Three-Level Parallel J-Jacobi Algorithms for Hermitian Matrices

The paper describes several efficient parallel implementations of the one-sided hyperbolic Jacobi-type algorithm for computing eigenvalues and eigenvectors of Hermitian matrices. By appropriate blocking of the algorithms an almost ideal load balancing between all available processors/cores is obtained. A similar blocking technique can be used to exploit local cache memory of each processor to further speed up the process. Due to diversity of modern computer architectures, each of the algorithms described here may be the method of choice for a particular hardware and a given matrix size. All proposed block algorithms compute the eigenvalues with relative accuracy similar to the original non-blocked Jacobi algorithm.Comment: Submitted for publicatio

Quantum state transfer for multi-input linear quantum systems

Effective state transfer is one of the most important problems in quantum information processing. Typically, a quantum information device is composed of many subsystems with multi-input ports. In this paper, we develop a general theory describing the condition for perfect state transfer from the multi-input ports to the internal system components, for general passive linear quantum systems. The key notion used is the zero of the transfer function matrix. Application to entanglement generation and distribution in a quantum network is also discussed.Comment: 6 pages, 3 figures. A preliminary condensed version of this work will appear in Proceedings of the 55th IEEE Conference on Decision and Contro

Controlling phonons and photons at the wavelength-scale: silicon photonics meets silicon phononics

Radio-frequency communication systems have long used bulk- and surface-acoustic-wave devices supporting ultrasonic mechanical waves to manipulate and sense signals. These devices have greatly improved our ability to process microwaves by interfacing them to orders-of-magnitude slower and lower loss mechanical fields. In parallel, long-distance communications have been dominated by low-loss infrared optical photons. As electrical signal processing and transmission approaches physical limits imposed by energy dissipation, optical links are now being actively considered for mobile and cloud technologies. Thus there is a strong driver for wavelength-scale mechanical wave or "phononic" circuitry fabricated by scalable semiconductor processes. With the advent of these circuits, new micro- and nanostructures that combine electrical, optical and mechanical elements have emerged. In these devices, such as optomechanical waveguides and resonators, optical photons and gigahertz phonons are ideally matched to one another as both have wavelengths on the order of micrometers. The development of phononic circuits has thus emerged as a vibrant field of research pursued for optical signal processing and sensing applications as well as emerging quantum technologies. In this review, we discuss the key physics and figures of merit underpinning this field. We also summarize the state of the art in nanoscale electro- and optomechanical systems with a focus on scalable platforms such as silicon. Finally, we give perspectives on what these new systems may bring and what challenges they face in the coming years. In particular, we believe hybrid electro- and optomechanical devices incorporating highly coherent and compact mechanical elements on a chip have significant untapped potential for electro-optic modulation, quantum microwave-to-optical photon conversion, sensing and microwave signal processing.Comment: 26 pages, 5 figure

Parallel and Distributed Simulation of Discrete Event Systems

The achievements attained in accelerating the simulation of the dynamics of complex discrete event systems using parallel or distributed multiprocessing environments are comprehensively presented. While parallel discrete event simulation (DES) governs the evolution of the system over simulated time in an iterative SIMD way, distributed DES tries to spatially decompose the event structure underlying the system, and executes event occurrences in spatial subregions by logical processes (LPs) usually assigned to different (physical) processing elements. Synchronization protocols are necessary in this approach to avoid timing inconsistencies and to guarantee the preservation of event causalities across LPs. Included in the survey are discussions on the sources and levels of parallelism, synchronous vs. asynchronous simulation and principles of LP simulation. In the context of conservative LP simulation (Chandy/Misra/Bryant) deadlock avoidance and deadlock detection/recovery strategies, Conservative Time Windows and the Carrier Nullmessage protocol are presented. Related to optimistic LP simulation (Time Warp), Optimistic Time Windows, memory management, GVT computation, probabilistic optimism control and adaptive schemes are investigated. (Also cross-referenced as UMIACS-TR-94-100

Search for Second-Generation Leptoquarks in Proton-Antiproton Collisions

This document describes the search for second-generation leptoquarks (LQ_2) in around 114 pb^-1 of proton-antiproton collisions, recorded with the D0 detector between September 2002 and June 2003 at a centre-of-mass energy of sqrt{s} = 1.96 TeV. The predictions of the Standard Model and models including scalar leptoquark production are compared to the data for various kinematic distributions. Since no excess of data over the Standard Model prediction has been observed, a lower limit on the leptoquark mass of M(LQ_2)_{beta=1} > 200 GeV/c^2 has been calculated at 95% confidence level (C.L.), assuming a branching fraction of beta = BF(LQ_2 --> mu j) = 100% into a charged lepton and a quark. The corresponding limit for beta = 1/2 is M(LQ_2)_{beta=1/2} > 152 GeV/c^2. Finally, the results were combined with those from the search in the same channel at D0 Run I. This combination yields the exclusion limit of 222 GeV/c^2 (177 GeV/c^2) for beta=1 (1/2) at 95% C.L., which is the best exclusion limit for scalar second-generation leptoquarks (for beta=1) from a single experiment to date.In diesem Dokument wird die Suche nach Leptoquarks der zweiten Generation (LQ_2) in Proton-Antiproton-Kollisionen beschrieben, die mit dem D0-Detektor am TeVatron-Beschleuniger aufgezeichnet wurden. Im Zeitraum von September 2002 bis Juni 2003 wurde eine integrierte Luminosität von rund 114 pb^-1 bei einer Schwerpunktsenergie von sqrt{s} = 1.96 TeV gesammelt. Die Vorhersagen des Standardmodells der Teilchenphysik und darüber hinausgehender Modelle mit skalaren Leptoquarks wurden mit den Daten verglichen. Da kein Überschuss an Daten über der Standardmodellvorhersage beobachtet werden konnte, wurde unter der Annahme, dass Leptoquarks zu 100% in geladene Leptonen und Quarks zerfallen (beta = BF(LQ_2 --> mu j) = 100%), eine untere Schranke von M(LQ_2)_{beta=1} > 200 GeV/c^2 (95% C.L.) für die Masse von skalaren Leptoquarks der zweiten Generation ermittelt. Die entsprechende Ausschlussgrenze für beta=1/2 liegt bei M(LQ_2)_{beta=1/2} > 152 GeV/c^2. Schließlich wurden die Resultate mit den Ergebnissen einer Suche im gleichen Kanal bei D0 Run I kombiniert. Diese Kombination liefert die Ausschlussgrenzen M(LQ_2)_{beta=1} > 222 GeV/c^2 (177 GeV/c^2) für beta=1 (1/2) und ist somit für beta=1 das zur Zeit beste Ergebnis für skalare Leptoquarks der zweiten Generation eines einzelnen Experimentes

Dynamic quantum clustering: a method for visual exploration of structures in data

A given set of data-points in some feature space may be associated with a Schrodinger equation whose potential is determined by the data. This is known to lead to good clustering solutions. Here we extend this approach into a full-fledged dynamical scheme using a time-dependent Schrodinger equation. Moreover, we approximate this Hamiltonian formalism by a truncated calculation within a set of Gaussian wave functions (coherent states) centered around the original points. This allows for analytic evaluation of the time evolution of all such states, opening up the possibility of exploration of relationships among data-points through observation of varying dynamical-distances among points and convergence of points into clusters. This formalism may be further supplemented by preprocessing, such as dimensional reduction through singular value decomposition or feature filtering.Comment: 15 pages, 9 figure