Quantum computers can process exponentially more information than classical computers. So, whereas,
classically, a 32-bit register can operate on one 32-bit number, a quantum counterpart could simultaneously
process 2^32 different numbers by using quantum entanglement and superposition. But you don't know which of
the 2^32 numbers you will see, and when you measure, you destroy your computer. No-one has succeeded in
building a useful quantum computer yet. Recently, physicists have developed a promising mo del called the
one-way quantum computer. It uses a pre-entangled graph resource. When you measure a graph vertex you
perform quantum computation and destroy that vertex. After all your measurements you have a residual graph
containing your quantum answer and a collection of measurement results which is your classical answer. How
does one efficiently interpret these measurements? Are some parts of the computation better done classically? We
will use message-passing algorithms on classical graphs to process and pass measurement results around the
quantum graph. Another viewpoint is that some of the vertices of the classical graph will be doped with quantum
vertices, and the overlaid quantum graph will enhance the message-passing algorithm. Usually message-p assing
algorithms are so efficient that they can solve seemingly exponentially hard problems. But they have their limits
and we expect that a suitably overlaid quantum graph could boost performance by a few well-chosen
measurements. So we have quantum and classical graphs - a Hybrid Quantum Computer Model. We will
investigate classical/quantum graph pairings of different geometries to see which work best. From our study of the
quantum graph and the Hybrid Model we will build new mathematical objects usefu l for classical coding,
cryptography, and telecommunications. Then we will investigate the performance of quantum algorithms in the
Hybrid Model, and look for best trade-offs between message-passing and measurement.