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Green function and self-adjoint Laplacians on polyhedral surfacesFeb 08 2019Using Roelcke formula for the Green function, we explicitly construct a basis in the kernel of the adjoint Laplacian on a compact polyhedral surface $X$ and compute the $S$-matrix of $X$ at the zero value of the spectral parameter. We apply these results ... More

Homomorphisms Between Specht Modules of the Ariki Koike AlgebraAug 18 2011In this paper we generalize a theorem due to Lyle, extending its application to the setting of the Ariki-Koike algebra, and in doing so establish an analogue of the kernel intersection theorem. This in turn provides us with a means towards constructing ... More

Four Tails Problems for Dynamical Collapse TheoriesJan 23 2015The primary quantum mechanical equation of motion entails that measurements typically do not have determinate outcomes, but result in superpositions of all possible outcomes. Dynamical collapse theories (e.g. GRW) supplement this equation with a stochastic ... More

Interstellar Probes: The Benefits to Astronomy & AstrophysicsJan 11 2019Long range observations in the field of astronomy have opened up our understanding of the Solar System, the Galaxy and the wider Universe. In this paper we discuss the idea of direct in-situ reconnaissance of nearby stellar systems, using robotic probes. ... More

Mass Additivity and A Priori EntailmentJan 29 2015The principle of mass additivity states that the mass of a composite object is the sum of the masses of its elementary components. Mass additivity is true in Newtonian mechanics but false in special relativity. Physicists have explained why mass additivity ... More

Surgery on postcritically finite rational maps by blowing up an arcDec 18 1995Using Thurston's characterization of postcritically finite rational functions as branched coverings of the sphere to itself, we give a new method of constructing new conformal dynamical systems out of old ones. Let $f(z)$ be a rational map and suppose ... More

Bayesian Learning of Conditional Kernel Mean Embeddings for Automatic Likelihood-Free InferenceMar 03 2019In likelihood-free settings where likelihood evaluations are intractable, approximate Bayesian computation (ABC) addresses the formidable inference task to discover plausible parameters of simulation programs that explain the observations. However, they ... More

A Critical Review on the Assumptions of SETIJan 11 2019The Search for Extraterrestrial Intelligence (SETI) makes certain assumptions which guide all current search programs. To illustrate some, this includes (1) that interstellar flight is not possible (2) that the motivations of interstellar cultures are ... More

On Orbits of Order Ideals of Minuscule Posets II: HomomesySep 27 2015The Fon-Der-Flaass action partitions the order ideals of a poset into disjoint orbits. For a product of two chains, Propp and Roby observed --- across orbits --- the mean cardinality of the order ideals within an orbit to be invariant. That this phenomenon, ... More

Existence of solutions to principal-agent problems under general preferences and non-compact allocation spaceFeb 18 2019We give an existence result for the principal-agent problem with adverse selection under general preferences and non-compact allocation space. The result is mainly based on the fact that the principal can always improve a feasible contract by another ... More

Information, uncertainty and holographic actionJun 09 2016In this short note we show through simple derivation the explicit relation between information flow and the theories of the emergence of space-time and gravity, specifically for Newton's second law of motion. Next, in a rather straightforward derivation ... More

Traversing Knowledge Graphs in Vector SpaceJun 03 2015Aug 19 2015Path queries on a knowledge graph can be used to answer compositional questions such as "What languages are spoken by people living in Lisbon?". However, knowledge graphs often have missing facts (edges) which disrupts path queries. Recent models for ... More

Unsupervised Perceptual Rewards for Imitation LearningDec 20 2016Jun 12 2017Reward function design and exploration time are arguably the biggest obstacles to the deployment of reinforcement learning (RL) agents in the real world. In many real-world tasks, designing a reward function takes considerable hand engineering and often ... More

Hyperparameter Learning for Conditional Kernel Mean Embeddings with Rademacher Complexity BoundsSep 01 2018Nov 08 2018Conditional kernel mean embeddings are nonparametric models that encode conditional expectations in a reproducing kernel Hilbert space. While they provide a flexible and powerful framework for probabilistic inference, their performance is highly dependent ... More

Unsupervised machine learning account of magnetic transitions in the Hubbard modelAug 10 2017We employ several unsupervised machine learning techniques, including autoencoders, random trees embedding, and t-distributed stochastic neighboring ensemble (t-SNE), to reduce the dimensionality of, and therefore classify, raw (auxiliary) spin configurations ... More

A Colored Petri Net Model of Simulation for Performance Evaluation for IEEE 802.22 based NetworkAug 30 2016Sep 20 2016Cognitive Radio is a new concept that allows radio devices access to licensed bands since they do not cause harmful interferences to systems that hold the license of use. The main motivation for the increase of research on Cognitive Radio is the scarcity ... More

Ground state of a resonant two-qubit Rabi model in the ultrastrong coupling regimeMar 14 2013Mar 15 2013We consider a generalized Rabi model formed by two identical qubits interacting with a common oscillator mode. In the near resonance configuration where the oscillator frequency is close to the transition frequency of the qubit, we determine the ground ... More

Transforming Question Answering Datasets Into Natural Language Inference DatasetsSep 09 2018Sep 11 2018Existing datasets for natural language inference (NLI) have propelled research on language understanding. We propose a new method for automatically deriving NLI datasets from the growing abundance of large-scale question answering datasets. Our approach ... More

Bayesian hierarchical modeling of simply connected 2D shapesJan 08 2012Models for distributions of shapes contained within images can be widely used in biomedical applications ranging from tumor tracking for targeted radiation therapy to classifying cells in a blood sample. Our focus is on hierarchical probability models ... More

Probabilistic Model-Agnostic Meta-LearningJun 07 2018Meta-learning for few-shot learning entails acquiring a prior over previous tasks and experiences, such that new tasks be learned from small amounts of data. However, a critical challenge in few-shot learning is task ambiguity: even when a powerful prior ... More

Skew plane partitions according to the $m$th largest and $m$th smallest partsSep 16 2016We extend recent results by G. E. Andrews and G. Simay on the $m$th largest and $m$th smallest parts of a partition to the more general context of skew plane partitions. In order to do this, we introduce new objects called skew plane overpartitions.

Linear and cyclic distance-three labellings of treesSep 06 2013Mar 24 2015Given a finite or infinite graph $G$ and positive integers $\ell, h_1, h_2, h_3$, an $L(h_1, h_2, h_3)$-labelling of $G$ with span $\ell$ is a mapping $f: V(G) \rightarrow \{0, 1, 2, \ldots, \ell\}$ such that, for $i = 1, 2, 3$ and any $u, v \in V(G)$ ... More

Environment-Assisted Quantum State Restoration Via Weak MeasurementApr 15 2014In this paper, a new quantum state restoration scheme is proposed based on the environment-assisted error correction (EAEC) scheme. By introducing a weak measurement reversal (WMR) operation, we shall show how to recover an initial state of a quantum ... More

The totally asymmetric exclusion process with extended objects, a model for protein synthesisFeb 06 2003Sep 16 2003The process of protein synthesis in biological systems resembles a one dimensional driven lattice gas in which the particles have spatial extent, covering more than one lattice site. We expand the well studied Totally Asymmetric Exclusion Process (TASEP), ... More

The effect of environment on the structure of disc galaxiesMay 28 2016Jan 20 2017We study the influence of environment on the structure of disc galaxies, using \texttt{IMFIT} to measure the g- and r-band structural parameters of the surface-brightness profiles for $\sim$700 low-redshift (z$<$0.063) cluster and field disc galaxies ... More

Fabrication of High Aspect Ratio Micro-Penning-Malmberg Gold Plated Silicon Trap ArraysJul 09 2013Acquiring a portable high density charged particles trap might consist of an array of micro-Penning-Malmberg traps (microtraps) with substantially lower end barriers potential than conventional Penning-Malmberg traps [1]. We report on the progress of ... More

ToARist: An Augmented Reality Tourism App created through User-Centred DesignJul 16 2018Through Augmented Reality (AR), virtual graphics can transform the physical world. This offers benefits to mobile tourism, where points of interest (POIs) can be annotated on a smartphone screen. Although several of these applications exist, usability ... More

Bridging the Gap Between Value and Policy Based Reinforcement LearningFeb 28 2017Nov 22 2017We establish a new connection between value and policy based reinforcement learning (RL) based on a relationship between softmax temporal value consistency and policy optimality under entropy regularization. Specifically, we show that softmax consistent ... More

Machine Learning Phases of Strongly Correlated FermionsSep 08 2016Sep 11 2017Machine learning offers an unprecedented perspective for the problem of classifying phases in condensed matter physics. We employ neural-network machine learning techniques to distinguish finite-temperature phases of the strongly correlated fermions on ... More

A Convex Model for Edge-Histogram Specification with Applications to Edge-preserving SmoothingJun 21 2018The goal of edge-histogram specification is to find an image whose edge image has a histogram that matches a given edge-histogram as much as possible. Mignotte has proposed a non-convex model for the problem [M. Mignotte. An energy-based model for the ... More

Deep Learning and Data Assimilation for Real-Time Production Prediction in Natural Gas WellsFeb 14 2018Feb 15 2018The prediction of the gas production from mature gas wells, due to their complex end-of-life behavior, is challenging and crucial for operational decision making. In this paper, we apply a modified deep LSTM model for prediction of the gas flow rates ... More

Chip-level CMP Modeling and Smart Dummy for HDP and Conformal CVD FilmsNov 09 2000Chip-level CMP modeling is investigated to obtain the post-CMP film profile thickness across a die from its design layout file and a few film deposition and CMP parameters. The work covers both HDP and conformal CVD film. The experimental CMP results ... More

Mean field approaches to the totally asymmetric exclusion process with quenched disorder and large particlesMar 19 2004The process of protein synthesis in biological systems resembles a one dimensional driven lattice gas in which the particles (ribosomes) have spatial extent, covering more than one lattice site. Realistic, nonuniform gene sequences lead to quenched disorder ... More

Construction and Evaluation of Hierarchical Parcellation of the Brain using fMRI with PrewhiteningDec 21 2017Feb 07 2018Brain atlases are a ubiquitous tool used for analyzing and interpreting brain imaging datasets. Traditionally, brain atlases divided the brain into regions separated by anatomical landmarks. In the last decade, several attempts have been made to parcellate ... More

Learning a Prior over Intent via Meta-Inverse Reinforcement LearningMay 31 2018Jan 29 2019A significant challenge for the practical application of reinforcement learning in the real world is the need to specify an oracle reward function that correctly defines a task. Inverse reinforcement learning (IRL) seeks to avoid this challenge by instead ... More

The Large-Scale Smoothness of the UniverseApr 06 1998Jun 27 1998New measurements of galaxy clustering and background radiations provide improved constraints on the isotropy and homogeneity of the Universe on large scales. In particular, the angular distribution of radio sources and the X-Ray Background probe density ... More

A Controller-Recognizer Framework: How necessary is recognition for control?Nov 19 2015Feb 09 2016Recently there has been growing interest in building active visual object recognizers, as opposed to the usual passive recognizers which classifies a given static image into a predefined set of object categories. In this paper we propose to generalize ... More

Multi-Commodity Flow with In-Network ProcessingFeb 26 2018Modern networks run "middleboxes" that offer services ranging from network address translation and server load balancing to firewalls, encryption, and compression. In an industry trend known as Network Functions Virtualization (NFV), these middleboxes ... More

Comment on "Experimental Studies of Os^-: Observation of a Bound-Bound Electric Dipole Transition in an Atomic Negative Ion"Aug 07 2012Bilodeau and Haugan [1], using Infrared laser photodetachment spectroscopy, measured the binding energies (BEs) of the ground state (4Fe9/2) and the excited state (4Fe7/2) of the Os^- ion to be 1.07780(12) eV and 0.553(3) eV, respectively. These values ... More

Machine Learning Phases of Strongly Correlated FermionsSep 08 2016Machine learning offers an unprecedented perspective for the problem of classifying phases in condensed matter physics. We employ neural network machine learning techniques to distinguish finite-temperature phases of the strongly-correlated fermions on ... More

Doppler-free, Multi-wavelength Acousto-optic deflector for two-photon addressing arrays of Rb atoms in a Quantum Information ProcessorNov 21 2007We demonstrate a dual wavelength acousto-optic deflector (AOD) designed to deflect two wavelengths to the same angles by driving with two RF frequencies. The AOD is designed as a beam scanner to address two-photon transitions in a two-dimensional array ... More

Local Inhomogeneity in Asymmetric Simple Exclusion Processes with Extended ObjectsOct 01 2003Totally asymmetric simple exclusion processes (TASEP) with particles which occupy more than one lattice site and with a local inhomogeneity far away from the boundaries are investigated. These non-equilibrium processes are relevant for the understanding ... More

Generating Sentences by Editing PrototypesSep 26 2017Sep 07 2018We propose a new generative model of sentences that first samples a prototype sentence from the training corpus and then edits it into a new sentence. Compared to traditional models that generate from scratch either left-to-right or by first sampling ... More

From Language to Programs: Bridging Reinforcement Learning and Maximum Marginal LikelihoodApr 25 2017Our goal is to learn a semantic parser that maps natural language utterances into executable programs when only indirect supervision is available: examples are labeled with the correct execution result, but not the program itself. Consequently, we must ... More

A Retrieve-and-Edit Framework for Predicting Structured OutputsDec 04 2018For the task of generating complex outputs such as source code, editing existing outputs can be easier than generating complex outputs from scratch. With this motivation, we propose an approach that first retrieves a training example based on the input ... More

Methane Oxidation to Methanol without CO2 Emission: Catalysis by Atomic Negative IonsMar 03 2014The catalytic activities of the atomic Y-, Ru-, At-, In-, Pd-, Ag-, Pt-, and Os- ions have been investigated theoretically using the atomic Au- ion as the benchmark for the selective partial oxidation of methane to methanol without CO2 emission. Dispersion-corrected ... More

The effect of environment on the structure of disc galaxiesMay 28 2016Sep 29 2016We study the influence of environment on the structure of disc galaxies, using \texttt{IMFIT} to measure the g- and r-band structural parameters of the surface-brightness profiles for $\sim$700 low-redshift (z$<$0.063) cluster and field disc galaxies ... More

On The Delays In Spiking Neural P SystemsDec 11 2012In this work we extend and improve the results done in a previous work on simulating Spiking Neural P systems (SNP systems in short) with delays using SNP systems without delays. We simulate the former with the latter over sequential, iteration, join, ... More

Time After Time: Notes on Delays In Spiking Neural P SystemsOct 23 2012Spiking Neural P systems, SNP systems for short, are biologically inspired computing devices based on how neurons perform computations. SNP systems use only one type of symbol, the spike, in the computations. Information is encoded in the time differences ... More

Trust-PCL: An Off-Policy Trust Region Method for Continuous ControlJul 06 2017Feb 22 2018Trust region methods, such as TRPO, are often used to stabilize policy optimization algorithms in reinforcement learning (RL). While current trust region strategies are effective for continuous control, they typically require a prohibitively large amount ... More

Mapping Natural Language Commands to Web ElementsAug 28 2018Oct 01 2018The web provides a rich, open-domain environment with textual, structural, and spatial properties. We propose a new task for grounding language in this environment: given a natural language command (e.g., "click on the second article"), choose the correct ... More

Ultracompact Vanadium Dioxide Dual-Mode Plasmonic Waveguide Electroabsorption ModulatorDec 30 2013Subwavelength modulators play an indispensable role in integrated photonic-electronic circuits. Due to weak light-matter interactions, it is always a challenge to develop a modulator with a nanometer scale footprint, low switching energy, low insertion ... More

Electro-optical graphene plasmonic logic gatesMay 07 2014The versatile control of graphene's plasmonic modes via an external gate-voltage inspires us to design efficient electro-optical graphene plasmonic logic gates at the midinfrared wavelengths. We show that these devices are superior to the conventional ... More

Photoionization cross section of 1s orthoexcitons in cuprous oxideJun 18 2014We report measurements of the attenuation of a beam of orthoexciton-polaritons by a photoionizing optical probe. Excitons were prepared in a narrow resonance by two photon absorption of a 1.016 eV, 54 ps pulsed light source in cuprous oxide (Cu2O) at ... More

Third Harmonic Generation in Cuprous Oxide: Efficiency DeterminationDec 27 2013The efficiency of third harmonic generation in cuprous oxide was measured. Intensities followed a non-cubic power law which indicates nonperturbative behavior. Polarization anisotropy of the harmonic generation was demonstrated and related to the third ... More

Brain Computer Interface Technologies in the Coming DecadesNov 05 2012As the proliferation of technology dramatically infiltrates all aspects of modern life, in many ways the world is becoming so dynamic and complex that technological capabilities are overwhelming human capabilities to optimally interact with and leverage ... More

Vacancy Relaxation in Cuprous Oxide (Cu$_{2-x}$O$_{1-y}$)Nov 27 2016Phonons are produced when an excited vacancy in cuprous oxide (Cu$_2$O) relaxes. Time resolved luminescence was used to find the excited copper vacancy (acceptor) and oxygen vacancy (donor) trap levels and lifetimes. It was also used to determine the ... More

A High-Level Reconfigurable Computing Platform Software FrameworksMay 05 2004Reconfigurable computing refers to the use of processors, such as Field Programmable Gate Arrays (FPGAs), that can be modified at the hardware level to take on different processing tasks. A reconfigurable computing platform describes the hardware and ... More

Show, Attend and Tell: Neural Image Caption Generation with Visual AttentionFeb 10 2015Apr 19 2016Inspired by recent work in machine translation and object detection, we introduce an attention based model that automatically learns to describe the content of images. We describe how we can train this model in a deterministic manner using standard backpropagation ... More

Uplink Contention Based SCMA for 5G Radio AccessJul 21 2014Jul 22 2014Fifth generation (5G) wireless networks are expected to support very diverse applications and terminals. Massive connectivity with a large number of devices is an important requirement for 5G networks. Current LTE system is not able to efficiently support ... More

SCMA for Downlink Multiple Access of 5G Wireless NetworksApr 22 2014Sparse code multiple access (SCMA) is a new frequency domain non-orthogonal multiple-access technique which can improve spectral efficiency of wireless radio access. With SCMA, different incoming data streams are directly mapped to codewords of different ... More

Implicit Manifold Learning on Generative Adversarial NetworksOct 30 2017This paper raises an implicit manifold learning perspective in Generative Adversarial Networks (GANs), by studying how the support of the learned distribution, modelled as a submanifold $\mathcal{M}_{\theta}$, perfectly match with $\mathcal{M}_{r}$, the ... More

The near-IR $M_{bh}$ - L and $M_{bh}$ - n relationsOct 05 2011We present near-IR surface photometry (2D-profiling) for a sample of 29 nearby galaxies for which super-massive black hole (SMBH) masses are constrained. The data is derived from the UKIDSS-LASS survey representing a significant improvement in image quality ... More

Atomic Gold and Palladium Anion-Catalysis of Water to Peroxide: Fundamental MechanismJan 10 2012We have performed dispersion-corrected density-functional transition state calculations on atomic Au- and Pd- catalysis of water conversion to peroxide. The Au- ion is found to be an excellent catalyst; however, atomic Pd- has a higher catalytic effect ... More

Resolving Structure in Human Brain Organization: Identifying Mesoscale Organization in Weighted Network RepresentationsDec 20 2013Human brain anatomy and function display a combination of modular and hierarchical organization, suggesting the importance of both cohesive structures and variable resolutions in the facilitation of healthy cognitive processes. However, tools to simultaneously ... More

Mid-infrared Active Graphene Nanoribbon Plasmonic Waveguide DevicesDec 30 2013Doped graphene emerges as a strong contender for active plasmonic material in the mid-infrared wavelengths due to the versatile external-control of its permittivity-function and also its highly-compressed graphene surface plasmon (GSP) wavelength. In ... More

Guaranteed Sufficient Decrease for Variance Reduced Stochastic Gradient DescentMar 20 2017Jun 04 2017In this paper, we propose a novel sufficient decrease technique for variance reduced stochastic gradient descent methods such as SAG, SVRG and SAGA. In order to make sufficient decrease for stochastic optimization, we design a new sufficient decrease ... More

Online Framework for Demand-Responsive Stochastic Route OptimizationFeb 26 2019This study develops an online predictive optimization framework for operating a fleet of autonomous vehicles to enhance mobility in an area, where there exists a latent spatio-temporal distribution of demand for commuting between locations. The proposed ... More

The Galaxy Stellar Mass Function and Low Surface Brightness Galaxies from Core-Collapse SupernovaeJan 15 2019We introduce a method for producing a galaxy sample unbiased by surface brightness and stellar mass, by selecting star-forming galaxies via the positions of core-collapse supernovae (CCSNe). Whilst matching $\sim$2400 supernovae from the SDSS-II Supernova ... More

Massive Machine-type Communications in 5G: Physical and MAC-layer solutionsJun 13 2016Machine-type communications (MTC) are expected to play an essential role within future 5G systems. In the FP7 project METIS, MTC has been further classified into "massive Machine-Type Communication" (mMTC) and "ultra-reliable Machine-Type Communication" ... More

An Actor-Critic Algorithm for Sequence PredictionJul 24 2016Jul 26 2016We present an approach to training neural networks to generate sequences using actor-critic methods from reinforcement learning (RL). Current log-likelihood training methods are limited by the discrepancy between their training and testing modes, as models ... More

Tunable Catalysis of Water to Peroxide with Anionic, Cationic, and Neutral Atomic Au, Ag, Pd, Rh, and OsOct 18 2014Fundamental anionic, cat-ionic, and neutral atomic metal predictions utilizing density functional theory calculations validate the recent discovery identifying the interplay between the resonances and the RT minimum obtained through complex angular momentum ... More

Plasmonic coupled-cavity system for enhancement of surface plasmon localization in plasmonic detectorsDec 30 2013A plasmonic coupled-cavity system, which consists of a quarter-wave coupler cavity, a resonant Fabry-Perot detector nanocavity, and an off-resonant reflector cavity, is used to enhance the localization of surface plasmons in a plasmonic detector. The ... More

An Actor-Critic Algorithm for Sequence PredictionJul 24 2016Mar 03 2017We present an approach to training neural networks to generate sequences using actor-critic methods from reinforcement learning (RL). Current log-likelihood training methods are limited by the discrepancy between their training and testing modes, as models ... More

A two-stage method for spectral-spatial classification of hyperspectral imagesJun 03 2018This paper proposes a novel two-stage method for the classification of hyperspectral images. Pixel-wise classifiers, such as the classical support vector machine (SVM), consider spectral information only; therefore they would generate noisy classification ... More

Vacancy Relaxation in Cuprous Oxide (Cu$_{2-x}$O$_{1-y}$)Nov 27 2016Nov 29 2016Phonons are produced when an excited vacancy in cuprous oxide (Cu$_2$O) relaxes. Time resolved luminescence was used to find the excited copper vacancy (acceptor) and oxygen vacancy (donor) trap levels and lifetimes. It was also used to determine the ... More

On a four-parameters generalization of some special sequencesMay 14 2017We introduce a new four-parameters sequence that simultaneously generalizes some well-known integer sequences, including Fibonacci, Padovan, Jacobsthatl, Pell, and Lucas numbers. Combinatorial interpretations are discussed and many identities for this ... More

Reinforcement Learning on Web Interfaces Using Workflow-Guided ExplorationFeb 24 2018Reinforcement learning (RL) agents improve through trial-and-error, but when reward is sparse and the agent cannot discover successful action sequences, learning stagnates. This has been a notable problem in training deep RL agents to perform web-based ... More

Detection, size, measurement and structural analysis limits for the 2MASS, UKIDSS-LAS & VISTA VIKING surveysNov 07 2013The 2MASS, UKIDSS-LAS and VISTA VIKING surveys have all now observed the GAMA 9hr region in the $K_s$ band. Here we compare the detection rates, photometry, basic size measurements, and single-component GALFIT structural measurements for a sample of 37,591 ... More

Choosing Wavelet Methods, Filters, and Lengths for Functional Brain Network ConstructionDec 23 2015Wavelet methods are widely used to decompose fMRI, EEG, or MEG signals into time series representing neurophysiological activity in fixed frequency bands. Using these time series, one can estimate frequency-band specific functional connectivity between ... More

Design of a Monopole Antenna Based Resonant Nanocavity for Detection of Optical Power from Hybrid Plasmonic WaveguidesDec 31 2013A novel plasmonic waveguide-coupled nanocavity with a monopole antenna is proposed to localize the optical power from a hybrid plasmonic waveguide and subsequently convert it into electrical current. The nanocavity is designed as a Fabry-P\'erot waveguide ... More

Waveguide engineering of graphene's nonlinearityNov 18 2014Graphene has recently been shown to possess giant nonlinearity; however, the utility of this nonlinearity is limited due to high losses and small interaction volume. We show that by performing waveguide engineering to graphene's nonlinearity, we are able ... More

Simulation studies of the behavior of positrons in a microtrap with long aspect ratioDec 31 2012Jul 09 2013The charged particles storage capacity of microtraps (micro-Penning-Malmberg traps) with large length to radius aspect ratios and radii of the order of tens of microns was explored. Simulation studies of the motions of charged particles were conducted ... More

Guaranteed Sufficient Decrease for Stochastic Variance Reduced Gradient OptimizationFeb 26 2018In this paper, we propose a novel sufficient decrease technique for stochastic variance reduced gradient descent methods such as SVRG and SAGA. In order to make sufficient decrease for stochastic optimization, we design a new sufficient decrease criterion, ... More

Fidelity of bacterial translation initiation: a stochastic kinetic modelFeb 06 2018During the initiation stage of protein synthesis, a ribosomal initiation complex (IC) is assembled on a messenger RNA (mRNA) template. In bacteria, the speed and accuracy of this assembly process are regulated by the complementary activities of three ... More

Efficiencies of Aloof-Scattered Electron Beam Excitation of Metal and Graphene PlasmonsJun 03 2015We assessed the efficiencies of surface plasmon excitation by an aloof-scattered electron beam on metals and graphene. Graphene is shown to exhibit high energy transfer efficiencies at very low electron kinetic energy requirements. We show that the exceptional ... More

Photon number statistics uncover the fluctuations in non-equilibrium lattice dynamicsJul 15 2015Jan 14 2016Fluctuations of the atomic positions are at the core of a large class of unusual material properties ranging from quantum para-electricity to high temperature superconductivity. Their measurement in solids is the subject of an intense scientific debate ... More

Non-Parametric Cell-Based Photometric Proxies for Galaxy Morphology: Methodology and Application to the Morphologically-Defined Star Formation -- Stellar Mass Relation of Spiral Galaxies in the Local UniverseNov 19 2013(Abridged) We present a non-parametric cell-based method of selecting highly pure and largely complete samples of spiral galaxies using photometric and structural parameters as provided by standard photometric pipelines and simple shape fitting algorithms, ... More

HSCO$^+$ and DSCO$^+$: a multi-technique approach in the laboratory for the spectroscopy of interstellar ionsOct 22 2018Protonated molecular species have been proven to be abundant in the interstellar gas. This class of molecules is also pivotal for the determination of important physical parameters for the ISM evolution (e.g. gas ionisation fraction) or as tracers of ... More

Gas phase detection and rotational spectroscopy of ethynethiol, HCCSHNov 30 2018We report the gas-phase detection and spectroscopic characterization of ethynethiol ($\mathrm{HCCSH}$), a metastable isomer of thioketene ($\mathrm{H_2C_2S}$) using a combination of Fourier-transform microwave and submillimeter-wave spectroscopies. Several ... More

Evaluation of defects in cuprous oxide through exciton luminescence imagingDec 08 2014The various decay mechanisms of excitons in cuprous oxide (Cu2O) are highly sensitive to defects which can relax selection rules. Here we report cryogenic hyperspectral imaging of exciton luminescence from cuprous oxide crystals grown via the floating ... More

On Using Monolingual Corpora in Neural Machine TranslationMar 11 2015Jun 12 2015Recent work on end-to-end neural network-based architectures for machine translation has shown promising results for En-Fr and En-De translation. Arguably, one of the major factors behind this success has been the availability of high quality parallel ... More

The statistical mechanics of complex signaling networks : nerve growth factor signalingJun 22 2004It is becoming increasingly appreciated that the signal transduction systems used by eukaryotic cells to achieve a variety of essential responses represent highly complex networks rather than simple linear pathways. While significant effort is being made ... More

Highly Efficient Midinfrared On-Chip Electrical Generation of Graphene Plasmons by Inelastic Electron Tunneling ExcitationAug 27 2015Inelastic electron tunneling provides a low-energy pathway for the excitation of surface plasmons and light emission. We theoretically investigate tunnel junctions based on metals and graphene. We show that graphene is potentially a highly efficient material ... More

The diversity of assembly histories leading to disc galaxy formation in a LambdaCDM modelOct 01 2017[Abridged] Typical disc galaxies forming in a LambdaCDM cosmology encounter a violent environment, where they often experience mergers with massive satellites. The fact that disc galaxies are ubiquitous in the local Universe suggests that a quiescent ... More

Insulating-to-Conducting Behavior and Band Profile Across the La0.9Ba0.1MnO3/Nb:SrTiO3 Epitaxial InterfaceSep 30 2017La0.9Ba0.1MnO3 is a ferromagnetic insulator in its bulk form, but exhibits metallicity in thin film form. It has a wide potential in a range of spintronic-related applications, and hence it is critical to understand thickness-dependent electronic structure ... More

Galaxy and Mass Assembly (GAMA): merging galaxies and their propertiesJul 18 2014We derive the close pair fractions and volume merger rates as a function of luminosity and morphology for galaxies in the GAMA survey with -23 < M(r) < -17 at 0.01 < z < 0.22. The merger fraction is about 0.015 at all luminosities (assuming 1/2 of pairs ... More

Pulsed homodyne Gaussian quantum tomography with low detection efficiencyJan 11 2013Feb 19 2014Pulsed homodyne quantum tomography usually requires a high detection efficiency limiting its applicability in quantum optics. Here, it is shown that the presence of low detection efficiency ($<50\%$) does not prevent the tomographic reconstruction of ... More

Galaxy and Mass Assembly (GAMA): maximum likelihood determination of the luminosity function and its evolutionMay 05 2015We describe modifications to the joint stepwise maximum likelihood method of Cole (2011) in order to simultaneously fit the GAMA-II galaxy luminosity function (LF), corrected for radial density variations, and its evolution with redshift. The whole sample ... More

Meta-Dataset: A Dataset of Datasets for Learning to Learn from Few ExamplesMar 07 2019Few-shot classification refers to learning a classifier for new classes given only a few examples. While a plethora of models have emerged to tackle this recently, we find the current procedure and datasets that are used to systematically assess progress ... More