546,104 research outputs found
A Reference Interpreter for the Graph Programming Language GP 2
GP 2 is an experimental programming language for computing by graph
transformation. An initial interpreter for GP 2, written in the functional
language Haskell, provides a concise and simply structured reference
implementation. Despite its simplicity, the performance of the interpreter is
sufficient for the comparative investigation of a range of test programs. It
also provides a platform for the development of more sophisticated
implementations.Comment: In Proceedings GaM 2015, arXiv:1504.0244
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FABRIC: A National-Scale Programmable Experimental Network Infrastructure
FABRIC is a unique national research infrastructure to enable cutting-edge and exploratory research at-scale in networking, cybersecurity, distributed computing and storage systems, machine learning, and science applications. It is an everywhere-programmable nationwide instrument comprised of novel extensible network elements equipped with large amounts of compute and storage, interconnected by high speed, dedicated optical links. It will connect a number of specialized testbeds for cloud research (NSF Cloud testbeds CloudLab and Chameleon), for research beyond 5G technologies (Platforms for Advanced Wireless Research or PAWR), as well as production high-performance computing facilities and science instruments to create a rich fabric for a wide variety of experimental activities
Bounding quantum gate error rate based on reported average fidelity
Remarkable experimental advances in quantum computing are exemplified by
recent announcements of impressive average gate fidelities exceeding 99.9% for
single-qubit gates and 99% for two-qubit gates. Although these high numbers
engender optimism that fault-tolerant quantum computing is within reach, the
connection of average gate fidelity with fault-tolerance requirements is not
direct. Here we use reported average gate fidelity to determine an upper bound
on the quantum-gate error rate, which is the appropriate metric for assessing
progress towards fault-tolerant quantum computation, and we demonstrate that
this bound is asymptotically tight for general noise. Although this bound is
unlikely to be saturated by experimental noise, we demonstrate using explicit
examples that the bound indicates a realistic deviation between the true error
rate and the reported average fidelity. We introduce the Pauli distance as a
measure of this deviation, and we show that knowledge of the Pauli distance
enables tighter estimates of the error rate of quantum gates.Comment: New Journal of Physics Fast Track Communication. Gold open access
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Exploring More-Coherent Quantum Annealing
In the quest to reboot computing, quantum annealing (QA) is an interesting
candidate for a new capability. While it has not demonstrated an advantage over
classical computing on a real-world application, many important regions of the
QA design space have yet to be explored. In IARPA's Quantum Enhanced
Optimization (QEO) program, we have opened some new lines of inquiry to get to
the heart of QA, and are designing testbed superconducting circuits and
conducting key experiments. In this paper, we discuss recent experimental
progress related to one of the key design dimensions: qubit coherence. Using
MIT Lincoln Laboratory's qubit fabrication process and extending recent
progress in flux qubits, we are implementing and measuring QA-capable flux
qubits. Achieving high coherence in a QA context presents significant new
engineering challenges. We report on techniques and preliminary measurement
results addressing two of the challenges: crosstalk calibration and qubit
readout. This groundwork enables exploration of other promising features and
provides a path to understanding the physics and the viability of quantum
annealing as a computing resource.Comment: 7 pages, 3 figures. Accepted by the 2018 IEEE International
Conference on Rebooting Computing (ICRC
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