Is there really such a thing as a 1000-qubit quantum computer that works?
Does D-Wave's computer really exhibit quantum effects?
What problems can you calculate with a D-Wave, and why did Google and NASA buy them?
Is a D-Wave really any faster than running a commercial software package like CPLEX
on a cluster of Intel or AMD machines?

And really, what's the difference between adiabatic quantum computation
and the quantum gate model?  

These are all controversial questions (except the last one).
Tomorrow's colloquium will address them.  I think it'll be interesting.

REMINDER:  Lunch is served at 12:15; the talk starts promptly at 12:30!
If you want lunch, come at 12:20 so you can get into the room before the
talk starts.  This applies to ALL lunchtime colloquiua in room 105.

-- Andrew Appel





Colloquium Speaker
Catherine McGeoch, Amherst College and D-Wave Systems
Benchmarking the D-Wave 2X: Challenges and Early Results
Tuesday, October 20- 12:30pm
Computer Science 105

Benchmarking the D-Wave 2X: Challenges and Early Results

A D-Wave platform implements a quantum annealing algorithm in hardware, to solve an NP-hard problem known as Ising Model Optimization (also called Quadratic Unconstrained Boolean Optimization).   The ``hardware'' is a processor chip containing qubits that exploit quantum properties such as superposition and entanglement to carry out the computation.   This is a heuristic algorithm that belongs to the adiabatic quantum model of computation, an alternative to the more familiar quantum gate model of computation.

The task of performance assessment for these novel platforms  -- comparing classical heuristics implemented in software to a quantum analog heuristic implemented in hardware -- gives rise to a number of new methodological issues, on top of the usual challenges relating to evaluation   of heuristics for NP-hard problems.  I will discuss some of these issues and present some early performance results for the D-Wave 2X,  a 1000-qubit processor launched in summer 2015.





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