Computationally studying complex many-body phenomena such as quantum criticality is a difficult problem due to the exponential scaling of Hilbert space dimension with system sizes, and diverging correlation lengths at quantum critical points. One promising approach towards this involves adiabatically simulating the ground state of a qubit-encoded representation of the system in question, using a quantum device. To this end, many qubit encodings have been developed to map electronic and nuclear structure problems to spin-1/2 Hamiltonians. However, quantum hardware limitations currently prevent us from simulating sufficiently large lattices to probe macroscopic phenomena in many cases. In this work, we examine whether qubit encodings could be beneficial for classical simulations of many-body systems. We focus on quantum rotor lattices which can be used to model several exotic phenomena such as the formation of ferro-electric order in lattices of nano-confined dipolar molecules. Here, we first develop a qubit mapping for a d-dimensional dipolar planar rotor lattice and show that the resulting spin-1/2 Hamiltonian corresponds to a (d+1)-dimensional XXZ model, which is highly amenable to Stochastic Series Expansion Quantum Monte Carlo (SSE-QMC) approaches. SSE-QMC, in the past, has enjoyed remarkable success towards simulating critical phenomena in Bose-Hubbard and Ising models. Since SSE-QMC is unique to spin lattices, developing such algorithms for rotors directly is typically difficult. Using this XXZ representation, we develop an SSE algorithm for the qubit-mapped dipolar rotor lattice. Finally, we study the effectiveness of this approach by simulating the ground state of the dipolar planar rotor chain.