Measurements of two- and multi-particle angular correlations in pp collisions at root s = 5, 7, and 13TeV are presented as a function of charged-particle multiplicity. The data, corresponding to integrated luminosities of 1.0 pb(-1) (5 TeV), 6.2 pb(-1) (7 TeV), and 0.7 pb(-1) (13 TeV), were collected using the CMS detector at the LHC. The second-order (v(2)) and third-order (v(3)) azimuthal anisotropy harmonics of unidentified charged particles, as well as v(2) of K-S(0) and Lambda/(Lambda) over bar particles, are extracted from long-range two-particle correlations as functions of particle multiplicity and transverse momentum. For high-multiplicity pp events, a mass ordering is observed for the v(2) values of charged hadrons (mostly pions), K-S(0), and Lambda/(Lambda) over bar, with lighter particle species exhibiting a stronger azimuthal anisotropy signal below pT approximate to GeV/c. For 13 TeV data, the v(2) signals are also extracted from four- and six-particle correlations for the first time in pp collisions, with comparable magnitude to those from two-particle correlations. These observations are similar to those seen in pPb and PbPb collisions, and support the interpretation of a collective origin for the observed long-range correlations in high-multiplicity pp collisions. (C) 2016 The Author. Published by Elsevier B.V. This is an open access article under the CC BY license

Results are presented from a search for the rare decays Bs(0)→μ+ μ- and B(0)→μ+ μ- in pp collisions at sqrt[s]=7 and 8 TeV, with data samples corresponding to integrated luminosities of 5 and 20  fb(-1), respectively, collected by the CMS experiment at the LHC. An unbinned maximum-likelihood fit to the dimuon invariant mass distribution gives a branching fraction B(Bs(0)→μ+ μ-)=(3.0(-0.9)(+1.0))×10(-9), where the uncertainty includes both statistical and systematic contributions. An excess of Bs(0)→μ+ μ- events with respect to background is observed with a significance of 4.3 standard deviations. For the decay B(0)→μ+ μ- an upper limit of B(B(0)→μ+ μ-)<1.1×10(-9) at the 95% confidence level is determined. Both results are in agreement with the expectations from the standard model.

12We provide additional details in support of "On a Higgs optimization problem with quantum annealing" 131 The quantum annealer approach to the Higgs optimization problem 14 Our problem, toward which we apply quantum annealing for machine learning (QAML), is that of constructing a 15 binary classifier that can detect the "signal" of the decay of a Higgs boson into two photons in a "background" of noise The binary classifier proposed and studied in this work, is trained with a "quantum annealing for machine Here we use both QA and SA to train a classifier and examine its performance compared to traditional methods. 49 We benchmark the performance of QAML against DNN and XGB. 50We train a DNN using Keras 36 with the Theano backend, 37 a standard tool in deep learning and increasingly 51 popular in high energy physics. Our network has two fully connected hidden layers with 1000 nodes each. The 52 model is optimized using the Adam algorithm 38 with a learning rate of 0.001 and a mini-batch size of 10. We 53 find that network performance is not affected by small changes in the number of nodes or the initial guesses for 54 the weights. The model hyperparameters, regularization terms, and optimization parameters for our deep neural 55 net are selected using the Spearmint Bayesian optimization software. 39, 40 Early stopping is used (with patience 56 parameter 10) to avoid overtraining and have sufficient generalization. 57We also train an ensemble of boosted decision trees using XGB 41 with a maximum depth of 10, a learning rate 58 of 0.3, and L2-regularization parameter λ = 2000. 59To train and optimize XGB, we use 100 rounds of training and start with the default choices for the various 60 parameters. We evaluate values of the learning ratenetwork structure, 20 operational planning, 21 DNNs, 22 quantum Boltzmann machines, 23-25 and tree cover 46 detection in aerial imagery. 26 Both the quantumness 27-31 and speedup 32-35 in these devices are intensely scrutinized 47 topics of ongoing research. 48 DNN and XGB optimization procedure 49We benchmark the performance of QAML against DNN and XGB. 50We train a DNN using Keras 36 with the Theano backend, 37 a standard tool in deep learning and increasingly 51 popular in high energy physics. Our network has two fully connected hidden layers with 1000 nodes each. The 52 model is optimized using the Adam algorithm 38 with a learning rate of 0.001 and a mini-batch size of 10. We 53 find that network performance is not affected by small changes in the number of nodes or the initial guesses for 54 the weights. The model hyperparameters, regularization terms, and optimization parameters for our deep neural 55 net are selected using the Spearmint Bayesian optimization software. 39, 40 Early stopping is used (with patience 56 parameter 10) to avoid overtraining and have sufficient generalization. 57We also train an ensemble of boosted decision trees using XGB 41 with a maximum depth of 10, a learning rate 58 of 0.3, and L2-regularization parameter λ = 2000. 59To tra...

A search for heavy, right-handed neutrinos, (), and right-handed bosons, which arise in the left-right symmetric extensions of the standard model, has been performed by the CMS experiment. The search was based on a sample of two lepton plus two jet events collected in proton–proton collisions at a center-of-mass energy of 8 corresponding to an integrated luminosity of 19.7 . For models with strict left-right symmetry, and assuming only one flavor contributes significantly to the decay width, the region in the two-dimensional mass plane excluded at a 95 % confidence level extends to approximately and covers a large range of neutrino masses below the boson mass, depending on the value of . This search significantly extends the exclusion region beyond previous results.Electronic supplementary materialThe online version of this article (doi:10.1140/epjc/s10052-014-3149-z) contains supplementary material, which is available to authorized users.

Charge-dependent azimuthal particle correlations with respect to the second-order event plane in p-Pb and PbPb collisions at a nucleon-nucleon center-of-mass energy of 5.02 TeV have been studied with the CMS experiment at the LHC. The measurement is performed with a three-particle correlation technique, using two particles with the same or opposite charge within the pseudorapidity range jηj < 2.4, and a third particle measured in the hadron forward calorimeters (4.4 < jηj < 5). The observed differences between the same and opposite sign correlations, as functions of multiplicity and η gap between the two charged particles, are of similar magnitude in p-Pb and PbPb collisions at the same multiplicities. These results pose a challenge for the interpretation of charge-dependent azimuthal correlations in heavy ion collisions in terms of the chiral magnetic effect.