Results for "Marc Peter Deisenroth"

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Expectation Propagation in Gaussian Process Dynamical Systems: Extended VersionJul 12 2012Aug 17 2016Rich and complex time-series data, such as those generated from engineering systems, financial markets, videos or neural recordings, are now a common feature of modern data analysis. Explaining the phenomena underlying these diverse data sets requires ... More
A Probabilistic Perspective on Gaussian Filtering and SmoothingJun 10 2010Jun 08 2011We present a general probabilistic perspective on Gaussian filtering and smoothing. This allows us to show that common approaches to Gaussian filtering/smoothing can be distinguished solely by their methods of computing/approximating the means and covariances ... More
Data-Efficient Reinforcement Learning with Probabilistic Model Predictive ControlJun 20 2017Feb 22 2018Trial-and-error based reinforcement learning (RL) has seen rapid advancements in recent times, especially with the advent of deep neural networks. However, the majority of autonomous RL algorithms require a large number of interactions with the environment. ... More
Design of Experiments for Model Discrimination Hybridising Analytical and Data-Driven ApproachesFeb 12 2018May 31 2018Healthcare companies must submit pharmaceutical drugs or medical devices to regulatory bodies before marketing new technology. Regulatory bodies frequently require transparent and interpretable computational modelling to justify a new healthcare technology, ... More
Hierarchical Mixture-of-Experts Model for Large-Scale Gaussian Process RegressionDec 09 2014We propose a practical and scalable Gaussian process model for large-scale nonlinear probabilistic regression. Our mixture-of-experts model is conceptually simple and hierarchically recombines computations for an overall approximation of a full Gaussian ... More
Design of Experiments for Model Discrimination Hybridising Analytical and Data-Driven ApproachesFeb 12 2018Healthcare companies must submit pharmaceutical drugs or medical devices to regulatory bodies before marketing new technology. Regulatory bodies frequently require transparent and interpretable computational modelling to justify a new healthcare technology, ... More
Distributed Gaussian ProcessesFeb 10 2015May 22 2015To scale Gaussian processes (GPs) to large data sets we introduce the robust Bayesian Committee Machine (rBCM), a practical and scalable product-of-experts model for large-scale distributed GP regression. Unlike state-of-the-art sparse GP approximations, ... More
Meta Reinforcement Learning with Latent Variable Gaussian ProcessesMar 20 2018Jul 07 2018Learning from small data sets is critical in many practical applications where data collection is time consuming or expensive, e.g., robotics, animal experiments or drug design. Meta learning is one way to increase the data efficiency of learning algorithms ... More
Multi-modal filtering for non-linear estimationDec 31 2013Multi-modal densities appear frequently in time series and practical applications. However, they cannot be represented by common state estimators, such as the Extended Kalman Filter (EKF) and the Unscented Kalman Filter (UKF), which additionally suffer ... More
Differentially Private Empirical Risk Minimization with Sparsity-Inducing NormsMay 13 2019Differential privacy is concerned about the prediction quality while measuring the privacy impact on individuals whose information is contained in the data. We consider differentially private risk minimization problems with regularizers that induce structured ... More
Multi-Task Policy SearchJul 02 2013Feb 12 2014Learning policies that generalize across multiple tasks is an important and challenging research topic in reinforcement learning and robotics. Training individual policies for every single potential task is often impractical, especially for continuous ... More
Manifold Gaussian Processes for RegressionFeb 24 2014Apr 11 2016Off-the-shelf Gaussian Process (GP) covariance functions encode smoothness assumptions on the structure of the function to be modeled. To model complex and non-differentiable functions, these smoothness assumptions are often too restrictive. One way to ... More
A Brief Survey of Deep Reinforcement LearningAug 19 2017Sep 28 2017Deep reinforcement learning is poised to revolutionise the field of AI and represents a step towards building autonomous systems with a higher level understanding of the visual world. Currently, deep learning is enabling reinforcement learning to scale ... More
The reparameterization trick for acquisition functionsDec 01 2017Bayesian optimization is a sample-efficient approach to solving global optimization problems. Along with a surrogate model, this approach relies on theoretically motivated value heuristics (acquisition functions) to guide the search process. Maximizing ... More
Maximizing acquisition functions for Bayesian optimizationMay 25 2018Dec 02 2018Bayesian optimization is a sample-efficient approach to global optimization that relies on theoretically motivated value heuristics (acquisition functions) to guide its search process. Fully maximizing acquisition functions produces the Bayes' decision ... More
Neural Embeddings of Graphs in Hyperbolic SpaceMay 29 2017Neural embeddings have been used with great success in Natural Language Processing (NLP). They provide compact representations that encapsulate word similarity and attain state-of-the-art performance in a range of linguistic tasks. The success of neural ... More
Gaussian Processes for Data-Efficient Learning in Robotics and ControlFeb 10 2015Oct 10 2017Autonomous learning has been a promising direction in control and robotics for more than a decade since data-driven learning allows to reduce the amount of engineering knowledge, which is otherwise required. However, autonomous reinforcement learning ... More
Gaussian Processes for Data-Efficient Learning in Robotics and ControlFeb 10 2015Autonomous learning has been a promising direction in control and robotics for more than a decade since data-driven learning allows to reduce the amount of engineering knowledge, which is otherwise required. However, autonomous reinforcement learning ... More
Probabilistic Inference of Twitter Users' Age based on What They FollowJan 18 2016Feb 24 2017Twitter provides an open and rich source of data for studying human behaviour at scale and is widely used in social and network sciences. However, a major criticism of Twitter data is that demographic information is largely absent. Enhancing Twitter data ... More
Detecting the Age of Twitter UsersJan 18 2016Twitter provides an extremely rich and open source of data for studying human behaviour at scale. It has been used to advance our understanding of social network structure, the viral flow of information and how new ideas develop. Enriching Twitter with ... More
From Pixels to Torques: Policy Learning with Deep Dynamical ModelsFeb 08 2015Jun 18 2015Data-efficient learning in continuous state-action spaces using very high-dimensional observations remains a key challenge in developing fully autonomous systems. In this paper, we consider one instance of this challenge, the pixels to torques problem, ... More
Deep Gaussian Processes with Importance-Weighted Variational InferenceMay 14 2019Deep Gaussian processes (DGPs) can model complex marginal densities as well as complex mappings. Non-Gaussian marginals are essential for modelling real-world data, and can be generated from the DGP by incorporating uncorrelated variables to the model. ... More
Learning deep dynamical models from image pixelsOct 28 2014Modeling dynamical systems is important in many disciplines, e.g., control, robotics, or neurotechnology. Commonly the state of these systems is not directly observed, but only available through noisy and potentially high-dimensional observations. In ... More
Doubly Stochastic Variational Inference for Deep Gaussian ProcessesMay 24 2017Nov 13 2017Gaussian processes (GPs) are a good choice for function approximation as they are flexible, robust to over-fitting, and provide well-calibrated predictive uncertainty. Deep Gaussian processes (DGPs) are multi-layer generalisations of GPs, but inference ... More
GPdoemd: a Python package for design of experiments for model discriminationOct 05 2018Jan 14 2019Model discrimination identifies a mathematical model that usefully explains and predicts a given system's behaviour. Researchers will often have several models, i.e.\ hypotheses, about an underlying system mechanism, but insufficient experimental data ... More
Bayesian Optimization with Dimension Scheduling: Application to Biological SystemsNov 17 2015Bayesian Optimization (BO) is a data-efficient method for global black-box optimization of an expensive-to-evaluate fitness function. BO typically assumes that computation cost of BO is cheap, but experiments are time consuming or costly. In practice, ... More
Data-Efficient Learning of Feedback Policies from Image Pixels using Deep Dynamical ModelsOct 08 2015Oct 09 2015Data-efficient reinforcement learning (RL) in continuous state-action spaces using very high-dimensional observations remains a key challenge in developing fully autonomous systems. We consider a particularly important instance of this challenge, the ... More
Identification of Gaussian Process State Space ModelsMay 30 2017Nov 07 2017The Gaussian process state space model (GPSSM) is a non-linear dynamical system, where unknown transition and/or measurement mappings are described by GPs. Most research in GPSSMs has focussed on the state estimation problem, i.e., computing a posterior ... More
Accelerating the BSM interpretation of LHC data with machine learningNov 08 2016The interpretation of Large Hadron Collider (LHC) data in the framework of Beyond the Standard Model (BSM) theories is hampered by the need to run computationally expensive event generators and detector simulators. Performing statistically convergent ... More
Real-Time Community Detection in Large Social Networks on a LaptopJan 15 2016Sep 04 2016For a broad range of research, governmental and commercial applications it is important to understand the allegiances, communities and structure of key players in society. One promising direction towards extracting this information is to exploit the rich ... More
Customer Lifetime Value Prediction Using EmbeddingsMar 07 2017Jul 06 2017We describe the Customer LifeTime Value (CLTV) prediction system deployed at ASOS.com, a global online fashion retailer. CLTV prediction is an important problem in e-commerce where an accurate estimate of future value allows retailers to effectively allocate ... More
GPdoemd: a Python package for design of experiments for model discriminationOct 05 2018Mar 08 2019Model discrimination identifies a mathematical model that usefully explains and predicts a given system's behaviour. Researchers will often have several models, i.e. hypotheses, about an underlying system mechanism, but insufficient experimental data ... More
Robust Filtering and Smoothing with Gaussian ProcessesMar 20 2012We propose a principled algorithm for robust Bayesian filtering and smoothing in nonlinear stochastic dynamic systems when both the transition function and the measurement function are described by non-parametric Gaussian process (GP) models. GPs are ... More
Variational Gaussian Process Auto-Encoder for Ordinal Prediction of Facial Action UnitsAug 16 2016Sep 05 2016We address the task of simultaneous feature fusion and modeling of discrete ordinal outputs. We propose a novel Gaussian process(GP) auto-encoder modeling approach. In particular, we introduce GP encoders to project multiple observed features onto a latent ... More
Orthogonally Decoupled Variational Gaussian ProcessesSep 24 2018Jan 15 2019Gaussian processes (GPs) provide a powerful non-parametric framework for reasoning over functions. Despite appealing theory, its superlinear computational and memory complexities have presented a long-standing challenge. State-of-the-art sparse variational ... More
High-Dimensional Bayesian Optimization with Manifold Gaussian ProcessesFeb 27 2019Bayesian optimization (BO) is a powerful approach for seeking the global optimum of expensive black-box functions and has proven successful for fine tuning hyper-parameters of machine learning models. The Bayesian optimization routine involves learning ... More
High-Dimensional Bayesian Optimization with Manifold Gaussian ProcessesFeb 27 2019May 01 2019Bayesian optimization (BO) is a powerful approach for seeking the global optimum of expensive black-box functions and has proven successful for fine tuning hyper-parameters of machine learning models. The Bayesian optimization routine involves learning ... More
Gaussian Process Domain Experts for Model Adaptation in Facial Behavior AnalysisApr 11 2016May 02 2016We present a novel approach for supervised domain adaptation that is based upon the probabilistic framework of Gaussian processes (GPs). Specifically, we introduce domain-specific GPs as local experts for facial expression classification from face images. ... More
Gaussian Process Conditional Density EstimationOct 30 2018Conditional Density Estimation (CDE) models deal with estimating conditional distributions. The conditions imposed on the distribution are the inputs of the model. CDE is a challenging task as there is a fundamental trade-off between model complexity, ... More
Degree Bounds on Homology and a Conjecture of DerksenOct 01 2014Harm Derksen made a conjecture concerning degree bounds for the syzygies of rings of polynomial invariants in the non-modular case. We provide counterexamples to this conjecture, but also prove a slightly weakened version. We also prove some general results ... More
On tensor factorizations of Hopf algebrasOct 23 2014We prove a variety results on tensor product factorizations of finite dimensional Hopf algebras (more generally Hopf algebras satisfying chain conditions in suitable braided categories). The results are analogs of well-known results on direct product ... More
Perturbations of Extremal Kerr Spacetime: Analytic Framework and Late-time TailsJan 17 2018We develop a complete and systematic analytical approach to field perturbations of the extreme Kerr spacetime based on the formalism of Mano, Suzuki, and Takasugi (MST) for the Teukolsky equation. We give analytical expressions for the radial solutions ... More
Bouncing alternatives to inflationMar 23 2015Although the inflationary paradigm is the most widely accepted explanation for the current cosmological observations, it does not necessarily correspond to what actually happened in the early stages of our Universe. To decide on this issue, two paths ... More
Unstable Attractors: Existence and Robustness in Networks of Oscillators With Delayed Pulse CouplingJan 17 2005We consider unstable attractors; Milnor attractors $A$ such that, for some neighbourhood $U$ of $A$, almost all initial conditions leave $U$. Previous research strongly suggests that unstable attractors exist and even occur robustly (i.e. for open sets ... More
Kinematic Morphing Networks for Manipulation Skill TransferMar 05 2018The transfer of a robot skill between different geometric environments is non-trivial since a wide variety of environments exists, sensor observations as well as robot motions are high-dimensional, and the environment might only be partially observed. ... More
MIS: a MIRIAD Interferometry Singledish toolkitFeb 06 2012Building on the "drPACS" contribution at ADASS XX of a simple Unix pipeline infrastructure, we implemented a pipeline toolkit using the package MIRIAD to combine Interferometric and Single Dish data (MIS). This was prompted by our observations made with ... More
Knots with only two strict essential surfacesApr 09 2004Dec 23 2004We consider irreducible 3-manifolds M that arise as knot complements in closed 3-manifolds and that contain at most two connected strict essential surfaces. The results in the paper relate the boundary slopes of the two surfaces to their genera and numbers ... More
Betti numbers and injectivity radiiJan 30 2009We give lower bounds on the maximal injectivity radius for a closed orientable hyperbolic 3-manifold M with first Betti number 2, under some additional topological hypotheses. A corollary of the main result is that if M has first Betti number 2 and contains ... More
Advancing Bayesian Optimization: The Mixed-Global-Local (MGL) Kernel and Length-Scale Cool DownDec 09 2016Bayesian Optimization (BO) has become a core method for solving expensive black-box optimization problems. While much research focussed on the choice of the acquisition function, we focus on online length-scale adaption and the choice of kernel function. ... More
Margulis numbers for Haken manifoldsJun 17 2010Jun 27 2011For every closed hyperbolic Haken 3-manifold and, more generally, for any hyperbolic 3-manifold M which is homeomorphic to the interior of a Haken manifold, the number 0.286 is a Margulis number. If M has non-zero first Betti number, or if M is closed ... More
Singular surfaces, mod 2 homology, and hyperbolic volume, IIJan 24 2007Oct 19 2010If M is a closed simple 3-manifold whose fundamental group contains a genus-g surface group for some g>1, and if the dimension of H_1(M;Z_2) is at least max(3g-1,6), we show that M contains a closed, incompressible surface of genus at most g. This improves ... More
Four-free groups and hyperbolic geometryJun 06 2008Sep 15 2011We give new information about the geometry of closed, orientable hyperbolic 3-manifolds with 4-free fundamental group. As an application we show that such a manifold has volume greater than 3.44. This is in turn used to show that if M is a closed orientable ... More
Volume and homology of one-cusped hyperbolic 3-manifoldsJul 29 2007Oct 28 2008Let M be a complete, finite-volume, orientable hyperbolic manifold having exactly one cusp. If we assume that pi_1(M) has no subgroup isomorphic to a genus-2 surface group, and that either (a) H_1(M;Z_p) has dimension at least 5 for some prime p, or (b) ... More
The Relaxed Square PropertyJul 11 2014Graph products are characterized by the existence of non-trivial equivalence relations on the edge set of a graph that satisfy a so-called square property. We investigate here a generalization, termed RSP-relations. The class of graphs with non-trivial ... More
Square Property, Equitable Partitions, and Product-like GraphsJan 29 2013Sep 02 2013Equivalence relations on the edge set of a graph $G$ that satisfy restrictive conditions on chordless squares play a crucial role in the theory of Cartesian graph products and graph bundles. We show here that such relations in a natural way induce equitable ... More
Ramanujan duals and automorphic spectrumApr 01 1992We introduce the notion of the automorphic dual of a matrix algebraic group defined over $Q$. This is the part of the unitary dual that corresponds to arithmetic spectrum. Basic functorial properties of this set are derived and used both to deduce arithmetic ... More
Non-Gaussianity excess problem in classical bouncing cosmologiesJun 16 2014Jan 13 2015The simplest possible classical model leading to a cosmological bounce is examined in the light of the non-Gaussianities it can generate. Concentrating solely on the transition between contraction and expansion, and assuming initially purely Gaussian ... More
Doping Dependence of Gap Inhomogeneities at Bi$_{2}$Sr$_{2}$CaCu$_{2}$O$_{8+δ}$ SurfacesOct 22 2011We study the inhomogeneity of the electronic pairing gap observed by STM near the surface of Bi$_{2}$Sr$_{2}$CaCu$_{2}$O$_{8+\delta}$ to be correlated with interstitial O defects. We treat the problem in a slave boson mean field theory of a disordered ... More
Soft Walls in Dynamic AdS/QCD and the Techni-dilatonAug 26 2015Dynamic AdS/QCD is a modification of AdS/QCD that includes the running of the anomalous dimension of the q-bar q quark bilinear and in which the generation of the constituent quark mass plays the role of an IR wall. The model allows one to move away smoothly ... More
Emulating dynamic non-linear simulators using Gaussian processesFeb 21 2018Feb 18 2019The dynamic emulation of non-linear deterministic computer codes where the output is a time series, possibly multivariate, is examined. Such computer models simulate the evolution of some real-world phenomenon over time, for example models of the climate ... More
Singular surfaces, mod 2 homology, and hyperbolic volume, IJun 20 2005Feb 03 2008This paper contains a purely topological theorem and a geometric application. The topological theorem states that if M is a simple closed orientable 3-manifold such that \pi_1(M) contains a genus g surface group and H_1(M;Z/2Z) has rank at least 4g-1 ... More
A classical bounce: constraints and consequencesFeb 08 2008Jun 18 2008We perform a detailed investigation of the simplest possible cosmological model in which a bounce can occur, namely that where the dynamics is led by a simple massive scalar field in a general self-interacting potential and a background spacetime with ... More
Emulating dynamic non-linear simulators using Gaussian processesFeb 21 2018Jun 09 2018In this paper, we examine the emulation of non-linear deterministic computer codes where the output is a time series, possibly multivariate. Such computer models simulate the evolution of some real-world phenomena over time, for example models of the ... More
$Λ_{\bar{\textrm{MS}}}^{(n_f=2)}$ from a momentum space analysis of the quark-antiquark static potentialJul 28 2014Sep 30 2014We determine $\Lambda_{\bar{\textrm{MS}}}^{(n_f=2)}$ by fitting perturbative expressions for the quark-antiquark static potential to lattice results for QCD with $n_f=2$ dynamical quark flavors. To this end we use the perturbative static potential at ... More
The Mathematics of Xenology: Di-cographs, Symbolic Ultrametrics, 2-structures and Tree-representable Systems of Binary RelationsMar 08 2016The concepts of orthology, paralogy, and xenology play a key role in molecular evolution. Orthology and paralogy distinguish whether a pair of genes originated by speciation or duplication. The corresponding binary relations on a set of genes form complementary ... More
Uncertainty Quantification for PDEs with Anisotropic Random DiffusionJul 19 2016In this article, we consider elliptic diffusion problems with an anisotropic random diffusion coefficient. We model the notable direction in terms of a random vector field and derive regularity results for the solution's dependence on the random parameter. ... More
A Comparison of Models for Uncertain Network DesignJan 11 2019To solve a real-world problem, the modeler usually needs to make a trade-off between model complexity and usefulness. This is also true for robust optimization, where a wide range of models for uncertainty, so-called uncertainty sets, have been proposed. ... More
Testing Alignment of Node Attributes with Network Structure Through Label PropagationMay 18 2018Attributed network data is becoming increasingly common across fields, as we are often equipped with information about nodes in addition to their pairwise connectivity patterns. This extra information can manifest as a classification, or as a multidimensional ... More
Conductance fluctuations and boundary conditionsJun 13 2001The conductance fluctuations for various types for two-- and three--dimensional disordered systems with hard wall and periodic boundary conditions are studied, all the way from the ballistic (metallic) regime to the localized regime. It is shown that ... More
Production of non-gaussianities in a bouncing phaseMar 31 2014Jul 08 2014We compute the level of non-gaussianities produced by a cosmological bouncing phase in the minimal non-singular setup that lies within the context of General Relativity when the matter content consists of a simple scalar field with a standard kinetic ... More
$b\bar b u\bar d$ four-quark systems in the Born-Oppenheimer approximation: prospects and challengesSep 11 2017We summarize previous work on $\bar b \bar bud$ four-quark systems in the Born-Oppenheimer approximation and discuss first steps towards an extension to the theoretically more challenging $b\bar b u\bar d$ system. Strategies to identify a possibly existing ... More
Physical properties of a very diffuse HI structure at high Galactic latitudeFeb 28 2007The main goal of this analysis is to present a new method to estimate the physical properties of diffuse cloud of atomic hydrogen observed at high Galactic latitude. This method, based on a comparison of the observations with fractional Brownian motion ... More
How to make Dupire's local volatility work with jumpsFeb 22 2013There are several (mathematical) reasons why Dupire's formula fails in the non-diffusion setting. And yet, in practice, ad-hoc preconditioning of the option data works reasonably well. In this note we attempt to explain why. In particular, we propose ... More
Symmetry, dimension and the distribution of the conductance at the mobility edgeApr 20 2001The probability distribution of the conductance at the mobility edge, $p_c(g)$, in different universality classes and dimensions is investigated numerically for a variety of random systems. It is shown that $p_c(g)$ is universal for systems of given symmetry, ... More
Coupled currents in cosmic stringsMar 25 2009We first examine the microstructure of a cosmic string endowed with two simple Abelian currents. This microstructure depends on two state parameters. We then provide the macroscopic description of such a string and show that it depends on an additional ... More
The probability distribution of the conductance in anisotropic systemsMar 28 2001We investigate the probability distribution $p(g)$ of the conductance $g$ in anisotropic two-dimensional systems. The scaling procedure applicable to mapping the conductance distributions of localized anisotropic systems to the corresponding isotropic ... More
First integrals and parametric solutions for equations integrable through Lie symmetriesApr 01 2001We present here the explicit parametric solutions of second order differential equations invariant under time translation and rescaling and third order differential equations invariant under time translation and the two homogeneity symmetries. The computation ... More
Horizon Instability of Extremal Kerr Black Holes: Nonaxisymmetric Modes and Enhanced Growth RateJun 27 2016Jul 11 2016We show that the horizon instability of the extremal Kerr black hole is associated with a singular branch point in the Green function at the superradiant bound frequency. We study generic initial data supported away from the horizon and find an enhanced ... More
Reciprocal Best Match GraphsMar 19 2019Reciprocal best matches play an important role in numerous applications in computational biology, in particular as the basis of many widely used tools for orthology assessment. Nevertheless, very little is known about their mathematical structure. Here, ... More
Reciprocal Best Match GraphsMar 19 2019Apr 11 2019Reciprocal best matches play an important role in numerous applications in computational biology, in particular as the basis of many widely used tools for orthology assessment. Nevertheless, very little is known about their mathematical structure. Here, ... More
Reciprocal Best Match GraphsMar 19 2019Apr 30 2019Reciprocal best matches play an important role in numerous applications in computational biology, in particular as the basis of many widely used tools for orthology assessment. Nevertheless, very little is known about their mathematical structure. Here, ... More
Incompressible surfaces, hyperbolic volume, Heegaard genus and homologyJul 29 2008Jan 07 2009We show that if M is a complete, finite-volume, hyperbolic 3-manifold having exactly one cusp, and if H_1(M;Z_2) has dimension at least 6, then M has volume greater than 5.06. We also show that if M is a closed, orientable hyperbolic 3-manifold such that ... More
Dehn surgery, homology and hyperbolic volumeAug 11 2005Jul 06 2009If a closed, orientable hyperbolic 3--manifold M has volume at most 1.22 then H_1(M;Z_p) has dimension at most 2 for every prime p not 2 or 7, and H_1(M;Z_2) and H_1(M;Z_7) have dimension at most 3. The proof combines several deep results about hyperbolic ... More
Dark-Matter Decays and Self-Gravitating HalosMar 01 2010May 26 2010We consider models in which a dark-matter particle decays to a slightly less massive daughter particle and a noninteracting massless particle. The decay gives the daughter particle a small velocity kick. Self-gravitating dark-matter halos that have a ... More
X-ray flashes and X-ray rich Gamma Ray BurstsNov 13 2001X-ray flashes are detected in the Wide Field Cameras on BeppoSAX in the energy range 2-25 keV as bright X-ray sources lasting of the order of minutes, but remaining undetected in the Gamma Ray Bursts Monitor on BeppoSAX. They have properties very similar ... More
Coupled Yu-Shiba-Rusinov states in molecular dimers on NbSe$_2$Jan 12 2017Nov 30 2017Magnetic impurities have a dramatic effect on superconductivity by breaking the time-reversal symmetry and inducing so-called Yu-Shiba-Rusinov (YSR) low energy bound states within the superconducting gap. The spatial extent of YSR states is greatly enhanced ... More
Graviton production in anti-de Sitter braneworld cosmology: A fully consistent treatment of the boundary conditionJan 23 2009Jul 16 2009In recent work by two of us, [Durrer & Ruser, PRL 99, 071601 (2007); Ruser & Durrer PRD 76, 104014 (2007)], graviton production due to a moving spacetime boundary (braneworld) in a five dimensional bulk has been considered. In the same way as the presence ... More
BB interactions with static bottom quarks from Lattice QCDOct 12 2015The isospin, spin and parity dependent potential of a pair of $B$ mesons is computed using Wilson twisted mass lattice QCD with two flavours of degenerate dynamical quarks. The $B$ meson is addressed in the static-light approximation, i.e.\ the $b$ quarks ... More
STE-QUEST Mission and System Design - Overview after completion of Phase-ASep 30 2013Jan 25 2014STE-QUEST is a fundamental science mission which is considered for launch within the Cosmic Vision programme of the European Space Agency (ESA). Its main scientific objectives relate to probing various aspects of Einstein's theory of general relativity ... More
Characteristic subsurfaces and Dehn fillingNov 25 2002Let M be a compact, orientable, irreducible, atoroidal 3-manifold with boundary an incompressible torus. Techniques based on the characteristic submanifold theory are used to bound the intersection number of two slopes \alpha and \beta on the boundary ... More
Lazy Model Expansion: Interleaving Grounding with SearchFeb 27 2014Feb 03 2015Finding satisfying assignments for the variables involved in a set of constraints can be cast as a (bounded) model generation problem: search for (bounded) models of a theory in some logic. The state-of-the-art approach for bounded model generation for ... More
$u d \bar{b} \bar{b}$ tetraquark resonances with lattice QCD potentials and the Born-Oppenheimer approximationApr 07 2017Oct 10 2017We study tetraquark resonances with lattice QCD potentials computed for a static bbar bbar pair in the presence of two lighter quarks u d, the Born-Oppenheimer approximation and the emergent wave method. As a proof of concept we focus on the system with ... More
Investigation of $B\bar B$ four-quark systems using lattice QCDFeb 24 2016Feb 29 2016We investigate $B \bar B$ systems by computing potentials of two static quarks in the presence of two quarks of finite mass using lattice QCD. By solving the Schr\"odinger equation we check whether these potentials are sufficiently attractive to host ... More
Exploring possibly existing $q q \bar b \bar b$ tetraquark states with $q q = ud, ss, cc$Aug 03 2015We compute potentials of two static antiquarks in the presence of two quarks $qq$ of finite mass using lattice QCD. In a second step we solve the Schr\"odinger equation, to determine, whether the resulting potentials are sufficiently attractive to host ... More
A Short Note on Undirected Fitch GraphsDec 05 2017The symmetric version of Fitch's xenology relation coincides with class of complete multipartite graph and thus cannot convey any non-trivial phylogenetic information.
Shaking a Box of SandMar 03 2001Oct 16 2001We present a simple model of a vibrated box of sand, and discuss its dynamics in terms of two parameters reflecting static and dynamic disorder respectively. The fluidised, intermediate and frozen (`glassy') dynamical regimes are extensively probed by ... More
Propagation front of correlations in an interacting Bose gasFeb 24 2012May 21 2012We analyze the quench dynamics of a one-dimensional bosonic Mott insulator and focus on the time evolution of density correlations. For these we identify a pronounced propagation front, the velocity of which, once correctly extrapolated at large distances, ... More
Braneworlds, graviton production, dynamical Casimir effectFeb 05 2009If our Universe is a 3+1 brane in a warped 4+1 dimensional bulk so that its expansion can be understood as the motion of the brane in the bulk, the time dependence of the boundary conditions for arbitrary bulk fields can lead to particle creation via ... More
Lattice QCD study of heavy-heavy-light-light tetraquark candidatesSep 01 2016We investigate heavy-light four-quark systems $ud\bar b \bar b$ with bottom quarks of finite mass which are treated in the framework of NRQCD. We focus on $I(J^P)=0(1^+)$, where we recently found evidence for the existence of a tetraquark state using ... More
Tetraquark resonances computed with static lattice QCD potentials and scattering theoryNov 23 2017We study tetraquark resonances with lattice QCD potentials computed for two static quarks and two dynamical quarks, the Born-Oppenheimer approximation and the emergent wave method of scattering theory. As a proof of concept we focus on systems with isospin ... More