Claudia Roberta Calidonna

Characteristics of asymmetric superconducting quantum interference devices

Direct current-superconducting quantum interference devices (SQUIDs) characterized by asymmetric Josephson junctions have never been used for applications. In order to demonstrate their potential advantages, a throughout numerical analysis of different asymmetric configurations has been carried out. A damping resistance has been included in the SQUID circuit and the thermal noise associated with junction and damping resistances has been considered in the numerical model. Magnetic modulations and flux noise spectral densities have been computed as a function of many parameters (bias current, asymmetry, SQUID inductance, and damping resistance) and the performance of symmetric and asymmetric devices have been compared. The results show that, by properly optimizing the SQUID design, asymmetric SQUIDs are characterized by higher magnetic flux to voltage transfer coefficient and lower flux noise. As a result, asymmetric configurations can be very useful in all the applications where high sensitivity is required.

A network of cellular automata for a landslide simulation

Cellular Automata (CA) offer a promising computational model to simulate complex phenomena that are characterized by different coupled parameters that account for the interactions of their different components. In this paper we present the Cellular Automata Network (CAN) computational model and its application to the simulation of debris/flow phenomena. We carried out some experimentations developing a CAN application that implements the SCIDDICA model (Simulation through Computational Innovative methods for the Detection of Debris flow path using Interactive Cellular Automatamodel), tested on the landslide occurred in Sarno (Italy) in 1998.nCAN model allows to represent each component of a physical system in terms of cellular automata, and the interactions among these components in terms of a network of cellular automata. The adoption of the CAN model allows to exploit two different types of parallelism: the data parallelism that comes from the use of Cellular Automata classical model, and the task parallelism that could occur introducing the network of Cellular Automata.

Improved superconducting quantum interference devices by resistance asymmetry

Direct current superconducting quantum interference devices made by Josephson junctions with asymmetric shunt resistances have been numerically investigated in the low temperature regime. When combined with a damping resistance, the asymmetry leads to a flux to voltage transfer coefficient several times larger than the one typical of symmetric devices, together with a lower magnetic flux noise. These results show that this type of asymmetric device may replace the standard ones in a large number of magnetometric applications, improving the sensitivity performance. The large transfer coefficient may also simplify the readout electronics allowing a direct coupling of asymmetric devices to an external preamplifier, without the need of an impedance matching flux transformer.

From classical infinite space–time CA to a hybrid CA model for natural sciences modeling

Abstract Complex phenomena occurring in natural sciences are usually characterized by a non trivial interplay between microscopic and macroscopic dynamics, which can be successfully captured by the cellular automata (CA) computational paradigm [1] . In this paper we show that some approximation of the classical CA paradigm is needed in order to properly deal with complex dynamical systems. Real phenomena can be efficiently modeled and simulated by introducing a modified CA approach, the CANv2 [2] . In this way one takes into account multiscale dynamics, through approximate infinite and/or infinitesimal dynamical stages, by means of a hybrid network of standard CA components and global operators. The power of the CANv2 approach is fully exploited by discussing three examples borrowed from the realm of natural science: debris flows after a landslide [3] , [4] , [5] , superconductive devices [2] and forest fires spread [6] , [7] . Advantages and limitations of our computational model explicitly arise when examples are discussed.

Mapping applications of cellular automata into applications of cellular automata networks

Cellular automata proved to be a promising model to simulate several complex systems: the requirement is that space and time, taken into account, have to be discretizable, while the system to be simulated has to satisfy locality and uniformity in the evolutionary space. Often, in dealing with the simulation of real complex systems some properties of locality are lost and consequently standard CA model application is very difficult. For this reason it is useful to extend the classical CA model and introduce feasible mechanisms in order to take advantage of the parallelism source of this computational model. With this aim the Cellular Automata Network (CAN) model was conceived that includes the advantages of classical CA models and introduces a new source of parallelism, i.e. the network of cellular automata. In this paper we deal with a sort of heuristics in order to map CA applications into CANs. This mapping can also be extremely useful as a proposal of a methodology to drive the modeling and simulation activity of complex phenomena that can be easily fragmented according to local interaction and components.

A graphic parallelizing environment for user-compiler interaction

Parallelizing compilers are essential tools for parallelizing old but sophisticated sequential programs. Program restructuring techniques, like loop transformations together with dependence analysis are applied to transform automatically sequential programs into parallel code. User interaction with the parallelizing process is very useful because, on massive parallel systems, small mistakes may cause large degradation on performance. In this paper we propose an interactive compiling environment, named Graphic Parallelizing Environment (GPE) ‘, equipped with visualization tools to join user knowledge and compiler techniques to efficiently tune the program parallelization process. GPE is oriented to the advanced users of parallel computers. The Parafrase-2 parallelizing compiler represents the core of the environment. TCL/TK is used as middleware integration language, mainly used to implement the environment components dispatcher, and the graphical components.

The Cellular Automata Network Compiler System: Modules and Features

In simulating complex phenomena by Cellular Automata (CA) programming model performances assume a crucial role. The efficient exploitation of intrinsic parallelism is a must for this kind of applications. The Cellular Automata Network (CAN) model, that is an extension of the CA classical model due to the introduction of the network abstraction between automata nodes, offer another parallelism source besides to the classical CA parallelism source. In order to exploit efficiently this opportunities tools and systems must be designed. In this paper we deal with the CAN compiler system components description and features designed ad hoc.

RUSICA initial implementations: Simulation results of sandy shore evolution in Porto Cesareo, Italy

Beach recession is spreading in Mediterranean by effects of climatic change. RUSICA is a Cellular Automata model, that is in developing phase for simulating such a complex phenomenon, considering its main mechanisms: loose particles (sand, gravel, silt, clay, etc.) mobilization, suspension, deposit and transport, triggered by waves and currents. A simplified version of the model was implemented and applied to data, related to the sandy shore of Torre Lapillo (Porto Cesareo, Italy), in August 2010, where shore evolution was monitored, even if data quality and quantity aren’t ideal in order to feed RUSICA. Simulations of different scenarios of stormy sea in that area evidenced the adequate performance of the model in capturing the main emergent features of the phenomenon in despite of the simplified approach.

Properties of asymmetric high critical temperature dc SQUIDs

Asymmetries between the two Josephson junctions of a dc-SQUID have always been considered undesirable spurious effects, responsible for the degradation of the device performance. However, it was recently demonstrated that a suitable choice of the asymmetric configuration can lead to magnetic flux noise values lower than symmetric ones. The numerical analysis was performed by using parameters typical of low-Tc SQUIDs, operating at the liquid helium temperature. In this paper, the analysis has been extended to high critical temperature dc SQUIDs, operating at the liquid nitrogen temperature. Also in this case, asymmetric SQUIDs show the best performance in terms of both flux to voltage transfer coefficient V/sub /spl Phi// and magnetic flux noise S/sub /spl Phi//. In order to optimize the device performance, the dependence of SQUID properties on damping resistance and normalized SQUID inductance has been computed for both symmetric and asymmetric configurations.

Exploring Multi-level Parallelism in Cellular Automata Networks

Usually physical systems are characterized by different coupled parameters accounting for the interaction of their different components. The Cellular Automata Network (CAN) model [1] allows to represent each component of a physical system in terms of Cellular Automata (CA) [9], and the interaction among these components in terms of CA networks. In this paper we report our experimentations in exploiting two different kinds of parallelism offered by the CAN model using policies for network restructuring and thread assignment. At this purpose we used a prototype graphic tool (CANviz) designed to let the user experimenting heuristics to effciently exploit two-level parallelism in CAN applications.