# On the generalization of the exponential basis for tensor network representations of long-range interactions in two and three dimensions

## TL;DR

This paper extends the exponential basis for tensor network representations of long-range interactions from 1D to higher dimensions, enabling efficient simulations of 2D and 3D quantum systems with long-range potentials.

## Contribution

The authors generalize the exponential basis to 2D and 3D using Green's functions of the Helmholtz equation, providing compact tensor network representations for long-range interactions.

## Key findings

- Tensor network representations for 2D and 3D long-range interactions are derived.
- The 3D construction yields a D=4 tensor network for Coulomb-like potentials.
- The method enables efficient simulation of realistic materials with long-range interactions.

## Abstract

In one dimension (1D), a general decaying long-range interaction can be fit to a sum of exponential interactions $e^{-\lambda r_{ij}}$ with varying exponents $\lambda$, each of which can be represented by a simple matrix product operator (MPO) with bond dimension $D=3$. Using this technique, efficient and accurate simulations of 1D quantum systems with long-range interactions can be performed using matrix product states (MPS). However, the extension of this construction to higher dimensions is not obvious. We report how to generalize the exponential basis to 2D and 3D by defining the basis functions as the Green's functions of the discretized Helmholtz equation for different Helmholtz parameters $\lambda$, a construction which is valid for lattices of any spatial dimension. Compact tensor network representations can then be found for the discretized Green's functions, by expressing them as correlation functions of auxiliary fermionic fields with nearest neighbor interactions via Grassmann Gaussian integration. Interestingly, this analytic construction in 3D yields a $D=4$ tensor network representation of correlation functions which (asymptotically) decay as the inverse distance ($r^{-1}_{ij}$), thus generating the (screened) Coulomb potential on a cubic lattice. These techniques will be useful in tensor network simulations of realistic materials.