Motility-Induced Pinning in Flocking System with Discrete Symmetry
Pith reviewed 2026-05-24 02:29 UTC · model grok-4.3
The pith
Pinned interfaces grow macroscopically and suppress polar order in the active Ising model when particle diffusion is much slower than self-propulsion.
A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.
Core claim
In the active Ising model, interfaces between colliding domains of self-propelled particles become pinned through a resonating back-and-forth motion of individual particles across the interface; as alignment interaction strength increases, these pinned interfaces grow to macroscopic size when the diffusion rate is sufficiently smaller than the self-propulsion rate, rendering polar order short-ranged in both space and time.
What carries the argument
The resonating back-and-forth motion of self-propelled particles across domain interfaces, which stabilizes pinning and drives the growth dynamics of pinned regions.
If this is right
- Polar order remains short-ranged in both space and time for intermediate alignment strengths due to traveling local domains.
- A numerical phase diagram separates regimes of unpinned traveling domains from pinned macroscopic interfaces.
- The approximate analytic theory predicts growth versus shrink dynamics of pinned interfaces as a function of alignment strength and diffusion rate.
- Polar order is prevented when diffusion is sufficiently slower than self-propulsion.
Where Pith is reading between the lines
- The pinning mechanism may generalize to other discrete-symmetry active systems where interface stability depends on particle crossing rates.
- In the opposite regime of faster diffusion, unresolved growth behavior could still limit the range of polar order through different dynamics.
- Experimental realizations with colloidal or granular particles could test the predicted dependence on the diffusion-to-propulsion ratio by varying temperature or drive strength.
Load-bearing premise
The observed pinning and its growth to macroscopic scale in simulations reflect the thermodynamic limit rather than finite-size or transient effects, and the approximate analytic theory captures the interface dynamics without additional fitting parameters.
What would settle it
Simulations in significantly larger systems that check whether pinned interfaces continue to grow without bound (or saturate at a finite fraction of system size) specifically when the diffusion-to-propulsion ratio is decreased below the reported threshold.
Figures
read the original abstract
We report a motility-induced pinning transition in the active Ising model for a self-propelled particle system with discrete symmetry. This model was known to exhibit a liquid-gas type flocking phase transition, but a recent study reveals that the polar order is metastable due to droplet excitation. Using extensive Monte Carlo simulations, we demonstrate that, for an intermediate alignment interaction strength, the steady state is characterized by traveling local domains, which renders the polar order short-ranged in both space and time. We further demonstrate that interfaces between colliding domains become pinned as the alignment interaction strength increases. A resonating back-and-forth motion of individual self-propelled particles across interfaces is identified as a mechanism for the pinning. We present a numerical phase diagram for the motility-induced pinning transition, and an approximate analytic theory for the growth and shrink dynamics of pinned interfaces. Our results show that pinned interfaces grow to a macroscopic size preventing the polar order in the regime where the particle diffusion rate is sufficiently smaller than the self-propulsion rate. The growth behavior in the opposite regime and its implications on the polar order remain unresolved and require further investigation.
Editorial analysis
A structured set of objections, weighed in public.
Referee Report
Summary. The manuscript reports a motility-induced pinning transition in the active Ising model. Using extensive Monte Carlo simulations, it finds that for intermediate alignment interaction strengths the steady state consists of traveling local domains that render polar order short-ranged. Interfaces between colliding domains become pinned via a resonating back-and-forth particle motion; an approximate analytic theory is given for the growth and shrink dynamics of these interfaces. The central claim is that, when the diffusion rate is sufficiently smaller than the self-propulsion rate, pinned interfaces grow to macroscopic size and thereby suppress long-range polar order. A numerical phase diagram is presented; the opposite (high-diffusion) regime is left unresolved.
Significance. If the pinning mechanism and its macroscopic growth survive the thermodynamic limit, the result would clarify the origin of short-ranged order in discrete-symmetry active systems and would complement existing work on metastable polar order. The combination of direct simulation with an analytic interface theory is a methodological strength.
major comments (2)
- [Monte Carlo results and phase-diagram section] The central claim that pinned interfaces reach a macroscopic size that survives the thermodynamic limit (thereby preventing long-range polar order) rests on finite-lattice Monte Carlo data. No finite-size scaling analysis of steady-state interface length, domain number, or correlation length versus linear size L is reported, so it remains possible that the observed pinning is a slow transient or finite-L crossover. This issue is load-bearing for the abstract's statement on macroscopic growth in the low-diffusion regime.
- [Analytic theory section] The analytic theory for interface growth/shrink dynamics is labeled approximate. The manuscript should state explicitly which approximations are made, whether any effective parameters are introduced by the approximation, and whether those parameters alter the predicted pinning threshold or growth law in the low-diffusion regime.
minor comments (2)
- The abstract states that the high-diffusion regime remains unresolved; a short paragraph explaining why this regime is left open would improve clarity.
- Simulation figures and the phase diagram should include error bars or estimates of statistical uncertainty.
Simulated Author's Rebuttal
We thank the referee for the careful reading and constructive comments on our manuscript. We respond to each major comment below and will revise the manuscript accordingly.
read point-by-point responses
-
Referee: [Monte Carlo results and phase-diagram section] The central claim that pinned interfaces reach a macroscopic size that survives the thermodynamic limit (thereby preventing long-range polar order) rests on finite-lattice Monte Carlo data. No finite-size scaling analysis of steady-state interface length, domain number, or correlation length versus linear size L is reported, so it remains possible that the observed pinning is a slow transient or finite-L crossover. This issue is load-bearing for the abstract's statement on macroscopic growth in the low-diffusion regime.
Authors: We agree that the absence of finite-size scaling leaves open the possibility of finite-L effects or transients. In the revised manuscript we will add finite-size scaling analysis of the steady-state interface length, domain number, and correlation length versus L, performed in the low-diffusion regime. Additional simulations at larger L already indicate that the macroscopic pinning persists, but the systematic scaling will be included to address this point directly. revision: yes
-
Referee: [Analytic theory section] The analytic theory for interface growth/shrink dynamics is labeled approximate. The manuscript should state explicitly which approximations are made, whether any effective parameters are introduced by the approximation, and whether those parameters alter the predicted pinning threshold or growth law in the low-diffusion regime.
Authors: We acknowledge that the approximations underlying the analytic interface theory require explicit enumeration. In the revision we will list the approximations (mean-field treatment of local densities and neglect of higher-order correlations), confirm that no auxiliary effective parameters are introduced, and demonstrate that the predicted pinning threshold and growth laws in the low-diffusion regime are unaffected by these approximations. revision: yes
Circularity Check
No circularity; results from independent simulations and approximate theory
full rationale
The paper reports Monte Carlo simulations demonstrating traveling domains and pinned interfaces, plus an approximate analytic theory for interface growth/shrink dynamics. No load-bearing step reduces a claimed prediction or first-principles result to a quantity defined in terms of its own fitted inputs or prior self-citation. The central claim (macroscopic pinning preventing polar order at low diffusion) is presented as an outcome of the simulations and theory rather than a tautological re-expression of inputs. Self-citations, if present, are not invoked to forbid alternatives or force the result by construction. This is the common honest outcome for simulation-driven work.
Axiom & Free-Parameter Ledger
free parameters (2)
- alignment interaction strength
- diffusion rate relative to self-propulsion
axioms (1)
- domain assumption The active Ising model on a lattice with discrete directions and Metropolis Monte Carlo dynamics faithfully represents the intended self-propelled particle system.
Reference graph
Works this paper leans on
-
[1]
M. C. Marchetti, J.-F. Joanny, S. Ramaswamy, T. B. Liverpool, J. Prost, M. Rao, and R. A. Simha, Hydrody- namics of soft active matter, Reviews of Modern Physics 85, 1143 (2013)
work page 2013
-
[2]
C. Bechinger, R. Di Leonardo, H. Löwen, C. Reichhardt, G. Volpe, and G. Volpe, Active particles in complex and crowded environments, Reviews of Modern Physics88, 045006 (2016)
work page 2016
-
[3]
R. Di Leonardo, L. Angelani, D. Dell’Arciprete, G. Ruocco, V. Iebba, S. Schippa, M. P. Conte, F. Mecarini, F. De Angelis, and E. Di Fabrizio, Bacterial ratchet motors, Proceedings of the National Academy of Sciences 107, 9541 (2010)
work page 2010
- [4]
- [5]
-
[6]
J. Buhl, D. J. Sumpter, I. D. Couzin, J. J. Hale, E. Des- pland, E. R. Miller, and S. J. Simpson, From disorder to order in marching locusts, Science312, 1402 (2006)
work page 2006
-
[7]
I. Giardina, Collective behavior in animal groups: the- oretical models and empirical studies, HFSP Journal2, 205 (2008)
work page 2008
-
[8]
M. Ballerini, N. Cabibbo, R. Candelier, A. Cavagna, E. Cisbani, I. Giardina, V. Lecomte, A. Orlandi, G. Parisi, A. Procaccini,et al., Interaction ruling animal collective behavior depends on topological rather than metric distance: Evidence from a field study, Proceedings of the national academy of sciences105, 1232 (2008)
work page 2008
-
[9]
A. J. Ward, D. J. Sumpter, I. D. Couzin, P. J. Hart, and J. Krause, Quorum decision-making facilitates informa- tion transfer in fish shoals, Proceedings of the National Academy of Sciences105, 6948 (2008)
work page 2008
-
[10]
A. Cavagna and I. Giardina, Bird flocks as condensed matter,Annu.Rev.Condens.MatterPhys. 5,183(2014)
work page 2014
-
[11]
A. Cavagna, D. Conti, C. Creato, L. Del Castello, I. Gi- ardina, T. S. Grigera, S. Melillo, L. Parisi, and M. Viale, Dynamic scaling in natural swarms, Nature Physics13, 914 (2017)
work page 2017
-
[12]
A. Bricard, J.-B. Caussin, N. Desreumaux, O. Dauchot, and D. Bartolo, Emergence of macroscopic directed mo- tion in populations of motile colloids, Nature 503, 95 (2013)
work page 2013
- [13]
-
[14]
J. Yan, M. Han, J. Zhang, C. Xu, E. Luijten, and S. Granick, Reconfiguring active particles by electrostatic imbalance, Nature Materials15, 1095 (2016)
work page 2016
-
[15]
B.LiebchenandH.Lowen,Syntheticchemotaxisandcol- lective behavior in active matter, Accounts of Chemical Research 51, 2982 (2018)
work page 2018
- [16]
-
[17]
J. Toner and Y. Tu, Long-range order in a two- dimensional dynamical xy model: how birds fly together, Physical Review Letters75, 4326 (1995)
work page 1995
-
[18]
N. D. Mermin and H. Wagner, Absence of ferromag- netism or antiferromagnetism in one-or two-dimensional isotropic heisenberg models, Physical Review Letters17, 1133 (1966)
work page 1966
-
[19]
Y. Fily and M. C. Marchetti, Athermal phase separation ofself-propelledparticleswithnoalignment,PhysicalRe- view Letters 108, 235702 (2012)
work page 2012
-
[20]
I. Buttinoni, J. Bialké, F. Kümmel, H. Löwen, C. Bechinger, and T. Speck, Dynamical clustering and phase separation in suspensions of self-propelled colloidal particles, Physical Review Letters110, 238301 (2013)
work page 2013
-
[21]
M. E. Cates and J. Tailleur, Motility-induced phase sepa- ration, Annu. Rev. Condens. Matter Phys.6, 219 (2015)
work page 2015
-
[22]
L. Caprini, U. M. B. Marconi, and A. Puglisi, Sponta- neous Velocity Alignment in Motility-Induced Phase Sep- aration, Physical Review Letters124, 078001 (2020)
work page 2020
-
[23]
Z. Csahók and T. Vicsek, Lattice-gas model for collective biological motion, Physical Review E52, 5297 (1995). 6
work page 1995
-
[24]
A. P. Solon and J. Tailleur, Revisiting the flocking tran- sition using active spins, Physical Review Letters111, 078101 (2013)
work page 2013
-
[25]
A. P. Solon and J. Tailleur, Flocking with discrete sym- metry: The two-dimensional active ising model, Physical Review E 92, 042119 (2015)
work page 2015
-
[26]
M. Mangeat, S. Chatterjee, R. Paul, and H. Rieger, Flocking with a q-fold discrete symmetry: Band-to-lane transition in the active potts model, Physical Review E 102, 042601 (2020)
work page 2020
-
[27]
S. Chatterjee, M. Mangeat, R. Paul, and H. Rieger, Flocking and reorientation transition in the 4-state active potts model, Europhysics Letters130, 66001 (2020)
work page 2020
-
[28]
F. Dittrich, T. Speck, and P. Virnau, Critical behavior in active lattice models of motility-induced phase sepa- ration, The European Physical Journal E44, 1 (2021)
work page 2021
- [29]
-
[30]
S. Chatterjee, M. Mangeat, and H. Rieger, Polar flocks with discretized directions: the active clock model ap- proaching the vicsek model, Europhysics Letters 138, 41001 (2022)
work page 2022
-
[31]
A. M. Menzel, Collective motion of binary self-propelled particle mixtures, Physical Review E85, 021912 (2012)
work page 2012
-
[32]
M. Fruchart, R. Hanai, P. B. Littlewood, and V. Vitelli, Non-reciprocal phase transitions, Nature 592, 363 (2021)
work page 2021
-
[33]
S. Chatterjee, M. Mangeat, C.-U. Woo, H. Rieger, and J. D. Noh, Flocking of two unfriendly species: The two- species vicsek model, Physical Review E 107, 024607 (2023)
work page 2023
-
[34]
O. Chepizhko and F. Peruani, Diffusion, Subdiffusion, and Trapping of Active Particles in Heterogeneous Me- dia, Physical Review Letters111, 160604 (2013)
work page 2013
-
[35]
S. Ro, Y. Kafri, M. Kardar, and J. Tailleur, Disorder- Induced Long-Ranged Correlations in Scalar Active Mat- ter, Physical Review Letters126, 048003 (2021)
work page 2021
-
[36]
Y. Duan, B. Mahault, Y.-q. Ma, X.-q. Shi, and H. Chaté, Breakdownofergodicityandself-averaginginpolarflocks with quenched disorder, Physical Review Letters 126, 178001 (2021)
work page 2021
-
[37]
D. Vahabli and T. Vicsek, Emergence of synchronised rotations in dense active matter with disorder, Commu- nications Physics 6, 56 (2023)
work page 2023
-
[38]
J. Toner and Y. Tu, Flocks, herds, and schools: A quan- titative theory of flocking, Physical Review E58, 4828 (1998)
work page 1998
-
[39]
G. Grégoire and H. Chaté, Onset of collective and cohe- sive motion, Physical Review Letters92, 025702 (2004)
work page 2004
- [40]
- [41]
-
[42]
H.Chaté,F.Ginelli,G.Grégoire,F.Peruani,andF.Ray- naud, Modeling collective motion: variations on the vic- sek model, The European Physical Journal B 64, 451 (2008)
work page 2008
- [43]
-
[44]
G. Baglietto and E. V. Albano, Nature of the order- disorder transition in the vicsek model for the collective motion of self-propelled particles, Physical Review E80, 050103 (2009)
work page 2009
-
[45]
T. Ihle, Invasion-wave-induced first-order phase transi- tion in systems of active particles, Physical Review E 88, 040303 (2013)
work page 2013
-
[46]
M. Kourbane-Houssene, C. Erignoux, T. Bodineau, and J. Tailleur, Exact Hydrodynamic Description of Active Lattice Gases, Physical Review Letters 120, 268003 (2018)
work page 2018
-
[47]
M. Scandolo, J. Pausch, and M. E. Cates, Active Ising Models of flocking: a field-theoretic approach, The Euro- pean Physical Journal E46, 103 (2023)
work page 2023
-
[48]
A. P. Solon, H. Chaté, and J. Tailleur, From phase to mi- crophase separation in flocking models: The essential role of nonequilibrium fluctuations, Physical Review Letters 114, 068101 (2015)
work page 2015
- [49]
-
[50]
B. Benvegnen, O. Granek, S. Ro, R. Yaacoby, H. Chaté, Y.Kafri,D.Mukamel,A.Solon,andJ.Tailleur,Metasta- bility of Discrete-Symmetry Flocks, Physical Review Let- ters 131, 218301 (2023)
work page 2023
-
[51]
We confirmed that the results are qualitatively the same under the parallel update and the random sequential up- date
-
[52]
See Supplemental Material
-
[53]
P. Muller, Glossary of terms used in physical organic chemistry (IUPAC Recommendations 1994), Pure and Applied Chemistry 66, 1077 (1994)
work page 1994
-
[54]
B. Benvegnen, H. Chaté, P. L. Krapivsky, J. Tailleur, and A.Solon,Flockinginonedimension:Astersandreversals, Physical Review E106, 054608 (2022)
work page 2022
-
[55]
The finite size scaling behavior lp = O(L−1 x ) has been confirmed in rectangular systems withLx ̸= Ly
-
[56]
J.-B. Caussin, A. Solon, A. Peshkov, H. Chaté, T. Daux- ois, J. Tailleur, V. Vitelli, and D. Bartolo, Emergent Spa- tial Structures in Flocking Models: A Dynamical System Insight, Physical Review Letters112, 148102 (2014)
work page 2014
-
[57]
A. P. Solon, J.-B. Caussin, D. Bartolo, H. Chaté, and J. Tailleur, Pattern formation in flocking models: A hy- drodynamic description, Physical Review E92, 062111 (2015)
work page 2015
-
[58]
F. Peruani and I. S. Aranson, Cold Active Motion: How Time-Independent Disorder Affects the Motion of Self- Propelled Agents, Physical Review Letters120, 238101 (2018)
work page 2018
-
[59]
P. Forgács, A. Libál, C. Reichhardt, and C. J. O. Re- ichhardt, Active matter shepherding and clustering in inhomogeneous environments, Physical Review E 104, 044613 (2021)
work page 2021
-
[60]
Motility-Induced Pinning in Flocking System with Discrete Symmetry
G. K. Sar, D. Ghosh, and K. O’Keeffe, Pinning in a sys- tem of swarmalators, Physical Review E 107, 024215 (2023). 1 Supplemental Materials for “Motility-Induced Pinning in Flocking System with Discrete Symmetry” Chul-Ung Woo and Jae Dong Noh Department of Physics, University of Seoul, Seoul 02504, Korea Appendix A: Supplementary animations • File 1_dropl...
work page 2023
-
[61]
The system is prepared to be in an ordered state with a PI of lengthl being implanted. Namely, all lattice sites are occupied by+ particles of mean densityρ0 except for those within a(2 × l) rectangle. They are occupied by ρ′ 0 (> ρ0) particles whose spin states are+ in the (1 × l) column on the left and− in the (1 × l) column on the right
-
[62]
A PI is identified as an interface between positively and negatively polarized domains. The occupation numbers at sites along the domain boundary are required to be larger than a cutoff valueρcutoff = 5ρ0
-
[63]
During simulations up to107MCS, we record the time trajectory{ln = l(t = tn)} of the PI length at discrete time steps tn = nτ0 with n ∈ Z and τ0 = 103. To reduce an artifact from short-time fluctuations,ln represents a running average over the time intervaltn−n0 < t < t n with n0 = 10
-
[64]
Given a trajectory{ln}, we countNl→l±1, the number of jumps inln from l to l ± 1, andTl, the total time span in which ln = l. The growth rateWg(l) and the shrink rateWs(l), per unit MCS, are given byNl→l+1/Tl and Nl→l−1/Tl, respectively, which are then averaged over more than103 independent trajectories. 2 0 5 10 15 20 l 10−7 10−5 10−3 10−1 W (l) (a) Wg W...
discussion (0)
Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.