A Remarkable Application of Zassenhaus Formula to Strongly Correlated Electron Systems
Louis Jourdan, Patrick Cassam-Chenaï
TL;DR
This work tackles the challenge of efficiently simulating quantum systems by decomposing the exponential of a sum of non-commuting operators. By exploiting a no-mixed adjoint property, the authors derive a closed-form Zassenhaus expansion: $e^{\hat{X}+\hat{Y}}=e^{\hat{X}}\exp\big(\sum_{n\ge 1}\frac{(-1)^{n-1}}{n!}ad^{n-1}_{\hat{X}}\hat{Y}\big)$, which becomes exact in a finite product for operators arising in mono- and di-excitations of electronic states. They apply this to a Unitary Frozen Pair CC (UfpCC) framework, particularly a 2D-block variant, showing that the excitation operators satisfy the no-mixed adjoint property and thus admit an exact circuit decomposition into Givens gates with a simple parameter map. For the general case of $N$ electron pairs, they derive a matrix-based expression using $M$ to yield an explicit, finite product of exponentials, with a gate count bounded by $\frac{N(N+1)}{2}$, providing a practical, Trotter-free route to quantum simulations of strongly correlated systems. Overall, the paper connects Lie-algebraic decompositions with quantum circuit design, offering a scalable, exact approach for preparing disentangled UCC states on NISQ devices and motivating further pair-based ansätze in quantum chemistry and beyond.
Abstract
We show that the Zassenhaus decomposition for the exponential of the sum of two non-commuting operators, simplifies drastically when these operators satisfy a simple condition, called the no-mixed adjoint property. An important application to a Unitary Coupled Cluster method for strongly correlated electron systems is presented. This ansatz requires no Trotterization and is exact on a quantum computer with a finite number of Givens gate equals to the number of free parameters. The formulas obtained in this work also shed light on why and when optimization after Trotterization gives exact solutions in disentangled forms of unitary coupled cluster.
