1,392 research outputs found
Computational speedups using small quantum devices
Suppose we have a small quantum computer with only M qubits. Can such a
device genuinely speed up certain algorithms, even when the problem size is
much larger than M? Here we answer this question to the affirmative. We present
a hybrid quantum-classical algorithm to solve 3SAT problems involving n>>M
variables that significantly speeds up its fully classical counterpart. This
question may be relevant in view of the current quest to build small quantum
computers.Comment: 5+12 page
Network Community Detection On Small Quantum Computers
In recent years a number of quantum computing devices with small numbers of
qubits became available. We present a hybrid quantum local search (QLS)
approach that combines a classical machine and a small quantum device to solve
problems of practical size. The proposed approach is applied to the network
community detection problem. QLS is hardware-agnostic and easily extendable to
new quantum computing devices as they become available. We demonstrate it to
solve the 2-community detection problem on graphs of size up to 410 vertices
using the 16-qubit IBM quantum computer and D-Wave 2000Q, and compare their
performance with the optimal solutions. Our results demonstrate that QLS
perform similarly in terms of quality of the solution and the number of
iterations to convergence on both types of quantum computers and it is capable
of achieving results comparable to state-of-the-art solvers in terms of quality
of the solution including reaching the optimal solutions
Quantum machine learning: a classical perspective
Recently, increased computational power and data availability, as well as
algorithmic advances, have led machine learning techniques to impressive
results in regression, classification, data-generation and reinforcement
learning tasks. Despite these successes, the proximity to the physical limits
of chip fabrication alongside the increasing size of datasets are motivating a
growing number of researchers to explore the possibility of harnessing the
power of quantum computation to speed-up classical machine learning algorithms.
Here we review the literature in quantum machine learning and discuss
perspectives for a mixed readership of classical machine learning and quantum
computation experts. Particular emphasis will be placed on clarifying the
limitations of quantum algorithms, how they compare with their best classical
counterparts and why quantum resources are expected to provide advantages for
learning problems. Learning in the presence of noise and certain
computationally hard problems in machine learning are identified as promising
directions for the field. Practical questions, like how to upload classical
data into quantum form, will also be addressed.Comment: v3 33 pages; typos corrected and references adde
Quantum Discord and Quantum Computing - An Appraisal
We discuss models of computing that are beyond classical. The primary
motivation is to unearth the cause of nonclassical advantages in computation.
Completeness results from computational complexity theory lead to the
identification of very disparate problems, and offer a kaleidoscopic view into
the realm of quantum enhancements in computation. Emphasis is placed on the
`power of one qubit' model, and the boundary between quantum and classical
correlations as delineated by quantum discord. A recent result by Eastin on the
role of this boundary in the efficient classical simulation of quantum
computation is discussed. Perceived drawbacks in the interpretation of quantum
discord as a relevant certificate of quantum enhancements are addressed.Comment: To be published in the Special Issue of the International Journal of
Quantum Information on "Quantum Correlations: entanglement and beyond." 11
pages, 4 figure
Quantum Computing in the NISQ era and beyond
Noisy Intermediate-Scale Quantum (NISQ) technology will be available in the
near future. Quantum computers with 50-100 qubits may be able to perform tasks
which surpass the capabilities of today's classical digital computers, but
noise in quantum gates will limit the size of quantum circuits that can be
executed reliably. NISQ devices will be useful tools for exploring many-body
quantum physics, and may have other useful applications, but the 100-qubit
quantum computer will not change the world right away --- we should regard it
as a significant step toward the more powerful quantum technologies of the
future. Quantum technologists should continue to strive for more accurate
quantum gates and, eventually, fully fault-tolerant quantum computing.Comment: 20 pages. Based on a Keynote Address at Quantum Computing for
Business, 5 December 2017. (v3) Formatted for publication in Quantum, minor
revision
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