5,345 research outputs found
Optimisation of confinement in a fusion reactor using a nonlinear turbulence model
The confinement of heat in the core of a magnetic fusion reactor is optimised
using a multidimensional optimisation algorithm. For the first time in such a
study, the loss of heat due to turbulence is modelled at every stage using
first-principles nonlinear simulations which accurately capture the turbulent
cascade and large-scale zonal flows. The simulations utilise a novel approach,
with gyrofluid treatment of the small-scale drift waves and gyrokinetic
treatment of the large-scale zonal flows. A simple near-circular equilibrium
with standard parameters is chosen as the initial condition. The figure of
merit, fusion power per unit volume, is calculated, and then two control
parameters, the elongation and triangularity of the outer flux surface, are
varied, with the algorithm seeking to optimise the chosen figure of merit. A
two-fold increase in the plasma power per unit volume is achieved by moving to
higher elongation and strongly negative triangularity.Comment: 32 pages, 8 figures, accepted to JP
Towards Real-Time Detection and Tracking of Spatio-Temporal Features: Blob-Filaments in Fusion Plasma
A novel algorithm and implementation of real-time identification and tracking
of blob-filaments in fusion reactor data is presented. Similar spatio-temporal
features are important in many other applications, for example, ignition
kernels in combustion and tumor cells in a medical image. This work presents an
approach for extracting these features by dividing the overall task into three
steps: local identification of feature cells, grouping feature cells into
extended feature, and tracking movement of feature through overlapping in
space. Through our extensive work in parallelization, we demonstrate that this
approach can effectively make use of a large number of compute nodes to detect
and track blob-filaments in real time in fusion plasma. On a set of 30GB fusion
simulation data, we observed linear speedup on 1024 processes and completed
blob detection in less than three milliseconds using Edison, a Cray XC30 system
at NERSC.Comment: 14 pages, 40 figure
Real-time Dynamics in U(1) Lattice Gauge Theories with Tensor Networks
Tensor network algorithms provide a suitable route for tackling real-time
dependent problems in lattice gauge theories, enabling the investigation of
out-of-equilibrium dynamics. We analyze a U(1) lattice gauge theory in (1+1)
dimensions in the presence of dynamical matter for different mass and electric
field couplings, a theory akin to quantum-electrodynamics in one-dimension,
which displays string-breaking: the confining string between charges can
spontaneously break during quench experiments, giving rise to charge-anticharge
pairs according to the Schwinger mechanism. We study the real-time spreading of
excitations in the system by means of electric field and particle fluctuations:
we determine a dynamical state diagram for string breaking and quantitatively
evaluate the time-scales for mass production. We also show that the time
evolution of the quantum correlations can be detected via bipartite von Neumann
entropies, thus demonstrating that the Schwinger mechanism is tightly linked to
entanglement spreading. To present the variety of possible applications of this
simulation platform, we show how one could follow the real-time scattering
processes between mesons and the creation of entanglement during scattering
processes. Finally, we test the quality of quantum simulations of these
dynamics, quantifying the role of possible imperfections in cold atoms, trapped
ions, and superconducting circuit systems. Our results demonstrate how
entanglement properties can be used to deepen our understanding of basic
phenomena in the real-time dynamics of gauge theories such as string breaking
and collisions.Comment: 15 pages, 25 figures. Published versio
Fast and compact self-stabilizing verification, computation, and fault detection of an MST
This paper demonstrates the usefulness of distributed local verification of
proofs, as a tool for the design of self-stabilizing algorithms.In particular,
it introduces a somewhat generalized notion of distributed local proofs, and
utilizes it for improving the time complexity significantly, while maintaining
space optimality. As a result, we show that optimizing the memory size carries
at most a small cost in terms of time, in the context of Minimum Spanning Tree
(MST). That is, we present algorithms that are both time and space efficient
for both constructing an MST and for verifying it.This involves several parts
that may be considered contributions in themselves.First, we generalize the
notion of local proofs, trading off the time complexity for memory efficiency.
This adds a dimension to the study of distributed local proofs, which has been
gaining attention recently. Specifically, we design a (self-stabilizing) proof
labeling scheme which is memory optimal (i.e., bits per node), and
whose time complexity is in synchronous networks, or time in asynchronous ones, where is the maximum degree of
nodes. This answers an open problem posed by Awerbuch and Varghese (FOCS 1991).
We also show that time is necessary, even in synchronous
networks. Another property is that if faults occurred, then, within the
requireddetection time above, they are detected by some node in the locality of each of the faults.Second, we show how to enhance a known
transformer that makes input/output algorithms self-stabilizing. It now takes
as input an efficient construction algorithm and an efficient self-stabilizing
proof labeling scheme, and produces an efficient self-stabilizing algorithm.
When used for MST, the transformer produces a memory optimal self-stabilizing
algorithm, whose time complexity, namely, , is significantly better even
than that of previous algorithms. (The time complexity of previous MST
algorithms that used memory bits per node was , and
the time for optimal space algorithms was .) Inherited from our proof
labelling scheme, our self-stabilising MST construction algorithm also has the
following two properties: (1) if faults occur after the construction ended,
then they are detected by some nodes within time in synchronous
networks, or within time in asynchronous ones, and (2) if
faults occurred, then, within the required detection time above, they are
detected within the locality of each of the faults. We also show
how to improve the above two properties, at the expense of some increase in the
memory
SU(3) Landau gauge gluon and ghost propagators using the logarithmic lattice gluon field definition
We study the Landau gauge gluon and ghost propagators of SU(3) gauge theory,
employing the logarithmic definition for the lattice gluon fields and
implementing the corresponding form of the Faddeev-Popov matrix. This is
necessary in order to consistently compare lattice data for the bare
propagators with that of higher-loop numerical stochastic perturbation theory
(NSPT). In this paper we provide such a comparison, and introduce what is
needed for an efficient lattice study. When comparing our data for the
logarithmic definition to that of the standard lattice Landau gauge we clearly
see the propagators to be multiplicatively related. The data of the associated
ghost-gluon coupling matches up almost completely. For the explored lattice
spacings and sizes discretization artifacts, finite-size and Gribov-copy
effects are small. At weak coupling and large momentum, the bare propagators
and the ghost-gluon coupling are seen to be approached by those of higher-order
NSPT.Comment: 18 pages, 19 figures, 5 table
Matrix Product States, Projected Entangled Pair States, and variational renormalization group methods for quantum spin systems
This article reviews recent developments in the theoretical understanding and
the numerical implementation of variational renormalization group methods using
matrix product states and projected entangled pair states.Comment: Review from 200
Emerging Jets
In this work, we propose a novel search strategy for new physics at the LHC
that utilizes calorimeter jets that (i) are composed dominantly of displaced
tracks and (ii) have many different vertices within the jet cone. Such emerging
jet signatures are smoking guns for models with a composite dark sector where a
parton shower in the dark sector is followed by displaced decays of dark pions
back to SM jets. No current LHC searches are sensitive to this type of
phenomenology. We perform a detailed simulation for a benchmark signal with two
regular and two emerging jets, and present and implement strategies to suppress
QCD backgrounds by up to six orders of magnitude. At the 14 TeV LHC, this
signature can be probed with mediator masses as large as 1.5 TeV for a range of
dark pion lifetimes, and the reach is increased further at the high-luminosity
LHC. The emerging jet search is also sensitive to a broad class of long-lived
phenomena, and we show this for a supersymmetric model with R-parity violation.
Possibilities for discovery at LHCb are also discussed.Comment: 45 pages, 22 figures. v2: Typos fixed. v3: Minor modifications,
references added, version accepted in JHEP. Supplementary code can be found
at github.com/pedroschwaller/EmergingJet
Experimental quantum coding against photon loss error
A significant obstacle for practical quantum computation is the loss of
physical qubits in quantum computers, a decoherence mechanism most notably in
optical systems. Here we experimentally demonstrate, both in the quantum
circuit model and in the one-way quantum computer model, the smallest
non-trivial quantum codes to tackle this problem. In the experiment, we encode
single-qubit input states into highly-entangled multiparticle codewords, and we
test their ability to protect encoded quantum information from detected
one-qubit loss error. Our results prove the in-principle feasibility of
overcoming the qubit loss error by quantum codes.Comment: "Quantum Computing even when Photons Go AWOL". published versio
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