In this work, we discuss two modifications that can be made to a known
variational quantum singular value decomposition algorithm popular in the
literature. The first is a change to the objective function which hints at
improved performance of the algorithm and decreases the depth of the circuits.
The second modification introduces a new way of computing expectation values of
general matrices, which is a key step in the algorithm. We then benchmark this
modified algorithm and compare the performance of our new objective function
with the existing one.Comment: 8 pages, 10 figures, 2 table