cometadata/datacite-rtg-text-other-reclassification-records huggingface dataset:
Entropy of labeled versus unlabeled networks
Creators: name: Paton, Jeremy
name: Hartle, Harrison
name: Stepanyants, Huck
name: van der Hoorn, Pim
name: Krioukov, Dmitri
Publisher: name: arXiv
Year: 2022
Subjects: subject: Physics and Society (physics.soc-ph)
subject: Statistical Mechanics (cond-mat.stat-mech)
subject: Social and Information Networks (cs.SI)
subject: Probability (math.PR)
subject: Data Analysis, Statistics and Probability (physics.data-an)
subject: FOS: Physical sciences
subject: FOS: Computer and information sciences
subject: FOS: Mathematics

description: The structure of a network is an unlabeled graph, yet graphs in most models of complex networks are labeled by meaningless random integers. Is the associated labeling noise always negligible, or can it overpower the network-structural signal? To address this question, we introduce and consider the sparse unlabeled versions of popular network models, and compare their entropy against the original labeled versions. We show that labeled and unlabeled Erdos-Renyi graphs are entropically equivalent, even though their degree distributions are very different. The labeled and unlabeled versions of the configuration model may have different prefactors in their leading entropy terms, although this remains conjectural. Our main results are upper and lower bounds for the entropy of labeled and unlabeled one-dimensional random geometric graphs. We show that their unlabeled entropy is negligible in comparison with the labeled entropy. This means that in sparse networks the entropy of meaningless labeling may dominate the entropy of the network structure. The main implication of this result is that the common practice of using exchangeable models to reason about real-world networks with distinguishable nodes may introduce uncontrolled aberrations into conclusions made about these networks, suggesting a need for a thorough reexamination of the statistical foundations and key results of network science.
Virtual Rings on Highways: Traffic Control by Connected Automated Vehicles
Creators: name: Molnar, Tamas G.
name: Hopka, Michael
name: Upadhyay, Devesh
name: Van Nieuwstadt, Michiel
name: Orosz, Gabor
Publisher: name: arXiv
Year: 2022
Subjects: subject: Systems and Control (eess.SY)
subject: Robotics (cs.RO)
subject: Dynamical Systems (math.DS)
subject: FOS: Electrical engineering, electronic engineering, information engineering
subject: FOS: Computer and information sciences
subject: FOS: Mathematics

description: This work gives introduction to traffic control by connected automated vehicles. The influence of vehicle control on vehicular traffic and traffic control strategies are discussed and compared. It is highlighted that vehicle-to-everything connectivity allows connected automated vehicles to access the state of the traffic behind them such that feedback can be utilized to mitigate evolving congestions. Numerical simulations demonstrate that such connectivity-based traffic control is beneficial for smoothness and energy efficiency of highway traffic. The dynamics and stability of traffic flow, under the proposed controllers, are analyzed in detail to construct stability charts that guide the selection of stabilizing control gains.
description: Accepted for publication in the book "AI-enabled Technologies for Autonomous and Connected Vehicles". 37 pages, 8 figures
DataPilot: Utilizing Quality and Usage Information for Subset Selection during Visual Data Preparation
Creators: name: Narechania, Arpit
name: Du, Fan
name: Sinha, Atanu R
name: Rossi, Ryan A.
name: Hoffswell, Jane
name: Guo, Shunan
name: Koh, Eunyee
name: Navathe, Shamkant B.
name: Endert, Alex
Publisher: name: arXiv
Year: 2023
Subjects: subject: Human-Computer Interaction (cs.HC)
subject: FOS: Computer and information sciences

description: Selecting relevant data subsets from large, unfamiliar datasets can be difficult. We address this challenge by modeling and visualizing two kinds of auxiliary information: (1) quality - the validity and appropriateness of data required to perform certain analytical tasks; and (2) usage - the historical utilization characteristics of data across multiple users. Through a design study with 14 data workers, we integrate this information into a visual data preparation and analysis tool, DataPilot. DataPilot presents visual cues about "the good, the bad, and the ugly" aspects of data and provides graphical user interface controls as interaction affordances, guiding users to perform subset selection. Through a study with 36 participants, we investigate how DataPilot helps users navigate a large, unfamiliar tabular dataset, prepare a relevant subset, and build a visualization dashboard. We find that users selected smaller, effective subsets with higher quality and usage, and with greater success and confidence.
description: 18 pages, 5 figures, 1 table, ACM CHI 2023
DeepSeer: Interactive RNN Explanation and Debugging via State Abstraction
Creators: name: Wang, Zhijie
name: Huang, Yuheng
name: Song, Da
name: Ma, Lei
name: Zhang, Tianyi
Publisher: name: arXiv
Year: 2023
Subjects: subject: Human-Computer Interaction (cs.HC)
subject: Machine Learning (cs.LG)
subject: Software Engineering (cs.SE)
subject: FOS: Computer and information sciences

description: Recurrent Neural Networks (RNNs) have been widely used in Natural Language Processing (NLP) tasks given its superior performance on processing sequential data. However, it is challenging to interpret and debug RNNs due to the inherent complexity and the lack of transparency of RNNs. While many explainable AI (XAI) techniques have been proposed for RNNs, most of them only support local explanations rather than global explanations. In this paper, we present DeepSeer, an interactive system that provides both global and local explanations of RNN behavior in multiple tightly-coordinated views for model understanding and debugging. The core of DeepSeer is a state abstraction method that bundles semantically similar hidden states in an RNN model and abstracts the model as a finite state machine. Users can explore the global model behavior by inspecting text patterns associated with each state and the transitions between states. Users can also dive into individual predictions by inspecting the state trace and intermediate prediction results of a given input. A between-subjects user study with 28 participants shows that, compared with a popular XAI technique, LIME, participants using DeepSeer made a deeper and more comprehensive assessment of RNN model behavior, identified the root causes of incorrect predictions more accurately, and came up with more actionable plans to improve the model performance.
description: To appear in the 2023 CHI Conference on Human Factors in Computing Systems (CHI '23), April 23--28, 2023, Hamburg, Germany
DeepLens: Interactive Out-of-distribution Data Detection in NLP Models
Creators: name: Song, Da
name: Wang, Zhijie
name: Huang, Yuheng
name: Ma, Lei
name: Zhang, Tianyi
Publisher: name: arXiv
Year: 2023
Subjects: subject: Human-Computer Interaction (cs.HC)
subject: Machine Learning (cs.LG)
subject: FOS: Computer and information sciences

description: Machine Learning (ML) has been widely used in Natural Language Processing (NLP) applications. A fundamental assumption in ML is that training data and real-world data should follow a similar distribution. However, a deployed ML model may suffer from out-of-distribution (OOD) issues due to distribution shifts in the real-world data. Though many algorithms have been proposed to detect OOD data from text corpora, there is still a lack of interactive tool support for ML developers. In this work, we propose DeepLens, an interactive system that helps users detect and explore OOD issues in massive text corpora. Users can efficiently explore different OOD types in DeepLens with the help of a text clustering method. Users can also dig into a specific text by inspecting salient words highlighted through neuron activation analysis. In a within-subjects user study with 24 participants, participants using DeepLens were able to find nearly twice more types of OOD issues accurately with 22% more confidence compared with a variant of DeepLens that has no interaction or visualization support.
description: The first two authors contributed equally. To appear in the 2023 CHI Conference on Human Factors in Computing Systems (CHI '23), April 23--28, 2023, Hamburg, Germany
A Mountaineering Strategy to Excited States: Revising Reference Values with EOM-CC4
Creators: name: Loos, Pierre-Fran\{c}ois
name: Lipparini, Filippo
name: Matthews, Devin A.
name: Blondel, Aymeric
name: Jacquemin, Denis
Publisher: name: arXiv
Year: 2022
Subjects: subject: Chemical Physics (physics.chem-ph)
subject: Materials Science (cond-mat.mtrl-sci)
subject: Strongly Correlated Electrons (cond-mat.str-el)
subject: Computational Physics (physics.comp-ph)
subject: FOS: Physical sciences

description: In the framework of the computational determination of highly-accurate vertical excitation energies in small organic compounds, we explore the possibilities offered by the equation-of-motion formalism relying on the approximate fourth-order coupled-cluster (CC) method, CC4. We demonstrate, using an extended set of more than 200 reference values based on CC including up to quadruples excitations (CCSDTQ), that CC4 is an excellent approximation to CCSDTQ for excited states with a dominant contribution from single excitations with an average deviation as small as $0.003$ eV. We next assess the accuracy of several additive basis set correction schemes, in which vertical excitation energies obtained with a compact basis set and a high-order CC method are corrected with lower-order CC calculations performed in larger basis sets. Such strategies are found to be overall very beneficial, though their accuracy depend significantly on the actual scheme. Finally, CC4 is employed to improve several theoretical best estimates of the QUEST database for molecules containing between four and six (non-hydrogen) atoms, for which previous estimates were computed at the CCSDT level.
description: 12 pages, 1 figure (supporting information available)
A Rickard equivalence for hopfological homotopy categories
Creators: name: Qi, You
Publisher: name: arXiv
Year: 2022
Subjects: subject: K-Theory and Homology (math.KT)
subject: FOS: Mathematics
subject: 18G65, 18G80

description: In his paper [Ric89], Rickard presents the stable module category of a self-injective algebra as a Verdier quotient of its derived category by perfect complexes. We present a similar realization of the homotopy category in hopfological algebra as such a Verdier quotient.
description: 13 pages, comments welcome. V2 contains changes from referee reports
Jets and Outflows From Star to Cloud: Observations Confront Theory
Creators: name: Frank, A.
name: Ray, T. P.
name: Cabrit, S.
name: Hartigan, P.
name: Arce, H. G.
name: Bacciotti, F.
name: Bally, J.
name: Benisty, M.
name: Eislöffel, J.
name: Güdel, M.
name: Lebedev, S.
name: Nisini, B.
name: Raga, A.
Publisher: name: arXiv
Year: 2014
Subjects: subject: Solar and Stellar Astrophysics (astro-ph.SR)
subject: FOS: Physical sciences

description: In this review we focus on the role jets and outflows play in the star and planet formation process. Our essential question can be posed as follows: are jets/outflows merely an epiphenomenon associated with star formation or do they play an important role in mediating the physics of assembling stars both individually and globally? We address this question by reviewing the current state of observations and their key points of contact with theory. Our review of jet/outflow phenomena is organized into three length-scale domains: Source and Disk Scales ($0.1-10^2$ au) where the connection with protostellar and disk evolution theories is paramount; Envelope Scales ($10^2-10^5$ au) where the chemistry and propagation shed further light on the jet launching process, its variability and its impact on the infalling envelope; Parent Cloud Scales ($10^5-10^6$ au) where global momentum injection into cluster/cloud environments become relevant. Issues of feedback are of particular importance on the smallest scales where planet formation regions in a disk may be impacted by the presence of disk winds, irradiation by jet shocks or shielding by the winds. Feedback on envelope scales may determine the final stellar mass (core-to-star efficiency) and envelope dissipation. Feedback also plays an important role on the larger scales with outflows contributing to turbulent support within clusters including alteration of cluster star formation efficiencies (feedback on larger scales currently appears unlikely). A particularly novel dimension of our review is that we consider results on jet dynamics from the emerging field of High Energy Density Laboratory Astrophysics (HEDLA). HEDLA is now providing direct insights into the 3-D dynamics of fully magnetized, hypersonic, radiative outflows.
description: Accepted for publication as a chapter in Protostars and Planets VI, University of Arizona Press (2014), eds. H. Beuther, R. Klessen, C. Dullemond, Th. Henning
Sterile neutrinos, $0νββ$ decay and the W-boson mass anomaly in a Flipped $SU(5)$ from F-theory
Creators: name: Basiouris, Vasileios
name: Leontaris, George K.
Publisher: name: arXiv
Year: 2022
Subjects: subject: High Energy Physics - Phenomenology (hep-ph)
subject: High Energy Physics - Experiment (hep-ex)
subject: High Energy Physics - Theory (hep-th)
subject: FOS: Physical sciences

description: We investigate the low energy properties of an effective local model with flipped $SU(5)\times U(1)_χ$ gauge group, constructed within the framework of F-theory. Its origin is traced back to the $SO(10)$ symmetry -- associated with a geometric singularity of the compactification manifold -- broken by an internal flux which is turned on along the seven-brane in the $U(1)_χ$ direction. Topological properties and the choice of flux parameters determine the massless spectrum of the model to be that of the minimal flipped $SU(5)$ supplemented with an extra right-handed electron-type state and its complex conjugate, $E^c+\bar E^c$, as well as neutral singlet fields. The subsequent symmetry breaking to the $SU(3)\times SU(2)\times U(1)_Y$ gauge group occurs with a Higgs pair in $10+\overline{10}$ representations of $SU(5)$. Next we proceed to the phenomenological analysis of the resulting effective model and the salient outcomes are: The $E^c+\bar E^c$ pair acquires a mass of few TeV and as such could solve the $g_μ-2$ discrepancy. Neutrino couplings to extra neutral singlets lead to an inverse seesaw mechanism where an extra light state could be a suitable dark matter candidate. The predictions of the model for the ${0ν}ββ$ decay rate could be tested in near future experiments. There are non-unitarity deviations from lepton mixing matrix ($U_{PMNS}$), which could in principle explain the new precision measurement of the W-boson mass recently reported by CDF II collaboration.
description: Revised and expanded version. To appear in EPJC
Dubrovin's conjecture for $IG(2,6)$
Creators: name: Galkin, Sergey
name: Mellit, Anton
name: Smirnov, Maxim
Publisher: name: arXiv
Year: 2014
Subjects: subject: Algebraic Geometry (math.AG)
subject: Rings and Algebras (math.RA)
subject: Symplectic Geometry (math.SG)
subject: FOS: Mathematics

description: We show that the big quantum cohomology of the symplectic isotropic Grassmanian $IG(2,6)$ is generically semisimple, whereas its small quantum cohomology is known to be non-semisimple. This gives yet another case where Dubrovin's conjecture holds and stresses the need to consider the big quantum cohomology in its formulation.
Evidence for charge and spin order in single crystals of La$_3$Ni$_2$O$_7$ and La$_3$Ni$_2$O$_6$
Creators: name: Liu, Zengjia
name: Sun, Hualei
name: Huo, Mengwu
name: Ma, Xiaoyan
name: Ji, Yi
name: Yi, Enkui
name: Li, Lisi
name: Liu, Hui
name: Yu, Jia
name: Zhang, Ziyou
name: Chen, Zhiqiang
name: Liang, Feixiang
name: Dong, Hongliang
name: Guo, Hanjie
name: Zhong, Dingyong
name: Shen, Bing
name: Li, Shiliang
name: Wang, Meng
Publisher: name: arXiv
Year: 2022
Subjects: subject: Strongly Correlated Electrons (cond-mat.str-el)
subject: FOS: Physical sciences

description: Charge and spin order is intimately related to superconductivity in copper oxide superconductors. To elucidate the competing orders in various nickel oxide compounds are crucial given the fact that superconductivity has been discovered in Nd$_{0.8}$Sr$_{0.2}$NiO$_2$ films. Herein, we report structural, electronic transport, magnetic, and thermodynamic characterizations on single crystals of La$_3$Ni$_2$O$_7$ and La$_3$Ni$_2$O$_6$. La$_3$Ni$_2$O$_7$ is metallic with mixed Ni$^{2+}$ and Ni$^{3+}$ valent states. Resistivity measurements yield two transition-like kinks at $\sim$110 and 153 K, respectively. The kink at 153 K is further revealed from magnetization and specific heat measurements, indicative of the formation of charge and spin order. La$_3$Ni$_2$O$_6$ single crystals obtained from topochemical reduction of La$_3$Ni$_2$O$_7$ are insulating and show an anomaly at $\sim$176 K on magnetic susceptibility. The transition-like behaviors of La$_3$Ni$_2$O$_7$ and La$_3$Ni$_2$O$_6$ are analogous to the charge and spin order observed in La$_4$Ni$_3$O$_{10}$ and La$_4$Ni$_3$O$_8$, suggesting charge and spin order is a common feature in the ternary La-Ni-O system with mixed-valent states of nickel.
description: 7 pages, 4 figures, 2 tables
The relation between accretion rates and the initial mass function in hydrodynamical simulations of star formation
Creators: name: Maschberger, Th.
name: Bonnell, I. A.
name: Clarke, C. J.
name: Moraux, E.
Publisher: name: arXiv
Year: 2013
Subjects: subject: Astrophysics of Galaxies (astro-ph.GA)
subject: Solar and Stellar Astrophysics (astro-ph.SR)
subject: FOS: Physical sciences

description: We analyse a hydrodynamical simulation of star formation. Sink particles in the simulations which represent stars show episodic growth, which is presumably accretion from a core that can be regularly replenished in response to the fluctuating conditions in the local environment. The accretion rates follow $\dot{m} \propto m^{2/3}$, as expected from accretion in a gas-dominated potential, but with substantial variations over-laid on this. The growth times follow an exponential distribution which is tapered at long times due to the finite length of the simulation. The initial collapse masses have an approximately lognormal distribution with already an onset of a power-law at large masses. The sink particle mass function can be reproduced with a non-linear stochastic process, with fluctuating accretion rates $\propto m^{2/3}$, a distribution of seed masses and a distribution of growth times. All three factors contribute equally to the form of the final sink mass function. We find that the upper power law tail of the IMF is unrelated to Bondi-Hoyle accretion.
description: 13 pages, 13 figures, MNRAS accepted
A Fragmentation Approach to Jet Flavor
Creators: name: Caletti, Simone
name: Larkoski, Andrew J.
name: Marzani, Simone
name: Reichelt, Daniel
Publisher: name: arXiv
Year: 2022
Subjects: subject: High Energy Physics - Phenomenology (hep-ph)
subject: FOS: Physical sciences

description: An intuitive definition of the partonic flavor of a jet in quantum chromodynamics is often only well-defined in the deep ultraviolet, where the strong force becomes a free theory and a jet consists of a single parton. However, measurements are performed in the infrared, where a jet consists of numerous particles and requires an algorithmic procedure to define their phase space boundaries. To connect these two regimes, we introduce a novel and simple partonic jet flavor definition in the infrared. We define the jet flavor to be the net flavor of the partons that lie exactly along the direction of the Winner-Take-All recombination scheme axis of the jet, which is safe to all orders under emissions of soft particles, but is not collinear safe. Collinear divergences can be absorbed into a perturbative fragmentation function that describes the evolution of the jet flavor from the ultraviolet to the infrared. The evolution equations are linear and a small modification to traditional DGLAP and we solve them to leading-logarithmic accuracy. The evolution equations exhibit fixed points in the deep infrared, we demonstrate quantitative agreement with parton shower simulations, and we present various infrared and collinear safe observables that are sensitive to this flavor definition.
description: 29 pages, 7 figures; version submitted to the journal
COOPERNAUT: End-to-End Driving with Cooperative Perception for Networked Vehicles
Creators: name: Cui, Jiaxun
name: Qiu, Hang
name: Chen, Dian
name: Stone, Peter
name: Zhu, Yuke
Publisher: name: arXiv
Year: 2022
Subjects: subject: Computer Vision and Pattern Recognition (cs.CV)
subject: Robotics (cs.RO)
subject: FOS: Computer and information sciences

description: Optical sensors and learning algorithms for autonomous vehicles have dramatically advanced in the past few years. Nonetheless, the reliability of today's autonomous vehicles is hindered by the limited line-of-sight sensing capability and the brittleness of data-driven methods in handling extreme situations. With recent developments of telecommunication technologies, cooperative perception with vehicle-to-vehicle communications has become a promising paradigm to enhance autonomous driving in dangerous or emergency situations. We introduce COOPERNAUT, an end-to-end learning model that uses cross-vehicle perception for vision-based cooperative driving. Our model encodes LiDAR information into compact point-based representations that can be transmitted as messages between vehicles via realistic wireless channels. To evaluate our model, we develop AutoCastSim, a network-augmented driving simulation framework with example accident-prone scenarios. Our experiments on AutoCastSim suggest that our cooperative perception driving models lead to a 40% improvement in average success rate over egocentric driving models in these challenging driving situations and a 5 times smaller bandwidth requirement than prior work V2VNet. COOPERNAUT and AUTOCASTSIM are available at https://ut-austin-rpl.github.io/Coopernaut/.
Dark MaGICC: the effect of Dark Energy on galaxy formation. Cosmology does matter
Creators: name: Penzo, Camilla
name: Macciò, Andrea V.
name: Casarini, Luciano
name: Stinson, Greg S.
name: Wadsley, James
Publisher: name: arXiv
Year: 2014
Subjects: subject: Cosmology and Nongalactic Astrophysics (astro-ph.CO)
subject: FOS: Physical sciences

description: We present the Dark MaGICC project, which aims to investigate the effect of Dark Energy (DE) modeling on galaxy formation via hydrodynamical cosmological simulations. Dark MaGICC includes four dynamical Dark Energy scenarios with time varying equations of state, one with a self-interacting Ratra-Peebles model. In each scenario we simulate three galaxies with high resolution using smoothed particle hydrodynamics (SPH). The baryonic physics model is the same used in the Making Galaxies in a Cosmological Context (MaGICC) project, and we varied only the background cosmology. We find that the Dark Energy parameterization has a surprisingly important impact on galaxy evolution and on structural properties of galaxies at z=0, in striking contrast with predictions from pure Nbody simulations. The different background evolutions can (depending on the behavior of the DE equation of state) either enhance or quench star formation with respect to a LCDM model, at a level similar to the variation of the stellar feedback parameterization, with strong effects on the final galaxy rotation curves. While overall stellar feedback is still the driving force in shaping galaxies, we show that the effect of the Dark Energy parameterization plays a larger role than previously thought, especially at lower redshifts. For this reason, the influence of Dark Energy parametrization on galaxy formation must be taken into account, especially in the era of precision cosmology.
description: 11 pages, 13 figures
Ab initio theory of free-carrier absorption in semiconductors
Creators: name: Zhang, Xiao
name: Shi, Guangsha
name: Leveillee, Joshua A.
name: Giustino, Feliciano
name: Kioupakis, Emmanouil
Publisher: name: arXiv
Year: 2022
Subjects: subject: Materials Science (cond-mat.mtrl-sci)
subject: Optics (physics.optics)
subject: FOS: Physical sciences

description: The absorption of light by free carriers in semiconductors results in optical loss for all photon wavelengths. Since free-carrier absorption competes with optical transitions across the band gap, it also reduces the efficiency of optoelectronic devices such as solar cells because it does not generate electron-hole pairs. In this work, we develop a first-principles theory of free-carrier absorption taking into account both single-particle excitations and the collective Drude term, and we demonstrate its application to the case of doped Si. We determine the free-carrier absorption coefficient as a function of carrier concentration and we obtain excellent agreement with experimental data. We identify the dominant processes that contribute to free-carrier absorption at various photon wavelengths, and analyze the results to evaluate the impact of this loss mechanism on the efficiency of Si-based optoelectronic devices.
description: 8 pages, 6 figures
Multiwavelength campaign on Mrk 509. XIII. Testing ionized-reflection models on Mrk 509
Creators: name: Boissay, R.
name: Paltani, S.
name: Ponti, G.
name: Bianchi, S.
name: Cappi, M.
name: Kaastra, J. S.
name: Petrucci, P. -O.
name: Arav, N.
name: Branduardi-Raymont, G.
name: Costantini, E.
name: Ebrero, J.
name: Kriss, G. A.
name: Mehdipour, M.
name: Pinto, C.
name: Steenbrugge, K. C.
Publisher: name: arXiv
Year: 2014
Subjects: subject: High Energy Astrophysical Phenomena (astro-ph.HE)
subject: FOS: Physical sciences

description: Active Galactic Nuclei (AGN) are the most luminous persistent objects in the universe. An excess of X-ray emission below about 2 keV, called soft-excess, is very common in Type 1 AGN spectra. The origin of this feature remains debated. Originally modeled with a blackbody, there are now several possibilities to model the soft-excess, including warm Comptonization and blurred ionized reflection. In this paper, we test ionized-reflection models on Mrk 509, a bright Seyfert 1 galaxy for which we have a unique data set, in order to determine whether it can be responsible for the strong soft-excess. We use ten simultaneous XMM-Newton and INTEGRAL observations performed every four days. We present here the results of the spectral analysis, the evolution of the parameters and the variability properties of the X-ray emission. The application of blurred ionized-reflection models leads to a very strong reflection and an extreme geometry, but fails to reproduce the broad-band spectrum of Mrk 509. Two different scenarios for blurred ionized reflection are discussed: stable geometry and lamp-post configuration. In both cases we find that the model parameters do not follow the expected relations, indicating that the model is fine-tuned to fit the data without physical justification. A large, slow variation of the soft-excess without counterpart in the hard X-rays could be explained by a change in ionization of the reflector. However, such a change does not naturally follow from the assumed geometrical configuration. Warm Comptonization remains the most probable origin of the soft-excess in this object. Nevertheless, it is possible that both ionized reflection and warm Comptonization mechanisms can explain the soft-excess in all objects, one dominating the other one, depending on the physical conditions of the disk and the corona.
description: 12 pages, A&A accepted
Absolutely $k$-Incoherent Quantum States and Spectral Inequalities for Factor Width of a Matrix
Creators: name: Johnston, Nathaniel
name: Moein, Shirin
name: Pereira, Rajesh
name: Plosker, Sarah
Publisher: name: arXiv
Year: 2022
Subjects: subject: Quantum Physics (quant-ph)
subject: FOS: Physical sciences
subject: 81P40, 15A18, 15B57

description: We investigate the set of quantum states that can be shown to be $k$-incoherent based only on their eigenvalues (equivalently, we explore which Hermitian matrices can be shown to have small factor width based only on their eigenvalues). In analogy with the absolute separability problem in quantum resource theory, we call these states "absolutely $k$-incoherent", and we derive several necessary and sufficient conditions for membership in this set. We obtain many of our results by making use of recent results concerning hyperbolicity cones associated with elementary symmetric polynomials.
description: 21 pages, 2 figures
Deep Reinforcement Learning for Computational Fluid Dynamics on HPC Systems
Creators: name: Kurz, Marius
name: Offenhäuser, Philipp
name: Viola, Dominic
name: Shcherbakov, Oleksandr
name: Resch, Michael
name: Beck, Andrea
Publisher: name: arXiv
Year: 2022
Subjects: subject: Machine Learning (cs.LG)
subject: Computational Engineering, Finance, and Science (cs.CE)
subject: FOS: Computer and information sciences

description: Reinforcement learning (RL) is highly suitable for devising control strategies in the context of dynamical systems. A prominent instance of such a dynamical system is the system of equations governing fluid dynamics. Recent research results indicate that RL-augmented computational fluid dynamics (CFD) solvers can exceed the current state of the art, for example in the field of turbulence modeling. However, while in supervised learning, the training data can be generated a priori in an offline manner, RL requires constant run-time interaction and data exchange with the CFD solver during training. In order to leverage the potential of RL-enhanced CFD, the interaction between the CFD solver and the RL algorithm thus have to be implemented efficiently on high-performance computing (HPC) hardware. To this end, we present Relexi as a scalable RL framework that bridges the gap between machine learning workflows and modern CFD solvers on HPC systems providing both components with its specialized hardware. Relexi is built with modularity in mind and allows easy integration of various HPC solvers by means of the in-memory data transfer provided by the SmartSim library. Here, we demonstrate that the Relexi framework can scale up to hundreds of parallel environment on thousands of cores. This allows to leverage modern HPC resources to either enable larger problems or faster turnaround times. Finally, we demonstrate the potential of an RL-augmented CFD solver by finding a control strategy for optimal eddy viscosity selection in large eddy simulations.
description: 11 pages, 5 figures, the code can be accessed at https://github.com/flexi-framework/relexi
WESPER: Zero-shot and Realtime Whisper to Normal Voice Conversion for Whisper-based Speech Interactions
Creators: name: Rekimoto, Jun
Publisher: name: arXiv
Year: 2023
Subjects: subject: Sound (cs.SD)
subject: Human-Computer Interaction (cs.HC)
subject: Audio and Speech Processing (eess.AS)
subject: FOS: Computer and information sciences
subject: FOS: Electrical engineering, electronic engineering, information engineering
subject: H.5.2; H.1.2; I.2.0; I.3.6

description: Recognizing whispered speech and converting it to normal speech creates many possibilities for speech interaction. Because the sound pressure of whispered speech is significantly lower than that of normal speech, it can be used as a semi-silent speech interaction in public places without being audible to others. Converting whispers to normal speech also improves the speech quality for people with speech or hearing impairments. However, conventional speech conversion techniques do not provide sufficient conversion quality or require speaker-dependent datasets consisting of pairs of whispered and normal speech utterances. To address these problems, we propose WESPER, a zero-shot, real-time whisper-to-normal speech conversion mechanism based on self-supervised learning. WESPER consists of a speech-to-unit (STU) encoder, which generates hidden speech units common to both whispered and normal speech, and a unit-to-speech (UTS) decoder, which reconstructs speech from the encoded speech units. Unlike the existing methods, this conversion is user-independent and does not require a paired dataset for whispered and normal speech. The UTS decoder can reconstruct speech in any target speaker's voice from speech units, and it requires only an unlabeled target speaker's speech data. We confirmed that the quality of the speech converted from a whisper was improved while preserving its natural prosody. Additionally, we confirmed the effectiveness of the proposed approach to perform speech reconstruction for people with speech or hearing disabilities. (project page: http://lab.rekimoto.org/projects/wesper )
description: ACM CHI 2023 paper
Parameterization of Electron Attachment Rate Constants for Common Impurities in LArTPC Detectors
Creators: name: Li, Y.
name: Bromberg, C.
name: Diwan, M.
name: Kettell, S.
name: Martynenko, S.
name: Qian, X.
name: Paolone, V.
name: Stewart, J.
name: Thorn, C.
name: Zhang, C.
Publisher: name: arXiv
Year: 2022
Subjects: subject: Instrumentation and Detectors (physics.ins-det)
subject: High Energy Physics - Experiment (hep-ex)
subject: FOS: Physical sciences

description: The ability of free electrons to drift long distances at high velocities in pure liquid argon under an applied electric field has been exploited for the past forty years to implement detectors with increasingly large volumes for high energy physics research. In this paper, we summarize the electron attachment rate constants as a function of the external electric field for common impurities in LArTPC with data from the literature. We further provide analytical functions to parameterize the data, which are useful to compare with new measurements as well as to make extrapolations.
description: 23 pages, 4 figures, Accepted by JINST
Impact of third order dispersion on nonlinear bifurcations in optical resonators
Creators: name: Leo, François
name: Coen, Stéphane
name: Kockaert, Pascal
name: Emplit, Philippe
name: Haelterman, Marc
name: Mussot, Arnaud
name: Taki, Majid
Publisher: name: arXiv
Year: 2014
Subjects: subject: Optics (physics.optics)
subject: FOS: Physical sciences

description: It is analytically shown that symmetry breaking, in dissipative systems, affects the nature of the bifurcation at onset of instability resulting in transitions from super to subcritical bifurcations. In the case of a nonlinear fiber cavity, we have derived an amplitude equation to describe the nonlinear dynamics above threshold. An analytical expression of the critical transition curve is obtained and the predictions are in excellent agreement with the numerical solutions of the full dynamical model.
description: 5 pages, 2 figures
Magneto-Transport Properties of Kagome Magnet TmMn$_6$Sn$_6$
Creators: name: Wang, Bin
name: Yi, Enkui
name: Li, Leyi
name: Qin, Jianwei
name: Hu, Bing-Feng
name: Shen, Bing
name: Wang, Meng
Publisher: name: arXiv
Year: 2022
Subjects: subject: Strongly Correlated Electrons (cond-mat.str-el)
subject: FOS: Physical sciences

description: Kagome magnet usually hosts nontrivial electronic or magnetic states drawing great interests in condensed matter physics. In this paper, we report a systematic study on transport properties of kagome magnet TmMn$_6$Sn$_6$. The prominent topological Hall effect (THE) has been observed in a wide temperature region spanning over several magnetic phases and exhibits strong temperature and field dependence. This novel phenomenon due to non-zero spin chirality indicates possible appearance of nontrival magnetic states accompanying with strong fluctuations. The planar applied field drives planar Hall effect(PHE) and anistropic magnetoresisitivity(PAMR) exhibiting sharp disconnections in angular dependent planar resistivity violating the empirical law. By using an effective field, we identify a magnetic transition separating the PAMR into two groups belonging to various magnetic states. We extended the empirical formula to scale the field and temperature dependent planar magnetoresistivity and provide the understandings for planar transport behaviors with the crossover between various magnetic states. Our results shed lights on the novel transport effects in presence of multiple nontrivial magnetic states for the kagome lattice with complicated magnetic structures.
Uncertainty prediction of built-up areas from global human settlement data in the United States based on landscape metrics
Creators: name: Uhl, Johannes H.
name: Leyk, Stefan
Publisher: name: arXiv
Year: 2022
Subjects: subject: Physics and Society (physics.soc-ph)
subject: FOS: Physical sciences

description: The level of landscape heterogeneity may affect the performance of remote sensing based land use / land cover classification. However, the relationship between mapping accuracy of built-up surfaces and morphological characteristics of built-up areas has not been analyzed explicitly, and previous studies typically rely on aggregated landscape metrics to quantify the morphology of built-up areas, neglecting the fine-grained spatial variation and scale dependency of such metrics. Herein, we aim to fill this gap by assessing the associations between focal landscape metrics, derived from binary built-up surfaces, and focal data accuracy estimates. We test our approach for built-up surfaces from the Global Human Settlement Layer (GHSL) for Massachusetts (USA), by examining the explanatory power of landscape metrics for predictive modeling of commission and omission errors in the GHS-BUILT R2018A data product. We find that the Landscape Shape Index (LSI) exhibits the highest levels of correlation to focal accuracy measures. These relationships are scale-dependent, and increase with the level of spatial support. Our results are consistent across different regions within the U.S., and we find that the Recall measure has the strongest relationship to measures of built-up surface morphology across different temporal epochs and spatial resolutions. Regression analysis results (R2>0.9) indicate that it is possible to estimate commission errors in the GHSL in the absence of reference data, and that omission errors in the GHSL can be modeled without accessing the data themselves. Lastly, we test the generalizability of our predictive accuracy models to a different version of the GHSL (i.e., the GHS-BUILT-S2) covering a study area in North Carolina. We find varying levels of model transferability that increases with the spatial support at which landscape metrics and accuracy estimates are calculated.
Dark Solar Wind
Creators: name: Chang, Jae Hyeok
name: Kaplan, David E.
name: Rajendran, Surjeet
name: Ramani, Harikrishnan
name: Tanin, Erwin H.
Publisher: name: arXiv
Year: 2022
Subjects: subject: High Energy Physics - Phenomenology (hep-ph)
subject: Solar and Stellar Astrophysics (astro-ph.SR)
subject: High Energy Physics - Experiment (hep-ex)
subject: FOS: Physical sciences

description: We study the solar emission of light dark sector particles that self-interact strongly enough to self-thermalize. The resulting outflow behaves like a fluid which accelerates under its own thermal pressure to highly relativistic bulk velocities in the solar system. Compared to the ordinary non-interacting scenario, the local outflow has at least $\sim 10^3$ higher number density and correspondingly at least $\sim 10^3$ lower average energy per particle. We show how this generic phenomenon arises in a dark sector comprised of millicharged particles strongly self-interacting via a dark photon. The millicharged plasma wind emerging in this model has novel yet predictive signatures that encourages new experimental directions. This phenomenon demonstrates how a small step away from the simplest models can lead to radically different outcomes and thus motivates a broader search for dark sector particles.
An improved estimator of Shannon entropy with applications to systems with memory
Creators: name: De Gregorio, Juan
name: Sanchez, David
name: Toral, Raul
Publisher: name: arXiv
Year: 2022
Subjects: subject: Statistical Mechanics (cond-mat.stat-mech)
subject: Data Analysis, Statistics and Probability (physics.data-an)
subject: FOS: Physical sciences

description: We investigate the memory properties of discrete sequences built upon a finite number of states. We find that the block entropy can reliably determine the memory for systems modeled as Markov chains of arbitrary finite order. Further, we provide an entropy estimator that remarkably gives accurate results when correlations are present. To illustrate our findings, we calculate the memory of daily precipitation series at different locations. Our results are in agreement with existing methods being at the same time valid in the undersampled regime and independent of model selection.
Standard Model anatomy of WIMP dark matter direct detection I: weak-scale matching
Creators: name: Hill, Richard J.
name: Solon, Mikhail P.
Publisher: name: arXiv
Year: 2014
Subjects: subject: High Energy Physics - Phenomenology (hep-ph)
subject: FOS: Physical sciences

description: We present formalism necessary to determine weak-scale matching coefficients in the computation of scattering cross sections for putative dark matter candidates interacting with the Standard Model. Particular attention is paid to the heavy-particle limit. A consistent renormalization scheme in the presence of nontrivial residual masses is implemented. Two-loop diagrams appearing in the matching to gluon operators are evaluated. Details are given for the computation of matching coefficients in the universal limit of WIMP-nucleon scattering for pure states of arbitrary quantum numbers, and for singlet-doublet and doublet-triplet mixed states.
description: 59 pages, 6 figures, 1 table
Parton Distribution Functions for Pseudoscalar Mesons in the COnfining Effective Chiral Quark Theory
Creators: name: Hutauruk, Parada T. P.
name: Nam, Seung-il
Publisher: name: arXiv
Year: 2023
Subjects: subject: High Energy Physics - Phenomenology (hep-ph)
subject: Nuclear Theory (nucl-th)
subject: FOS: Physical sciences

description: This review paper presents the gluon, sea, and valence quark distributions of the pseudoscalar (PS) mesons. The calculations of the parton structure of PS mesons are performed using the Bethe-Salpeter equation-Nambu--Jona-Lasinio (BSE-NJL) model, which offers a clear description of the dynamical chiral symmetry breaking (D$χ$SB) of the low-energy nonperturbative quantum chromodynamics (QCD), with the help of the Schwinger proper-time regularization scheme that simulates the color QCD confinement. Our results for the dynamical quark mass -- which emerged from the spontaneous chiral symmetry breaking (S$χ$SB) -- are generated via the chiral condensate in the chiral limit and beyond. Results for the valence parton distribution functions for the PS meson at the factorization scale $Q = 2$ GeV are in excellent agreement with experimental data and the gluon distribution for the pion fitted well with the lattice QCD and Jefferson Lab Angular Momentum (JAM) QCD global fit analysis.
description: 9 pages, 7 figures
The $ν=5/2$ Fractional Quantum Hall State in the Presence of Alloy Disorder
Creators: name: Deng, Nianpei
name: Gardner, G. C.
name: Mondal, S.
name: Kleinbaum, E.
name: Manfra, M. J.
name: Csáthy, G. A.
Publisher: name: arXiv
Year: 2014
Subjects: subject: Mesoscale and Nanoscale Physics (cond-mat.mes-hall)
subject: Strongly Correlated Electrons (cond-mat.str-el)
subject: FOS: Physical sciences

description: We report quantitative measurements of the impact of alloy disorder on the $ν=5/2$ fractional quantum Hall state. Alloy disorder is controlled by the aluminum content $x$ in the Al$_x$Ga$_{1-x}$As channel of a quantum well. We find that the $ν=5/2$ state is suppressed with alloy scattering. To our surprise, in samples with alloy disorder the $ν=5/2$ state appears at significantly reduced mobilities when compared to samples in which alloy disorder is not the dominant scattering mechanism. Our results highlight the distinct roles of the different types of disorder present in these samples, such as the short-range alloy and the long-range Coulomb disorder.
Kinetic Alfvén solitary and rogue waves in superthermal plasmas
Creators: name: Bains, A.
name: Li, B.
name: Xia, L. -D.
Publisher: name: arXiv
Year: 2014
Subjects: subject: Plasma Physics (physics.plasm-ph)
subject: FOS: Physical sciences

description: We investigate the small but finite amplitude solitary Kinetic Alfvén waves (KAWs) in low $β$ plasmas with superthermal electrons modeled by a kappa-type distribution. A nonlinear Korteweg-de Vries (KdV) equation describing the evolution of KAWs is derived by using the standard reductive perturbation method. Examining the dependence of the nonlinear and dispersion coefficients of the KdV equation on the superthermal parameter $κ$, plasma $β$ and obliqueness of propagation, we show that these parameters may change substantially the shape and size of solitary KAW pulses. Only sub-Alfvénic, compressive solitons are supported. We then extend the study to examine kinetic Alfvén rogue waves by deriving a nonlinear Schrödinger equation from {the KdV} equation. Rational solutions that form rogue wave envelopes are obtained. We examine how the behavior of rogue waves depends on the plasma parameters in question, finding that the rogue envelopes are lowered with increasing electron superthermality whereas the opposite is true when the plasma $β$ increases. The findings of this study may find applications to low $β$ plasmas in astrophysical environments where particles are superthermally distributed.
description: accepted in Physics of Plasmas
LooperGP: A Loopable Sequence Model for Live Coding Performance using GuitarPro Tablature
Creators: name: Adkins, Sara
name: Sarmento, Pedro
name: Barthet, Mathieu
Publisher: name: arXiv
Year: 2023
Subjects: subject: Sound (cs.SD)
subject: Multimedia (cs.MM)
subject: Audio and Speech Processing (eess.AS)
subject: FOS: Computer and information sciences
subject: FOS: Electrical engineering, electronic engineering, information engineering

description: Despite their impressive offline results, deep learning models for symbolic music generation are not widely used in live performances due to a deficit of musically meaningful control parameters and a lack of structured musical form in their outputs. To address these issues we introduce LooperGP, a method for steering a Transformer-XL model towards generating loopable musical phrases of a specified number of bars and time signature, enabling a tool for live coding performances. We show that by training LooperGP on a dataset of 93,681 musical loops extracted from the DadaGP dataset, we are able to steer its generative output towards generating 3x as many loopable phrases as our baseline. In a subjective listening test conducted by 31 participants, LooperGP loops achieved positive median ratings in originality, musical coherence and loop smoothness, demonstrating its potential as a performance tool.
description: The Version of Record of this contribution is published in Proceedings of EvoMUSART: International Conference on Computational Intelligence in Music, Sound, Art and Design (Part of EvoStar) 2023