450,093 research outputs found
Holographic local quench and effective complexity
We study the evolution of holographic complexity of pure and mixed states in
-dimensional conformal field theory following a local quench using both
the "complexity equals volume" (CV) and the "complexity equals action" (CA)
conjectures. We compare the complexity evolution to the evolution of
entanglement entropy and entanglement density, discuss the Lloyd computational
bound and demonstrate its saturation in certain regimes. We argue that the
conjectured holographic complexities exhibit some non-trivial features
indicating that they capture important properties of what is expected to be
effective (or physical) complexity.Comment: 33 pages, 19 figures; v2: typos corrected; 35 pages, references
added, new appendix. Version to match published in JHE
Benchmark Analysis of Representative Deep Neural Network Architectures
This work presents an in-depth analysis of the majority of the deep neural
networks (DNNs) proposed in the state of the art for image recognition. For
each DNN multiple performance indices are observed, such as recognition
accuracy, model complexity, computational complexity, memory usage, and
inference time. The behavior of such performance indices and some combinations
of them are analyzed and discussed. To measure the indices we experiment the
use of DNNs on two different computer architectures, a workstation equipped
with a NVIDIA Titan X Pascal and an embedded system based on a NVIDIA Jetson
TX1 board. This experimentation allows a direct comparison between DNNs running
on machines with very different computational capacity. This study is useful
for researchers to have a complete view of what solutions have been explored so
far and in which research directions are worth exploring in the future; and for
practitioners to select the DNN architecture(s) that better fit the resource
constraints of practical deployments and applications. To complete this work,
all the DNNs, as well as the software used for the analysis, are available
online.Comment: Will appear in IEEE Acces
A Survey on Continuous Time Computations
We provide an overview of theories of continuous time computation. These
theories allow us to understand both the hardness of questions related to
continuous time dynamical systems and the computational power of continuous
time analog models. We survey the existing models, summarizing results, and
point to relevant references in the literature
Holographic non-computers
We introduce the notion of holographic non-computer as a system which
exhibits parametrically large delays in the growth of complexity, as calculated
within the Complexity-Action proposal. Some known examples of this behavior
include extremal black holes and near-extremal hyperbolic black holes. Generic
black holes in higher-dimensional gravity also show non-computing features.
Within the expansion of General Relativity, we show that large-
scalings which capture the qualitative features of complexity, such as a linear
growth regime and a plateau at exponentially long times, also exhibit an
initial computational delay proportional to . While consistent for large AdS
black holes, the required `non-computing' scalings are incompatible with
thermodynamic stability for Schwarzschild black holes, unless they are tightly
caged.Comment: 23 pages, 7 figures. V3: References added. Figures updated. New
discussion of small black holes in the canonical ensembl
Parameterized Algorithmics for Computational Social Choice: Nine Research Challenges
Computational Social Choice is an interdisciplinary research area involving
Economics, Political Science, and Social Science on the one side, and
Mathematics and Computer Science (including Artificial Intelligence and
Multiagent Systems) on the other side. Typical computational problems studied
in this field include the vulnerability of voting procedures against attacks,
or preference aggregation in multi-agent systems. Parameterized Algorithmics is
a subfield of Theoretical Computer Science seeking to exploit meaningful
problem-specific parameters in order to identify tractable special cases of in
general computationally hard problems. In this paper, we propose nine of our
favorite research challenges concerning the parameterized complexity of
problems appearing in this context
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