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Adversarial Mixup ResynthesizersMar 07 2019In this paper, we explore new approaches to combining information encoded within the learned representations of autoencoders. We explore models that are capable of combining the attributes of multiple inputs such that a resynthesised output is trained ... More

Spatio-Temporal Deep Graph InfomaxApr 12 2019Spatio-temporal graphs such as traffic networks or gene regulatory systems present challenges for the existing deep learning methods due to the complexity of structural changes over time. To address these issues, we introduce Spatio-Temporal Deep Graph ... More

Iterative Refinement of Approximate Posterior for Training Directed Belief NetworksNov 19 2015Mar 14 2016Recent advances in variational inference that make use of an inference or recognition network for training and evaluating deep directed graphical models have advanced well beyond traditional variational inference and Markov chain Monte Carlo methods. ... More

Prediction of Progression to Alzheimer`s disease with Deep InfoMaxApr 24 2019Arguably, unsupervised learning plays a crucial role in the majority of algorithms for processing brain imaging. A recently introduced unsupervised approach Deep InfoMax (DIM) is a promising tool for exploring brain structure in a flexible non-linear ... More

Recurrent Neural Networks for Spatiotemporal Dynamics of Intrinsic Networks from fMRI DataNov 03 2016Functional magnetic resonance imaging (fMRI) of temporally-coherent blood oxygenization level-dependent (BOLD) signal provides an effective means of analyzing functionally coherent patterns in the brain. Intrinsic networks and functional connectivity ... More

Variational Autoencoders for Feature Detection of Magnetic Resonance Imaging DataMar 21 2016Independent component analysis (ICA), as an approach to the blind source-separation (BSS) problem, has become the de-facto standard in many medical imaging settings. Despite successes and a large ongoing research effort, the limitation of ICA to square ... More

Negative Learning Rates and P-LearningMar 27 2016Mar 29 2016We present a method of training a differentiable function approximator for a regression task using negative examples. We effect this training using negative learning rates. We also show how this method can be used to perform direct policy learning in ... More

Deep learning for neuroimaging: a validation studyDec 20 2013Feb 19 2014Deep learning methods have recently made notable advances in the tasks of classification and representation learning. These tasks are important for brain imaging and neuroscience discovery, making the methods attractive for porting to a neuroimager's ... More

Iterative Refinement of Approximate Posterior for Training Directed Belief NetworksNov 19 2015Oct 29 2016Variational methods that rely on a recognition network to approximate the posterior of directed graphical models offer better inference and learning than previous methods. Recent advances that exploit the capacity and flexibility in this approach have ... More

Maximum-Likelihood Augmented Discrete Generative Adversarial NetworksFeb 26 2017Despite the successes in capturing continuous distributions, the application of generative adversarial networks (GANs) to discrete settings, like natural language tasks, is rather restricted. The fundamental reason is the difficulty of back-propagation ... More

Spatio-temporal Dynamics of Intrinsic Networks in Functional Magnetic Imaging Data Using Recurrent Neural NetworksNov 03 2016Aug 27 2018We introduce a novel recurrent neural network (RNN) approach to account for temporal dynamics and dependencies in brain networks observed via functional magnetic resonance imaging (fMRI). Our approach directly parameterizes temporal dynamics through recurrent ... More

Learning deep representations by mutual information estimation and maximizationAug 20 2018Feb 22 2019In this work, we perform unsupervised learning of representations by maximizing mutual information between an input and the output of a deep neural network encoder. Importantly, we show that structure matters: incorporating knowledge about locality of ... More

Adversarial Mixup ResynthesizersMar 07 2019Apr 04 2019In this paper, we explore new approaches to combining information encoded within the learned representations of autoencoders. We explore models that are capable of combining the attributes of multiple inputs such that a resynthesised output is trained ... More

Learning deep representations by mutual information estimation and maximizationAug 20 2018Jan 26 2019In this work, we perform unsupervised learning of representations by maximizing mutual information between an input and the output of a deep neural network encoder. Importantly, we show that structure matters: incorporating knowledge about locality of ... More

Boundary-Seeking Generative Adversarial NetworksFeb 27 2017Feb 21 2018Generative adversarial networks (GANs) are a learning framework that rely on training a discriminator to estimate a measure of difference between a target and generated distributions. GANs, as normally formulated, rely on the generated samples being completely ... More

Iterative Refinement of the Approximate Posterior for Directed Belief NetworksNov 19 2015Feb 20 2018Variational methods that rely on a recognition network to approximate the posterior of directed graphical models offer better inference and learning than previous methods. Recent advances that exploit the capacity and flexibility in this approach have ... More

On-line Adaptative Curriculum Learning for GANsJul 31 2018Mar 11 2019Generative Adversarial Networks (GANs) can successfully approximate a probability distribution and produce realistic samples. However, open questions such as sufficient convergence conditions and mode collapse still persist. In this paper, we build on ... More

ACtuAL: Actor-Critic Under Adversarial LearningNov 13 2017Generative Adversarial Networks (GANs) are a powerful framework for deep generative modeling. Posed as a two-player minimax problem, GANs are typically trained end-to-end on real-valued data and can be used to train a generator of high-dimensional and ... More

MINE: Mutual Information Neural EstimationJan 12 2018Jun 07 2018We argue that the estimation of mutual information between high dimensional continuous random variables can be achieved by gradient descent over neural networks. We present a Mutual Information Neural Estimator (MINE) that is linearly scalable in dimensionality ... More

Deep Graph InfomaxSep 27 2018Dec 21 2018We present Deep Graph Infomax (DGI), a general approach for learning node representations within graph-structured data in an unsupervised manner. DGI relies on maximizing mutual information between patch representations and corresponding high-level summaries ... More

Invariant Feature Mappings for Generalizing Affordance Understanding Using Regularized Metric LearningJan 30 2019This paper presents an approach for learning invariant features for object affordance understanding. One of the major problems for a robotic agent acquiring a deeper understanding of affordances is finding sensory-grounded semantics. Being able to understand ... More

GibbsNet: Iterative Adversarial Inference for Deep Graphical ModelsDec 12 2017Directed latent variable models that formulate the joint distribution as $p(x,z) = p(z) p(x \mid z)$ have the advantage of fast and exact sampling. However, these models have the weakness of needing to specify $p(z)$, often with a simple fixed prior that ... More

The Distance to the Draco CloudSep 14 1998The understanding of the nature of intermediate and high velocity gas in the Milky Way is hampered by a paucity of distance estimates to individual clouds. A project has been started at the David Dunlap Observatory to address this lack of distance measures ... More

Keep Drawing It: Iterative language-based image generation and editingNov 24 2018Conditional text-to-image generation approaches commonly focus on generating a single image in a single step. One practical extension beyond one-step generation is an interactive system that generates an image iteratively, conditioned on ongoing linguistic ... More

Tell, Draw, and Repeat: Generating and modifying images based on continual linguistic instructionNov 24 2018Apr 01 2019Conditional text-to-image generation is an active area of research, with many possible applications. Existing research has primarily focused on generating a single image from available conditioning information in one step. One practical extension beyond ... More

On the number of primes for which a polynomial is EisensteinJan 25 2019Previously Heyman and Shparlinski gave an asymptotic formula with error term for the number of Eisenstein polynomials of fixed degree and bounded height. Let $\psi(f)$ denote the number of primes for which a polynomial $f$ is Eisenstein. We give expressions ... More

Standards and Intellectual Property Rights in the Age of Global Communication - A Review of the International Standardization of Third-Generation Mobile SystemSep 25 2001Oct 30 2001When the European Telecommunications Standards Institute (ETSI) selected a radio access technology based on Wideband Code-Division Multiple Access (WCDMA), sponsored by European telecommunications equipment manufactures Ericsson and Nokia, for its third-generation ... More

Deep Models of Interactions Across SetsMar 07 2018Jun 08 2018We use deep learning to model interactions across two or more sets of objects, such as user-movie ratings, protein-drug bindings, or ternary user-item-tag interactions. The canonical representation of such interactions is a matrix (or a higher-dimensional ... More

A new and flexible method for constructing designs for computer experimentsOct 02 2010We develop a new method for constructing "good" designs for computer experiments. The method derives its power from its basic structure that builds large designs using small designs. We specialize the method for the construction of orthogonal Latin hypercubes ... More

The XMM Cluster Survey: evolution of the velocity dispersion -- temperature relation over half a Hubble timeDec 09 2015Aug 03 2016We measure the evolution of the velocity dispersion--temperature ($\sigma_{\rm v}$--$T_{\rm X}$) relation up to $z = 1$ using a sample of 38 galaxy clusters drawn from the \textit{XMM} Cluster Survey. This work improves upon previous studies by the use ... More

The Effect of Adsorbed Liquid and Material Density on Saltation Threshold: Insight from Laboratory and Wind Tunnel ExperimentsJun 30 2017Saltation threshold, the minimum wind speed for sediment transport, is a fundamental parameter in aeolian processes. The presence of liquid, such as water on Earth or methane on Titan, may affect the threshold values to a great extent. Sediment density ... More

Benchtop Nonresonant X-ray Emission Spectroscopy: Coming Soon to Laboratories and XAS Beamlines Near You?Sep 18 2015Recently developed instrumentation at the University of Washington has allowed for nonresonant x-ray emission spectra (XES) to be measured in a laboratory-setting with an inexpensive, easily operated system. We present a critical evaluation of this equipment ... More

An exact general remeshing scheme applied to physically conservative voxelizationDec 16 2014Jun 01 2015We present an exact general remeshing scheme to compute analytic integrals of polynomial functions over the intersections between convex polyhedral cells of old and new meshes. In physics applications this allows one to ensure global mass, momentum, and ... More

A Modern Laboratory XAFS CookbookSep 18 2015We have recently demonstrated a very favorable, inexpensive modernization of lab-based x-ray absorption fine structure (XAFS) and high-resolution x-ray emission spectroscopy (XES) using only commercially-available optics and x-ray tube sources. Here, ... More

The Buzzard Flock: Dark Energy Survey Synthetic Sky CatalogsJan 08 2019We present a suite of 18 synthetic sky catalogs designed to support science analysis of galaxies in the Dark Energy Survey Year 1 (DES Y1) data. For each catalog, we use a computationally efficient empirical approach, ADDGALS, to embed galaxies within ... More

Deep Models for Relational DatabasesMar 21 2019Due to its extensive use in databases, the relational model is ubiquitous in representing big-data. We propose to apply deep learning to this type of relational data by introducing an Equivariant Relational Layer (ERL), a neural network layer derived ... More

Voids in cosmological simulations over cosmic timeFeb 27 2016Mar 30 2016We study evolution of voids in cosmological simulations using a new method for tracing voids over cosmic time. The method is based on tracking watershed basins (contiguous regions around density minima) of well developed voids at low redshift, on a regular ... More

A Sequential Design Approach for Calibrating a Dynamic Population Growth ModelOct 31 2018A comprehensive understanding of the population growth of a variety of pests is often crucial for efficient crop management. Our motivating application comes from calibrating a two-delay blowfly (TDB) model which is used to simulate the population growth ... More

Global Fitting of the Response Surface via Estimating Multiple Contours of a SimulatorFeb 04 2019Computer simulators are nowadays widely used to understand complex physical systems in many areas such as aerospace, renewable energy, climate modeling, and manufacturing. One fundamental issue in the study of computer simulators is known as experimental ... More

Local Gaussian Process Model for Large-scale Dynamic Computer ExperimentsNov 29 2016Apr 03 2018The recent accelerated growth in the computing power has generated popularization of experimentation with dynamic computer models in various physical and engineering applications. Despite the extensive statistical research in computer experiments, most ... More

On a method to resolve the nuclear activity in galaxies as applied to the Seyfert 2 galaxy NGC1358Jan 14 2010Aug 29 2010Nuclear regions of galaxies generally host a mixture of components with different exitation, composition, and kinematics. Derivation of emission line ratios and kinematics could then be misleading, if due correction is not made for the limited spatial ... More

Local Gaussian Process Model for Large-scale Dynamic Computer ExperimentsNov 29 2016The recent accelerated growth in the computing power has generated popularization of experimentation with dynamic computer models in various physical and engineering applications. Despite the extensive statistical research in computer experiments, most ... More

An Improved Laboratory-Based XAFS and XES Spectrometer for Analytical Applications in Materials Chemistry ResearchJul 21 2018X-ray absorption fine structure (XAFS) and x-ray emission spectroscopy (XES) are advanced x-ray spectroscopies that impact a wide range of disciplines. However, unlike the majority of other spectroscopic methods, XAFS and XES are accompanied by an unusual ... More

Mining for Geographically Disperse Communities in Social Networks by Leveraging Distance ModularityMay 16 2013Social networks where the actors occupy geospatial locations are prevalent in military, intelligence, and policing operations such as counter-terrorism, counter-insurgency, and combating organized crime. These networks are often derived from a variety ... More

Near-Infrared Spectroscopy of Trojan Asteroids: Evidence for Two Compositional GroupsDec 06 2010The Trojan asteroids remain quite poorly understood, yet their physical properties provide unique perspective on chemical and dynamical processes that shaped the Solar System. The current study was undertaken to investigate surface compositions of these ... More

The Doppler effect on indirect detection of dark matter using dark matter only simulationsNov 08 2016Aug 03 2017Indirect detection of dark matter is a major avenue for discovery. However, baryonic backgrounds are diverse enough to mimic many possible signatures of dark matter. In this work, we study the newly proposed technique of dark matter velocity spectroscopy\,\cite{speckhard2016}. ... More

Explicit bounds for small prime nonresiduesFeb 12 2019Let $\chi$ be a Dirichlet character modulo a prime~$p$. We give explicit upper bounds on $q_1<q_2<\dots<q_n$, the $n$ smallest prime nonresidues of $\chi$. More precisely, given $n_0$ and $p_0$ there exists an absolute constant $C=C(n_0,p_0)>0$ such that ... More

Shaping Operations to Attack Robust Terror NetworksNov 04 2012Security organizations often attempt to disrupt terror or insurgent networks by targeting "high value targets" (HVT's). However, there have been numerous examples that illustrate how such networks are able to quickly re-generate leadership after such ... More

Chirped-pulse interferometry with finite frequency correlationsSep 04 2009Chirped-pulse interferometry is a new interferometric technique encapsulating the advantages of the quantum Hong-Ou-Mandel interferometer without the drawbacks of using entangled photons. Both interferometers can exhibit even-order dispersion cancellation ... More

The Doppler effect on indirect detection of dark matter using dark matter only simulationsNov 08 2016Indirect detection of dark matter is a major avenue for discovery. However, baryonic backgrounds are diverse enough to mimic many possible signatures of dark matter. In this work, we study the newly proposed technique of dark matter velocity spectroscopy ... More

Reducing Noise in Cosmological N-body Simulations with NeutrinosJan 11 2018We present a new method for generating initial conditions for numerical cosmological simulations in which massive neutrinos are treated as an extra set of N-body (collisionless) particles. It allows us to accurately follow the density field for both Cold ... More

Reaction-Diffusion Degradation Model for Delayed Erosion of Cross-Linked Polyanhydride BiomaterialsOct 28 2015We develop a theoretical model to explain the long induction interval of water intake that precedes the onset of erosion due to degradation caused by hydrolysis in the recently synthesized and studied cross-linked polyanhydrides. Various kinetic mechanisms ... More

Procrastinating with Confidence: Near-Optimal, Anytime, Adaptive Algorithm ConfigurationFeb 14 2019Algorithm configuration methods optimize the performance of a parameterized heuristic algorithm on a given distribution of problem instances. Recent work introduced an algorithm configuration procedure ('Structured Procrastination') that provably achieves ... More

DOCSDN: Dynamic and Optimal Configuration of Software-Defined NetworksFeb 15 2019Networks are designed with functionality, security, performance, and cost in mind. Tools exist to check or optimize individual properties of a network. These properties may conflict, so it is not always possible to run these tools in series to find a ... More

Advanced Scenario Creation Strategies for Stochastic Economic Dispatch with RenewablesJun 27 2018Real-time dispatch practices for operating the electric grid in an economic and reliable manner are evolving to accommodate higher levels of renewable energy generation. In particular, stochastic optimization is receiving increased attention as a technique ... More

The DDO IVC Distance ProjectNov 18 1998We present the first set of distance limits from the David Dunlap Observatory Intermediate Velocity Cloud (DDO IVC) distance project. Such distance measures are crucial to understanding the origins and dynamics of IVCs, as the distances set most of the ... More

Mapping our Universe in 3D with MITEoRSep 10 2013Mapping our universe in 3D by imaging the redshifted 21 cm line from neutral hydrogen has the potential to overtake the cosmic microwave background as our most powerful cosmological probe, because it can map a much larger volume of our Universe, shedding ... More

Attacking the Nintendo 3DS Boot ROMsFeb 01 2018Feb 02 2018We demonstrate attacks on the boot ROMs of the Nintendo 3DS in order to exfiltrate secret information from normally protected areas of memory and gain persistent early code execution on devices which have not previously been compromised. The attack utilizes ... More

Learning to diagnose from scratch by exploiting dependencies among labelsOct 28 2017Feb 01 2018The field of medical diagnostics contains a wealth of challenges which closely resemble classical machine learning problems; practical constraints, however, complicate the translation of these endpoints naively into classical architectures. Many tasks ... More

Was ordinary matter synthesised from mirror matter? An attempt to explain why $Ω_{Baryon} \approx 0.2Ω_{Dark}$Apr 28 2003Jun 03 2003The cosmological dust has begun to settle. A likely picture is a universe comprised (predominantly) of three components: ordinary baryons ($\Omega_B \approx 0.05$), non-baryonic dark matter ($\Omega_{Dark} \approx 0.22$) and dark energy ($\Omega_{\Lambda} ... More

How neutrino oscillations can induce an effective neutrino number of less than 3 during Big Bang NucleosynthesisJun 04 1997Ordinary-sterile neutrino oscillations can generate significant neutrino asymmetry in the early Universe. In this paper we extend this work by computing the evolution of neutrino asymmetries and light element abundances during the Big Bang Nucleosynthesis ... More

Maximal neutrino oscillation solution to the solar neutrino problemOct 17 1995We discuss a simple predictive solution to the solar neutrino problem based on maximal vacuum neutrino oscillations. The solution can be motivated by the exact parity symmetric model which predicts that the neutrino mass eigenstates are maximal mixtures ... More

A mirror world explanation for the Pioneer spacecraft anomalies?Aug 06 2001We show that the anomalous acceleration of the Pioneer 10/11 spacecraft can be explained if there is some mirror gas or mirror dust in our solar system.

The exact parity symmetric model and big bang nucleosynthesisDec 04 1996The assumption of exact, unbroken parity symmetry leads directly to a simple predictive resolution of the atmospheric and solar neutrino puzzles. This is because the existence of this symmetry implies the existence of a set of mirror neutrinos which must ... More

Fast Segmentation of Left Ventricle in CT Images by Explicit Shape Regression using Random Pixel Difference FeaturesJul 27 2015Jul 28 2015Recently, machine learning has been successfully applied to model-based left ventricle (LV) segmentation. The general framework involves two stages, which starts with LV localization and is followed by boundary delineation. Both are driven by supervised ... More

Cluster-state quantum computing enhanced by high-fidelity generalized measurementsSep 15 2009We introduce and implement a technique to extend the quantum computational power of cluster states by replacing some projective measurements with generalized quantum measurements (POVMs). As an experimental demonstration we fully realize an arbitrary ... More

Spheroidal galactic halos and mirror dark matterJul 26 2004Mirror matter has been proposed as a dark matter candidate. It has several very attractive features, including automatic stability and darkness, the ability to mimic the broad features of cold dark matter while in the linear density perturbation regime, ... More

New and improved quark-lepton symmetric modelsMay 18 1995We show how the use of a see-saw mechanism based on a $3 \times 3$ neutrino mass matrix texture can considerably simplify Higgs sectors for quark-lepton symmetric models (and for Standard Model extensions generally). The main theory we discuss also incorporates ... More

Natural electroweak symmetry breaking in generalised mirror matter modelsOct 02 2006Nov 28 2006It has recently been pointed out that the mirror or twin Higgs model is more technically natural than the standard model, thus alleviating the ``little'' hierarchy problem. In this paper we generalise the analysis to models with an arbitrary number of ... More

Studies of neutrino asymmetries generated by ordinary-sterile neutrino oscillations in the early universe and implications for big bang nucleosynthesis boundsOct 03 1996Nov 19 1996Ordinary-sterile neutrino oscillations can generate a significant lepton number asymmetry in the early Universe. We study this phenomenon in detail. We show that the dynamics of ordinary-sterile neutrino oscillations in the early Universe can be approximately ... More

Do the SuperKamiokande atmospheric neutrino results explain electric charge quantisation?Aug 24 1998We show that the SuperKamiokande atmospheric neutrino results explain electric charge quantisation, provided that the oscillation mode is $\nu_{\mu} \to \nu_{\tau}$ and that the neutrino mass is of Majorana type.

Neutrino physics and the mirror world: how exact parity symmetry explains the solar neutrino deficit, the atmospheric neutrino anomaly and the LSND experimentMay 23 1995Nov 08 1995Evidence for $\bar \nu_{\mu} \rightarrow \bar \nu_e$ oscillations has been reported at LAMPF using the LSND detector. Further evidence for neutrino mixing comes from the solar neutrino deficit and the atmospheric neutrino anomaly. All of these anomalies ... More

Derivation and experimental test of fidelity benchmarks for remote preparation of arbitrary qubit statesSep 30 2009Remote state preparation (RSP) is the act of preparing a quantum state at a remote location without actually transmitting the state itself. Using at most two classical bits and a single shared maximally entangled state, one can in theory remotely prepare ... More

Joint quantum measurements with minimum uncertaintyAug 26 2013Aug 28 2013Quantum physics constrains the accuracy of joint measurements of incompatible observables. Here we test tight measurement-uncertainty relations using single photons. We implement two independent, idealized uncertainty-estimation methods, the 3-state method ... More

Astrometry and Occultation predictions to Trans-Neptunian and Centaur Objects observed within the Dark Energy SurveyNov 26 2018Transneptunian objects (TNOs) are a source of invaluable information to access the history and evolution of the outer solar system. However, observing these faint objects is a difficult task. As a consequence, important properties such as size and albedo ... More

Legendrian contact homology and topological entropySep 12 2014Apr 23 2016In this paper we study the growth rate of a version of Legendrian contact homology, which we call strip Legendrian contact homology, in 3-dimensional contact manifolds and its relation to the topological entropy of Reeb flows. We show that: if for a pair ... More

The heat-kernel and the average effective potentialMay 29 1995We discuss the definition of the average effective action in terms of the heat-kernel. As an example we examine a model describing a self-interacting scalar field, both in flat and curved background, and study the renormalization group flow of some of ... More

The renormalization group flow of the dilaton potentialDec 20 1994We consider a scalar-metric gauge theory of gravity with independent metric, connection and dilaton. The role of the dilaton is to provide the scale of all masses, via its vacuum expectation value. In this theory, we study the renormalization group flow ... More

Ordinary-derivative formulation of conformal low-spin fieldsJul 30 2007Nov 14 2011Conformal fields in flat space-time of even dimension greater than or equal to four are studied. Second-derivative formulation for spin 0,1,2 conformal bosonic fields and first-derivative formulation for spin 1/2,3/2 conformal fermionic fields are developed. ... More

Gravitational and higher-derivative interactions of massive spin 5/2 field in (A)dS spaceDec 27 2006Sep 10 2007Using on-shell gauge invariant formulation of relativistic dynamics we study interaction vertices for a massive spin 5/2 Dirac field propagating in (A)dS space of dimension greater than or equal to four. Gravitational interaction vertex for the massive ... More

CFT adapted gauge invariant formulation of arbitrary spin fields in AdS and modified de Donder gaugeAug 28 2008Jan 22 2009Using Poincare parametrization of AdS space, we study totally symmetric arbitrary spin massless fields in AdS space of dimension greater than or equal to four. CFT adapted gauge invariant formulation for such fields is developed. Gauge symmetries are ... More

CFT adapted approach to massless fermionic fields, AdS/CFT, and fermionic conformal fieldsNov 28 2013Dec 10 2013Fermionic totally symmetric arbitrary spin massless fields in AdS space of dimension greater than or equal to four are studied. Using Poincar\'e parametrization of AdS space, CFT adapted gauge invariant formulation for such fields is developed. We demonstrate ... More

The Color-Flavor Locking Phase at T \not =0$Sep 17 1999Nov 03 1999We study the color-flavor locked phase of QCD with three massless quarks at high chemical potential and small non zero temperatures. We make use of the recently introduced effective action to describe such a phase. We obtain the exact order T^2 behaviour ... More

TARCER - A Mathematica program for the reduction of two-loop propagator integralsJan 21 1998TARCER is an implementation of the recurrence algorithm of O.V. Tarasov for the reduction of two-loop propagator integrals with arbitrary masses to a small set of basis integrals. The tensor integral reduction scheme is adapted to moment integrals emerging ... More

Implications of the JHF-Kamioka neutrino oscillation experimentNov 20 2002After quickly reviewing the existing evidence for neutrino oscillations, I summarise the goals and capabilities of the JHF-Kamioka long baseline superbeam experiment. Theoretical implications of what this experiment could potentially discover are then ... More

Automated Checking and Visualization of Interlocks in the ISAC Control SystemNov 09 2001The EPICS based control system of the ISAC radioactive beam facility supervises several sub-systems, which are controlled by PLCs. Most of the devices are protected by non-trivial interlocks, which are implemented with ladder-logic software. Detailed ... More

On the q-analogues of the Zassenhaus formula for dientangling exponential operatorsDec 24 2002Apr 28 2003Katriel, Rasetti and Solomon introduced a $q$-analogue of the Zassenhaus formula written as $e_q^{(A+B)}$ $=$ $e_q^Ae_q^Be_q^{c_2}e_q^{c_3}e_q^{c_4}e_q^{c_5}...$, where $A$ and $B$ are two generally noncommuting operators and $e_q^z$ is the Jackson $q$-exponential, ... More

Casimir-Polder force density between an atom and a conducting wallNov 14 2006In this paper we calculate the Casimir-Polder force density (force per unit area acting on the elements of the surface) on a metallic plate placed in front of a neutral atom. To obtain the force density we use the quantum operator associated to the electromagnetic ... More

An Algorithm for the Microscopic Evaluation of the Coefficients of the Seiberg-Witten PrepotentialAug 25 2002Sep 14 2002A procedure, allowing to calculate the coefficients of the SW prepotential in the framework of the instanton calculus is presented. As a demonstration explicit calculations for 2, 3 and 4- instanton contributions are carried out.

Thermostatistics of extensive and non-extensive systems using generalized entropiesMay 04 2000We describe in detail two numerical simulation methods valid to study systems whose thermostatistics is described by generalized entropies, such as Tsallis. The methods are useful for applications to non-trivial interacting systems with a large number ... More

Extremal size fluctuations in QCD dipole cascadingFeb 07 2005Oct 28 2005This paper has been superseded by hep-ph/0510352.

Free Fields Equations For Space-Time Algebras With Tensorial MomentumDec 25 2001Free field equations, with various spins, for space-time algebras with second-rank tensor (instead of usual vector) momentum are constructed. Similar algebras are appearing in superstring/M theories. The most attention is payed to the gauge invariance ... More

On the Evolution of Scalar Metric Perturbations in an Inflationary CosmologySep 15 1995We further clarify how scalar metric perturbations are amplified in an inflationary cosmology. We first construct a simple, analytic model of an inflationary cosmology in which the expansion scale factor evolves continuously from an inflationary era to ... More

Breakup Reactions of Drip Line NucleiOct 18 2003Oct 28 2003The formal theory of breakup reactions is reviewed. The direct breakup mechanism which is formulated within the framework of the post form distorted wave Born approximation is discussed in detail. In this theory, which requires the information about only ... More

Fluid Limits of Pure Jump Markov Processes: a Practical GuideOct 08 2002Dec 23 2002A rescaled Markov chain converges uniformly in probability to the solution of an ordinary differential equation, under carefully specified assumptions. The presentation is much simpler than those in the outside literature. The result may be used to build ... More

Comments on turbulence theory by Qian and by Edwards and McCombJul 04 2015We reexamine Liouville equation based turbulence theories proposed by Qian {[}Phys. Fluids \textbf{26}, 2098 (1983){]} and Edwards and McComb {[}J. Phys. A: Math. Gen. \textbf{2}, 157 (1969){]}, which are compatible with Kolmogorov spectrum. These theories ... More

Preliminary Investigation of a Waveform Analysis with the WASA and the ACQIRIS Readout ElectronicsJun 28 2013Jul 16 2013The Group for the development of neutron and gamma detectors in the Central Institute of Engineering, Electronics and Analytics (ZEA-2) at Forschungszentrum J\"ulich (FZJ) is developing a fast Anger Camera prototype for improving the rejection of the ... More

Groupoids Determined by Involutive Automorphisms on Semilattices of GroupsMar 01 2015Jun 02 2017We give several characterisations of groupoids determined by involutive automorphisms on semilattices of groups.

Legendrian contact homology and topological entropySep 12 2014May 08 2017In this paper we study the growth rate of a version of Legendrian contact homology, which we call strip Legendrian contact homology, in 3-dimensional contact manifolds and its relation to the topological entropy of Reeb flows. We show that: if for a pair ... More

Skewness, kurtosis and Newton's inequalitySep 11 2013Feb 21 2014We show that an inequality related to Newton's inequality provides one more relation between skewness and kurtosis. This also gives simple and alternative proofs of the bounds for skewness and kurtosis.