# Tensor Network libraries: comparisons and future directions

+ 2 like - 0 dislike
353 views

Can the QuTiP library be used to implement tensor network models with the same kind of features offered by the iTensor and Xerus libraries? What about TensorFlow, can it be used for this purpose to take advantage of its readiness to run on GPUs and distributed systems? iTensor seems to be better maintained, but TensorFlow is very recent and maybe it can achieve better performance (?), on top of having a simple Python interface. Are there example codes with QuTiP and/or TensorFlow implementing MPS, DMRG, MERA, PEPS, etc? Other libraries I see are TNT and OpenMPS. So many options...

I'm looking for opinions, advice and insights from users with first-hand experience in simulating tensor networks on the applications achievable by these and other software libraries around, and how they compare in performance, usability, available algorithms, and future perspectives.

 Please use answers only to (at least partly) answer questions. To comment, discuss, or ask for clarification, leave a comment instead. To mask links under text, please type your text, highlight it, and click the "link" button. You can then enter your link URL. Please consult the FAQ for as to how to format your post. This is the answer box; if you want to write a comment instead, please use the 'add comment' button. Live preview (may slow down editor)   Preview Your name to display (optional): Email me at this address if my answer is selected or commented on: Privacy: Your email address will only be used for sending these notifications. Anti-spam verification: If you are a human please identify the position of the character covered by the symbol $\varnothing$ in the following word:p$\hbar$ysicsOver$\varnothing$lowThen drag the red bullet below over the corresponding character of our banner. When you drop it there, the bullet changes to green (on slow internet connections after a few seconds). To avoid this verification in future, please log in or register.