508 citations
- Centre National de la Recherche ScientifiqueFR63 papers
- Vietnam National University, HanoiVN57 papers
- Institut National de Physique Nucléaire et de Physique des ParticulesFR55 papers
- Imperial College LondonGB54 papers
- European Organization for Nuclear ResearchCH53 papers
- Institute for Nuclear ResearchRU53 papers
- University of LiverpoolGB53 papers
- Horia Hulubei National Institute for R and D in Physics and Nuclear EngineeringRO52 papers
- Rutherford Appleton LaboratoryGB52 papers
- University of OxfordGB52 papers
- University of WarwickGB52 papers
- Institute for High Energy PhysicsES51 papers
5 papers · 1 filter
Observation of X(3872) production in pp collisions at sqrt(s)= 7 TeV
LHCb Collaboration, R. Aaij, C. Abellan Beteta +585
Using 34.7 pb-1 of data collected with the LHCb detector, the inclusive production of the X(3872) meson in pp collisions at sqrt(s) = 7 TeV is observed for the first time. Candidat…
Combining Convex-Concave Decompositions and Linearization Approaches for solving BMIs, with application to Static Output Feedback
Quoc Tran Dinh, Suat Gumussoy, Wim Michiels +1
A novel optimization method is proposed to minimize a convex function subject to bilinear matrix inequality (BMI) constraints. The key idea is to decompose the bilinear mapping as…
Measurement of the Double Beta Decay Half-life of 130Te with the NEMO-3 Detector
R. Arnold, C. Augier, J. Baker +67
This Letter reports results from the NEMO-3 experiment based on an exposure of 1275 days with 661g of 130Te in the form of enriched and natural tellurium foils. The double beta dec…
Determination of f_s/f_d for 7 TeV pp collisions and a measurement of the branching fraction of the decay Bd->D-K+
LHCb Collaboration, R. Aaij, B. Adeva +548
The relative abundance of the three decay modes , and produced in 7 TeV collisions at the LHC is determined from data co…
Combining Lagrangian Decomposition and Excessive Gap Smoothing Technique for Solving Large-Scale Separable Convex Optimization Problems
Tran Dinh Quoc, Carlo Savorgnan, Moritz Diehl
A new algorithm for solving large-scale convex optimization problems with a separable objective function is proposed. The basic idea is to combine three techniques: Lagrangian dual…