  Utilizing present and futuristic Quantum Computers to solve difficult
problems in different domains has become one of the main endeavors at this
moment. Of course, in arriving at the requisite solution both quantum and
classical computers work in conjunction. With the continued popularity of Low
Density Parity Check (LDPC) codes and hence their decoding, this paper looks
into the latter as a Quadratic Unconstrained Binary Optimization (QUBO) and
utilized D-Wave 2000Q Quantum Annealer to solve it. The outputs from the
Annealer are classically post-processed using simple minimum distance decoding
to further improve the performance. We evaluated and compared this
implementation against the decoding performance obtained using Simulated
Annealing (SA) and belief propagation (BP) decoding with classical computers.
The results show that implementations of annealing (both simulated and quantum)
are superior to BP decoding and suggest that the advantage becomes more
prominent as block lengths increase. Reduced Bit Error Rate (BER) and Frame
Error Rate (FER) are observed for simulated annealing and quantum annealing, at
useful SNR range - a trend that persists for various codeword lengths.
