Superdiffusion resilience in Heisenberg Chains with 2D interactions on a quantum processor
Pith reviewed 2026-05-22 23:38 UTC · model grok-4.3
The pith
SU(2)-preserving 2D interactions show highest resilience to superdiffusion breakdown in Heisenberg chains.
A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.
Core claim
By increasing the strength of various 2D interactions from zero in an otherwise 1D superdiffusive Heisenberg model, the SU(2) preserving interaction maintains superdiffusive spin transport to the highest coupling value among those studied. Quantum hardware reproduces the theoretical resilience ordering with high accuracy, and scattering analysis explains why certain 2D terms disrupt transport less than others. These results indicate conditions under which superdiffusive scaling can persist in two-dimensional lattices.
What carries the argument
Scattering coefficients of excitations off the added 2D interactions within otherwise 1D chains, which set the relative strength at which each term destroys superdiffusion.
If this is right
- The SU(2) preserving interaction allows superdiffusive spin transport to survive at finite 2D coupling strengths.
- Quantum processors can faithfully rank the resilience of different integrability-breaking terms.
- Superdiffusive scaling may be observable in 2D lattices when the dominant perturbation preserves SU(2) symmetry.
- The breakdown threshold of superdiffusion can be tuned by choosing the symmetry properties of added interactions.
Where Pith is reading between the lines
- Real materials whose dominant couplings are close to SU(2) symmetric could exhibit extended superdiffusive regimes before crossing over to diffusion.
- The scattering-coefficient approach could be applied to classify resilience in other integrable spin chains or higher-dimensional generalizations.
- Variants of materials like KCuF3 engineered with stronger SU(2) character might serve as test beds for 2D superdiffusion.
Load-bearing premise
The quantum hardware implements the generalized 2D Floquet model without decoherence, gate errors, or readout noise that would reorder the observed resilience of different interactions.
What would settle it
An exact calculation or clean experiment showing that all studied 2D interactions produce identical scattering coefficients and therefore identical breakdown thresholds.
Figures
read the original abstract
Observing superdiffusive scaling in the spin transport of the integrable 1D Heisenberg model is one of the key discoveries in non-equilibrium quantum many-body physics. Despite this remarkable theoretical development and the subsequent experimental observation of the phenomena in KCuF$_3$, real materials are often imperfect and contain integrability breaking interactions. Understanding the effect of such terms on the superdiffusion is crucial in identifying connections to such materials. Current quantum hardware has already ascertained its utility in studying such non-equilibrium phenomena by simulating the superdiffusion of the 1D Heisenberg model. In this work, we perform a quantum simulation of the superdiffusion breakdown by generalizing the superdiffusive Floquet-type 1D Heisenberg model to a general 2D model. We comprehensively study the effect of different 2D interactions on the superdiffusion breakdown by tuning up their strength from zero, corresponding to the 1D Heisenberg chain, to finite nonzero values. We observe that certain 2D interactions are more resilient against superdiffusion breakdown than others and that the $SU(2)$ preserving 2D interaction has the highest resilience among all the 2D interactions we study. Importantly, this observed resilience has direct implications for sustaining superdiffusive spin transport in two-dimensional lattices. We reason out the relative resilience against the superdiffusion breakdown through an analysis of the scattering coefficients off the 2D interaction in otherwise 1D chains. The relative resilience of different interaction types against superdiffusion breakdown was also captured in quantum hardware with remarkable accuracy, further establishing the current quantum hardware's applicability in simulating interesting non-equilibrium quantum many-body phenomena.
Editorial analysis
A structured set of objections, weighed in public.
Referee Report
Summary. The paper generalizes the integrable 1D Heisenberg Floquet model to include tunable 2D interactions and uses quantum-processor simulations to study how these terms break superdiffusive spin transport. It reports that the SU(2)-preserving 2D interaction shows the highest resilience to superdiffusion breakdown, with a clear ordering across interaction types; this ordering is rationalized by scattering-coefficient analysis in the 1D limit and is reproduced on hardware, with implications for 2D lattices.
Significance. If the hardware ordering is robust, the work supplies a concrete link between specific integrability-breaking perturbations and the stability of superdiffusion, together with a scattering-based explanation that is independent of fitting parameters. The successful hardware reproduction also adds to the evidence that current quantum processors can address non-equilibrium many-body questions beyond simple 1D chains.
major comments (1)
- [Hardware validation section] Hardware validation section: the claim that the resilience ordering is reproduced 'with remarkable accuracy' on the processor does not include a quantitative assessment of how gate errors, decoherence, or readout noise—whose strength can depend on the symmetry properties of the added 2D term—shift the extracted diffusion exponents or alter the relative ranking. Because the central claim rests on the hardware data faithfully reflecting unitary dynamics, this omission is load-bearing.
minor comments (2)
- [Abstract] The abstract states that the SU(2)-preserving interaction 'has the highest resilience' but does not define the quantitative resilience metric (e.g., critical interaction strength at which the diffusion exponent drops below a threshold) until later in the text; an early definition would improve readability.
- [Theoretical analysis] Scattering-coefficient derivation: the text presents the coefficients as explaining the ordering, yet the explicit formulas and the limit in which they are computed are not cross-referenced to a numbered equation or appendix, making it hard to verify independence from fitting parameters.
Simulated Author's Rebuttal
We thank the referee for their careful reading of the manuscript and for highlighting an important point regarding the hardware validation. We address the major comment below.
read point-by-point responses
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Referee: [Hardware validation section] Hardware validation section: the claim that the resilience ordering is reproduced 'with remarkable accuracy' on the processor does not include a quantitative assessment of how gate errors, decoherence, or readout noise—whose strength can depend on the symmetry properties of the added 2D term—shift the extracted diffusion exponents or alter the relative ranking. Because the central claim rests on the hardware data faithfully reflecting unitary dynamics, this omission is load-bearing.
Authors: We agree that a quantitative assessment of hardware noise effects is necessary to substantiate the claim of faithful reproduction of the resilience ordering. In the revised manuscript we will add an error analysis subsection that models gate errors, decoherence, and readout noise using hardware-calibrated parameters. For each 2D interaction type we will propagate these noise channels through the circuit and recompute the extracted diffusion exponents, explicitly checking whether the relative ordering is preserved. We will also examine whether symmetry properties of the 2D terms lead to measurably different noise strengths and report the resulting uncertainty bands on the exponents. This addition will directly address the load-bearing concern that the observed ordering might be an artifact of symmetry-dependent noise. revision: yes
Circularity Check
No significant circularity in derivation chain
full rationale
The paper's claims rest on direct quantum-hardware simulation of the generalized 2D Floquet Heisenberg model (tuning 2D interaction strength from the 1D limit) together with a separate scattering-coefficient analysis performed in the ideal 1D-chain limit. Neither step is shown to reduce to a fitted parameter renamed as a prediction, a self-definitional loop, or a load-bearing self-citation whose content is itself unverified. The hardware results are presented as external reproduction rather than as the sole justification for the theoretical ordering, and no ansatz or uniqueness theorem is imported from prior author work in a manner that collapses the argument. The derivation therefore remains self-contained against the stated inputs.
Axiom & Free-Parameter Ledger
axioms (1)
- domain assumption The integrable 1D Heisenberg model exhibits superdiffusive spin transport
Forward citations
Cited by 1 Pith paper
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Benchmarking quantum simulation with neutron-scattering experiments
A 50-qubit quantum processor produces dynamical structure factors for KCuF3 that quantitatively match neutron-scattering measurements of its spinon spectrum.
Reference graph
Works this paper leans on
- [1]
-
[2]
A.Francis,J.K.Freericks,andA.F.Kemper,Quantumcompu- tation of magnon spectra, Phys. Rev. B101, 014411 (2020)
work page 2020
-
[3]
E.Campbell,Aseriesoffast-pacedadvancesinQuantumError Correction, Nature Reviews Physics6, 160 (2024)
work page 2024
-
[4]
Y. Kim, A. Eddins, S. Anand, K. X. Wei, E. van den Berg, S. Rosenblatt, H. Nayfeh, Y. Wu, M. Zaletel, K. Temme, and A. Kandala, Evidence for the utility of quantum computing be- fore fault tolerance, Nature618, 500 (2023)
work page 2023
-
[5]
A. Miessen, D. J. Egger, I. Tavernelli, and G. Mazzola, Bench- marking Digital Quantum Simulations Above Hundreds of Qubits Using Quantum Critical Dynamics, PRX Quantum5, 040320 (2024)
work page 2024
-
[6]
J.Robledo-Moreno,M.Motta,H.Haas,A.Javadi-Abhari,P.Ju- rcevic, W. Kirby, S. Martiel, K. Sharma, S. Sharma, T. Shi- rakawa, I. Sitdikov, R.-Y. Sun, K. J. Sung, M. Takita, M. C. Tran, S. Yunoki, and A. Mezzacapo, Chemistry Beyond Ex- act Solutions on a Quantum-Centric Supercomputer (2024), arXiv:2405.05068 [quant-ph]
- [7]
- [8]
-
[9]
H. Yu, Y. Zhao, and T.-C. Wei, Simulating large-size quantum spin chains on cloud-based superconducting quantum comput- ers, Phys. Rev. Res.5, 013183 (2023)
work page 2023
-
[10]
R. Livi and P. Politi,Nonequilibrium Statistical Physics: A Modern Perspective(Cambridge University Press, 2017)
work page 2017
-
[11]
T. Yoshimura and L. Sá, Robustness of quantum chaos and anomalous relaxation in open quantum circuits, Nature Com- munications15, 9808 (2024)
work page 2024
-
[12]
A. Chan, S. Shivam, D. A. Huse, and A. De Luca, Many-body quantum chaos and space-time translational invariance, Nature Communications13, 7484 (2022)
work page 2022
- [13]
- [14]
-
[15]
M. Žnidarič, Spin transport in a one-dimensional anisotropic heisenbergmodel,PhysicalReviewLetters106,220601(2011)
work page 2011
-
[16]
Sirker, Spin diffusion and the anisotropic spin-1 2 Heisenberg chain, Phys
J. Sirker, Spin diffusion and the anisotropic spin-1 2 Heisenberg chain, Phys. Rev. B73, 224424 (2006)
work page 2006
-
[18]
S. Gopalakrishnan, D. A. Huse, V. Khemani, and R. Vasseur, Hydrodynamics of operator spreading and quasiparticle diffu- sion in interacting integrable systems, Phys. Rev. B98, 220303 (2018)
work page 2018
-
[19]
S. Gopalakrishnan and R. Vasseur, Kinetic Theory of Spin Dif- fusion and Superdiffusion in𝑋𝑋𝑍Spin Chains, Phys. Rev. Lett.122, 127202 (2019)
work page 2019
-
[20]
M.DupontandJ.E.Moore,Universalspindynamicsininfinite- temperature one-dimensional quantum magnets, Phys. Rev. B 101, 121106 (2020)
work page 2020
-
[21]
M. Ljubotina, M. Znidaric, and T. Prosen, Spin diffusion from aninhomogeneousquenchinanintegrablesystem,NatureCom- munications8, 10.1038/ncomms16117 (2017)
-
[22]
J. De Nardis, D. Bernard, and B. Doyon, Hydrodynamic Diffu- sioninIntegrableSystems,Phys.Rev.Lett.121,160603(2018)
work page 2018
-
[23]
B. Ware, S. Gopalakrishnan, and R. Vasseur, Nonlinear Fluc- tuating Hydrodynamics for Kardar-Parisi-Zhang Scaling in Isotropic Spin Chains, Phys. Rev. Lett.131, 197102 (2023)
work page 2023
-
[24]
M. Kulkarni and A. Lamacraft, Finite-temperature dynamical structure factor of the one-dimensional Bose gas: From the Gross-PitaevskiiequationtotheKardar-Parisi-Zhanguniversal- ity class of dynamical critical phenomena, Phys. Rev. A88, 021603 (2013)
work page 2013
-
[25]
S. G. Das, A. Dhar, K. Saito, C. B. Mendl, and H. Spohn, Nu- merical test of hydrodynamic fluctuation theory in the Fermi- Pasta-Ulam chain, Phys. Rev. E90, 012124 (2014)
work page 2014
-
[26]
A. Das, K. Damle, A. Dhar, D. A. Huse, M. Kulkarni, C. B. Mendl, and H. Spohn, Nonlinear Fluctuating Hydrodynamics fortheClassicalXXZSpinChain,JournalofStatisticalPhysics 180, 238–262 (2019)
work page 2019
- [27]
-
[28]
A.Nahum,S.Vijay,andJ.Haah,OperatorSpreadinginRandom Unitary Circuits, Phys. Rev. X8, 021014 (2018)
work page 2018
-
[29]
D.A.RowlandsandA.Lamacraft,Noisycoupledqubits: Oper- atorspreadingandtheFredrickson-Andersenmodel,Phys.Rev. B98, 195125 (2018)
work page 2018
-
[30]
M. Dupont, N. E. Sherman, and J. E. Moore, Spatiotempo- ral Crossover between Low- and High-Temperature Dynamical Regimes in the Quantum Heisenberg Magnet, Physical Review Letters127, 10.1103/physrevlett.127.107201 (2021)
-
[31]
A.Scheie,N.E.Sherman,M.Dupont,S.E.Nagler,M.B.Stone, G. E. Granroth, J. E. Moore, and D. A. Tennant, Detection of Kardar–Parisi–Zhang hydrodynamics in a quantum Heisenberg spin-1/2 chain, Nature Physics17, 726–730 (2021)
work page 2021
-
[33]
M. K. Joshi, F. Kranzl, A. Schuckert, I. Lovas, C. Maier, R. Blatt, M. Knap, and C. F. Roos, Observing emergent hy- drodynamics in a long-range quantum magnet, Science376, 720–724 (2022)
work page 2022
-
[34]
N. Keenan, N. F. Robertson, T. Murphy, S. Zhuk, and J. Goold, Evidence of Kardar-Parisi-Zhang scaling on a digital quantum simulator, npj Quantum Information9, 10.1038/s41534-023- 00742-4 (2023)
-
[35]
E. Rosenberg, T. I. Andersen, R. Samajdar, A. Petukhov, J. C. Hoke, D. Abanin, A. Bengtsson, I. K. Drozdov, C. Erick- son, P. V. Klimov, X. Mi, A. Morvan, M. Neeley, C. Neill, R. Acharya, R. Allen, K. Anderson, M. Ansmann, F. Arute, K. Arya, A. Asfaw, J. Atalaya, J. C. Bardin, A. Bilmes, G. Bor- 9 toli, A. Bourassa, J. Bovaird, L. Brill, M. Broughton, B. ...
work page 2024
-
[36]
Z. Krajnik and T. Prosen, Kardar–Parisi–Zhang Physics in Integrable Rotationally Symmetric Dynamics on Discrete Space–TimeLattice,JournalofStatisticalPhysics179,110–130 (2020)
work page 2020
-
[37]
M. Ljubotina, L. Zadnik, and T. c. v. Prosen, Ballistic Spin TransportinaPeriodicallyDrivenIntegrableQuantumSystem, Phys. Rev. Lett.122, 150605 (2019)
work page 2019
-
[38]
J. Richter and A. Pal, Simulating Hydrodynamics on Noisy Intermediate-Scale Quantum Devices with Random Circuits, Phys. Rev. Lett.126, 230501 (2021)
work page 2021
-
[39]
F.D.M.Haldane,ExcitationspectrumofageneralisedHeisen- berg ferromagnetic spin chain with arbitrary spin, Journal of Physics C: Solid State Physics15, L1309 (1982)
work page 1982
-
[40]
Slow crossover from superdiffusion to diffusion in isotropic spin chains, author = McCarthy, Catherine and Gopalakrish- nan, Sarang and Vasseur, Romain, Phys. Rev. B110, L180301 (2024)
work page 2024
-
[41]
A.J.McRobertsandR.Moessner,ParametricallyLongLifetime ofSuperdiffusioninNonintegrableSpinChains,Phys.Rev.Lett. 133, 256301 (2024)
work page 2024
- [42]
-
[43]
K. Wang and J. E. Moore, Breakdown of superdiffusion in perturbed quantum integrable spin chains and ladders (2025), arXiv:2501.08866 [cond-mat.stat-mech]
-
[44]
Y.-H. Shi, Z.-H. Sun, Y.-Y. Wang, Z.-A. Wang, Y.-R. Zhang, W.-G. Ma, H.-T. Liu, K. Zhao, J.-C. Song, G.-H. Liang, Z.-Y. Mei, J.-C. Zhang, H. Li, C.-T. Chen, X. Song, J. Wang, G. Xue, H.Yu,K.Huang,Z.Xiang,K.Xu,D.Zheng,andH.Fan,Prob- ingspinhydrodynamicsonasuperconductingquantumsimula- tor, Nature Communications15, 10.1038/s41467-024-52082-2 (2024)
-
[45]
D. Wei, A. Rubio-Abadal, B. Ye, F. Machado, J. Kemp, K. Srakaew, S. Hollerith, J. Rui, S. Gopalakrishnan, N. Y. Yao, I. Bloch, and J. Zeiher, Quantum gas microscopy of Kardar-Parisi-Zhang superdiffusion, Science376, 716 (2022), https://www.science.org/doi/pdf/10.1126/science.abk2397
-
[46]
C.Chen,Y.Chen,andX.Wang,Superdiffusivetoballistictrans- portinnonintegrableRydbergsimulator,npjQuantumInforma- tion10, 10.1038/s41534-024-00884-z (2024)
-
[47]
M. Vanicat, L. Zadnik, and T. c. v. Prosen, Integrable Trotteri- zation: Local Conservation Laws and Boundary Driving, Phys. Rev. Lett.121, 030606 (2018)
work page 2018
- [48]
-
[49]
M. Ljubotina, M. Znidaric, and T. Prosen, Kardar-Parisi-Zhang Physics in the Quantum Heisenberg Magnet, Physical Review Letters122, 10.1103/physrevlett.122.210602 (2019)
-
[50]
R. Kubo, M. Toda, and N. Hashitsume,Statistical Physics II. Nonequilibrium Statistical Mechanics. 2nd Edition(Springer- Verlag, 1991)
work page 1991
-
[51]
X.Zotos,F.Naef,andP.Prelovsek,Transportandconservation laws, Phys. Rev. B55, 11029 (1997)
work page 1997
-
[52]
N. Ezzell, B. Pokharel, L. Tewala, G. Quiroz, and D. A. Lidar, Dynamical decoupling for superconducting qubits: A perfor- mancesurvey,PhysicalReviewApplied20,10.1103/physrevap- plied.20.064027 (2023)
-
[53]
B. Pokharel, N. Anand, B. Fortman, and D. A. Lidar, Demon- stration of fidelity improvement using dynamical decoupling with superconducting qubits, Physical review letters121, 220502 (2018)
work page 2018
- [54]
-
[55]
E.vandenBerg,Z.K.Minev,A.Kandala,andK.Temme,Prob- abilistic error cancellation with sparse Pauli–Lindblad models on noisy quantum processors, Nature Physics19, 1116–1121 (2023)
work page 2023
-
[56]
Z. Cai, R. Babbush, S. C. Benjamin, S. Endo, W. J. Hug- gins, Y. Li, J. R. McClean, and T. E. O’Brien, Quantum error mitigation, Reviews of Modern Physics95, 10.1103/revmod- phys.95.045005 (2023)
-
[57]
D.Bultrini,M.H.Gordon,P.Czarnik,A.Arrasmith,M.Cerezo, P.J.Coles,andL.Cincio,Unifyingandbenchmarkingstate-of- the-art quantum error mitigation techniques, Quantum7, 1034 (2023)
work page 2023
-
[58]
S. N. Filippov, S. Maniscalco, and G. García-Pérez, Scalability of quantum error mitigation techniques: from utility to advan- tage (2024), arXiv:2403.13542 [quant-ph]. 10 Appendix A: Quantum Algorithm: Implementation details The infinite temperature𝑍𝑍spin spin auto-correlation function on site𝑖is given by 𝐶 𝑧𝑧 𝑖𝑖 (𝑡) =Tr(𝜎 𝑖 𝑧(0)𝜎𝑖 𝑧(𝑡))∕2𝑛 (A1) where𝑛is...
-
[59]
Trotterization To compute the expectation of𝜎𝑖 𝑧(𝑡)in Eq A2, we evolve the initial state|Ψ𝑅,𝑖⟩as described in Eq 4. This involves the application of two-qubit gates at𝑟,𝑔, and𝑏-type bonds (Fig 1) for the two local Hamiltonian terms acting on them. If a two-local Hamiltonain,ℎ, acts on sites𝑘and𝑙with interaction given by𝐽ℎ( 𝜆𝑥 4 𝜎𝑘 𝑥𝜎𝑙 𝑥 + 𝜆𝑦 4 𝜎𝑘 𝑦 𝜎𝑙 𝑦 +...
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