Two-Loop Virtual Corrections to Drell-Yan Production at order alpha_s alpha^3

The Drell-Yan mechanism for the production of lepton pairs is one of the most basic processes for physics studies at hadron colliders. It is therefore important to have accurate theoretical predictions. In this work we compute the two-loop virtual mixed QCD x QED corrections to Drell-Yan production. We evaluate the Feynman diagrams by decomposing the amplitudes into a set of known master integrals and their coefficients, which allows us to derive an analytical result. We also perform a detailed study of the ultraviolet and infrared structure of the two-loop amplitude and the corresponding poles in epsilon.Comment: 20 pages, 3 figure

Tunable Balun Low-Noise Amplifier in 65nm CMOS Technology

The presented paper includes the design and implementation of a 65 nm CMOS low-noise amplifier (LNA) based on inductive source degeneration. The amplifier is realized with an active balun enabling a single-ended input which is an important requirement for low-cost system on chip implementations. The LNA has a tunable bandpass characteristics from 4.7 GHz up to 5.6 GHz and a continuously tunable gain from 22 dB down to 0 dB, which enables the required flexibility for multi-standard, multi-band receiver architectures. The gain and band tuning is realized with an optimized tunable active resistor in parallel to a tunable L-C tank amplifier load. The amplifier achieves an IIP3 linearity of -8dBm and a noise figure of 2.7 dB at the highest gain and frequency setting with a low power consumption of 10 mW. The high flexibility of the proposed LNA structure together with the overall good performance makes it well suited for future multi-standard low-cost receiver front-ends

Deep Learning and Music Adversaries

OA Monitor ExerciseOA Monitor ExerciseAn {\em adversary} is essentially an algorithm intent on making a classification system perform in some particular way given an input, e.g., increase the probability of a false negative. Recent work builds adversaries for deep learning systems applied to image object recognition, which exploits the parameters of the system to find the minimal perturbation of the input image such that the network misclassifies it with high confidence. We adapt this approach to construct and deploy an adversary of deep learning systems applied to music content analysis. In our case, however, the input to the systems is magnitude spectral frames, which requires special care in order to produce valid input audio signals from network-derived perturbations. For two different train-test partitionings of two benchmark datasets, and two different deep architectures, we find that this adversary is very effective in defeating the resulting systems. We find the convolutional networks are more robust, however, compared with systems based on a majority vote over individually classified audio frames. Furthermore, we integrate the adversary into the training of new deep systems, but do not find that this improves their resilience against the same adversary

Single charge sensing and transport in double quantum dots fabricated from commercially grown Si/SiGe heterostructures

We perform quantum Hall measurements on three types of commercially available modulation doped Si/SiGe heterostructures to determine their suitability for depletion gate defined quantum dot devices. By adjusting the growth parameters, we are able to achieve electron gases with charge densities 1-3 X 10^{11}/cm^2 and mobilities in excess of 100,000 cm^2/Vs. Double quantum dot devices fabricated on these heterostructures show clear evidence of single charge transitions as measured in dc transport and charge sensing and exhibit electron temperatures of 100 mK in the single quantum dot regime.Comment: Related papers at http://pettagroup.princeton.ed

Interpersonal Power: A Review, Critique, and Research Agenda

Power is a fundamental force in social relationships and is pervasive throughout various types of interactions. Although research has shown that the possession of power can change the powerholder, the full extent of power's consequences on individuals' decision making capabilities and social interactions within organizations is not fully understood. The goal of this paper is to review, synthesize, and critique the literature on power with a focus on its organizational and managerial implications. Specifically, we propose a definition of power that takes into account its three defining characteristics-having the discretion and means to enforce one's will-and summarize the extant literature on how power influences individuals' thoughts, emotions, and actions both in terms of prosocial and antisocial outcomes. In addition, we highlight important moderators of power and describe ways in which it can be studied in a more rigorous manner by examining methodological issues and pitfalls with regard to its measurement and manipulation. We also provide future research directions to motivate and guide the study of power by management scholars. Our desire is to present a thorough and parsimonious account of power's influence on individuals within an organizational context, as well as provide a foundation that scholars can build upon as they continue to make consequential contributions to the study of power

Study of the Distillability of Werner States Using Entanglement Witnesses and Robust Semidefinite Programs

We use Robust Semidefinite Programs and Entanglement Witnesses to study the distillability of Werner states. We perform exact numerical calculations which show 2-undistillability in a region of the state space which was previously conjectured to be undistillable. We also introduce bases which yield interesting expressions for the {\em distillability witnesses} and for a tensor product of Werner states with arbitrary number of copies.Comment: 16 pages, 2 figure