A Detailed Fluctuation Theorem for Heat Fluxes in Harmonic Networks out of Thermal Equilibrium
Mondher Damak, Mayssa Hammami, Claude-Alain Pillet

TL;DR
This paper derives a detailed fluctuation theorem for heat fluxes in harmonic oscillator networks out of thermal equilibrium, providing insights into the statistical behavior of heat transfer in nonequilibrium steady states.
Contribution
It extends previous work by establishing a large deviation principle and a fluctuation relation for heat flux fluctuations in harmonic networks.
Findings
Proves a large deviation principle for heat flux fluctuations.
Derives a fluctuation relation for the rate function.
Analyzes heat flux statistics in nonequilibrium steady states.
Abstract
We continue the investigation, started in [J. Stat. Phys. 166, 926-1015 (2017)], of a network of harmonic oscillators driven out of thermal equilibrium by heat reservoirs. We study the statistics of the fluctuations of the heat fluxes flowing between the network and the reservoirs in the nonequilibrium steady state and in the large time limit. We prove a large deviation principle for these fluctuations and derive the fluctuation relation satisfied by the associated rate function.
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A Detailed Fluctuation Theorem for Heat Fluxes
in Harmonic Networks out of Thermal Equilibrium
Mondher Damak1
Mayssa Hammami1,2
Claude-Alain Pillet2
1Departement of Mathematics, Faculty of Sciences of Sfax, University of Sfax, Tunisia.
2Aix Marseille Univ, Université de Toulon, CNRS, CPT, Marseille, France
Abstract. We continue the investigation, started in [JPS], of a network of harmonic oscillators driven out of thermal equilibrium by heat reservoirs. We study the statistics of the fluctuations of the heat fluxes flowing between the network and the reservoirs in the nonequilibrium steady state and in the large time limit. We prove a large deviation principle for these fluctuations and derive the fluctuation relation satisfied by the associated rate function.
**Keywords. Large Deviations, Fluctuation Relations, Entropy Production, Heat Fluxes, Nonequilibrium Steady State. **
1 Introduction
Fluctuation Relations (FRs for short) describe universal features of the statistical properties of physical systems. The first instance of such a relation goes back to 1905 and the celebrated work of Einstein on Brownian motion. Despite a few early occurrences in the literature111 see [BK], and also, in view of the now well understood connection with the thermodynamic formalism, [Ru1, Proposition 5.3.2, Equ. (3.9)]., it is only after the works [ECM, ES, GC1, GC2] that FRs became a major research direction in nonequilibrium statistical mechanics, see, e.g., [Ja, Cr, LS, Ma, CG] on the theoretical side and [CCZ, CDF] on the experimental one. See also [Ga2, Ga3, Ru2] for more mathematically oriented introductions to the subject and the reviews [RM, Se, JPR, JOPP] for more exhaustive references. In this work, we shall adhere to the somewhat restrictive but mathematically precise perspective advocated by Gallavotti and Cohen in [GC1, GC2], and call FR a universal – i.e., model independent – symmetry property of the rate function describing the large deviations of some distinguished observable of a physical system in a steady state in the large time limit. As explained in [ECM, Ga1, LS, JPR], such FRs, sometimes coined detailed FRs in the physics literature, provide extensions of the well-known Green–Kubo and Onsager relations of linear response theory to the nonequilibrium regime.
While FRs in smooth chaotic dynamical systems on compact phase space are now pretty well understood, their status is more problematic in the presence of singularities and for general deterministic or stochastic dynamical system with non-compact phase space. As observed through the study of specific models, FRs may only have a limited domain of validity and/or acquire non-universal features in such circumstances, see [BGGZ, Fa, Vi, RT, RH].
- •
From the physical point of view, there are issues related to the proper choice of the relevant observable, as discussed in [JPS]. While most studies concern entropy production, work and heat transfer in time-dependent protocols involving a single heat reservoir, there is also some interests in investigating individual heat fluxes in multi-reservoir systems.
- •
From the mathematical point of view, the problems are often related to the failure of standard approaches to the derivation of a large deviation principle (see the series [JNPS1]–[JNPS4] and [Ne]), or due to the technical difficulties met in applying the contraction principle, as in [BL, Section 3.4].
In order to reach a better understanding of FRs we need to further investigate simple models which allow for a clean mathematical treatment. Networks of oscillators [MN, EZ] are among the simplest candidates. While some progresses have been achieved in our understanding of the non-equilibrium dynamics of networks of anharmonic oscillators (see, e.g., the recent works [CE, CEHR]), a complete picture of FRs for these systems seems to be still out of reach of currently available techniques (to the best of our knowledge, the only partial results can be found in [RT] for chains of oscillators). The circumstances are much more favorable to networks of harmonic oscillators [CDF, KSD]. Despite being very special, the latter provide effective models for a wide range of systems and processes, from macroscopic electrical circuits [CCZ, GMR] to the microscopic dynamics of protein [HE, ADJ], including the motion of mesoscopic colloidal particles [Vi, JPC]. A novel control-theoretic approach to stochastically driven harmonic networks has been developed in [JPS]. There, FRs were obtained for various quantities related to the entropy produced by a general harmonic network driven out of equilibrium by thermal forcing (see Eq. (2.11) below for a typical result). The purpose of the present work is to continue these investigations, following the same control-theoretic strategy, and focusing on the individual energy currents flowing between the network and its environment.
Let us briefly describe the settings of [JPS] which will be used in this work. We focus on a collection, indexed by a finite set , of one-dimensional harmonic oscillators with position and momentum coordinates and . The Hamiltonian of this system is the quadratic form
[TABLE]
where denotes the Euclidean norm and an automorphism of .
Besides the conservative harmonic forces deriving from this Hamiltonian, a subset of the oscillators, indexed by , is acted upon by thermal reservoirs. The latter are described by Langevin forces
[TABLE]
where denotes the temperature of the –reservoir, the rate at which energy is dissipated in this reservoir and is a standard white noise. We interpret the work222The integral there is to be taken in Itô’s sense.
[TABLE]
performed by the Langevin force during the time interval as the amount of heat injected in the network by the –reservoir during this period. We denote by the vector space where the heat currents take their values and write the associated Euclidean inner product as .
The main results of the present work concern the statistics of the –valued process induced by the stationary Markov process generated by the system of stochastic differential equations
[TABLE]
with appropriate initial conditions. More precisely, and under a controllability condition which ensures the existence and uniqueness of an invariant measure for this Markov process:
- •
We identify a subspace characterized by the fact that for one has
[TABLE]
where is a quadratic form which is a first integral of the harmonic network. Applying a general result of [BJP] allows us to describe the asymptotics of (1.3) in the limit . Besides a large deviation principle (LDP for short) for the fluctuations of order of this quantity, we also get the explicit form of its limiting distribution, which has full support. This is in sharp contrast with what would happen if was a bounded function on the phase space: the right-hand side of (1.3) – often coined a “boundary term” in the physics literature – would have no order fluctuations and its limiting law would have compact support.
- •
We then focus on the component of the heat flux orthogonal to . We show that it has fluctuations of order satisfying a local LDP whose rate function is the (partial) Legendre transform of a real analytic function for which we provide several explicit representations. In particular, we connect to the spectral properties of a finite dimensional matrix and the domain of validity of the LDP to some associated algebraic Riccati equation. Both functions and satisfy a FR.
- •
We derive a simple sufficient condition, in terms of the solutions to the above mentioned Riccati equation, which ensures that our LDP and the associated FR hold globally. We also provide several examples where our condition is fulfilled. This shows that there is a regime where the components of the heat flux along the subspace are responsible for the failure of the global FR for the entropy production observed in [JPS]. Our examples show, however, that our sufficient condition does not survive strong thermal forcing.
- •
In cases where the LDP for holds globally without our sufficient condition being satisfied, we show that the rate function only satisfies the universal FR on a proper subset of which is again described in terms of the solutions to the Riccati equation.
The remaining parts of the paper are organized as follows. In Section 2, we introduce a general class of harmonic networks driven out of thermal equilibrium by heat reservoirs. We describe the stochastic processes generated by their nonequilibrium dynamics and, within this probabilistic framework, we identify the fluxes of energy flowing between the network and the heat reservoirs. Then, we briefly recall some results of [JPS] on the fluctuations of the entropy produced by the networks in a nonequilibrium steady state: a large deviation principle and the associated FRs. Finally, we sketch a naive argument which will motivate the approach followed in this work.
In Section 3, we formulate our main results on the fluctuations of the heat fluxes in a nonequilibrium steady state of the network. Under a natural controllability assumption, we provide an explicit formula for the large time asymptotics of the cumulant generating function of these fluxes. Then, we describe the resulting local LDP for the fluctuations of the heat fluxes and the associated FRs. Finally, under an additional assumption on the network, we provide a global LDP with its associated FRs.
In Section 4, we provide some specific examples to which our results apply. The final Section 5 collects all the proofs of our results.
Acknowledgements. This research was supported by the Agence Nationale de la Recherche (ANR) through the grant NONSTOPS (ANR-17-CE40-0006) and the CNRS collaboration grant Fluctuation theorems in stochastic systems. The work of C.-A.P. has been carried out in the framework of the Labex Archimède (ANR-11-LABX-0033) and of the A*MIDEX project (ANR-11-IDEX-0001-02), funded by the “Investissements d’Avenir” French Government program managed by the ANR.
Parts of this work were performed during the visits of M.D. and M.H. at the University of Toulon and of C.-A.P. at the University of Sfax. We thank the CPT, the University of Toulon and the Mathematics Department of Sfax for their hospitality and support. M.H. and C.-A.P. are also grateful to the Centre de Recherches Mathématiques de l’Université de Montréal for its hospitality and the Simons foundation and CNRS for their support during their stay in Montréal in the fall 2018.
2 The model
2.1 Setup
In order to set up the notation to be used in the sequel, we briefly recall the general framework of [JPS], referring the reader to this paper for more details.
Notations and conventions. Let and be real or complex Hilbert spaces. denotes the set of (continuous) linear operators and . For , denotes the adjoint of , its operator norm, its range and its kernel. We denote the spectrum of by . is non-negative (resp. positive), written (resp. ), if it is self-adjoint and (resp. ). We write whenever . A pair is said to be controllable if the smallest -invariant subspace of containing is itself. Denoting by the open left/right half-plane, is said to be stable/anti-stable whenever .
We consider the harmonic network described in the Introduction. The configuration space is endowed with its Euclidean structure and the phase space is equipped with its canonical symplectic structure. On these spaces, and denote the Euclidean norm and inner product, respectively. Recall that the Euclidean inner product of the space is written .
Convention. We identify with the element of defined by
[TABLE]
In particular, whenever we write inequalities involving such , they are always to be interpreted as operator inequalities.
Introducing the linear map defined by
[TABLE]
we set
[TABLE]
The internal energy of the network then writes , and its dynamics is described by the following system of Itô stochastic differential equations
[TABLE]
denoting a standard –valued Wiener process. The solution of the Cauchy problem associated to (2.2), with initial condition , can be written explicitly as
[TABLE]
This relation defines a family of –valued Markov processes indexed by the initial condition . The generator of this degenerate diffusion process is given by
[TABLE]
where . We shall denote the probability measure induced on the path space and by the corresponding expectation functional. Given a probability measure on , we further set and define similarly .
For later references, we note the following structural relations
[TABLE]
Moreover, denoting by the time-reversal involution of ,
[TABLE]
Setting
[TABLE]
we also have
[TABLE]
In the sequel, we shall further assume the Kalman condition
(C) The pair is controllable.
We recall (see [JPS, Theorem 3.2] and references therein) that under this assumption the process (2.3) admits a unique invariant measure , the centered Gaussian measure on with covariance
[TABLE]
which is also characterized as the unique solution of the Lyapunov equation .
Remark. If the environment is in thermal equilibrium at temperature , i.e., if , then and is the Gibbs measure .
2.2 Heat fluxes and entropy production
Following [JPS], we shall interpret the work (1.2) performed by the Langevin force during the time interval as the amount of heat injected in the network by the –reservoir during this period. In [JPS], a LDP and extended fluctuation relations were proven for the total amount of entropy dissipated in the reservoirs, i.e., the entropy produced by the network
[TABLE]
Let us briefly recall these results.
Assuming the Kalman condition (C), the family satisfies a global LDP with a good rate function , i.e., for any Borel set , one has
[TABLE]
where and denote respectively the interior and the closure of . The mean entropy production rate
[TABLE]
exists and is non-negative. Whenever , the rate function satisfies the FR
[TABLE]
for . However, this universal relation fails for where, instead, a model dependent extended fluctuation relation holds (see [JPS, Section 3.7]).
Our aim here is to derive a LDP and FRs for the individual heat fluxes . To motivate our approach, let us sketch a naive argument leading to the desired results.
The Gärtner-Ellis theorem (see, e.g., [DZ] or [dH]) is a well-known route to the LDP. To follow it, one has to show the existence and some regularity properties of the large time limit
[TABLE]
of the cumulant generating function
[TABLE]
A simple calculation yields the expression
[TABLE]
By Itô calculus, one has
[TABLE]
where
[TABLE]
is a deformation of the Markov generator (2.4), the matrices and being given by
[TABLE]
A naive application of Girsanov formula yields
[TABLE]
and in particular
[TABLE]
Given the specific form of and the fact that it generates a positivity preserving semigroup, it is natural to seek an eigenvector to its dominant eigenvalue in the Gaussian form
[TABLE]
A simple calculation shows that the eigenvalue problem splits into the following algebraic Riccati equation for a symmetric matrix ,
[TABLE]
and the relation
[TABLE]
where denotes the maximal333 is maximal whenever for all self-adjoint such that . solution of (2.16). From the structural relations (2.5)–(2.7) and the fact that one easily deduces that the formal adjoint of is given by
[TABLE]
where the map is defined by .
Assuming to have a non-vanishing spectral gap, we obtain
[TABLE]
as , and hence
[TABLE]
provided the prefactor
[TABLE]
is finite and positive.444Here, we used the fact that the steady state covariance satisfies . The fluctuation relation
[TABLE]
then follows from (2.17).
Assuming the limiting cumulant generating function to be everywhere differentiable on , the Gärtner-Ellis theorem yields the LDP
[TABLE]
where denotes the interior/closure of the Borel set , the rate function being given by the Legendre transform
[TABLE]
Relation (2.19) thus translates into the FR
[TABLE]
where we recognize, in the right-hand side, the entropy production rate corresponding to the heat flux .
There are several issues with the above formal derivation. In particular, we can’t expect the fluctuation relation (2.20) (resp. (2.19)) to hold for all values of (resp. for all values of ). Indeed, by the contraction principle, the validity of (2.20) for all would entail the validity of (2.11) for all , in contradiction with the above mentioned result of [JPS]. The main contribution of the present work is to provide a rigorous proof of a large deviation principle for heat fluxes, an explicit formula for the rate function and a description of the domain of validity of the universal relation (2.20).
3 Main results
3.1 The limiting cumulant generating function
In this paragraph, we first formulate the generalized detailed balance relation (see [EPR, Section 4.3] and [BL, Section 2.2]) which plays a central role in our analysis. Then we state our main result on the large time asymptotics of the cumulant generating function (2.13).
Proposition 3.1**.**
Given , we shall write whenever is self-adjoint and satisfies
[TABLE]
To such a , we associate the quadratic forms
[TABLE]
and
[TABLE]
and the measure on defined by
[TABLE]
Then, the following assertions hold:
- (1)
* and satisfy*
[TABLE] 2. (2)
Denote by the formal adjoint of the Markov generator (2.4) w.r.t. the inner product of the Hilbert space . Then the generalized detailed balance relation
[TABLE]
holds. 3. (3)
There exists satisfying (3.1) and such that iff
[TABLE]
holds for all . Moreover, under Condition (C), such a , if it exists, is unique and satisfies
[TABLE] 4. (4)
The functional (2.14) can be written as
[TABLE]
Given the structure of the map and the diagonal nature of , the existence of satisfying (3.1) is obvious. Apart from Part (3), the proof of the previous proposition is identical to the elementary proof of Proposition 3.5 in [JPS] and we omit it. The first statement in (3) follows from an explicit calculation. One easily checks that is equivalent to , which implies that for any . Thus, Condition (C) immediately yields the uniqueness of . Similarly, one deduces from the relation , obviously valid for , that and have the same spectrum.
Proposition 3.2**.**
Assume that Condition (C) holds.
- (1)
For and , the operator
[TABLE]
is self-adjoint on the complexification of and does not depend on the choice of . Moreover, the map is continuous. 2. (2)
The set
[TABLE]
is open, convex, centrally symmetric around the point and contains
[TABLE]
Its lineality space555The lineality space of a convex set is the set of vectors such that for all and all , see [Ro]* is given by*
[TABLE]
and in particular . 3. (3)
The function
[TABLE]
is convex and real analytic on . It is centrally symmetric w.r.t. the point and translation invariant in the direction , i.e.,
[TABLE]
for all and . In particular, . 4. (4)
One has
[TABLE]
and the following alternative holds: Either and vanishes identically, or and is strictly convex on the section , the closure of being a compact convex subset of . 5. (5)
For , define
[TABLE]
where and are given by (2.15). Then is the connected component of the point in the set
[TABLE]
Moreover, for any one has
[TABLE] 6. (6)
The function has a bounded continuous extension to the closed set which is given by
[TABLE]
where denotes the algebraic multiplicity of . 7. (7)
For any finite one has
[TABLE]
Thus, setting for yields an essentially smooth, essentially strictly convex, closed, proper convex function . 8. (8)
For all the Riccati equation (2.16) has a maximal self-adjoint solution . The map is continuous and concave on , and
[TABLE]
Moreover, setting , the pair is controllable and .
The lineality subspace is related to conservation laws of the harmonic network. Indeed, under its Hamiltonian dynamics, the network evolves according to and hence
[TABLE]
for . It follows that, for any , the quadratic form is a first integral of the Hamiltonian flow. In particular the direction and the invariance is related to the conservation of the total energy of the network, . This symmetry of the cumulant generating function of currents was already described, in the quantum setting, in [AGMT], see also [BPP] for a detailed discussion.
It follows from [JPS, Theorem 3.13] that the entropy production rate of the network (2.10) is related to the function by
[TABLE]
Thus, whenever the alternative in Part (4) of Proposition 3.2 holds. In the following we shall avoid trivialities assuming, without further notice, that and hence and
[TABLE]
with . By Proposition 3.2 (8) the functions
[TABLE]
are continuous and respectively convex/concave on . The function of the preceding proposition is related to the limiting cumulant generating function (2.12) by the following
Proposition 3.3**.**
Under Assumption (C) one has
[TABLE]
where (compare this with the right-hand side of (2.18))
[TABLE]
is a bounded, open, convex subset of such that
[TABLE]
In particular, contains a neighborhood of [math].
3.2 Fluctuations of conserved quantities
As mentioned above, each is associated to a first integral of the harmonic network. In this section, we briefly focus on these conserved quantities. Since and for large enough, there is no loss of generality in assuming that . It follows from Proposition 3.1 (4) and [BJP, Proposition 2.2] that the law of
[TABLE]
under converges towards a variance-gamma distribution
[TABLE]
with density
[TABLE]
where666Recall that , given in (2.8), is the covariance of the invariant measure . , , is the Lebesgue measure on the unit sphere of , and denotes a modified Bessel function [W]. As mentioned in the Introduction, the variance-gamma distribution as full support on . Moreover, the above convergence is accompanied by a LDP: for any open set ,
[TABLE]
with the rate function
[TABLE]
This applies, in particular, to the fluctuations of the total energy which was the primary concern in [BJP].
3.3 A local Fluctuation Theorem
While the results of the previous section quantify departures from the conservation laws, the main results of this paper deal with the component of the heat currents fluctuations which do not violate these conservation laws.
Recall that is the (precompact, convex) base of the cylinder . Denoting by the orthogonal projection on , setting and defining the function by
[TABLE]
a direct application of the Gärtner-Ellis theorem yields the following
Theorem 3.4**.**
Assume that Condition (C) holds. Then, under the law , the family satisfies a local LDP with the good rate function given by (3.9), i.e., for any Borel set , one has
[TABLE]
where and denote respectively the interior and the closure of and
[TABLE]
Moreover, for , the fluctuation relation
[TABLE]
holds.
3.4 A global Fluctuation Theorem
To improve on Theorem 3.4 and obtain a global LDP on , we impose a further condition on the network:
(R)
Since is a concave function of on , Condition (R) ensures that it is positive on .
Theorem 3.5**.**
Assume that Conditions (C) and (R) hold. Then, under the law , the family satisfies a global LDP with the good rate function given by (3.9), i.e., for any Borel set , one has
[TABLE]
where and denote respectively the interior and the closure of . Moreover, the fluctuation relation
[TABLE]
holds for all .
Remark. We stress that Theorem 3.5 only gives sufficient conditions for the global validity of the LDP. We conjecture that Condition (C) alone is sufficient for (3.11) to hold for all Borel sets (with the rate function given by (3.9)). However, we were not able to prove this claim, and in particular we are not aware of any general result in the theory of large deviations which would imply it. We leave this conjecture as an interesting open problem.
Discussion.
-
The quantity is the entropy production rate associated with a given heat current (compare with (2.9)). Thus, the FR (3.12) implies that current fluctuations with negative entropy production rate are exponentially suppressed, as , relative to the opposite fluctuation (which has positive entropy production rate).
-
We note that, according to the results of [JPS], the entropy production (2.9) never satisfies the FR (2.11) globally (i.e., for all ). This is in sharp contrast with the component of the heat flux along . Indeed, we will see in the next section that a global FR is possible in this case.
-
Suppose that, in view of the above conjecture, Condition (R) being violated, the LDP (3.11) holds for all Borel sets . It follows that the FR (3.12) does not hold for all but is replaced by an extended – i.e., non-universal – FR on the unbounded set
[TABLE]
as illustrated in Figure 3, below. The graph of the rate function in the region has the peculiar form of a ruled surface. More precisely, for let and denote by the exterior normal to at . Then, one has for all . This behavior generalizes to the multivariate case the affine character of the rate function of scalar observables (heat, entropy production,…) found in [CZ, BJTM, Fa, RH, Vi, JPS]. In these circumstances, the rate function is convex on but fails to be strictly convex on the complement of . As in the scalar cases mentioned above, the somewhat striking consequence of these extended FRs is an increase of the probability ratio for current fluctuations with negative to positive entropy production rate.
-
From a mathematical perspective, deviations from the FR (3.12) are due to the lack of essential smoothness of the limiting cumulant generating function (3.8). In the setting of the present work, this can be traced back to the divergence of a pre-exponential factor in the asymptotic expansion of the cumulant generating function (the term in (5.13) below). The analysis of [EN, RH] suggests that this phenomenon may remain relevant beyond the harmonic/Gaussian setting, however we are not aware of any rigorous result in this direction.
-
From the physical point of view, the circumstances leading to the failure of the global FR (3.12) are still not well understood. However, the examples below tend to indicate that the strength of the thermal drive (and hence large currents) is one determinant factor.
4 Examples
Observe that Eq. (3.2) implies that the matrix and thence the function are invariant under the simultaneous rescaling
[TABLE]
with . Furthermore, one easily checks that, under the same rescaling, the maximal solution to the Riccati equation (2.16) obeys , so that . Consequently, without losing in generality, we shall fix the average temperature according to
[TABLE]
in all our examples, denoting temperature ratios by . For systems out of thermal equilibrium, we shall also use a special system of cartesian coordinates on the space : we set its origin at the orthogonal projection of the symmetry center on , and chose the first basis vector along the same direction. Finally, we note that in all the examples below, it is straightforward to check that Condition (C) is satisfied and that . We shall therefore concentrate our discussions on the validity of Condition (R).
4.1 A lozenge network
As a first example of numerical exploitation of our scheme, we investigate some properties of the Lozenge network of Figure 1. With and , the parameters of the model are given by
[TABLE]
Consider first the case of thermal equilibrium: . The mean heat fluxes vanish, . From the right pane of figure 1, which shows the functions , one infers that Condition (R) is verified so that, by Theorem 3.5, the global LDP (3.11) holds with a rate function satisfying the FR (2.20) on .
By continuity, Condition (R) persists sufficiently near thermal equilibrium so that the same conclusions hold there. Figure 2 shows the “spectral gap” on the boundary of the set for different temperature ratios. It appears that this gap eventually closes (i.e., takes non-positive values) when the temperature differences become large. We conclude that the FR (2.20) breaks down in this regime. This is illustrated on Figure 3 where the rate function and the anomalous fluctuation function are plotted for the temperature ratios .
4.2 A triangular network
Our second example is the triangular network already considered in [JPS] and illustrated on the left pane of Figure 4. Here we have , and the parameters are
[TABLE]
In thermal equilibrium one finds that is the disk of radius centered at [math] on . The spectral gap is open, as seen on the right pane of Figure 4. Hence, here again, Theorem 3.5 applies: the global LDP (3.11) and the FR (2.20) hold on near equilibrium.
The spectral gap on the boundary is plotted in Figure 5 for various temperature ratios . One observes a similar behavior as in our first example.
4.3 A heat pump network
Our last example is the heat pump network of [EZ], see Figure 6. With and , the parameters:
[TABLE]
were chosen in [EZ] in such a way that the mean steady heat current between the vertices 5 and 6 vanishes while the heat flows from the hot reservoir to the cold one on the left side, and from the cold to the hot one on the right side. Thus, the right side of the device acts as a heat pump. On the right pane of Figure 6 we plot the two functions on the boundary .777 In Figures 6 and 7 the set is mapped to the closed unit disk by first mapping to the unit sphere and then mapping the point with spherical coordinates on this sphere to the point of the plane. Condition (R) is satisfied, so that the global large deviation principle (3.11) and the FR (2.20) hold on near this non-equilibrium heat pump regime.
As shown in Figure 7, here again the spectral gap closes as the temperatures differences increase.
5 Proofs
5.1 Proof of Proposition 3.2
In order to prove the proposition, we shall need the following two Lemmas.
Lemma 5.1**.**
Let and be linear operators on a finite dimensional Hilbert space and a partition of the plane into two open half-planes and a separating line . Assume that and that and have the same number of repeated eigenvalues in . Denote by and the parts of and corresponding to their spectra in . Let be a compact set such that . Then the following holds:
- (1)
The function is analytic in . 2. (2)
For any Jordan curve in “enclosing”
[TABLE]
Proof. (1) By assumption we can enumerate the repeated eigenvalues of and in such a way that
[TABLE]
with
[TABLE]
In terms of these eigenvalues, we have
[TABLE]
The Möbius transformation maps the interior of the complement of any open neighborhood of the line segment joining to to a simply connected open subset of . It follows that the function is analytic on the complement of any neighborhood of the segment joining to . Thus, the functions and are analytic in and so is .
(2) The first identity in (5.1) now follows from integration by parts. Finally, noticing that
[TABLE]
the second identity follows from the Riesz formula
[TABLE]
Lemma 5.2**.**
Let and be as in the previous Lemma, where is the imaginary axis and the right half-plane. Then
[TABLE]
In particular, if the spectra of and are symmetric w.r.t. , then and similarly for , so
[TABLE]
where denotes the algebraic multiplicity of the eigenvalue .
Proof. Denote by the positively oriented boundary of the intersection of the disk of radius centered at [math] with the right half-plane. Applying the previous Lemma and observing that is analytic in a neighborhood of we get, for large enough,
[TABLE]
To evaluate the second integral on the right-hand side we note that, as ,
[TABLE]
so
[TABLE]
and
[TABLE]
It follows that
[TABLE]
and we conclude that
[TABLE]
The last two statements follow from elementary calculations.
We now turn to the proof of Proposition 3.2
(1) Set . Assumption (C) implies that is stable (see (2.5)) so that the map is continuous. Using the identities
[TABLE]
a simple calculation yields that for any one has
[TABLE]
with . All the stated properties immediately follow.
(2) It will be convenient to introduce and to rescale by setting . With this change of variable
[TABLE]
and
[TABLE]
It immediately follows that . Moreover, since is an affine function of , is convex.
Using (2.5), elementary calculations (see [JPS, Section 5.5]) show that, for any , and . The first relation allows us to derive
[TABLE]
and the second one yields that , which shows that is centrally symmetric around the point . To show that it is open, we now argue that its complement is closed. Indeed, iff there exists such that has an eigenvalue . Thus, if is a sequence in which converges to , there exist , and unit vectors such that . Given the fact that
[TABLE]
one concludes that and . Thus the sequence has a convergent subsequence with limit satisfying , and . Hence, and consequently is closed.
If the map vanishes identically on , then it follows from the identity that for all . Reciprocally, if the later condition holds, then for all and all , one has
[TABLE]
Letting we deduce that vanishes identically. Note that the later condition is satisfied for any such that there exists with . This is in particular the case for and . Reciprocally, since it follows from Condition (C) that the set is total in , one concludes that for all implies for any .
(3) Consider first the map for fixed . The previous discussion clearly implies that it is real analytic. Its convexity follows from an elementary calculation which yields that
[TABLE]
for and . From (5.2) one further deduces that as , locally uniformly in . It follows that
[TABLE]
is convex and real analytic on . The identity (5.3) leads to
[TABLE]
and in particular . This proves the first equality in (3.4). The second one follows from (3.3) and the linearity of the map .
(4) The second equality in (3.4) implies that for all and all . To establish the reciprocal property, note that since is open, for any and any there exists such that for . It follows that the function is constant in a real neighborhood of [math] and hence extends by analyticity to the constant function on the line . Since, by Part (7), is singular on , it follows that , i.e., .
Consequently, vanishes identically whenever . In the opposite case, the calculation in Part (3) gives that the Hessian of satisfies
[TABLE]
for non-zero . It follows that the restriction of to is positive definite which implies that the restriction of to is strictly convex. To show that the closure of is compact, let us assume that is unbounded. Since is convex and centrally symmetric w.r.t. the orthogonal projection of onto , it follows that for some non-vanishing one has for all , i.e.,
[TABLE]
for all . Letting yields that which contradicts the fact that .
(5) We start with some simple consequences of Condition (C). For a short introduction to the necessary elementary material, we refer the reader to [LR, Section 4]. Since , the pair is controllable for all . The relation shows that the same is true for the pair . Thus, one has
[TABLE]
for all . This implies that if and or , then , i.e., no eigenvector of or can live in . Assume now and let be a corresponding eigenvector. Since
[TABLE]
taking the real part of we infer
[TABLE]
Thus, controllability of implies that for one has and in particular . Hence, for and , Schur’s complement formula yields
[TABLE]
where we have set
[TABLE]
One easily checks that from which a simple calculation gives
[TABLE]
Inserting the last identity into the right-hand side of (5.4) and using the fact that
[TABLE]
we obtain
[TABLE]
Both sides of this identity being polynomials in , it extends to all . It follows that
[TABLE]
By continuity of the function , is the connected component of the point in the left-hand side of this identity.
(6) For , is -linear on the real vector space . Thus, its spectrum is symmetric w.r.t. the real axis. Observing that , where is the unitary operator
[TABLE]
we conclude that the spectrum of is also symmetric w.r.t. the imaginary axis. Assume now that . Since the eigenvalues of are continuous functions of , and have the same number of repeated eigenvalues in the left/right half-plane. From (5.5) we deduce
[TABLE]
and Lemma 5.2 allows us to conclude that
[TABLE]
Since and is stable, we have
[TABLE]
and (3.6) follows for . Since the eigenvalues of are continuous functions of , this relation extends to . The boundedness of this extension follows from the translation invariance along and the precompactness of .
(7) The idea of the proof is that iff at least one eigenvalue of reaches its global maximum at some . Since is a real analytic function of , the function has a pôle at , and since this function is non-negative the order of this pôle must be even. Consequently,
[TABLE]
For , a simple calculation and Cauchy–Schwarz inequality yield
[TABLE]
Since , it suffices to show that the integral on the right-hand side diverges to as . Let us fix and set . Elementary considerations show that for sufficiently small and sufficiently large there exists a constant such that
[TABLE]
for any . Making smaller and larger if necessary, we can assume that satisfies for . Writing
[TABLE]
and observing that this implies, in particular, that , we derive
[TABLE]
By Fatou’s lemma
[TABLE]
and by the above argument, the last integral is .
(8) The existence and uniqueness of the maximal solutions of Eq. (2.16) as well as the stated properties of follow from [LR, Theorems 7.3.7 and 7.5.1], Part (5), and the relation . It further follows from (3.6) and the symmetries of discussed in the proof of Part (5) that
[TABLE]
The proof of Proposition 3.2 is complete.
5.2 Proof of Proposition 3.3
5.2.1 Some properties of the algebraic Riccati equations (2.16)
In order to prove Proposition 3.3 we shall need some properties of the algebraic Riccati equation
[TABLE]
This is the purpose of the following proposition which provides a generalization of [JPS, Proposition 5.5]. In the sequel, whenever we mention a solution of (5.6), we always mean a self-adjoint such that . We say that such a solution is maximal (resp. minimal) if any other solution satisfies (resp. ).
Proposition 5.3**.**
Assume that Condition (C) holds.
- (1)
For the Riccati equation (5.6) has a unique maximal solution and a unique minimal solution . Moreover, the matrix
[TABLE]
is stable and satisfies
[TABLE] 2. (2)
If is finite, then the non-tangential limit
[TABLE]
exists and is the maximal solution of the corresponding limiting Riccati equation . 3. (3)
The function is real analytic and concave. Moreover, for , for in the convex hull of the set , and . 4. (4)
For any and one has
[TABLE] 5. (5)
For , set
[TABLE]
Then, for all one has
[TABLE]
and is the spectral subspace of corresponding to its imaginary eigenvalues. 6. (6)
Set . For all , one has
[TABLE]
and
[TABLE]
In particular, for , exponentially fast as . 7. (7)
Let . Then
[TABLE]
for all and . 8. (8)
For and
[TABLE]
Proof. We refer to [LR] for a detailed introduction to algebraic Riccati equations (see also the Appendix in [JPS] for a summary of the necessary basic facts). Our proof is similar to that of [JPS, Proposition 5.5]. The Hamiltonian matrix associated to the Riccati equation (5.6) is given by Eq. (3.5). Let be the complex Hilbert space on which acts. The operator
[TABLE]
acts unitarily on . We have already observed in the proof of Proposition 3.2 (6) that for , the spectrum of is symmetric w.r.t. the real axis and the imaginary axis. The time-reversal covariance relations
[TABLE]
which follow easily from the definitions of the operators , , , further yield which implies
[TABLE]
Let be the spectral subspace of for the part of its spectrum in the open left half-plane .
(1) By Proposition 3.2 (5), for and the existence and uniqueness of the maximal and minimal solutions of the Riccati equation (5.6) follow from [LR, Theorems 7.3.7 and 7.5.1]. The relation between minimal and maximal solutions is a consequence of the Relations (5.8) which imply that
[TABLE]
By [LR, Theorems 7.5.1], the maximal solution is related to the spectral subspace by
[TABLE]
moreover, .
is called the gap of Eq. (5.6). As the difference between its maximal and minimal solutions, it is obviously non-negative. It further has the remarkable property that for any solution , is the spectral subspace of for the part of its spectrum in [LR, Theorem 7.5.3]. Since , we must have .
(2) Let be finite and be non-tangential to at . Set . W.l.o.g. we may assume that . The function
[TABLE]
is concave and its first derivative vanishes at . Hence, it is monotone non-decreasing. We claim that the set is bounded in for any finite . It thus follows that
[TABLE]
exists. By continuity, one has and , and it follows from [LR, Theorem 7.5.1] that is the maximal solution of the limiting Riccati equation. In particular, the non-tangential limit exists (i.e., does not depend on the direction).
To prove our claim, we first derive a bound on . Using , one easily deduces from (5.6) and Cauchy-Schwarz inequality
[TABLE]
where and are locally bounded functions of . Solving the resulting quadratic inequality yields that , and hence are locally bounded as functions of . Rewriting (5.6) as the Lyapunov equation
[TABLE]
and using the fact that is stable, we get
[TABLE]
It follows that for any
[TABLE]
from which one easily concludes that is locally bounded.
(3) The spectral projection of for the part of its spectrum in can be written as
[TABLE]
Since is real analytic by regular perturbation theory, and are real analytic function of . The same holds for and .
Invoking the implicit function theorem and using the stability of , one easily computes derivatives of the map . The first derivative is the linear map
[TABLE]
where, as usual, we identify with the corresponding diagonal matrix in and . The second derivative is the quadratic form
[TABLE]
and concavity follows from the obvious fact that .
To prove the inequalities let us rewrite the Riccati equation (5.6) as a Lyapunov equation
[TABLE]
and recall that, as established in the proof of Proposition 3.2 (5), is stable for . Thus, we have
[TABLE]
and since for , we conclude that for and for . The controllability of yields that these inequalities for are strict. Writing (5.6) as
[TABLE]
the stability of gives
[TABLE]
and since for , we can conclude that for such . The controllability of again yields the strict inequality. The concavity of the map implies that the subset of all such that is convex, so that it contains the convex hull of .
From
[TABLE]
we deduce . To prove the last assertion, starting from Eq. (5.6) and invoking Relations (5.8) one shows that satisfies the Lyapunov equation . Since is stable, this equation has a unique solution given by (2.8), hence .
(4) A simple calculation yields
[TABLE]
for any and . Thus, and since , we conclude that whenever one has .
(5)–(7) The proof follows line by line the one of the corresponding Parts of [JPS, Proposition 5.5].
(8) Upon differentiating Eq. (3.7) one gets
[TABLE]
Further, using (5.10) leads to
[TABLE]
and the result now follows from Part (5).
5.2.2 Proof of Proposition 3.3
By Proposition 5.3, for , we have with , and we can rewrite the equation of the motion (2.2) as
[TABLE]
where
[TABLE]
Let be the stochastic exponential of the local martingale
[TABLE]
Combining Eq. (5.6) with the relations and , we derive
[TABLE]
and we can write the quadratic variation of as
[TABLE]
Itô calculus and Proposition 3.1 (4) give
[TABLE]
with
[TABLE]
and, taking (3.7) into account,
[TABLE]
The proof of the following Lemma is identical to the one of [JPS, Lemma 5.7], and we omit it.
Lemma 5.4**.**
For , the process
[TABLE]
is a -martingale for all .
Applying Girsanov theorem, we conclude that is a standard Wiener process under the law . It follows that the finite-time cumulant generating function can be written as
[TABLE]
for , i.e.,
[TABLE]
where
[TABLE]
and is the Markov semigroup associated with the SDE (5.11). From the explicit solution
[TABLE]
to this SDE we easily obtain the representation
[TABLE]
Setting
[TABLE]
and , an elementary calculation then leads to
[TABLE]
Schur’s complement formula and Proposition 5.3 (5–6) lead to the factorization
[TABLE]
where
[TABLE]
, as defined in Proposition 5.3 (6), and are strictly positive for and vanish exponentially as . Thus, for ,
[TABLE]
and setting
[TABLE]
one has
[TABLE]
It follows that, for all , the limit
[TABLE]
is finite and positive, which yields the first part of (3.8). To deal with the second part, we note that whenever , then either or . In the latter case, either or has a negative eigenvalue and the matrix loses its positiveness as . It follows that and hence for large enough . For , applying [JPS, Lemma 5.8] to the functions yields the desired result.
Finally, we note that the continuity and concavity of the map imply that is an open convex subset of . The positiveness of for is a consequence of its continuity and proves the last statement, concluding the proof of Proposition 3.3.
5.3 Proof of Theorem 3.4
Since and , it follows from the continuity of the map that the open set contains [math]. By Proposition 3.3, is the interior of the essential domain of the limiting cumulant generating function (3.8). The Gärtner-Ellis theorem thus implies that the LDP upper bound in (3.10) hold for any Borel , with the rate function
[TABLE]
Moreover, the corresponding lower bound holds for any subset of the set of exposed points of this function. Let us set . We have to show that .
By Proposition 3.2 (3+4+6) , for all one has
[TABLE]
It follows from Proposition 3.2 (4+7) and [Ro, Theorem 26.5] that, as a function on , is the Legendre conjugate of the restriction of to . In particular, it is strictly convex and differentiable on . Moreover, is a homeomorphism whose inverse is . Since is open and convex, so is , and its image is open and connected. We note that
[TABLE]
for . For one has
[TABLE]
i.e., and coincide on . In particular, is strictly convex on any convex subset of . Suppose that is not an exposed point of . Since with , there exists such that and . Invoking convexity, one shows that with and , which contradicts the strict convexity of in a convex neighborhood of .
Whenever both , we have and with and , and thus,
[TABLE]
Finally, we note that . Proposition 5.3 (3) implies that and for , and hence that .
5.4 Proof of Theorem 3.5
By Theorem 3.4 it suffices to show that, under Condition (R), one has . By Proposition 5.3 (4), for any and any one has
[TABLE]
so that
[TABLE]
Similarly, from
[TABLE]
we deduce that
[TABLE]
It follows that
[TABLE]
and hence
[TABLE]
Thus, under Condition (R), .
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