Weber blockade theory of magnetoresistance oscillations in superconducting strips

Recent experiments on the conductance of thin, narrow superconducting strips have found periodic fluctuations, as a function of the perpendicular magnetic field, with a period corresponding to approximately two flux quanta per strip area [A. Johansson et al., Phys. Rev. Lett. {\bf 95}, 116805 (2005)]. We argue that the low-energy degrees of freedom responsible for dissipation correspond to vortex motion. Using vortex/charge duality, we show that the superconducting strip behaves as the dual of a quantum dot, with the vortices, magnetic field, and bias current respectively playing the roles of the electrons, gate voltage and source-drain voltage. In the bias-current vs. magnetic-field plane, the strip conductance displays what we term `Weber blockade' diamonds, with vortex conductance maxima (i.e., electrical resistance maxima) that, at small bias-currents, correspond to the fields at which strip states of $N$ and $N+1$ vortices have equal energy.Comment: 4+a bit pages, 3 figures, 1 tabl

Effectiveness of kanban approaches in systems engineering within rapid response environments

AbstractEffective application of systems engineering in rapid response environments has been difficult, particularly those where large, complex brownfield systems or systems of systems exist and are constantly being updated with both short and long term software enhancements. This paper proposes a general case for solving this problem by combining a services approach to systems engineering with a kanban-based scheduling system. It provides the basis for validating the approach with agent-based simulations

On human correspondence

Funded by European Research CouncilPeer reviewedPostprin

AdaFair: Cumulative Fairness Adaptive Boosting

The widespread use of ML-based decision making in domains with high societal impact such as recidivism, job hiring and loan credit has raised a lot of concerns regarding potential discrimination. In particular, in certain cases it has been observed that ML algorithms can provide different decisions based on sensitive attributes such as gender or race and therefore can lead to discrimination. Although, several fairness-aware ML approaches have been proposed, their focus has been largely on preserving the overall classification accuracy while improving fairness in predictions for both protected and non-protected groups (defined based on the sensitive attribute(s)). The overall accuracy however is not a good indicator of performance in case of class imbalance, as it is biased towards the majority class. As we will see in our experiments, many of the fairness-related datasets suffer from class imbalance and therefore, tackling fairness requires also tackling the imbalance problem. To this end, we propose AdaFair, a fairness-aware classifier based on AdaBoost that further updates the weights of the instances in each boosting round taking into account a cumulative notion of fairness based upon all current ensemble members, while explicitly tackling class-imbalance by optimizing the number of ensemble members for balanced classification error. Our experiments show that our approach can achieve parity in true positive and true negative rates for both protected and non-protected groups, while it significantly outperforms existing fairness-aware methods up to 25% in terms of balanced error.Comment: 10 pages, to appear in proceedings of the 28th ACM International Conference on Information and Knowledge Management (CIKM

Navigating the Range of Statistical Tools for Inferential Network Analysis

The last decade has seen substantial advances in statistical techniques for the analysis of network data, as well as a major increase in the frequency with which these tools are used. These techniques are designed to accomplish the same broad goal, statistically valid inference in the presence of highly interdependent relationships, but important differences remain between them. We review three approaches commonly used for inferential network analysis—the quadratic assignment procedure, exponential random graph models, and latent space network models—highlighting the strengths and weaknesses of the techniques relative to one another. An illustrative example using climate change policy network data shows that all three network models outperform standard logit estimates on multiple criteria. This article introduces political scientists to a class of network techniques beyond simple descriptive measures of network structure, and it helps researchers choose which model to use in their own research

Reports of the DAS02 Working Groups

This document is a collection of four working group reports in the areas of digital libraries, document image retrieval, layout analysis, and Web document analysis. These reports were the outcome of discussions by participants at the Fifth IAPR International Workshop on Document Analysis Systems held in Princeton, NJ on 19-21 August 2002

Claiming But Connected to Work

This report presents the first findings from the Welfare at a (Social) Distance project, a major national research project investigating the benefits system during the COVID-19 pandemic, funded by the Economic and Social Research Council as part of UK Research and Innovation’s rapid response to COVID-19. It draws upon a new survey of 2,364 new Universal Credit (UC)/Jobseekers’ Allowance (JSA) claimants (carried out between 25th May and 3rd June) to look at how far benefit claimants are connected to the world of work, helping to better understand the emerging picture from recent UK labour market statistics

Thermodynamic anomalies in open quantum systems: Strong coupling effects in the isotropic XY model

The exactly solvable model of a one dimensional isotropic XY spin chain is employed to study the thermodynamics of open systems. For this purpose the chain is subdivided into two parts, one part is considered as the system while the rest as the environment or bath. The equilibrium properties of the system display several anomalous aspects such as negative entropies, negative specific heat, negative susceptibilities in dependence of temperature and coupling strength between system and bath. The statistical mechanics of this system is studied in terms of a reduced density matrix. At zero temperature and for a certain parameter values we observe a change of the ground state, a situation akin to a quantum phase transition.Comment: 12 pages, 8 figures. Published in the special issue of Chemical Physics "Stochastic processes in Physics and Chemistry" (in honor of Peter H\"anggi

Fairness Testing: Testing Software for Discrimination

This paper defines software fairness and discrimination and develops a testing-based method for measuring if and how much software discriminates, focusing on causality in discriminatory behavior. Evidence of software discrimination has been found in modern software systems that recommend criminal sentences, grant access to financial products, and determine who is allowed to participate in promotions. Our approach, Themis, generates efficient test suites to measure discrimination. Given a schema describing valid system inputs, Themis generates discrimination tests automatically and does not require an oracle. We evaluate Themis on 20 software systems, 12 of which come from prior work with explicit focus on avoiding discrimination. We find that (1) Themis is effective at discovering software discrimination, (2) state-of-the-art techniques for removing discrimination from algorithms fail in many situations, at times discriminating against as much as 98% of an input subdomain, (3) Themis optimizations are effective at producing efficient test suites for measuring discrimination, and (4) Themis is more efficient on systems that exhibit more discrimination. We thus demonstrate that fairness testing is a critical aspect of the software development cycle in domains with possible discrimination and provide initial tools for measuring software discrimination.Comment: Sainyam Galhotra, Yuriy Brun, and Alexandra Meliou. 2017. Fairness Testing: Testing Software for Discrimination. In Proceedings of 2017 11th Joint Meeting of the European Software Engineering Conference and the ACM SIGSOFT Symposium on the Foundations of Software Engineering (ESEC/FSE), Paderborn, Germany, September 4-8, 2017 (ESEC/FSE'17). https://doi.org/10.1145/3106237.3106277, ESEC/FSE, 201