4], the definition of the assumptions is a delicate issue considering the restrictions that can be required on the system under consideration. The present paper aims at generalizing the mathematical analysis of the discrete thermostatted kinetic theory framework recently proposed in [5,6] and employed in [7] for the modeling of the pedestrian dynamics into a metro station. The mathematical framework consists of a nonlinear differential equations system derived considering the balancing into the elementary volume of the microscopic states (space, velocity, strategy or activity) of the gain and loss particle-flows. The mathematical framework contains also a dissipative term, called thermostat, for balancing the action of an external force field which acts on the complex system, thus moving the system out-of-equilibrium [8,9]. The thermostat term allows for the existence and thus the modeling of the non-equilibrium stationary (possibly steady) states; see, among others, [10–15]. The mathematical analysis presented in [5] is based on the assumption that the discrete activity variable is greater than 1. In order to model complex systems, such as social and economical systems [16–20], the possibility for the activity variable to also attain negative values should be planned. Accordingly, this paper is devoted to a further generalization of the existence and uniqueness of the solution and of the non-equilibrium stationary solution for a real activity variable. The present paper is organized as follows: after this introduction, Section2 is devoted to the main definitions of the differential framework and the related non equilibrium stationary states; Section3 deals with the new mathematical results. Mathematics 2020, 8, 57; doi:10.3390/math8010057 www.mdpi.com/journal/mathematics Mathematics 2020, 8, 57 2 of 8 2. The Mathematical Framework + i + Let Ep > 0, Iu = fu1, u2, ... , ung, ui 2 R, hh,k : Iu × Iu ! R , Bhk : Iu × Iu × Iu ! R , and + Fi : [0, +¥[! R , for i, h, k 2 f1, 2, . , ng. + This paper is devoted to the mathematical analysis of the solutions fi : [0, +¥[! R of the following system of n nonlinear ordinary differential equations (called discrete thermostatted kinetic framework): d f i (t) = J [f](t) + T [f](t), i 2 f1, 2, . , ng, (1) dt i i where f(t) = ( f1(t), f2(t),..., fn(t)) is the vector solution, and Ji[f](t) := Gi[f](t) − Li[f](t) and Ti[f](t) are the operators defined as follows: n n i Gi[f] := ∑ ∑ Bhk hhk fh(t) fk(t); h=1 k=1 n Li[f] := fi(t) ∑ hhk fk(t); k=1 0 n 1 p u (J [f] + F ) B ∑ j j j C B j=1 C T [f](t) := F − B C f (t). i i B C i @ Ep A Let Ep[f](t) be the pth-order moment: n p Ep[f](t) = ∑ ui fi(t), p 2 N, i=1 and Rp the following function space: p + n R := f 2 C [0, +¥[; (R ) : Ep[f](t) = Ep . Let f0 2 Rp, the Cauchy problem related to Equation (1) reads: 8 df(t) > = J[f](t) + T[f](t) t 2 [0, +¥[ <> dt (2) > :>f(0) = f0, where J[f] = G[f] − L[f] = (J1[f], J2[f], ... , Jn[f]) = (G1[f] − L1[f], G2[f] − L2[f], ... , Gn[f] − Ln[f]) and T[f] = (T1[f], T2[f],..., Tn[f]). The existence and uniqueness of the solution of the Cauchy problem (2) have been proved in [5], under the main assumption ui ≥ 1, for i 2 f1, 2, ... , ng. This paper aims at generalizing the result of [5] when ui 2 R. A non-equilibrium stationary state of the framework (1) is a constant function fi, for i 2 f1, 2, . , ng, solution of the following problem: 0 n 1 p u (J [f] + F ) B ∑ j j j C B j=1 C J [f] − B C f = 0. (3) i B C i @ Ep A Mathematics 2020, 8, 57 3 of 8 The existence and uniqueness of the non-equilibrium stationary state have been shown in [6] under the assumption ui ≥ 1, for all i 2 f1, 2, ... , ng. This result can be relaxed as stated in Theorem2. Remark 1. Nonlinear systems (1) are a mathematical framework proposed in [5] for the modeling of a complex system C homogeneous with respect to the mechanical variables (space and velocity), where u, called activity, models the states of the particles. The function fi, for i 2 f1, 2, ... , ng, denotes the distribution function of the ith functional subsystem. 3. The Generalized Results p n Let kxkp be the ` -norm on R : 1 n ! p p kxkp := ∑ xi , i=1 and E¯ p the following number: n ! ¯ p Ep := sup ∑ juij fi(t) . (4) t>0 i=1 It is worth stressing that, if p is even, then E¯ p = Ep; if p is odd, then Ep ≤ E¯ p. The main result of the paper follows. 0 p Theorem 1. Let p 2 N, E¯ p < ¥ and f 2 R . Assume that • ui 2 R n f0g; n i • ∑ Bhk = 1, for all h, k 2 f1, 2, . , ng; i=1 • There exists a constant h > 0 such that hhk ≤ h, for all h, k 2 f1, 2, . , ng; • There exists a constant F > 0 such that Fi(t) ≤ F, for all i 2 f1, 2, . , ng and t ≥ 0. Then, there exists a unique positive function f 2 Rp which is solution of the Cauchy problem (2). n p i Proof. Let f, g 2 R . Since ∑ Bhk = 1, for all h, k 2 f1, 2, . , ng, one has: i=1 n kG[f] − G[g]k1 = ∑ jGi[f] − Gi[g]j i=1 n n n n n i i = ∑ ∑ ∑ Bhk hhk fh(t) fk(t) − ∑ ∑ Bhk hhk gh(t) gk(t) i=1 h=1 k=1 h=1 k=1 n n n i = ∑ ∑ ∑ Bhk hhk ( fh(t) fk(t) − gh(t)gk(t)) i=1 h=1 k=1 n n ≤ h ∑ ∑ j fh(t) fk(t) − gh(t)gk(t)j (5) h=1 k=1 n n ≤ h ∑ ∑ j fh(t) fk(t) − fh(t)gk(t) + fh(t)gk(t) − gh(t)gk(t)j h=1 k=1 n n n ≤ h ∑ fh(t) + ∑ gh(t) ∑ j fk(t) − gk(t)j h=1 h=1 k=1 = h (kfk1 + kgk1) kf − gk1 = h jE0[f](t) + E0[g](t)j kf − gk1, Mathematics 2020, 8, 57 4 of 8 and n n n [ ] − [ ] = ( ) ( ) − ( ) ( ) kL f L g k1 ∑ fi t ∑ hik fk t gi t ∑ hik gi t i=1 k=1 k=1 (6) ≤ h jE0[f](t) + E0[g](t)j kf − gk1. Since n n up i jE0[f]j = ∑ fi(t) = ∑ p fi(t) , (7) i=1 i=1 ui 1 if L := max p , then, by Equation (7), one has: 0≤i≤n juij n p ¯ jE0[f]j ≤ L ∑ juij fi(t) ≤ L Ep. (8) i=0 By Equations (5), (6) and (8), one has: kJ[f] − J[g]k1 ≤ 2 h jE0[f] + E0[g]j kf − gk1 (9) ¯ ≤ 4 h L Epkf − gk1. Moreover: n kT[f] − T[g]k1 = ∑ jTi[f] − Ti[g]j i=1 n p ! n p ! n ∑ u (Jj[f] + Fj) ∑ u (Jj[g] + Fj) j=1 j j=1 j = ∑ fi(t) − gi(t) i=1 Ep Ep n p ! n p ! n p ! (10) n ∑ u Fj n ∑ u Jj[f] ∑ u Jj[g] j=1 j j=1 j j=1 j ≤ ∑ j fi(t) − gi(t)j + ∑ fi(t) − gi(t) i=1 Ep i=1 Ep Ep n p ! n p ! n p ! ∑ u Fj n ∑ u Jj[f] ∑ u Jj[g] j=1 j j=1 j j=1 j = kf(t) − g(t)k1 + ∑ fi(t) − gi(t) . Ep i=1 Ep Ep Mathematics 2020, 8, 57 5 of 8 Bearing the expressions of the operator J[f] in mind, one has: n p ! n p ! n ∑ u Jj[f] ∑ u Jj[g] j=1 j j=1 j ∑ fi(t) − gi(t) i=1 Ep Ep n 1 n 1 n = p [ ] ( ) − p [ ] ( ) ∑ ∑ ul Jl f fi t ∑ ul Jl g gi t i=1 Ep l=1 Ep l=1 n 1 n n n = p l ( ) ( ) ( ) ∑ ∑ ul ∑ ∑ Bhk hhk fh t fk t fi t i=1 Ep l=1 h=1 k=1 1 n n − p ( ) ( ) ( ) ∑ ul fl t ∑ hlk fk t fi t Ep l=1 k=1 1 n n n − p l ( ) ( ) ( ) ∑ ul ∑ ∑ Bhk hhk gh t gk t gi t Ep l=1 h=1 k=1 (11) 1 n n + p ( ) ( ) ( ) ∑ ul gl t ∑ hlk gk t gi t Ep l=1 k=1 n 1 n n n ≤ p l ( ( ) ( ) ( ) − ( ) ( ) ( )) ∑ ∑ ul ∑ ∑ Bhk hhk fh t fk t fi t gh t gk t gi t i=1 Ep l=1 h=1 k=1 n n + h ∑ ∑ j fk(t) fi(t) − gk(t)gi(t)j i=1 k=1 p n n n n h ∑j=1 uj ≤ ∑ ∑ ∑ j fh(t) fk(t) fi(t) − gh(t)gk(t)gi(t)j Ep i=1 h=1 k=1 n n + h ∑ ∑ j fh(t) fi(t) − gk(t)gi(t)j .