M. Buehler

Bio: M. Buehler is an academic researcher from Fermilab. The author has contributed to research in topics: Tevatron & Top quark. The author has an hindex of 39, co-authored 193 publications receiving 4784 citations.

Evidence for a particle produced in association with weak bosons and decaying to a bottom-antibottom quark pair in higgs boson searches at the tevatron

Abstract: We combine searches by the CDF and D0 Collaborations for the associated production of a Higgs boson with a W or Z boson and subsequent decay of the Higgs boson to a bottom-antibottom quark pair. The data, originating from Fermilab Tevatron p (p) over bar collisions at root s = 1.96 TeV, correspond to integrated luminosities of up to 9.7 fb(-1). The searches are conducted for a Higgs boson with mass in the range 100-150 GeV/c(2). We observe an excess of events in the data compared with the background predictions, which is most significant in the mass range between 120 and 135 GeV/c(2). The largest local significance is 3.3 standard deviations, corresponding to a global significance of 3.1 standard deviations. We interpret this as evidence for the presence of a new particle consistent with the standard model Higgs boson, which is produced in association with a weak vector boson and decays to a bottom-antibottom quark pair.

Combination of the top-quark mass measurements from the Tevatron collider

Abstract: We thank the Fermilab staff and technical staffs of the participating institutions for their vital contributions and acknowledge support from the DOE and NSF (USA), ARC (Australia), CNPq, FAPERJ, FAPESP, and FUNDUNESP (Brazil), NSERC (Canada), NSC, CAS, and CNSF (China), Colciencias (Colombia), MSMT and GACR (Czech Republic), the Academy of Finland, CEA, and CNRS/IN2P3 (France), BMBF and DFG (Germany), DAE and DST (India), SFI (Ireland), INFN (Italy), MEXT (Japan), the Korean World Class University Program and NRF (Korea), CONACyT (Mexico), FOM (Netherlands), MON, NRC KI, and RFBR (Russia), the Slovak R&D Agency, the Ministerio de Ciencia e Innovacio´n, and Programa Consolider-Ingenio 2010 (Spain), The Swedish Research Council (Sweden), SNSF (Switzerland), STFC and the Royal Society (United Kingdom), and the A. P. Sloan Foundation (USA).

Evidence for a B-s(0)pi(+/-) State

Abstract: We report evidence for a narrow structure, X(5568), in the decay sequence X(5568) -> B-s(0)pi(+/-), B-s(0) -> J/psi phi, J/psi -> mu(+)mu(-), phi -> K+K-. This is evidence for the first instance of a hadronic state with valence quarks of four different flavors. The mass and natural width of this state are measured to be m = 5567.8 +/- 2.9(stat)(-1.9)(+0.9) (syst) MeV/c(2) and Gamma = 21.9 +/- 6.4(stat)(-2.5)(+5.0) (syst) MeV/c(2). If the decay is X(5568) -> B-s*pi(+/-). B-s(0)gamma pi(+/-) with an unseen gamma, m(X(5568)) will be shifted up by m(B-s*) - m(B-s(0)) similar to 49 MeV/c(2). This measurement is based on 10.4 fb(-1) of p (p) over bar collision data at root s = 1.96 TeV collected by the D0 experiment at the Fermilab Tevatron collider.

Measurement of the W boson mass with the D0 detector

Abstract: We present a measurement of the W boson mass using data corresponding to 4.3fb^-1 of integrated luminosity collected with the D0 detector during Run II at the Fermilab Tevatron p\bar{p} collider. With a sample of 1,677,394 W -> e u candidate events, we measure M_W = 80.367 +/- 0.026 GeV. This result is combined with an earlier D0 result determined using an independent Run II data sample, corresponding to 1fb^-1 of integrated luminosity, to yield M_W = 80.375 +/- 0.023 GeV.

Combination of CDF and D0 W-Boson mass measurements

Abstract: We summarize and combine direct measurements of the mass of the $W$ boson in $\sqrt{s} = 1.96 \text{TeV}$ proton-antiproton collision data collected by CDF and D0 experiments at the Fermilab Tevatron Collider. Earlier measurements from CDF and D0 are combined with the two latest, more precise measurements: a CDF measurement in the electron and muon channels using data corresponding to $2.2 \mathrm{fb}^{-1}$ of integrated luminosity, and a D0 measurement in the electron channel using data corresponding to $4.3 \mathrm{fb}^{-1}$ of integrated luminosity. The resulting Tevatron average for the mass of the $W$ boson is $\MW = 80\,387 \pm 16 \text{MeV}$. Including measurements obtained in electron-positron collisions at LEP yields the most precise value of $\MW = 80\,385 \pm 15 \text{MeV}$.

Machine learning

Abstract: Machine Learning is the study of methods for programming computers to learn. Computers are applied to a wide range of tasks, and for most of these it is relatively easy for programmers to design and implement the necessary software. However, there are many tasks for which this is difficult or impossible. These can be divided into four general categories. First, there are problems for which there exist no human experts. For example, in modern automated manufacturing facilities, there is a need to predict machine failures before they occur by analyzing sensor readings. Because the machines are new, there are no human experts who can be interviewed by a programmer to provide the knowledge necessary to build a computer system. A machine learning system can study recorded data and subsequent machine failures and learn prediction rules. Second, there are problems where human experts exist, but where they are unable to explain their expertise. This is the case in many perceptual tasks, such as speech recognition, hand-writing recognition, and natural language understanding. Virtually all humans exhibit expert-level abilities on these tasks, but none of them can describe the detailed steps that they follow as they perform them. Fortunately, humans can provide machines with examples of the inputs and correct outputs for these tasks, so machine learning algorithms can learn to map the inputs to the outputs. Third, there are problems where phenomena are changing rapidly. In finance, for example, people would like to predict the future behavior of the stock market, of consumer purchases, or of exchange rates. These behaviors change frequently, so that even if a programmer could construct a good predictive computer program, it would need to be rewritten frequently. A learning program can relieve the programmer of this burden by constantly modifying and tuning a set of learned prediction rules. Fourth, there are applications that need to be customized for each computer user separately. Consider, for example, a program to filter unwanted electronic mail messages. Different users will need different filters. It is unreasonable to expect each user to program his or her own rules, and it is infeasible to provide every user with a software engineer to keep the rules up-to-date. A machine learning system can learn which mail messages the user rejects and maintain the filtering rules automatically. Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis. Statistics focuses on understanding the phenomena that have generated the data, often with the goal of testing different hypotheses about those phenomena. Data mining seeks to find patterns in the data that are understandable by people. Psychological studies of human learning aspire to understand the mechanisms underlying the various learning behaviors exhibited by people (concept learning, skill acquisition, strategy change, etc.).

New generation of parton distributions with uncertainties from global QCD analysis

Abstract: A new generation of parton distribution functions with increased precision and quantitative estimates of uncertainties is presented. This work signiflcantly extends previous CTEQ and other global analyses on two fronts: (i) a full treatment of available experimental correlated systematic errorsforbothnewandolddata sets; (ii) asystematic and pragmatic treatment of uncertainties of the parton distributions and their physical predictions, using a recently developed eigenvector-basis approach to the hessian method. The new gluon distribution is considerably harder than that of previous standard flts. A numberofphysicsissues,particularlyrelatingtothebehaviorofthegluondistribution,are addressedinmorequantitativetermsthanbefore. Extensiveresultsontheuncertaintiesof parton distributions at various scales, and on parton luminosity functions at the Tevatron RunII and the LHC, are presented. The latter provide the means to quickly estimate the uncertainties of a wide range of physical processes at these high-energy hadron colliders, basedoncurrentknowledgeofthepartondistributions. Inparticular, theuncertaintieson the production cross sections of the W, Z at the Tevatron and the LHC are estimated to be§4% and§5%, respectively, and that of a light Higgs at the LHC to be§5%.

Averages of b-hadron, c-hadron, and tau-lepton properties as of early 2012

Abstract: This article reports world averages of measurements of b-hadron, c-hadron, and tau-lepton properties obtained by the Heavy Flavor Averaging Group (HFAG) using results available through the end of 2011. In some cases results available in the early part of 2012 are included. For the averaging, common input parameters used in the various analyses are adjusted (rescaled) to common values, and known correlations are taken into account. The averages include branching fractions, lifetimes, neutral meson mixing parameters, CP violation parameters, parameters of semileptonic decays and CKM matrix elements.