Simulation of three-dimensional quantum systems with projected entangled-pair states

Tensor network algorithms have proven to be very powerful tools for studying one- and two-dimensional quantum many-body systems. However, their application to three-dimensional (3D) quantum systems has so far been limited, mostly because the efficient contraction of a 3D tensor network is very challenging. In this paper, we develop and benchmark two contraction approaches for infinite projected entangled-pair states (iPEPS) in 3D. The first approach is based on a contraction of a finite cluster of tensors including an effective environment to approximate the full 3D network. The second approach performs a full contraction of the network by first iteratively contracting layers of the network with a boundary iPEPS, followed by a contraction of the resulting quasi-2D network using the corner transfer matrix renormalization group. Benchmark data for the Heisenberg and Bose-Hubbard models on the cubic lattice show that the algorithms provide competitive results compared to other approaches, making iPEPS a promising tool to study challenging open problems in 3D.

[1]  Frank Pollmann,et al.  Theory of finite-entanglement scaling at one-dimensional quantum critical points. , 2008, Physical review letters.

[2]  P. Corboz,et al.  Time evolution of an infinite projected entangled pair state: An efficient algorithm , 2018, Physical Review B.

[3]  J. Cirac,et al.  Algorithms for finite projected entangled pair states , 2014, 1405.3259.

[4]  J I Cirac,et al.  Classical simulation of infinite-size quantum lattice systems in two spatial dimensions. , 2008, Physical review letters.

[5]  I. Niesen,et al.  A tensor network study of the complete ground state phase diagram of the spin-1 bilinear-biquadratic Heisenberg model on the square lattice , 2017, 1707.01953.

[6]  M. Lewenstein,et al.  Efficient quantum simulation for thermodynamics of infinite-size many-body systems in arbitrary dimensions , 2018, Physical Review B.

[7]  Piotr Czarnik,et al.  Tensor network simulation of the Kitaev-Heisenberg model at finite temperature , 2019, Physical Review B.

[9]  D. Poilblanc,et al.  Nematic and supernematic phases in kagome quantum antiferromagnets under the influence of a magnetic field , 2014, 1406.7205.

[10]  R. Orús,et al.  Thermal bosons in 3d optical lattices via tensor networks , 2020, Scientific Reports.

[11]  Hoang Duong Tuan,et al.  Infinite projected entangled pair states algorithm improved: Fast full update and gauge fixing , 2015, 1503.05345.

[12]  Roman Orus,et al.  Exploring corner transfer matrices and corner tensors for the classical simulation of quantum lattice systems , 2011, 1112.4101.

[13]  White,et al.  Density matrix formulation for quantum renormalization groups. , 1992, Physical review letters.

[14]  Ericka Stricklin-Parker,et al.  Ann , 2005 .

[15]  D. Graf,et al.  Emergent bound states and impurity pairs in chemically doped Shastry-Sutherland system , 2018, Nature Communications.

[16]  J Chen,et al.  Gapless Spin-Liquid Ground State in the S=1/2 Kagome Antiferromagnet. , 2016, Physical review letters.

[17]  Z. Y. Xie,et al.  Coarse-graining renormalization by higher-order singular value decomposition , 2012, 1201.1144.

[18]  Garnet Kin-Lic Chan,et al.  Stripe order in the underdoped region of the two-dimensional Hubbard model , 2016, Science.

[19]  R. Orús,et al.  Fate of the cluster state on the square lattice in a magnetic field , 2012, 1205.5185.

[20]  P. Corboz,et al.  Period 4 stripe in the extended two-dimensional Hubbard model , 2019, Physical Review B.

[21]  Roman Orus,et al.  Simulation of two-dimensional quantum systems on an infinite lattice revisited: Corner transfer matrix for tensor contraction , 2009, 0905.3225.

[22]  Ho N. Phien,et al.  Fast convergence of imaginary time evolution tensor network algorithms by recycling the environment , 2014, 1411.0391.

[23]  F. Verstraete,et al.  Simulating excitation spectra with projected entangled-pair states , 2018, Physical Review B.

[24]  B. Svistunov,et al.  Phase diagram and thermodynamics of the three-dimensional Bose-Hubbard model , 2007, cond-mat/0701178.

[25]  Wei Li,et al.  Efficient simulation of infinite tree tensor network states on the Bethe lattice , 2012, 1209.2387.

[26]  Piotr Czarnik,et al.  Variational approach to projected entangled pair states at finite temperature , 2015, 1503.01077.

[27]  Bela Bauer,et al.  Simulation of strongly correlated fermions in two spatial dimensions with fermionic projected entangled-pair states , 2009, 0912.0646.

[28]  Lei Wang,et al.  Differentiable Programming Tensor Networks , 2019, Physical Review X.

[29]  M. Batchelor,et al.  Finite-temperature fidelity and von Neumann entropy in the honeycomb spin lattice with quantum Ising interaction , 2016, 1611.10072.

[30]  U. Schollwoeck The density-matrix renormalization group in the age of matrix product states , 2010, 1008.3477.

[31]  R. Haghshenas,et al.  U (1 ) -symmetric infinite projected entangled-pair states study of the spin-1/2 square J 1 -J 2 Heisenberg model , 2017, 1711.07584.

[32]  J. Ignacio Cirac,et al.  Unifying projected entangled pair state contractions , 2013, 1311.6696.

[33]  J. Eisert,et al.  Tensor Network Annealing Algorithm for Two-Dimensional Thermal States. , 2018, Physical review letters.

[34]  G. Vidal,et al.  Classical simulation of quantum many-body systems with a tree tensor network , 2005, quant-ph/0511070.

[35]  T. Xiang,et al.  Accurate determination of tensor network state of quantum lattice models in two dimensions. , 2008, Physical review letters.

[36]  Adam Nagy,et al.  Simulating quantum systems on the Bethe lattice by translationally invariant infinite-tree tensor network , 2011, 1106.3033.

[37]  Östlund,et al.  Thermodynamic limit of density matrix renormalization. , 1995, Physical review letters.

[38]  Glen Evenbly,et al.  Algorithms for tensor network renormalization , 2015, 1509.07484.

[39]  Yong Baek Kim,et al.  Magnetic field induced quantum phases in a tensor network study of Kitaev magnets , 2019, Nature Communications.

[40]  Numerical renormalization approach to two-dimensional quantum antiferromagnets with valence-bond-solid type ground state , 1999, cond-mat/9901155.

[42]  J. Latorre,et al.  Renormalization group contraction of tensor networks in three dimensions , 2011, 1112.1412.

[43]  Bin Xi,et al.  Theory of network contractor dynamics for exploring thermodynamic properties of two-dimensional quantum lattice models , 2013, 1301.6439.

[44]  Z. Y. Xie,et al.  Second renormalization of tensor-network states. , 2008, Physical review letters.

[45]  F. Pollmann,et al.  Phase diagram of the isotropic spin-3/2 model on the z=3 Bethe lattice , 2013, 1303.1110.

[46]  J. I. Latorre,et al.  Scaling of entanglement support for matrix product states , 2007, 0712.1976.

[47]  F. Verstraete,et al.  Faster methods for contracting infinite two-dimensional tensor networks , 2017, Physical Review B.

[48]  Fisher,et al.  Boson localization and the superfluid-insulator transition. , 1989, Physical review. B, Condensed matter.

[49]  M. Lewenstein,et al.  Few-body systems capture many-body physics: Tensor network approach , 2017, 1703.09814.

[50]  Hendrik Weimer,et al.  A simple tensor network algorithm for two-dimensional steady states , 2016, Nature Communications.

[51]  Frédéric Mila,et al.  Crystals of bound states in the magnetization plateaus of the Shastry-Sutherland model. , 2014, Physical review letters.

[52]  M. Rams,et al.  Tensor network study of the m=12 magnetization plateau in the Shastry-Sutherland model at finite temperature , 2020, Physical Review B.

[53]  Edward Farhi,et al.  Quantum transverse-field Ising model on an infinite tree from matrix product states , 2007, 0712.1806.

[54]  Shi-Ju Ran,et al.  Fermionic algebraic quantum spin liquid in an octa-kagome frustrated antiferromagnet , 2017, 1705.06006.

[55]  M. Fannes,et al.  Finitely correlated states on quantum spin chains , 1992 .

[56]  A. Weichselbaum,et al.  Emergent spin-1 trimerized valence bond crystal in the spin-1/2 Heisenberg model on the star lattice , 2015, 1508.03451.

[57]  Yasuhiro Hieida,et al.  Two-Dimensional Tensor Product Variational Formulation , 2001 .

[58]  A. Honecker,et al.  Thermodynamic properties of the Shastry-Sutherland model throughout the dimer-product phase , 2019, Physical Review Research.

[59]  M. Kikuchi,et al.  NUMERICAL RENORMALIZATION GROUP AT CRITICALITY , 1996, cond-mat/9601078.

[60]  N Maeshima,et al.  Vertical density matrix algorithm: a higher-dimensional numerical renormalization scheme based on the tensor product state ansatz. , 2001, Physical review. E, Statistical, nonlinear, and soft matter physics.

[61]  G. Evenbly,et al.  Tensor Network Renormalization. , 2014, Physical review letters.

[62]  J. Eisert,et al.  Tensor network investigation of the double layer Kagome compound Ca10Cr7O28 , 2020 .

[63]  Shi-Ju Ran,et al.  Thermodynamics of spin-1/2 Kagomé Heisenberg antiferromagnet: algebraic paramagnetic liquid and finite-temperature phase diagram. , 2017, Science bulletin.

[64]  Bin Xi,et al.  Optimized decimation of tensor networks with super-orthogonalization for two-dimensional quantum lattice models , 2012, 1205.5636.

[65]  Piotr Czarnik,et al.  Projected entangled pair states at finite temperature: Iterative self-consistent bond renormalization for exact imaginary time evolution , 2014, 1411.6778.

[66]  R. Orús,et al.  Spin-S Kagome quantum antiferromagnets in a field with tensor networks , 2015, 1508.07189.

[67]  F. Becca,et al.  Investigation of the Néel phase of the frustrated Heisenberg antiferromagnet by differentiable symmetric tensor networks , 2020, SciPost Physics.

[68]  Danna Zhou,et al.  d. , 1840, Microbial pathogenesis.

[69]  Matthias Troyer,et al.  Competing states in the t-J model: uniform D-wave state versus stripe state. , 2014, Physical review letters.

[70]  A. Gendiar,et al.  Latent heat calculation of the three-dimensional q=3, 4, and 5 Potts models by the tensor product variational approach. , 2001, Physical review. E, Statistical, nonlinear, and soft matter physics.

[71]  Guifré Vidal Efficient simulation of one-dimensional quantum many-body systems. , 2004, Physical review letters.

[72]  M. Troyer,et al.  Implementing global Abelian symmetries in projected entangled-pair state algorithms , 2010, 1010.3595.

[73]  Satoshi Morita,et al.  Boundary tensor renormalization group , 2019, Physical Review B.

[74]  F. Verstraete,et al.  Matrix product states for critical spin chains: Finite-size versus finite-entanglement scaling , 2012, Physical Review B.

[75]  A. Lauchli,et al.  Finite Correlation Length Scaling in Lorentz-Invariant Gapless iPEPS Wave Functions , 2018, Physical Review X.

[76]  Piotr Czarnik,et al.  Time evolution of an infinite projected entangled pair state: An algorithm from first principles , 2018, Physical Review B.

[77]  P. Corboz,et al.  Finite Correlation Length Scaling with Infinite Projected Entangled-Pair States , 2018, Physical Review X.

[78]  A. Gendiar,et al.  Stable Optimization of a Tensor Product Variational State , 2003, cond-mat/0303376.

[79]  S. Todo,et al.  The ALPS project release 2.0: open source software for strongly correlated systems , 2011, 1101.2646.

[80]  Self-consistent tensor product variational approximation for 3D classical models , 2000 .

[81]  M. Tarzia,et al.  Exact solution of the Bose-Hubbard model on the Bethe lattice , 2009, 0904.3075.

[82]  Linearized tensor renormalization group algorithm for the calculation of thermodynamic properties of quantum lattice models. , 2010, Physical review letters.

[83]  T. Nishino,et al.  Corner Transfer Matrix Renormalization Group Method , 1995, cond-mat/9507087.

[84]  Peiyuan Teng Generalization of the tensor renormalization group approach to 3-D or higher dimensions , 2016, 1605.00062.

[85]  P. Corboz,et al.  Finite correlation length scaling with infinite projected entangled pair states at finite temperature , 2019, Physical Review B.

[86]  M. Troyer,et al.  Dynamical mean field solution of the Bose-Hubbard model. , 2010, Physical Review Letters.

[87]  Lukasz Cincio,et al.  Projected entangled pair states at finite temperature: Imaginary time evolution with ancillas , 2012, 1209.0454.

[88]  R. Orús,et al.  Universal tensor-network algorithm for any infinite lattice , 2018, Physical Review B.

[89]  Simon Friederich,et al.  Functional renormalization for spontaneous symmetry breaking in the Hubbard model , 2010, 1012.5436.

[90]  Frank Verstraete,et al.  Residual entropies for three-dimensional frustrated spin systems with tensor networks , 2018, Physical Review E.

[91]  G. G. Stokes "J." , 1890, The New Yale Book of Quotations.

[92]  Frank Verstraete,et al.  Gradient methods for variational optimization of projected entangled-pair states , 2016, 1606.09170.

[93]  A. M. Ole's,et al.  Overcoming the sign problem at finite temperature: Quantum tensor network for the orbital eg model on an infinite square lattice , 2017, 1703.03586.

[94]  J. Cirac,et al.  Time-dependent study of disordered models with infinite projected entangled pair states , 2018, SciPost Physics.

[95]  Philippe Corboz,et al.  Variational optimization with infinite projected entangled-pair states , 2016, 1605.03006.

[96]  Guifre Vidal,et al.  Tensor network states and algorithms in the presence of a global SU(2) symmetry , 2010, 1008.4774.

[97]  P. Corboz,et al.  SU(3) fermions on the honeycomb lattice at 13 filling , 2019, Physical Review B.

[98]  W. Marsden I and J , 2012 .

[99]  J. I. Cirac,et al.  Variational study of hard-core bosons in a two-dimensional optical lattice using projected entangled pair states , 2007 .

[100]  N. Schuch,et al.  SU(3)_{1} Chiral Spin Liquid on the Square Lattice: A View from Symmetric Projected Entangled Pair States. , 2019, Physical review letters.

[101]  Tomotoshi Nishino,et al.  A Density Matrix Algorithm for 3D Classical Models , 1998 .

[102]  Michael Levin,et al.  Tensor renormalization group approach to two-dimensional classical lattice models. , 2006, Physical review letters.

[103]  F. Verstraete,et al.  Variational optimization algorithms for uniform matrix product states , 2017, 1701.07035.

[104]  A. Honecker,et al.  The ALPS project release 1.3: Open-source software for strongly correlated systems , 2007 .