Skip to main content
Log in

Multi-body entanglement and information rearrangement in nuclear many-body systems: a study of the Lipkin–Meshkov–Glick model

  • Regular Article - Theoretical Physics
  • Published:
The European Physical Journal A Aims and scope Submit manuscript

Abstract

We examine how effective-model-space (EMS) calculations of nuclear many-body systems rearrange and converge multi-particle entanglement. The generalized Lipkin–Meshkov–Glick (LMG) model is used to motivate and provide insight for future developments of entanglement-driven descriptions of nuclei. The effective approach is based on a truncation of the Hilbert space together with a variational rotation of the qubits (spins), which constitute the relevant elementary degrees of freedom. The non-commutivity of the rotation and truncation allows for an exponential improvement of the energy convergence throughout much of the model space. Our analysis examines measures of correlations and entanglement, and quantifies their convergence with increasing cut-off. We focus on one- and two-spin entanglement entropies, mutual information, and n-tangles for \(n=2,4\) to estimate multi-body entanglement. The effective description strongly suppresses entropies and mutual information of the rotated spins, while being able to recover the exact results to a large extent with low cut-offs. Naive truncations of the bare Hamiltonian, on the other hand, artificially underestimate these measures. The n-tangles in the present model provide a basis-independent measures of n-particle entanglement. While these are more difficult to capture with the EMS description, the improvement in convergence, compared to truncations of the bare Hamiltonian, is significantly more dramatic. We conclude that the low-energy EMS techniques, that successfully provide predictive capabilities for low-lying observables in many-body systems, exhibit analogous efficacy for quantum correlations and multi-body entanglement in the LMG model, motivating future studies in nuclear many-body systems and effective field theories relevant to high-energy physics and nuclear physics.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14

Similar content being viewed by others

Data Availability

This manuscript has no associated data or the data will not be deposited. [Authors’ comment: This is a theoretical study and no experimental data was generated.].

Notes

  1. In the text, we sometimes use the words “mode”, “spin” (or “qubit”) interchangeably.

  2. In the literature, the anisotropy parameter \(\chi \) is also often referred to as \(\gamma \).

  3. However, such an energy surface does cause issues with generic energy minimization techniques.

  4. A formal proof that the present EMS description minimizes entanglement has, in principle, only been established for the one-body entanglement entropy [17, 91], corresponding to the (rescaled) one-orbital entropy in the case of the LMG model. The present results suggest that this may also be true for higher-body entanglement measures, in particular the two-body entropy, or the mutual information.

  5. In their original formulation, odd-n-tangle have been found to be undefined for \(n > 3\) as they are not invariant under permutation of the qubits [97]. In the present LMG model, this is not an issue, since all spins are equivalent, the system is invariant under permutation of the spins, and thus, odd-n-tangles are in principle defined for any value of \(n \le N\). An extended definition of the odd-n-tangles, that eliminate this problem, has been developed in Ref. [99].

  6. We note that this is entirely empirical, and whether \(\eta _{1(2...N)}\) would satisfy all criteria to qualify as a proper entanglement measures has not been examined.

  7. The relevant uncertainty principle, \((\Delta \hat{J}_x)^2(\Delta \hat{J}_y)^2 \ge {1\over 4}|\langle \hat{J}_z\rangle |^2\), naturally leads to a definition of squeezing \((\Delta \hat{J}_\perp )^2 < {1\over 2}|\langle \hat{J}_z\rangle |\), and hence \(\xi ^W<1\).

References

  1. S.R. White, Density matrix formulation for quantum renormalization groups. Phys. Rev. Lett. 69, 2863–2866 (1992). https://doi.org/10.1103/PhysRevLett.69.2863

    Article  ADS  Google Scholar 

  2. U. Schollwöck, The density-matrix renormalization group in the age of matrix product states. Annals of Physics 326(1), 96–192 (2011) https://doi.org/10.1016/j.aop.2010.09.012.https://www.sciencedirect.com/science/article/pii/S0003491610001752.January 2011 Special Issue

  3. R. Orús, Tensor networks for complex quantum systems. Nat. Rev. Phys. 1(9), 538–550 (2019). https://doi.org/10.1038/s42254-019-0086-7

    Article  Google Scholar 

  4. J. Eisert, M. Cramer, M.B. Plenio, Colloquium: Area laws for the entanglement entropy. Rev. Mod. Phys. 82, 277–306 (2010). https://doi.org/10.1103/RevModPhys.82.277

    Article  MathSciNet  ADS  MATH  Google Scholar 

  5. G. Vidal, Efficient classical simulation of slightly entangled quantum computations. Phys. Rev. Lett. 91, 147902 (2003). https://doi.org/10.1103/PhysRevLett.91.147902

    Article  ADS  Google Scholar 

  6. E. Pazy, Entanglement entropy between short range correlations and the Fermi sea in nuclear structure. Phys. Rev. C 107(5), 054308 (2023). https://doi.org/10.1103/PhysRevC.107.054308. arXiv:2206.10702 [nucl-th]

  7. C. Gu, Z.H. Sun, G. Hagen, T. Papenbrock, Entanglement entropy of nuclear systems. (2023). arXiv:2303.04799 [nucl-th]

  8. T. Papenbrock, D.J. Dean, Density matrix renormalization group and wavefunction factorization for nuclei. J. Phys. G 31(8), S1377 (2005). https://doi.org/10.1088/0954-3899/31/8/016

    Article  ADS  Google Scholar 

  9. C.W. Johnson, O.C. Gorton, Proton-neutron entanglement in the nuclear shell model. J. Phys. G 50(4), 045110 (2023). 10.1088/1361-6471/acbece. arXiv:2210.14338 [nucl-th]

  10. J. Rotureau, N. Michel, W. Nazarewicz, M. Płoszajczak, J. Dukelsky, Density matrix renormalization group approach for many-body open quantum systems. Phys. Rev. Lett. 97, 110603 (2006). https://doi.org/10.1103/PhysRevLett.97.110603

    Article  ADS  Google Scholar 

  11. J. Rotureau, N. Michel, W. Nazarewicz, M. Płoszajczak, J. Dukelsky, Density matrix renormalization group approach to two-fluid open many-fermion systems. Phys. Rev. C 79, 014304 (2009). https://doi.org/10.1103/PhysRevC.79.014304

    Article  ADS  Google Scholar 

  12. G. Papadimitriou, J. Rotureau, N. Michel, M. Płoszajczak, B.R. Barrett, Ab initio no-core gamow shell model calculations with realistic interactions. Phys. Rev. C 88, 044318 (2013). https://doi.org/10.1103/PhysRevC.88.044318

    Article  ADS  Google Scholar 

  13. J. Dukelsky, S. Pittel, S.S. Dimitrova, M.V. Stoitsov, Density matrix renormalization group method and large-scale nuclear shell-model calculations. Phys. Rev. C 65, 054319 (2002). https://doi.org/10.1103/PhysRevC.65.054319

    Article  ADS  Google Scholar 

  14. J. Dukelsky, S. Pittel, The Density matrix renormalization group for finite Fermi systems. Rept. Prog. Phys. 67, 513–552 (2004). https://doi.org/10.1088/0034-4885/67/4/R02. arXiv:cond-mat/0404212

  15. B. Thakur, S. Pittel, N. Sandulescu, Density matrix renormalization group study of \(^{48}{\rm Cr}\) and \(^{56}{\rm Ni}\). Phys. Rev. C 78, 041303 (2008). https://doi.org/10.1103/PhysRevC.78.041303

    Article  ADS  Google Scholar 

  16. K. Fossez, J. Rotureau, Density matrix renormalization group description of the island of inversion isotopes \(^{28\text{- }33}\rm F \). Phys. Rev. C 106, 034312 (2022). https://doi.org/10.1103/PhysRevC.106.034312

    Article  ADS  Google Scholar 

  17. C. Robin, M.J. Savage, N. Pillet, Entanglement Rearrangement in Self-Consistent Nuclear Structure Calculations. Phys. Rev. C 103(3), 034325 (2021). https://doi.org/10.1103/PhysRevC.103.034325. arXiv:2007.09157 [nucl-th]

  18. O. Legeza, J. Sólyom, Optimizing the density-matrix renormalization group method using quantum information entropy. Phys. Rev. B 68, 195116 (2003). https://doi.org/10.1103/PhysRevB.68.195116

    Article  ADS  Google Scholar 

  19. O. Legeza, L. Veis, A. Poves, J. Dukelsky, Advanced density matrix renormalization group method for nuclear structure calculations. Phys. Rev. C 92, 051303 (2015). https://doi.org/10.1103/PhysRevC.92.051303

    Article  ADS  Google Scholar 

  20. A. Tichai, S. Knecht, A.T. Kruppa, O. Legeza, C.P. Moca, A. Schwenk, M.A. Werner, G. Zarand, Combining the in-medium similarity renormalization group with the density matrix renormalization group: Shell structure and information entropy. (2022). arXiv:2207.01438 [nucl-th]

  21. S.R. Beane, D.B. Kaplan, N. Klco, M.J. Savage, Entanglement Suppression and Emergent Symmetries of Strong Interactions. Phys. Rev. Lett. 122(10), 102001 (2019). https://doi.org/10.1103/PhysRevLett.122.102001. arXiv:1812.03138 [nucl-th]

  22. S.R. Beane, R.C. Farrell, Geometry and entanglement in the scattering matrix. Annals Phys. 433, 168581 (2021). https://doi.org/10.1016/j.aop.2021.168581. arXiv:2011.01278 [hep-th]

  23. S.R. Beane, R.C. Farrell, UV/IR symmetries of the S-matrix and RG flow. Nucl. Phys. A 1024, 122478 (2022). https://doi.org/10.1016/j.nuclphysa.2022.122478. arXiv:2112.03472 [hep-ph]

  24. I. Low, T. Mehen, Symmetry from entanglement suppression. Phys. Rev. D 104(7), 074014 (2021). https://doi.org/10.1103/PhysRevD.104.074014. arXiv:2104.10835 [hep-th]

  25. Q. Liu, I. Low, T. Mehen, Minimal entanglement and emergent symmetries in low-energy QCD. Phys. Rev. C 107(2), 025204 (2023). https://doi.org/10.1103/PhysRevC.107.025204. arXiv:2210.12085 [quant-ph]

  26. S.R. Beane, E. Chang, S.D. Cohen, W. Detmold, H.W. Lin, T.C. Luu, K. Orginos, A. Parreno, M.J. Savage, A. Walker-Loud, Light Nuclei and Hypernuclei from Quantum Chromodynamics in the Limit of SU(3) Flavor Symmetry. Phys. Rev. D 87(3), 034506 (2013). https://doi.org/10.1103/PhysRevD.87.034506. arXiv:1206.5219 [hep-lat]

  27. M.L. Wagman, F. Winter, E. Chang, Z. Davoudi, W. Detmold, K. Orginos, M.J. Savage, P.E. Shanahan, Baryon-Baryon Interactions and Spin-Flavor Symmetry from Lattice Quantum Chromodynamics. Phys. Rev. D 96(11), 114510 (2017). https://doi.org/10.1103/PhysRevD.96.114510. arXiv:1706.06550 [hep-lat]

  28. D.B. Kaplan, M.J. Savage, The Spin flavor dependence of nuclear forces from large n QCD. Phys. Lett. B 365, 244–251 (1996). https://doi.org/10.1016/0370-2693(95)01277-X. arXiv:hep-ph/9509371

    Article  ADS  Google Scholar 

  29. D. Bai, Z. Ren, Entanglement generation in few-nucleon scattering. Phys. Rev. C 106(6), 064005 (2022). https://doi.org/10.1103/PhysRevC.106.064005. arXiv:2212.11092 [nucl-th]

  30. D. Bai, Spin entanglement in neutron-proton scattering. (2023). arXiv:2306.04918 [nucl-th]

  31. G.A. Miller, Entanglement Maximization in Low-Energy Neutron-Proton Scattering. (2023). arXiv:2306.03239 [nucl-th]

  32. G.A. Miller, The Entanglement of Elastic and Inelastic Scattering. (2023). arXiv:2306.14800 [nucl-th]

  33. T. Papenbrock, D.J. Dean, Factorization of shell-model ground states. Phys. Rev. C 67, 051303 (2003). https://doi.org/10.1103/PhysRevC.67.051303

    Article  ADS  Google Scholar 

  34. T. Papenbrock, A. Juodagalvis, D.J. Dean, Solution of large scale nuclear structure problems by wave function factorization. Phys. Rev. C 69, 024312 (2004). https://doi.org/10.1103/PhysRevC.69.024312

    Article  ADS  Google Scholar 

  35. A.T. Kruppa, J. Kovács, P. Salamon, O. Legeza, Entanglement and correlation in two-nucleon systems. J. Phys. G 48(2), 025107 (2021). https://doi.org/10.1088/1361-6471/abc2dd

    Article  ADS  Google Scholar 

  36. A.T. Kruppa, J. Kovács, P. Salamon, O. Legeza, G. Zaránd, Entanglement and seniority. Phys. Rev. C 106, 024303 (2022). https://doi.org/10.1103/PhysRevC.106.024303

    Article  ADS  Google Scholar 

  37. I. Stetcu, A. Baroni, J. Carlson, Variational approaches to constructing the many-body nuclear ground state for quantum computing. Phys. Rev. C 105, 064308 (2022). https://doi.org/10.1103/PhysRevC.105.064308

    Article  ADS  Google Scholar 

  38. A. Perez-Obiol, A.M. Romero, J. Menendez, A. Rios, A. Garcia-Saez, B. Julia-Diaz, Nuclear shell-model simulation in digital quantum computers. (2023). arXiv:2302.03641 [quant-ph]

  39. A. Bulgac, M. Kafker, I. Abdurrahman, Measures of complexity and entanglement in many-fermion systems. Phys. Rev. C 107(4), 044318 (2023). https://doi.org/10.1103/PhysRevC.107.044318. arXiv:2203.04843 [nucl-th]

  40. A. Bulgac, Entanglement entropy, single-particle occupation probabilities, and short-range correlations. (2022). arXiv:2203.12079 [nucl-th]

  41. J. Faba, V. Martín, L. Robledo, Two-orbital quantum discord in fermion systems. Phys. Rev. A 103, 032426 (2021). https://doi.org/10.1103/PhysRevA.103.032426

    Article  MathSciNet  ADS  Google Scholar 

  42. J. Faba, V. Martín, L. Robledo, Correlation energy and quantum correlations in a solvable model. Phys. Rev. A 104, 032428 (2021). https://doi.org/10.1103/PhysRevA.104.032428

    Article  MathSciNet  ADS  Google Scholar 

  43. J. Faba, V. Martín, L. Robledo, Analysis of quantum correlations within the ground state of a three-level lipkin model. Phys. Rev. A 105, 062449 (2022). https://doi.org/10.1103/PhysRevA.105.062449

    Article  MathSciNet  ADS  Google Scholar 

  44. C.W. Bauer, Z. Davoudi, N. Klco, M.J. Savage, Quantum simulation of fundamental particles and forces. Nat. Rev. Phys. (2023). https://doi.org/10.1038/s42254-023-00599-8

    Article  Google Scholar 

  45. M. Kitagawa, M. Ueda, Squeezed spin states. Phys. Rev. A 47, 5138–5143 (1993). https://doi.org/10.1103/PhysRevA.47.5138

    Article  ADS  Google Scholar 

  46. D.J. Wineland, J.J. Bollinger, W.M. Itano, F.L. Moore, D.J. Heinzen, Spin squeezing and reduced quantum noise in spectroscopy. Phys. Rev. A 46, R6797–R6800 (1992). https://doi.org/10.1103/PhysRevA.46.R6797

    Article  ADS  Google Scholar 

  47. D.J. Wineland, J.J. Bollinger, W.M. Itano, D.J. Heinzen, Squeezed atomic states and projection noise in spectroscopy. Phys. Rev. A 50, 67–88 (1994). https://doi.org/10.1103/PhysRevA.50.67

    Article  ADS  Google Scholar 

  48. X. Wang, B.C. Sanders, Spin squeezing and pairwise entanglement for symmetric multiqubit states. Phys. Rev. A 68, 012101 (2003). https://doi.org/10.1103/PhysRevA.68.012101

    Article  ADS  Google Scholar 

  49. M.J. Cervia, A.B. Balantekin, S.N. Coppersmith, C.W. Johnson, P.J. Love, C. Poole, K. Robbins, M. Saffman, Lipkin model on a quantum computer. Phys. Rev. C 104, 024305 (2021). https://doi.org/10.1103/PhysRevC.104.024305

    Article  ADS  Google Scholar 

  50. M.Q. Hlatshwayo, Y. Zhang, H. Wibowo, R. LaRose, D. Lacroix, E. Litvinova, Simulating excited states of the Lipkin model on a quantum computer. Phys. Rev. C 106(2), 024319 (2022). https://doi.org/10.1103/PhysRevC.106.024319. arXiv:2203.01478 [nucl-th]

  51. A. Chikaoka, H. Liang, Quantum computing for the Lipkin model with unitary coupled cluster and structure learning ansatz. Chin. Phys. C 46(2), 024106 (2022). https://doi.org/10.1088/1674-1137/ac380a

    Article  ADS  Google Scholar 

  52. A.M. Romero, J. Engel, H.L. Tang, S.E. Economou, Solving nuclear structure problems with the adaptive variational quantum algorithm. Phys. Rev. C 105, 064317 (2022). https://doi.org/10.1103/PhysRevC.105.064317

    Article  ADS  Google Scholar 

  53. C.E.P. Robin, M.J. Savage, Quantum simulations in effective model spaces: Hamiltonian-learning variational quantum eigensolver using digital quantum computers and application to the Lipkin-Meshkov-Glick model. Phys. Rev. C 108(2), 024313 (2023). https://doi.org/10.1103/PhysRevC.108.024313. arXiv:2301.05976 [quant-ph]

    Article  ADS  Google Scholar 

  54. E.F. Dumitrescu, A.J. McCaskey, G. Hagen, G.R. Jansen, T.D. Morris, T. Papenbrock, R.C. Pooser, D.J. Dean, P. Lougovski, Cloud quantum computing of an atomic nucleus. Phys. Rev. Lett. 120, 210501 (2018). https://doi.org/10.1103/PhysRevLett.120.210501

    Article  ADS  Google Scholar 

  55. H. Lu, N. Klco, J.M. Lukens, T.D. Morris, A. Bansal, A. Ekström, G. Hagen, T. Papenbrock, A.M. Weiner, M.J. Savage, P. Lougovski, Simulations of subatomic many-body physics on a quantum frequency processor. Phys. Rev. A 100, 012320 (2019). https://doi.org/10.1103/PhysRevA.100.012320

    Article  ADS  Google Scholar 

  56. O. Kiss, M. Grossi, P. Lougovski, F. Sanchez, S. Vallecorsa, T. Papenbrock, Quantum computing of the \(^{6}\rm Li \) nucleus via ordered unitary coupled clusters. Phys. Rev. C 106, 034325 (2022). https://doi.org/10.1103/PhysRevC.106.034325

    Article  ADS  Google Scholar 

  57. D. Lacroix, Symmetry-assisted preparation of entangled many-body states on a quantum computer. Phys. Rev. Lett. 125, 230502 (2020). https://doi.org/10.1103/PhysRevLett.125.230502

    Article  MathSciNet  ADS  Google Scholar 

  58. E.A. Ruiz Guzman, D. Lacroix, Accessing ground-state and excited-state energies in a many-body system after symmetry restoration using quantum computers. Phys. Rev. C 105, 024324 (2022). https://doi.org/10.1103/PhysRevC.105.024324

  59. D. Lacroix, E.A. Ruiz Guzman, P. Siwach, Symmetry breaking/symmetry preserving circuits and symmetry restoration on quantum computers: A quantum many-body perspective. Eur. Phys. J. A 59(1), 3 (2023). https://doi.org/10.1140/epja/s10050-022-00911-7. arXiv:2208.11567 [quant-ph]

  60. E.A.R. Guzman, D. Lacroix, Restoring broken symmetries using quantum search “oracles’’. Phys. Rev. C 107, 034310 (2023). https://doi.org/10.1103/PhysRevC.107.034310

    Article  ADS  Google Scholar 

  61. P. Pérez-Fernández, J.M. Arias, J.E. García-Ramos, L. Lamata, A digital quantum simulation of the Agassi model. Phys. Lett. B 829, 137133 (2022). https://doi.org/10.1016/j.physletb.2022.137133. arXiv:2105.02834 [quant-ph]

  62. A. Sáiz, J.E. García-Ramos, J.M. Arias, L. Lamata, P. Pérez-Fernández, Digital quantum simulation of an extended Agassi model: Using machine learning to disentangle its phase-diagram. Phys. Rev. C 106(6), 064322 (2022). https://doi.org/10.1103/PhysRevC.106.064322. arXiv:2205.15122 [quant-ph]

  63. M. Illa, C.E.P. Robin, M.J. Savage, Quantum Simulations of SO(5) Many-Fermion Systems using Qudits. (2023). arXiv:2305.11941 [quant-ph]

  64. E.T. Holland, K.A. Wendt, K. Kravvaris, X. Wu, W.E. Ormand, J.L. DuBois, S. Quaglioni, F. Pederiva, Optimal control for the quantum simulation of nuclear dynamics. Phys. Rev. A 101, 062307 (2020). https://doi.org/10.1103/PhysRevA.101.062307

    Article  ADS  Google Scholar 

  65. A. Roggero, C. Gu, A. Baroni, T. Papenbrock, Preparation of excited states for nuclear dynamics on a quantum computer. Phys. Rev. C 102, 064624 (2020). https://doi.org/10.1103/PhysRevC.102.064624

    Article  ADS  Google Scholar 

  66. F. Turro, et al., A quantum-classical co-processing protocol towards simulating nuclear reactions on contemporary quantum hardware. (2023). arXiv:2302.06734 [quant-ph]

  67. A. Roggero, A.C.Y. Li, J. Carlson, R. Gupta, G.N. Perdue, Quantum computing for neutrino-nucleus scattering. Phys. Rev. D 101, 074038 (2020). https://doi.org/10.1103/PhysRevD.101.074038

    Article  ADS  Google Scholar 

  68. A. Baroni, J. Carlson, R. Gupta, A.C.Y. Li, G.N. Perdue, A. Roggero, Nuclear two point correlation functions on a quantum computer. Phys. Rev. D 105, 074503 (2022). https://doi.org/10.1103/PhysRevD.105.074503

    Article  ADS  Google Scholar 

  69. S. Lu, M.C. Banuls, J.I. Cirac, Algorithms for quantum simulation at finite energies. PRX Quantum 2(2) (2021). 10.1103/prxquantum.2.020321. arXiv:2006.03032 [quant-ph]

  70. K. Choi, D. Lee, J. Bonitati, Z. Qian, J. Watkins, Rodeo Algorithm for Quantum Computing. Phys. Rev. Lett. 127(4), 040505 (2021). https://doi.org/10.1103/PhysRevLett.127.040505. arXiv:2009.04092 [quant-ph]

  71. IBM Quantum.https://quantum-computing.ibm.com/, 2021

  72. H. Lipkin, N. Meshkov, A. Glick, Validity of many-body approximation methods for a solvable model: (i). exact solutions and perturbation theory. Nuclear Physics 62(2), 188–198 (1965). https://doi.org/10.1016/0029-5582(65)90862-X. https://www.sciencedirect.com/science/article/pii/002955826590862X

  73. J. Vidal, G. Palacios, R. Mosseri, Entanglement in a second-order quantum phase transition. Phys. Rev. A 69, 022107 (2004). https://doi.org/10.1103/PhysRevA.69.022107

    Article  ADS  Google Scholar 

  74. J. Vidal, R. Mosseri, J. Dukelsky, Entanglement in a first-order quantum phase transition. Phys. Rev. A 69, 054101 (2004). https://doi.org/10.1103/PhysRevA.69.054101

    Article  MathSciNet  ADS  Google Scholar 

  75. J. Vidal, G. Palacios, C. Aslangul, Entanglement dynamics in the Lipkin-Meshkov-Glick model. Phys. Rev. A 70, 062304 (2004). https://doi.org/10.1103/PhysRevA.70.062304. arXiv:cond-mat/0406481

  76. J.I. Latorre, R. Orús, E. Rico, J. Vidal, Entanglement entropy in the lipkin-meshkov-glick model. Phys. Rev. A 71, 064101 (2005). https://doi.org/10.1103/PhysRevA.71.064101

    Article  MathSciNet  ADS  MATH  Google Scholar 

  77. H.T. Cui, Multiparticle entanglement in the lipkin-meshkov-glick model. Phys. Rev. A 77, 052105 (2008). https://doi.org/10.1103/PhysRevA.77.052105

    Article  ADS  Google Scholar 

  78. R. Orús, S. Dusuel, J. Vidal, Equivalence of critical scaling laws for many-body entanglement in the lipkin-meshkov-glick model. Phys. Rev. Lett. 101, 025701 (2008). https://doi.org/10.1103/PhysRevLett.101.025701

    Article  ADS  Google Scholar 

  79. M. Di Tullio, R. Rossignoli, M. Cerezo, N. Gigena, Fermionic entanglement in the lipkin model. Phys. Rev. A 100, 062104 (2019). https://doi.org/10.1103/PhysRevA.100.062104

    Article  MathSciNet  ADS  Google Scholar 

  80. A.C. Lourenço, S. Calegari, T.O. Maciel, T. Debarba, G.T. Landi, E.I. Duzzioni, Genuine multipartite correlations distribution in the criticality of the lipkin-meshkov-glick model. Phys. Rev. B 101, 054431 (2020). https://doi.org/10.1103/PhysRevB.101.054431

    Article  ADS  Google Scholar 

  81. M. Calixto, A. Mayorgas, J. Guerrero, Entanglement and U(D)-spin squeezing in symmetric multi-quDit systems and applications to quantum phase transitions in Lipkin–Meshkov–Glick D-level atom models. Quantum Inf. Process. 20, 304 (2021). 10.1007/s11128-021-03218-6. arXiv:2104.10581 [quant-ph]

  82. M. Illa, M.J. Savage, Multi-Neutrino Entanglement and Correlations in Dense Neutrino Systems. Phys. Rev. Lett. 130(22), 221003 (2023). https://doi.org/10.1103/PhysRevLett.130.221003. arXiv:2210.08656 [nucl-th]

  83. R.C. Farrell, I.A. Chernyshev, S.J.M. Powell, N.A. Zemlevskiy, M. Illa, M.J. Savage, Preparations for quantum simulations of quantum chromodynamics in 1+1 dimensions. I. Axial gauge. Phys. Rev. D 107(5), 054512 (2023). https://doi.org/10.1103/PhysRevD.107.054512. arXiv:2207.01731 [quant-ph]

  84. K.K. Docken, J. Hinze, LiH Potential Curves and Wavefunctions for X 1 \(\Sigma \)+, A 1 \(\Sigma \)+, B 1 \(\Pi \), 3 \(\Sigma \)+, and \(\Pi \) 3. The Journal of Chemical Physics 57(11), 4928–4936 (2003). https://doi.org/10.1063/1.1678164. https://pubs.aip.org/aip/jcp/article-pdf/57/11/4928/10969993/4928_1_online.pdf

  85. R. Colle, O. Salvetti, Multiconfiguration-self-consistent field (mc-scf) method for excited states. Molecular Physics 47(4), 959–972 (1982). https://doi.org/10.1080/00268978200100722

  86. J. Hinze, F.F. Chemie, Developments in the calculation of electronic wavefunctions for molecules: Mcscf, ci, and numerical scf for molecules. International Journal of Quantum Chemistry 20(S15), 69–90 (1981). https://doi.org/10.1002/qua.560200809. https://onlinelibrary.wiley.com/doi/pdf/10.1002/qua.560200809

  87. M.P. Deskevich, D.J. Nesbitt, H.J. Werner, Dynamically weighted multiconfiguration self-consistent field: Multistate calculations for f+h2o?hf+oh reaction paths. J. Chem. Phys. 120(16), 7281–7289 (2004). https://doi.org/10.1063/1.1667468

    Article  ADS  Google Scholar 

  88. R. Rossignoli, N. Canosa, J.M. Matera, Entanglement of finite cyclic chains at factorizing fields. Phys. Rev. A 77, 052322 (2008). https://doi.org/10.1103/PhysRevA.77.052322

    Article  ADS  Google Scholar 

  89. R. Rossignoli, N. Canosa, J.M. Matera, Factorization and entanglement in general \(xyz\) spin arrays in nonuniform transverse fields. Phys. Rev. A 80, 062325 (2009). https://doi.org/10.1103/PhysRevA.80.062325

    Article  ADS  Google Scholar 

  90. M. Nielsen, I. Chuang, Quantum Computation and Quantum Information: 10th Anniversary Edition (Cambridge University Press, 2010). https://books.google.de/books?id=j2ULnwEACAAJ

  91. N. Gigena, R. Rossignoli, Entanglement in fermion systems. Phys. Rev. A 92, 042326 (2015). https://doi.org/10.1103/PhysRevA.92.042326

    Article  ADS  Google Scholar 

  92. K. Boguslawski, P. Tecmer, Örs Legeza, M. Reiher, Entanglement measures for single- and multireference correlation effects. J. Phys. Chem. Lett. 3(21), 3129–3135 (2012). https://doi.org/10.1021/jz301319v

  93. H. Ollivier, W.H. Zurek, Quantum discord: A measure of the quantumness of correlations. Phys. Rev. Lett. 88, 017901 (2001). https://doi.org/10.1103/PhysRevLett.88.017901

    Article  ADS  MATH  Google Scholar 

  94. W.K. Wootters, Entanglement of formation of an arbitrary state of two qubits. Phys. Rev. Lett. 80, 2245–2248 (1998). https://doi.org/10.1103/PhysRevLett.80.2245

    Article  ADS  MATH  Google Scholar 

  95. S.A. Hill, W.K. Wootters, Entanglement of a pair of quantum bits. Phys. Rev. Lett. 78, 5022–5025 (1997). https://doi.org/10.1103/PhysRevLett.78.5022

    Article  ADS  Google Scholar 

  96. V. Coffman, J. Kundu, W.K. Wootters, Distributed entanglement. Phys. Rev. A 61, 052306 (2000). https://doi.org/10.1103/PhysRevA.61.052306

    Article  ADS  Google Scholar 

  97. A. Wong, N. Christensen, Potential multiparticle entanglement measure. Phys. Rev. A 63, 044301 (2001). https://doi.org/10.1103/PhysRevA.63.044301

    Article  ADS  Google Scholar 

  98. J.D. Martin, A. Roggero, H. Duan, J. Carlson, Many-body neutrino flavor entanglement in a simple dynamic model. (2023). arXiv:2301.07049 [hep-ph]

  99. D. Li, The n-tangle of odd n qubits. Quantum Inform. Process. 11(2), 481–492 (2011). https://doi.org/10.1007/s11128-011-0256-8

    Article  MathSciNet  ADS  MATH  Google Scholar 

  100. H. Duan, G.M. Fuller, Y.Z. Qian, Collective neutrino flavor transformation in supernovae. Phys. Rev. D 74, 123004 (2006). https://doi.org/10.1103/PhysRevD.74.123004. arXiv:astro-ph/0511275

  101. A.B. Balantekin, Y. Pehlivan, Neutrino–neutrino interactions and flavour mixing in dense matter. J. Phys. G 34(1), 47–65 (2006). https://doi.org/10.1088/0954-3899/34/1/004

    Article  ADS  Google Scholar 

  102. T.J. Osborne, Entanglement measure for rank-2 mixed states. Phys. Rev. A 72, 022309 (2005). https://doi.org/10.1103/PhysRevA.72.022309

    Article  MathSciNet  ADS  Google Scholar 

  103. X. Li, D. Li, Relationship between the n-tangle and the residual entanglement of even n qubits. Quantum Inf. Comput. 10, 1018 (2010). arXiv:1003.4774 [quant-ph]

    MathSciNet  ADS  MATH  Google Scholar 

  104. C.s. Yu, H.s. Song, Multipartite entanglement measure. Phys. Rev. A 71, 042331 (2005). https://doi.org/10.1103/PhysRevA.71.042331

  105. Qiskit contributors. Qiskit: An open-source framework for quantum computing (2023). https://doi.org/10.5281/zenodo.2573505

  106. S. Weinberg, Nuclear forces from chiral Lagrangians. Phys. Lett. B 251, 288–292 (1990). https://doi.org/10.1016/0370-2693(90)90938-3

    Article  ADS  Google Scholar 

  107. S. Weinberg, Effective chiral Lagrangians for nucleon - pion interactions and nuclear forces. Nucl. Phys. B 363, 3–18 (1991). https://doi.org/10.1016/0550-3213(91)90231-L

    Article  ADS  Google Scholar 

  108. C. Ordonez, L. Ray, U. van Kolck, The Two nucleon potential from chiral Lagrangians. Phys. Rev. C 53, 2086–2105 (1996). https://doi.org/10.1103/PhysRevC.53.2086. arXiv:hep-ph/9511380

    Article  ADS  Google Scholar 

  109. D.B. Kaplan, M.J. Savage, M.B. Wise, A New expansion for nucleon-nucleon interactions. Phys. Lett. B 424, 390–396 (1998). https://doi.org/10.1016/S0370-2693(98)00210-X. arXiv:nucl-th/9801034

  110. D.B. Kaplan, M.J. Savage, M.B. Wise, Two nucleon systems from effective field theory. Nucl. Phys. B 534, 329–355 (1998). https://doi.org/10.1016/S0550-3213(98)00440-4. arXiv:nucl-th/9802075

  111. D.B. Kaplan, Convergence of nuclear effective field theory with perturbative pions. Phys. Rev. C 102(3), 034004 (2020). https://doi.org/10.1103/PhysRevC.102.034004. arXiv:1905.07485 [nucl-th]

  112. S.R. Beane, P.F. Bedaque, M.J. Savage, U. van Kolck, Towards a perturbative theory of nuclear forces. Nucl. Phys. A 700, 377–402 (2002). https://doi.org/10.1016/S0375-9474(01)01324-0. arXiv:nucl-th/0104030

Download references

Acknowledgements

We would like to thank Douglas Beck, Calvin Johnson and Denis Lacroix for helpful discussions, and for all of our other colleagues and collaborators that provide the platform from which this work has emerged. We would also like to thank the participants at the IQuS workshop “At the Interface of Quantum Sensors and Quantum Simulations”, organized by Doug Beck, Natalie Klco, Crystal Noel and Joel Ullom, (https://iqus.uw.edu/events/iqus-workshop-22-3b/), for stimulating presentations and discussions. S. M. Hengstenberg and C. E. P. Robin would like to thank the InQubator for Quantum Simulation for support and kind hospitality during part of this work. This work was supported, in part, by Universität Bielefeld and ERC-885281-KILONOVA Advanced Grant, and, in part, by U.S. Department of Energy, Office of Science, Office of Nuclear Physics, InQubator for Quantum Simulation (IQuS) under Award Number DOE (NP) Award DE-SC0020970 via the program on Quantum Horizons: QIS Research and Innovation for Nuclear Science. We acknowledge the use of IBM Quantum services for this work. The views expressed are those of the authors, and do not reflect the official policy or position of IBM or the IBM Quantum team. It was supported, in part, through the Department of Physics (https://phys.washington.edu) and the College of Arts and Sciences (https://www.artsci.washington.edu) at the University of Washington.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Caroline E. P. Robin.

Additional information

Communicated by Vittorio Somà.

Martin J. Savage: On leave from the Institute for Nuclear Theory.

Appendices

A Matrix elements of the bare and effective Hamiltonians

The bare Hamiltonian of the LMG model

$$\begin{aligned} \hat{H}= & {} \varepsilon \hat{J}_z - \frac{V}{2} \left( \hat{J}_+^2 + \hat{J}_-^2 \right) - \frac{W}{2} (\hat{J}_+ \hat{J}_- + \hat{J}_- \hat{J}_+ -\hat{N}) \; , \nonumber \\ \end{aligned}$$
(54)

has matrix elements in the original \(\{ \left| N_+\right\rangle \equiv \left| J,M\right\rangle \}\) basis that read

$$\begin{aligned} {\langle N_+' | \hat{H} | N_+\rangle }= & {} \left( \varepsilon \, M -\frac{W}{2} \left[ C_+(M)^2 + C_-(M)^2 - N \right] \right) \delta _{N_+',N_+} \nonumber \\{} & {} - \frac{V}{2} \Bigl [ C_+(M) C_+(M+1) \, \delta _{N_+',N_+ +2} \nonumber \\{} & {} +C_-(M) C_-(M-1) \, \delta _{N_+',N_+-2} \Bigr ] \; , \end{aligned}$$
(55)

where \(M = N_+ - J\) and \(J=\frac{N}{2}\), and where we have defined

$$\begin{aligned} C_\pm (M) = \sqrt{J(J+1) - M(M\pm 1)} \; . \end{aligned}$$
(56)

The Hamiltonian acting in the effective model space can be obtained by performing a rotation \(\hat{U}(\beta )\) around the y axis of the collective (quasi-)spin operators \(\hat{J}_\alpha \) given in Eq. (3), by an angle \(\beta \). The rotated operators \(\hat{J}_\alpha (\beta )\) are then related to the original ones by

$$\begin{aligned} \hat{J}_z= & {} \cos (\beta ) \hat{J}_z(\beta ) + \frac{1}{2} \sin \beta \left( \hat{J}_+(\beta ) + \hat{J}_-(\beta )\right) \; , \end{aligned}$$
(57)
$$\begin{aligned} \hat{J}_+= & {} \frac{1}{2} \Bigl [ - 2 \sin (\beta ) \hat{J}_z(\beta ) \nonumber \\{} & {} + \bigl ( \cos \beta +1 \bigr ) \hat{J}_+(\beta ) + \bigl ( \cos \beta -1 \bigr ) \hat{J}_-(\beta ) \Bigr ] \; , \end{aligned}$$
(58)
$$\begin{aligned} \hat{J}_-= & {} (\hat{J}_+)^\dagger = \frac{1}{2} \Bigl [ - 2\sin \beta \hat{J}_z(\beta ) \nonumber \\{} & {} + \bigl ( \cos \beta +1 \bigr ) \hat{J}_-(\beta ) + \bigl ( \cos \beta -1 \bigr ) \hat{J}_+(\beta ) \Bigr ] \; . \end{aligned}$$
(59)

The resulting effective Hamiltonian then becomes

$$\begin{aligned} \hat{H}(\beta )= & {} \hat{U}^\dagger (\beta ) \hat{H} \hat{U}(\beta ) \nonumber \\= & {} \hat{H}_\varepsilon (\beta ) + \hat{H}_V(\beta ) + \hat{H}_W(\beta ) \; , \end{aligned}$$
(60)

where

$$\begin{aligned} H_\varepsilon (\beta )= & {} \varepsilon \; \left[ \cos \beta \hat{J}_z(\beta ) + \frac{1}{2} \sin \beta \bigl ( \hat{J}_+(\beta ) + \hat{J}_-(\beta ) \bigr ) \right] \; , \nonumber \\ \end{aligned}$$
(61)
$$\begin{aligned} \hat{H}_V(\beta )= & {} - \frac{V}{4} \Bigl [ \sin ^2\beta \bigl ( 4 \hat{J}_z(\beta )^2 - \{ \hat{J}_+(\beta ), \hat{J}_-(\beta ) \} \bigr ) \nonumber \\{} & {} - 2 \sin \beta \cos \beta \bigl ( \{ \hat{J}_z(\beta ),\hat{J}_+(\beta )\} \!+\! \{ \hat{J}_z(\beta ), \hat{J}_-(\beta ) \} \bigr ) \nonumber \\{} & {} + (1 + \cos ^2\beta ) \bigl (\hat{J}_+(\beta )^2 + \hat{J}_-(\beta )^2 \bigr ) \Bigr ] \; , \end{aligned}$$
(62)

and

$$\begin{aligned} \hat{H}_W(\beta )= & {} - \frac{W}{4} \Bigl [ 4 \sin ^2\beta \hat{J}_z(\beta )^2 \nonumber \\{} & {} + (1 + \cos ^2\beta ) \{ \hat{J}_+(\beta ), \hat{J}_-(\beta ) \}- 2 \hat{N} \nonumber \\{} & {} - 2 \sin \beta \cos \beta \bigl ( \{ \hat{J}_z(\beta ),\hat{J}_+(\beta )\} \!+\! \{ \hat{J}_z(\beta ), \hat{J}_-(\beta ) \} \bigr ) \nonumber \\{} & {} - \sin ^2\beta \bigl (\hat{J}_+(\beta )^2 + \hat{J}_-(\beta )^2 \bigr ) \Bigr ] \; .\nonumber \\ \end{aligned}$$
(63)

Matrix elements of the effective Hamiltonian in Eq. (60) in the basis \(\{ N_+, \beta \}\) can now be computed. In contrast to the bare Hamiltonian in Eq. (54), the effective Hamiltonian can clearly couple configurations with values of \(N_+\) differing by one unit, in addition to those differing by zero, or two units. Since the rotation preserves the value of J, we can use \(M = N_+ - J = N_+ -\frac{N}{2}\), and write the non-zero matrix elements as

$$\begin{aligned}{} & {} {\langle N_+, \beta |\hat{H}(\beta ) | N_+, \beta \rangle }\nonumber \\{} & {} \quad = \varepsilon M \cos \beta -\frac{V}{4} \sin ^2\beta \left[ 4 M^2 - [C_+(M)^2 +C_-(M)^2] \right] \nonumber \\{} & {} \qquad -\frac{W}{4} \Big [ 4 \sin ^2\beta M^2 + (1 + \cos ^2\beta ) [C_+(M)^2 \nonumber \\ {}{} & {} \qquad +C_-(M)^2] - 2N \Big ] , \end{aligned}$$
(64)
$$\begin{aligned}{} & {} {\langle N_+\pm 1, \beta |\hat{H}(\beta ) | N_+, \beta \rangle } = \frac{\varepsilon }{2} \sin \beta \, C_\pm (M) \nonumber \\{} & {} \qquad + \frac{V+W}{4} \left[ 2 \sin \beta \cos \beta (2M \pm 1) C_\pm (M) \right] , \end{aligned}$$
(65)

and

$$\begin{aligned}{} & {} {\langle N_+\pm 2, \beta |\hat{H}(\beta ) | N_+, \beta \rangle }\nonumber \\{} & {} \quad = - \frac{V}{4} \Big [ (1+ \cos ^2 \beta ) \, C_\pm (M) C_\pm (M\pm 1) \Big ] \nonumber \\{} & {} \qquad + \frac{W}{4} \left[ \sin ^2 \beta \, C_\pm (M) \, C_\pm (M\pm 1) \right] \; . \end{aligned}$$
(66)

It is straightforward to observe that the bare Hamiltonian in Eq. (54) and the matrix elements in Eq. (55) are recovered when \(\beta =0\).

B Derivations the n-tangles

In the case where the many-body state is real, i.e., \(\left| \Psi ^*\right\rangle = \left| \Psi \right\rangle \), the n-tangles \(\tau _n\) are the following,

$$\begin{aligned} \tau _n= & {} |{\langle \Psi | \hat{\sigma }_y^{\otimes n} |\Psi ^*\rangle }|^2 \ =\ |{\langle \Psi | \hat{\sigma }_y^{\otimes n} |\Psi \rangle }|^2 \; . \end{aligned}$$
(67)

Their calculation thus requires the evaluation of the expectation value of the tensor products of single-spin Pauli operators \(\hat{\sigma }_y\). The fact that all spins are equivalent in the LMG model simplifies the derivation of such expectation values which can be obtained from averages of expectation values of collective operators \(\hat{J_y} = \sum _p \hat{\sigma }_y^p/2\), where \(\sigma _y^p\) acts on the single spin p.

For example, the 2-tangle requires the calculation of

$$\begin{aligned} {\langle \hat{\sigma }_y^p \otimes \hat{\sigma }_y^q \rangle }= & {} \frac{1}{N(N-1)} \sum _{p \ne q} {\langle \hat{\sigma }_y^p \otimes \hat{\sigma }_y^q \rangle } \nonumber \\= & {} \frac{1}{N(N-1)} \left[ \sum _{pq} {\langle \hat{\sigma }_y^p \otimes \hat{\sigma }_y^q \rangle } - \sum _p {\langle (\hat{\sigma }_y^p )^2 \rangle } \right] \nonumber \\= & {} \frac{1}{N(N-1)} \Bigl [ 4 {\langle \hat{J}_y^2\rangle } - N \Bigr ] \; , \end{aligned}$$
(68)

where we used the notation \({\langle .\rangle } = {\langle \Psi |.|\Psi \rangle }\), and the fact that \((\sigma _p)^2 =1\). One can further insert

$$\begin{aligned} {\langle \hat{J}_y^2\rangle }{} & {} = - \frac{1}{4} \left( {\langle \hat{J}_+^2 \rangle } +{\langle \hat{J}_-^2\rangle } - {\langle \hat{J}_+ \hat{J}_- + \hat{J}_- \hat{J}_+\rangle } \right) \nonumber \\{} & {} = - \frac{1}{4} \left( {\langle \hat{J}_+^2\rangle } +{\langle \hat{J}_-^2\rangle } + 2 {\langle \hat{J}_z^2\rangle } - N \left( \frac{N}{2} + 1 \right) \right) \; , \nonumber \\ \end{aligned}$$
(69)

which is easily calculated in the \(\{\left| J,M\right\rangle \}\) basis.

Similarly the expectation value for the calculation of the 3-tangle is

$$\begin{aligned} {\langle \hat{\sigma }_y^p \otimes \hat{\sigma }_y^q \otimes \hat{\sigma }_y^r \rangle }= & {} \frac{1}{N(N-1)(N-2)}\nonumber \\ \sum _{p \ne q \ne r} {\langle \hat{\sigma }_y^p \otimes \hat{\sigma }_y^q \otimes \hat{\sigma }_y^r\rangle }= & {} \frac{1}{N(N-1)(N-2)} \left[ \sum _{pqr} {\langle \hat{\sigma }_y^p \otimes \hat{\sigma }_y^q \otimes \hat{\sigma }_y^r\rangle } \right. \nonumber \\{} & {} \left. - 3 \sum _{p \ne r} {\langle (\hat{\sigma }_y^p )^2 \otimes \hat{\sigma }_y^r\rangle } - \sum _p {\langle (\hat{\sigma }_y^p )^3 \rangle } \right] \nonumber \\= & {} \frac{1}{N(N-1)(N-2)}\nonumber \\ {}{} & {} \times \Bigl [ 8 {\langle \hat{J}_y^3\rangle } - 2(3N-2) {\langle \hat{J}_y\rangle } \Bigr ] . \end{aligned}$$
(70)

For the 4-tangle the expectation value reads

$$\begin{aligned}{} & {} {\langle \hat{\sigma }_y^p \otimes \hat{\sigma }_y^q \otimes \hat{\sigma }_y^r \otimes \hat{\sigma }_y^s \rangle }\nonumber \\{} & {} \quad = \frac{1}{\widetilde{\Omega }_N} \sum _{p \ne q\ne r \ne s} {\langle \hat{\sigma }_y^p \otimes \hat{\sigma }_y^q \otimes \hat{\sigma }_y^r \otimes \hat{\sigma }_y^s\rangle } \end{aligned}$$
(71)

where \(\widetilde{\Omega }_N = N (N-1)(N-2)(N-3)\), and,

$$\begin{aligned}{} & {} \sum _{p \ne q\ne r \ne s} {\langle \hat{\sigma }_y^p \otimes \hat{\sigma }_y^q \otimes \hat{\sigma }_y^r \otimes \hat{\sigma }_y^s\rangle } \nonumber \\{} & {} \quad = \sum _{pqrs} {\langle \hat{\sigma }_y^p \otimes \hat{\sigma }_y^q \otimes \hat{\sigma }_y^r \otimes \hat{\sigma }_y^s\rangle }\nonumber \\{} & {} \qquad - 6 \sum _{p \ne r \ne s}\! {\langle (\hat{\sigma }_y^p)^2 \!\otimes \hat{\sigma }_y^r \otimes \hat{\sigma }_y^s\rangle } \nonumber \\{} & {} \qquad - 3 \sum _{p \ne s} {\langle (\hat{\sigma }_y^p)^2 \otimes (\hat{\sigma }_y^s )^2\rangle } - 4 \sum _{p \ne s} {\langle (\hat{\sigma }_y^p)^3 \otimes \hat{\sigma }_y^s\rangle }\nonumber \\{} & {} \qquad - \sum _p {\langle (\hat{\sigma }_y^p)^4 \rangle } \nonumber \\{} & {} \quad = \sum _{pqrs} {\langle \hat{\sigma }_y^p \otimes \hat{\sigma }_y^q \otimes \hat{\sigma }_y^r \otimes \hat{\sigma }_y^s\rangle } \nonumber \\{} & {} \qquad - 2( 3N -4) \sum _{p \ne s} {\langle \hat{\sigma }_y^p \otimes \hat{\sigma }_y^s\rangle } - 3N^2 +2N \end{aligned}$$
(72)

where

$$\begin{aligned} \sum _{pqrs} {\langle \hat{\sigma }_y^p \otimes \hat{\sigma }_y^q \otimes \hat{\sigma }_y^r \otimes \hat{\sigma }_y^s\rangle } = 16 {\langle \hat{J}_y^4\rangle } \; , \end{aligned}$$
(73)

and

$$\begin{aligned} \sum _{p\ne s} {\langle \hat{\sigma }_y^p \otimes \hat{\sigma }_y^s\rangle } = 4 {\langle \hat{J}_y^2\rangle } - N \; . \end{aligned}$$
(74)

Thus we obtain

$$\begin{aligned} {\langle \hat{\sigma }_y^p \otimes \hat{\sigma }_y^q \otimes \hat{\sigma }_y^r \otimes \hat{\sigma }_y^s \rangle }= & {} \frac{1}{\widetilde{\Omega }_N} \Bigl [ 16 {\langle \hat{J}_y^4\rangle } - 8 (3N-4) {\langle \hat{J}_y^2\rangle } \nonumber \\{} & {} \quad + 3N(N-2) \Bigr ] . \end{aligned}$$
(75)

The explicit expression for \({\langle \hat{J}_y^2\rangle }\) given in Eq. (69) can be used to finally obtain

$$\begin{aligned} {\langle \hat{\sigma }_y^p \otimes \hat{\sigma }_y^q \otimes \hat{\sigma }_y^r \otimes \hat{\sigma }_y^s \rangle }= & {} \frac{1}{\widetilde{\Omega }_N} \left[ {\langle (\hat{J}_+-\hat{J}_-)^4\rangle } + 2(3N-4) \right. \nonumber \\{} & {} \left. \left( {\langle \hat{J}_+^2\rangle } + {\langle \hat{J}_-^2\rangle } + 2 {\langle \hat{J}_z^2\rangle }\right) \right. \nonumber \\{} & {} \left. - 3N^3 +N^2 +2N \right] \; , \end{aligned}$$
(76)

The expectation values of products of \(\hat{J}_\pm \) and \(\hat{J}_z^2\) operators can again be easily calculated in the \(\{\left| J,M\right\rangle \}\) basis.

1.1 B.1 Example of 4-tangles

To reinforce the reader’s intuition about the physical meaning of n-tangles, we provide the example of \(\tau _4^{abcd}\) in a system of five spins with a select wavefunction. Consider a system with

$$\begin{aligned} \left| \Psi \right\rangle= & {} {1\over \sqrt{3}}\left[ |11110\rangle + |00000\rangle + |10101\rangle \right] \ \ \ . \end{aligned}$$
(77)

Forming the five possible \(\left| \tilde{\Psi }\right\rangle =\hat{\sigma }_y^a\hat{\sigma }_y^b\hat{\sigma }_y^c\hat{\sigma }_y^d \left| \Psi ^*\right\rangle \) gives

$$\begin{aligned} \langle \Psi \vert \hat{\sigma }_y^1\hat{\sigma }_y^2\hat{\sigma }_y^3\hat{\sigma }_y^4 \left| \Psi ^*\right\rangle= & {} {2\over 3} \ \ ,\ \ \tau _4^{(1234)}={4\over 9} \ \ \ , \end{aligned}$$
(78)

with the other four possible \(\tau _4^{abcd}\) vanishing.

1.2 B.2 Two- and four-body entanglement in the \(N=4\) system

The \(N=4\) system is simple enough that it can be investigated analytically in the general case. Considering a (real) wave function expanded in the \(\{ \left| N_+\right\rangle = \left| JM\right\rangle \}\) basis, as in Eq. (11):

$$\begin{aligned} \left| \Psi \right\rangle = \sum _{N_+=0}^N A_{N_+} \left| N_+\right\rangle \; , \end{aligned}$$
(79)

we find,

$$\begin{aligned} \tau _2= & {} \Bigl | \frac{1}{3} A_0^2 + \frac{5}{6} A_1^2 + A_2^2 + \frac{5}{6} A_3^2 + \frac{1}{3} A_4^2 \nonumber \\{} & {} -\frac{\sqrt{6}}{3} A_0 A_2 - A_1 A_3 -\frac{\sqrt{6}}{3} A_2 A_4 -\frac{1}{3} \Bigr |^2 \; , \nonumber \\= & {} \Bigl | \frac{1}{2} A_1^2 + \frac{2}{3} A_2^2 + \frac{1}{2} A_3^2 - A_1 A_3\nonumber \\{} & {} \qquad -\sqrt{\frac{2}{3}} A_0 A_2 -\sqrt{\frac{2}{3}} A_2 A_4 \Bigr |^2 \; , \end{aligned}$$
(80)
$$\begin{aligned} \tau _4= & {} \Big | 7 A_0^2 + 7 A_1^2 +8 A_2^2 +7 A_3^2 +7 A_4^2 -2 A_1 A_3 \nonumber \\ {}{} & {} \qquad + 2 A_0 A_4 -7\Big |^2 \; , \nonumber \\= & {} \left| A_2^2 -2 A_1 A_3 + 2 A_0 A_4 \right| ^2 \; , \end{aligned}$$
(81)

where the norm of the wavefunction has been used to simplify the expressions. It is clear that \(\tau _2\) can be non-zero only if \(\Lambda \ge 1\) is considered, and \(\tau _4\) can be non-zero only if \(\Lambda \ge 2\). Subsequently, one can determine the “irreducible” 4-spin entanglement, for the \(N=4\) system, given by Eq. (51) as

$$\begin{aligned} \eta _{4} \!=\! 1 - \frac{ {\langle \hat{J}_z\rangle }^2}{4} - 3 \tau _2 , \ \ \text{ with } \ \ {\langle \hat{J}_z\rangle } \!=\! \sum _{N_+} A_{N_+} \left( N_+ - \frac{N}{2}\right) .\nonumber \\ \end{aligned}$$
(82)

As a pedagogical case, we consider the limit when the wave function reduces to a single \(\left| N_+\right\rangle \) basis state. In that case there is only one non-zero coefficient \(A_{N_+} =1\).

  • For \(N_+=0\) (\(M=-2\)), the state consists of a single tensor-product state with spins aligned (all particles on the lower level). Such state is unentangled and indeed it is easy to see that all \(\tau _2\), \(\tau _4\) and \(\eta _4\) reduce to zero.

  • For \(N_+=1\) (\(M= -1\)), the state a W-like state, i.e. a superposition of configurations with only one of the spins up (one particle on the upper level). Such state has \(\tau _2=1/9\), while \(\tau _4=\eta _4 =0\). This of course is in agreement with the well known fact that W states have only 2-body entanglement.

  • For \(N_+=2\) (\(M= 0\)), the state is a superposition of configurations with equal number of spins up and down (same number of particles on the upper and lower level). Such state has \(\tau _2 = 1/9\), \(\tau _4 =1\), and \(\eta _4=2/3\), suggesting that genuine 4-spin entanglement is larger than the 2-spin entanglement.

A state with \(M>0\) has same entanglement properties as that with \(M<0\). The general case when the wave function is a superposition of states \(\left| N_+\right\rangle \) depends on the values of the coefficients which are governed by the interaction of the LMG model. The numerical results are shown in Sect. 3.2.2.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Hengstenberg, S.M., Robin, C.E.P. & Savage, M.J. Multi-body entanglement and information rearrangement in nuclear many-body systems: a study of the Lipkin–Meshkov–Glick model. Eur. Phys. J. A 59, 231 (2023). https://doi.org/10.1140/epja/s10050-023-01145-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1140/epja/s10050-023-01145-x

Navigation