Efficient data processing and quantum phenomena: Single-particle systems

We study the relation between the acquisition and analysis of data and quantum theory using a probabilistic and deterministic model for photon polarizers. We introduce criteria for efficient processing of data and then use these criteria to demonstrate that efficient processing of the data contained in single events is equivalent to the observation that Malus' law holds. A strictly deterministic process that also yields Malus' law is analyzed in detail. We present a performance analysis of the probabilistic and deterministic model of the photon polarizer. The latter is an adaptive dynamical system that has primitive learning capabilities. This additional feature has recently been shown to be sufficient to perform event-by-event simulations of interference phenomena, without using concepts of wave mechanics. We illustrate this by presenting results for a system of two chained Mach-Zehnder interferometers, suggesting that systems that perform efficient data processing and have learning capability are able to exhibit behavior that is usually attributed to quantum systems only.     

The influence of packaging materials on RF performance

At frequencies beyond 1 GHz, every component of the IC package contributes to the RF performance, whether required or not. In this work, we study the effects of packaging materials namely, the substrate and the globtop/underfill material on RF performance. We have measured interconnects on two area-array CSPs, the ball grid array and the polymer stud grid array using IMEC’s MCM-D technology. The measurements on the package interconnect show that the losses in the package substrate material account for about 50% of the total losses at 1.8 GHz and this drops to less than 20% at 5.2 GHz. The losses due to impedance mismatch dominate the losses especially below 10 GHz and considerable improvement in performance cannot be obtained by using an improved/expensive substrate. The other study is about the influence of globtop/underfill materials on wirebonds (through 3D EM simulations) as well as on standard 50 Ω MCM-D transmission lines (through experiments). While a higher value of dielectric constant of the globtop/underfill material is better on wirebonds, the influence of loss tangent is felt only above values of 0.1. The influence of seven different globtop/undefill materials on 50 Ω transmission lines has been used to extract their dielectric constant and loss tangent values at 30 GHz. These results are very valuable since one can hardly find the properties of globtop/underfill materials beyond 1 GHz.     

A 60‐GHz on‐chip slot‐array antenna in integrated‐passive‐device technology for antenna‐in‐package applications

A new millimeter‐wave antenna structure on a low‐cost, production platform integrated passive device technology is presented. The antenna consists of a 2‐by‐1 array of slot antennas at 60 GHz. An in‐house developed on‐chip antenna measurement setup was used to characterize the fabricated antenna. The measurement results show an antenna gain of more than 5 dBi with a return loss of 18 dB at 60 GHz. The better‐than‐10‐dB impedance bandwidth of the antenna covers the 60‐GHz unlicensed band from 57 to 64 GHz. The 3‐dB beamwidths of the antenna are 105° and 76° at E‐plane and H‐plane at 60 GHz, respectively. The size of the die of the antenna is 2 mm × 4.5 mm. © 2013 Wiley Periodicals, Inc. Int J RF and Microwave CAE 24:155–160, 2014.     

Itemset mining: A constraint programming perspective

The field of data mining has become accustomed to specifying constraints on patterns of interest. A large number of systems and techniques has been developed for solving such constraint-based mining problems, especially for mining itemsets. The approach taken in the field of data mining contrasts with the constraint programming principles developed within the artificial intelligence community. While most data mining research focuses on algorithmic issues and aims at developing highly optimized and scalable implementations that are tailored towards specific tasks, constraint programming employs a more declarative approach. The emphasis lies on developing high-level modeling languages and general solvers that specify what the problem is, rather than outlining how a solution should be computed, yet are powerful enough to be used across a wide variety of applications and application domains.This paper contributes a declarative constraint programming approach to data mining. More specifically, we show that it is possible to employ off-the-shelf constraint programming techniques for modeling and solving a wide variety of constraint-based itemset mining tasks, such as frequent, closed, discriminative, and cost-based itemset mining. In particular, we develop a basic constraint programming model for specifying frequent itemsets and show that this model can easily be extended to realize the other settings. This contrasts with typical procedural data mining systems where the underlying procedures need to be modified in order to accommodate new types of constraint, or novel combinations thereof. Even though the performance of state-of-the-art data mining systems outperforms that of the constraint programming approach on some standard tasks, we also show that there exist problems where the constraint programming approach leads to significant performance improvements over state-of-the-art methods in data mining and as well as to new insights into the underlying data mining problems. Many such insights can be obtained by relating the underlying search algorithms of data mining and constraint programming systems to one another. We discuss a number of interesting new research questions and challenges raised by the declarative constraint programming approach to data mining.     

ILP turns 20

Inductive Logic Programming (ILP) is an area of Machine Learning which has now reached its twentieth year. Using the analogy of a human biography this paper recalls the development of the subject from its infancy through childhood and teenage years. We show how in each phase ILP has been characterised by an attempt to extend theory and implementations in tandem with the development of novel and challenging real-world applications. Lastly, by projection we suggest directions for research which will help the subject coming of age.