27 research outputs found
The dynamo effect - A dynamic renormalisation group approach
The Dynamo effect is used to describe the generation of magnetic fields in
astrophysical objects. However, no rigorous derivation of the dynamo equation
is available. We justify the form of the equation using an Operator Product
Expansion (OPE) of the relevant fields. We also calculate the coefficients of
the OPE series using a dynamic renormalisation group approach and discuss the
time evolution of the initial conditions on the initial seed magnetic field.Comment: submitted to EP
Universal properties of three-dimensional magnetohydrodynamic turbulence: Do Alfv\'en waves matter?
We analyse the effects of the propagating Alfv\'en waves, arising due to
non-zero mean magnetic fields, on the nonequilibrium steady states of
three-dimensional (3d) homogeneous Magnetohydrodynamic (MHD) turbulence. In
particular, the effects of Alfv\'en waves on the universal properties of 3dMHD
turbulence are studied in a one-loop self-consistent mode-coupling approach. We
calculate the kinetic- and magnetic energy-spectra. We find that {\em even} in
the presence of a mean magnetic field the energy spectra are Kolmogorov-like,
i.e., scale as in the inertial range where is a Fourier
wavevector belonging to the inertial range. We also elucidate the multiscaling
of the structure functions in a log-normal model by evaluating the relevant
intermittency exponents, and our results suggest that the multiscaling
deviations from the simple Kolmogorov scaling of the structure functions
decrease with increasing strength of the mean magnetic field. Our results
compare favourably with many existing numerical and observational results.Comment: To appear in JSTAT (2005
GEMv2: multilingual NLG benchmarking in a single line of code.
Evaluations in machine learning rarely use the latest metrics, datasets, or human evaluation in favor of remaining compatible with prior work. The compatibility, often facilitated through leaderboards, thus leads to outdated but standardized evaluation practices. We pose that the standardization is taking place in the wrong spot. Evaluation infrastructure should enable researchers to use the latest methods and what should be standardized instead is how to incorporate these new evaluation advances. We introduce GEMv2, the new version of the Generation, Evaluation, and Metrics Benchmark which uses a modular infrastructure for dataset, model, and metric developers to benefit from each other's work. GEMv2 supports 40 documented datasets in 51 languages, ongoing online evaluation for all datasets, and our interactive tools make it easier to add new datasets to the living benchmark
BanglaNLG and BanglaT5: Benchmarks and Resources for Evaluating Low-Resource Natural Language Generation in Bangla
This work presents BanglaNLG, a comprehensive benchmark for evaluating
natural language generation (NLG) models in Bangla, a widely spoken yet
low-resource language. We aggregate six challenging conditional text generation
tasks under the BanglaNLG benchmark, introducing a new dataset on dialogue
generation in the process. Then, using a clean corpus of 27.5 GB of Bangla
data, we pretrain BanglaT5, a sequence-to-sequence Transformer model for
Bangla. BanglaT5 achieves state-of-the-art performance in all of these tasks,
outperforming several multilingual models by up to 9% absolute gain and 32%
relative gain. We are making the new dataset, the BanglaT5 language model, and
a leaderboard publicly available at https://github.com/csebuetnlp/BanglaNLG in
the hope of advancing future research and evaluation on Bangla NLG.Comment: Accepted at the Findings of EACL 202
Coupled non-equilibrium growth equations: Self-consistent mode coupling using vertex renormalization
We find that studying the simplest of the coupled non-equilibrium growth
equations of Barabasi by self-consistent mode coupling requires the use of
dressed vertices. Using the vertex renormalization, we find a roughness
exponent which already in the leading order is quite close to the numerical
value.Comment: 7 pages, 3 figure
CrossSum: Beyond English-Centric Cross-Lingual Abstractive Text Summarization for 1500+ Language Pairs
We present CrossSum, a large-scale cross-lingual abstractive summarization
dataset comprising 1.7 million article-summary samples in 1500+ language pairs.
We create CrossSum by aligning identical articles written in different
languages via cross-lingual retrieval from a multilingual summarization
dataset. We propose a multi-stage data sampling algorithm to effectively train
a cross-lingual summarization model capable of summarizing an article in any
target language. We also propose LaSE, a new metric for automatically
evaluating model-generated summaries and showing a strong correlation with
ROUGE. Performance on ROUGE and LaSE indicate that pretrained models fine-tuned
on CrossSum consistently outperform baseline models, even when the source and
target language pairs are linguistically distant. To the best of our knowledge,
CrossSum is the largest cross-lingual summarization dataset and the first-ever
that does not rely solely on English as the pivot language. We are releasing
the dataset, alignment and training scripts, and the models to spur future
research on cross-lingual abstractive summarization. The resources can be found
at https://github.com/csebuetnlp/CrossSum
Fluctuating hydrodynamics and turbulence in a rotating fluid: Universal properties
We analyze the statistical properties of three-dimensional () turbulence
in a rotating fluid. To this end we introduce a generating functional to study
the statistical properties of the velocity field . We obtain the master
equation from the Navier-Stokes equation in a rotating frame and thence a set
of exact hierarchical equations for the velocity structure functions for
arbitrary angular velocity . In particular we obtain the {\em
differential forms} for the analogs of the well-known von Karman-Howarth
relation for fluid turbulence. We examine their behavior in the limit of
large rotation. Our results clearly suggest dissimilar statistical behavior and
scaling along directions parallel and perpendicular to . The
hierarchical relations yield strong evidence that the nature of the flows for
large rotation is not identical to pure two-dimensional flows. To complement
these results, by using an effective model in the small- limit, within
a one-loop approximation, we show that the equal-time correlation of the
velocity components parallel to displays Kolmogorov scaling
, where as for all other components, the equal-time correlators scale
as in the inertial range where is a wavevector in . Our
results are generally testable in experiments and/or direct numerical
simulations of the Navier-Stokes equation in a rotating frame.Comment: 24 pages in preprint format; accepted for publication in Phys. Rev. E
(2011