Search results for "integrated"

showing 10 items of 1783 documents

"Table 24" of "Measurement of event shape and inclusive distributions at s**(1/2) = 130-GeV and 136-GeV."

1997

3-jet rate for the Jade Algorithm.

Computer Science::Multiagent Systems133.0E+ E- --> 3JETAstrophysics::High Energy Astrophysical PhenomenaE+ E- ScatteringIntegrated Cross SectionExclusiveHigh Energy Physics::ExperimentJet ProductionCross SectionSIGComputer Science::Distributed Parallel and Cluster Computing
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"Table 23" of "Measurement of event shape and inclusive distributions at s**(1/2) = 130-GeV and 136-GeV."

1997

2-jet rate for the Jade Algorithm.

Computer Science::Multiagent SystemsDijet Production133.0Astrophysics::High Energy Astrophysical PhenomenaE+ E- ScatteringIntegrated Cross SectionExclusiveHigh Energy Physics::ExperimentJet ProductionE+ E- --> 2JETCross SectionSIGComputer Science::Distributed Parallel and Cluster Computing
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"Table 25" of "Measurement of event shape and inclusive distributions at s**(1/2) = 130-GeV and 136-GeV."

1997

4-jet rate for the Jade Algorithm.

Computer Science::Multiagent SystemsE+ E- --> 4JET133.0Astrophysics::High Energy Astrophysical PhenomenaE+ E- ScatteringIntegrated Cross SectionExclusiveHigh Energy Physics::ExperimentJet ProductionCross SectionSIGComputer Science::Distributed Parallel and Cluster Computing
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"Table 26" of "Measurement of event shape and inclusive distributions at s**(1/2) = 130-GeV and 136-GeV."

1997

5-jet rate for the Jade Algorithm.

Computer Science::Multiagent SystemsE+ E- --> 5JET133.0Astrophysics::High Energy Astrophysical PhenomenaE+ E- ScatteringIntegrated Cross SectionExclusiveHigh Energy Physics::ExperimentJet ProductionCross SectionSIGComputer Science::Distributed Parallel and Cluster Computing
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Theory of Heterogeneous Circuits With Stochastic Memristive Devices

2022

We introduce an approach based on the Chapman-Kolmogorov equation to model heterogeneous stochastic circuits, namely, the circuits combining binary or multi-state stochastic memristive devices and continuum reactive components (capacitors and/or inductors). Such circuits are described in terms of occupation probabilities of memristive states that are functions of reactive variables. As an illustrative example, the series circuit of a binary memristor and capacitor is considered in detail. Some analytical solutions are found. Our work offers a novel analytical/numerical tool for modeling complex stochastic networks, which may find a broad range of applications.

Computer scienceContinuum (topology)Binary numberCapacitorsMemristorSwitching circuitsTopologyInductorSeries and parallel circuitslaw.inventionComputer Science::Hardware ArchitectureCapacitorRange (mathematics)Mathematical modelComputer Science::Emerging TechnologiesStochastic processesIntegrated circuit modelinglawHardware_INTEGRATEDCIRCUITSElectrical and Electronic EngineeringMemristorsSwitchesElectronic circuitIEEE Transactions on Circuits and Systems II: Express Briefs
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Improving topological mapping on NoCs

2010

Networks-on-Chip (NoCs) have been proposed as an efficient solution to the complex communications on System-on-chip (SoCs). The design flow of network-on-chip (NoCs) include several key issues, and one of them is the decision of where cores have to be topologically mapped. This thesis proposes a new approach to the topological mapping strategy for NoCs. Concretely, we propose a new topological mapping technique for regular and irregular NoC platforms and its application for optimizing application specific NoC based on distributed and source routing.

Computer scienceDistributed computingDesign flowBandwidth (signal processing)Hardware_PERFORMANCEANDRELIABILITYIntegrated circuit designSource routingNetwork topologyComputer Science::Hardware ArchitectureComputer Science::Emerging TechnologiesNetwork on a chipHardware_INTEGRATEDCIRCUITSSystem on a chipRouting (electronic design automation)2010 IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum (IPDPSW)
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The promise of spintronics for unconventional computing

2021

Novel computational paradigms may provide the blueprint to help solving the time and energy limitations that we face with our modern computers, and provide solutions to complex problems more efficiently (with reduced time, power consumption and/or less device footprint) than is currently possible with standard approaches. Spintronics offers a promising basis for the development of efficient devices and unconventional operations for at least three main reasons: (i) the low-power requirements of spin-based devices, i.e., requiring no standby power for operation and the possibility to write information with small dynamic energy dissipation, (ii) the strong nonlinearity, time nonlocality, and/o…

Computer scienceFOS: Physical sciencesApplied Physics (physics.app-ph)02 engineering and technology01 natural sciencesQuantum nonlocalityAffordable and Clean EnergyBlueprintMesoscale and Nanoscale Physics (cond-mat.mes-hall)0103 physical sciencescond-mat.mes-hallElectronic engineeringHardware_ARITHMETICANDLOGICSTRUCTURESStandby powerApplied Physics010302 applied physicsSpintronicsCondensed Matter - Mesoscale and Nanoscale PhysicsMechanical EngineeringReservoir computingPhysics - Applied PhysicsMaterials EngineeringPhysik (inkl. Astronomie)Dissipation021001 nanoscience & nanotechnologyCondensed Matter PhysicsElectronic Optical and Magnetic MaterialsCMOS integrated circuits; Computation theory; Energy dissipation; Green computing; Spin fluctuations; Spintronics; Tunnel junctionsCMOS0210 nano-technologyUnconventional computingphysics.app-ph
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Unsupervised image processing scheme for transistor photon emission analysis in order to identify defect location

2015

International audience; The study of the light emitted by transistors in a highly scaled complementary metal oxide semiconductor (CMOS) integrated circuit (IC) has become a key method with which to analyze faulty devices, track the failure root cause, and have candidate locations for where to start the physical analysis. The localization of defective areas in IC corresponds to a reliability check and gives information to the designer to improve the IC design. The scaling of CMOS leads to an increase in the number of active nodes inside the acquisition area. There are also more differences between the spot’s intensities. In order to improve the identification of all of the photon emission sp…

Computer scienceImage processing[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing02 engineering and technologyIntegrated circuitIntegrated circuit design01 natural scienceslaw.inventionlaw0103 physical sciences0202 electrical engineering electronic engineering information engineeringComputer visionElectrical and Electronic Engineering[SPI.NANO]Engineering Sciences [physics]/Micro and nanotechnologies/Microelectronics010302 applied physicsSignal processingNoise (signal processing)business.industryPattern recognitionImage segmentationThresholdingAtomic and Molecular Physics and OpticsComputer Science ApplicationsCMOS[ SPI.NANO ] Engineering Sciences [physics]/Micro and nanotechnologies/Microelectronics020201 artificial intelligence & image processingArtificial intelligencebusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
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A random-walk benchmark for single-electron circuits

2021

Mesoscopic integrated circuits aim for precise control over elementary quantum systems. However, as fidelities improve, the increasingly rare errors and component crosstalk pose a challenge for validating error models and quantifying accuracy of circuit performance. Here we propose and implement a circuit-level benchmark that models fidelity as a random walk of an error syndrome, detected by an accumulating probe. Additionally, contributions of correlated noise, induced environmentally or by memory, are revealed as limits of achievable fidelity by statistical consistency analysis of the full distribution of error counts. Applying this methodology to a high-fidelity implementation of on-dema…

Computer scienceScienceFOS: Physical sciencesGeneral Physics and AstronomyWord error rateQuantum metrology02 engineering and technologyIntegrated circuit01 natural sciencesNoise (electronics)ArticleGeneral Biochemistry Genetics and Molecular Biologylaw.inventionComputer Science::Hardware ArchitecturelawMesoscale and Nanoscale Physics (cond-mat.mes-hall)0103 physical sciencesElectronic devicesQuantum metrology010306 general physicsQuantumQuantum computerQuantum PhysicsMultidisciplinaryCondensed Matter - Mesoscale and Nanoscale PhysicsQuantum dotsQGeneral Chemistry021001 nanoscience & nanotechnologyRandom walkComputerSystemsOrganization_MISCELLANEOUSBenchmark (computing)Quantum Physics (quant-ph)0210 nano-technologyAlgorithmNature Communications
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Systems chemical analytics: introduction to the challenges of chemical complexity analysis

2019

Understanding complex (bio/geo)systems is a pivotal challenge in modern sciences that fuels a constant development of modern analytical technology, finding innovative solutions to resolve and analyse. In this introductory paper to the Faraday Discussion "Challenges in the analysis of complex natural systems", we aim to present concepts of complexity, and complex chemistry in systems subjected to biotic and abiotic transformations, and introduce the analytical possibilities to disentangle chemical complexity into its elementary parts (i.e. compositional and structural resolution) as a global integrated approach termed systems chemical analytics.

Computer sciencebusiness.industry02 engineering and technologyIntegrated approach010402 general chemistry021001 nanoscience & nanotechnology01 natural sciencesData sciencecomplex biogeosystems0104 chemical sciencesanalytical technologyComplex chemistryAnalyticsPhysical and Theoretical Chemistrychemical complexity0210 nano-technologybusiness
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