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arxiv: 2402.11358 · v1 · submitted 2024-02-17 · ❄️ cond-mat.stat-mech

Dynamical crossovers and correlations in a harmonic chain of active particles

Pith reviewed 2026-05-24 03:10 UTC · model grok-4.3

classification ❄️ cond-mat.stat-mech
keywords active particlesharmonic chainsingle-file diffusionmean squared displacementGreen's functiontwo-point correlationsdynamical crossoversdisplacement distributions
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0 comments X

The pith

In a harmonic chain of active particles, tagged-particle mean-squared displacement crosses from ballistic to diffusive to single-file scaling.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper calculates the mean squared displacement of a tagged particle in a chain of active particles connected by harmonic springs. Depending on the stiffness of interactions and the persistence time of activity, the displacement shows three scaling regimes over time: ballistic at short times, diffusive at intermediate, and single-file diffusion at long times. Analytic expressions from Green's functions predict the crossover times between these regimes. Displacement distributions collapse onto master curves in each regime, transitioning from bimodal to Gaussian forms. Steady-state static and dynamic two-point displacement correlations are derived exactly and match simulation results, approaching equilibrium behavior for weak activity.

Core claim

In a harmonic chain of active Brownian particles, the tagged particle's mean-squared displacement displays crossovers between ballistic, diffusive, and single-file diffusion scalings, with the crossover times determined by the ratio of interaction stiffness and activity persistence. These scalings, along with the associated displacement distributions that exhibit data collapse and kurtosis changes, are obtained via Green's function methods. Steady-state two-point displacement correlations are also computed and shown to be consistent with simulations.

What carries the argument

Green's function formalism applied to the linearly coupled harmonic chain with active noise terms.

If this is right

  • The crossover times between scaling regimes are explicitly given by analytic expressions involving stiffness and persistence.
  • Displacement distributions pass through bimodal, unimodal with negative kurtosis, and long-tailed positive kurtosis before becoming Gaussian.
  • Two-point static and dynamic correlations converge to passive equilibrium results when persistence time is small.
  • The two-time stretch correlation extends to larger separations at later times.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • Similar crossover phenomena may appear in other one-dimensional active systems with confining potentials.
  • Experimental realization could use optically trapped colloids with active driving.
  • The framework might extend to nonlinear interactions or higher dimensions for broader active matter models.

Load-bearing premise

The particles interact only through linear harmonic springs and their activity is modeled as a persistent random force that fits into the linear response framework.

What would settle it

If numerical simulations of the harmonic active chain fail to show the predicted sequence of MSD scalings or the data collapse in distributions, the analytic expressions would be invalidated.

Figures

Figures reproduced from arXiv: 2402.11358 by Abhishek Dhar, Debasish Chaudhuri, Subhajit Paul.

Figure 1
Figure 1. Figure 1: FIG. 1. Plot of the space-time trajectories of [PITH_FULL_IMAGE:figures/full_fig_p003_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: we plot ∆𝑁/2(𝑡) for different choices of 𝛼 and 𝑘 for a chain of length 𝑁 = 128 with the boundary particles pinned locally by harmonic traps. Due to pinning, asymptotically, the MSD of the bulk particle saturates at time scales of order 𝜏sat ∼ 𝑁2/𝑘. Thus, for 𝑘 = 0.05, the saturation is barely visible in a plot up to 𝑡 = 105 . Before saturation, all the plots show a short-time ballistic regime ∆𝑁/2 ∼ 𝑡 2 an… view at source ↗
Figure 3
Figure 3. Figure 3: FIG. 3. (a)-(d) Plots of the time evolution of the distributions [PITH_FULL_IMAGE:figures/full_fig_p007_3.png] view at source ↗
Figure 5
Figure 5. Figure 5: FIG. 5. Plot of mean-squared-displacements ( [PITH_FULL_IMAGE:figures/full_fig_p008_5.png] view at source ↗
Figure 6
Figure 6. Figure 6: FIG. 6. (a)-(b) Simulation results for scaled correlation [PITH_FULL_IMAGE:figures/full_fig_p009_6.png] view at source ↗
Figure 7
Figure 7. Figure 7: FIG. 7. (a) Two-time correlations [PITH_FULL_IMAGE:figures/full_fig_p010_7.png] view at source ↗
Figure 8
Figure 8. Figure 8: FIG. 8. (a) Heat-map plot of the scaled [PITH_FULL_IMAGE:figures/full_fig_p015_8.png] view at source ↗
Figure 9
Figure 9. Figure 9: FIG. 9. (a) Plot of two-time correlations [PITH_FULL_IMAGE:figures/full_fig_p015_9.png] view at source ↗
read the original abstract

We explore the dynamics of a tracer in an active particle harmonic chain, investigating the influence of interactions. Our analysis involves calculating mean-squared displacements (MSD) and space-time correlations through Green's function techniques and numerical simulations. Depending on chain characteristics, i.e., different time scales determined by interaction stiffness and persistence of activity, tagged-particle MSD exhibit ballistic, diffusive, and single-file diffusion (SFD) scaling over time, with crossovers explained by our analytic expressions. Our results reveal transitions in bulk particle displacement distributions from an early-time bimodal to late-time Gaussian, passing through regimes of unimodal distributions with finite support and negative excess kurtosis and longer-tailed distributions with positive excess kurtosis. The distributions exhibit data collapse, aligning with ballistic, diffusive, and SFD scaling in the appropriate time regimes. However, at much longer times, the distributions become Gaussian. Finally, we derive expressions for steady-state static and dynamic two-point displacement correlations, consistent with simulations and converging to equilibrium results for small persistence. Additionally, the two-time stretch correlation extends to longer separation at later times, while the autocorrelation for the bulk particle shows diffusive scaling beyond the persistence time.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

0 major / 2 minor

Summary. The manuscript analyzes the dynamics of a tagged particle in a one-dimensional harmonic chain of active particles (modeled as a linear system with harmonic interactions and active forces). Using Green's function techniques, the authors derive closed-form expressions for the mean-squared displacement (MSD) that predict time-dependent crossovers among ballistic, diffusive, and single-file diffusion (SFD) regimes, controlled by the interaction stiffness and activity persistence time. They further report transitions in the displacement probability distributions (bimodal to unimodal with negative kurtosis to positive excess kurtosis to Gaussian) with corresponding data collapses, and derive steady-state static and dynamic two-point displacement correlations that match simulations and recover equilibrium results for small persistence.

Significance. If the derivations hold, the work supplies a solvable benchmark for active single-file systems, with explicit analytic MSD crossovers, distribution collapses, and correlation functions obtained from the linear Green's function. The parameter-free asymptotic analysis of the linear model and the reported consistency between analytics and numerics constitute clear strengths, providing falsifiable predictions for the location of crossovers and the form of correlations in active colloidal chains or analogous experimental setups.

minor comments (2)
  1. [Abstract] Abstract: the statement that 'distributions exhibit data collapse aligning with ballistic, diffusive, and SFD scaling' would be strengthened by an explicit statement of the scaling variables used for each regime (e.g., t/τ or x/√t).
  2. The manuscript states that the two-time stretch correlation 'extends to longer separation at later times' and that the bulk-particle autocorrelation shows 'diffusive scaling beyond the persistence time'; a brief remark on whether these scalings follow directly from the same Green's function or require additional approximations would improve clarity.

Simulated Author's Rebuttal

0 responses · 0 unresolved

We thank the referee for the positive summary, significance assessment, and recommendation of minor revision. No major comments were listed in the report, so we have no specific points to address. The manuscript appears ready for publication subject to any minor editorial changes the editor may request.

Circularity Check

0 steps flagged

No significant circularity

full rationale

The derivation proceeds from the linear Langevin equations of the harmonically coupled active particles by constructing the Green's function (or equivalent matrix exponential/Laplace-transform solutions) and extracting asymptotic regimes for MSD and correlations. These steps are direct consequences of the model definition and do not reduce to fitted parameters, self-citations, or ansatzes that presuppose the reported scalings or data collapses. The reported ballistic-diffusive-SFD crossovers and distribution behaviors are obtained by analyzing the closed-form expressions rather than by construction from the observables themselves.

Axiom & Free-Parameter Ledger

2 free parameters · 1 axioms · 0 invented entities

Review performed from abstract alone; concrete parameter values, integration details, and any additional modeling assumptions are not supplied.

free parameters (2)
  • interaction stiffness
    Sets one of the characteristic time scales separating ballistic, diffusive, and SFD regimes.
  • activity persistence time
    Sets the second characteristic time scale that controls the duration of ballistic motion and the approach to equilibrium correlations.
axioms (1)
  • domain assumption The particle chain is linear and interactions are strictly harmonic, permitting an exact Green's function solution.
    Invoked to obtain closed-form expressions for MSD and correlations.

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Reference graph

Works this paper leans on

78 extracted references · 78 canonical work pages

  1. [1]

    We obtain closed-form expressions for bulk particles to describe crossovers between ballistic, dif- fusive, and single-file-diffusion (SFD) scaling

    We obtain analytic expressions for MSD of individual particles. We obtain closed-form expressions for bulk particles to describe crossovers between ballistic, dif- fusive, and single-file-diffusion (SFD) scaling. For a finite chain with pinned boundaries, MSD saturates ear- lier and to smaller values for particles near the bound- ary

  2. [2]

    However, at late times 𝑡 ≫ [𝜏𝑘, 𝜏𝛼], all the distribu- tions become Gaussian (See Tables I and II)

    At short times, the displacement distributions of the central (bulk) particle show different characteristic fea- tures depending on persistence 𝛼−1 and interaction strength 𝑘, e.g., a bimodal distribution typical of free RTPs, unimodal but non-Gaussian distributions with fi- nite support (negative kurtosis), and distributions with extended tails longer th...

  3. [3]

    In the limit of large 𝛼, the results agree with equilibrium prediction

    The equal-time correlation functions 𝑆𝑥 𝑙,𝑚 and 𝑆𝑦 𝑙,𝑚 show departures from equilibrium over a separation 𝑣0/𝛼. In the limit of large 𝛼, the results agree with equilibrium prediction

  4. [4]

    The same point correlation 𝐶 𝑦 𝑁/2,𝑁/2(𝑡) remains unchanged over a time-scale 𝜏𝛼, and decays in an approximate dif- fusive manner 𝐶 𝑦 𝑁/2,𝑁/2(𝑡) ∼ 𝑡−1/2 for longer times

    The two-time and two-point correlation of local stretch spreads over larger distances for longer time gaps. The same point correlation 𝐶 𝑦 𝑁/2,𝑁/2(𝑡) remains unchanged over a time-scale 𝜏𝛼, and decays in an approximate dif- fusive manner 𝐶 𝑦 𝑁/2,𝑁/2(𝑡) ∼ 𝑡−1/2 for longer times. TABLE II. Same as Table I but for 𝛼 = 0.01 and 𝑘 = 1.0. Here the two time scal...

  5. [5]

    𝜏𝛼 ≪ 𝑡 ≪ 𝜏𝑘 → free, diffusive,

  6. [6]

    𝜏𝑘 ≪ 𝑡 ≪ 𝜏𝛼 → interacting, ballistic, (iii) long time: 𝑡 ≫ 𝜏𝛼, 𝜏𝑘 → single-file diffusion. Below, we discuss the scaling properties observed in the above-mentioned regimes in detail: (i) For 𝑡 ≪ 𝜏𝛼, 𝜏𝑘, the interaction is unimportant and the particles perform fully persistent motion. In this case, the leading contribution to the integral in Eq. (26) comes...

  7. [7]

    It is consistent with the original criterion of getting the intermediate regimen at 𝑡 > 𝜏 𝛼

    leading to 𝑡𝑐 1 ∼ 1/𝛼. It is consistent with the original criterion of getting the intermediate regimen at 𝑡 > 𝜏 𝛼. The crossover time 𝑡𝑐 2 from intermediate time effective diffusion to the late time single-file-diffusion can be obtained by using 2𝐷eff(𝑡𝑐

  8. [8]

    ≈ 2(𝐷eff/ √ 𝜋𝑘)(𝑡𝑐 2)1/2 to get 𝑡𝑐 2 ∼ 1/(𝜋𝑘). Finally, a pos- sibility arises in which the initial ballistic regime directly crosses over to the SFD regime at 𝑡𝑐 3 such that 𝑣2 0(𝑡𝑐 3)2 ≈ 2(𝐷eff/ √ 𝜋𝑘)(𝑡𝑐 3)1/2 to give 𝑡𝑐 3 ∼ (𝛼 √ 𝜋𝑘)−2/3. The con- dition for this direct crossover is 𝑡𝑐 3 < 𝑡 𝑐 1. As we now discuss, the above estimates show reasonable co...

  9. [9]

    Moreover, as discussed before, to observe the intermediate regime of simple diffusion, the criterion 𝜏𝛼 ≪ 𝑡 ≪ 𝜏𝑘 has to 7 FIG. 3. (a)-(d) Plots of the time evolution of the distributions 𝑃 (𝛿𝑥𝑁/2, 𝑡) of a bulk RTP for two sets of activity parameter 𝛼 and interaction 𝑘. (e)-(h) Data collapse at various dynamical regimes showing the scaling form 𝑃 (𝛿𝑥𝑁/2, 𝑡...

  10. [10]

    Active Matter and Beyond

    ≈ 𝑁/2 to obtain ˜𝐺 𝑁 2 𝑁 2 (𝜔) = | sin(𝑁 𝑞)|2 𝜔| sin 𝑞|2| sin(𝑁 + 1)𝑞|2 [︂ 𝜔| sin(𝑁 𝑞)|2 +Re {︂ 𝑖 √︀ 𝜔(4𝑖 + 𝜔) cos (︂𝑁 𝑞* 2 )︂ sin (︂𝑁 𝑞 2 )︂}︂]︂ . (39) In Fig. 5, we illustrate the difference in the dynamics be- tween bulk and boundary elements by plotting the MSDs FIG. 6. (a)-(b) Simulation results for scaled correlation 𝑆𝑥 𝑙,𝑚/𝑁 versus the scaled dista...

  11. [11]

    Chaté, F

    H. Chaté, F. Ginelli, G. Grégoire, F. Peruani, and F. Raynaud, Modeling collective motion: Variations on the Vicsek model, The Eur. Phys. J. B 64, 451 (2008)

  12. [12]

    Ramaswamy, The mechanics and statistics of active matter, Ann

    S. Ramaswamy, The mechanics and statistics of active matter, Ann. Rev. Cond. Mat. Phys. 1, 323 (2010)

  13. [13]

    Romanczuk, M

    P. Romanczuk, M. Bär, W. Ebeling, B. Lindner, and L. Schimansky-Geier, Active Brownian particles: From individual to collective stochastic dynamics, The Eur. Phys. J. Spec. Top. 202, 1 (2012)

  14. [14]

    M. C. Marchetti, J.-F. Joanny, S. Ramaswamy, T. B. Liverpool, J. Prost, M. Rao, and R. A. Simha, Hydrodynamics of soft active matter, Rev. Mod. Phys. 85, 1143 (2013)

  15. [15]

    Bechinger, R

    C. Bechinger, R. Di Leonardo, H. Löwen, C. Reichhardt, G. V olpe, and G. V olpe, Active particles in complex and crowded environments, Rev. Mod. Phys. 88, 045006 (2016)

  16. [16]

    D. Loi, S. Mossa, and L. F. Cugliandolo, Effective temperature of active matter, Phys. Rev. E 77, 051111 (2008)

  17. [17]

    Fodor, C

    E. Fodor, C. Nardini, M. E. Cates, J. Tailleur, P. Visco, and F. van Wijland, How far from equilibrium is active matter?, Phys. Rev. Lett. 117, 038103 (2016)

  18. [18]

    R. D. Astumian and P. Hänggi, Brownian motors, Physics Today 55, 33 (2002)

  19. [19]

    H. C. Berg and D. A. Brown, Chemotaxis in Escherichia coli analysed by three-dimensional tracking, Nature 239, 500 (1972)

  20. [20]

    H. S. Niwa, Self-organizing dynamic model of fish schooling, J. Theor. Biol. 171, 123 (1994)

  21. [21]

    Ginelli, F

    F. Ginelli, F. Peruani, M.-H. Pillot, H. Chaté, G. Theraulaz, and R. Bon, Intermittent collective dynamics emerge from conflicting imperatives in sheep herds, Proc. Natl. Acad. Sci. 112, 12729 (2015)

  22. [22]

    H. L. Devereux, C. R. Twomey, M. S. Turner, and S. Thutupalli, Whirligig beetles as corralled active Brownian particles, J. R. Soc. Interface 18, 10.1098/rsif.2021.0114 (2021)

  23. [23]

    Illien, R

    P. Illien, R. Golestanian, and A. Sen, ‘Fuelled’ motion: Phoretic motility and collective behaviour of active colloids, Chem. Soc. Rev.46, 5508 (2017)

  24. [24]

    W. F. Paxton, K. C. Kistler, C. C. Olmeda, A. Sen, S. K. St. Angelo, Y . Cao, T. E. Mallouk, P. E. Lammert, and V . H. Crespi, Catalytic nanomotors: Autonomous movement of striped nanorods, J. Am. Chem. Soc. 126, 13424 (2004)

  25. [25]

    Bricard, J

    A. Bricard, J. B. Caussin, N. Desreumaux, O. Dauchot, and D. Bartolo, Emergence of macroscopic directed motion in populations of motile colloids, Nature 503, 95 (2013)

  26. [26]

    Bricard, J.-B

    A. Bricard, J.-B. Caussin, D. Das, C. Savoie, V . Chikkadi, K. Shitara, O. Chepizhko, F. Peruani, D. Saintillan, and D. Bartolo, Emergent vortices in populations of colloidal rollers, Nat. Commun. 6, 7470 (2015). 17

  27. [27]

    Dauchot and V

    O. Dauchot and V . Démery, Dynamics of a Self-Propelled Particle in a Harmonic Trap, Phys. Rev. Lett.122, 068002 (2019)

  28. [28]

    Scholz, M

    C. Scholz, M. Engel, and T. Pöschel, Rotating robots move collectively and self-organize, Nat. Commun. 9, 931 (2018)

  29. [29]

    Narayan, S

    V . Narayan, S. Ramaswamy, N. Menon, T. Caspt, and T. Caspt, Long-Lived Giant Number Fluctuations, Science317, 105 (2007)

  30. [30]

    Kudrolli, G

    A. Kudrolli, G. Lumay, D. V olfson, and L. S. Tsimring, Swarming and Swirling in Self-Propelled Polar Granular Rods, Phys. Rev. Lett. 100, 058001 (2008)

  31. [31]

    Deseigne, O

    J. Deseigne, O. Dauchot, and H. Chaté, Collective Motion of Vibrated Polar Disks, Phys. Rev. Lett. 105, 098001 (2010)

  32. [32]

    Farhadi, S

    S. Farhadi, S. Machaca, J. Aird, B. O. Torres Maldonado, S. Davis, P. E. Arratia, and D. J. Durian, Dynamics and thermodynamics of air-driven active spinners, Soft Matter 14, 5588 (2018)

  33. [33]

    Stenhammar, A

    J. Stenhammar, A. Tiribocchi, R. J. Allen, D. Marenduzzo, and M. E. Cates, Continuum theory of phase separation kinetics for active Brownian particles, Phys. Rev. Lett. 111, 145702 (2013)

  34. [34]

    M. E. Cates and J. Tailleur, Motility-induced phase separation, Ann. Rev. Cond. Mat. Phys. 6, 219 (2015)

  35. [35]

    Tailleur and M

    J. Tailleur and M. E. Cates, Statistical mechanics of interacting run-and-tumble bacteria, Phys. Rev. Lett. 100, 218103 (2008)

  36. [36]

    U. Basu, S. N. Majumdar, A. Rosso, and G. Schehr, Active Brownian motion in two dimensions, Phys. Rev. E 98, 062121 (2018)

  37. [37]

    A. P. Solon, Y . Fily, A. Baskaran, M. E. Cates, Y . Kafri, M. Kardar, and J. Tailleur, Pressure is not a state function for generic active fluids, Nat. Phys. 11, 673 (2015)

  38. [38]

    A. Dhar, A. Kundu, S. N. Majumdar, S. Sabhapandit, and G. Schehr, Run-and-tumble particle in one-dimensional confining potentials: Steady-state, relaxation, and first-passage properties, Phys. Rev. E99, 032132 (2019)

  39. [39]

    Patel and D

    M. Patel and D. Chaudhuri, Exact moments and re-entrant transitions in the inertial dynamics of active Brownian particles, New J. Phys. 25, 123048 (2023)

  40. [40]

    F. J. Sevilla and L. A. Gómez Nava, Theory of diffusion of active particles that move at constant speed in two dimensions, Phys. Rev. E 90, 22130 (2014)

  41. [41]

    Großmann, F

    R. Großmann, F. Peruani, and M. Bär, Diffusion properties of active particles with directional reversal, New J. Phys. 18, 43009 (2016)

  42. [42]

    Kurzthaler, C

    C. Kurzthaler, C. Devailly, J. Arlt, T. Franosch, W. C. Poon, V . A. Martinez, and A. T. Brown, Probing the Spatiotemporal Dynamics of Catalytic Janus Particles with Single-Particle Tracking and Differential Dynamic Microscopy, Phys. Rev. Lett.121, 1 (2018)

  43. [43]

    Malakar, V

    K. Malakar, V . Jemseena, A. Kundu, K. V . Kumar, S. Sabhapandit, S. N. Majumdar, S. Redner, and A. Dhar, Steady state, relaxation and first-passage properties of a run-and-tumble particle in one-dimension, J. Stat. Mech.: Theor. and Expt. 2018, 043215 (2018)

  44. [44]

    U. Basu, S. N. Majumdar, A. Rosso, and G. Schehr, Long-time position distribution of an active Brownian particle in two dimensions, Phys. Rev. E 100, 1 (2019)

  45. [45]

    A. Shee, A. Dhar, and D. Chaudhuri, Active Brownian particles: Mapping to equilibrium polymers and exact computation of moments, Soft Matter 16, 4776 (2020)

  46. [46]

    Santra, U

    I. Santra, U. Basu, and S. Sabhapandit, Run-and-tumble particles in two dimensions: Marginal position distributions, Phys. Rev. E 101, 062120 (2020)

  47. [47]

    S. N. Majumdar and B. Meerson, Toward the full short-time statistics of an active Brownian particle on the plane, Phys. Rev. E 102, 022113 (2020)

  48. [48]

    Malakar, A

    K. Malakar, A. Das, A. Kundu, K. V . Kumar, and A. Dhar, Steady state of an active Brownian particle in a two-dimensional harmonic trap, Phys. Rev. E 101, 022610 (2020)

  49. [49]

    U. Basu, S. N. Majumdar, A. Rosso, S. Sabhapandit, and G. Schehr, Exact stationary state of a run-and-tumble particle with three internal states in a harmonic trap, J. Phys. A: Math. Theor. 53, 10.1088/1751-8121/ab6af0 (2020)

  50. [50]

    Santra and U

    I. Santra and U. Basu, Activity driven transport in harmonic chains, SciPost Phys. 13, 041 (2022)

  51. [51]

    Santra, U

    I. Santra, U. Basu, and S. Sabhapandit, Active Brownian motion with directional reversals, Phys. Rev. E 104, L012601 (2021)

  52. [52]

    Chaudhuri and A

    D. Chaudhuri and A. Dhar, Active Brownian particle in harmonic trap: Exact computation of moments, and re-entrant transition, J. Stat. Mech.: Theor. and Expt. 2021, 013207 (2021)

  53. [53]

    Shee and D

    A. Shee and D. Chaudhuri, Active Brownian motion with speed fluctuations in arbitrary dimensions: exact calculation of moments and dynamical crossovers, J. Stat. Mech.: Theor. Expt. 2022, 013201 (2022)

  54. [54]

    Shee and D

    A. Shee and D. Chaudhuri, Self-propulsion with speed and orientation fluctuation: Exact computation of moments and dynamical bista- bilities in displacement, Phys. Rev. E 105, 054148 (2022)

  55. [55]

    D. S. Dean, S. N. Majumdar, and H. Schawe, Position distribution in a generalized run-and-tumble process, Phys. Rev. E 103, 012130 (2021)

  56. [56]

    A. B. Slowman, M. R. Evans, and R. A. Blythe, Exact solution of two interacting run-and-tumble random walkers with finite tumble duration, J. Phys. A: Math. and Theor. 50, 375601 (2017)

  57. [57]

    A. Das, A. Dhar, and A. Kundu, Gap statistics of two interacting run and tumble particles in one dimension, J. Phys. A: Math. and Theor. 53, 345003 (2020)

  58. [58]

    Le Doussal, S

    P. Le Doussal, S. N. Majumdar, and G. Schehr, Noncrossing run-and-tumble particles on a line, Phys. Rev. E 100, 012113 (2019)

  59. [59]

    A. B. Slowman, M. R. Evans, and R. A. Blythe, Jamming and attraction of interacting run-and-tumble random walkers, Phys. Rev. Lett. 116, 218101 (2016)

  60. [60]

    Kourbane-Houssene, C

    M. Kourbane-Houssene, C. Erignoux, T. Bodineau, and J. Tailleur, Exact hydrodynamic description of active lattice gases, Phys. Rev. Lett. 120, 268003 (2018)

  61. [61]

    S. Put, J. Berx, and C. Vanderzande, Non-Gaussian anomalous dynamics in systems of interacting run-and-tumble particles, J. Stat. Mech.: Theor. and Expt. 2019, 123205 (2019)

  62. [62]

    Dolai, A

    P. Dolai, A. Das, A. Kundu, C. Dasgupta, A. Dhar, and K. V . Kumar, Universal scaling in active single-file dynamics, Soft Matter 16, 7077 (2020)

  63. [63]

    Singh and A

    P. Singh and A. Kundu, Crossover behaviours exhibited by fluctuations and correlations in a chain of active particles, J. Phys. A: Math. and Theor. 54, 305001 (2021). 18

  64. [64]

    Banerjee, R

    T. Banerjee, R. L. Jack, and M. E. Cates, Tracer dynamics in one dimensional gases of active or passive particles, J. Stat. Mech.: Theor. and Expt. 2022, 013209 (2022)

  65. [65]

    Touzo, P

    L. Touzo, P. L. Doussal, and G. Schehr, Interacting, running and tumbling: The active Dyson Brownian motion, Europhys. Lett. 142, 61004

  66. [66]

    Agranov, S

    T. Agranov, S. Ro, Y . Kafri, and V . Lecomte, Macroscopic fluctuation theory and current fluctuations in active lattice gases, SciPost Phys. 14, 045 (2023)

  67. [67]

    collisions

    T. E. Harris, Diffusion with “collisions” between particles, Journal of Applied Probability 2, 323 (1965)

  68. [68]

    Kollmann, Single-file diffusion of atomic and colloidal systems: Asymptotic laws, Phys

    M. Kollmann, Single-file diffusion of atomic and colloidal systems: Asymptotic laws, Phys. Rev. Lett. 90, 180602 (2003)

  69. [69]

    Lizana and T

    L. Lizana and T. Ambjörnsson, Single-file diffusion in a box, Phys. Rev. Lett. 100, 200601 (2008)

  70. [70]

    Hegde, S

    C. Hegde, S. Sabhapandit, and A. Dhar, Universal large deviations for the tagged particle in single-file motion, Phys. Rev. Lett. 113, 120601 (2014)

  71. [71]

    P. L. Krapivsky, K. Mallick, and T. Sadhu, Tagged particle in single-file diffusion, J. Stat. Phys.160, 885 (2015)

  72. [72]

    Q.-H. Wei, C. Bechinger, and P. Leiderer, Single-file diffusion of colloids in one-dimensional channels, Science287, 625 (2000)

  73. [73]

    C. Lutz, M. Kollmann, and C. Bechinger, Single-file diffusion of colloids in one-dimensional channels, Phys. Rev. Lett. 93, 026001 (2004)

  74. [74]

    Dhar, Heat transport in low-dimensional systems, Advances in Physics 57, 457 (2008)

    A. Dhar, Heat transport in low-dimensional systems, Advances in Physics 57, 457 (2008)

  75. [75]

    G. Y . Hu and R. F. O’Connell, Analytical inversion of symmetric tridiagonal matrices, J. Phys. A: Math. Gen.29, 1511 (1996)

  76. [76]

    Lizana, T

    L. Lizana, T. Ambjörnsson, A. Taloni, E. Barkai, and M. A. Lomholt, Foundation of fractional Langevin equation: Harmonization of a many-body problem, Phys. Rev. E 81, 051118 (2010)

  77. [77]

    Dhar, Heat conduction in the disordered harmonic chain revisited, Phys

    A. Dhar, Heat conduction in the disordered harmonic chain revisited, Phys. Rev. Lett. 86, 5882 (2001)

  78. [78]

    A. Dhar, O. Narayan, A. Kundu, and K. Saito, Linear-response formula for finite-frequency thermal conductance of open systems, Phys. Rev. E 83, 011101 (2011)