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  • Letter
  • Open Access

Fitness landscape for quantum state tomography from neutron scattering

Tymoteusz Tula, Jorge Quintanilla*, and Gunnar Möller†

  • Physics of Quantum and Materials Group, School of Engineering, Mathematics and Physics, University of Kent, Canterbury, Kent CT2 7NH, United Kingdom

  • *Contact author: J.Quintanilla@kent.ac.uk
  • †Contact author: G.Moller@kent.ac.uk

Phys. Rev. B 112, L140402 – Published 16 October, 2025

DOI: https://doi.org/10.1103/x9mb-x1gz

Abstract

Recently, a direct connection between static structure factors and quantum ground states for two-spin interaction Hamiltonians was proven. This suggests the possibility of quantum state tomography from neutron scattering. Here, we investigate the associated fitness landscape numerically. We find a linear relationship between the mean-square distances of structure factors and associated state overlaps, implying a well-behaved fitness landscape. Furthermore, we find evidence suggesting that the approach can be generalized to thermal equilibrium states. We also extend the arguments to the cases of applied magnetic fields and finite clusters.

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References (37)

  1. P. Hohenberg and W. Kohn, Inhomogeneous electron gas, Phys. Rev. 136, B864 (1964).
  2. T. K. Ng, Generalized Hohenberg-Kohn theorem and effective Hamiltonian of a quantum system, Phys. Rev. B 44, 2407 (1991).
  3. J. Quintanilla, Relationship between the wave function of a magnet and its static structure factor, Phys. Rev. B 106, 104435 (2022).
  4. B. Murta and J. Fernández-Rossier, One-to-one correspondence between thermal structure factors and coupling constants of general bilinear Hamiltonians, Phys. Rev. E 105, L062101 (2022).
  5. B. Swingle and I. H. Kim, Reconstructing quantum states from local data, Phys. Rev. Lett. 113, 260501 (2014).
  6. M. Cramer, M. B. Plenio, S. T. Flammia, R. Somma, D. Gross, S. D. Bartlett, O. Landon-Cardinal, D. Poulin, and Y.-K. Liu, Efficient quantum state tomography, Nat. Commun. 1, 149 (2010).
  7. E. Chertkov and B. K. Clark, Computational inverse method for constructing spaces of quantum models from wave functions, Phys. Rev. X 8, 031029 (2018).
  8. M. Greiter, V. Schnells, and R. Thomale, Method to identify parent Hamiltonians for trial states, Phys. Rev. B 98, 081113(R) (2018).
  9. E. Bairey, I. Arad, and N. H. Lindner, Learning a local Hamiltonian from local measurements, Phys. Rev. Lett. 122, 020504 (2019).
  10. X.-L. Qi and D. Ranard, Determining a local Hamiltonian from a single eigenstate, Quantum 3, 159 (2019).
  11. X. Turkeshi, T. Mendes-Santos, G. Giudici, and M. Dalmonte, Entanglement-guided search for parent Hamiltonians, Phys. Rev. Lett. 122, 150606 (2019).
  12. A. Anshu, S. Arunachalam, T. Kuwahara, and M. Soleimanifar, Sample-efficient learning of interacting quantum systems, Nat. Phys. 17, 931 (2021).
  13. R. Coldea, D. A. Tennant, E. M. Wheeler, E. Wawrzynska, D. Prabhakaran, M. Telling, K. Habicht, P. Smeibidl, and K. Kiefer, Quantum criticality in an Ising chain: Experimental evidence for emergent E8 symmetry, Science 327, 177 (2010).
  14. O. Breunig, M. Garst, A. Klümper, J. Rohrkamp, M. M. Turnbull, and T. Lorenz, Quantum criticality in the spin-1/2 Heisenberg chain system copper pyrazine dinitrate, Sci. Adv. 3, eaao3773 (2017).
  15. See Supplemental Material at http://link.aps.org/supplemental/10.1103/x9mb-x1gz for further details on our approach to sampling the fitness landscape; the chosen metrics for scattering function and state spaces; sampling random pure states or density matrices near a target state; extending the theorems underpinning Hamiltonian learning and quantum state tomography from magnetic structure factors to Hamiltonians with arbitrary local magnetic fields; and extending these proofs to finite magnetic clusters, which includes Refs. [33, 34, 35, 36, 37].
  16. J. Schnack, in Computational Modelling of Molecular Nanomagnets, edited by G. Rajaraman (Springer, Cham, 2023), pp. 155–177.
  17. A. Kandala, A. Mezzacapo, K. Temme, M. Takita, M. Brink, J. M. Chow, and J. M. Gambetta, Hardware-efficient variational quantum eigensolver for small molecules and quantum magnets, Nature (London) 549, 242 (2017).
  18. An analysis of the difficulty of proving this rigorously has been offered in Ref. [4].
  19. F. Becca and S. Sorella, Quantum Monte Carlo Approaches for Correlated Systems (Cambridge University Press, Cambridge, UK, 2017).
  20. K. Capelle, A bird's-eye view of density-functional theory, Braz. J. Phys. 36, 1318 (2006).
  21. P. O. Scherer, Computational Physics (Springer, Berlin, 2010).
  22. G. Carleo and M. Troyer, Solving the quantum many-body problem with artificial neural networks, Science 355, 602 (2017).
  23. J.-G. Liu, L. Mao, P. Zhang, and L. Wang, Solving quantum statistical mechanics with variational autoregressive networks and quantum circuits, Mach. Learn.: Sci. Technol. 2, 025011 (2021).
  24. H. Ott, Single atom detection in ultracold quantum gases: A review of current progress, Rep. Prog. Phys. 79, 054401 (2016).
  25. M. F. Parsons, A. Mazurenko, C. S. Chiu, G. Ji, D. Greif, and M. Greiner, Site-resolved measurement of the spin-correlation function in the Fermi-Hubbard model, Science 353, 1253 (2016).
  26. Y. A. Alaoui, B. Zhu, S. R. Muleady, W. Dubosclard, T. Roscilde, A. M. Rey, B. Laburthe-Tolra, and L. Vernac, Measuring correlations from the collective spin fluctuations of a large ensemble of lattice-trapped dipolar spin-3 atoms, Phys. Rev. Lett. 129, 023401 (2022).
  27. P. Willke, Y. Bae, K. Yang, J. L. Lado, A. Ferrón, T. Choi, A. Ardavan, J. Fernández-Rossier, A. J. Heinrich, and C. P. Lutz, Hyperfine interaction of individual atoms on a surface, Science 362, 336 (2018).
  28. R. J. G. Elbertse, D. Coffey, J. Gobeil, and A. F. Otte, Remote detection and recording of atomic-scale spin dynamics, Commun. Phys. 3, 94 (2020).
  29. S.-h. Phark, Y. Chen, H. T. Bui, Y. Wang, M. Haze, J. Kim, Y. Bae, A. J. Heinrich, and C. Wolf, Double-resonance spectroscopy of coupled electron spins on a surface, ACS Nano 17, 14144 (2023).
  30. Y. del Castillo and J. Fernández-Rossier, Certifying entanglement of spins on surfaces using ESR-STM, Phys. Rev. B 108, 115413 (2023).
  31. V. Zauner, D. Draxler, L. Vanderstraeten, J. Haegeman, and F. Verstraete, Symmetry breaking and the geometry of reduced density matrices, New J. Phys. 18, 113033 (2016).
  32. T. Tula, G. Möller, and J. Quintanilla, Tymoteusztula/fitnesslandscape: V1.0.2, Zenodo (2025), https://doi.org/10.5281/zenodo.16844743.
  33. H. R. Irons, J. Quintanilla, T. G. Perring, L. Amico, and G. Aeppli, Control of entanglement transitions in quantum spin clusters, Phys. Rev. B 96, 224408 (2017).
  34. C. Broholm, Neutron scattering, correlation functions & linear response functions, Lecture notes (2010), https://neutrons2.ornl.gov/conf/nxs2013/lecture/pdf/SS-2013BroholmMagneticNeutronScattering.pdf.
  35. E. Ising, Beitrag zur Theorie des Ferromagnetismus, Ph.D. thesis, University of Hamburg, 1924; Z. Physik 31, 253 (1925).
  36. S.-J. Gu, G.-S. Tian, and H.-Q. Lin, Ground-state entanglement in the XXZ model, Phys. Rev. A 71, 052322 (2005).
  37. A. Kitaev, Anyons in an exactly solved model and beyond, Ann. Phys. 321, 2 (2006).

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