Stochastic sampling of operator growth dynamics
Source abstract
Abstract
We put forward a Monte Carlo algorithm that samples the Euclidean time operator growth dynamics at infinite temperature. Crucially, our approach is free from the numerical sign problem for a broad family of quantum many-body spin systems, allowing for numerically exact and unbiased calculations. We apply this methodological headway to study the high-frequency dynamics of the mixed-field quantum Ising model in one and two dimensions. The resulting quantum dynamics display rapid thermalization, supporting the recently proposed operator growth hypothesis. Physically, our findings correspond to an exponential falloff of generic response functions of local correlators at large frequencies. Remarkably, our calculations are sufficiently sensitive to detect subtle logarithmic corrections of the hypothesis in one dimension. In addition, in two dimensions, we uncover a nontrivial dynamical crossover between two large-frequency decay rates. Last, we reveal spatiotemporal scaling laws associated with operator growth, which are found to be strongly affected by boundary contributions.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Quantum many-body systems · Model Reduction and Neural Networks · Tensor decomposition and applications
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Hebrew University of Jerusalem
Laboratoire de Physique de l'École normale supérieure
Université PSL
Sorbonne Université
Université Paris Cité
Funding
Israel Science Foundation · United States - Israel Binational Science Foundation · Israel Academy of Sciences and Humanities · Hebrew University of Jerusalem · France-Berkeley Fund
References (55)
Show source-provided references
1. 10.1103/PhysRevA.94.04030210.1103/PhysRevA.94.040302 ↗
2. 10.1103/PhysRevX.8.02101410.1103/PhysRevX.8.021014 ↗
3. 10.1103/PhysRevX.8.03105710.1103/PhysRevX.8.031057 ↗
4. 10.1103/PhysRevB.98.14430410.1103/PhysRevB.98.144304 ↗
5. 10.1103/PhysRevB.98.22030310.1103/PhysRevB.98.220303 ↗
6. 10.1007/JHEP08(2019)01210.1007/JHEP08(2019)012 ↗
7. 10.1007/JHEP06(2018)12210.1007/JHEP06(2018)122 ↗
8. 10.1038/s41567-019-0712-410.1038/s41567-019-0712-4 ↗
9. 10.1038/s41567-018-0295-510.1038/s41567-018-0295-5 ↗
10. 10.1103/PhysRevA.43.204610.1103/PhysRevA.43.2046 ↗
11. 10.1103/PhysRevE.50.88810.1103/PhysRevE.50.888 ↗
12. 10.1080/00018732.2016.119813410.1080/00018732.2016.1198134 ↗
13. 10.1103/RevModPhys.91.02100110.1103/RevModPhys.91.021001 ↗
14. 10.1146/annurev-conmatphys-031214-01472610.1146/annurev-conmatphys-031214-014726 ↗
15. 10.1088/1126-6708/2008/10/06510.1088/1126-6708/2008/10/065 ↗
16. 10.1007/JHEP03(2014)06710.1007/JHEP03(2014)067 ↗
17. 10.1007/JHEP08(2016)10610.1007/JHEP08(2016)106 ↗
18. 10.1103/PRXQuantum.4.01032010.1103/PRXQuantum.4.010320 ↗
19. 10.1103/PhysRevX.12.03101310.1103/PhysRevX.12.031013 ↗
20. 10.1103/PhysRevE.90.02291010.1103/PhysRevE.90.022910 ↗
21. 10.1103/PhysRevX.9.04101710.1103/PhysRevX.9.041017 ↗
22. 10.1103/PhysRevLett.123.23060610.1103/PhysRevLett.123.230606 ↗
23. 10.1007/JHEP03(2022)13310.1007/JHEP03(2022)133 ↗
24. 10.1007/JHEP10(2019)26410.1007/JHEP10(2019)264 ↗
25. 10.1007/JHEP06(2021)06210.1007/JHEP06(2021)062 ↗
26. 10.1007/JHEP07(2022)15110.1007/JHEP07(2022)151 ↗
27. 10.1103/PhysRevResearch.2.04323410.1103/PhysRevResearch.2.043234 ↗
28. 10.1103/PhysRevD.104.L08170210.1103/PhysRevD.104.L081702 ↗
29. 10.1007/JHEP06(2024)06610.1007/JHEP06(2024)066 ↗
30. 10.1007/JHEP03(2021)01410.1007/JHEP03(2021)014 ↗
31. 10.1103/PhysRevX.10.02104410.1103/PhysRevX.10.021044 ↗
32. 10.1007/s00220-017-2930-x10.1007/s00220-017-2930-x ↗
33. 10.1103/PhysRevLett.111.12720510.1103/PhysRevLett.111.127205 ↗
34. 10.1103/PhysRevLett.100.17640310.1103/PhysRevLett.100.176403 ↗
35. 10.1007/JHEP08(2023)09910.1007/JHEP08(2023)099 ↗
36. 10.1007/JHEP05(2022)17410.1007/JHEP05(2022)174 ↗
37. 10.1103/PhysRevE.106.01415210.1103/PhysRevE.106.014152 ↗
38. 10.1063/1.493620910.1063/1.4936209 ↗
39. 10.1088/1751-8121/abe77c10.1088/1751-8121/abe77c ↗
40. 10.1103/PhysRevB.43.595010.1103/PhysRevB.43.5950 ↗
41. 10.1063/1.351890010.1063/1.3518900 ↗
42. 10.1103/PhysRevLett.86.205010.1103/PhysRevLett.86.2050 ↗
43. 10.1103/PhysRevLett.90.12020110.1103/PhysRevLett.90.120201 ↗
44. 10.1103/PhysRevE.78.06770110.1103/PhysRevE.78.067701 ↗
45. 10.1007/BF0164513410.1007/BF01645134 ↗
46. 10.1103/PhysRevLett.114.14040110.1103/PhysRevLett.114.140401 ↗
47. 10.1103/PhysRevE.104.03411210.1103/PhysRevE.104.034112 ↗
48. 10.1103/PhysRevB.81.05451210.1103/PhysRevB.81.054512 ↗
49. 10.1103/PhysRevB.109.03511710.1103/PhysRevB.109.035117 ↗
50. 10.1063/1.34585910.1063/1.345859 ↗
51. V. Viswanath · 2008
52. 10.1103/PhysRevB.93.22420510.1103/PhysRevB.93.224205 ↗
53. 10.1103/PhysRevB.105.07513110.1103/PhysRevB.105.075131 ↗
54. 10.1103/PhysRevB.110.10441310.1103/PhysRevB.110.104413 ↗
55. 10.1103/PhysRevB.109.L14030110.1103/PhysRevB.109.L140301 ↗