Official Resources
- Repository: https://github.com/issp-center-dev/TeNeS
- Documentation: https://issp-center-dev.github.io/TeNeS/
- License: GNU General Public License v3.0
- Developers: ISSP (University of Tokyo)
Overview
TeNeS (Tensor Network Solver) is an open-source, massively parallel software package for calculating the ground-state wavefunctions of two-dimensional quantum many-body systems. It employs the infinite Projected Entangled Pair States (iPEPS) ansatz and optimizes it using imaginary time evolution. Designed for high-performance computing, TeNeS leverages the mptensor library for efficient distributed tensor operations, allowing it to tackle large bond dimensions and complex frustrated spin/boson models on square, honeycomb, and triangular lattices.
Scientific domain: Condensed Matter Physics, 2D Quantum Magnetism, Strongly Correlated Systems.
Target user community: Physicists studying ground state phases of 2D lattice models on supercomputers.
Theoretical Methods
- iPEPS: Infinite Projected Entangled Pair States ansatz for 2D systems.
- Imaginary Time Evolution: Simple and full update optimization schemes.
- CTMRG: Corner Transfer Matrix Renormalization Group for environment contraction.
- MFE: Mean-Field Environment method (optional).
- Lattices: Built-in support for Square, Honeycomb, and Triangular lattices.
Capabilities (CRITICAL)
- Massive Parallelism: Hybrid MPI/OpenMP parallelization for distributed memory systems.
- Ground State Search: Finds ground states of user-defined 2D Hamiltonians.
- Observables: Calculates magnetization, correlation functions, and energy.
- Finite T/Dynamics: (v2+) Support for finite temperature and real-time evolution.
- Simple Input: Utilities (
tenes_std, tenes_simple) to generate inputs for standard models (Heisenberg, Hubbard, etc.).
- Differentiable: Supports automatic differentiation in newer versions (check docs).
Key Strengths
HPC Scaling
- Built on
mptensor to distribute large tensors across nodes.
- Capable of handling larger $\chi$ (bond dimension) than single-node codes.
Versatility
- Handles varying unit cell sizes and common 2D geometries.
- Robust contraction using CTMRG.
Inputs & Outputs
- Input: TOML-based configuration for Hamiltonian, lattice, and run parameters.
- Output: Physical observables (energy, order parameters) and wavefunction checkpoint files.
Interfaces & Ecosystem
- Dependencies:
mptensor, ScaLAPACK, MPI.
- Language: C++ (Core), Python (Input generation tools).
- Integration: Part of the ISSP software suite (MateriApps).
Advanced Features
- Symmetries: Support for Abelian symmetries (U(1), Z2) via
mptensor.
- Checkpointing: Restart simulations from previous tensor states.
Performance Characteristics
- Speed: competitive with state-of-the-art C++ TN codes.
- Scalability: Excellent scaling on supercomputers (e.g., Fugaku, Summit) due to distributed tensor backend.
Computational Cost
- High: 2D TN contractions scale as $O(\chi^{10})$ or similar depending on the algorithm, requiring HPC for accurate results.
- Memory: Distributed memory allows handling tensors too large for a single node.
Comparison with Other Codes
- vs PEPS (QuantumLiquids): TeNeS uses CTMRG (deterministic contraction) and runs on clusters; PEPS uses Variational Monte Carlo (stochastic).
- vs ITensor: TeTenS is specialized for 2D infinite systems (iPEPS); ITensor is general but historically 1D-focused (MPS).
- vs peps-torch: peps-torch uses PyTorch and AD for optimization; TeNeS uses imaginary time evolution and C++ MPI.
Application Areas
- Frustrated Magnets: J1-J2 models, Kagome antiferromagnets.
- Bosonic Systems: Bose-Hubbard models.
- Quantum Phase Transitions: Determining phase boundaries in 2D.
Best Practices
- Bond Dimension: Systematically increase $\chi$ to check convergence.
- Environment: Ensure CTMRG environment dimension ($\chi_{env}$) is large enough (typically $\chi_{env}^2 \sim \chi$).
- Parallelism: Match MPI ranks to tensor block structure for efficiency.
Verification & Sources
Primary sources:
- Repository: https://github.com/issp-center-dev/TeNeS
- Paper: "TeNeS: Tensor Network Solver for Quantum Lattice Systems" (arXiv/phys. Rev.).
Confidence: VERIFIED - Established code from ISSP.
Verification status: ✅ VERIFIED