4 research outputs found
Peering into the Anneal Process of a Quantum Annealer
Commercial adiabatic quantum annealers have the potential to solve important
NP-hard optimization problems efficiently. The newest generation of those
machines additionally allows the user to customize the anneal schedule, that
is, the schedule with which the anneal fraction is changed from the start to
the end of the annealing. In this work we use the aforementioned feature of the
D-Wave 2000Q to attempt to monitor how the anneal solution evolves during the
anneal process. This process we call slicing: at each time slice during the
anneal, we are able to obtain an approximate distribution of anneal solutions.
We use our technique to obtain a variety of insights into the D-Wave 2000Q. For
example, we observe when individual bits flip during the anneal process and
when they stabilize, which allows us to determine the freeze-out point for each
qubit individually. We highlight our results using both random QUBO (quadratic
unconstrained binary optimization) instances and, for better visualization,
instances which we specifically optimize (using our own genetic algorithm) to
exhibit a pronounced evolution of its solution during the anneal
Inferring the Dynamics of the State Evolution During Quantum Annealing
To solve an optimization problem using a commercial quantum annealer, one has
to represent the problem of interest as an Ising or a quadratic unconstrained
binary optimization (QUBO) problem and submit its coefficients to the annealer,
which then returns a user-specified number of low-energy solutions. It would be
useful to know what happens in the quantum processor during the anneal process
so that one could design better algorithms or suggest improvements to the
hardware. However, existing quantum annealers are not able to directly extract
such information from the processor. Hence, in this work we propose to use
advanced features of D-Wave 2000Q to indirectly infer information about the
dynamics of the state evolution during the anneal process. Specifically, D-Wave
2000Q allows the user to customize the anneal schedule, that is, the schedule
with which the anneal fraction is changed from the start to the end of the
anneal. Using this feature, we design a set of modified anneal schedules whose
outputs can be used to generate information about the states of the system at
user-defined time points during a standard anneal. With this process, called
"slicing", we obtain approximate distributions of lowest-energy anneal
solutions as the anneal time evolves. We use our technique to obtain a variety
of insights into the annealer, such as the state evolution during annealing,
when individual bits in an evolving solution flip during the anneal process and
when they stabilize, and we introduce a technique to estimate the freeze-out
point of both the system as well as of individual qubits