cometadata/datacite-rtg-text-other-reclassification-records huggingface dataset:
Identifying polycentricism: a review of concepts and research challenges
Creators: name: Natalia, Venny Veronica
name: Heinrichs, Dirk
Publisher: name: Technische Universität Berlin
Year: 2019
Subjects: subject: 710 Städtebau, Raumplanung, Landschaftsgestaltung
subject: polycentricism
subject: urban centers
subject: developed world
subject: developing world
subject: indicators

description: Assessment of polycentricism is one approach to understand the process of urban expansion and its structural changes. The assessment is important to provide knowledge as a basis for future planning and policy. This review article structures the existing concepts of polycentricism, examines the methodologies applied for polycentricism assessment at different spatial scales and across world regions. Based on this, it identifies future research challenges. The review shows that studies of polycentricism have been conducted primarily in cities across the more developed world regions while in the developing world regions, fewer studies are available and only began to emerge in the 1990s, two decades later than the West. The reviewed studies use employment distribution and travel behavior as the primary sources of data. To compensate for the lack of well-documented employment distribution and mobility data, more diverse indicators and sophisticated digital-based approaches have been applied in the latest studies that focus on cities in developing world regions. The reviewed studies demonstrate for the examined cases a general shift towards polycentric development. While in the more developed world regions polycentricism is influenced by employment decentralization, in the developing world regions this phenomenon is influenced by market forces and spatial planning policies.
Computing Light-Front Wave Functions Without Light-Front Quantization: A Large-Momentum Effective Theory Approach
Creators: name: Ji, Xiangdong
name: Liu, Yizhuang
Publisher: name: arXiv
Year: 2021
Subjects: subject: High Energy Physics - Phenomenology (hep-ph)
subject: High Energy Physics - Lattice (hep-lat)
subject: Nuclear Experiment (nucl-ex)
subject: Nuclear Theory (nucl-th)
subject: FOS: Physical sciences

description: Light-front wave functions play a fundamental role in the light-front quantization approach to QCD and hadron structure. However, a naive implementation of the light-front quantization suffers from various subtleties including the well-known zero-mode problem, the associated rapidity divergences which mixes ultra-violet divergences with infrared physics, as well as breaking of spatial rotational symmetry. We advocate that the light-front quantization should be viewed as an effective theory in which small $k^+$ modes have been effectively ``integrated out'', with an infinite number of renormalization constants. Instead of solving light-front quantized field theories directly, we make the large momentum expansion of the equal-time Euclidean correlation functions in instant quantization as an effective way to systematically calculate light-front correlations, including the light-front wave function amplitudes. This large-momentum effective theory accomplishes an effective light-front quantization through lattice QCD calculations. We demonstrate our approach using an example of a pseudo-scalar meson wave function.
description: 17 pages, 8 figures
A quantitative comparison of amplitude versus intensity interferometry for astronomy
Creators: name: Bojer, Manuel
name: Huang, Zixin
name: Karl, Sebastian
name: Richter, Stefan
name: Kok, Pieter
name: von Zanthier, J.
Publisher: name: arXiv
Year: 2021
Subjects: subject: Instrumentation and Methods for Astrophysics (astro-ph.IM)
subject: Quantum Physics (quant-ph)
subject: FOS: Physical sciences

description: Astronomical imaging can be broadly classified into two types. The first type is amplitude interferometry, which includes conventional optical telescopes and Very Large Baseline Interferometry (VLBI). The second type is intensity interferometry, which relies on Hanbury Brown and Twiss-type measurements. At optical frequencies, where direct phase measurements are impossible, amplitude interferometry has an effective numerical aperture that is limited by the distance from which photons can coherently interfere. Intensity interferometry, on the other hand, correlates only photon fluxes and can thus support much larger numerical apertures, but suffers from a reduced signal due to the low average photon number per mode in thermal light. It has hitherto not been clear which method is superior under realistic conditions. Here, we give a comparative analysis of the performance of amplitude and intensity interferometry, and we relate this to the fundamental resolution limit that can be achieved in any physical measurement. Using the benchmark problem of determining the separation between two distant thermal point sources, e.g., two adjacent stars, we give a short tutorial on optimal estimation theory and apply it to stellar interferometry. We find that for very small angular separations the large baseline achievable in intensity interferometry can more than compensate for the reduced signal strength. We also explore options for practical implementations of Very Large Baseline Intensity Interferometry (VLBII).
A new look at calendar anomalies: Multifractality and day of the week effect
Creators: name: Stosic, Darko
name: Stosic, Dusan
name: Vodenska, Irena
name: Stanley, H. Eugene
name: Stosic, Tatijana
Publisher: name: arXiv
Year: 2021
Subjects: subject: Statistical Finance (q-fin.ST)
subject: FOS: Economics and business

description: Stock markets can become inefficient due to calendar anomalies known as day-of-the-week effect. Calendar anomalies are well-known in financial literature, but the phenomena remain to be explored in econophysics. In this paper we use multifractal analysis to evaluate if the temporal dynamics of market returns also exhibits calendar anomalies such as day-of-the-week effects. We apply the multifractal detrended fluctuation analysis (MF-DFA) to daily returns of market indices around the world for each day of the week. Our results indicate that individual days of the week are characterized by distinct multifractal properties. Monday returns tend to exhibit more persistent behavior and richer multifractal structures than other day-resolved returns. Shuffling the series reveals that multifractality arises both from a broad probability density function and from long-term correlations. From the time-dependent multifractal analysis we find that multifractal spectra for Monday returns are much wider than for other days during periods of financial crises. The presence of day-of-the-week effects in multifractal dynamics of market returns motivates further research on calendar anomalies from an econophysics perspective.
On the wall velocity dependence of electroweak baryogenesis
Creators: name: Dorsch, Glauber C.
name: Huber, Stephan J.
name: Konstandin, Thomas
Publisher: name: arXiv
Year: 2021
Subjects: subject: High Energy Physics - Phenomenology (hep-ph)
subject: Cosmology and Nongalactic Astrophysics (astro-ph.CO)
subject: FOS: Physical sciences

description: We re-evaluate the status of supersonic electroweak baryogenesis using a generalized fluid Ansatz for the non-equilibrium distribution functions. Instead of truncating the expansion to first order in momentum, we allow for higher order terms as well, including up to 21 fluctuations. The collision terms are computed analytically at leading-log accuracy. We also point out inconsistencies in the standard treatments of transport in electroweak baryogenesis, arguing that one cannot do without specifying an Ansatz for the distribution function. We present the first analysis of baryogenesis using the fluid approximation to higher orders. Our results support the recent findings that baryogenesis may indeed be possible even in the presence of supersonic wall velocities.
The impact of methadone maintenance therapy on heptatis c incidence among illicit drug users
Creators: name: Nolan, Seonaid
name: Dias Lima, Viviane
name: Fairbairn, Nadia
name: Kerr, Thomas
name: Montaner, Julio
name: Grebely, Jason
name: Wood, Evan
Publisher: name: The University of British Columbia
Year: 2017

description: Aims To determine the relationship between methadone maintenance therapy (MMT) and hepatitis C (HCV) seroconversion among illicit drug users. Design Generalized Estimating Equation model assuming a binomial distribution and a logit link function was used to examine for a possible protective effect of MMT use on HCV incidence. Setting Data from three prospective cohort studies of illicit drug users in Vancouver, Canada between 1996 and 2012. Participants 1004 HCV antibody negative illicit drug users stratified by exposure to MMT. Measurements Baseline and semi-annual HCV antibody testing and standardised interviewer administered questionnaire soliciting self-reported data relating to drug use patterns, risk behaviours, detailed sociodemographic data and status of active participation in an MMT program. Findings 184 HCV seroconversions were observed for an HCV incidence density of 6.32 [95% confidence interval [CI]: 5.44 – 7.31] per 100 person-years. After adjusting for potential confounders, MMT exposure was protective against HCV seroconversion (Adjusted Odds Ratio [AOR] = 0.47; 95% CI: 0.29 - 0.76). In sub-analyses, a dose-response protective effect of increasing MMT exposure on HCV incidence (AOR = 0.87; 95% CI: 0.78 – 0.97) per increasing 6-month period exposed to MMT was observed. Conclusion Participation in methadone maintenance treatment appears to be highly protective against hepatitis C incidence among illicit drug users. There appears to be a dose-response protective effect of increasing methadone exposure on hepatitis C incidence.
Architecture optimisation of embedded systems under uncertainty in probabilistic reliability evaluation model parameters
Creators: name: Meedeniya, Indika
Publisher: name: Swinburne
Year: 2024

description: Software plays a vital role in most of the embedded systems including safety and mission-critical systems in avionics, automotive, nuclear and medical applications. Along with the functional complexity of software, the quality of software-intensive systems has become a crucial concern. Numerous techniques are being developed to evaluate the quality of a software system from its architecture in terms of quality attributes such as reliability, safety and performance, and to automate the search for alternative designs which provides good trade-offs with respect to those quality attributes of interest. However, the results of these quantitative architecture evaluations depend on design-time estimates for a series of model parameters, which may not be accurate and can change at run-time. Conventional approaches use numerical values (point estimates) as design-time estimates, where the uncertainty in the parameter estimation is not part of the evaluation. As a result, architecture-based quality evaluations at design-time can be inaccurate and thus, sub-optimal design decisions may be taken. To overcome this problem, this thesis presents a novel design-time architecture evaluation and optimisation approach that incorporates parameter uncertainties. The work specifically focuses on architecture-based reliability evaluation models, where a number of parameters have to be estimated subject to heterogeneous uncertain factors. Instead of using point-estimates for architecture-based reliability evaluation models, this work proposes to incorporate heterogeneous and diverse uncertainty information into the reliability evaluation and architecture optimisation. A framework is devised which can capture uncertainty information associated with parameters and use them for the search for robust and optimal candidate architectures. This approach is able to find good architecture solutions that can tolerate the impact of the uncertainties, and thus provides better decision support. The accuracy and scalability of the presented approach is validated with an industrial case study and a series of experiments with generated examples in different problem sizes and characteristics.
Measuring the repertoire of age-related behavioral changes in Drosophila melanogaster
Creators: name: Overman, Katherine E.
name: Choi, Daniel M.
name: Leung, Kawai
name: Shaevitz, Joshua W.
name: Berman, Gordon J.
Publisher: name: arXiv
Year: 2021
Subjects: subject: Quantitative Methods (q-bio.QM)
subject: Biological Physics (physics.bio-ph)
subject: FOS: Biological sciences
subject: FOS: Physical sciences

description: Aging affects almost all aspects of an organism -- its morphology, its physiology, its behavior. Isolating which biological mechanisms are regulating these changes, however, has proven difficult, potentially due to our inability to characterize the full repertoire of an animal's behavior across the lifespan. Using data from fruit flies (D. melanogaster) we measure the full repertoire of behaviors as a function of age. We observe a sexually dimorphic pattern of changes in the behavioral repertoire during aging. Although the stereotypy of the behaviors and the complexity of the repertoire overall remains relatively unchanged, we find evidence that the observed alterations in behavior can be explained by changing the fly's overall energy budget, suggesting potential connections between metabolism, aging, and behavior.
Site-Agnostic 3D Dose Distribution Prediction with Deep Learning Neural Networks
Creators: name: Mashayekhi, Maryam
name: Tapia, Itzel Ramirez
name: Balagopal, Anjali
name: Zhong, Xinran
name: Barkousaraie, Azar Sadeghnejad
name: McBeth, Rafe
name: Lin, Mu-Han
name: Jiang, Steve
name: Nguyen, Dan
Publisher: name: arXiv
Year: 2021
Subjects: subject: Machine Learning (cs.LG)
subject: Artificial Intelligence (cs.AI)
subject: Medical Physics (physics.med-ph)
subject: FOS: Computer and information sciences
subject: FOS: Physical sciences

description: Typically, the current dose prediction models are limited to small amounts of data and require re-training for a specific site, often leading to suboptimal performance. We propose a site-agnostic, 3D dose distribution prediction model using deep learning that can leverage data from any treatment site, thus increasing the total data available to train the model. Applying our proposed model to a new target treatment site requires only a brief fine-tuning of the model to the new data and involves no modifications to the model input channels or its parameters. Thus, it can be efficiently adapted to a different treatment site, even with a small training dataset.
Relationship between physical activities and chili consumption on anti-oxidative effects and autonomic nervous system activities in healthy volunteers
Creators: name: Lasopa, Arisa
Publisher: name: Faculty of Pharmaceutical Sciences KKU MSU UBU
Year: 2020
Subjects: capsaicin, heart rate variability or HRV, physical activity, oxidative stress, chili

description: Isan Journal ofPharmaceutical Sciences, 16, 2, 57-73
Practical Barriers and Ethical Challenges in Genetic Data Sharing
Creators: name: Simpson, Claire L.
name: Goldenberg, Aaron J.
name: Culverhouse, Rob
name: Daley, Denise
name: Igo, Robert P.
name: Jarvik, Gail P.
name: Mandal, Diptasri M.
name: Mascalzoni, Deborah
name: Montgomery, Courtney Gray
name: Pierce, Brandon L.
name: Plaetke, Rosemarie
name: Shete, Sanjay
name: Goddard, Katrina A. B.
name: Stein, Catherine M.
Publisher: name: Multidisciplinary Digital Publishing Institute
Year: 2019

description: The underlying ethos of dbGaP is that access to these data by secondary data analysts facilitates advancement of science. NIH has required that genome-wide association study data be deposited in the Database of Genotypes and Phenotypes (dbGaP) since 2003. In 2013, a proposed updated policy extended this requirement to next-generation sequencing data. However, recent literature and anecdotal reports suggest lingering logistical and ethical concerns about subject identifiability, informed consent, publication embargo enforcement, and difficulty in accessing dbGaP data. We surveyed the International Genetic Epidemiology Society (IGES) membership about their experiences. One hundred and seventy five (175) individuals completed the survey, a response rate of 27%. Of respondents who received data from dbGaP (43%), only 32% perceived the application process as easy but most (75%) received data within five months. Remaining challenges include difficulty in identifying an institutional signing official and an overlong application process. Only 24% of respondents had contributed data to dbGaP. Of these, 31% reported local IRB restrictions on data release; an additional 15% had to reconsent study participants before depositing data. The majority of respondents (56%) disagreed that the publication embargo period was sufficient. In response, we recommend longer embargo periods and use of varied data-sharing models rather than a one-size-fits-all approach.
Constraining gravitational wave velocities using gravitational and electromagnetic wave observations of white dwarf binaries
Creators: name: Cao, Tian-Yong
name: Kumar, Ankit
name: Yi, Shu-Xu
Publisher: name: arXiv
Year: 2024
Subjects: subject: General Relativity and Quantum Cosmology (gr-qc)
subject: FOS: Physical sciences

description: Although the general theory of relativity (GR) predicts that gravitational waves (GWs) have exactly the same propagation velocity as electromagnetic (EM) waves, many theories of gravity beyond GR expect otherwise. Accurate measurement of the difference in their propagation speed, or a tight constraint on it, could be crucial to validate or put limits on theories beyond GR. The proposed future space-borne GW detectors are poised to detect a substantial number of Galactic white dwarf binaries (GWDBs), which emit the GW as semi-monochromatic signals. Concurrently, these GWDBs can also be identified as optical variable sources. Here we proposed that allocating a GWDB's optical light curve and contemporaneous GW signal can be used to trace the difference between the velocity of GW and EM waves. Simulating GW and EM wave data from 14 verification binaries (VBs), our method constrains propagation-originated phase differences, limiting the discrepancy between the speed of light ($c$) and GW ($c_{GW}$). Through the utilization of LISA's design sensitivity and the current precision in optical observation on GWDB, our study reveals that a four-year observation of the 14 recognized VBs results in a joint constraint that confines $Δc/c$ ($Δc = c_{\mathrm{GW}} - c$) to the range of $-2.1\times10^{-12}$ and $4.8\times10^{-12}$. Additionally, by incorporating this constraint on $c_{\mathrm{GW}}$, we are able to establish boundaries for the mass of the graviton, limiting it to $m_{\mathrm{g}}\le3\times10^{-23}\,e\mathrm{V}/c^{2}$, and for the parameter associated with local Lorentz violation, $\bar{s}_{00}$, constrained within the range of $-3.4\times10^{-11}\le\bar{s}_{00}\le1.5\times10^{-11}$.
description: 10 pages, 10 figures
The host galaxy and persistent radio counterpart of FRB 20201124A
Creators: name: Ravi, Vikram
name: Law, Casey J.
name: Li, Dongzi
name: Aggarwal, Kshitij
name: Burke-Spolaor, Sarah
name: Connor, Liam
name: Lazio, T. Joseph W.
name: Simard, Dana
name: Somalwar, Jean
name: Tendulkar, Shriharsh P.
Publisher: name: arXiv
Year: 2021
Subjects: subject: High Energy Astrophysical Phenomena (astro-ph.HE)
subject: Astrophysics of Galaxies (astro-ph.GA)
subject: FOS: Physical sciences

description: The physical properties of fast radio burst (FRB) host galaxies provide important clues towards the nature of FRB sources. The 16 FRB hosts identified thus far span three orders of magnitude in mass and specific star-formation rate, implicating a ubiquitously occurring progenitor object. FRBs localised with ~arcsecond accuracy also enable effective searches for associated multi-wavelength and multi-timescale counterparts, such as the persistent radio source associated with FRB 20121102A. Here we present a localisation of the repeating source FRB 20201124A, and its association with a host galaxy (SDSS J050803.48+260338.0, z=0.098) and persistent radio source. The galaxy is massive ($\sim3\times10^{10} M_{\odot}$), star-forming (few solar masses per year), and dusty. Very Large Array and Very Long Baseline Array observations of the persistent radio source measure a luminosity of $1.2\times10^{29}$ erg s$^{-1}$ Hz$^{-1}$, and show that is extended on scales $\gtrsim50$ mas. We associate this radio emission with the ongoing star-formation activity in SDSS J050803.48+260338.0. Deeper, more detailed observations are required to better utilise the milliarcsecond-scale localisation of FRB 20201124A reported from the European VLBI Network, and determine the origin of the large dispersion measure ($150-220$ pc cm$^{-3}$) contributed by the host. SDSS J050803.48+260338.0 is an order of magnitude more massive than any galaxy or stellar system previously associated with a repeating FRB source, but is comparable to the hosts of so far non-repeating FRBs, further building the link between the two apparent populations.
description: 9 pages, 6 figures, 1 table, submitted to MNRAS
Sparse Linear Spectral Unmixing of Hyperspectral images using Expectation-Propagation
Creators: name: Li, Zeng
name: Altmann, Yoann
name: Chen, Jie
name: Mclaughlin, Stephen
name: Rahardja, Susanto
Publisher: name: arXiv
Year: 2021
Subjects: subject: Applications (stat.AP)
subject: Image and Video Processing (eess.IV)
subject: FOS: Computer and information sciences
subject: FOS: Electrical engineering, electronic engineering, information engineering

description: This paper presents a novel Bayesian approach for hyperspectral image unmixing. The observed pixels are modeled by a linear combination of material signatures weighted by their corresponding abundances. A spike-and-slab abundance prior is adopted to promote sparse mixtures and an Ising prior model is used to capture spatial correlation of the mixture support across pixels. We approximate the posterior distribution of the abundances using the expectation-propagation (EP) method. We show that it can significantly reduce the computational complexity of the unmixing stage and meanwhile provide uncertainty measures, compared to expensive Monte Carlo strategies traditionally considered for uncertainty quantification. Moreover, many variational parameters within each EP factor can be updated in a parallel manner, which enables mapping of efficient algorithmic architectures based on graphics processing units (GPU). Under the same approximate Bayesian framework, we then extend the proposed algorithm to semi-supervised unmixing, whereby the abundances are viewed as latent variables and the expectation-maximization (EM) algorithm is used to refine the endmember matrix. Experimental results on synthetic data and real hyperspectral data illustrate the benefits of the proposed framework over state-of-art linear unmixing methods.
The effect of viscosity and resistivity on Rayleigh-Taylor instability induced mixing in magnetized high energy density plasmas
Creators: name: Bera, Ratan Kumar
name: Song, Yang
name: Srinivasan, Bhuvana
Publisher: name: arXiv
Year: 2021
Subjects: subject: Plasma Physics (physics.plasm-ph)
subject: FOS: Physical sciences

description: This work numerically investigates the role of viscosity and resistivity on Rayleigh-Taylor instabilities in magnetized high-energy-density (HED) plasmas for a high Atwood number and high plasma beta regimes surveying across plasma beta and magnetic Prandtl numbers. The numerical simulations are performed using the visco-resistive magnetohydrodynamic (MHD) equations. Results presented here show that the inclusion of self-consistent viscosity and resistivity in the system drastically changes the growth of the Rayleigh-Taylor instability (RTI) as well as modifies its internal structure at smaller scales. It is seen here that the viscosity has a stabilizing effect on the RTI. Moreover, the viscosity inhibits the development of small scale structures and also modifies the morphology of the tip of the RTI spikes. On the other hand, the resistivity reduces the magnetic field stabilization supporting the development of small scale structures. The morphology of the RTI spikes is seen to be unaffected by the presence of resistivity in the system. An additional novelty of this work is in the disparate viscosity and resistivity profiles that may exist in HED plasmas and their impact on RTI growth, morphology, and the resulting turbulence spectra. Furthermore, this work shows that the dynamics of the magnetic field is independent of viscosity and likewise the resistivity does not affect the dissipation of enstrophy and kinetic energy. In addition, power-law scalings of enstrophy, kinetic energy, and magnetic field energy are provided in both injection range and inertial sub-range which could be useful for understanding RTI induced turbulent mixing in HED laboratory and astrophysical plasmas and could aid in the interpretation of observations of RTI-induced turbulence spectra.
Parametric generation of spin waves in nano-scaled magnonic conduits
Creators: name: Heinz, Björn
name: Mohseni, Morteza
name: Lentfert, Akira
name: Verba, Roman
name: Schneider, Michael
name: Lägel, Bert
name: Levchenko, Khrystyna
name: Brächer, Thomas
name: Dubs, Carsten
name: Chumak, Andrii V.
name: Pirro, Philipp
Publisher: name: arXiv
Year: 2021
Subjects: subject: Mesoscale and Nanoscale Physics (cond-mat.mes-hall)
subject: Applied Physics (physics.app-ph)
subject: FOS: Physical sciences

description: The research feld of magnonics proposes a low-energy wave-logic computation technology based on spin waves to complement the established CMOS technology and provide a basis for emerging unconventional computation architectures. However, magnetic damping is a limiting factor for all-magnonic logic circuits and multi-device networks, ultimately rendering mechanisms to effciently manipulate and amplify spin waves a necessity. In this regard, parallel pumping is a versatile tool since it allows to selectively generate and amplify spin waves. While extensively studied in microscopic systems, nano-scaled systems are lacking investigation to assess the feasibility and potential future use of parallel pumping in magnonics. Here, we investigate a longitudinally magnetized 100 nm-wide magnonic nano-conduit using space and time-resolved micro-focused Brillouin-light-scattering spectroscopy. Employing parallel pumping to generate spin waves, we observe that the non-resonant excitation of dipolar spin waves is favored over the resonant excitation of short wavelength exchange spin waves. In addition, we utilize this technique to access the effective spin-wave relaxation time of an individual nano-conduit, observing a large relaxation time up to (115.0 +- 7.6) ns. Despite the significant decrease of the pumping effciency in the investigated nano-conduit, a reasonably small threshold is found rendering parallel pumping feasible on the nano-scale.
Tetrahedron instantons
Creators: name: Pomoni, Elli
name: Yan, Wenbin
name: Zhang, Xinyu
Publisher: name: arXiv
Year: 2021
Subjects: subject: High Energy Physics - Theory (hep-th)
subject: FOS: Physical sciences

description: We introduce and study tetrahedron instantons, which can be realized in string theory by D$1$-branes probing a configuration of intersecting D$7$-branes in flat spacetime with a proper constant $B$-field. Physically they capture instantons on $\mathbb{C}^{3}$ in the presence of the most general intersecting real codimension-two supersymmetric defects. Moreover, we construct the tetrahedron instantons as particular solutions of general instanton equations in noncommutative field theory. We analyze the moduli space of tetrahedron instantons and discuss the geometric interpretations. We compute the instanton partition function both via the equivariant localization on the moduli space of tetrahedron instantons and via the elliptic genus of the worldvolume theory on the D$1$-branes probing the intersecting D$7$-branes, obtaining the same result. The instanton partition function of the tetrahedron instantons lies between the higher-rank Donaldson-Thomas invariants on $\mathbb{C}^{3}$ and the partition function of the magnificent four model, which is conjectured to be the mother of all instanton partition functions. Finally, we show that the instanton partition function admits a free field representation, suggesting the existence of a novel kind of symmetry which acts on the cohomology of the moduli spaces of tetrahedron instantons.
description: 62 pages; v2: additional references and minor corrections; v3: numerous minor improvements
Topological phase singularities in atomically thin high-refractive-index materials
Creators: name: Ermolaev, Georgy
name: Voronin, Kirill
name: Baranov, Denis G.
name: Kravets, Vasyl
name: Tselikov, Gleb
name: Stebunov, Yury
name: Yakubovsky, Dmitry
name: Novikov, Sergey
name: Vyshnevyy, Andrey
name: Mazitov, Arslan
name: Kruglov, Ivan
name: Zhukov, Sergey
name: Romanov, Roman
name: Markeev, Andrey M.
name: Arsenin, Aleksey
name: Novoselov, Kostya S.
name: Grigorenko, Alexander N.
name: Volkov, Valentyn
Publisher: name: arXiv
Year: 2021
Subjects: subject: Optics (physics.optics)
subject: Applied Physics (physics.app-ph)
subject: FOS: Physical sciences

description: Atomically thin transition metal dichalcogenides (TMDCs) present a promising platform for numerous photonic applications due to excitonic spectral features, possibility to tune their constants by external gating, doping, or light, and mechanical stability. Utilization of such materials for sensing or optical modulation purposes would require a clever optical design, as by itself the 2D materials can offer only a small optical phase delay - consequence of the atomic thickness. To address this issue, we combine films of 2D semiconductors which exhibit excitonic lines with the Fabry-Perot resonators of the standard commercial SiO$_2$/Si substrate, in order to realize topological phase singularities in reflection. Around these singularities, reflection spectra demonstrate rapid phase changes while the structure behaves as a perfect absorber. Furthermore, we demonstrate that such topological phase singularities are ubiquitous for the entire class of atomically thin TMDCs and other high-refractive-index materials, making it a powerful tool for phase engineering in flat optics. As a practical demonstration, we employ PdSe$_2$ topological phase singularities for a refractive index sensor and demonstrate its superior phase sensitivity compared to typical surface plasmon resonance sensors.
The combined effects of buoyancy, rotation, and shear on phase boundary evolution
Creators: name: Ravichandran, S.
name: Toppaladoddi, S.
name: Wettlaufer, J. S.
Publisher: name: arXiv
Year: 2021
Subjects: subject: Fluid Dynamics (physics.flu-dyn)
subject: FOS: Physical sciences

description: We use well-resolved numerical simulations to study the combined effects of buoyancy, pressure-driven shear and rotation on the melt rate and morphology of a layer of pure solid overlying its liquid phase in three dimensions at a Rayleigh number $Ra = 1.25 \times 10^5$. During thermal convection we find that the rate of melting of the solid phase varies non-monotonically with the strength of the imposed shear flow. In the absence of rotation, depending on whether buoyancy or shear dominates the flow, we observe either domes or ridges aligned in the direction of the shear flow respectively. Furthermore, we show that the geometry of the phase boundary has important effects on the magnitude and evolution of the heat flux in the liquid layer. In the presence of rotation, the strength of which is characterized by the Rossby number, Ro, we observe that for Ro = O(1) the mean flow in the interior is perpendicular to the direction of the constant horizontal applied pressure gradient. As the magnitude of this pressure gradient increases, the geometry of solid-liquid interface evolves from the voids characteristic of melting by rotating convection, to grooves oriented perpendicular or obliquely to the direction of the pressure gradient.
description: 13 pages, 17 figures
Fast, high-fidelity Lyman $α$ forests with convolutional neural networks
Creators: name: Harrington, Peter
name: Mustafa, Mustafa
name: Dornfest, Max
name: Horowitz, Benjamin
name: Lukić, Zarija
Publisher: name: arXiv
Year: 2021
Subjects: subject: Cosmology and Nongalactic Astrophysics (astro-ph.CO)
subject: Artificial Intelligence (cs.AI)
subject: FOS: Physical sciences
subject: FOS: Computer and information sciences

description: Full-physics cosmological simulations are powerful tools for studying the formation and evolution of structure in the universe but require extreme computational resources. Here, we train a convolutional neural network to use a cheaper N-body-only simulation to reconstruct the baryon hydrodynamic variables (density, temperature, and velocity) on scales relevant to the Lyman-$α$ (Ly$α$) forest, using data from Nyx simulations. We show that our method enables rapid estimation of these fields at a resolution of $\sim$20kpc, and captures the statistics of the Ly$α$ forest with much greater accuracy than existing approximations. Because our model is fully-convolutional, we can train on smaller simulation boxes and deploy on much larger ones, enabling substantial computational savings. Furthermore, as our method produces an approximation for the hydrodynamic fields instead of Ly$α$ flux directly, it is not limited to a particular choice of ionizing background or mean transmitted flux.
description: 10 pages, 6 figures
A Low-Rank Matrix Recovery Approach for Energy Efficient EEG Acquisition for a Wireless Body Area Network
Creators: name: Majumdar, Angshul
name: Gogna, Anupriya
name: Ward, Rabab Kreidieh
Publisher: name: Multidisciplinary Digital Publishing Institute
Year: 2019

description: We address the problem of acquiring and transmitting EEG signals in Wireless Body Area Networks (WBAN) in an energy efficient fashion. In WBANs, the energy is consumed by three operations: sensing (sampling), processing and transmission. Previous studies only addressed the problem of reducing the transmission energy. For the first time, in this work, we propose a technique to reduce sensing and processing energy as well: this is achieved by randomly under-sampling the EEG signal. We depart from previous Compressed Sensing based approaches and formulate signal recovery (from under-sampled measurements) as a matrix completion problem. A new algorithm to solve the matrix completion problem is derived here. We test our proposed method and find that the reconstruction accuracy of our method is significantly better than state-of-the-art techniques; and we achieve this while saving sensing, processing and transmission energy. Simple power analysis shows that our proposed methodology consumes considerably less power compared to previous CS based techniques.
Construction of Quantum Target Space from World-Sheet States using Quantum State Tomography
Creators: name: Wani, Salman Sajad
name: Shabir, Arshid
name: Hassan, Junaid Ul
name: Kannan, S.
name: Patel, Hrishikesh
name: Sudheesh, C.
name: Faizal, Mir
Publisher: name: arXiv
Year: 2021
Subjects: subject: High Energy Physics - Theory (hep-th)
subject: Quantum Physics (quant-ph)
subject: FOS: Physical sciences

description: In this paper, we will construct the quantum states of target space coordinates from world-sheet states, using quantum state tomography. To perform quantum state tomography of an open string, we will construct suitable quadrature operators. We do this by first defining the quadrature operators in world-sheet, and then using them to construct the quantum target space quadrature operators for an open string. We will connect the quantum target space to classical geometry using coherent string states. We will be using a novel construction based on a string displacement operator to construct these coherent states. The coherent states of the world-sheet will also be used to construct the coherent states in target space.
description: 13 pages, 4 figures, 1 appendix
Exploring SMEFT Induced Non-Standard Interactions from COHERENT to Neutrino Oscillations
Creators: name: Du, Yong
name: Li, Hao-Lin
name: Tang, Jian
name: Vihonen, Sampsa
name: Yu, Jiang-Hao
Publisher: name: arXiv
Year: 2021
Subjects: subject: High Energy Physics - Phenomenology (hep-ph)
subject: High Energy Physics - Experiment (hep-ex)
subject: FOS: Physical sciences

description: We investigate the prospects of next-generation neutrino oscillation experiments DUNE, T2HK and JUNO including TAO within Standard Model Effective Field Theory (SMEFT). We also re-interpret COHERENT data in this framework. Considering both charged and neutral current neutrino Non-Standard Interactions (NSIs), we analyse dimension-6 SMEFT operators and derive lower bounds to UV scale $Λ$. The most powerful probe is obtained on ${\cal O}_{{ledq}_{1211}}$ with $Λ\gtrsim$ 450 TeV due to the electron neutrino sample in T2HK near detector. We find DUNE and JUNO to be complementary to T2HK in exploring different subsets of SMEFT operators at about 25 TeV. We conclude that near detectors play a significant role in each experiment. We also find COHERENT with CsI and LAr targets to be sensitive to new physics up to $\sim$900 GeV.
description: 48 pages, 9+9 figures, 7+5 tables, updated to account for CKM elements extracted from data properly
Bounding 3d CFT correlators
Creators: name: Paulos, Miguel F.
name: Zheng, Zechuan
Publisher: name: arXiv
Year: 2021
Subjects: subject: High Energy Physics - Theory (hep-th)
subject: FOS: Physical sciences

description: We consider the problem of bounding CFT correlators on the Euclidean section. By reformulating the question as an optimization problem, we construct functionals numerically which determine upper and lower bounds on correlators under several circumstances. A useful outcome of our analysis is that the gap maximization bootstrap problem can be reproduced by a numerically easier optimization problem. We find that the 3d Ising spin correlator takes the minimal possible allowed values on the Euclidean section. Turning to the maximization problem we find that for d > 2 there are gap-independent maximal bounds on CFT correlators. Under certain conditions we show that the maximizing correlator is given by the generalized free boson for general Euclidean kinematics. In our explorations we also uncover an intriguing 3d CFT which saturates gap, OPE maximization and correlator value bounds. Finally we comment on the relation between our functionals and the Polyakov bootstrap.
description: 34 pages, 14 figures
On the local eigenvalue statistics for random band matrices in the localization regime
Creators: name: Hislop, Peter D.
name: Krishna, M.
Publisher: name: arXiv
Year: 2021
Subjects: subject: Mathematical Physics (math-ph)
subject: Probability (math.PR)
subject: FOS: Physical sciences
subject: FOS: Mathematics
subject: 82B44, 60B20, 35J10, 81Q10, 35P20

description: We study the local eigenvalue statistics $ξ_{ω,E}^N$ associated with the eigenvalues of one-dimensional, $(2N+1) \times (2N+1)$ random band matrices with independent, identically distributed, real random variables and band width growing as $N^α$, for $0 < α< \frac{1}{2}$. We consider the limit points associated with the random variables $ξ_{ω,E}^N [I]$, for $I \subset \mathbb{R}$, and $E \in (-2,2)$. For Gaussian distributed random variables with $0 \leq α< \frac{1}{7}$, we prove that this family of random variables has nontrivial limit points for almost every $E \in (-2,2)$, and that these limit points are Poisson distributed with positive intensities. The proof is based on an analysis of the characteristic functions of the random variables $ξ_{ω,E}^N [I]$ and associated quantities related to the intensities, as $N$ tends towards infinity, and employs known localization bounds of \cite{schenker, peled, et. al.}, and the strong Wegner and Minami estimates \cite{peled, et. al.}. Our more general result applies to random band matrices with random variables having absolutely continuous distributions with bounded densities. Under the hypothesis that the localization bounds hold for $0 < α< \frac{1}{2}$, we prove that any nontrivial limit points of the random variables $ξ_{ω,E}^N [I]$ are distributed according to Poisson distributions.
description: We improved Theorem 1.2 from compound Poisson distributions to Poisson distributions in all cases considered. We more clearly highlighted the models to which our results apply
A comparative study of eight human auditory models of monaural processing
Creators: name: Vecchi, Alejandro Osses
name: Varnet, Léo
name: Carney, Laurel H.
name: Dau, Torsten
name: Bruce, Ian C.
name: Verhulst, Sarah
name: Majdak, Piotr
Publisher: name: arXiv
Year: 2021
Subjects: subject: Audio and Speech Processing (eess.AS)
subject: Sound (cs.SD)
subject: FOS: Electrical engineering, electronic engineering, information engineering
subject: FOS: Computer and information sciences

description: A number of auditory models have been developed using diverging approaches, either physiological or perceptual, but they share comparable stages of signal processing, as they are inspired by the same constitutive parts of the auditory system. We compare eight monaural models that are openly accessible in the Auditory Modelling Toolbox. We discuss the considerations required to make the model outputs comparable to each other, as well as the results for the following model processing stages or their equivalents: Outer and middle ear, cochlear filter bank, inner hair cell, auditory nerve synapse, cochlear nucleus, and inferior colliculus. The discussion includes a list of recommendations for future applications of auditory models.
description: Revision 1 of the manuscript
Multivariate functional group sparse regression: functional predictor selection
Creators: name: Mahzarnia, Ali
name: Song, Jun
Publisher: name: arXiv
Year: 2021
Subjects: subject: Methodology (stat.ME)
subject: Statistics Theory (math.ST)
subject: Neurons and Cognition (q-bio.NC)
subject: Applications (stat.AP)
subject: Machine Learning (stat.ML)
subject: FOS: Computer and information sciences
subject: FOS: Mathematics
subject: FOS: Biological sciences

description: In this paper, we propose methods for functional predictor selection and the estimation of smooth functional coefficients simultaneously in a scalar-on-function regression problem under high-dimensional multivariate functional data setting. In particular, we develop two methods for functional group-sparse regression under a generic Hilbert space of infinite dimension. We show the convergence of algorithms and the consistency of the estimation and the selection (oracle property) under infinite-dimensional Hilbert spaces. Simulation studies show the effectiveness of the methods in both the selection and the estimation of functional coefficients. The applications to the functional magnetic resonance imaging (fMRI) reveal the regions of the human brain related to ADHD and IQ.
description: The R package that is developed for this paper is available at GitHub. See https://github.com/Ali-Mahzarnia/MFSGrp
SpectralFormer: Rethinking Hyperspectral Image Classification with Transformers
Creators: name: Hong, Danfeng
name: Han, Zhu
name: Yao, Jing
name: Gao, Lianru
name: Zhang, Bing
name: Plaza, Antonio
name: Chanussot, Jocelyn
Publisher: name: arXiv
Year: 2021
Subjects: subject: Computer Vision and Pattern Recognition (cs.CV)
subject: Artificial Intelligence (cs.AI)
subject: FOS: Computer and information sciences

description: Hyperspectral (HS) images are characterized by approximately contiguous spectral information, enabling the fine identification of materials by capturing subtle spectral discrepancies. Owing to their excellent locally contextual modeling ability, convolutional neural networks (CNNs) have been proven to be a powerful feature extractor in HS image classification. However, CNNs fail to mine and represent the sequence attributes of spectral signatures well due to the limitations of their inherent network backbone. To solve this issue, we rethink HS image classification from a sequential perspective with transformers, and propose a novel backbone network called \ul{SpectralFormer}. Beyond band-wise representations in classic transformers, SpectralFormer is capable of learning spectrally local sequence information from neighboring bands of HS images, yielding group-wise spectral embeddings. More significantly, to reduce the possibility of losing valuable information in the layer-wise propagation process, we devise a cross-layer skip connection to convey memory-like components from shallow to deep layers by adaptively learning to fuse "soft" residuals across layers. It is worth noting that the proposed SpectralFormer is a highly flexible backbone network, which can be applicable to both pixel- and patch-wise inputs. We evaluate the classification performance of the proposed SpectralFormer on three HS datasets by conducting extensive experiments, showing the superiority over classic transformers and achieving a significant improvement in comparison with state-of-the-art backbone networks. The codes of this work will be available at https://github.com/danfenghong/IEEE_TGRS_SpectralFormer for the sake of reproducibility.
Effective field theories of topological crystalline insulators and topological crystals
Creators: name: Huang, Sheng-Jie
name: Hsieh, Chang-Tse
name: Yu, Jiabin
Publisher: name: arXiv
Year: 2021
Subjects: subject: Strongly Correlated Electrons (cond-mat.str-el)
subject: Mesoscale and Nanoscale Physics (cond-mat.mes-hall)
subject: FOS: Physical sciences

description: We present a general approach to obtain effective field theories for topological crystalline insulators whose low-energy theories are described by massive Dirac fermions. We show that these phases are characterized by the responses to spatially dependent mass parameters with interfaces. These mass interfaces implement the dimensional reduction procedure such that the state of interest is smoothly deformed into a topological crystal, which serves as a representative state of a phase in the general classification. Effective field theories are obtained by integrating out the massive Dirac fermions, and various quantized topological terms are uncovered. Our approach can be generalized to other crystalline symmetry protected topological phases and provides a general strategy to derive effective field theories for such crystalline topological phases.
description: 20 pages, 10 figures, 1 table. Published version with minor changes
Quantum double aspects of surface code models
Creators: name: Cowtan, Alexander
name: Majid, Shahn
Publisher: name: arXiv
Year: 2021
Subjects: subject: Quantum Physics (quant-ph)
subject: Mathematical Physics (math-ph)
subject: Quantum Algebra (math.QA)
subject: FOS: Physical sciences
subject: FOS: Mathematics

description: We revisit the Kitaev model for fault tolerant quantum computing on a square lattice with underlying quantum double $D(G)$ symmetry, where $G$ is a finite group. We provide projection operators for its quasiparticles content as irreducible representations of $D(G)$ and combine this with $D(G)$-bimodule properties of open ribbon excitation spaces $L(s_0,s_1)$ to show how open ribbons can be used to teleport information between their endpoints $s_0,s_1$. We give a self-contained account that builds on earlier work but emphasises applications to quantum computing as surface code theory, including gates on $D(S_3)$. We show how the theory reduces to a simpler theory for toric codes in the case of $D( \Bbb Z_n)\cong \Bbb C\Bbb Z_n^2$, including toric ribbon operators and their braiding. In the other direction, we show how our constructions generalise to $D(H)$ models based on a finite-dimensional Hopf algebra $H$, including site actions of $D(H)$ and partial results on ribbon equivariance even when the Hopf algebra is not semisimple.
description: 54 pages, many figures both pdf and tkz