234 research outputs found
A note on QUBO instances defined on Chimera graphs
McGeoch and Wang (2013) recently obtained optimal or near-optimal solutions
to some quadratic unconstrained boolean optimization (QUBO) problem instances
using a 439 qubit D-Wave Two quantum computing system in much less time than
with the IBM ILOG CPLEX mixed-integer quadratic programming (MIQP) solver. The
problems studied by McGeoch and Wang are defined on subgraphs -- with up to 439
nodes -- of Chimera graphs. We observe that after a standard reformulation of
the QUBO problem as a mixed-integer linear program (MILP), the specific
instances used by McGeoch and Wang can be solved to optimality with the CPLEX
MILP solver in much less time than the time reported in McGeoch and Wang for
the CPLEX MIQP solver. However, the solution time is still more than the time
taken by the D-Wave computer in the McGeoch-Wang tests.Comment: Version 1 discussed computational results with random QUBO instances.
McGeoch and Wang made an error in describing the instances they used; they
did not use random QUBO instances but rather random Ising Model instances
with fields (mapped to QUBO instances). The current version of the note
reports on tests with the precise instances used by McGeoch and Wan
QuASeR -- Quantum Accelerated De Novo DNA Sequence Reconstruction
In this article, we present QuASeR, a reference-free DNA sequence
reconstruction implementation via de novo assembly on both gate-based and
quantum annealing platforms. Each one of the four steps of the implementation
(TSP, QUBO, Hamiltonians and QAOA) is explained with simple proof-of-concept
examples to target both the genomics research community and quantum application
developers in a self-contained manner. The details of the implementation are
discussed for the various layers of the quantum full-stack accelerator design.
We also highlight the limitations of current classical simulation and available
quantum hardware systems. The implementation is open-source and can be found on
https://github.com/prince-ph0en1x/QuASeR.Comment: 24 page
Towards Hybrid Classical-Quantum Computation Structures in Wirelessly-Networked Systems
With unprecedented increases in traffic load in today's wireless networks,
design challenges shift from the wireless network itself to the computational
support behind the wireless network. In this vein, there is new interest in
quantum-compute approaches because of their potential to substantially speed up
processing, and so improve network throughput. However, quantum hardware that
actually exists today is much more susceptible to computational errors than
silicon-based hardware, due to the physical phenomena of decoherence and noise.
This paper explores the boundary between the two types of
computation---classical-quantum hybrid processing for optimization problems in
wireless systems---envisioning how wireless can simultaneously leverage the
benefit of both approaches. We explore the feasibility of a hybrid system with
a real hardware prototype using one of the most advanced experimentally
available techniques today, reverse quantum annealing. Preliminary results on a
low-latency, large MIMO system envisioned in the 5G New Radio roadmap are
encouraging, showing approximately 2--10X better performance in terms of
processing time than prior published results.Comment: HotNets 2020: Nineteenth ACM Workshop on Hot Topics in Networks
(https://doi.org/10.1145/3422604.3425924
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