High p_T Triggered Delta-eta,Delta-phi Correlations over a Broad Range in Delta-eta

The first measurement of pseudorapidity (Delta-eta) and azimuthal angle (Delta-phi) correlations between high transverse momentum charged hadrons (p_T > 2.5 GeV/c) and all associated particles is presented at both short- (small Delta-eta) and long-range (large Delta-eta) over a continuous pseudorapidity acceptance (-4<Delta-eta<2). In these proceedings, the various near- and away-side features of the correlation structure are discussed as a function of centrality in Au+Au collisions measured by PHOBOS at sqrt(s_NN)=200 GeV. In particular, this measurement allows a much more complete determination of the longitudinal extent of the ridge structure, first observed by the STAR collaboration over a limited eta range. In central collisions the ridge persists to at least Delta-eta=4, diminishing in magnitude as collisions become more peripheral until it disappears around Npart=80.Comment: 5 pages, 2 figures, presented at the 20th International Conference on Ultra-Relativistic Nucleus-Nucleus Collisions, "Quark Matter 2008", Jaipur, India, February 4-10, 2008. Full author list included and typo corrected in equation

SoK: Anti-Facial Recognition Technology

The rapid adoption of facial recognition (FR) technology by both government and commercial entities in recent years has raised concerns about civil liberties and privacy. In response, a broad suite of so-called "anti-facial recognition" (AFR) tools has been developed to help users avoid unwanted facial recognition. The set of AFR tools proposed in the last few years is wide-ranging and rapidly evolving, necessitating a step back to consider the broader design space of AFR systems and long-term challenges. This paper aims to fill that gap and provides the first comprehensive analysis of the AFR research landscape. Using the operational stages of FR systems as a starting point, we create a systematic framework for analyzing the benefits and tradeoffs of different AFR approaches. We then consider both technical and social challenges facing AFR tools and propose directions for future research in this field.Comment: Camera-ready version for Oakland S&P 202

Intracule Functional Models I. Angle-corrected correlation kernels

We explore the merits of applying a simple angle-dependent correction to the correlation kernel within the framework of Hartree–Fock–Wigner theory. Based on numerical results for the first eighteen atoms, we conclude that such a correction offers a significant improvement over the action kernel that we and others have explored previously

Latest results from the PHOBOS experiment

Over the past years PHOBOS has continued to analyze the large datasets obtained from the first five runs of the Relativistic Heavy Ion Collider (RHIC) at Brookhaven National Laboratory. The two main analysis streams have been pursued. The first one aims to obtain a broad and systematic survey of global properties of particle production in heavy ion collisions. The second class includes the study of fluctuations and correlations in particle production. Both type of studies have been performed for a variety of the collision systems, covering a wide range in collision energy and centrality. The uniquely large angular coverage of the PHOBOS detector and its ability to measure charged particles down to very low transverse momentum is exploited. The latest physics results from PHOBOS, as presented at Quark Matter 2008 Conference, are contained in this report.Comment: 9 pages, 9 figures, presented at the 20th International Conference on Ultra-Relativistic Nucleus-Nucleus Collisions, "Quark Matter 2008", Jaipur, India, Feb.4-10, 200

Towards a killer app for the Semantic Web

Killer apps are highly transformative technologies that create new markets and widespread patterns of behaviour. IT generally, and the Web in particular, has benefited from killer apps to create new networks of users and increase its value. The Semantic Web community on the other hand is still awaiting a killer app that proves the superiority of its technologies. There are certain features that distinguish killer apps from other ordinary applications. This paper examines those features in the context of the Semantic Web, in the hope that a better understanding of the characteristics of killer apps might encourage their consideration when developing Semantic Web applications

Novel Bose-Einstein Interference in the Passage of a Fast Particle in a Dense Medium

When an energetic particle collides coherently with many medium particles at high energies, the Bose-Einstein symmetry with respect to the interchange of the exchanged virtual bosons leads to a destructive interference of the Feynman amplitudes in most regions of the phase space but a constructive interference in some other regions of the phase space. As a consequence, the recoiling medium particles have a tendency to come out collectively along the direction of the incident fast particle, each carrying a substantial fraction of the incident longitudinal momentum. Such an interference appearing as collective recoils of scatterers along the incident particle direction may have been observed in angular correlations of hadrons associated with a high-$p_T$ trigger in high-energy AuAu collisions at RHIC.Comment: 10 pages, 2 figures, invited talk presented at the 35th Symposium on Nuclear Physics, Cocoyoc, Mexico, January 3, 2012, to be published in IOP Conference Serie

Filtered overlap: speedup, locality, kernel non-normality and Z_A~1

We investigate the overlap operator with a UV filtered Wilson kernel. The filtering leads to a better localization of the operator even on coarse lattices and with the untuned choice $\rho=1$. Furthermore, the axial-vector renormalization constant $Z_A$ is much closer to 1, reducing the mismatch with perturbation theory. We show that all these features persist over a wide range of couplings and that the details of filtering prove immaterial. We investigate the properties of the kernel spectrum and find that the kernel non-normality is reduced. As a side effect we observe that for certain applications of the filtered overlap a speed-up factor of 2-4 can be achieved.Comment: 30 pp, 23 fig

Blacklight: Defending Black-Box Adversarial Attacks on Deep Neural Networks

The vulnerability of deep neural networks (DNNs) to adversarial examples is well documented. Under the strong white-box threat model, where attackers have full access to DNN internals, recent work has produced continual advancements in defenses, often followed by more powerful attacks that break them. Meanwhile, research on the more realistic black-box threat model has focused almost entirely on reducing the query-cost of attacks, making them increasingly practical for ML models already deployed today. This paper proposes and evaluates Blacklight, a new defense against black-box adversarial attacks. Blacklight targets a key property of black-box attacks: to compute adversarial examples, they produce sequences of highly similar images while trying to minimize the distance from some initial benign input. To detect an attack, Blacklight computes for each query image a compact set of one-way hash values that form a probabilistic fingerprint. Variants of an image produce nearly identical fingerprints, and fingerprint generation is robust against manipulation. We evaluate Blacklight on 5 state-of-the-art black-box attacks, across a variety of models and classification tasks. While the most efficient attacks take thousands or tens of thousands of queries to complete, Blacklight identifies them all, often after only a handful of queries. Blacklight is also robust against several powerful countermeasures, including an optimal black-box attack that approximates white-box attacks in efficiency. Finally, Blacklight significantly outperforms the only known alternative in both detection coverage of attack queries and resistance against persistent attackers