This fixes a bug in the multithreaded block sparse code when a block sparse contraction doesn't result in any viable blocks, for example, something like:
using ITensors
i = Index([QN(0) => 1, QN(1) => 1])
A = emptyITensor(i', dag(i))
B = emptyITensor(i', dag(i))
A[i' => 1, i => 1] = 11.0
B[i' => 2, i => 2] = 22.0
using_threaded_blocksparse = ITensors.disable_threaded_blocksparse()
C1 = A' * B
ITensors.enable_threaded_blocksparse()
C2 = A' * B
if using_threaded_blocksparse
ITensors.enable_threaded_blocksparse()
else
ITensors.disable_threaded_blocksparse()
end
This showed up in a very particular DMRG calculation (2D Hubbard model conserving spin and particle number, with the Hamiltonian modified by splitblocks and using multithreading over blocks). It only showed up in the multithreading code since the serial code automatically handled this special case.
This fixes a bug in the multithreaded block sparse code when a block sparse contraction doesn't result in any viable blocks, for example, something like:
This showed up in a very particular DMRG calculation (2D Hubbard model conserving spin and particle number, with the Hamiltonian modified by
splitblocksand using multithreading over blocks). It only showed up in the multithreading code since the serial code automatically handled this special case.