A5102790041- Particle physics theoretical and experimental studies
- High-Energy Particle Collisions Research
- Quantum Chromodynamics and Particle Interactions
- Particle Detector Development and Performance
- Dark Matter and Cosmic Phenomena
- Neutrino Physics Research
- Computational Physics and Python Applications
- Cosmology and Gravitation Theories
- Particle Accelerators and Free-Electron Lasers
- Black Holes and Theoretical Physics
- Advanced Data Storage Technologies
- Medical Imaging Techniques and Applications
- Distributed and Parallel Computing Systems
- Astrophysics and Cosmic Phenomena
- Scientific Computing and Data Management
- Atomic and Subatomic Physics Research
- Superconducting Materials and Applications
- Algorithms and Data Compression
- Parallel Computing and Optimization Techniques
- advanced mathematical theories
- Generative Adversarial Networks and Image Synthesis
- Particle accelerators and beam dynamics
- Radiation Detection and Scintillator Technologies
- Nuclear physics research studies
- Stochastic processes and statistical mechanics
Lawrence Berkeley National Laboratory
2015-2024
University of California, Berkeley
2015-2022
National Energy Research Scientific Computing Center
2017-2021
University of Edinburgh
2010-2016
The University of Adelaide
2013-2016
Tel Aviv University
2011-2016
University of Belgrade
2015-2016
University of Science and Technology of China
2015
Imperial College London
2003-2014
Scottish Universities Physics Alliance
2014
We present an updated measurement of time-dependent CP-violating asymmetries in neutral B decays with the BABAR detector at PEP-II asymmetric Factory SLAC. This result uses additional sample Upsilon(4S) collected 2001, bringing data available to 32 x 10(6) BB macro pairs. select events which one meson is fully reconstructed a final state containing charmonium and flavor other determined from its decay products. The amplitude asymmetry, standard model proportional sin2 beta, derived time...
Machine learning is an important applied research area in particle physics, beginning with applications to high-level physics analysis the 1990s and 2000s, followed by explosion of event identification reconstruction 2010s. In this document we discuss promising future development areas machine a roadmap for their implementation, software hardware resource requirements, collaborative initiatives data science community, academia industry, training community science. The main objective connect...
We present results on time-dependent CP asymmetries in neutral B decays to several eigenstates. The measurements use a data sample of about 88 x 10(6) Upsilon(4S)-->B(-)B collected between 1999 and 2002 with the BABAR detector at PEP-II asymmetric-energy factory SLAC. study events which one meson is fully reconstructed final state containing charmonium other determined be either B(0) or B(-0) from its decay products. amplitude asymmetry, standard model proportional sin2beta, derived...
Bringing HEP computing to HPC can be difficult. Software stacks are often very complicated with numerous dependencies that difficult get installed on an system. To address this issue, NERSC has created Shifter, a framework delivers Docker-like functionality HPC. It works by extracting images from native formats and converting them common format is optimally tuned for the environment. We have used Shifter deliver CVMFS software stack ALICE, ATLAS, STAR supercomputers at NERSC. As well as...
Particle physics has an ambitious and broad experimental programme for the coming decades. This requires large investments in detector hardware, either to build new facilities experiments, or upgrade existing ones. Similarly, it commensurate investment R&D of software acquire, manage, process, analyse shear amounts data be recorded. In planning HL-LHC particular, is critical that all collaborating stakeholders agree on goals priorities, efforts complement each other. this spirit, white paper...
We present a measurement of time-dependent CP-violating asymmetries in neutral B meson decays collected with the BABAR detector at PEP-II asymmetric-energy ${e}^{+}{e}^{\ensuremath{-}}$ collider Stanford Linear Accelerator Center. The data sample consists 29.7 ${\mathrm{fb}}^{\mathrm{\ensuremath{-}}1}$ recorded $\ensuremath{\Upsilon}(4S)$ resonance and 3.9 off resonance. One mesons, which are produced pairs $\ensuremath{\Upsilon}(4S),$ is fully reconstructed CP decay modes...
We present measurements of branching fractions and CP-violating asymmetries for two-body neutral B meson decays to charged pions kaons based on a sample about 88x10(6) Upsilon(4S)-->BB decays. From time-independent fit we measure the charge-averaged B(B0-->pi+pi-)=(4.7+/-0.6+/-0.2)x10(-6), B(B0-->K+pi-)=(17.9+/-0.9+/-0.7)x10(-6), direct charge asymmetry A(Kpi)=-0.102+/-0.050+/-0.016 [-0.188,-0.016], where ranges in square brackets indicate 90% confidence intervals. time-dependent B0-->pi+pi-...
Abstract Inferring model parameters from experimental data is a grand challenge in many sciences, including cosmology. This often relies critically on high fidelity numerical simulations, which are prohibitively computationally expensive. The application of deep learning techniques to generative modeling renewing interest using dimensional density estimators as inexpensive emulators fully-fledged simulations. These models have the potential make dramatic shift field scientific but for that...
Tasks involving the analysis of geometric (graph-and manifold-structured) data have recently gained prominence in machine learning community, giving birth to a rapidly developing field deep learning. In this work, we leverage graph neural networks improve signal detection IceCube neutrino observatory. The detector array is modeled as graph, where vertices are sensors and edges learned function spatial coordinates. As only subset IceCubes active during given observation, note adaptive nature...
This paper presents the first, 15-PetaFLOP Deep Learning system for solving scientific pattern classification problems on contemporary HPC architectures. We develop supervised convolutional architectures discriminating signals in high-energy physics data as well semi-supervised localizing and classifying extreme weather climate data. Our Intelcaffe-based implementation obtains ~2TFLOP/s a single Cori Phase-II Xeon-Phi node. use hybrid strategy employing synchronous node-groups, while using...
A bstract High-multiplicity all-hadronic final states are an important, but difficult state for searching physics beyond the Standard Model. powerful search method is to look large jets with accidental substructure due multiple hard partons falling within a single jet. One way estimating background in this exploit approximate factorization quantum chromodynamics whereby jet mass distribution determined only by its kinematic properties. Traditionally, approach has been executed using...
Abstract The reconstruction of charged particles will be a key computing challenge for the high-luminosity Large Hadron Collider (HL-LHC) where increased data rates lead to large increase in running time current pattern recognition algorithms. An alternative approach explored here expresses as quadratic unconstrained binary optimization (QUBO), which allows algorithms run on classical and quantum annealers. While overall timing proposed its scaling has still measured studied, we demonstrate...
There has been considerable recent activity applying deep convolutional neural nets (CNNs) to data from particle physics experiments. Current approaches on ATLAS/CMS have largely focussed a subset of the calorimeter, and for identifying objects or particular types. We explore that use entire combined with track information, directly conducting analyses: i.e. classifying events as known-physics background new-physics signals.
Probabilistic programming languages (PPLs) are receiving widespread attention for performing Bayesian inference in complex generative models. However, applications to science remain limited because of the impracticability rewriting scientific simulators a PPL, computational cost inference, and lack scalable implementations. To address these, we present novel PPL framework that couples directly existing through cross-platform probabilistic execution protocol provides Markov chain Monte Carlo...
Computing $k$-Nearest Neighbors (KNN) is one of the core kernels used in many machine learning, data mining and scientific computing applications. Although kd-tree based $O(\log n)$ algorithms have been proposed for KNN, due to its inherent sequentiality, linear are being practice. This limits applicability such methods millions points, with limited scalability Big Data analytics challenges domain. In this paper, we present parallel highly optimized KNN (both construction querying) suitable...
The inclusive production of charmonium mesons in B meson decay has been studied a 20.3 ${\mathrm{fb}}^{\mathrm{\ensuremath{-}}1}$ data set collected by the BABAR experiment operating at $\ensuremath{\Upsilon}(4S)$ resonance. Branching fractions have measured for $J/\ensuremath{\psi},$ $\ensuremath{\psi}(2S),$ ${\ensuremath{\chi}}_{c1},$ and ${\ensuremath{\chi}}_{c2}.$ branching are also presented as function center-of-mass momentum helicity $J/\ensuremath{\psi}.$
The production of $J/\ensuremath{\psi}$ mesons in continuum ${e}^{+}{e}^{\ensuremath{-}}$ annihilations has been studied with the BABAR detector at energies near $\ensuremath{\Upsilon}(4S)$ resonance. are distinguished from $B$ decays through their center-of-mass momentum and energy. We measure cross section ${e}^{+}{e}^{\ensuremath{-}}\ensuremath{\rightarrow}J/\ensuremath{\psi}X$ to be $2.52\ifmmode\pm\else\textpm\fi{}0.21\ifmmode\pm\else\textpm\fi{}0.21\mathrm{pb}$. set a $90%$ C.L. upper...
We report branching fraction measurements for exclusive decays of charged and neutral B mesons into two-body final states containing a charmonium meson. use sample $22.72\ifmmode\pm\else\textpm\fi{}0.36$ million $B\overline{B}$ events collected between October 1999 2000 with the BABAR detector at PEP-II storage rings Stanford Linear Accelerator Center. The considered here are $J/\ensuremath{\psi},$ $\ensuremath{\psi}(2S),$ ${\ensuremath{\chi}}_{c1},$ light meson in decay is either K,...
We present a measurement of the decay amplitudes in B-->J/psiK*(892) channels using 20.7 fb(-1) data collected at Upsilon(4S) resonance with BABAR detector PEP-II. measure P-wave fraction R(perpendicular) = (16.0 +/- 3.2 1.4)% and longitudinal polarization (59.7 2.8 2.4)%. The relative phase that is neither 0 nor pi, phi 2.50 0.20 +/-0.08 radians, favors departure from factorization hypothesis. Although B-->/psiK(pi) proceeds mainly via K*(892), there also evidence for K2*(1430) K(pi) S-wave...
Machine learning has been applied to several problems in particle physics research, beginning with applications high-level analysis the 1990s and 2000s, followed by an explosion of event identification reconstruction 2010s. In this document we discuss promising future research development areas for machine physics. We detail a roadmap their implementation, software hardware resource requirements, collaborative initiatives data science community, academia industry, training community science....
We present measurements, based on a sample of approximately 23×106 B¯B pairs, the branching fractions and search for CP-violating charge asymmetries in charmless hadronic decays B mesons into two-body final states kaons pions. find B(B0→π+π−)=(4.1±1.0±0.7)×10−6, B(B0→K+π−)=(16.7±1.6±1.3)×10−6, B(B+→K+π0)=(10.8+2.1−1.9±1.0)×10−6, B(B+→K0π+)=(18.2+3.3−3.0±2.0)×10−6, B(B0→K0π0)=(8.2+3.1−2.7±1.2)×10−6. also report 90% confidence level upper limits meson to π+π0, K+K−, ¯K0K+ states. In addition,...
We present the results of searches for B decays to charmless two-body final states containing eta(') or omega mesons, based on 20.7 fb(-1) data collected with BABAR detector. find branching fractions Beta(B(+)-->eta(')K(+)) = (70+/-8+/-5) x 10(-6), Beta(B(0)-->eta(')K(0)) (42(+13)(-11) +/- 4) and Beta(B(+)-->omega pi(+)) (6.6(+2.1)(-1.8) 0.7) where first error quoted is statistical second systematic. give measurements four additional modes which 90% confidence level upper limits are...