Clone via github.
(Preferred method—see our git quickstart guide.)
Or download latest
ITensor—Intelligent Tensor—is a C++ library for implementing tensor product wavefunction calculations.
It is efficient and flexible enough to be used for research-grade simulations.
- A complete DMRG code
- Efficient matrix product state class
- Quantum number conserving tensors
- Complex numbers (handled lazily: no efficiency loss if real)
- Easy install: only dependency is BLAS/Lapack
- ITensor Version 1.0
- Article: Should you use Periodic Boundary Conditions in DMRG?
- ITensor at 2014 Sherbrooke Summer School
ITensors are as easy to multiply as scalars: matching indices automatically contract, making it simple to transcribe tensor network diagrams into correct, efficient code.
For example, the diagram below (resembling the overlap of two matrix product states) can be converted to code as
- Clone the latest version:
Or download zip file if you do not have git.
git clone https://github.com/ITensor/ITensor itensor
(Cloning with git allows you to track changes to ITensor and is the preferred method; for more see our git quickstart guide.)
- Read the installation instructions.
- Learn more from the documentation.
Perform a DMRG Calculation
SpinOne sites(100); //define Hilbert space of 100 spin-lattice sites MPO H = Heisenberg(sites); //pre-defined Hamiltonian; easy to write your own MPS psi(sites); Sweeps sweeps(5); //perform 5 sweeps of DMRG sweeps.maxm() = 50, 50, 100, 100, 200; //max number of states kept each sweep dmrg(psi,H,sweeps); //run the DMRG algorithm Real energy = psiHphi(psi,H,psi); //can analyze wavefunction afterwards
Multiply Two ITensors
Index a("a",2), b("b",2), c("c",2); ITensor Z(a,b), X(c,b); commaInit(Z,a,b) = 1, 0, 0,-1; commaInit(X,b,c) = 0, 1, 1, 0; //the * operator finds and //contracts common index 'b' //regardless of index order: ITensor R = Z * X; Print( R(a(1),c(2)) ); //Prints: R(a(1),c(2)) = 1 Print( R(a(2),c(1)) ); //Prints: R(a(1),c(2)) = -1