Physics

The discovery that a spin polarized current can exert a large torque on a ferromagnet through a transfusion of spin angular momentum, offers a new way to control a magnetization by simple current injection, without the help of an applied external field. Spin transfer can be used to induce magnetization reversals and oscillations, or to control the position of a magnetic domain wall. In this review, we focus on this last mechanism, which is today the subject of an extensive research, both because the microscopic details for its origin are still debated, but also because promising applications are at stake for non-volatile magnetic memories.

We present time-resolved measurements of the displacement of magnetic domain-walls (DWs) driven by vertical spin-polarized currents in track-shaped magnetic tunnel junctions. In these structures we observe very high DW velocities (600 m/s) at current densities below 10 7 A/cm 2 . We show that the efficient spin-transfer torque combined with a short propagation distance allows to avoid the Walker breakdown process, and achieve deterministic, reversible and fast (≈ 1 ns) DW-mediated switching of magnetic tunnel junction elements, which is of great interest to the implementation of fast DW-based spintronic devices.

We present time-resolved measurements of the displacement of magnetic domain-walls (DWs) driven by vertical spin-polarized currents in track-shaped magnetic tunnel junctions. In these structures we observe very high DW velocities (600 m/s) at current densities below 10 7 A/cm 2 . We show that the efficient spin-transfer torque combined with a short propagation distance allows to avoid the Walker breakdown process, and achieve deterministic, reversible and fast (≈ 1 ns) DW-mediated switching of magnetic tunnel junction elements, which is of great interest to the implementation of fast DW-based spintronic devices.

We present time-resolved measurements of the displacement of magnetic domain-walls (DWs) driven by vertical spin-polarized currents in track-shaped magnetic tunnel junctions. In these structures we observe very high DW velocities (600 m/s) at current densities below $10^7 A/cm^2$. We show that the efficient spin-transfer torque combined with a short propagation distance allows to avoid the Walker breakdown process, and achieve deterministic, reversible and fast ($\approx$ 1 ns) DW-mediated switching of magnetic tunnel junction elements, which is of great interest to the implementation of fast DW-based spintronic devices.

In standard near-field scanning optical microscopy (NSOM), a subwavelength probe acts as an optical 'stethoscope' to map the near field produced at the sample surface by external illumination 1 . This technique has been applied using visible 1,2 , infrared 3 , terahertz 4 and gigahertz 5,6 radiation to illuminate the sample, providing a resolution well beyond the diffraction limit. NSOM is well suited to study surface waves such as surface plasmons 7 or surfacephonon polaritons 8 . Using an aperture NSOM with visible laser illumination, a near-field interference pattern around a corral structure has been observed 9 , whose features were similar to the scanning tunnelling microscope image of the electronic waves in a quantum corral 10 . Here we describe an infrared NSOM that operates without any external illumination: it is a near-field analogue of a night-vision camera, making use of the thermal infrared evanescent fields emitted by the surface, and behaves as an optical scanning tunnelling microscope 11,12 . We therefore term this instrument a 'thermal radiation scanning tunnelling microscope' (TRSTM). We show the first TRSTM images of thermally excited surface plasmons, and demonstrate spatial coherence effects in near-field thermal emission.

To cope with the 40 MHz event production rate of LHC, the trigger of the ATLAS experiment selects events in three sequential steps of increasing complexity and accuracy whose final results are close to the offline reconstruction. The Level-1, implemented with custom hardware, identifies physics objects within Regions of Interests and operates with a first reduction of the event rate to 75 kHz. The higher trigger levels, Level-2 and Level-3, provide a software based event selection which further reduces the event rate to about 100 Hz. This paper presents the algorithm ( Fast) employed at Level-2 to confirm the muon candidates flagged by the Level-1. Fast identifies hits of muon tracks inside the barrel region of the Muon Spectrometer and provides a precise measurement of the muon momentum at the production vertex. The algorithm must process the Level-1 muon output rate ( 20 kHz), thus particular care has been taken for its optimization. The result is a very fast track reconstruction algorithm with good physics performance which, in some cases, approaches that of the offline reconstruction: it finds muon tracks with an efficiency of about 95% and computes of prompt muons with a resolution of 5.5% at 6 GeV and 4.0% at 20 GeV. The algorithm requires an overall execution time of 1 ms on a 100 SpecInt95 machine and has been tested in the online environment of the Atlas detector test beam.

The ATLAS combined test beam in the second half of 2004 saw the first deployment of the ATLAS High-Level Trigger (HLT). The next steps are deployment on the pre-series farms in the experimental area during 2005, commissioning and cosmics tests with the full detector in 2006 and collisions in 2007.

The ATLAS experiment at the Large Hadron Collider (LHC) will face the challenge of efficiently selecting interesting candidate events in©¨collisions at 14 TeV center-of-mass energy, whilst rejecting the enormous number of background events. The High-Level Trigger (HLT = second level trigger and Event Filter), which is a software based trigger will need to reduce the level-1 output rate of kHz to Hz written out to mass storage. In this talk an overview of the current physics and system performance of the HLT selection for electrons and photons is given. The performance has been evaluated using Monte Carlo simulations and has been partly demonstrated in the ATLAS testbeam in 2004. The efficiency for the signal channels, the rate expected for the selection, the global data preparation and execution times will be highlighted. Furthermore, some physics examples will be discussed to demonstrate that the triggers are well adapted for the physics programme envisaged at the LHC.

The ATLAS high-level trigger (HLT) system provides software-based event selection after the initial LVL1 hardware trigger. It is composed of two stages, the LVL2 trigger and the event filter (EF). The LVL2 trigger performs event selection with optimized algorithms using selected data guided by Region of Interest pointers provided by the LVL1 trigger. Those events selected by LVL2 are built into complete events, which are passed to the EF for a further stage of event selection and classification using off-line algorithms. Events surviving the EF selection are passed for off-line storage. The two stages of HLT are implemented on processor farms. The concept of distributing the selection process between LVL2 and EF is a key element in the architecture, which allows it to be flexible to changes (luminosity, detector knowledge, background conditions, etc.) Although there are some differences in the requirements between these subsystems there are many commonalities. An overview of the dataflow (event selection) and supervision (control, configuration, monitoring) activities in the HLT is given, highlighting where commonalities between the two subsystems can be exploited and indicating where requirements dictate that implementations differ. An HLT prototype system has been built at CERN. Functional testing is being carried out in order to validate the HLT architecture.

Following rigorous software design and analysis methods, an object-based architecture has been developed to derive the second-and third-level trigger decisions for the future ATLAS detector at the LHC. The functional components within this system responsible for generating elements of the trigger decisions are algorithms running within the software architecture. Relevant aspects of the architecture are reviewed along with concrete examples of specific algorithms and their performance in "vertical" slices of various physics selection strategies.

The ATLAS trigger reduces the rate of interesting events to be recorded for off-line analysis in three successive levels from 40 MHz to 100 kHz, 2 kHz and 200 Hz. The high level triggers and data acquisition system are designed to profit from commodity computing and networking components to achieve the required performance. In this paper, we discuss data flow aspects of the design of the second level trigger (LVL2) and present results of performance measurements.

The ATLAS High Level Trigger's (HLT) primary function of event selection will be accomplished with a Level-2 trigger farm and an event filter (EF) farm, both running software components developed in the ATLAS offline reconstruction framework. While this approach provides a unified software framework for event selection, it poses strict requirements on offline components critical for the Level-2 trigger. A Level-2 decision in ATLAS must typically be accomplished within 10 ms and with multiple event processing in concurrent threads.To address these constraints, prototypes have been developed that incorporate elements of the ATLAS data flow, high level trigger, and offline framework software. To realize a homogeneous software environment for offline components in the HLT, the Level-2 Steering Controller was developed. With electron/gammaand muon-selection slices it has been shown that the required performance can be reached, if the offline components used are carefully designed and optimized for the application in the HLT.

Event data from proton-proton collisions at the LHC will be selected by the ATLAS experiment in a three level trigger system, which reduces the initial bunch crossing rate of 40 MHz at its first two trigger levels (LVL1+LVL2) to ∼ 3 kHz. At this rate the Event-Builder collects the data from all Read-Out system