453,750 research outputs found
Relative multiplexing for minimizing switching in linear-optical quantum computing
Many existing schemes for linear-optical quantum computing (LOQC) depend on
multiplexing (MUX), which uses dynamic routing to enable near-deterministic
gates and sources to be constructed using heralded, probabilistic primitives.
MUXing accounts for the overwhelming majority of active switching demands in
current LOQC architectures. In this manuscript, we introduce relative
multiplexing (RMUX), a general-purpose optimization which can dramatically
reduce the active switching requirements for MUX in LOQC, and thereby reduce
hardware complexity and energy consumption, as well as relaxing demands on
performance for various photonic components. We discuss the application of RMUX
to the generation of entangled states from probabilistic single-photon sources,
and argue that an order of magnitude improvement in the rate of generation of
Bell states can be achieved. In addition, we apply RMUX to the proposal for
percolation of a 3D cluster state in [PRL 115, 020502 (2015)], and we find that
RMUX allows a 2.4x increase in loss tolerance for this architecture.Comment: Published version, New Journal of Physics, Volume 19, June 201
Status and Future Perspectives for Lattice Gauge Theory Calculations to the Exascale and Beyond
In this and a set of companion whitepapers, the USQCD Collaboration lays out
a program of science and computing for lattice gauge theory. These whitepapers
describe how calculation using lattice QCD (and other gauge theories) can aid
the interpretation of ongoing and upcoming experiments in particle and nuclear
physics, as well as inspire new ones.Comment: 44 pages. 1 of USQCD whitepapers
ASCR/HEP Exascale Requirements Review Report
This draft report summarizes and details the findings, results, and
recommendations derived from the ASCR/HEP Exascale Requirements Review meeting
held in June, 2015. The main conclusions are as follows. 1) Larger, more
capable computing and data facilities are needed to support HEP science goals
in all three frontiers: Energy, Intensity, and Cosmic. The expected scale of
the demand at the 2025 timescale is at least two orders of magnitude -- and in
some cases greater -- than that available currently. 2) The growth rate of data
produced by simulations is overwhelming the current ability, of both facilities
and researchers, to store and analyze it. Additional resources and new
techniques for data analysis are urgently needed. 3) Data rates and volumes
from HEP experimental facilities are also straining the ability to store and
analyze large and complex data volumes. Appropriately configured
leadership-class facilities can play a transformational role in enabling
scientific discovery from these datasets. 4) A close integration of HPC
simulation and data analysis will aid greatly in interpreting results from HEP
experiments. Such an integration will minimize data movement and facilitate
interdependent workflows. 5) Long-range planning between HEP and ASCR will be
required to meet HEP's research needs. To best use ASCR HPC resources the
experimental HEP program needs a) an established long-term plan for access to
ASCR computational and data resources, b) an ability to map workflows onto HPC
resources, c) the ability for ASCR facilities to accommodate workflows run by
collaborations that can have thousands of individual members, d) to transition
codes to the next-generation HPC platforms that will be available at ASCR
facilities, e) to build up and train a workforce capable of developing and
using simulations and analysis to support HEP scientific research on
next-generation systems.Comment: 77 pages, 13 Figures; draft report, subject to further revisio
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