Next Article in Journal
Why Uncertainty Is Essential for Consciousness: Local Prospect Theory vs. Predictive Processing
Next Article in Special Issue
Partition Function Zeros of Paths and Normalization Zeros of ASEPS
Previous Article in Journal
Neuro-Fuzzy Network-Based Nonlinear Hybrid Active Noise Control Systems
Previous Article in Special Issue
Partition Function Zeros of the Frustrated J1J2 Ising Model on the Honeycomb Lattice
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Finite-Size Scaling in the Ageing Dynamics of the 1D Glauber–Ising Model †

1
Laboratoire de Physique et Chimie Théoriques (CNRS UMR 7019), Université de Lorraine Nancy, B.P. 70239, F-54506 Vandœuvre lès Nancy Cedex, France
2
Centro de Física Teórica e Computacional, Universidade de Lisboa, Campo Grande, P-1749-016 Lisboa, Portugal
In memoriam Ralph Kenna.
Entropy 2025, 27(2), 139; https://doi.org/10.3390/e27020139
Submission received: 24 December 2024 / Revised: 9 January 2025 / Accepted: 10 January 2025 / Published: 28 January 2025

Abstract

:
Single-time and two-time correlators are computed exactly in the 1 D Glauber-Ising model after a quench to zero temperature and on a periodic chain of finite length N, using a simple analytical continuation technique. Besides the general confirmation of finite-size scaling in non-equilibrium dynamics, this allows for testing the scaling behaviour of the plateau height C ( 2 ) , to which the two-time auto-correlator converges when deep in the finite-size regime.

1. Introduction

An important class of physical phenomena arises in the context of ageing phenomena [1,2] which occur after a many-body system has been quenched from some prescribed initial state, either onto a critical point where at least two physical phases become indistinguishable or into a phase co-existence region where two macroscopic physical phases coexist. In either case, the post-quench dynamics are slow, which may come from the effects of critical-point fluctuations or from the competition between relaxation towards at least two distinct physical states. Microscopically, the system separates into many (correlated or ordered) clusters whose mean size, ( t ) , grows with time. Phenomenologically, one observes the three defining properties of physical ageing on a macroscopic scale [3]:
  • Slow dynamics (relaxations are slower than might be described by simple exponentials);
  • Absence of time-translation invariance;
  • Dynamical scaling.
These properties manifest themselves in the typical behaviour of correlation functions, which might be thought of in terms of a coarse-grained order-parameter ϕ = ϕ ( t , r ) which depends on the time t and the space coordinates r . For example, notably in situations where the average order parameter ϕ ( t , r ) = 0 , one often considers single-time or two-time correlators (which depend on both the waiting time s and the observation time t > s )
C ( t ; r ) = ϕ ( t , r ) ϕ ( t , 0 ) , C ( t , s ; r ) = ϕ ( t , r ) ϕ ( s , 0 )
We restrict this work to phase ordering, which occurs for a non-conserved order parameter quenched to T < T c . Then, one generically finds, for large enough times (spatial translation and rotation invariance are implicitly admitted)
C ( t ; r ) : = C ( t ; | r | ) = F C 1 , | r | t 1 / z , C ( t , s ; r ) : = C ( t , s ; | r | ) = F C t s , | r | s 1 / z
which is specified here for systems where the typical domain size ( t ) t 1 / z increases algebraically for large times. This defines the dynamical exponent z. For a non-conserved order parameter and short-ranged interactions, to which we shall restrict ourselves throughout this work, one has z = 2 [4,5,6] (For a conserved order parameter, one speaks of phase separation and z takes different values [4,5,6]. Long-range interactions lead to further modifications [5,7,8,9,10,11,12]). Up to metric scale factors, the form of the scaling function F C is generically expected to be universal, meaning it is independent of most of the ‘details’ of the underlying microscopic physics; see [4,13,14,15,16] for reviews. Knowing the form of F C is an important theoretical task and is also of practical importance, as a priori knowledge of F C allows us to make long-time predictions on the basis of short-time data. These expectations (2) are also confirmed experimentally [17,18].
In practical situations, it may be difficult to achieve spatially totally homogeneous samples without any kind of interfaces and/or granular effects. It is therefore of interest to study situations of physical ageing in geometries of finite extent, such as a hyper-cubic form with N d sites. A simple example illustrates a typical kind of finite-size effect (see Figure 1). If one considers the auto-correlation function (please distinguish carefully between the two-time auto-correlator C ( t , s ) , Equation (3a) below, and the time-space correlator C ( t ; r ) , Equation (2)). C ( t , s ) : = C ( t , s ; 0 ) of a phase-ordering (or phase-separating) system, one finds for a spatially infinite system and for sufficiently large times, where t , s τ micro and t s τ micro , that (i) a data collapse occurs and (ii) the characteristic power-law behaviour
C ( t , s ) = F C t s , | 0 | = f C t s , f C ( y ) y 1 y λ / z
for large time ratios y = t / s > 1 . Here, λ is the auto-correlation exponent and is independent of the equilibrium critical exponents. A recent list of estimates of z and λ for phase-ordering systems can be found in [19]. On the other hand, in a fully finite system, even if the auto-correlator is still close to that of the spatially infinite system for not-too-large y, deviations from (3a) will arise (see again Figure 1). Generically, in a finite system, the auto-correlator should first decrease more rapidly as a function of y than it would in the infinite system. For even larger values of y, the auto-correlator saturates at a plateau of height
lim y C ( y s , s ; 0 ; N ) = C ( 2 ) ( s , N )
which, in principle, should depend on the waiting time s and the system size N. Qualitative discussions on this go back a long time (see [20,21]). The systematic study of finite-size effects—by which we mean the consequences of the system being in a restricted spatial volume of linear size N, and the associated finite-size scaling—has a long history indeed, both for equilibrium phase transitions [22,23,24,25] and equilibrium dynamics [26]. Early examples of finite-size studies in non-equilibrium systems include [27,28,29]. Finite-size effects in glassy dynamics are studied theoretically in [30,31,32] and experimentally in [20,21,33,34]. They are also one possible way to artificially create spurious sub-ageing effects [35]). Another early observation of this saturation effect occurs in the Kuramoto model of self-synchronisation [36].
The expected limit behaviour of (3b) can be understood heuristically [19,37]. We recall the argument for quenches to T < T c . For large times, one expects that the auto-correlator in terms of domain sizes ( t ) and ( s ) reads C ( t , s ) ( t ) ( s ) λ (see Equation (3a)). If the observation time t becomes so large that the domain size ( t ) N crosses over into the saturation regime, while the waiting time s is still small enough that the infinite-system rule ( s ) s 1 / z applies (hence ( s ) N ), one would find
C ( 2 ) N λ if s is fixed , C ( 2 ) s λ / z if N is fixed
More formally, (4) is one of the several consequences of the hypothesis of generalised time-translation invariance [38]. Furthermore, one can write generalisations for quenches to all temperatures T T c , for both conserved and non-conserved order parameters, and so on. One interesting aspect of (4) is that it offers a new way to numerically estimate the exponents λ and λ / z , respectively.
The present work strives to obtain a test of (4) in the context of an exactly solvable model. Since there already exists an exact confirmation of (4) in the spherical model for dimensions 2 < d < 4 and T < T c [19], we consider here the case of the 1 D Glauber–Ising model (for a short summary of the rôle of the Ising model in equilibrium phase transitions, discovered by Cagniard de la Tour about 200 years ago, see, e.g., [39] and refs. therein), quenched to temperature T = 0 from a fully disordered initial state (initial correlations are irrelevant at large times in the 1 D Glauber–Ising model [40]) and whose single- and two-time correlators obey the scaling form (2). Tests of (4) in the 2 D Glauber–Ising model quenched to T < T c will be presented elsewhere [37]. We shall be interested in deriving the full size-dependent single-time and two-time spin–spin correlators which will ultimately allow us to perform an explicit test of (4).
This work is organised as follows: In Section 2, we shall introduce the analytic continuation technique and confirm that it reproduces the known exact results. In Section 3, we shall use this technique to compute the finite-size effects in the ageing dynamics and finally confirm (4). Section 4 gives our conclusions. Technical details of the exact solution are given in Appendix A, Appendix B, Appendix C, Appendix D and Appendix E.

2. Critical Relaxations in Infinite-Size Systems

2.1. The 1 D Glauber–Ising Model

The nearest-neighbour Ising model on a chain Λ Z is defined through the hamiltonian
H = n Λ σ n σ n + 1
for the Ising spins σ n = ± 1 and the exchange coupling is normalised to unity. In a heat-bath formulation, at temperature T, at each time step Δ t , a randomly chosen site n Λ is updated according to Glauber dynamics [41] with the rates [42]
σ n ( t ) ± 1 with the probability 1 2 1 ± tanh σ n 1 ( t ) + σ n + 1 ( t ) T
On a discrete chain, the single-time correlator is C n ( t ) : = σ n ( t ) σ 0 ( t ) , where the average is taken over the thermal histories defined by Equation (6). The correlator obeys the equation of motion [41,42,43,44]
t C n ( t ) = 2 C n ( t ) + γ C n 1 ( t ) + C n + 1 ( t ) when n 0 , C 0 ( t ) = 1
with the abbreviation γ = tanh ( 2 / T ) (such that 0 γ 1 ), and where the microscopic rate constant is normalised to unity. An initial condition must still be given; for an initially fully disordered system, one has C n ( 0 ) = δ n , 0 [41,42]. Throughout this work, spatial translation invariance is implicitly admitted. We shall give the periodicity conditions for systems on a lattice of finite size N later. Similarly, with the time difference τ = t s , the two-time correlator is defined as C n ( τ , s ) : = σ n ( t ) σ 0 ( s ) = σ n ( τ + s ) σ 0 ( s ) and obeys the equation of motion [41,42,43,44]
τ C n ( τ , s ) = C n ( τ , s ) + γ 2 C n 1 ( τ , s ) + C n + 1 ( τ , s ) , C n ( 0 , s ) = C n ( s )
Herein, the single-time correlator C n ( s ) serves as initial value. Solving Equations (7) and (8) constitutes the mathematical problem for the determination of the single-time and two-time correlators.

2.2. The Discrete Case

There are many well-known ways [40,41,42,43,44,45,46,47,48,49,50,51,52,53] to solve Equations (7) and (8), using, for example, generating functions [41], free fermions [48], a scaling ansatz [45,50], Laplace transforms [42], grassmannian variables [46], or systems of equations of motion [40,43,44,51,52,53]. Here, we shall adopt a method which easily generalises to finite systems as well.
We begin with the single-time correlator (For a disordered initial condition σ n ( 0 ) = 0 , the site-dependent magnetisation σ n ( t ) = 0 for all times). In principle, one wishes to decouple the equations of motion (7) by a Fourier transform, but because of the boundary condition C 0 ( t ) = 1 , this is not straightforward. Rather, we observe first that the single-time correlator C n ( t ) = σ n ( t ) σ 0 ( t ) = σ 0 ( t ) σ n ( t ) = σ | n | ( t ) σ 0 ( t ) is even in n and does not depend on the sign of n. It is enough to restrict the physical interpretation to positive values of n > 0 . In particular, the equation of motion (7) is needed for n > 0 only. Therefore, we consider that C n ( t ) can be thought of as an entity devoid of physical significance. It can therefore be used for purely calculational, mathematical purposes. We shall define  C n ( t ) in such a way that the equation of motion (7) holds for all values of n Z . To do so, we write down the ansatz
C n ( t ) = α n C n ( t ) ; n 0
and try to choose α n such that the boundary condition C 0 ( t ) = 1 and the equation of motion (7) become valid for all n Z . This kind of analytical continuation will be used several times below (it had already been used in the exact treatment of 1 D coagulation-diffusion processes [54,55,56] to find the single-time and two-time correlation and response functions). It is easy to check that this is indeed possible if the α n obey the (time-independent) recursion relation
α n + 1 = 2 γ α n α n 1 , α 0 = 2 , α 1 = 2 γ
Lemma 1.
The solution of the recursion relation (10) is for all n 0
α n = γ 1 1 γ 2 n + γ 1 + 1 γ 2 n
Proof. 
This is easily checked by induction. For n = 0 and n = 1 , the initial values in (10) are immediately reproduced. Then, it is straightforward to check that (11) obeys indeed the recurrence relation (10). □
It then follows that one has for all n Z the linear equation of motion
t C n ( t ) = 2 C n ( t ) + γ C n 1 ( t ) + C n + 1 ( t )
but now in the absence of any boundary condition. This is the goal we wanted to achieve. The solution of Equation (12) is described in Appendix A. It follows that the physical correlator is
C n ( t ) = σ | n | ( t ) σ 0 ( t ) = η | n | + m = 1 C m ( 0 ) η m e 2 t I | n | m ( 2 γ t ) I | n | + m ( 2 γ t )
where I n ( t ) is a modified Bessel function [57] and
C n , eq = η | n | = 1 1 γ 2 γ | n |
is the equilibrium correlator C n , eq = σ | n | σ 0 eq . This is indeed nothing else than Glauber’s time-honoured result [41] (Equation (63)). For any 0 γ < 1 , it shows the rapid relaxation towards the equilibrium correlator (14) on a finite time-scale τ rel 1 = 2 ( 1 γ ) . Formally, τ rel diverges if γ 1 (or the temperature T 0 ), and ageing is only possible in this latter case (see Section 1).
This whole calculation only has the purpose of showing that the analytical continuation technique used here does reproduce the well-known results in the literature [40,41,42,44,51]. Having verified this, we can now proceed towards the derivation of new results, notably on critical dynamics, with γ = 1 .
For the two-time correlator, it is straightforward to solve (8) by a Fourier transform and then insert the single-time correlator (13). Since this leads to lengthy expressions [51], which are not needed below, we do not carry this out explicitly.

2.3. The Continuum Limit

1. Having seen that ageing can only occur for γ = 1 , we restrict ourselves to this case from now on. The calculations become shorter in the continuum limit (This is valid in the scaling limit of (7) where t , n but n 2 / t is kept fixed. This will always be taken in what follows, where t and x are re-scaled time and space coordinates), where, for the single-time correlator C ( t ; x ) = σ ( t , x ) σ ( t , 0 ) , we have from (7) the equation of motion
t C ( t ; x ) = x 2 C ( t ; x ) , C ( t ; 0 ) = 1
where the diffusion constant was scaled to unity. Since the physical correlator C ( t ; x ) is even in x, we can restrict the problem (15) to the half-line x 0 and use the function C ( t ; x ) for computational purposes. The analytic continuation (9) then simplifies to
C ( t ; x ) = 2 C ( t ; x )
for x 0 . In Appendix B, we show that (with the complementary error function erfc ( x ) [57])
C ( t ; x ) = erfc | x | 2 t 1 / 2 + e x 2 / 4 t π t 0 d x C ( 0 ; x ) e x 2 / 4 t sinh | x | x 2 t
remains for any initial correlations C ( 0 ; x ) . For an initially fully disordered lattice, C ( 0 ; x ) = 0 for x > 0 and the second term in (17) vanishes, as stated countless times in the literature (see e.g., [4,41,42,43,44,45,50] and references therein). In order to further clarify its importance, consider as an example C ( 0 ; x ) = 1 + x 2 / 2 with a positive exponent > 0 . For large times, C ( t ; x ) = T 1 + T 2 , where the contribution of the second term T 2 will be of the order
T 2 e x 2 / 4 t 0 d x t / 2 e x 2 / 4 sinh | x | x 2 t 1 / 2 t / 2 0
when t but where x 2 / t is kept fixed. This is much smaller than the scale-invariant and finite first term T 1 = erfc | x | / 2 t 1 / 2 . We conclude that, in the 1 D Glauber–Ising model at T = 0 , initially decaying correlations are always irrelevant for t . This merely confirms long-standing results for the two-time correlator in this model [40]. Consequently, only the universal first term in (17) is important in the long-time scaling limit and the initial-condition-dependent second term can be discarded. The leading term in (17) might have been found more readily by inserting the scaling ansatz (2) into (15) [45].
Using the notation of (2), and for an initially fully disordered lattice, the scaled correlator C ( t ; x ) = F C ( 1 , | x | / 2 t ) is shown in the right panel of Figure 2 as the full black curve, labelled y = 1.0 , as a function of the scaling variable ξ 2 = x 2 / 2 t . For small arguments, one observes a sharp peak at ξ = 0 . This indicates that the interfaces between domains are sharp, as expected for kinetic Ising models and in agreement with Porod’s law [4,14].
2. In Appendix B, we also compute the characteristic length scale ( t ) t 1 / z from the second moment of C ( t ; x ) and find
2 ( t ) = 0 d x x 2 C ( t ; x ) 0 d x C ( t ; x ) = 4 3 t
which is exact for a fully disordered initial state. Equation (18) confirms the expected [5] dynamical exponent z = 2 . One might use it in (17) to achieve a data collapse C ( t ; x ) = erfc | x | / ( 3 ( t ) ) , up to irrelevant terms.
3. We now turn to the two-time correlator
C ( τ , s ; x ) : = σ ( τ + s , x ) σ ( s , 0 )
For the zero-temperature case γ = 1 , we have from (8) the equation of motion
τ C ( τ , s ; x ) = 1 2 x 2 C ( τ , s ; x ) , C ( 0 , s ; x ) = C ( s ; x ) = erfc | x | 2 s 1 / 2
where, in the initial condition, we merely retain from (17) the most relevant term for large times or use a totally disordered initial state. In what follows, we shall use the scaling variables
y = t s > 1 , ξ 2 = x 2 2 s
for the ratio y of the two times and the re-scaled length ξ . Then, the time difference τ = t s = s ( y 1 ) . From now on, we shall always work in the long-time limit s , with y and ξ being kept fixed. In Appendix B, we show that (20) is solved by
C ( τ , s ; x ) = 1 1 π e x 2 / ( 2 τ ) 2 τ s 1 / 2 Ψ 1 1 , 1 2 ; 3 2 , 1 2 ; τ 2 s , x 2 2 τ
= 1 2 π e ξ 2 / ( y 1 ) y 1 2 1 / 2 Ψ 1 1 , 1 2 ; 3 2 , 1 2 ; y 1 2 , ξ 2 y 1
where Ψ 1 is a Humbert confluent hypergeometric function of two variables [58,59]. In the scaled expression (22b), we observe the independence from the waiting time s. In what follows, with a slight change of notation with respect to (2), we shall write more shortly F C ( y , ξ ) : = C ( τ , s ; x ) in terms of the scaling variables y and ξ , defined above in (21). To the best of our knowledge, previous efforts have concentrated on the two-time auto-correlator C ( τ , s ; 0 ) (When considering the scaling influence of the temperature through γ , the two-time auto-correlator can be expressed via another Humbert function Φ 1 [42]. Taking into account all three scaling variables will likely involve a three-argument Lauricella/Horn hypergeometric series).
To recover the known two-time auto-correlator C ( y s , s ) = F C ( y , 0 ) , we now recall that Ψ 1 ( a , b ; c , c ; x , 0 ) = F 1 2 ( a , b ; c ; x ) reduces to Gauß’ hypergeometric function, which, in turn, is related to the elementary functions in our example [58] (7.3.1.123), [58] (7.3.2.83). This gives
F C ( y , 0 ) = 1 2 π τ s 1 2 τ 2 s 1 2 artanh τ 2 s = 2 π arctan 2 s τ = 2 π arctan 2 y 1
where [57] (4.4.42) was also used. The last two expressions reproduce the well-known [42] (Equation (4.24)), [43] (Equation (17)), as expected. Specifically, for y 1 , one has F C ( y , 0 ) 2 2 π y 1 / 2 , and by comparison with the standard expected asymptotics (3a), one reads off λ z = 1 2 , or, since z = 2 [5], the auto-correlation exponent λ = 1 [40,42,43], as it should be. In the left panel of Figure 2, the auto-correlator is the full black line labelled ξ = 0.0 .
Several mathematical identities, listed in Appendix E, can be used to check the expressions (22) and to extract a few consequences. First, the limit relation given in Lemma A1 allows us to confirm that in the limit τ 0 or y 1 , the expressions (22) indeed reduce to the single-time correlator (17), without, however, the irrelevant and sub-dominant terms coming from the initial conditions. This is illustrated in the left panel of Figure 2, where the curves become more close to the auto-correlator when ξ 0 . Second, the asymptotic relation given in Lemma A2, especially the independence of the two leading terms on the second argument, describes what happens when y = t / s becomes large. In Figure 2, the left panel shows that the asymptotic behaviour is
F C ( y , ξ ) y 1 8 π 1 y 1 / 2 1 + O ( y 1 / 2 )
and that this leading behaviour is universal in the sense that it is independent of the scaled distance ξ 2 = x 2 2 s . This is reproduced from (A35), since the leading term cancels, but the next order does give (24). Third, one may also investigate the leading behaviour of the correlator when ξ becomes large but y is kept fixed. This is shown in the right panel of Figure 2. While the main figure merely displays a rather rapid decay with increasing ξ , the inset shows that the plot of the square root of the logarithm of F C , namely ln F C ( y , ξ ) against ξ , produces an almost straight line as a function of ξ , but with a y-dependent slope. Lemma A3 gives the mathematical justification of this observation and, again, the second term in (A36) establishes that for ξ 1
F C ( y , ξ ) ξ 1 1 2 π y + 1 ξ exp ξ 2 y + 1
The dashed lines in the inset represent these asymptotic predictions for several values of y 1 . Again, if one takes the limit y 1 in (25), one recovers the leading large-distance asymptotics of the single-time correlator erfc ( ξ / 2 ) , as it should be.

3. Critical Relaxations in Finite-Size Systems

Having seen for the infinite system that our technique of analytical continuation, via (9) or (16), reproduces the known results, we shall now apply it to extract the finite-size scaling properties of the ageing dynamics.
1. Consider the Glauber–Ising model on a periodic ring with N sites (see Figure 3). In the continuum limit, the equation of motion for the single-time correlator is now
t C ( t ; x ) = x 2 C ( t ; x ) , C ( t ; 0 ) = C ( t ; N ) = 1
The first of these boundary conditions will be treated as before by analytic continuation. For the second one, in the case of periodic boundary conditions, we expect to have
C ( t ; x ) = C ( t ; N x , C ( t ; x ) = 2 C ( t ; x )
The first of these is an inversion relation, as suggested by Figure 3. Both together analytically continue C ( t ; x ) from the physical region x [ 0 , N ] towards x R , via (27). Together, they imply the periodicity relation
C t ; 2 N + x = C t ; N ( N x ) = C t ; N x = 2 C t ; N + x = 2 C t ; N ( x ) = 2 C t ; x = C t ; x
where, in the first line, we used the inversion condition (27). In the second line, we applied the second continuation condition (27) and then the inversion once more. Finally, a last application of the second condition (27) brought us to the end result in the third line.
Consequently, while the physical correlator is obtained for values 0 x N , the analytically continued function C ( t ; x ) is a function of period 2 N in x, but only half of it has a physical meaning. We therefore have the Fourier representation
C ( t ; x ) = k = C ˜ ( t ; k ) e i π k x N , C ˜ ( t ; k ) = 1 2 N N N d x C ( t ; x ) e i π k x N
Because of the periodicity condition (28), we specifically have
C ( t ; N ) = C ( t ; N ) , x C ( t ; N ) = x C ( t ; N )
which are, of course, compatible with the required boundary conditions in (26).
In this way, the boundary conditions are taken into account, such that the analytically continued function C ( t ; x ) is a periodic solution of period 2 N , of the simple diffusion equation t C ( t ; x ) = x 2 C ( t ; x ) . In Appendix C, we show that for | x | N , the physical correlator can be expressed in terms of a Jacobi theta function ϑ 3 ( z , q )
C ( t ; x ) = 1 2 N 0 N d x 2 ϑ 3 π 2 | x | + x N , e π 2 t / N 2 + C ( 0 ; x ) ϑ 3 π 2 | x | x N , e π 2 t / N 2 ϑ 3 π 2 | x | + x N , e π 2 t / N 2
and that the required periodicity properties (27) are indeed satisfied, if they only hold for the initial correlator C ( 0 ; x ) . The term depending on the initial conditions C ( 0 ; x ) should be irrelevant. Then, or for a fully disordered initial state, one may alternatively re-write the physical single-time correlator (2) as
C ( t ; x ) = F C 1 , | x | 2 t = 0 1 d u ϑ 3 π 2 u + π 2 | x | N , e π 2 t / N 2 = 1 2 π 0 | x | / N d v ϑ 2 π v , e 4 π 2 t / N 2
where ϑ 2 , 3 are distinct Jacobi theta functions [57]. The expressions (32) give finite-size scaling expressions for the single-time correlator in terms of the finite-size scaling variables x / N and t / N 2 .
In Figure 4a, we show the analytically continued function C ( t ; x ) as computed in Appendix C. By construction, for t > 0 , it is an analytic function of x and periodic with period 2 N , but it only has a physical meaning in the interval 0 x N . That function is quite distinct from the physical scaling function F C ( 1 , ξ ) of the single-time correlator (2), with the scaling variables (21), which is shown in Figure 4b on the same scale. It becomes periodic in x with period N, as expected intuitively for a periodic lattice of N sites, but its derivative has jumps at x = n N with n Z . For N , it converges towards the infinite-size correlator; however, at | x | = N 2 , it has a minimum value which converges exponentially to zero as N . For a fully disordered initial state, the correlator is non-vanishing only at x = n N .
2. A finite-size generalisation of the second moment can be given as follows
2 ( t ) = 0 N d x 8 N π sin π x N 2 C ( t ; x ) 0 N d x C ( t ; x ) = 2 N 2 π 2 1 1 2 π 0 1 d w sin ( 2 π w ) ϑ 3 π 2 w , q 0 1 d w w ϑ 3 π 2 w , q = 2 π 2 N 2 if t N 2 4 3 t if t N 2
with the only variable q = e π π t / N 2 (see Appendix C for details). This reproduces the infinite lattice result (18) and has the expected finite-size scaling form 2 ( t ) = N 2 F t N 2 . Deep into the finite-size saturation regime, one has ( t ) 0.45 N .
3. The critical two-time correlator C ( τ , s ; x ) satisfies the equation of motion
τ C ( τ , s ; x ) = 1 2 x 2 C ( τ , s ; x ) , C ( 0 , s ; x ) = C ( s ; x )
with the single-time correlator, restricted to the relevant term, from (32). In Appendix D, we show that
C ( τ , s ; x ) = 1 2 0 1 d v d u ϑ 3 π 2 ( v + u ) , e π 2 N 2 s ϑ 3 π 2 | x | N π 2 v , e π 2 N 2 τ 2 + ϑ 3 π 2 | x | N + π 2 v , e π 2 N 2 τ 2
and hence, the auto-correlator becomes
C ( τ , s ; 0 ) = 0 1 d v 0 1 d u ϑ 3 π 2 ( v + u ) , e π 2 N 2 s ϑ 3 π 2 v , e y 1 2 π 2 N 2 s
which only depends on the finite-size scaling variables s / N 2 and τ / N 2 = s N 2 ( y 1 ) .
In Figure 5a, the scaled two-time auto-correlator C ( y s , s ) = F C ( y , 0 ) given in (36) is shown for several values of N and s = 5 fixed. Analogous with the generic expectation formulated in Section 1, we find a cross-over to a plateau when y 1 , with its height C ( 2 ) decreasing as N increases for fixed s. However, in the 1 D Glauber–Ising model, the cross-over towards to the plateau occurs directly, and we do not initially see the more rapid decay observed in the spherical model in 2 < d < 4 dimensions and T < T c [19] or in the 2 D Glauber–Ising model at T < T c [37] (see Figure 1). From the heuristics of Section 1, this plateau should be found when the observation time t N 2 is deeply into the finite-size regime, but the waiting time s is not, thus s N 2 . When we apply this to the auto-correlator (36) and let y 1 , the second theta function should converge rapidly towards unity, whereas the evaluation of the first one requires us to take many terms of the defining series [57] into account. This is treated by using the modular identity (A23), such that the auto-correlator becomes, in the plateau region
C ( τ , s ; 0 ) y 1 0 1 d v 0 1 d u 1 π N s e ( u + v ) 2 N 2 / 4 s ϑ 3 i u + v 2 N 2 s , e N 2 / s 1 + = 1 π N s N s 2 0 N / s d α 0 N / s d β e ( α + β ) 2 / 4 ϑ 3 i α + β 2 N s , e N 2 / s N s 1 π s 1 / 2 N 0 d α 0 d β e ( α + β ) 2 / 4 2 + = 4 π s 1 / 2 N
where we changed the integration variables and then see that, in the theta function ϑ 3 , only the leading terms are not strongly suppressed for N 2 s . Because of the exponential suppression in the integrand, the integration limits can be extended to infinity without significantly changing the value of the integral, which rapidly converges to 2. Then, we have the finite-size plateau height, for s N 2
C ( 2 ) = lim y C s ( y 1 ) , s ; 0 ; N = 4 π s 1 / 2 N
Given that we have previously seen that z = 2 and λ = 1 , we confirm the generic expectations (4). That was the main aim of this work. Both scaling laws quoted in (4) are tested in Figure 5, respectively. Figure 5a shows that C ( 2 ) decreases with N while Figure 5b shows that C ( 2 ) increases with s, as long as s N 2 . Figure 5 also serves as an illustration that the asymptotic form (38) already holds to good approximation for relatively small values of s and N. After the kinetic spherical model [19], this is only the second exactly solvable example where this kind of test was carried out exactly.

4. Conclusions

We evaluated the scaled single-time and two-time correlators in the 1 D Glauber–Ising model, quenched to T = 0 , on a finite-size and periodic chain. This allows us to check for the validity of the generically expected finite-size scaling forms [26] and, in particular, to confirm the novel expectation (4) of the plateau height C ( 2 ) . Both scaling laws quoted in (4) are exemplified in Figure 5a and Figure 5b, respectively. We notice that the precise form of the finite-size auto-correlator of the 1 D Glauber–Ising model, as shown in Figure 5, does not reproduce all of the generic expectations in coarsening systems, as schematised in Figure 1.
In view of the general derivation [38], we expect the result (4) to hold in general, but further tests, including non-exactly-solvable models, are welcome. One forthcoming case is the detailed test of (4) in the 2 D Glauber–Ising model at T < T c [37]. Since the exact solution of the 1 D Glauber–Ising model is restricted to nearest-neighbour interactions, any tests of (4) in the currently intensively studied long-range coarsening [7,8,9,10,11,60,61,62,63,64,65,66,67,68,69,70] or phase-separating Ising models [12] will require numerical studies. Here, it might also be of interest to study non-integrable generalisations of Glauber dynamics (6), for example, by combining non-conserved Glauber-type dynamics with conserved Kawasaki-type dynamics at a different temperature, which no longer satisfies detailed balance [47]. At the least, the use of (4) gives a different computational tool for the determination of λ and λ / z , although it still has to be seen how precise a numerical technique it will turn out to be.
In addition, there is not yet any test of the generalisation of (4) [38] for quenches onto T = T c . Furthermore, eventual extensions to quantum systems have not yet been tried.

Funding

This work was supported by the French ANR-PRME UNIOPEN (ANR-22-CE30-0004-01).

Data Availability Statement

The data that support the findings of this study are available from the corresponding author(s) upon reasonable request.

Acknowledgments

It is a pleasure to thank D. Warkotsch, W. Janke, and P.-C. Hang for their interesting discussions and correspondence.

Conflicts of Interest

The author declare no conflicts of interest.

Appendix A. Analytical Derivations: Discrete Case

For the infinite system, on the discrete chain, the analytically continued single-time correlator C n ( t ) obeys, for all n Z , the equation of motion
t C n ( t ) = 2 C n ( t ) + γ C n 1 ( t ) + C n + 1 ( t )
and without any boundary condition. Equation (A1) is solved by a standard Fourier transform, namely
C ˜ ( t , k ) = n Z e i k n C n ( t ) , C n ( t ) = 1 2 π π π d k e + i k n C ˜ ( t , k )
In Fourier space, we have
t C ˜ ( t , k ) = 2 1 γ cos k C ˜ ( t , k ) C ˜ ( t , k ) = C ˜ ( 0 , k ) e 2 ( 1 γ cos k ) t
This can be re-expressed in direct space, but now we must remember from (9) that the initial conditions C n ( 0 ) = α n C n ( 0 ) for the ‘negative’ position must be specified in terms of the physical initial correlators C n ( 0 ) with n > 0 . This gives
C n ( t ) = 1 2 π π π d k e i k n C ˜ ( 0 , k ) e 2 ( 1 γ cos k ) t       = m Z C m ( 0 ) e 2 t I n m ( 2 γ t )       = m 0 C m ( 0 ) e 2 t I n m ( 2 γ t ) + m > 0 C m ( 0 ) e 2 t I n + m ( 2 γ t )       = e 2 t I n ( 2 γ t ) + m > 0 C m ( 0 ) e 2 t I n m ( 2 γ t )             + m > 0 γ 1 + 1 γ 2 m + γ 1 + 1 γ 2 m e 2 t I n + m ( 2 γ t ) C m ( 0 ) e 2 t I n + m ( 2 γ t )       = e 2 t I n ( 2 γ t ) + m > 0 C m ( 0 ) e 2 t I n m ( 2 γ t ) I n + m ( 2 γ t )
+ m > 0 γ 1 + 1 γ 2 m + γ 1 + 1 γ 2 m e 2 t I n + m ( 2 γ t )
where, in the second line, we used the integral representation of the modified Bessel function I n ( t ) [57]. In the forth line, we re-used the ansatz (9), along with (11), for the initial condition at t = 0 . In particular, the critical zero-temperature case γ = 1 reproduces [40] (Equation (2.9)).
Sometimes, it is advantageous to reformulate this result with respect to stationary (or equilibrium) properties. Making the ansatz C n , st = η n , the equilibrium constant η is found from the stationarity condition t C n , st = 0 in (A1). This gives the condition [41] η 2 2 γ η + 1 = 0 . It has the two solutions η ± = 1 γ 1 ± 1 γ 2 which are related by η + η = 1 . Clearly, the stationary (equilibrium only for n > 0 ) correlator is then
C n , st = η n = 1 1 γ 2 γ n
Because of the identity, derived from [57] (9.6.33)
S : = e 2 t m Z η m I n m ( 2 γ t ) = e 2 t m Z η m n + n I n m ( 2 γ t ) = e 2 t η n e 1 2 2 γ t η 1 + η = η n
(since η 1 + η = η + η + = 2 γ ) one may re-write the single-time correlator as follows, starting again at (A4)
C n ( t ) = m Z C m ( 0 ) η m + η m e 2 t I n m ( 2 γ t ) = η n + m Z C m ( 0 ) η m e 2 t I n m ( 2 γ t ) = η n + C 0 ( t ) η 0 = 0 e 2 t I n ( 2 γ t ) + m = 1 C m ( 0 ) η m e 2 t I n m ( 2 γ t ) I n + m ( 2 γ t )
where we also used C m ( 0 ) η m = C m ( 0 ) α m + α m η m = ( 1 ) C m ( 0 ) η m because α m = α m from the Lemma in Section 2. The physical validity is restricted to non-negative values of n because of (9). Then, we obtain the result quoted in (13) in the text.

Appendix B. Analytical Derivations: Continuum Limit

The calculations for the infinite system in the continuum limit are described below.
1. With the analytic continuation (15), the equation of motion of the single-time correlator has become the simple diffusion equation t C ( t ; x ) = x 2 C ( t ; x ) . It is solved by using the Fourier representation C ( t ; x ) = 1 2 π R d k e i k x C ˜ ( t ; k ) , which gives
t C ˜ ( t ; k ) = k 2 C ˜ ( t ; k ) C ˜ ( t ; k ) = C ˜ ( 0 ; k ) e k 2 t
This is re-expressed in direct space via
C ( t ; x ) = 1 2 π R d y C ( 0 ; y ) R d k e i k ( x y ) k 2 t = 1 4 π t d y C ( 0 ; y ) e ( x y ) 2 / ( 4 t ) = 1 4 π t 0 d y C ( 0 ; y ) e ( x y ) 2 / ( 4 t ) + 0 d y C ( 0 ; y ) e ( x + y ) 2 / ( 4 t ) = erfc x 2 t 1 / 2 + exp x 2 4 t π t 0 d y C ( 0 ; y ) e y 2 / ( 4 t ) sinh x y 2 t
where, in the first line, we use the solution (A9) in Fourier space. In the second line, we carry out the k-integration. In third line, we insert the analytical continuation (15) and then compute the remaining integrals using the definition of the complementary error function erfc ( x ) [57]. From this, the physical correlator is retrieved by restricting to positive values of x. This gives (17) in the text (this might as well have been derived from (A8) or (A5) by the asymptotic expansion [57] of the modified Bessel function I n ( t ) ).
2. A characteristic length scale ( t ) is found as a second moment of C ( t ; x ) as follows
2 ( t ) = 0 d x x 2 C ( t ; x ) 0 d x C ( t ; x ) = 4 t 0 d x x 2 erfc ( x ) 0 d x erfc ( x ) = 4 3 t
for a completely disordered initial state. Herein, the integrals are computed with the help of the identities [57] (7.2.7) and [57] (7.2.14). This is (18) in Section 2.
3. The equation of motion of the two-point correlator C ( τ , s ; x ) = σ ( τ + s , x ) σ ( s , 0 ) is again the simple diffusion Equation (20). In Fourier space, this means C ˜ ( τ , s ; k ) = C ˜ ( 0 , s ; k ) exp 1 2 k 2 τ . From the single-time correlator (17), we only retain the most relevant term (or restrict to a disordered initial state), which gives
C ( τ , s ; x ) = 1 2 π R d y erfc | y | 2 s 1 / 2 R d k e i k ( x y ) 1 2 τ k 2       = 1 2 π τ R d y erfc | y | 2 s 1 / 2 e ( x y ) 2 / ( 2 τ )       = exp x 2 2 τ 2 π τ 0 d y erfc y 2 s 1 / 2 e y 2 / ( 2 τ ) + x y / τ + 0 d y erfc y 2 s 1 / 2 e y 2 / ( 2 τ ) x y / τ       = 2 exp x 2 2 τ 2 π τ 0 d y 1 erf y 2 s 1 / 2 e y 2 / ( 2 τ ) cosh x y τ
where, in the second line, the k-integration was carried out. In the third line, the contributions of positive and negative y are separated. These are then re-united in a cosh-function in the forth line. The second of the integrals in the forth line is carried out with the help of the identity [71] (2.8.6.5)
0 d x e b x 2 cosh ( p x ) erf ( c x ) = c π b Ψ 1 1 , 1 2 ; 3 2 , 1 2 ; c 2 b , p 2 4 b
involving the Humbert function Ψ 1 (see Appendix E), which can be proven by series expansion of the cosh- and erf -functions [57] and by subsequent term-wise integration. The first integral in (A12) is elementary (see e.g., [72]) (2.4.15.2). Combining all this, we arrive at (22) in the text.

Appendix C. Finite-Size Single-Time Correlator

In order to find the finite-size single-time correlator C ( t ; x ) , we need the Fourier-transformed equation of motion. From the Fourier representation (29), we have
t C ˜ ( t ; k ) = 1 2 N N N d x t C ( t ; x ) e i π k x / N = 1 2 N N N d x x 2 C ( t ; x ) e i π k x / N
This is evaluated by repeated partial integrations and taking the periodicity conditions (30) into account
t C ˜ ( t ; k ) = 1 2 N e i π k x C ( t ; N ) e i π k x C ( t ; N ) = 2 i sin ( π k ) x C ( t ; N ) = 0 + i π k N N N d x e i π k x N x C ( t ; x ) = i π k 2 N 2 e i π k C ( t ; N ) e i π k C ( t ; N ) = 2 i sin ( π k ) C ( t ; N ) = 0 π 2 k 2 2 N 3 N N d x e i π k x N C ( t ; x ) = π k N 2 C ˜ ( t ; k )
where, in the first and second lines, the periodicity conditions (30) were used and the boundary terms vanish since k Z . The obvious solution
C ˜ ( t ; k ) = C ˜ ( 0 ; k ) exp π k N 2 t
is readily transformed back into real space, with the help of (16)
C ( t ; x ) = k = C ˜ ( 0 ; k ) exp π 2 k 2 t N 2 + i π k x N = 1 2 N N N d y C ( 0 ; y ) k = exp π 2 k 2 t N 2 + i π k x y N = ϑ 3 π 2 x y N , e π 2 t / N 2 = 1 2 N 0 N d y C ( 0 ; y ) ϑ 3 π 2 x y N , e π 2 t / N 2 + C ( 0 ; y ) ϑ 3 π 2 x + y N , e π 2 t / N 2 = 1 2 N 0 N d y 2 ϑ 3 π 2 x + y N , e π 2 t / N 2 + C ( 0 ; y ) ϑ 3 π 2 x y N , e π 2 t / N 2 ϑ 3 π 2 x + y N , e π 2 t / N 2
where ϑ 3 ( z , q ) is a Jacobi theta function [57] (16.27.4). In view of what was said in Section 2 about the infinite-size system, we expect that the second line in (A17) is negligible for times t 1 if only C ( 0 ; x ) 0 decreases with x (see Figure 4a for an illustration).
A convenient reformulation of this result applies the following identities, namely
1 N 0 N d y ϑ 3 π x + y 2 N , e π 2 t / N 2 = 1 N 0 N d y k = exp π 2 k 2 t N 2 + i π k x + y N = 1 + 2 π k = 1 e π 2 k 2 t / N 2 1 k sin π k x N N sin π k x N = 1 + 2 π k = 1 e π 2 k 2 t / N 2 1 k sin π k x N ( 1 ) k 1 = 1 4 π k = 0 e π 2 ( 2 k + 1 ) 2 t / N 2 1 2 k + 1 sin π ( 2 k + 1 ) x N = 1 2 π N k = 0 e π 2 ( 2 k + 1 ) 2 t / N 2 0 x d x cos π ( 2 k + 1 ) x N
= 1 2 π 0 x / N d v ϑ 2 π v , e 2 π N 2 t
where the auxiliary integration over y is carried out first. Then, we see that only the odd values of k contribute before comparing with the other Jacobi theta function ϑ 2 ( z , q ) [57] (16.27.2); and then
1 2 N 0 N d y C ( 0 ; y ) ϑ 3 π x y 2 N , e π 2 t / N 2 ϑ 3 π x + y 2 N , e π 2 t / N 2 = 1 2 N 0 N d y C ( 0 ; y ) k Z e π 2 k 2 t / N 2 e i π k ( x y ) / N e i π k ( x y ) / N = 1 N k = 1 e π 2 k 2 t / N 2 0 N d y C ( 0 ; y ) cos π k x y N cos π k x + y N = 2 N k = 1 e π 2 k 2 t / N 2 sin π k x N 0 N d y C ( 0 ; y ) sin π k y N
which follows from trigonometric addition theorems. Using these identities in (A17), we find
C ( t ; x ) = 1 4 π k = 0 e π 2 ( 2 k + 1 ) 2 t / N 2 2 k + 1 sin π ( 2 k + 1 ) x N + 2 N k = 1 e π 2 k 2 t / N 2 sin π k x N 0 N d y C ( 0 ; y ) sin π k y N
for any initial correlator C ( 0 ; x ) . Together, this gives (32) in the text. Clearly, these representations are periodic in x, with period 2 N . In addition, we also have from (A21) that
C ( t ; N x ) = 1 4 π k = 0 e π 2 ( 2 k + 1 ) 2 t / N 2 2 k + 1 sin π ( 2 k + 1 ) ( N x ) N + 2 N k = 1 e π 2 k 2 t / N 2 sin π k ( N x ) N 0 N d y C ( 0 ; y ) sin π k y N = 1 4 π k = 0 e π 2 ( 2 k + 1 ) 2 t / N 2 2 k + 1 cos π ( 2 k + 1 ) sin π ( 2 k + 1 ) ( x ) N + 2 N k = 1 e π 2 k 2 t / N 2 cos π k sin π k ( x ) N 0 N d y C ( 0 ; N y ) sin π k ( N y ) N = 1 4 π k = 0 e π 2 ( 2 k + 1 ) 2 t / N 2 2 k + 1 1 2 sin π ( 2 k + 1 ) x N + 2 N k = 1 e π 2 k 2 t / N 2 ( 1 ) k 2 1 2 sin π k x N 0 N d y C ( 0 ; y ) sin π k y N = C ( t ; x )
which proves the required inversion relation. In this, we changed the integration variable in the second line, applied the trigonometric addition theorem, and used the inversion relation C ( 0 ; N x ) = C ( 0 ; x ) for the initial configuration in the third line.
Finally, the Jacobi theta function ϑ 3 π 2 u , q = ϑ 3 π 2 ( 2 u ) , q obeys the following modular transformation identity, which is shown via Poisson’s resummation formula [73]
ϑ 3 π u , e π t = t 1 / 2 exp π u 2 t ϑ 3 i π u t , e π / t
For the proof of (33), we need a few preparations. First, with the change of variables w = u + v and w = u v and f ( u , v ) = g ( w , w ) , the square domain of integration [ 0 , 1 ] 2 is decomposed into two triangles, giving us
0 1 d u 0 1 d v f ( u , v ) = 1 2 0 1 d w w w d w g ( w , w ) + 1 2 1 2 d w ( 2 w ) 2 w d w g ( w , w ) = 1 2 0 1 d w w w d w g ( w , w ) + g ( 2 w , w )
Then, with (A17) for a disordered initial state, we have q = e π π t / N 2 and the properties of ϑ 3
1 N 0 N d x C ( t ; x ) = 0 1 d v 0 1 d u ϑ 3 π 2 ( v + u ) , q     = 1 2 0 1 d w w w d w ϑ 3 π 2 w , q + ϑ 3 π 2 ( 2 w ) , q = 2 0 1 d w w ϑ 3 π 2 w , q
and, again using (A24)
1 N 0 N d x N π sin ( π x N ) 2 C ( t ; x ) = N 2 π 2 0 1 d v 0 1 d u sin 2 ( π v ) ϑ 3 π 2 ( v + u ) , q     = N 2 4 π 2 0 1 d w ϑ 3 π 2 w , q w w d w 1 cos ( π ( w w )     = N 2 4 π 2 0 1 d w ϑ 3 π 2 w , q 2 w 1 π sin 2 π w
The quotient of these gives the integral form for ( t ) in (18). Deep into the finite-size regime, one has t N 2 , so that ϑ 3 1 . This establishes the first asymptotic form. For the second one, we use the modular identity (A23) and find
2 ( t ) = 2 N 2 π 2 1 1 2 π 0 1 d w sin ( 2 π w ) e N 2 w 2 / t ϑ 3 i π N 2 w / ( 2 t ) , e N 2 / t 0 1 d w w e N 2 w 2 / t ϑ 3 i π N 2 w / ( 2 t ) , e N 2 / t
For early times and large systems, t N 2 such that now e N 2 / t 0 and again ϑ 3 1 . Then
2 ( t ) 2 N 2 π 2 1 0 1 d w sin ( 2 π w ) e N 2 w 2 / t 1 + 0 1 d w 2 π w e N 2 w 2 / t 1 + 2 N 2 π 2 1 1 + 0 1 d z 4 π 2 6 z e N 2 z / t 0 1 d z e N 2 z / t 1 + o ( t N 2 ) 4 3 t 1 + o ( t N 2 )
reproduces (18), as claimed.

Appendix D. Finite-Size Two-Time Correlator

As a first step, we must derive the Fourier-transformed equation of motion (34). Because of the periodicity (30) of the single-time correlator C ( 0 , s ; x ) = C ( s ; x ) , one can integrate forward in time to establish that
C ( τ , s ; N ) = C ( τ , s ; N ) , x C ( τ , s ; N ) = x C ( τ , s ; N )
and the analytically continued two-time correlator is a periodic function in x of period 2 N . With the Fourier representation (29), we immediately repeat the steps of Appendix C to arrive at the equation
τ C ˜ ( τ , s ; k ) = 1 2 π k N 2 C ˜ ( τ , s ; k )
The obvious solution is then re-transformed into direct space, in analogy with (A12) in Appendix B
C ( τ , s ; x ) = k = C ˜ ( 0 , s ; k ) e 1 2 π k N 2 τ     = 1 2 N k = 0 N d y C ( 0 , s ; y ) e i π k ( x y ) / N + e i π k ( x + y ) / N e 1 2 π k N 2 τ     = 1 2 N 0 N d y 0 1 d u ϑ 3 π 2 y N + π 2 u , e π 2 s / N 2 ×           × ϑ 3 π 2 x y N , e 1 2 π 2 N τ + ϑ 3 π 2 x + y N , e 1 2 π 2 N τ     = 1 2 0 1 d v 0 1 d u ϑ 3 π 2 ( v + u ) , e π 2 s N 2 ϑ 3 π 2 x N π 2 v , e π 2 N 2 τ 2 + ϑ 3 π 2 x N + π 2 v , e π 2 N 2 τ 2
which is (35) in Section 3. Herein, we used the solution of the equation of motion (A30) in the second line, inserted the relevant part of the single-time correlator (A17) in the third line, and then re-scaled the integration variable. Repeating the argument from Appendix C, we also have C ( τ , s ; N x ) = C ( τ , s ; x ) .

Appendix E. On Humbert Function Identities

The Humbert function Ψ 1 is defined [59,74,75,76] in terms of a power series (converging for | x | < 1 and | y | < ), to which we add a useful integral representation [77] for the analytical continuation to all negative arguments
Ψ 1 ( a , b ; c , c ; x , y ) = n = 0 m = 0 ( a ) n + m ( b ) n ( c ) n ( c ) m x n n ! y m m !
= 1 Γ ( a ) 0 d u e u u a 1 F 1 1 ( b ; c ; x u ) F 1 0 ( c ; y u )
with the Pochhammer symbol ( a ) n and the generalised hypergeometric functions F 1 1 and F 1 0 [58]. In view of (22), several asymptotic identities on the Humbert function Ψ 1 1 , 1 2 ; 3 2 , 1 2 ; x , y are stated, which are needed in the text. These asymptotic relations are special cases of more general theorems proven in [78]. In the following results, it is important that the second argument is always positive.
Lemma A1.
One has the identity, where ξ > 0 is kept fixed
lim z 0 + e ξ 2 / 2 z z 1 / 2 Ψ 1 1 , 1 2 ; 3 2 , 1 2 ; z , ξ 2 2 z = π 2 erf ( ξ / 2 )
This Lemma mathematically expresses the reduction from the two-time correlator to the single-time one, in the equal-time limit τ = t s 0 .
Proof. 
This straightforward calculation starts from the integral representation (A32b). Then
Ψ 1 1 , 1 2 ; 3 2 , 1 2 ; z , y 2 z = 0 d u e u F 1 1 1 2 ; 3 2 ; z u F 1 0 1 2 ; y 2 z u     = 1 z 0 d v e v / z F 1 1 1 2 ; 3 2 ; v cosh 2 y 2 z 2 v     = 1 z 0 d w w F 1 1 1 2 ; 3 2 ; w 2 e 1 z [ ( w y ) 2 y 2 ] + e 1 z [ ( w + y ) 2 y 2 ]
where, in the second line, we used the identity [58] (7.13.1.5) and tacitly admit y > 0 . When z 0 + , the first term will have its main contribution from w y > 0 and the second one from w y < 0 , but this will be out of the integration domain. We can then write
e y 2 / z z 1 / 2 Ψ 1 1 , 1 2 ; 3 2 , 1 2 ; z , y 2 2 z = 0 d w w F 1 1 1 2 ; 3 2 ; w 2 π π z e 1 z ( w y ) 2 + e 1 z ( w + y ) 2
For z 0 + , we recognise that the first term in the bracket will give a representation of the Dirac delta function
δ ( w ) = lim z 0 + 1 π z e w 2 / z
so that we finally have
lim z 0 + e y 2 / z z 1 2 Ψ 1 1 , 1 2 ; 3 2 , 1 2 ; z , y 2 z = 0 d w w F 1 1 1 2 ; 3 2 ; w 2 π δ ( w y ) + δ ( w + y ) = π y F 1 1 1 2 ; 3 2 ; y 2 = π 2 erf ( y )
where, in the last step, the identities [58] (7.11.3.1) and [57] (6.5.17) were used. □
Lemma A2.
[78] (Theorem 3.6) In the limit where x + and y R is kept fixed, one has
Ψ 1 1 , 1 2 ; 3 2 , 1 2 ; x , y 2 x π 2 1 x 1 / 2 1 x + y 2 x 3 / 2 + 1 3 1 x 2 +
The two leading terms do not depend on y. This is needed for deriving (24).
Lemma A3.
In the limit where y and x > 0 is kept fixed, to leading order in 1 / y , one has
Ψ 1 1 , 1 2 ; 3 2 , 1 2 ; x , y 2 x π 2 1 x 1 / 2 e y 2 / x π 2 1 y 1 + x x 1 / 2 e y 2 / [ ( 1 + x ) x ]
We notice the presence of two distinct exponential terms, both of which are needed in the text, for the derivation of (25).
  • Heuristic argument. We start from the integral representation (A32b) [77]. It turns out that the contributions of interest to us come from the upper limit of the integration, whereas the lower limit merely contributes terms of algebraic size, which can be discarded. Therefore, we may split the relevant integral 0 = 0 η x / y 2 + η x / y 2 , where η is some constant to be fixed later. We concentrate on the second term, which reads
T 2 ( η ) = 1 Γ ( a ) η x / y 2 d u e u u a 1 F 1 1 ( b ; c ; x u ) F 1 0 ( c ; y 2 u / x ) = 2 Γ ( c ) Γ ( a ) y 1 c x c / 2 1 / 2 ( η x ) 1 / 2 / y d w e w 2 w 2 a c F 1 1 ( b ; c ; x w 2 ) I c 1 2 y x 1 / 2 w
where [58] (7.13.1.1) was used. Since y will be large, we need the large-argument expansions of F 1 1 and I c 1 , Equations (13.5.1) and (9.7.1) of [57], of which we shall only write the first term, respectively. Formally,
T 2 ( η ) 2 Γ ( c ) Γ ( a ) y 1 c x c / 2 1 / 2 ( η x ) 1 / 2 / y d w e w 2 w 2 a c × × Γ ( c ) Γ ( c b ) x w 2 b 1 + + Γ ( c ) Γ ( b ) e x w 2 x w 2 b c 1 + · exp 2 y x 1 / 2 w 2 π · 2 y x 1 / 2 w 1 + Γ ( c ) Γ ( c ) Γ ( a ) Γ ( c b ) y 1 / 2 c x c / 2 b 1 / 4 0 d w w 2 a 2 b c 1 / 2 e [ ( w y x 1 / 2 ) 2 y 2 / x ] y π + Γ ( c ) Γ ( c ) Γ ( a ) Γ ( b ) y 1 / 2 c x b c + c / 2 1 / 4 0 d w w 2 a + 2 b 2 c c 1 / 2 × × exp 1 + x ) 1 / 2 w y [ ( 1 + x ) x ] 1 / 2 2 y 2 ( 1 + x ) x y π e i π ( b c ) = Γ ( c ) Γ ( c ) Γ ( a ) Γ ( c b ) y 1 / 2 c x c / 2 b 1 / 4 0 d v y 2 a 2 b c + 1 / 2 v 2 a 2 b c 1 / 2 e y 2 v x 1 / 2 2 δ ( v x 1 / 2 ) π / y e y 2 / x y π + Γ ( c ) Γ ( c ) Γ ( a ) Γ ( b ) y 1 / 2 c x b c + c / 2 1 / 4 0 d v y 2 a + 2 b 2 c c + 1 / 2 v 2 a + 2 b 2 c c 1 / 2 × × ( 1 + x ) 1 / 4 a b + c + c / 2 e y 2 v [ ( 1 + x ) x ] 1 / 2 2 δ ( v [ ( 1 + x ) x ] 1 / 2 ) π / y e y 2 / [ ( 1 + x ) x ] y π e i π ( b c ) Γ ( c ) Γ ( c ) Γ ( a ) Γ ( c b ) e y 2 / x y 2 x a b c x b + Γ ( c ) Γ ( c ) Γ ( a ) Γ ( b ) e y 2 / [ ( 1 + x ) x ] y 2 x a + b c c x b c ( 1 + x ) 2 a 2 b + 2 c + c + 1 / 2
and specialising to a = 1 , b = 1 2 , c = 3 2 and c = 1 2 gives the assertion. In the second line, the integrals were extended down to zero, admissible for y 1 . In the third line, after a change of variables, we recognise the Dirac delta function (A34) for y 1 .
This is merely a heuristic argument. In principle, both terms in (A36) should be the first ones of an asymptotic series. It remains an open mathematical problem why there should be no such series associated with the first term. Mathematically, (A36) remains a conjecture.
For completeness, we add the following. It is well-known [75] (Theorem 3.6), [76] (Theorem 3.4 and 3.6) that if x > 0 and y > 0 are fixed constants, and with the necessary conditions on a , b , c , c , one has
lim t e t y t 2 b + c a Ψ 1 ( a , b ; c , c ; t x , t y ) = Γ ( c ) Γ ( c ) Γ ( a ) Γ ( c b ) y x b y a 2 b c
This result also leads to the kind of singularity of Ψ 1 when x 1 from the left, namely
Lemma A4.
If y > 0 and with the necessary conditions on a , b , c , c , we have
lim x 1 e y / ( 1 x ) ( 1 x ) 2 a + 2 b 2 c c Ψ 1 ( a , b ; c , c ; x , y ) = Γ ( c ) Γ ( c ) Γ ( a ) Γ ( b ) y a + b c c
Proof. 
For x < 1 , this is based on the Kummer-type relation [76] (2.8)
Ψ 1 ( a , b ; c , c ; x , y ) = ( 1 x ) a Ψ 1 a , c b ; c , c ; x 1 x , y 1 x
In view of (A39), we define a new variable t and observe that when x 1 from the left
t : = 1 1 x , x 1 x = t 1 1 t = t 1
so that we can write, with y > 0 being kept fixed,
lim x 1 e y / ( 1 x ) ( 1 x ) 2 a 2 ( c b ) c Ψ 1 ( a , b ; c , c ; x , + y ) = lim t e t y t 2 ( c b ) + c a Ψ 1 ( a , c b ; c , c ; t , + t y )
Using (*), we recast (A37) into the form presently required. □
As an example, as x 1 and y > 0 , read off:
Ψ 1 1 , 1 2 ; 3 2 , 1 2 ; x , y π 4 y · 1 x 1 2 e y / ( 1 x ) .

References

  1. Arceri, F.; Landes, F.P.; Berthier, L.; Biroli, G. A statistical mechanics perspective on glasses and ageing. In Encyclopedia of Complexity and Systems Science; Meyers, R.A., Ed.; Springer: Berlin/Heidelberg, Germany, 2021. [Google Scholar] [CrossRef]
  2. Vincent, E. Encyclopedia of Condensed Matter Physics; Chakraborty, T., Ed.; Oxford University Press: Oxford, UK, 2024; Volume 2, pp. 371–387. [Google Scholar] [CrossRef]
  3. Struik, L.C.E. Physical Ageing in Amorphous Polymers and Other Materials; Elsevier: Amsterdam, The Netherlands, 1978. [Google Scholar]
  4. Bray, A.J. Theory of Phase Ordering Kinetics. Adv. Phys. 1994, 43, 357. [Google Scholar] [CrossRef]
  5. Bray, A.J.; Rutenberg, A.D. Growth Laws for Phase Ordering. Phys. Rev. 1994, E49, R27. [Google Scholar] [CrossRef] [PubMed]
  6. Bray, A.J.; Rutenberg, A.D. The Energy-Scaling Approach to Phase-Ordering Growth Laws. Phys. Rev. 1994, E51, 5499. [Google Scholar] [CrossRef]
  7. Christiansen, H.; Majumder, S.; Janke, W. Phase-ordering kinetics of the long-range Ising model. Phys. Rev. 2019, E99, 011301. [Google Scholar] [CrossRef] [PubMed]
  8. Christiansen, H.; Majumder, S.; Henkel, M.; Janke, W. Ageing in the long-range Ising model. Phys. Rev. Lett. 2020, 125, 180601. [Google Scholar] [CrossRef]
  9. Corberi, F.; Lippiello, E.; Politi, P. One dimensional phase-ordering in the Ising model with space decaying interactions. J. Stat. Phys. 2019, 176, 510. [Google Scholar] [CrossRef]
  10. Corberi, F.; Lippiello, E.; Politi, P. Universality in the time correlations of the long-range 1d Ising model. J. Stat. Mech. 2019, 2019, 074002. [Google Scholar] [CrossRef]
  11. Corberi, F.; dello Russo, S.; Smaldone, L. Ordering kinetics with long-range interactions: Interpolating between voter and Ising models. J. Stat. Mech. 2024, 2024, 093206. [Google Scholar] [CrossRef]
  12. Müller, F.; Christiansen, H.; Janke, W. Non-universality in ageing during phase-separation of the two-dimensional long-range Ising model. Phys. Rev. Lett. 2024, 133, 237102. [Google Scholar] [CrossRef]
  13. Cugliandolo, L.F. Slow Relaxations and Non-Equilibrium Dynamics in Condensed Matter; Barrat, J.-L., Feiglman, M., Kurchan, J., Dalibard, J., Eds.; Les Houches LXXVII; Springer: Berlin/Heidelberg, Germany, 2003; pp. 367–521. [Google Scholar] [CrossRef]
  14. Henkel, M.; Pleimling, M. Non-Equilibrium Phase Transitions Vol. 2: Ageing and Dynamical Scaling Far from Equilibrium; Springer: Berlin/Heidelberg, Germany, 2010. [Google Scholar]
  15. Puri, S.; Wadhawan, V. (Eds.) Kinetics of Phase Transitions; Taylor and Francis: London, UK, 2009. [Google Scholar]
  16. Täuber, U.C. Critical Dynamics: A Field-Theory Approach to Equilibrium and Non-Equilibrium Scaling Behaviour; Cambridge University Press: Cambridge, UK, 2014. [Google Scholar] [CrossRef]
  17. Mason, N.; Pargellis, A.N.; Yurke, B. Scaling behavior of two-time correlations in a twisted nematic liquid crystal. Phys. Rev. Lett. 1993, 70, 190. [Google Scholar] [CrossRef]
  18. Almeida, R.; Takeuchi, K. Phase-ordering kinetics in the Allen-Cahn (Model A) class: Universal aspects elucidated by electrically-induced transition in liquid crystals. Phys. Rev. 2021, E104, 054103. [Google Scholar] [CrossRef]
  19. Henkel, M. Non-equilibrium relaxations: Ageing and finite-size effects. Condens. Matt. Phys. 2023, 26, 13501. [Google Scholar] [CrossRef]
  20. Joh, Y.G.; Orbach, R.; Wood, G.G.; Hammann, J.; Vincent, E. Finite-size effects on spin-glass dynamics. J. Phys. Soc. Jpn. 2004, 69 (Suppl. A), 215. [Google Scholar] [CrossRef]
  21. Kenning, G.G.; Tennant, D.M.; Rost, C.M.; Garrote da Silva, F.; Walters, B.J.; Zhai, Q.; Harrison, D.C.; Dahlberg, E.D.; Orbach, R.L. End of ageing as a probe of finite-size effects near the spin-glass transition temperature. Phys. Rev. 2018, B98. [Google Scholar] [CrossRef]
  22. Barber, M.N. Finite-size scaling. In Phase Transitions and Critical Phenomena; Domb, C., Lebowitz, J.L., Eds.; Academic Press: London, UK, 1983; Volume 8, p. 146. [Google Scholar]
  23. Brankov, J.G.; Danchev, D.M.; Tonchev, N.S. Theory of Critical Phenomena in Finite-Size Systems; World Scientific: Singapore, 2000. [Google Scholar]
  24. Brézin, É. An investigation of finite size scaling. J. Phys. 1982, 43, 15–22. [Google Scholar] [CrossRef]
  25. Fisher, M.E. Critical Phenomena, Proceedings of the 51st International School of Physics “Enrico Fermi”; Green, M.S., Ed.; Academic Press: London, UK, 1971; p. 1. [Google Scholar]
  26. Suzuki, M. Static and Dynamic Finite-Size Scaling Theory Based on the Renormalization Group Approach. Prog. Theor. Phys. 1977, 58, 1142. [Google Scholar] [CrossRef]
  27. Alcaraz, F.C.; Droz, M.; Henkel, M.; Rittenberg, V. Reaction-diffusion processes, critical dynamics and quantum chains. Ann. Phys. 1994, 230, 250. [Google Scholar] [CrossRef]
  28. Krebs, K.; Pfannmüller, M.P.; Wehefritz, B.; Hinrichsen, H. Finite-Size Scaling Studies of One-Dimensional Reaction-Diffusion Systems. Part I. Analytical Results. J. Stat. Phys. 1994, 78, 1429. [Google Scholar] [CrossRef]
  29. Krebs, K.; Pfannmüller, M.P.; Simon, H.; Wehefritz, B. Finite-Size Scaling Studies of One-Dimensional Reaction-Diffusion Systems. Part II. Numerical Methods. J. Stat. Phys. 1994, 78, 1471. [Google Scholar] [CrossRef]
  30. Barbier, D.; de Freitas Pimenta, P.H.; Cugliandolo, L.F.; Stariolo, D.A. Finite size effects and loss of self-averageness in the relaxational dynamics of the spherical Sherrington-Kirkpatrick model. J. Stat. Mech. 2021, arXiv:2103.12654. [Google Scholar] [CrossRef]
  31. Fernandez, L.A.; Marinari, E.; Martin-Mayor, V.; Paga, I.; Ruiz-Lorenzo, J.J. Dimensional cross-over in the ageing dynamics of spin glasses in a film geometry. Phys. Rev. 2019, B100, 184412. [Google Scholar] [CrossRef]
  32. Zamponi, N.; Zamponi, E.; Cannas, S.A.; Chialvo, D.R. Universal dynamics of mitochondrial networks: A finite-size scaling analysis. Sci. Rep. 2022, 12, 17074. [Google Scholar] [CrossRef] [PubMed]
  33. Zhai, Q.; Harrison, D.C.; Tennant, D.; Dahlberg, E.D.; Kenning, G.G.; Orbach, R.L. Glassy dynamics in CuMn thin-film multilayers. Phys. Rev. 2017, B95, 054304. [Google Scholar] [CrossRef]
  34. Zhai, Q.; Martin-Mayor, V.; Schlagel, D.L.; Kenning, G.G.; Orbach, R.L. On the Slowing Down of Spin Glass Correlation Length Growth: Simulations meet experiments. Phys. Rev. 2019, B100, 094202. [Google Scholar] [CrossRef]
  35. Christiansen, H.; Majumder, S.; Janke, W.; Henkel, M. Finite-size effects in ageing can be interpreted as sub-ageing. Phys. Rev. Lett. 2025. [Google Scholar] [CrossRef]
  36. Ionita, F.; Meyer-Ortmanns, H. Physical ageing of classical oscillators. Phys. Rev. Lett. 2014, 112, 094101. [Google Scholar] [CrossRef]
  37. Warkotsch, D.; Institute for Theoretical Physics, University of Leipzig, Leipzig, Germany; Henkel, M.; Groupe de Physique Statistique, Institut Jean Lamour, Universite de Lorraine Nancy, B.P. 70239, F-54506 Vandoeuvre-les-Nancy Cedex, France; Janke, W.; Institute for Theoretical Physics, University of Leipzig, Leipzig, Germany. Unpublished work. 2025. [Google Scholar]
  38. Henkel, M. Generalised time-translation-invariance in simple ageing. In Springer Proceedings in Mathematics and Statistics; Dobrev, V., Ed.; Springer: Berlin/Heidelberg, Germany, 2025; Volume 473. [Google Scholar]
  39. Berche, B.; Henkel, M.; Kenna, R. Critical phenomena: 150 years since Cagniard de la Tour. J. Phys. Stud. 2009, 13, 3201. [Google Scholar] [CrossRef]
  40. Henkel, M.; Schütz, G.M. On the universality of the fluctuation-dissipation ratio in non-equilibrium critical dynamics. J. Phys. 2004, A37, 591. [Google Scholar] [CrossRef]
  41. Glauber, R. Time-dependent statistics of the Ising model. J. Math. Phys. 1963, 4, 294. [Google Scholar] [CrossRef]
  42. Godrèche, C.; Luck, J.-M. Response of non-equilibrium systems at criticality: Exact results for the Glauber-Ising chain. J. Phys. 2000, A33, 1151. [Google Scholar] [CrossRef]
  43. Lippiello, E.; Zannetti, M. Fluctuation dissipation ratio in the one-dimensional kinetic Ising model. Phys. Rev. 2000, E61, 3369. [Google Scholar] [CrossRef]
  44. Mayer, P.; Sollich, P. General solution for multispin two-time correlation and response functions in the Glauber-Ising chain. J. Phys. 2004, A37, 9. [Google Scholar] [CrossRef]
  45. Bray, A.J. Nonequilibrium Statistical Mechanics in One Dimension; Privman, V., Ed.; Cambridge University Press: Cambridge, UK, 1997; pp. 143–165. [Google Scholar]
  46. Aliev, M.A. Generating function of spin correlations functions for kinetic Glauber-Ising model with time-dependent transition rates. J. Math. Phys. 2009, 50, 083302. [Google Scholar] [CrossRef]
  47. Droz, M.; Rácz, Z.; Schmidt, J. One-dimensional kinetic Ising model with competing dynamics: Steady-state correlations and relaxation times. Phys. Rev. 1989, A39, 2141. [Google Scholar] [CrossRef] [PubMed]
  48. Felderhof, B.U. Spin relaxation in the Ising chain. Rep. Math. Phys. 1971, 1, 215, Erratum in Rep. Math. Phys. 1971, 2, 151. [Google Scholar] [CrossRef]
  49. Godrèche, C.; Luck, J.-M. The Glauber-Ising chain under low-temperature protocols. J. Phys. 2022, A55, 495001. [Google Scholar] [CrossRef]
  50. Krapivsky, P.L.; Redner, S.; Ben-Naim, E. A Kinetic View of Statistical Physics; Cambridge University Press: Cambridge, UK, 2010. [Google Scholar]
  51. Mayer, P.; Berthier, L.; Garrahan, J.P.; Sollich, P. Fluctuation-dissipation relations in the non-equilibrium critical dynamics of Ising models. Phys. Rev. 2003, E68, 016116. [Google Scholar] [CrossRef]
  52. Mayer, P.; Sollich, P.; Berthier, L.; Garrahan, J.P. Dynamic heterogeneity in the Glauber-Ising chain. J. Stat. Mech. 2005, 2005, P05002. [Google Scholar] [CrossRef]
  53. Verley, G.; Chétrite, R.; Lacoste, D. Modified fluctuation-dissipation theorem near non-equilibrium states and applications to the Glauber-Ising chain. J. Stat. Mech. 2011. [Google Scholar] [CrossRef]
  54. Durang, X.; Fortin, J.-Y.; del Biondo, D.; Henkel, M.; Richert, J. Exact correlations in the one-dimensional coagulation-diffusion process by the empty-interval method. J. Stat. Mech. 2010, 2010, P04002. [Google Scholar] [CrossRef]
  55. Durang, X.; Fortin, J.-Y.; Henkel, M. Exact two-time correlation and response functions in the one-dimensional coagulation-diffusion process by the empty-interval-particle method. J. Stat. Mech. 2011, 2011, P02030. [Google Scholar] [CrossRef]
  56. Fortin, J.-Y. Crossover properties of a one-dimensional reaction-diffusion process with a transport current. J. Stat. Mech. 2010. [Google Scholar] [CrossRef]
  57. Abramowitz, M.; Stegun, I.A. Handbook of Mathematical Functions; Dover: New York, NY, USA, 1965. [Google Scholar]
  58. Prudnikov, A.P.; Brychkov, Y.A.; Marichev, O.I. Integrals and Series, Vol. 3: More Special Functions; Gordon and Breach: New York, NY, USA, 1990. [Google Scholar]
  59. Srivastava, H.M.; Karlsson, P.W. Multiple Gaussian Hypergeometric Series; Ellis Horwood: Chichester, UK, 1985. [Google Scholar]
  60. Christiansen, H.; Majumder, S.; Janke, W. Coarsening and Aging of Lattice Polymers: Influence of Bond Fluctuations. J. Chem. Phys. 2017, 147, 094902. [Google Scholar] [CrossRef]
  61. Agrawal, R.; Corberi, F.; Lippiello, E.; Politi, P.; Puri, S. Kinetics of the Two-dimensional Long-range Ising Model at Low Temperatures. Phys. Rev. 2021, E103, 012108. [Google Scholar] [CrossRef]
  62. Agrawal, R.; Corberi, F.; Insalata, F.; Puri, S. Asymptotic States of Ising Ferromagnets with Long-range Interactions. Phys. Rev. 2022, E105, 034131. [Google Scholar] [CrossRef] [PubMed]
  63. Agrawal, R.; Corberi, F.; Lippiello, E.; Puri, S. Ordering dynamics of the random-field long-range Ising model in one dimension. Phys. Rev. 2023, E108, 044131. [Google Scholar] [CrossRef]
  64. Christiansen, H.; Majumder, S.; Janke, W. Zero-temperature coarsening in the two-dimensional long-range Ising model. Phys. Rev. 2021, E103, 052122. [Google Scholar] [CrossRef]
  65. Corberi, F.; Lippiello, E.; Zannetti, M. Scaling and universality in the aging kinetics of the two-dimensional clock model. Phys. Rev. 2006, E74, 04106. [Google Scholar] [CrossRef] [PubMed]
  66. Corberi, F.; Iannone, A.; Kumar, M.; Lippiello, E.; Politi, P. Coexistence of coarsening and mean-field relaxation in the long-range Ising chain. Sci. Post Phys. 2021, 10, 109. [Google Scholar] [CrossRef]
  67. Gessert, D.; Christiansen, H.; Janke, W. Ageing following a zero-temperature quench in the d=3 Ising model. Phys. Rev. 2024, E109, 044148. [Google Scholar] [CrossRef]
  68. Janke, W.; Christiansen, H.; Majumder, S. The role of magnetisation in phase-ordering kinetics of the short-range and long-range Ising model. Eur. Phys. J. ST 2023, 232, 1693. [Google Scholar] [CrossRef]
  69. Majumder, S.; Janke, W. Evidence of aging and dynamic scaling in the collapse of a polymer. Phys. Rev. 2016, E93, 032506. [Google Scholar] [CrossRef]
  70. Majumder, S.; Christiansen, H.; Janke, W. Understanding nonequilibrium scaling laws governing collapse of a polymer. Eur. Phys. J. 2020, 93, 142. [Google Scholar] [CrossRef]
  71. Prudnikov, A.P.; Brychkov, Y.A.; Marichev, O.I. Integrals and Series, Vol. 2: Special Functions; Gordon and Breach: New York, NY, USA, 1986. [Google Scholar]
  72. Prudnikov, A.P.; Brychkov, Y.A.; Marichev, O.I. Integrals and Series, Vol. 1: Elementary Functions; Gordon and Breach: New York, NY, USA, 1986. [Google Scholar]
  73. Itzykson, C.; Drouffe, J.-M. Théorie Statistique des Champs; CNRS: Paris, France, 1989; Volume 2. [Google Scholar]
  74. Hang, P.-C.; Luo, M.-J. Note on the Humbert function Ψ1. arXiv 2024, arXiv:2410.21985. [Google Scholar] [CrossRef]
  75. Hang, P.-C.; Luo, M.-J. Asymptotics of the Humbert Function Ψ1 for Two Large Arguments. SIGMA 2024, 20, 074. [Google Scholar] [CrossRef]
  76. Hang, P.-C.; Luo, M.-J. Asymptotics of Saran’s hypergeometric function FK. J. Math. Anal. Appl. 2025, 541, 128707. [Google Scholar] [CrossRef]
  77. Wald, S.; Henkel, M. Lindblad dynamics of the quantum spherical model. Int. Transf. Spec. Funct. 2018, 29, 95. [Google Scholar] [CrossRef]
  78. Hang, P.-C.; Henkel, M.; Luo, M.-J. Asymptotics of the Humbert functions Ψ1 and Ψ2. J. Approx. Theory 2025, arXiv:2501.07281. [Google Scholar] [CrossRef]
Figure 1. Qualitative dependence of the scaled two-time auto-correlator C ( t , s ) on the time ratio y = t / s for (i) a spatially infinite system (dashed line) with the power-law behaviour ∼ y λ / z and (ii) in a fully finite system (full line) which converges to a characteristic plateau C ( 2 ) .
Figure 1. Qualitative dependence of the scaled two-time auto-correlator C ( t , s ) on the time ratio y = t / s for (i) a spatially infinite system (dashed line) with the power-law behaviour ∼ y λ / z and (ii) in a fully finite system (full line) which converges to a characteristic plateau C ( 2 ) .
Entropy 27 00139 g001
Figure 2. Properties of the scaled two-time correlator (2) in the 1 D Glauber–Ising model. Left panel: Universal decay of the correlator F C ( y , ξ ) for large y, with ξ = [ 0.0 , 0.2 , 0.5 , 1.0 , 2.0 ] from top to bottom. The inset shows the expected universal power-law decay (24) for large values of y. Right panel: Decay of the correlator F C ( y , ξ ) as a function of ξ for for y = [ 1.0 , 1.5 , 3.0 , 4.5 ] from bottom to top on the right of the figure. The inset highlights the expected Gaussian decay for large ξ and the dashed lines indicate the leading decay behaviour (25).
Figure 2. Properties of the scaled two-time correlator (2) in the 1 D Glauber–Ising model. Left panel: Universal decay of the correlator F C ( y , ξ ) for large y, with ξ = [ 0.0 , 0.2 , 0.5 , 1.0 , 2.0 ] from top to bottom. The inset shows the expected universal power-law decay (24) for large values of y. Right panel: Decay of the correlator F C ( y , ξ ) as a function of ξ for for y = [ 1.0 , 1.5 , 3.0 , 4.5 ] from bottom to top on the right of the figure. The inset highlights the expected Gaussian decay for large ξ and the dashed lines indicate the leading decay behaviour (25).
Entropy 27 00139 g002
Figure 3. Periodic ring with N sites. Starting from an arbitrary site labelled 0, the property C ( t ; x ) = C ( t ; N x ) becomes intuitive for x 1 .
Figure 3. Periodic ring with N sites. Starting from an arbitrary site labelled 0, the property C ( t ; x ) = C ( t ; N x ) becomes intuitive for x 1 .
Entropy 27 00139 g003
Figure 4. (a) Analytically continued function C ( t ; x ) , as computed in Appendix C, for t = 5 and N = [ 5 , 10 , 20 , 30 ] from top to bottom, in the interval 0 x N . It satisfies the periodicity conditions (27). The full black line gives the initial function C ( 0 ; x ) for a completely disordered initial lattice. The thin horizontal lines indicate the values C ( t ; x ) = 0 and C ( t ; x ) = 1 , respectively. (b) Physical scaling function F C ( 1 , ξ ) of Equation (2), for the same values of t and N. The full black line corresponds to a completely disordered initial state.
Figure 4. (a) Analytically continued function C ( t ; x ) , as computed in Appendix C, for t = 5 and N = [ 5 , 10 , 20 , 30 ] from top to bottom, in the interval 0 x N . It satisfies the periodicity conditions (27). The full black line gives the initial function C ( 0 ; x ) for a completely disordered initial lattice. The thin horizontal lines indicate the values C ( t ; x ) = 0 and C ( t ; x ) = 1 , respectively. (b) Physical scaling function F C ( 1 , ξ ) of Equation (2), for the same values of t and N. The full black line corresponds to a completely disordered initial state.
Entropy 27 00139 g004
Figure 5. Two-time scaled auto-correlator C ( y s , s ) = F C ( y , 0 ) in the 1 D Glauber–Ising model quenched to T = 0 , as a function of y = t / s for (a) finite systems of sizes N = [ 10 , 20 , 30 , 40 ] from top to bottom and for a waiting time s = 5 , and (b) the waiting times s = [ 5 , 20 , 80 ] from bottom to top and of finite size N = 30 . The full black line is the scaled infinite-size auto-correlator ( 23 ) .
Figure 5. Two-time scaled auto-correlator C ( y s , s ) = F C ( y , 0 ) in the 1 D Glauber–Ising model quenched to T = 0 , as a function of y = t / s for (a) finite systems of sizes N = [ 10 , 20 , 30 , 40 ] from top to bottom and for a waiting time s = 5 , and (b) the waiting times s = [ 5 , 20 , 80 ] from bottom to top and of finite size N = 30 . The full black line is the scaled infinite-size auto-correlator ( 23 ) .
Entropy 27 00139 g005
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Henkel, M. Finite-Size Scaling in the Ageing Dynamics of the 1D Glauber–Ising Model. Entropy 2025, 27, 139. https://doi.org/10.3390/e27020139

AMA Style

Henkel M. Finite-Size Scaling in the Ageing Dynamics of the 1D Glauber–Ising Model. Entropy. 2025; 27(2):139. https://doi.org/10.3390/e27020139

Chicago/Turabian Style

Henkel, Malte. 2025. "Finite-Size Scaling in the Ageing Dynamics of the 1D Glauber–Ising Model" Entropy 27, no. 2: 139. https://doi.org/10.3390/e27020139

APA Style

Henkel, M. (2025). Finite-Size Scaling in the Ageing Dynamics of the 1D Glauber–Ising Model. Entropy, 27(2), 139. https://doi.org/10.3390/e27020139

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop