The CMS trigger system must reduce an input data rate from the LHC bunch-crossing frequency of 40 MHz to a rate which will be written to permanent storage. A detailed study has recently been made of the performance of this system. This paper presents key elements of the results obtained and gives details of a draft “trigger table” for the Level-1 Trigger and the High-Level Trigger selection at a “start-up” luminosity of 2× 1033 cm – 2s – 1. High efficiencies for most physics objects are attainable with a selection that remains inclusive and avoids detailed topological or other requirements on the event.
This work summarizes and puts in an overall perspective studies done within the compact muon solenoid (CMS) concerning the discovery potential for squarks and gluinos, sleptons, charginos and neutralinos, supersymmetric (SUSY) dark matter, lightest Higgs, sparticle mass determination methods and the detector design optimization in view of SUSY searches. It represents the status of our understanding of these subjects as of summer 1997. As a benchmark we used the minimal supergravity-inspired supersymmetric standard model (mSUGRA) with a stable lightest supersymmetric particle (LSP). Discovery of supersymmetry at the large hadron collider should be relatively straightforward. It may occur through the observation of large excesses of events in missing ET plus jets, or with one or more isolated leptons. An excess of trilepton events or isolated dileptons with missing ET, exhibiting a characteristic signature in the l+l− invariant mass distribution, could also be the first manifestation of SUSY production. Squarks and gluinos can be discovered for masses in excess of 2 TeV. Charginos and neutralinos can be discovered from an excess of events in dilepton or trilepton final states. Inclusive searches can give early indications from their copious production in squark and gluino cascade decays. Indirect evidence for sleptons can also be obtained from inclusive dilepton studies. Isolation requirements and a jet veto would allow detection of both the direct chargino/neutralino production and the directly produced sleptons. Squark and gluino production may also represent a copious source of Higgs bosons through cascade decays. The lightest SUSY Higgs h → b may be reconstructed with a signal/background ratio of order 1 thanks to hard cuts on ETmiss justified by escaping LSPs. The LSP of SUSY models with conserved R-parity represents a very good candidate for cosmological dark matter. The region of parameter space where this is true is well covered by our searches, at least for tanβ = 2. If supersymmetry exists at the electroweak scale, it could hardly escape detection in CMS and the study of supersymmetry will form a central part of our physics program.
Annette Michalski, Eugen Damoc, J. Hauschild
et al.
Mass spectrometry-based proteomics has greatly benefitted from enormous advances in high resolution instrumentation in recent years. In particular, the combination of a linear ion trap with the Orbitrap analyzer has proven to be a popular instrument configuration. Complementing this hybrid trap-trap instrument, as well as the standalone Orbitrap analyzer termed Exactive, we here present coupling of a quadrupole mass filter to an Orbitrap analyzer. This “Q Exactive” instrument features high ion currents because of an S-lens, and fast high-energy collision-induced dissociation peptide fragmentation because of parallel filling and detection modes. The image current from the detector is processed by an “enhanced Fourier Transformation” algorithm, doubling mass spectrometric resolution. Together with almost instantaneous isolation and fragmentation, the instrument achieves overall cycle times of 1 s for a top10 higher energy collisional dissociation method. More than 2500 proteins can be identified in standard 90-min gradients of tryptic digests of mammalian cell lysate— a significant improvement over previous Orbitrap mass spectrometers. Furthermore, the quadrupole Orbitrap analyzer combination enables multiplexed operation at the MS and tandem MS levels. This is demonstrated in a multiplexed single ion monitoring mode, in which the quadrupole rapidly switches among different narrow mass ranges that are analyzed in a single composite MS spectrum. Similarly, the quadrupole allows fragmentation of different precursor masses in rapid succession, followed by joint analysis of the higher energy collisional dissociation fragment ions in the Orbitrap analyzer. High performance in a robust benchtop format together with the ability to perform complex multiplexed scan modes make the Q Exactive an exciting new instrument for the proteomics and general analytical communities.
Frequency combs are having a broad impact on science and technology because they provide a way to coherently link radio/microwave-rate electrical signals with optical-rate signals derived from lasers and atomic transitions. Integrating these systems on a photonic chip would revolutionize instrumentation, time keeping, spectroscopy, navigation, and potentially create new mass-market applications. A key element of such a system-on-a-chip will be a mode-locked comb that can be self-referenced. The recent demonstration of soliton mode locking in crystalline and silicon nitride microresonators has provided a way to both mode lock and generate femtosecond time-scale pulses. Here, soliton mode locking is demonstrated in high-Q silica resonators. The resonators produce low-phase-noise soliton pulse trains at readily detectable pulse rates—two essential properties for the operation of frequency combs. A method for the long-term stabilization of the solitons is also demonstrated, and is used to test the theoretical dependence of the comb power, efficiency, and soliton existence power on the pulse width. The influence of the Raman process on the soliton existence power and efficiency is also observed. The resonators are microfabricated on silicon chips and feature reproducible modal properties required for soliton formation. A low-noise and detectable pulse rate soliton frequency comb on a chip is a significant step towards a fully integrated frequency comb system.
q‐Rung orthopair fuzzy set (q‐ROFS) is a powerful tool that attracts the attention of many scholars in dealing with uncertainty and vagueness. The aim of paper is to present a new score function of q‐rung orthopair fuzzy number (q‐ROFN) for solving the failure problems when comparing two q‐ROFNs. Then a new exponential operational law about q‐ROFNs is defined, in which the bases are positive real numbers and the exponents are q‐ROFNs. Meanwhile, some properties of the operational law are investigated. Later, we apply them to derive the q‐rung orthopair fuzzy weighted exponential aggregation operator. Additionally, an approach for multicriteria decision‐making problems under the q‐rung orthopair fuzzy data is explored by applying proposed aggregation operator. Finally, an example is investigated to illustrate the feasibility and validity of the proposed approach. The salient features of the proposed method, compared to the existing q‐rung orthopair fuzzy decision‐making methods, are (1) it can obtain the optimal alternative without counterintuitive phenomena; (2) it has a great power in distinguishing the optimal alternative.
Abstract Task scheduling, which plays a vital role in cloud computing, is a critical factor that determines the performance of cloud computing. From the booming economy of information processing to the increasing need of quality of service (QoS) in the business of networking, the dynamic task-scheduling problem has attracted worldwide attention. Due to its complexity, task scheduling has been defined and classified as an NP-hard problem. Additionally, most dynamic online task scheduling often manages tasks in a complex environment, which makes it even more challenging to balance and satisfy the benefits of each aspect of cloud computing. In this paper, we propose a novel artificial intelligence algorithm, called deep Q-learning task scheduling (DQTS), that combines the advantages of the Q-learning algorithm and a deep neural network. This new approach is aimed at solving the problem of handling directed acyclic graph (DAG) tasks in a cloud computing environment. The essential idea of our approach uses the popular deep Q-learning (DQL) method in task scheduling, where fundamental model learning is primarily inspired by DQL. Based on developments in WorkflowSim, experiments are conducted that comparatively consider the variance of makespan and load balance in task scheduling. Both simulation and real-life experiments are conducted to verify the efficiency of optimization and learning abilities in DQTS. The result shows that when compared with several standard algorithms precoded in WorkflowSim, DQTS has advantages regarding learning ability, containment, and scalability. In this paper, we have successfully developed a new method for task scheduling in cloud computing.
Background Q-methodology is an approach to studying complex issues of human ‘subjectivity’. Although this approach was developed in the early twentieth century, the value of Q-methodology in healthcare was not recognised until relatively recently. The aim of this review was to scope the empirical healthcare literature to examine the extent to which Q-methodology has been utilised in healthcare over time, including how it has been used and for what purposes. Methods A search of three electronic databases (Scopus, EBSCO-CINAHL Complete, Medline) was conducted. No date restriction was applied. A title and abstract review, followed by a full-text review, was conducted by a team of five reviewers. Included articles were English-language, peer-reviewed journal articles that used Q-methodology (both Q-sorting and inverted factor analysis) in healthcare settings. The following data items were extracted into a purpose-designed Excel spreadsheet: study details (e.g., setting, country, year), reasons for using Q-methodology, healthcare topic area, participants (type and number), materials (e.g., ranking anchors and Q-set), methods (e.g., development of the Q-set, analysis), study results, and study implications. Data synthesis was descriptive in nature and involved frequency counting, open coding and the organisation by data items. Results Of the 2,302 articles identified by the search, 289 studies were included in this review. We found evidence of increased use of Q-methodology in healthcare, particularly over the last 5 years. However, this research remains diffuse, spread across a large number of journals and topic areas. In a number of studies, we identified limitations in the reporting of methods, such as insufficient information on how authors derived their Q-set, what types of analyses they performed, and the amount of variance explained. Conclusions Although Q-methodology is increasingly being adopted in healthcare research, it still appears to be relatively novel. This review highlight commonalities in how the method has been used, areas of application, and the potential value of the approach. To facilitate reporting of Q-methodological studies, we present a checklist of details that should be included for publication.