1,932 research outputs found
What to learn from dilepton transverse momentum spectra in heavy-ion collisions?
Recently the NA60 collaboration has presented high precision measurements of
dimuon spectra double differential in invariant mass and transverse pair
momentum in In-In collisions at . While the
-dependence is important for an understanding of in-medium changes of light
vector mesons and is integrated insensitive to collective expansion, the
-dependence arises from an interplay between emission temperature and
collective transverse flow. This fact can be exploited to derive constraints on
the evolution model and in particular on the contributions of different phases
of the evolution to dimuon radiation into a given window. We present
arguments that a thermalized evolution phase with leaves
its imprint on the spectra.Comment: Contributed to 19th International Conference on Ultrarelativistic
Nucleus-Nucleus Collisions: Quark Matter 2006 (QM 2006), Shanghai, China, 14-
20 Nov 200
Bayesian Analysis for Penalized Spline Regression Using WinBUGS
Penalized splines can be viewed as BLUPs in a mixed model framework, which allows the use of mixed model software for smoothing. Thus, software originally developed for Bayesian analysis of mixed models can be used for penalized spline regression. Bayesian inference for nonparametric models enjoys the flexibility of nonparametric models and the exact inference provided by the Bayesian inferential machinery. This paper provides a simple, yet comprehensive, set of programs for the implementation of nonparametric Bayesian analysis in WinBUGS. Good mixing properties of the MCMC chains are obtained by using low-rank thin-plate splines, while simulation times per iteration are reduced employing WinBUGS specific computational tricks.
Tuning the Level of Concurrency in Software Transactional Memory: An Overview of Recent Analytical, Machine Learning and Mixed Approaches
Synchronization transparency offered by Software Transactional Memory (STM) must not come at the expense of run-time efficiency, thus demanding from the STM-designer the inclusion of mechanisms properly oriented to performance and other quality indexes. Particularly, one core issue to cope with in STM is related to exploiting parallelism while also avoiding thrashing phenomena due to excessive transaction rollbacks, caused by excessively high levels of contention on logical resources, namely concurrently accessed data portions. A means to address run-time efficiency consists in dynamically determining the best-suited level of concurrency (number of threads) to be employed for running the application (or specific application phases) on top of the STM layer. For too low levels of concurrency, parallelism can be hampered. Conversely, over-dimensioning the concurrency level may give rise to the aforementioned thrashing phenomena caused by excessive data contentionâan aspect which has reflections also on the side of reduced energy-efficiency. In this chapter we overview a set of recent techniques aimed at building âapplication-specificâ performance models that can be exploited to dynamically tune the level of concurrency to the best-suited value. Although they share some base concepts while modeling the system performance vs the degree of concurrency, these techniques rely on disparate methods, such as machine learning or analytic methods (or combinations of the two), and achieve different tradeoffs in terms of the relation between the precision of the performance model and the latency for model instantiation. Implications of the different tradeoffs in real-life scenarios are also discussed
Multiple regions of TBP participate in the response to transcriptional activators in vivo
We used mutant yeast and human TBP molecules with an altered DNA-binding specificity to examine the role of TBP in transcriptional activation in vivo. We show that yeast TBP is functionally equivalent to human TBP for response to numerous transcriptional activators in human cells, including those that do not function in yeast. Despite the extensive conservation of TBP, its ability to respond to transcriptional activators in vivo is curiously resistant to clustered sets of alanine substitution mutations in different regions of the protein, including those that disrupt DNA binding and basal transcription in vitro. Combined sets of these mutations, however, can attenuate the in vivo activity of TBP and can differentially affect response to different activation domains. Although the activity of TBP mutants in vivo did not correlate with DNA binding or basal transcription in vitro, it did correlate with binding in vitro to the largest subunit of TFIID, hTAFII250. Together, these data suggest that TBP utilizes multiple interactions across its surface to respond to RNA polymerase II transcriptional activators in vivo; some of these interactions appear to involve recruitment of TBP into TFIID, whereas others are involved in response to specific types of transcriptional activators
Interpretation of Recent SPS Dilepton Data
We summarize our current theoretical understanding of in-medium properties of
the electromagnetic current correlator in view of recent dimuon data from the
NA60 experiment in In(158 AGeV)-In collisions at the CERN-SPS. We discuss the
sensitivity of the results to space-time evolution models for the hot and dense
partonic and hadronic medium created in relativistic heavy-ion collisions and
the contributions from different sources to the dilepton-excess spectra.Comment: To appear in the proceedings of the 19th International Conference on
Ultra-Relativistic Nucleus-Nucleus Collisions (Quark Matter 2006) v2:
references added, minor typos correcte
GGNN: Graph-based GPU Nearest Neighbor Search
Approximate nearest neighbor (ANN) search in high dimensions is an integral
part of several computer vision systems and gains importance in deep learning
with explicit memory representations. Since PQT and FAISS started to leverage
the massive parallelism offered by GPUs, GPU-based implementations are a
crucial resource for today's state-of-the-art ANN methods. While most of these
methods allow for faster queries, less emphasis is devoted to accelerate the
construction of the underlying index structures. In this paper, we propose a
novel search structure based on nearest neighbor graphs and information
propagation on graphs. Our method is designed to take advantage of GPU
architectures to accelerate the hierarchical building of the index structure
and for performing the query. Empirical evaluation shows that GGNN
significantly surpasses the state-of-the-art GPU- and CPU-based systems in
terms of build-time, accuracy and search speed
Semiparametric Regression During 2003â2007
Semiparametric regression is a fusion between parametric regression and nonparametric regression and the title of a book that we published on the topic in early 2003. We review developments in the field during the five year period since the book was written. We find semiparametric regression to be a vibrant field with substantial involvement and activity, continual enhancement and widespread application
Extraction of coherent structures in a rotating turbulent flow experiment
The discrete wavelet packet transform (DWPT) and discrete wavelet transform
(DWT) are used to extract and study the dynamics of coherent structures in a
turbulent rotating fluid. Three-dimensional (3D) turbulence is generated by
strong pumping through tubes at the bottom of a rotating tank (48.4 cm high,
39.4 cm diameter). This flow evolves toward two-dimensional (2D) turbulence
with increasing height in the tank. Particle Image Velocimetry (PIV)
measurements on the quasi-2D flow reveal many long-lived coherent vortices with
a wide range of sizes. The vorticity fields exhibit vortex birth, merger,
scattering, and destruction. We separate the flow into a low-entropy
``coherent'' and a high-entropy ``incoherent'' component by thresholding the
coefficients of the DWPT and DWT of the vorticity fields. Similar thresholdings
using the Fourier transform and JPEG compression together with the Okubo-Weiss
criterion are also tested for comparison. We find that the DWPT and DWT yield
similar results and are much more efficient at representing the total flow than
a Fourier-based method. Only about 3% of the large-amplitude coefficients of
the DWPT and DWT are necessary to represent the coherent component and preserve
the vorticity probability density function, transport properties, and spatial
and temporal correlations. The remaining small amplitude coefficients represent
the incoherent component, which has near Gaussian vorticity PDF, contains no
coherent structures, rapidly loses correlation in time, and does not contribute
significantly to the transport properties of the flow. This suggests that one
can describe and simulate such turbulent flow using a relatively small number
of wavelet or wavelet packet modes.Comment: experimental work aprox 17 pages, 11 figures, accepted to appear in
PRE, last few figures appear at the end. clarifications, added references,
fixed typo
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