cometadata/datacite-rtg-text-other-reclassification-records huggingface dataset:
Extended phase space thermodynamics of black holes: A study in Einstein's gravity and beyond
Creators: name: Bhattacharya, Krishnakanta
Publisher: name: arXiv
Year: 2021
Subjects: subject: General Relativity and Quantum Cosmology (gr-qc)
subject: High Energy Physics - Theory (hep-th)
subject: FOS: Physical sciences

description: In the extended phase space approach, one can define thermodynamic pressure and volume that gives rise to the van der Waals type phase transition for black holes. For Einstein's GR, the expressions of these quantities are unanimously accepted. Of late, the van der Waals phase transition in black holes has been found in modified theories of gravity as well, such as the $f(R)$ gravity and the scalar-tensor gravity. However, in the case of these modified theories of gravity, the expression of pressure (and, hence, volume) is not uniquely determined. In addition, for these modified theories, the extended phase space thermodynamics has not been studied extensively, especially in a covariant way. Since both the scalar-tensor and the $f(R)$ gravity can be discussed in the two conformally connected frames (the Jordan and the Einstein frame respectively), the arbitrariness in the expression of pressure, will act upon the equivalence of the thermodynamic parameters in the two frames. We highlight these issues in the paper. Before that, in Einstein's gravity (GR), we obtain a general expression of the equilibrium state version of first law and the Smarr-like formula from the Einstein's equation for a general static and spherically symmetric (SSS) metric. Here we directly obtain the first law as well as the Smarr-like formula in GR in terms of the parameters present in the metric (such as mass, charge \textit{etc.}). This study also shows how the extended phase space is formulated (by considering the cosmological constant as variable) and, also shows why the cosmological constant plays the role of thermodynamic pressure in GR in extended phase space. Moreover, obtaining the Smarr formula from the Einstein's equation for the SSS metric suggests that this dynamical equation encodes more information on BH thermodynamics than what has been anticipated before.
description: Modified version, To appear in NPB
Photoluminescence and charge transfer in the prototypical 2D/3D semiconductor heterostructure MoS$_2$/GaAs
Creators: name: Rojas-Lopez, Rafael R.
name: Brant, Juliana C.
name: Ramos, Maíra S. O.
name: Castro, Túlio H. L. G.
name: Guimarães, Marcos H. D.
name: Neves, Bernardo R. A.
name: Guimarães, Paulo S. S.
Publisher: name: arXiv
Year: 2021
Subjects: subject: Mesoscale and Nanoscale Physics (cond-mat.mes-hall)
subject: FOS: Physical sciences

description: The new generation of two-dimensional (2D) materials has shown a broad range of applications for optical and electronic devices. Understanding the properties of these materials when integrated with the more traditional three-dimensional (3D) semiconductors is an important challenge for the implementation of ultra-thin electronic devices. Recent observations have shown that by combining MoS$_2$ with GaAs it is possible to develop high quality photodetectors and solar cells. Here, we present a study of the effects of intrinsic GaAs, p-doped GaAs, and n-doped GaAs substrates on the photoluminescence of monolayer MoS$_2$. We observe a decrease of an order of magnitude in the emission intensity of MoS$_2$ in all MoS$_2$/GaAs heterojunctions, when compared to a control sample consisting of a MoS$_2$ monolayer isolated from GaAs by a few layers of hexagonal boron nitride. We also see a dependence of the trion to A-exciton emission ratio in the photoluminescence spectra on the type of substrate, a dependence that we relate to the static charge exchange between MoS$_2$ and the substrates when the junction is formed. Scanning Kelvin probe microscopy measurements of the heterojunctions suggest type-I band alignments, so that excitons generated on the MoS$_2$ monolayer will be transferred to the GaAs substrate. Our results shed light on the charge exchange leading to band offsets in 2D/3D heterojunctions which play a central role in the understanding and further improvement of electronic devices.
description: Accepted in Applied Physics Letters
Archetypes of Supply Chain Analytics Initiatives—An Exploratory Study
Creators: name: Herden, Tino T.
name: Bunzel, Steffen
Publisher: name: Technische Universität Berlin
Year: 2018
Subjects: subject: 380 Handel, Kommunikation, Verkehr
subject: supply chain analytics
subject: business analytics
subject: cluster analysis

description: While Big Data and Analytics are arguably rising stars of competitive advantage, their application is often presented and investigated as an overall approach. A plethora of methods and technologies combined with a variety of objectives creates a barrier for managers to decide how to act, while researchers investigating the impact of Analytics oftentimes neglect this complexity when generalizing their results. Based on a cluster analysis applied to 46 case studies of Supply Chain Analytics (SCA) we propose 6 archetypes of initiatives in SCA to provide orientation for managers as means to overcome barriers and build competitive advantage. Further, the derived archetypes present a distinction of SCA for researchers seeking to investigate the effects of SCA on organizational performance.
Recent Advances in Reinforcement Learning in Finance
Creators: name: Hambly, Ben
name: Xu, Renyuan
name: Yang, Huining
Publisher: name: arXiv
Year: 2021
Subjects: subject: Mathematical Finance (q-fin.MF)
subject: Machine Learning (cs.LG)
subject: Computational Finance (q-fin.CP)
subject: Trading and Market Microstructure (q-fin.TR)
subject: FOS: Economics and business
subject: FOS: Computer and information sciences

description: The rapid changes in the finance industry due to the increasing amount of data have revolutionized the techniques on data processing and data analysis and brought new theoretical and computational challenges. In contrast to classical stochastic control theory and other analytical approaches for solving financial decision-making problems that heavily reply on model assumptions, new developments from reinforcement learning (RL) are able to make full use of the large amount of financial data with fewer model assumptions and to improve decisions in complex financial environments. This survey paper aims to review the recent developments and use of RL approaches in finance. We give an introduction to Markov decision processes, which is the setting for many of the commonly used RL approaches. Various algorithms are then introduced with a focus on value and policy based methods that do not require any model assumptions. Connections are made with neural networks to extend the framework to encompass deep RL algorithms. Our survey concludes by discussing the application of these RL algorithms in a variety of decision-making problems in finance, including optimal execution, portfolio optimization, option pricing and hedging, market making, smart order routing, and robo-advising.
description: 60 pages, 1 figure
Quantum key distribution with untrusted detectors
Creators: name: Gonzalez, P.
name: Rebon, L.
name: da Silva, T. Ferreira
name: Figueroa, M.
name: Saavedra, C.
name: Curty, M.
name: Lima, G.
name: Xavier, G. B.
name: Nogueira, W. A. T.
Publisher: name: arXiv
Year: 2014
Subjects: subject: Quantum Physics (quant-ph)
subject: FOS: Physical sciences

description: Side-channel attacks currently constitute the main challenge for quantum key distribution (QKD) to bridge theory with practice. So far two main approaches have been introduced to address this problem, (full) device-independent QKD and measurement-device-independent QKD. Here we present a third solution that might exceed the performance and practicality of the previous two in circumventing detector side-channel attacks, which arguably is the most hazardous part of QKD implementations. Our proposal has, however, one main requirement: the legitimate users of the system need to ensure that their labs do not leak any unwanted information to the outside. The security in the low-loss regime is guaranteed, while in the high-loss regime we already prove its robustness against some eavesdropping strategies.
description: 9 pages, 4 figures. Matches published version
Lexical semantics enhanced neural word embeddings
Creators: name: Yang, Dongqiang
name: Li, Ning
name: Zou, Li
name: Ma, Hongwei
Publisher: name: arXiv
Year: 2022
Subjects: subject: Computation and Language (cs.CL)
subject: FOS: Computer and information sciences

description: Current breakthroughs in natural language processing have benefited dramatically from neural language models, through which distributional semantics can leverage neural data representations to facilitate downstream applications. Since neural embeddings use context prediction on word co-occurrences to yield dense vectors, they are inevitably prone to capture more semantic association than semantic similarity. To improve vector space models in deriving semantic similarity, we post-process neural word embeddings through deep metric learning, through which we can inject lexical-semantic relations, including syn/antonymy and hypo/hypernymy, into a distributional space. We introduce hierarchy-fitting, a novel semantic specialization approach to modelling semantic similarity nuances inherently stored in the IS-A hierarchies. Hierarchy-fitting attains state-of-the-art results on the common- and rare-word benchmark datasets for deriving semantic similarity from neural word embeddings. It also incorporates an asymmetric distance function to specialize hypernymy's directionality explicitly, through which it significantly improves vanilla embeddings in multiple evaluation tasks of detecting hypernymy and directionality without negative impacts on semantic similarity judgement. The results demonstrate the efficacy of hierarchy-fitting in specializing neural embeddings with semantic relations in late fusion, potentially expanding its applicability to aggregating heterogeneous data and various knowledge resources for learning multimodal semantic spaces.
On adaptive inverse estimating linear functionals of unknown smoothness in Hilbert scales
Creators: name: Goldenshluger, Alexander
name: Pereverzev, Sergei V.
Publisher: name: Weierstrass Institute
Year: 2001
Subjects: subject: adaptive estimation
subject: Hilbert scales
subject: inverse problems
subject: linear functionals
subject: minimax risk
subject: regularization
subject: 62G05
subject: 62G20
subject: 65R30

description: We address the problem of estimating the value of a linear functional 〈 ƒ,푥 〉 from random noisy observations of 푦 = A 푥 in Hilbert scales. Both the white noise and density observation models are considered. We develop an inverse estimator of 〈 ƒ,푥 〉 which automatically adapts to unknown smoothness of 푥 and ƒ. It is shown that accuracy of this adaptive estimator is only by a logarithmic factor worse than one could achieve in the case of known smoothness. As an illustrative example, the problem of deconvolving a bivariate density with singular support is considered.
Supplementary Material from A space of goals: the cognitive geometry of informationally bounded agents
Creators: name: Archer, Karen
name: Catenacci Volpi, Nicola
name: Bröker, Franziska
name: Polani, Daniel
Publisher: name: The Royal Society
Year: 2022
Subjects: subject: Artificial Intelligence and Image Processing
subject: FOS: Computer and information sciences
subject: Computational Biology
subject: 10203 Calculus of Variations, Systems Theory and Control Theory
subject: FOS: Mathematics
subject: 80611 Information Systems Theory

description: Supporting background information, trade-off curves and a mathematical proof.
Interacting Fractons in 2+1-Dimensional Quantum Field Theory
Creators: name: Distler, Jacques
name: Jafry, Murtaza
name: Karch, Andreas
name: Raz, Amir
Publisher: name: arXiv
Year: 2021
Subjects: subject: High Energy Physics - Theory (hep-th)
subject: Strongly Correlated Electrons (cond-mat.str-el)
subject: FOS: Physical sciences

description: We analyze, in perturbation theory, a theory of weakly interacting fractons and non-relativistic fermions in a 2+1 dimensional Quantum Field Theory. In particular we compute the 1-loop corrections to the self energies and interaction vertex, and calculate the associated 1-loop Renormalization Group flows of the coupling constants. Surprisingly, we find that the fracton-fermion coupling does not flow due to an emergent coordinate-dependent symmetry of the effective Lagrangian, making this model a well-defined quantum field theory. We provide additional discussions on the regularization and renormalization of interacting fractonic theories, as well as both qualitative and quantitative remarks regarding the theory at finite temperature and finite chemical potential.
description: 23 pages, 6 figures. V3: Correction: The scalar-self energy vanishes, but conclusions unchanged
Dual D-Brane Actions in Nonrelativistic String Theory
Creators: name: Ebert, Stephen
name: Sun, Hao-Yu
name: Yan, Ziqi
Publisher: name: arXiv
Year: 2021
Subjects: subject: High Energy Physics - Theory (hep-th)
subject: FOS: Physical sciences

description: We study worldvolume actions for D-branes coupled to the worldvolume U(1) gauge field and Ramond-Ramond (RR) potentials in nonrelativistic string theory. This theory is a self-contained corner of relativistic string theory and has a string spectrum with a Galilean-invariant dispersion relation. We therefore refer to such D-branes in nonrelativistic string theory as nonrelativistic D-branes. We focus on the bosonic fields in spacetime and also couple the D-branes to general closed string geometry, Kalb-Ramond, and dilaton background fields. We dualize nonrelativistic D-branes by performing a duality transformation on the worldvolume U(1) gauge field and uncover novel dual D-brane actions. This generalizes familiar properties, such as the SL(2,Z) duality in Type IIB superstring theory and the relation between Type IIA superstring and M-theory, to nonrelativistic string and M-theory. Moreover, we generalize the limit of string theory, in which nonrelativistic string theory arises, to include RR potentials. This stringy limit induces a codimension-two foliation structure in spacetime. This spacetime geometry is non-Riemannian and known as string Newton-Cartan geometry. In contrast, nonrelativistic M-theory that we probe by dualizing D2- and D4-branes in nonrelativistic string theory arises as a membrane limit of M-theory, and it is coupled to a membrane Newton-Cartan geometry with a codimension-three foliation structure. We also discuss T-duality in nonrelativistic string theory and generalize Buscher rules from earlier work to include RR potentials.
description: 63 pages; v2: published version
Détection de petites cibles par apprentissage profond et critère a contrario
Creators: name: Ciocarlan, Alina
name: Hegarat-Mascle, Sylvie Le
name: Lefebvre, Sidonie
name: Barbanson, Clara
Publisher: name: arXiv
Year: 2022
Subjects: subject: Computer Vision and Pattern Recognition (cs.CV)
subject: FOS: Computer and information sciences

description: Small target detection is an essential yet challenging task in defense applications, since differentiating low-contrast targets from natural textured and noisy environment remains difficult. To better take into account the contextual information, we propose to explore deep learning approaches based on attention mechanisms. Specifically, we propose a customized version of TransUnet including channel attention, which has shown a significant improvement in performance. Moreover, the lack of annotated data induces weak detection precision, leading to many false alarms. We thus explore a contrario methods in order to select meaningful potential targets detected by a weak deep learning training. -- La détection de petites cibles est une problématique délicate mais essentielle dans le domaine de la défense, notamment lorsqu'il s'agit de différencier ces cibles d'un fond bruité ou texturé, ou lorsqu'elles sont de faible contraste. Pour mieux prendre en compte les informations contextuelles, nous proposons d'explorer différentes approches de segmentation par apprentissage profond, dont certaines basées sur les mécanismes d'attention. Nous proposons également d'inclure un module d'attention par canal au TransUnet, réseau à l'état de l'art, ce qui permet d'améliorer significativement les performances. Par ailleurs, le manque de données annotées induit une perte en précision lors des détections, conduisant à de nombreuses fausses alarmes non pertinentes. Nous explorons donc des méthodes a contrario afin de sélectionner les cibles les plus significatives détectées par un réseau entraîné avec peu de données.
description: 4 pages, in French
Spectral density of generalized Wishart matrices and free multiplicative convolution
Creators: name: Mlotkowski, Wojciech
name: Nowak, Maciej A.
name: Penson, Karol A.
name: Zyczkowski, Karol
Publisher: name: arXiv
Year: 2014
Subjects: subject: Mathematical Physics (math-ph)
subject: Quantum Physics (quant-ph)
subject: FOS: Physical sciences

description: We investigate the level density for several ensembles of positive random matrices of a Wishart--like structure, $W=XX^{\dagger}$, where $X$ stands for a nonhermitian random matrix. In particular, making use of the Cauchy transform, we study free multiplicative powers of the Marchenko-Pastur (MP) distribution, ${\rm MP}^{\boxtimes s}$, which for an integer $s$ yield Fuss-Catalan distributions corresponding to a product of $s$ independent square random matrices, $X=X_1\cdots X_s$. New formulae for the level densities are derived for $s=3$ and $s=1/3$. Moreover, the level density corresponding to the generalized Bures distribution, given by the free convolution of arcsine and MP distributions is obtained. We also explain the reason of such a curious convolution. The technique proposed here allows for the derivation of the level densities for several other cases.
description: 10 latex pages including 4 figures, Ver 4, minor improvements and references update
Longtime dynamics in adaptive gain control systems
Creators: name: Leonov, Gennady A.
name: Schneider, Klaus R.
Publisher: name: Weierstrass Institute
Year: 2001
Subjects: subject: adaptive control systems
subject: frequency domain methods
subject: global attractor
subject: Hausdorff dimension
subject: 93C40
subject: 34D23
subject: 34D05
subject: 34D45
subject: 93C80

description: We study the longtime dynamics of a nonlinear adaptive control system introduced by Mareels et al. [10] to control the behavior of a plant which can be described by a finite dimensional SISO linear time invariant system stabilizable by a high gain output feedback. We apply frequency domain methods to derive conditions for global stability, to approximate the region containing the global attractor and to estimate its Hausdorff dimension.
Observation of the superconducting proximity effect from surface states in SmB$_6$/YB$_6$ thin film heterostructures via terahertz spectroscopy
Creators: name: Stensberg, Jonathan
name: Han, Xingyue
name: Lee, Seunghun
name: McGill, Stephen A.
name: Paglione, Johnpierre
name: Takeuchi, Ichiro
name: Kane, Charles L.
name: Wu, Liang
Publisher: name: arXiv
Year: 2021
Subjects: subject: Materials Science (cond-mat.mtrl-sci)
subject: Superconductivity (cond-mat.supr-con)
subject: FOS: Physical sciences

description: The AC conduction of epitaxially-grown SmB$_6$ thin films and superconducting heterostructures of SmB$_6$/YB$_6$ are investigated via time domain terahertz spectroscopy. A two-channel model of thickness-dependent bulk states and thickness-independent surface states accurately describes the measured conductance of bare SmB$_6$ thin films, demonstrating the presence of surface states in SmB$_6$. While the observed reductions in the simultaneously-measured superconducting gap, transition temperature, and superfluid density of SmB$_6$/YB$_6$ heterostructures relative to bare YB$_6$ indicate the penetration of proximity-induced superconductivity into the SmB$_6$ overlayer; the corresponding SmB$_6$-thickness independence between different heterostructures indicates that the induced superconductivity is predominantly confined to the interface surface state of the SmB$_6$. This study demonstrates the ability of terahertz spectroscopy to probe proximity-induced superconductivity at an interface buried within a heterostructure, and our results show that SmB$_6$ behaves as a predominantly insulating bulk surrounded by conducting surface states in both the normal and induced-superconducting states in both terahertz and DC responses, which is consistent with the topological Kondo insulator picture.
description: 7 pages, 3 figures. Accepted to Phys. Rev. Lett
Integrable turbulence and formation of rogue waves
Creators: name: Agafontsev, D. S.
name: Zakharov, V. E.
Publisher: name: arXiv
Year: 2014
Subjects: subject: Exactly Solvable and Integrable Systems (nlin.SI)
subject: Fluid Dynamics (physics.flu-dyn)
subject: FOS: Physical sciences

description: In the framework of the focusing Nonlinear Schrodinger (NLS) equation we study numerically the nonlinear stage of the modulation instability (MI) of the condensate. As expected, the development of the MI leads to formation of "integrable turbulence" [V.E. Zakharov, Turbulence in integrable systems, Stud. in Appl. Math. 122, no. 3, 219-234, (2009)]. We study the time evolution of it's major characteristics averaged across realizations of initial data - the condensate solution seeded by small random noise with fixed statistical properties. The measured quantities are: (1) wave-action spectrum and spatial correlation function, (2) the probability density function (PDF) of wave amplitudes and their momenta, and (3) kinetic and potential energies.
description: 42 pages, 24 figures
title: KI als Künstlerin
Creators: name: Kersten, Jens
Publisher: name: Center for Advanced Studies LMU
Year: 2020
Subjects: subject: 700 Arts and recreation
subject: 340 Law
subject: FOS: Law
subject: FOS: Art (arts, history of arts, performing arts, music)

description: Die Kunst verändert sich mit den Medien der Gesellschaft. Wie immer geben sich Kunst- und Kulturkritik bei diesem Thema gereizt: Hat nicht Reproduktionstechnik schon die Aura des Kunstwerks zertrümmert? Müssen jetzt auch noch intelligente Maschinen dichten, malen und komponieren?
Beyond the Fokker-Planck equation: Pathwise control of noisy bistable systems
Creators: name: Berglund, Nils
name: Gentz, Barbara
Publisher: name: Weierstrass Institute
Year: 2001
Subjects: subject: Langevin equation
subject: Fokker-Planck equation
subject: double-well potential
subject: first-exit time
subject: scaling laws
subject: stochastic resonance
subject: dynamicalhysteresis
subject: bifurcation delay
subject: white noise
subject: coloured noise
subject: 37H20
subject: 60H10
subject: 34E15
subject: 82C31
subject: 02.50.-r
subject: 05.10.Gg
subject: 75.60.-d
subject: 92.40.Cy

description: We introduce a new method, allowing to describe slowly time-dependent Langevin equations through the behaviour of individual paths. This approach yields considerably more information than the computation of the probability density. The main idea is to show that for sufficiently small noise intensity and slow time dependence, the vast majority of paths remain in small space-time sets, typically in the neighbourhood of potential wells. The size of these sets often has a power-law dependence on the small parameters, with universal exponents. The overall probability of exceptional paths is exponentially small, with an exponent also showing power-law behaviour. The results cover time spans up to the maximal Kramers time of the system. We apply our method to three phenomena characteristic for bistable systems: stochastic resonance, dynamical hysteresis and bifurcation delay, where it yields precise bounds on transition probabilities, and the distribution of hysteresis areas and first-exit times. We also discuss the effect of coloured noise.
No short polynomials vanish on bounded rank matrices
Creators: name: Draisma, Jan
name: Kahle, Thomas
name: Wiersig, Finn
Publisher: name: arXiv
Year: 2021
Subjects: subject: Commutative Algebra (math.AC)
subject: Algebraic Geometry (math.AG)
subject: FOS: Mathematics
subject: 14M12, 14Q20, 15A15

description: We show that the shortest nonzero polynomials vanishing on bounded-rank matrices and skew-symmetric matrices are the determinants and Pfaffians characterising the rank. Algebraically, this means that in the ideal generated by all $t$-minors or $t$-Pfaffians of a generic matrix or skew-symmetric matrix one cannot find any polynomial with fewer terms than those determinants or Pfaffians, respectively, and that those determinants and Pfaffians are essentially the only polynomials in the ideal with that many terms. As a key tool of independent interest, we show that the ideal of a sufficiently general $t$-dimensional subspace of an affine $n$-space does not contain polynomials with fewer than $t+1$ terms.
description: 13 pages, comments welcome, v2: 15 pages, final version as in Bulletin LMS
Stochastic Lagrangian model for spatially inhomogeneous Smoluchowski equation governing coagulating and diffusing particles
Creators: name: Kolodko, Anastasia
name: Sabelfeld, Karl
Publisher: name: Weierstrass Institute
Year: 2001
Subjects: subject: Smoluchowski coagulation equation
subject: turbulent mixing
subject: Lagrangian stochastic model
subject: 65C05
subject: 76F99

description: The following generally unsolved yet problem is studied: construct the solution of a spatially inhomogeneous Smoluchowski equation governing coagulating and diffusing particles in a host gas, on the basis of solutions to homogeneous Smoluchowski equation. In citeksw we solved this problem in the case when there is no diffusion. The non-zero diffusion term drastically complicates the situation. Under some general assumptions we give the interrelations between the homogeneous and inhomogeneous cases. This provides an effective numerical scheme especially when the host gas is incompressible. New Lagrangian scheme leads to a new model governing by a Smoluchowski type equation with an additional effective source. We give a numerical comparison of these two models. The computer time of the new algorithm is so dramatically decreased, compared to the conventional deterministic algorithm (tens of hours drop down to several minutes) that many practical problems like the formation of soot particles in flames or chemical reactions coupled to formation of a new phase can be solved in a reasonable computer time. However this method works only if the diffusion coefficient of all particles is the same which can be a reasonable approximation only for special systems. The problem of generalisation of the method presented to the case when the diffusion coefficient depends on the particle's size is open.
Production of $Σ(1385)^{\pm}$ and $Ξ(1530)^{0}$ in proton-proton collisions at $\sqrt{s}=$ 7 TeV
Creators: name: ALICE Collaboration
Publisher: name: arXiv
Year: 2014
Subjects: subject: Nuclear Experiment (nucl-ex)
subject: High Energy Physics - Experiment (hep-ex)
subject: FOS: Physical sciences

description: The production of the strange and double-strange baryon resonances ($Σ(1385)^{\pm}$, $Ξ(1530)^{0}$) has been measured at mid-rapidity ($\left | y \right |<0.5$) in proton-proton collisions at $\sqrt{s}$ = 7 TeV with the ALICE detector at the LHC. Transverse momentum spectra for inelastic collisions are compared to QCD-inspired models, which in general underpredict the data. A search for the $ϕ(1860)$ pentaquark, decaying in the $Ξπ$ channel, has been carried out but no evidence is seen.
description: 29 pages, 9 captioned figures, 9 tables, authors from page 24, published version, figures at http://aliceinfo.cern.ch/ArtSubmission/node/1936
title: Dis:konnektivität und Krise
Creators: name: Wenzlhuemer, Roland
Publisher: name: Center for Advanced Studies LMU
Year: 2020
Subjects: subject: 900 History and geography
subject: FOS: History and archaeology

description: Die noch kurze Geschichte des 21. Jahrhunderts ist – weit über die so genannte westliche Welt hinaus – geprägt von einer Abfolge wirtschaftlich und gesellschaftlich in höchstem Maße transformativer Krisen.
Glauber dynamics of the random energy model I. Metastable motion on the extreme states
Creators: name: Ben Arous, Gérard
name: Bovier, Anton
name: Gayrard, Véronique
Publisher: name: Weierstrass Institute
Year: 2001
Subjects: subject: aging
subject: Glauber dynamics
subject: random energy model
subject: trap models
subject: metastability
subject: extreme values
subject: 82C44
subject: 60K35

description: We investigate the long-time behavior of the Glauber dynamics for the random energy model below the critical temperature. We give very precise estimates on the motion of the process to and between the states of extremal energies. We show that when disregarding time, the consecutive steps of the process on these states are governed by a Markov chain that jumps uniformly on all possible states. The mean times of these jumps are also computed very precisely and are seen to be asymptotically independent of the terminal point. A first indicator of aging is the observation that the mean time of arrival in the set of states that have waiting times of order T is itself of order T . The estimates proven in this paper will furnish crucial input for a follow-up paper where aging is analysed in full detail.
$\bar{B}^0$ and $\bar{B}^0_s$ decays into $J/ψ$ and $f_0(1370),~f_0(1710),~f_2(1270),~f'_2(1525),~K^*_2(1430)$
Creators: name: Xie, Ju-Jun
name: Oset, E.
Publisher: name: arXiv
Year: 2014
Subjects: subject: High Energy Physics - Phenomenology (hep-ph)
subject: High Energy Physics - Experiment (hep-ex)
subject: Nuclear Theory (nucl-th)
subject: FOS: Physical sciences

description: We make predictions for the ratios of branching fractions of ${\bar B}^0$ and ${\bar B}^0_s$ decays into $J/ψ$ and the scalar mesons $f_0(1370),~f_0(1710)$ or tensor mesons $f_2(1270),~f'_2(1525),~K^*_2(1430)$. The theoretical approach is based on results of chiral unitary theory where these resonances are shown to be generated from the vector meson-vector meson interaction. Eight independent ratios can be predicted and comparison is made with the recent data on $\bar{B}^0_s$ decay into $J/ψf'_2(1525)$ versus the $\bar{B}^0_s$ decay into $J/ψf_2(1270)$.
description: Published version. Phys. Rev. D 90, 094006 (2014)
Aging in the random energy model
Creators: name: Ben Arous, Gérard
name: Bovier, Anton
name: Gayrard, Véronique
Publisher: name: Weierstrass Institute
Year: 2001
Subjects: subject: aging
subject: Glauber dynamics
subject: random energy model
subject: trap models
subject: metastability
subject: extreme values
subject: 75.10.Nr
subject: 75.10.Jm
subject: 75.10.Hk
subject: 05.30.-d

description: In this letter we announce rigorous results on the phenomenon of aging in the Glauber dynamics of the random energy model and their relation to Bouchaud's 'REM-like' trap model. We show that, below the critical temperature, if we consider a time-scale that diverges with the system size in such a way that equilibrium is almost, but not quite reached on that scale, a suitably defined autocorrelation function has the same asymptotic behaviour than its analog in the trap model.
FourierNet: Shape-Preserving Network for Henle's Fiber Layer Segmentation in Optical Coherence Tomography Images
Creators: name: Cansiz, Selahattin
name: Kesim, Cem
name: Bektas, Sevval Nur
name: Kulali, Zeynep
name: Hasanreisoglu, Murat
name: Gunduz-Demir, Cigdem
Publisher: name: arXiv
Year: 2022
Subjects: subject: Computer Vision and Pattern Recognition (cs.CV)
subject: FOS: Computer and information sciences

description: The Henle's fiber layer (HFL) in the retina carries valuable information on the macular condition of an eye. However, in the common practice, this layer is not separately segmented but rather included in the outer nuclear layer since it is difficult to perceive HFL contours on standard optical coherence tomography (OCT) imaging. Due to its variable reflectivity under an imaging beam, delineating the HFL contours necessitates directional OCT, which requires additional imaging. This paper addresses this issue by introducing a shape-preserving network, FourierNet, that achieves HFL segmentation in standard OCT scans with the target performance obtained when directional OCT scans are used. FourierNet is a new cascaded network design that puts forward the idea of benefiting the shape prior of HFL in the network training. This design proposes to represent the shape prior by extracting Fourier descriptors on the HFL contours and defining an additional regression task of learning these descriptors. It then formulates HFL segmentation as concurrent learning of regression and classification tasks, in which Fourier descriptors are estimated from an input image to encode the shape prior and used together with the input image to construct the HFL segmentation map. Our experiments on 1470 images of 30 OCT scans reveal that quantifying the HFL shape with Fourier descriptors and concurrently learning them with the main task of HFL segmentation lead to better results. This indicates the effectiveness of designing a shape-preserving network to improve HFL segmentation by reducing the need to perform directional OCT imaging.
Post-selected von Neumann measurement with Hermite-Gaussian and Laguerre-Gaussian pointer states
Creators: name: Turek, Yusuf
name: Kobayashi, Hirokazu
name: Akutsu, Tomotada
name: Sun, Chang-Pu
name: Shikano, Yutaka
Publisher: name: arXiv
Year: 2014
Subjects: subject: Quantum Physics (quant-ph)
subject: Mathematical Physics (math-ph)
subject: Optics (physics.optics)
subject: FOS: Physical sciences
subject: 81P15, 78A10

description: Through the von Neumann interaction followed by post-selection, we can extract not only the eigenvalue of an observable of the measured system but also the weak value. In this post-selected von Neumann measurement, the initial pointer state of the measuring device is assumed to be a fundamental Gaussian wave function. By considering the optical implementation of the post-selected von Neumann measurement, higher-order Gaussian modes can be used. In this paper, we consider the Hermite--Gaussian (HG) and Laguerre--Gaussian (LG) modes as pointer states and calculate the average shift of the pointer states of the post-selected von Neumann measurement by assuming the system observable $\hat{A}$ with $\hat{A}^{2}=\hat{I}$ and $\hat{A}^{2}=\hat{A}$ for an arbitrary interaction strength, where $\hat{I}$ represents the identity operator. Our results show that the HG and LG pointer states for a given coupling direction have advantages and disadvantages over the fundamental Gaussian mode in improving the signal-to-noise ratio (SNR). We expect that our general treatment of the weak values will be helpful for understanding the connection between weak- and strong-measurement regimes and may be used to propose new experimental setups with higher-order Gaussian beams to investigate further the applications of weak measurement in optical systems such as the optical vortex.
description: 22 pages, 9 figures
From Explanations to Segmentation: Using Explainable AI for Image Segmentation
Creators: name: Seibold, Clemens
name: Künzel, Johannes
name: Hilsmann, Anna
name: Eisert, Peter
Publisher: name: arXiv
Year: 2022
Subjects: subject: Computer Vision and Pattern Recognition (cs.CV)
subject: FOS: Computer and information sciences

description: The new era of image segmentation leveraging the power of Deep Neural Nets (DNNs) comes with a price tag: to train a neural network for pixel-wise segmentation, a large amount of training samples has to be manually labeled on pixel-precision. In this work, we address this by following an indirect solution. We build upon the advances of the Explainable AI (XAI) community and extract a pixel-wise binary segmentation from the output of the Layer-wise Relevance Propagation (LRP) explaining the decision of a classification network. We show that we achieve similar results compared to an established U-Net segmentation architecture, while the generation of the training data is significantly simplified. The proposed method can be trained in a weakly supervised fashion, as the training samples must be only labeled on image-level, at the same time enabling the output of a segmentation mask. This makes it especially applicable to a wider range of real applications where tedious pixel-level labelling is often not possible.
description: to be published in: 17th International Conference on Computer Vision Theory and Applications (VISAPP), February 2022
Measurement of beauty production via non-prompt ${\rm D}^{0}$ mesons in Pb-Pb collisions at $\sqrt{s_{\rm NN}}$ = 5.02 TeV
Creators: name: ALICE Collaboration
Publisher: name: arXiv
Year: 2022
Subjects: subject: Nuclear Experiment (nucl-ex)
subject: FOS: Physical sciences

description: The production of non-prompt ${\rm D}^{0}$ mesons from beauty-hadron decays was measured at midrapidity ($\left| y \right| < 0.5$) in Pb-Pb collisions at a nucleon-nucleon center-of-mass energy of $\sqrt{s_{\rm NN}}=5.02~\mathrm{TeV}$ with the ALICE experiment at the LHC. Their nuclear modification factor ($R_{\rm AA}$), measured for the first time down to $p_{\rm T}=1~\mathrm{GeV}/c$ in the $0-10$% and $30-50$% centrality classes, indicates a significant suppression, up to a factor of about three, for $p_{\rm T} > 5~\mathrm{GeV}/c$ in the $0-10$% central Pb-Pb collisions. The data are described by models that include both collisional and radiative processes in the calculation of beauty-quark energy loss in the quark-gluon plasma, and quark recombination in addition to fragmentation as a hadronisation mechanism. The ratio of the non-prompt to prompt ${\rm D}^{0}$-meson $R_{\rm AA}$ is larger than unity for $p_{\rm T} > 4~\mathrm{GeV}/c$ in the $0-10$% central Pb-Pb collisions, as predicted by models in which beauty quarks lose less energy than charm quarks in the quark-gluon plasma because of their larger mass.
description: 24 pages, 4 captioned figures, authors from page 19, published version, figures at http://alice-publications.web.cern.ch/node/7637
Decision curve analysis for personalized treatment choice between multiple options
Creators: name: Chalkou, Konstantina
name: Vickers, Andrew J.
name: Pellegrini, Fabio
name: Manca, Andrea
name: Salanti, Georgia
Publisher: name: arXiv
Year: 2022
Subjects: subject: Methodology (stat.ME)
subject: FOS: Computer and information sciences

description: Decision curve analysis can be used to determine whether a personalized model for treatment benefit would lead to better clinical decisions. Decision curve analysis methods have been described to estimate treatment benefit using data from a single RCT. Our main objective is to extend the decision curve analysis methodology to the scenario where several treatment options exist and evidence about their effects comes from a set of trials, synthesized using network meta-analysis (NMA). We describe the steps needed to estimate the net benefit of a prediction model using evidence from studies synthesized in an NMA. We show how to compare personalized versus one-size-fit-all treatment decision-making strategies, like "treat none" or "treat all patients with a specific treatment" strategies. The net benefit per strategy can then be plotted for a plausible range of threshold probabilities to reveal the most clinically useful strategy. We applied our methodology to an NMA prediction model for relapsing-remitting multiple sclerosis, which can be used to choose between Natalizumab, Dimethyl Fumarate, Glatiramer Acetate, and placebo. We illustrated the extended decision curve analysis methodology using several threshold values combinations for each available treatment. For the examined threshold values, the "treat patients according to the prediction model" strategy performs either better than or close to the one-size-fit-all treatment strategies. However, even small differences may be important in clinical decision-making. As the advantage of the personalized model was not consistent across all thresholds, an improved model may be needed before advocating its applicability for decision-making. This novel extension of decision curve analysis can be applied to NMA based prediction models to evaluate their use to aid treatment decision-making.
Identification of b-jets using QCD-inspired observables
Creators: name: Fedkevych, Oleh
name: Khosa, Charanjit K.
name: Marzani, Simone
name: Sforza, Federico
Publisher: name: arXiv
Year: 2022
Subjects: subject: High Energy Physics - Phenomenology (hep-ph)
subject: High Energy Physics - Experiment (hep-ex)
subject: FOS: Physical sciences

description: We study the issue of separating hadronic jets that contain bottom quarks ($b$-jets) from jets featuring light partons only. We develop a novel approach to $b$-tagging that exploits the application of QCD-inspired jet substructure observables such as one-dimensional jet angularities and the two-dimensional primary Lund plane. We demonstrate that these observables can be used as inputs to modern machine-learning algorithms to efficiently separate $b$-jets from light ones. In order to test our tagging procedure, we consider simulated events where a $Z$ boson is produced is association with jets and show that using jet angularities as an input for a deep neural network, as well as using images obtained from the primary Lund jet plane as input to a convolutional neural network, one can achieve tagging accuracy comparable with the accuracy of conventional track-based taggers. We argue that the complementary usage of the track-based taggers together with the ones based upon QCD-inspired observables could improve $b$-tagging accuracy.
Information-Theoretic Analysis of Minimax Excess Risk
Creators: name: Hafez-Kolahi, Hassan
name: Moniri, Behrad
name: Kasaei, Shohreh
Publisher: name: arXiv
Year: 2022
Subjects: subject: Machine Learning (cs.LG)
subject: Information Theory (cs.IT)
subject: Machine Learning (stat.ML)
subject: FOS: Computer and information sciences

description: Two main concepts studied in machine learning theory are generalization gap (difference between train and test error) and excess risk (difference between test error and the minimum possible error). While information-theoretic tools have been used extensively to study the generalization gap of learning algorithms, the information-theoretic nature of excess risk has not yet been fully investigated. In this paper, some steps are taken toward this goal. We consider the frequentist problem of minimax excess risk as a zero-sum game between the algorithm designer and the world. Then, we argue that it is desirable to modify this game in a way that the order of play can be swapped. We then prove that, under some regularity conditions, if the world and designer can play randomly the duality gap is zero and the order of play can be changed. In this case, a Bayesian problem surfaces in the dual representation. This makes it possible to utilize recent information-theoretic results on minimum excess risk in Bayesian learning to provide bounds on the minimax excess risk. We demonstrate the applicability of the results by providing information theoretic insight on two important classes of problems: classification when the hypothesis space has finite VC-dimension, and regularized least squares.
description: Published in the IEEE Transactions on Information Theory
Bounds on quantum nonlocality via partial transposition
Creators: name: Horodecki, Karol
name: Murta, Gláucia
Publisher: name: arXiv
Year: 2014
Subjects: subject: Quantum Physics (quant-ph)
subject: FOS: Physical sciences

description: We explore the link between two concepts: the level of violation of a Bell inequality by a quantum state and discrimination between two states by means of restricted classes of operations, such as local operations and classical communication (LOCC) and separable ones. For any bipartite Bell inequality, we show that its value on a given quantum state cannot exceed the classical bound by more than the maximal quantum violation shrunk by a factor related to distinguishability of this state from the separable set by means of some restricted class of operations. We then consider the general scenarios where the parties are allowed to perform a local pre-processing of many copies of the state before the Bell test (asymptotic and hidden-nonlocality scenarios). We define the asymptotic relative entropy of nonlocality and, for PPT states, we bound this quantity by the relative entropy of entanglement of the partially transposed state. The bounds are strong enough to limit the use of certain states containing private key in the device-independent scenario.
description: 5+4 pages, 1 figure. Theorem 1 extended to Bell inequalities with negative coefficients. Text slightly improved
HPC Storage Service Autotuning Using Variational-Autoencoder-Guided Asynchronous Bayesian Optimization
Creators: name: Dorier, Matthieu
name: Egele, Romain
name: Balaprakash, Prasanna
name: Koo, Jaehoon
name: Madireddy, Sandeep
name: Ramesh, Srinivasan
name: Malony, Allen D.
name: Ross, Rob
Publisher: name: arXiv
Year: 2022
Subjects: subject: Distributed, Parallel, and Cluster Computing (cs.DC)
subject: Machine Learning (cs.LG)
subject: FOS: Computer and information sciences

description: Distributed data storage services tailored to specific applications have grown popular in the high-performance computing (HPC) community as a way to address I/O and storage challenges. These services offer a variety of specific interfaces, semantics, and data representations. They also expose many tuning parameters, making it difficult for their users to find the best configuration for a given workload and platform. To address this issue, we develop a novel variational-autoencoder-guided asynchronous Bayesian optimization method to tune HPC storage service parameters. Our approach uses transfer learning to leverage prior tuning results and use a dynamically updated surrogate model to explore the large parameter search space in a systematic way. We implement our approach within the DeepHyper open-source framework, and apply it to the autotuning of a high-energy physics workflow on Argonne's Theta supercomputer. We show that our transfer-learning approach enables a more than $40\times$ search speedup over random search, compared with a $2.5\times$ to $10\times$ speedup when not using transfer learning. Additionally, we show that our approach is on par with state-of-the-art autotuning frameworks in speed and outperforms them in resource utilization and parallelization capabilities.
description: Accepted at IEEE Cluster 2022
title: Civil War in Brunswick, Maine
Creators: name: Kimmage, Michael C.
Publisher: name: Center for Advanced Studies LMU
Year: 2020
Subjects: subject: 970 General history of North America
subject: FOS: History and archaeology

description: Harriet Beecher Stowe lived in Brunswick, Maine from 1850 to 1852. It was and is a small town in coastal Maine, home to Bowdoin College, where Stowe’s husband was briefly a professor of theology. Harriet Beecher Stowe was not then famous. Neither was her husband.