  Linear combination of unitaries (LCU) decompositions have appeared as one of
the main tools for encoding operators on quantum computers, allowing efficient
implementations of arbitrary operators. In particular, LCU approaches present a
way of encoding information from the electronic structure Hamiltonian into a
quantum circuit. Over the past years, many different decomposition techniques
have appeared for the electronic structure Hamiltonian. Here we present the
Majorana Tensor Decomposition (MTD), a framework that unifies existing LCUs and
offers novel decomposition methods by using popular low-rank tensor
factorizations.
