Abstract
Many-particle systems driven out of thermal equilibrium can show properties qualitatively different from any thermal state. Here, we study a ferrimagnet in a weak oscillating magnetic field. In this model, domain walls are not static, but are shown to move actively in a direction chosen by spontaneous symmetry breaking. Thus they act like self-propelling units. Their collective behaviour is reminiscent of other systems with actively moving units studied in the field of ‘active matter’, where, e.g., flocks of birds are investigated. The active motion of the domain walls emerges from ‘dynamical frustration’. The antiferromagnetic xy-order rotates clockwise or anticlockwise, determined by the sign of the ferromagnetic component. This necessarily leads to frustration at a domain wall, which gets resolved by propelling the domain wall with a velocity proportional to the square root of the driving power across large parameter regimes. This motion and strong hydrodynamic interactions lead to a linear growth of the magnetic correlation length over time, much faster than in equilibrium. The dynamical frustration furthermore makes the system highly resilient to noise. The correlation length of the weakly driven one-dimensional system can be orders of magnitude larger than in the corresponding equilibrium system with the same noise level.
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Introduction
Realising new states of matter out of thermal equilibrium in a solid is a challenging task, as solids tend to relax rapidly towards equilibrium. However, by laser or microwave irradiation it has been possible to realise, e.g., Bose-Einstein condensates (BEC) of excitons, polaritons, or magnons1,2,3. These condensates spontaneously break time-translation invariance and realise novel non-equilibrium phase transitions3,4. Nevertheless, the differences to equilibrium systems remain relatively subtle in such systems.
The goal of this paper is to show that a simple model of a driven magnet shows a qualitatively different type of non-equilibrium dynamics. We consider a ferrimagnet that hosts both antiferromagnetic (AFM) order in the xy-plane and ferromagnetic (FM) order in the z-direction5,6. This magnet has a continuous spin-rotation symmetry. We drive it out of thermal equilibrium by, e.g., external radiation. Even for weak perturbations, the domain walls in this system obtain a finite velocity and actively move through the system. Importantly, the direction of motion is not imprinted by the setup, but arises from spontaneous symmetry breaking. These moving domain walls strongly interact with each other by hydrodynamics interactions.
The dynamics of actively moving, self-propelled units have been intensively investigated in the field of active matter7,8,9,10,11,12,13,14,15,16,17,18,19,20,21, which studies systems very different from solids, such as cars on a busy street10, self-propelling bacteria11, flocks or herds of animals12,13, or artificial self-propelled particles (synthetic systems)14,15,16,17. They have in common that the constituents locally use energy to induce, e.g., motion. Thus, detailed balance is broken on a local level, and systems of this kind are intrinsically far from equilibrium. Such active matter systems show collective behaviours with no equilibrium counterparts. One familiar example is a traffic jam. Another concern is the synchronisation of the orientation of birds flying in large flocks. A model introduced by Vicsek et al. in 199513 to describe flocking birds has been argued to exhibit spontaneous breaking of rotational symmetry in a two-dimensional system with noise, which is ruled out by the Mermin–Wagner theorem in equilibrium systems20. Furthermore, new types of phase transitions emerge in such systems6,21,22.
Several recent theoretical studies have investigated the link between solid-state physics and active matter. Lindblad operators23,24, non-Hermitian Hamilton operators25,26 or ‘active spins’ with unusual dynamics27,28 have been used to obtain quantum analogues of active matter and active matter coupled to magnetic order.
Here we use a different route towards realising active magnetic matter. Our model starts from a realistic description of a driven ferrimagnet, which simultaneously may show properties reminiscent of active matter. Thereby, we make use of two general principles: ‘activation of Goldstone modes’29,30 and a mechanism which we call ‘dynamical frustration’. Goldstone modes have the advantage that they can be ‘activated’ by arbitrarily small perturbations. This can be modelled by an equation for the angle φ, which describes the orientation of the staggered in-plane magnetisation of our ferrimagnet. Symmetries allow us to consider the following term in the equation of motion of φ,
where mz is the FM magnetisation in the z-direction and γ is a prefactor. In thermal equilibrium, γ = 0 and φ = const., which follows from the fact that a perpetuum mobile is forbidden. This can also be formally derived from symmetries of the Keldysh action encoding thermal equilibrium31. Out of equilibrium, however, there is no reason why γ should vanish, and indeed one finds that γ grows linearly in the power used to drive the system out of equilibrium6,29. Thus, the Goldstone mode of the ferrimagnet is activated, φ = -γmzt + φ0. A detailed theory of the activation of Goldstone modes in helimagnets and single skyrmions is presented in refs. 29,30. In ref. 6, it was shown that the coupling γ in Eq. (1) drastically changes the phase transition from an xy-AFM phase into the ferrimagnetic phase by rendering it first-order. Experimentally, rotations of out-of-equilibrium magnets are, for example, routinely observed in so-called spin-torque oscillators32,33. Ref. 34 discusses how a rotation of a skyrmion lattice can be induced by laser pulses. Furthermore, Bose-Einstein condensates of magnons2 also lead to oscillating and rotating magnetisation patterns. Models of self-rotating particles with hydrodynamic interactions have also been intensively studied18,19 in the context of biological systems and models for synchronisation. An important difference here is that in our systems the spins are localised. The rotation in time of the local magnetisation shows that detailed balance is broken on a local level, a necessary (but not sufficient) condition to obtain ‘active matter’.
To obtain self-propelled domain walls, we need a second concept: ‘dynamical frustration’, which occurs in our system at domain walls in magnetisation mz, see Fig. 1a. On the left and right sides of the domain wall, the (staggered) xy-order rotates in opposite directions, according to Eq. (1). ‘Dynamical frustration’ describes that the in-plane magnetisation directions periodically point in opposite directions, costing a large amount of energy. We will show that for a static domain wall, due to this frustration no smooth, singularity-free interpolation of the angle φ(x, t) as a function of space and time exists across the domain wall. However, this frustration can be lifted if the domain wall is moving. We will indeed show that, across wide parameter regimes, we obtain an active motion of the domain wall. Importantly, the direction of motion, left or right, arises from spontaneous symmetry breaking, making it similar to self-driven particles. The domain wall thus behaves as if having a ‘motor’ attached to it which can point in two different directions, reminiscent of actively moving particles. This makes our system very different from a significant number of previously studied systems where a directed motion of domain walls is induced by (spin-) currents, laser pulses or static or oscillating fields, see, e.g., refs. 33,35,36,37,38.
a Schematic picture of a domain wall in a driven ferrimagnet. The (staggered) in-plane magnetisation rotates in opposite directions on the left and right side, leading to dynamical frustration. This can lead to an active motion of the domain wall either to the left or right. Data from a numerical simulation of a right-moving domain wall are displayed in (b) and (c). b Magnetisation mz(x, t), while c) shows the phase φ(x, t), describing the orientation of the staggered in-plane magnetisation. A substantial phase gradient ∂xφ is built up behind the moving domain. Parameters: J = 1, Δ = 0.8, δ2 = −0.6, δ4 = 1, g1 = 1, g2 = 0.1, α = 0.1, B0 = 0.15, ω = 3.6 resulting in a rotation period Trot ≈ 612, used to scale the vertical axis for a system of 40,000 spins.
Another example of dynamical frustration arises when lattices of magnetic skyrmions39,40 are imaged by an electron microscope41. Here, the skyrmion lattice starts to rotate42 due to torques induced by the imaging process and breaks into domains43. In this case, the relative rotation of the domains is a source of dynamical frustration that induces long-range forces and a collective motion of dislocations, which are studied both experimentally and theoretically in ref. 43.
Results
Model
We consider a 1D classical spin model, ∣S∣ = 1, with the following Hamiltonian
where J, Δ > 0 impose AFM couplings in the x- and y-directions, but FM interactions for the z-component. Our main results apply also to easy-cone ferromagnets obtained for J < 0, Δ > 0 as long as long-ranged dipolar interaction can be neglected. δ2 and δ4 > 0 introduce a uniaxial anisotropy. For δ2 < 2J(Δ − 1) and Bz = 0, one obtains a ferrimagnetic ground state with a constant \({S}_{i}^{z}=\pm {m}_{0}^{z}\), where \({m}_{0}^{z}=\sqrt{\frac{-{\delta }_{2}-2J(1-\Delta )}{{\delta }_{4}}}\ge 0\). The g-factors gi are chosen differently for even and odd sites. Such staggered g factors naturally occur in magnets with, e.g., a screw axis44 and are used here to avoid that Bz(t) couples to the conserved magnetisation only. The dynamics of the system is described by the stochastic Landau-Lifshitz-Gilbert equation, which includes a phenomenological damping term α and a corresponding noise term proportional to the temperature T, see methods. We first study the noiseless case, T = 0.
To drive the system out of thermal equilibrium, we consider the effect of a rapidly oscillating magnetic field, \({B}_{z}(t)={B}_{0}\cos (\omega t)\), ω ~ J. In the ferrimagnetic phase, \(0 \, < \, | {m}_{0}^{z}| \, < \, 1\), this oscillation ‘activates’ the Goldstone mode. The staggered xy-order, described by the angle φ, begins to precess collectively,
where the formulas are valid for small B0 and a small FM magnetisation. The fields mz and φ are defined by \(\langle {S}_{i}^{z}\rangle={m}^{z}(x)\), \(\langle ({S}_{i}^{x},{S}_{i}^{y})\rangle={(-1)}^{i}\sqrt{1-{({m}^{z})}^{2}}\left(\cos (\varphi (x)),\sin (\varphi (x))\right.\). Here, x is the coarse-grained position variable, with x = ia at the position of spin Si. 〈…〉 denotes an average over the oscillation period of the external field (in plots, however, for simplicity’s sake we show stroboscopic images instead, see methods). An analytical calculation of ωrot using second order perturbation theory in B0 for arbitrary mz is given in Supplementary material, App. C. The precise way in which non-equilibrium is implemented is expected to be irrelevant as long as the xy-symmetry remains intact. In an experimental system one could, e.g., also use a laser to create electronic excitations. In this case, no staggered g-factors are needed and one expects that γ is proportional to the power of the laser.
Moving domain walls
In our system, the xy-magnetisation rotates in the clockwise or anticlockwise direction when the FM magnetisation points up or down, respectively. As argued in the introduction, this leads to dynamical frustration at the centre of the domain wall where mz changes sign. Figure 1b, c shows the result of a numerical simulation of such a domain wall. Depending on the initial conditions, the domain wall moves either to the right or to the left with a constant velocity. Far from the domain wall boundary, the angle φ develops a finite slope that builds up behind the moving domain wall.
To develop an analytical theory for the velocity of the moving domain wall, we first consider the limit of vanishing damping, α → 0. The following calculation uses the interplay of spin (super) currents and domain wall motion as studied previously by Kim and Tserkovnyak35, see also refs. 36,38. For a domain wall moving with the velocity v, we make the ansatz
see Supplementary material App. D.5 for details. This ansatz captures the magnetisation profile shown in Fig. 1b, c, obtained in the long-time limit. The term \(\tilde{\omega }t\) is needed to capture the asymmetry between the left and the right side. Note that both the direction of v and the sign of the phase gradients arise from spontaneous symmetry breaking by tiny asymmetries in the initial condition. We need only one extra input to solve the steady-state problem: for vanishing damping, the magnetisation mz is conserved, ∂tmz + ∂x jz = 0 and the spin (super) current is proportional to the gradient of the phase35,36,45,46,
where \({\rho }_{s}\approx J{a}^{2}(1-{({m}_{0}^{z})}^{2})\) is the spin stiffness and a the lattice constant. Substituting in Eq. (4), and integrating the continuity equation over space from − x0 to x0, one obtains
Far from the domain wall, the magnetisation takes its bulk value \({m}^{z}=\pm {m}_{0}^{z}\) and the spins rotate with \({\partial }_{t}\varphi=-v{\partial }_{x}\Phi+\tilde{\omega }=\mp | {\omega }_{{{\rm{rot}}}}|\), Eq. (3). Therefore, we obtain from Eq. (6) directly \(-2v{m}_{0}^{z}+2{\rho }_{s}\frac{| {\omega }_{{{\rm{rot}}}}| }{v}=0\) or, equivalently,
where the sign of the velocity is determined by the sign of the jump in the gradients, ∂xΦ(x0) − ∂xΦ( − x0). Eq. (7) is a noteworthy result for four reasons: (i) It has been derived without any knowledge of the shape of the domain wall. All microscopic parameters entering the equation are known analytically for small B0. (ii) The direction of motion has to be chosen by spontaneous symmetry breaking and is, for example, determined by small fluctuations of φ in the initial state. (iii) As ωrot is linear in \({m}_{0}^{z}\), the velocity of domain walls remains finite even for \({m}_{0}^{z}\to 0\), i.e., when the phase transition from an xy-ordered phase to the ferrimagnetic phase is approached. Indeed, in a previous analysis6, we found that this velocity characterises the field theory of the critical point in higher dimensions. Finally, (iv), the velocity is very fast. v is proportional to the square root of ωrot, making it linear in the amplitude B0 of the oscillating field or, equivalently, proportional to the square root of the power used to drive our system out of thermal equilibrium. For weak B0, this makes v much larger than, e.g., ωrotξ0, where ξ0 is the width of the domain wall. Actively moving phase boundaries have also been shown to exist in models containing mixtures of active and passive Brownian particles17.
Eq. (7) is valid for α → 0 for finite ωrot. The calculation for finite α is more challenging. In Supplementary material, App. D, we derive an approximate formula for the velocity,
where ξ0 is the width of the domain wall in equilibrium, \({\xi }_{0}=\frac{a\sqrt{2J\Delta /{\delta }_{4}}}{{m}_{0}^{z}}\), and η is a dimensionless numerical factor, with η = 3 close to the ferrimagnetic phase transition. For ωrot → 0, the velocity of the domain wall is linear in ωrot. In this limit, the domain wall moves by a large distance \(\frac{\pi \eta {\xi }_{0}}{\alpha {m}_{0}^{z}} \, \gg \, {\xi }_{0}\) during each rotation, inversely proportional to the (often very small) Gilbert damping α and the average magnetisation \({m}_{0}^{z} \, < \, 1\). In this regime, a similar formula has previously been obtained for a domain wall in a ferrimagnet driven by an external rotating field37, but in this case the direction of motion is not chosen spontaneously but imprinted externally.
In Fig. 2, we show the velocity of the domain wall obtained from numerical simulations, together with Eq. (8). Taking into account that there is no fitting parameter and the approximate nature of the derivation of Eq. (8), the agreement for B0 ≲ 0.2 is very good. The analytical formula Eq. (8) does not include the renormalisation of \({m}_{0}^{z}\) and ρs for large B0, which may explain small deviations for larger B0.
Across a wide parameter range, v is linear in B0 and thus proportional to \(\sqrt{| {\omega }_{{{\rm{rot}}}}| }\), see Eq. (7). Lines: analytical calculation of the domain wall velocity, Eq. (8), without fitting parameters. Parameters: J = 1, Δ = 0.8, δ2 = −0.6 and −0.8, δ4 = 1, g1 = 1, g2 = 0.1, α = 0.1 and 0.2, ω = 3.6 for a system of 40,000 spins. Numerical errors are smaller than the size of the symbols.
Above a critical strength of the driving field, B0 > Bc, the moving domain wall solution ceases to exist. Instead, one obtains localised domain walls. In Supplementary material, App. A.1, we show that in this case, topology enforces the presence of singular configurations of φ(x, t) (phase slips or, equivalently, space-time vortices47), which manifest as sudden bursts of spin excitations occurring periodically once per rotation period, Trot = 2π/ωrot.
Dynamics of ordering
To investigate the dynamics of ordering, we consider a quench starting from an initial state with long-ranged AFM order perturbed by a small random component of the magnetisation in the z-direction. An example for the dynamics after such a quench is shown in Fig. 3. The domain walls move and when two of them meet, they get annihilated. Thus, the correlation length, defined as the inverse of the domain wall density, ξ = 1/nDW, grows rapidly, see Fig. 4. At intermediate times, the correlation length grows approximately with the speed of a single domain wall, ξ ≈ vt. In the long time limit, ξ also grows linearly in time,
where μ ≲ 1 is a numerical constant. μ vt, with μ ≈ 0.53 for the chosen parameters, is shown as a dashed black line in Fig. 4a. A linear growth of correlations has been reported before for active matter models with self-propelled particles48,49.
Worldlines end either when a left-moving and a right-moving domain collide or when the distance between two domain walls shrinks to zero. Colour: amplitude of ∂xφ in units of δφ, given by the difference of phase gradients δφ = ∂xφleft − ∂xφright ≈ 0.176 across a single domain wall, see Fig. 1b, c. The motion of domain walls is subject to a long-range hydrodynamic interaction mediated by ∂xφ. Parameters: same as in Fig. 1, initial state: ordered xy-AFM with a small random \({S}_{i}^{z}=\pm 0.1\), see section “Methods”.
a Correlation length ξ = 1/nDW as function of time after a quench from an AFM-ordered phase into the ferrimagnetic phase both for a driven and a non-driven system, marked by NEQ (non-equilibrium) and EQ (equilibrium) in the legend, respectively. The inset shows that the short-time dynamics of the driven and non-driven system is identical, but after a few rotation periods Trot, the driven system shows a very fast increase of the correlation length. In the long-time limit, ξ grows linearly in time (~0.065t, black dashed line). For comparison, vt, where v is the velocity of a single domain wall, is also shown as a dashed red line. The linear growth of correlations with time can also be seen directly from a scaling plot of the equal-time correlation function \(C(x)=\langle {S}_{j}^{z}{S}_{j+x/a}^{z}\rangle\) (averaged over j), which is shown (for even x/a) in panel b as function of x/(vt). Here v is the velocity of a single domain wall. The plot shows that the maximal speed is 2v, arising from two domain walls moving in opposite directions. Parameters: as in Fig. 3, average over 20 initial states in simulations with 500,000 spins each (15 initial states for the equilibrium states). Error bars denote the corresponding standard deviation of the mean.
This very efficient and fast growth of the correlation length is not what is expected from a theory of independently moving and pairwise annihilating domain walls. Consider a 1D model, where particles with velocity ± v annihilate each other whenever two of them collide50. In such a model, within time t roughly \({N}_{L}=N\pm \sqrt{N}\) left-moving and \({N}_{R}=N\pm \sqrt{N}\) right-moving particles interact with each other, where N ~ vt/d0 if d0 is the initial distance of the particles. After a time t, most of them will have annihilated, but this process leaves approximately \(| {N}_{R}-{N}_{L}| \sim \sqrt{N}\) particles in an area of size vt. Thus, in this model the correlation length grows relatively slowly with
for vt ≫ d050,51, in contrast to our finding.
Therefore, we conclude that the rapid growth of ξ can only arise from a strong interaction of the domain walls, which is mediated by the gradients of the xy-order imprinted by dynamical frustration. This is shown by the following qualitative argument: within a FM domain, the angle φ grows linearly in time, φ ≈ ± ωrott, with opposite signs for up and down domains. If domains have the typical size ξ(t), this implies that the typical gradient of φ is of the order of
If we now demand that gradients remain bounded for t → ∞, then it is plausible that ξ(t) has to grow linearly in t, which explains our numerical observation, Eq. (9). This derivation is not rigorous, as it is possible to construct solutions of, e.g., equally spaced domain walls with a time-independent distance. However, in our simulations such configurations are not stable due to their interactions with an inhomogeneous ∂xφ-background.
Microscopically, the necessary interactions are mediated by φ. More precisely, the domain walls interact with \({\partial }_{x}^{2}\varphi\), as can be seen directly from the relevant Ginzburg-Landau theory, see methods. A negative \({\partial }_{x}^{2}\varphi\) leads to ∂x jz < 0, see Eq. (5), and thus to an increase of mz, which acts as a repulsive force for an approaching domain with mz < 0. Here, the main source of large \({\partial }_{x}^{2}\varphi\) are cases where two domain walls meet and annihilate. As can be seen in Fig. 3, each annihiliation event leaves behind a characteristic trace in \({\partial }_{x}^{2}\varphi\) where ∂xφ changes sign. Close to x = 37,000 a in Fig. 3, a left-moving down domain wall changes its direction of motion when approaching a region with \({\partial }_{x}^{2} \, \varphi \, < 0\). After transforming into a right-moving domain wall, it finally annihilates with another left-moving domain wall. Importantly, the interactions mediated by \({\partial }_{x}^{2}\varphi\) are strongly retarded, as it takes a very long time proportional to ξ2 for \({\partial }_{x}^{2}\varphi\) to decay by diffusion. This is much shorter than the time of order ξ/v needed for the approach of other domain walls, see Supplementary material App. A.3 for a hydrodynamic view of these effects.
Resilience to noise
Finally, we investigate the influence of thermal noise (described by a random magnetic field ξi(t), see methods) on our findings. In a 1D system in thermal equilibrium, such a noise term destroys long-ranged order and induces domain walls with a typical distance \({\xi }_{{{\rm{th}}}} \sim {e}^{{E}_{{{\rm{DW}}}}/{k}_{B}T}\), where EDW is the domain wall energy at T = 0, and the temperature T controls the noise strength. For the parameters chosen in our figures, EDW = 0.076 J. In the following, we will therefore always use T/EDW to specify temperatures. Fig. 5a, b show the magnetisation of a driven ferrimagnet as function of space and time after a quench from the AFM phase for two different temperatures. As in the noiseless case studied above, domain walls actively move with a velocity approximately 10% larger than in the noiseless case, see Supplementary material, App. E.4. It is surprising that the velocity is affected so little, taking into account that the xy-correlation length ξAFM in the noisy and driven system becomes tiny, ξAFM ≲ 30, see Supplementary material, App. E.1.
a, b Magnetisation as function of x and t for two slightly different temperatures, and thus different noise levels, for systems of 250,000 spins (other parameters and colour scale as in Fig. 1). c \({m}^{z}(x)={S}_{i}^{z}\) at the final timestep of the simulations shown in (a, b), for a small region with 2000 spins. The lower green curve shows that an equilibrium system has a much shorter correlation length at similar noise levels.
Figure 5a shows the formation of giant domains with a size exceeding 105 spins. This has to be compared to an equilibrium system, where for the same noise level the correlation length is less than 20 sites.
In Fig. 6 we show the steady-state correlation function for both the equilibrium and non-equilibrium systems. In the driven system, the correlation function decays very slow in space, roughly with a linear slope on a logarithmic scale, \(C(x)=C(0)\left(1-\ln [x/a]/\ln [{\xi }_{\max }(T)/a]\right.\), showing that the system hosts domains with very different sizes. \({\xi }_{\max }(T)\) can be interpreted as the largest correlation length in the system, see Supplementary material, App. E.3, for details. \({\xi }_{\max }(T)\) grows much faster than exponential with 1/T, see inset of Fig. 6 showing that the rapid growth does not arise from a thermal process. A direct comparison of the space-time correlations of the driven and non-driven systems, see Supplementary material, App. E.4, shows the qualitative change of dynamical properties of the driven system.
Equal-time correlation function C(x) = 〈mz(x0 + x)mz(x0)〉 in the presence of thermal noise for systems of the size of 250,000 spins (parameters as in Fig. 1, only even x/a are shown, error bars denote the standard deviation of the mean). The data is measured at t ≈ 520,000/J ≈ 850 Trot after a quench from an AFM state. The error bars are standard deviation of the mean obtained by averaging over four runs. With the exception of the curve for the lowest T (blue), the system has obtained a stationary state at that time, see Supplementary material, App. E.3. Note the logarithmic scale on the x-axis, needed due to a broad distribution of domain sizes, see Fig. 5. Compared to the non-driven system in thermal equilibrium (dashed lines), the correlation length becomes many orders of magnitude larger for T ≲ 0.025 J. Inset: The correlation length \({\xi }_{\max }\) grows faster than exponential with 1/T. For a discussion of error bars in the inset, see Supplementary material, App. E.3.
How can even a relatively weak oscillating field increase the correlation length by many orders of magnitude and why is the driven system so resilient to noise? In the regime investigated here, fluctuations are not small and even within an ordered domain, they often induce a sign change, see the upper curve in Fig. 5c. Locally, fluctuations are very similar to the thermal system. The difference is, however, that the driven system is very efficient in suppressing the generation of defects and also in healing some of the most frequently occurring defects. The main origin of this healing effect is the dynamical frustration of domains rotating in opposite direction. In Supplementary material, App. B, we discuss and investigate the detailed microscopic mechanisms behind this observation.
One may ask whether one can (or indeed should) use the term ‘active magnetic matter’ to describe the system studied here. As discussed in the introduction, active matter is usually defined as being composed of large numbers of ‘active agents’, each breaking detailed balance on a local level and giving rise to collective non-equilibrium phenomena. In our case, one can either view each spin or each domain wall as one of the active agents. Each spin in our system is rotating either clockwise or counter-clockwise, thus breaking detailed balance on a local level. Similarly, a domain wall moves actively in space, either to the right or to the left side. Furthermore, we have shown that the collective dynamics of domain walls is dominated by long-range interactions and cannot be understood from their individual motion. In our case of an active magnetic system, the external drive is implemented in a continuous way by an oscillating external field. This is also the case in more traditional active systems, for example of biological origin. There, some type of feeding is required, but continuous drive is not needed in most biological systems, where energy can be stored. Other examples of continuously driven active matter systems use light or ultrasound as a stimulus9,16,52,53.
In conclusion, we show that a simple oscillating field transforms a ferrimagnet into an ‘active magnet’. This is a state of matter with properties very different to those of equilibrium systems. Ferrimagnets recently attracted considerable interest in the field of spintronics5, as they combine the advantages of FM and AFM systems. Here, we mainly need the rotation of an xy-order parameter in a driven system to be controlled by the orientation of a FM component perpendicular to it. The rotation of the xy-order parameter leads to an effect which we call ‘dynamical frustration’, resulting in an efficient propulsion of the domain wall, which now moves actively either to the left or to the right by spontaneous symmetry breaking. The net effect is a very fast buildup of FM correlations on huge length scales, indicating a high degree of robustness of the system to thermal noise due to an efficient non-equilibrium self-healing mechanism. While our study has focused on one-dimensional systems, we show in Supplementary material App. F that key results such as the active motion of domain walls and the rapid buildup of correlations also apply in two dimensions. The most promising route for an experimental realisation of our model is to use widely studied magnetic multilayer systems, whose properties (including magnetic anisotropies) can largely be tuned by layer thickness and the combination of different materials54,55. For example, Ślȩzak et al.56 recently demonstrated direct coupling of an easy-plane antiferromagnetic NiO layer to an adjacent ferromagnet Fe layer, providing a direct route towards a room-temperature realisation of our model. Experimentally, it should be rather straightforward to observe the motion of domain walls using standard imaging methods based on the Faraday or Kerr effect, which are routinely used to observe the motion of domain walls57.
A surprising aspect of our results is that very weak perturbations have a profound effect on the qualitative and quantitative behaviour of the system. For the chosen parameters, the speed of rotation of the magnetisation was tiny, ωrot J ≈ ±0.01. This tiny perturbation changes the dynamics of the system, affects the correlations both on small and large length scales, see Fig. 6, and can increase the correlation length by orders of magnitude. In equilibrium systems, tiny perturbations (if they are ‘relevant’ in the renormalisation-group sense) can also sometimes strongly affect properties of correlation functions, but only at very long distances. We are not aware of any equilibrium systems in which small perturbations cause such a profound change of magnetic correlations on all length scales. Our driven system is different, as it induces active motion of domain walls.
In our study, we have investigated a minimal model of a driven magnet. We anticipate that it is possible to activate (approximate) Goldstone modes in a large class of systems and to use the principle of dynamical frustration to realise actively moving defects. For example, basic features of our models can be realised directly by coupling a superconducting layer to a ferroelectric or a polar metal in the presence of external radiation using, e.g., oxide heterostructures58. Given the enormous variety of complex symmetries and associated topological defects available in solid-state systems, we anticipate numerous opportunities to realise systems which may be identified as active magnetic matter or, more broadly, active quantum matter. An important aspect of this challenge will be finding experimental realisations of such systems.
Methods
The dynamics of the ferrimagnetic system, Eq. (2), is obtained from the (stochastic) Landau–Lifshitz–Gilbert (LLG) equation
with the dimensionless damping constant α. ξi(t) is a Gaussian random noise term with \(\langle {{\boldsymbol{\xi}} }_{i}(t){{\boldsymbol{\xi}} }_{j}({t}^{\prime} ) \rangle=2\alpha {k}_{B}T{\delta }_{i,j}\delta (t- {t} ^{\prime} )\) which arises from thermal fluctuations. H is given in Eq. (2).
In order to simulate the micromagnetic system, we use the GPU-accelerated open-source software Mumax359,60. We simulate one-dimensional systems with sizes ranging from 20,000 to 500,000 spins with open boundary conditions for simulations of a single domain wall and periodic boundary conditions for all other simulations. In Supplementary material, we also show simulations for two-dimensional systems with up to 108 spins but only for shorter runtimes. For quenches from the AFM phase, we use initial states with \({S}_{i}^{z}\) drawn from a uniform distribution in the interval of (−0.1, 0.1), \({S}_{i}^{x}={(-1)}^{i}\sqrt{1-{({S}_{i}^{z})}^{2}}\) and \({S}_{i}^{y}=0\), i.e., φ = 0.
In all figures displaying the time evolution, we show stroboscopic images, obtained at integer multiples of the driving period 2π/ω.
For our analytical arguments, we mainly use the LLG Eq. (12) either directly or evaluated in a continuum limit, see Supplementary material, App. C and D, for details. Alternatively, one can analyse the appropriate (noisy) Ginzburg-Landau theory describing the ferrimagnet close to the transition to the AFM6. This Ginzburg Landau theory is formulated in the continuum limit for the FM magnetisation mz(x, t) and the angle φ(x, t) parametrising the orientation of the AFM xy-order. A Taylor expansion in mz, derivatives of φ and the number of gradients gives to leading order
where ξφ/m describe Gaussian white noise with 〈ξφ/m〉 = 0 and \(\langle {\xi }_{\varphi /m}{\xi }_{\varphi /m}\rangle=2\alpha T\delta (t- {t}^{\prime} )\delta (x- {x}^{\prime} )\). The noise strength is fixed by the damping terms ( ~ α) and temperature. The equilibrium system is obtained by setting γ = K = 0. All parameters of Eq. (13) are known analytically with the exception of K, with r = δ2 + 2J(1 − Δ), u = δ4, ρs = Ja2, D = JΔ a2. γ, responsible for the rotation of the xy-order, is proportional to \({B}_{0}^{2}\) for small B0, and is computed in Supplementary material, App. C. Note that the effective field theory cannot be used to quantitatively describe the space-time vortices discussed in the Supplementary material, App. A.1, as the magnetisation reaches ± 1 at the vortex core, which is outside of the range of validity of Eq. (13).
From the first line in Eq. (13), one recovers Eq. (1) in the ferrimagnetic phase for \({\partial }_{x}^{2}\varphi=0\) and stationary mz. Similarly, for α → 0 one obtains a continuity equation for mz, with the current given by Eq. (5).
Data availability
The supporting data generated in this study have been deposited in a Zenodo database under accession code61.
Code availability
All data shown was generated with Mumax3 as described in the “Methods” section. We provide one file to run such simulations as an example on Zenodo61.
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Acknowledgements
We acknowledge useful discussions with Romain Daviet, Gerhard Gompper, Joachim Krug, and Carl Zelle. We thank the German Research Foundation for financial support via CRC 1238 (Project-ID 277146847, project C04) and CRC/TRR 183 (Project-ID 277101999, project A01). Furthermore, we thank the Regional Computing Center of the University of Cologne (RRZK) for providing computing time on the DFG-funded (Funding number: INST 216/512/1FUGG) High Performance Computing (HPC) system CHEOPS as well as technical support.
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D.H., N.d.S and A.R. developed the analytical theory with N.d.S deriving the theory of domain wall velocities at finite α. D.H. and R.D. performed simulations using the effective Ginzburg Landau theory (D.H.) and Mumax (R.D.). S.D. and A.R. designed the study. All authors contributed to the manuscript.
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Hardt, D., Doostani, R., Diehl, S. et al. Propelling ferrimagnetic domain walls by dynamical frustration. Nat Commun 16, 3817 (2025). https://doi.org/10.1038/s41467-025-58920-1
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DOI: https://doi.org/10.1038/s41467-025-58920-1