cssi/SciSciGPT-SciSciNet huggingface dataset:
Settling of cohesive sediment: particle-resolved simulations

We develop a physical and computational model for performing fully coupled, grain-resolved direct numerical simulations of cohesive sediment, based on the immersed boundary method. The model distributes the cohesive forces over a thin shell surrounding each particle, thereby allowing for the spatial and temporal resolution of the cohesive forces during particle–particle interactions. The influence of the cohesive forces is captured by a single dimensionless parameter in the form of a cohesion number, which represents the ratio of cohesive and gravitational forces acting on a particle. We test and validate the cohesive force model for binary particle interactions in the drafting–kissing–tumbling (DKT) configuration. Cohesive sediment grains can remain attached to each other during the tumbling phase following the initial collision, thereby giving rise to the formation of flocs. The DKT simulations demonstrate that cohesive particle pairs settle in a preferred orientation, with particles of very different sizes preferentially aligning themselves in the vertical direction, so that the smaller particle is drafted in the wake of the larger one. This preferred orientation of cohesive particle pairs is found to remain influential for systems of higher complexity. To this end, we perform large simulations of 1261 polydisperse settling particles starting from rest. These simulations reproduce several earlier experimental observations by other authors, such as the accelerated settling of sand and silt particles due to particle bonding, the stratification of cohesive sediment deposits, and the consolidation process of the deposit. They identify three characteristic phases of the polydisperse settling process, viz. (i) initial stir-up phase with limited flocculation, (ii) enhanced settling phase characterized by increased flocculation, and (iii) consolidation phase. The simulations demonstrate that cohesive forces accelerate the overall settling process primarily because smaller grains attach to larger ones and settle in their wakes. For the present cohesive number values, we observe that settling can be accelerated by up to 29 %. We propose physically based parametrization of classical hindered settling functions introduced by earlier authors, in order to account for cohesive forces. An investigation of the energy budget shows that, even though the work of the collision forces is much smaller than that of the hydrodynamic drag forces, it can substantially modify the relevant energy conversion processes.
Entanglement Dynamics of Disordered Quantum XY Chains

We consider the dynamics of the quantum XY chain with disorder under the general assumption that the expectation of the eigenfunction correlator of the associated one-particle Hamiltonian satisfies a decay estimate typical of Anderson localization. We show that, starting from a broad class of product initial states, entanglement remains bounded for all times. For the XX chain, we also derive bounds on the particle transport which, in particular, show that the density profile of initial states that consist of fully occupied and empty intervals only have significant dynamics near the edges of those intervals, uniformly for all times.
PROPERTIES OF NEAR-SUN ASTEROIDS*

Asteroids near the Sun can attain equilibrium temperatures sufficient to induce surface modification from thermal fracture, desiccation, and decomposition of hydrated silicates. We present optical observations of nine asteroids with perihelia <0.25 AU (sub-solar temperatures ≥800 K) taken to search for evidence of thermal modification. We find that the broadband colors of these objects are diverse but statistically indistinguishable from those of planet-crossing asteroids having perihelia near 1 AU. Furthermore, images of these bodies taken away from perihelion show no evidence for on-going mass-loss (model-dependent limits 1 kg s–1) that might result from thermal disintegration of the surface. We conclude that, while thermal modification may be an important process in the decay of near-Sun asteroids and in the production of debris, our new data provide no evidence for it.
Manifold learning for organizing unstructured sets of process observations

Data mining is routinely used to organize ensembles of short temporal observations so as to reconstruct useful, low-dimensional realizations of an underlying dynamical system. In this paper, we use manifold learning to organize unstructured ensembles of observations ("trials") of a system's response surface. We have no control over where every trial starts, and during each trial, operating conditions are varied by turning "agnostic" knobs, which change system parameters in a systematic, but unknown way. As one (or more) knobs "turn," we record (possibly partial) observations of the system response. We demonstrate how such partial and disorganized observation ensembles can be integrated into coherent response surfaces whose dimension and parametrization can be systematically recovered in a data-driven fashion. The approach can be justified through the Whitney and Takens embedding theorems, allowing reconstruction of manifolds/attractors through different types of observations. We demonstrate our approach by organizing unstructured observations of response surfaces, including the reconstruction of a cusp bifurcation surface for hydrogen combustion in a continuous stirred tank reactor. Finally, we demonstrate how this observation-based reconstruction naturally leads to informative transport maps between the input parameter space and output/state variable spaces.
Optimal Auction Design With Quantized Bids

This letter considers the design of an auction mechanism to sell the object of a seller when the buyers quantize their private value estimates regarding the object into binary values prior to communicating them to the seller. The designed auction mechanism maximizes the utility of the seller (i.e., the auction is optimal), prevents buyers from communicating falsified quantized bids (i.e., the auction is incentive compatible), and ensures that buyers will participate in the auction (i.e., the auction is individually rational). The letter also investigates the design of the optimal quantization thresholds using which buyers quantize their private value estimates. Numerical results provide insights regarding the influence of the quantization thresholds on the auction mechanism.
An Overview of Emergent Order in Far-from-Equilibrium Driven Systems: From Kuramoto Oscillators to Rayleigh-Bénard Convection.

Soft-matter systems when driven out of equilibrium often give rise to structures that usually lie in between the macroscopic scale of the material and microscopic scale of its constituents. In this paper we review three such systems, the two-dimensional square-lattice Ising model, the Kuramoto model and the Rayleigh–Benard convection system which when driven out of equilibrium give rise to emergent spatio-temporal order through self-organization. A common feature of these systems is that the entities that self-organize are coupled to one another in some way, either through local interactions or through a continuous media. Therefore, the general nature of non-equilibrium fluctuations of the intrinsic variables in these systems are found to follow similar trends as order emerges. Through this paper, we attempt to find connections between these systems, and systems in general which give rise to emergent order when driven out of equilibrium. This study, thus acts as a foundation for modeling a complex system as a two-state system, where the states: order and disorder can coexist as the system is driven away from equilibrium.
Ta-Nb-Mo-W refractory high-entropy alloys: Anomalous ordering behavior and its intriguing electronic origin

From electronic-structure-based thermodynamic linear response, we establish chemical ordering behavior in complex solid solutions versus how Gibbs' space is traversed---applying it on prototype refractory A2 Ta-Nb-Mo-W high-entropy alloys. Near ideal stoichiometry, this alloy has anomalous, intricate chemical ordering tendencies, with long-ranged chemical interactions that produce competing short-range order (SRO) with a crossover to spinodal segregation. This atypical SRO arises from canonical band behavior that, with alloying, creates features near the Fermi surface (well defined even with disorder) that change to simple commensurate SRO with (un)filling of these states. Our results reveal how complexity and competing electronic effects control ordering in these alloys.
Nonlinear Turbulent Dynamo during Gravitational Collapse

Via amplification by turbulent dynamo, magnetic fields can be potentially important for the formation of the first stars. To examine the dynamo behavior during the gravitational collapse of primordial gas, we extend the theory of nonlinear turbulent dynamo to include the effect of gravitational compression. The relative importance between dynamo and compression varies during contraction, with the transition from dynamo- to compression-dominated amplification of magnetic fields with the increase of density. In the nonlinear stage of magnetic field amplification with the scale-by-scale energy equipartition between turbulence and magnetic fields, reconnection diffusion of magnetic fields in ideal magnetohydrodynamic (MHD) turbulence becomes important. It causes the violation of flux-freezing condition and accounts for (a) the small growth rate of nonlinear dynamo, (b) the weak dependence of magnetic energy on density during contraction, (c) the saturated magnetic energy, and (d) the large correlation length of magnetic fields. The resulting magnetic field structure and the scaling of magnetic field strength with density are radically different from the expectations of flux-freezing.
Brane Induced Gravity:. CODIMENSION-2

We review the results of arXiv:hep-th/0703190, on brane induced gravity (BIG) in 6D. Among a large diversity of regulated codimension-2 branes, we find that for near-critical tension branes live inside very deep throats which efficiently compactify the angular dimension. In there, 4D gravity first changes to 5D, and only later to 6D. The crossover from 4D to 5D is independent of the tension, but the crossover from 5D to 6D is not. This shows how the vacuum energy problem manifests in BIG: instead of tuning vacuum energy to adjust the 4D curvature, generically one must tune it to get the desired crossover scales and the hierarchy between the scales governing the 4D → 5D → 6D transitions. In the near-critical limit, linearized perturbation theory remains under control below the crossover scale, and we find that linearized gravity around the vacuum looks like a scalar–tensor theory.
Shaping nanoparticle fingerprints at the interface of cholesteric droplets

The ordering of nanoparticles into predetermined configurations is of importance to the design of advanced technologies. Here, we balance the interfacial energy of nanoparticles against the elastic energy of cholesteric liquid crystals to dynamically shape nanoparticle assemblies at a fluid interface. By adjusting the concentration of surfactant that plays the dual role of tuning the degree of nanoparticle hydrophobicity and altering the molecular anchoring of liquid crystals, we pattern nanoparticles at the interface of cholesteric liquid crystal emulsions. In this system, interfacial assembly is tempered by elastic patterns that arise from the geometric frustration of confined cholesterics. Patterns are tunable by varying both surfactant and chiral dopant concentrations. Adjusting the particle hydrophobicity more finely by regulating the surfactant concentration and solution pH further modifies the rigidity of assemblies, giving rise to surprising assembly dynamics dictated by the underlying elasticity of the cholesteric. Because particle assembly occurs at the interface with the desired structures exposed to the surrounding water solution, we demonstrate that particles can be readily cross-linked and manipulated, forming structures that retain their shape under external perturbations. This study serves as a foundation for better understanding inter-nanoparticle interactions at interfaces by tempering their assembly with elasticity and for creating materials with chemical heterogeneity and linear, periodic structures, essential for optical and energy applications.
Stochastic single-molecule dynamics of synaptic membrane protein domains

Motivated by single-molecule experiments on synaptic membrane protein domains, we use a stochastic lattice model to study protein reaction and diffusion processes in crowded membranes. We find that the stochastic reaction-diffusion dynamics of synaptic proteins provide a simple physical mechanism for collective fluctuations in synaptic domains, the molecular turnover observed at synaptic domains, key features of the single-molecule trajectories observed for synaptic proteins, and spatially inhomogeneous protein lifetimes at the cell membrane. Our results suggest that central aspects of the single-molecule and collective dynamics observed for membrane protein domains can be understood in terms of stochastic reaction-diffusion processes at the cell membrane.
Standard Temperature and Pressure Superconductivity

Superconductivity at standard temperature and pressure is far from the extreme conditions where new fundamental laws of physics are expected to arise (Anderson in Science 177:393, 1972). Yet it is widely believed that the Landau–Ginzburg–Wilson–Fisher paradigm of broken symmetry and renormalization does not give a satisfactory account of the phenomenon (Matthias in Science 144:373, 1964). Almost a decade ago, we used the Bardeen–Cooper—Shrieffer wavefunction to show that superconductors have topological order (Bray-Ali et al. in Phys Rev B 80:180504, 2009). Here, we report progress using topological order to look for standard temperature and pressure superconductivity.
The Emerging Scholarly Brain

It is now a commonplace observation that human society is becoming a coherent super-organism, and that the information infrastructure forms its emerging brain. Perhaps, as the underlying technologies are likely to become billions of times more powerful than those we have today, we could say that we are now building the lizard brain for the future organism.
Symmetry and conservation laws in semiclassical wave packet dynamics

We formulate symmetries in semiclassical Gaussian wave packet dynamics and find the corresponding conserved quantities, particularly the semiclassical angular momentum, via Noether’s theorem. We consider two slightly different formulations of Gaussian wave packet dynamics; one is based on earlier works of Heller and Hagedorn and the other based on the symplectic-geometric approach by Lubich and others. In either case, we reveal the symplectic and Hamiltonian nature of the dynamics and formulate natural symmetry group actions in the setting to derive the corresponding conserved quantities (momentum maps). The semiclassical angular momentum inherits the essential properties of the classical angular momentum as well as naturally corresponds to the quantum picture.
Neutron diffraction in a model itinerant metal near a quantum critical point

Neutron diffraction measurements on single crystals of Cr1-xVx (x=0, 0.02, 0.037) show that the ordering moment and the Neel temperature are continuously suppressed as x approaches 0.037, a proposed Quantum Critical Point (QCP). The wave vector Q of the spin density wave (SDW) becomes more incommensurate as x increases in accordance with the two band model. At xC=0.037 we have found temperature dependent, resolution limited elastic scattering at 4 incommensurate wave vectors Q=(1 ± δ1,2, 0, 0)*2π/a, which correspond to 2 SDWs with Neel temperatures of 19 K and 300 K. Our neutron diffraction measurements indicate that the electronic structure of Cr is robust, and that tuning Cr to its QCP results not in the suppression of antiferromagnetism, but instead enables new spin ordering due to novel nesting of the Fermi surface of Cr.
The Interplay between Radiation Pressure and the Photoelectric Instability in Optically Thin Disks of Gas and Dust

In optically thin disks, dust grains are photoelectrically stripped of electrons by starlight, heating nearby gas and possibly creating a dust clumping instability—the photoelectric instability (PeI)—that significantly alters global disk structure. In the current work, we use the Pencil Code to perform the first numerical models of the PeI that include stellar radiation pressure on dust grains in order to explore the parameter regime in which the instability operates. In some models with low gas and dust surface densities, we see a variety of dust structures, including sharp concentric rings. In the most gas- and dust-rich models, nonaxisymmetric clumps, arcs, and spiral arms emerge that represent dust surface density enhancements of factors of ~5–20. In one high gas surface density model, we include a large, low-order gas viscosity and find that it observably smooths the structures that form in the gas and dust, suggesting that resolved images of a given disk may be useful for deriving constraints on the effective viscosity of its gas. Our models show that radiation pressure does not preclude the formation of complex structure from the PeI, but the qualitative manifestation of the PeI depends strongly on the parameters of the system. The PeI may provide an explanation for unusual disk morphologies, such as the moving blobs of the AU Mic disk, the asymmetric dust distribution of the 49 Ceti disk, and the rings and arcs found in the HD 141569A disk.
Khovanov Homology, Sutured Floer Homology, and Annular Links

In [28], Lawrence Roberts, extending the work of Ozsvath and Szabo in [23], showed how to associate to a link, L, in the complement of a fixed unknot, B ⊂ S, a spectral sequence whose E term is the Khovanov homology of a link in a thickened annulus defined in [2], and whose E term is the knot Floer homology of the preimage of B inside the double-branched cover of L. In [6], we extended [23] in a different direction, constructing for each knot K ⊂ S and each n ∈ Z+, a spectral sequence from Khovanov’s categorification of the reduced, n–colored Jones polynomial to the sutured Floer homology of a reduced n–cable of K. In the present work, we reinterpret Roberts’ result in the language of Juhasz’s sutured Floer homology [8] and show that the spectral sequence of [6] is a direct summand of the spectral sequence of [28].
Fields of character values for finite special unitary groups

Turull has described the fields of values for characters of $SL_n(q)$ in terms of the parametrization of the characters of $GL_n(q)$. In this article, we extend these results to the case of $SU_n(q)$.
Stereodynamics of rotationally inelastic scattering in cold He + HD collisions.

Stereodynamics of cold collisions has become a fertile ground for sensitive probe of molecular collisions and control of the collision outcome. A benchmark system for stereodynamic control of rotational transition is He + HD. This system was recently probed experimentally by Perreault et al. by examining quenching from j = 2 to j′ = 0 state in the v = 1 vibrational manifold of HD. Here, through explicit quantum scattering calculations on a highly accurate ab initio interaction potential for He + H2, we reveal how a combination of two shape resonances arising from l = 1 and l = 2 partial waves controls the stereodynamic outcome rather than a single l = 2 partial wave attributed in the experiment. Furthermore, for collision energies below 0.5 cm−1, it is shown that stereodynamic preference for the integral cross section follows a simple universal trend.
Three-Dimensional Simulations of Tearing and Intermittency in Coronal Jets

Observations of coronal jets increasingly suggest that local fragmentation and intermittency play an important role in the dynamics of these events. In this work we investigate this fragmentation in high-resolution simulations of jets in the closed-field corona. We study two realizations of the embedded-bipole model, whereby impulsive helical out flows are driven by reconnection between twisted and untwisted field across the domed fan plane of a magnetic null. We find that the reconnection region fragments following the onset of a tearing-like instability, producing multiple magnetic null points and flux-rope structures within the current layer. The flux ropes formed within the weak- field region in the center of the current layer are associated with \blobs" of density enhancement that become filamentary threads as the flux ropes are ejected from the layer, whereupon new flux ropes form behind them. This repeated formation and ejection of flux ropes provides a natural explanation for the intermittent out flows, bright blobs of emission, and filamentary structure observed in some jets. Additional observational signatures of this process are discussed. Essentially all jet models invoke reconnection between regions of locally closed and locally open field as the jet-generation mechanism. Therefore, we suggest that this repeated tearing process should occur at the separatrix surface between the two flux systems in all jets. A schematic picture of tearing-mediated jet reconnection in three dimensions is outlined.
The effect of student learning styles on the learning gains achieved when interactive simulations are coupled with real-time formative assessment via pen-enabled mobile technology

This paper describes results from a project in an undergraduate engineering physics course that coupled classroom use of interactive computer simulations with the collection of real-time formative assessment using pen-enabled mobile technology. Interactive simulations (free or textbook-based) are widely used across the undergraduate engineering curriculum to help actively engaged students increase their understanding of abstract concepts or phenomena which are not directly or easily observable. However, there are indications in the literature that we do not yet know the pedagogical best practices associated with their use to maximize learning. This project couples student use of interactive simulations with the gathering of real-time formative assessment via pen-enabled mobile technology (in this case, Tablet PCs). The research question addressed in this paper is: are learning gains achieved with this coupled model greater for certain types of learners in the undergraduate engineering classroom? To answer this, we correlate learning gains with various learning styles, as identified using the Index of Learning Styles (ILS) developed by Felder and Soloman. These insights will be useful for others who use interactive computer simulations in their instruction and other adopters of this pedagogical model; the insights may have broader implications about modification of instruction to address various learning styles.
Ground State Energy of the Low Density Hubbard Model

We derive a lower bound on the ground state energy of the Hubbard model for given value of the total spin. In combination with the upper bound derived previously by Giuliani (J. Math. Phys. 48:023302, [2007]), our result proves that in the low density limit the leading order correction compared to the ground state energy of a non-interacting lattice Fermi gas is given by 8π a ϱ u ϱ d , where ϱ u(d) denotes the density of the spin-up (down) particles, and a is the scattering length of the contact interaction potential. This result extends previous work on the corresponding continuum model to the lattice case.
Bad Global Minima Exist and SGD Can Reach Them

Several recent works have aimed to explain why severely overparameterized models, generalize well when trained by Stochastic Gradient Descent (SGD). The emergent consensus explanation has two parts: the first is that there are "no bad local minima", while the second is that SGD performs implicit regularization by having a bias towards low complexity models. We revisit both of these ideas in the context of image classification with common deep neural network architectures. Our first finding is that there exist bad global minima, i.e., models that fit the training set perfectly, yet have poor generalization. Our second finding is that given only unlabeled training data, we can easily construct initializations that will cause SGD to quickly converge to such bad global minima. For example, on CIFAR, CINIC10, and (Restricted) ImageNet, this can be achieved by starting SGD at a model derived by fitting random labels on the training data: while subsequent SGD training (with the correct labels) will reach zero training error, the resulting model will exhibit a test accuracy degradation of up to 40% compared to training from a random initialization. Finally, we show that regularization seems to provide SGD with an escape route: once heuristics such as data augmentation are used, starting from a complex model (adversarial initialization) has no effect on the test accuracy.
Light programmable micro/nanomotors with optically tunable in-phase electric polarization

To develop active nanomaterials that can instantly respond to external stimuli with designed mechanical motions is an important step towards the realization of nanorobots. Herein, we present our finding of a versatile working mechanism that allows instantaneous change of alignment direction and speed of semiconductor nanowires in an external electric field with simple visible-light exposure. The light induced alignment switch can be cycled over hundreds of times and programmed to express words in Morse code. With theoretical analysis and simulation, the working principle can be attributed to the optically tuned real-part (in-phase) electrical polarization of a semiconductor nanowire in aqueous suspension. The manipulation principle is exploited to create a new type of microscale stepper motor that can readily switch between in-phase and out-phase modes, and agilely operate independent of neighboring motors with patterned light. This work could inspire the development of new types of micro/nanomachines with individual and reconfigurable maneuverability for many applications.
Generalizing Tanisaki's ideal via ideals of truncated symmetric functions

We define a family of ideals I h in the polynomial ring ?[x 1,?,x n ] that are parameterized by Hessenberg functions h (equivalently Dyck paths or ample partitions). The ideals I h generalize algebraically a family of ideals called the Tanisaki ideal, which is used in a geometric construction of permutation representations called Springer theory. To define I h , we use polynomials in a proper subset of the variables {x 1,?,x n } that are symmetric under the corresponding permutation subgroup. We call these polynomials truncated symmetric functions and show combinatorial identities relating different kinds of truncated symmetric polynomials. We then prove several key properties of I h , including that if h>h? in the natural partial order on Dyck paths, then I h ?I h?, and explicitly construct a Grobner basis for I h . We use a second family of ideals J h for which some of the claims are easier to see and prove that I h =J h . The ideals J h arise in work of Ding, Develin-Martin-Reiner, and Gasharov-Reiner on a family of Schubert varieties called partition varieties. Using earlier work of the first author, the current manuscript proves that the ideals I h =J h generalize the Tanisaki ideals both algebraically and geometrically, from Springer varieties to a family of nilpotent Hessenberg varieties.
Design of Extra Robotic Legs for Augmenting Human Payload Capabilities by Exploiting Singularity and Torque Redistribution

We present the design of a new robotic human augmentation system that will assist the operator in carrying a heavy payload, reaching and maintaining difficult postures, and ultimately better performing their job. The Extra Robotic Legs (XRL) system is worn by the operator and consists of two articulated robotic legs that move with the operator to bear a heavy payload. The design was driven by a need to increase the effectiveness of hazardous material emergency response personnel who are encumbered by their personal protective equipment (PPE). The legs will ultimately walk, climb stairs, crouch down, and crawl with the operator while eliminating all external PPE loads on the operator. The forces involved in the most extreme loading cases were analyzed to find an effective strategy for reducing actuator loads. The analysis reveals that the maximum torque is exerted during the transition from the crawling to standing mode of motion. Peak torques are significantly reduced by leveraging redundancy in force application resulting from a closed-loop kinematic chain formed by a particular posture of the XRL. The actuators, power systems, and transmission elements were designed from the results of these analyses. Using differential mechanisms to combine the inputs of multiple actuators into a single degree of freedom, the gear reductions needed to bear the heavy loads could be kept at a minimum, enabling high bandwidth force control due to the near-direct-drive transmission. A prototype was fabricated utilizing the insights gained from these analyses and initial tests indicate the feasibility of the XRL system.
Vector Riemann–Hilbert problem with almost periodic and meromorphic coefficients and applications

The vector Riemann–Hilbert problem is analysed when the entries of its matrix coefficient are meromorphic and almost periodic functions. Three cases for the meromorphic functions, when they have (i) a finite number of poles and zeros (rational functions), (ii) periodic poles and zeros, and (iii) an infinite number of non-periodic zeros and poles, are considered. The first case is illustrated by the heat equation for a composite rod with a finite number of discontinuities and a system of convolution equations; both problems are solved explicitly. In the second case, a Wiener–Hopf factorization is found in terms of the hypergeometric functions, and the exact solution of a mixed boundary value problem for the Laplace equation in a wedge is derived. In the last case, the Riemann–Hilbert problem reduces to an infinite system of linear algebraic equations with the exponential rate of convergence. As an example, the Neumann boundary value problem for the Helmholtz equation in a strip with a slit is analysed.
CUSTOMIZED TRAINING WITH AN APPLICATION TO MASS SPECTROMETRIC IMAGING OF CANCER TISSUE.

We introduce a simple, interpretable strategy for making predictions on test data when the features of the test data are available at the time of model fitting. Our proposal—customized training—clusters the data to find training points close to each test point and then fits an $\ell_{1}$-regularized model (lasso) separately in each training cluster. This approach combines the local adaptivity of $k$-nearest neighbors with the interpretability of the lasso. Although we use the lasso for the model fitting, any supervised learning method can be applied to the customized training sets. We apply the method to a mass-spectrometric imaging data set from an ongoing collaboration in gastric cancer detection which demonstrates the power and interpretability of the technique. Our idea is simple but potentially useful in situations where the data have some underlying structure.
Field of view advantage of conjugate adaptive optics in microscopy applications

The imaging performance of an optical microscope can be degraded by sample-induced aberrations. A general strategy to undo the effect of these aberrations is to apply wavefront correction with a deformable mirror (DM). In most cases the DM is placed conjugate to the microscope pupil, called pupil adaptive optics (AO). When the aberrations are spatially variant an alternative configuration involves placing the DM conjugate to the main source of aberrations, called conjugate AO. We provide a theoretical and experimental comparison of both configurations for the simplified case where spatially variant aberrations are produced by a well-defined phase screen. We pay particular attention to the resulting correction field of view (FOV). Conjugate AO is found to provide a significant FOV advantage. While this result is well known in the astronomical community, our goal here is to recast it specifically for the optical microscopy community.
Bootstrapping MN and Tetragonal CFTs in Three Dimensions

Conformal field theories (CFTs) with MN and tetragonal global symmetry in $d=2+1$ dimensions are relevant for structural, antiferromagnetic and helimagnetic phase transitions in a wide class of materials. The study of these theories with the nonperturbative numerical conformal bootstrap is initiated in this work. Bounds for operator dimensions are obtained and they are found to possess sharp kinks in the MN case, suggesting the existence of full-fledged CFTs. In the tetragonal case, no new kinks are found. Estimates for critical exponents are provided for a few cases describing phase transitions in various materials. In two particular MN cases, corresponding to theories with global symmetry groups $O(2)^2\rtimes S_2$ and $O(2)^3\rtimes S_3$, a second kink is found. In the $O(2)^2\rtimes S_2$ case it is argued to be saturated by a CFT that belongs to a new universality class relevant for the structural phase transition of NbO$_2$ and paramagnetic-helimagnetic transitions of the rare-earth metals Ho and Dy. In the $O(2)^3\rtimes S_3$ case it is suggested that the CFT that saturates the second kink belongs to a new universality class relevant for the paramagnetic-antiferromagnetic phase transition of the rare-earth metal Nd.
Fast Zero-Shot Image Tagging

The well-known word analogy experiments show that the recent word vectors capture fine-grained linguistic regularities in words by linear vector offsets, but it is unclear how well the simple vector offsets can encode visual regularities over words. We study a particular image-word relevance relation in this paper. Our results show that the word vectors of relevant tags for a given image rank ahead of the irrelevant tags, along a principal direction in the word vector space. Inspired by this observation, we propose to solve image tagging by estimating the principal direction for an image. Particularly, we exploit linear mappings and nonlinear deep neural networks to approximate the principal direction from an input image. We arrive at a quite versatile tagging model. It runs fast given a test image, in constant time w.r.t. the training set size. It not only gives superior performance for the conventional tagging task on the NUSWIDE dataset, but also outperforms competitive baselines on annotating images with previously unseen tags.
Conformal operators for partially massless states

The AdS/CFT correspondence is explored for ``partially massless'' fields in AdS space (which have fewer helicity states than a massive field but more than a conventional massless field). Such fields correspond in the boundary conformal field theory to fields obeying a certain conformally-invariant differential equation that has been described by Eastwood et al. The first descendant of such a field is a conformal field of negative norm. Hence, partially massless fields may make more physical sense in de Sitter as opposed to Anti de Sitter space.
Probing the high-density behavior of symmetry energy with gravitational waves

Gravitational wave (GW) astronomy opens up an entirely new window on the Universe to probe the equations of state (EOS) of neutron-rich matter. With the advent of next-generation GW detectors, measuring the gravitational radiation from coalescing binary neutron star systems, mountains on rotating neutron stars, and stellar oscillation modes may become possible in the near future. Using a set of model EOSs satisfying the latest constraints from terrestrial nuclear experiments, state-of-the-art nuclear many-body calculations of the pure neutron matter EOS, and astrophysical observations consistently, we study various GW signatures of the high-density behavior of the nuclear symmetry energy, which is considered among the most uncertain properties of dense neutron-rich nucleonic matter. In particular, we find the tidal polarizability of neutron stars, potentially measurable in binary systems just prior to merger, is more sensitive to the high-density component of the nuclear symmetry energy than the symmetry energy at nuclear saturation density. We also find that the upper limit on the GW strain amplitude from elliptically deformed stars is very sensitive to the density dependence of the symmetry energy. This suggests that future developments in modeling of the neutron star crust, and direct gravitational wave signals from accreting binaries will provide a wealth of information on the EOS of neutron-rich matter. We also review the sensitivity of the r -mode instability window to the density dependence of the symmetry energy. Whereas models with larger values of the density slope of the symmetry energy at saturation seem to be disfavored by the current observational data, within a simple r -mode model, we point out that a subsequent softer behavior of the symmetry energy at high densities (hinted at by recent observational interpretations) could rule them in.
Which resonances in small metallic nanoparticles are plasmonic

We use time-dependent density functional theory to examine the character of various resonances corresponding to peaks in the optical response of small metallic nanoparticles. Each resonance has both 'sloshing' and 'inversion' character. The sloshing mode is an oscillation in the occupation of the shells nearest the Fermi energy, transferring charge back and forth from below the Fermi level to above it. It results in oscillation in charge density near the surface of the particle. Inversions monotonically move charge from occupied to unoccupied states, and result in oscillation in charge density in the core of the particle. We also discuss the dependence of the optical response on the size of the simulation grid, noting that the character of resonances appears stable with respect to changes in simulation size, even though the details of the spectrum change. This makes a reliable characterization possible. We consider what characteristics are important in deciding that a resonance is plasmonic.
Specifications Using Multiple-Conclusion Logic Programs

Multiset rewriting has proved to be a useful presentation of process synchronization [1, 2, 3, 6]. Since sequent calculus presentations of logics that do not use the structural rules of contractions and weakening are based on using multisets of formulas as left and right contexts, it is natural to identify processes with formulas, multisets with sequent contexts, and multiset rewriting as an inference rule. Given earlier work on using sequent calculus to describe logic programming as goal-directed search for proofs [8], it is most natural to use right-hand contexts of sequents to represent multisets of processes. This choice requires the identification of the multiset constructor and the empty multiset with the multiplicative disjunction and false (the and ⊥ of linear logic [4]), and backchaining with a single step of multiset rewriting. While the logic programming language λProlog [10] and its linear logic refinement Lolli [5] contain rich sources of abstraction (such as modular programming, abstract data types, and higher-order programming), they contain no primitives for specifying concurrency, communications, or synchronization. If multiset rewriting is added to Lolli via the logical connectives and ⊥, the result is a language that contains primitives for both abstraction and concurrency. Surprisingly, the resulting logic, called Forum [7], is a presentation of all of linear logic in the sense that all of the connectives of linear logic can be defined via logical equivalences using only the connectives of Forum. Thus the rich meta-theory of linear logic, for example, the de Morgan dualities and cut-elimination, can be applied to the analysis of Forum programs. Several examples to illustrate the expressiveness of this presentation of linear logic will be given. These examples will involve a specification of sequent calculi for object-level logics, a specification of the π-calculus [9], and a specification of a functional programming language that contains side-effects and concurrency operators. In each of these examples, we shall argue that the specification is perspicuous and modular and that the meta-theory of linear logic can be used to derive properties of the specification.
Fully consistent density functional theory determination of the insulator-metal transition boundary in warm dense hydrogen

This works provides a density functional theory determination for the pressure-temperature boundary of the insulator-metal transition of warm dense fluid hydrogen
Analytic approximations for transit light curve observables and uncertainties

The light curve of an exoplanetary transit can be used to estimate the planetary radius and other parameters of interest. Because accurate parameter estimation is a non-analytic and computationally intensive problem, it is often useful to have analytic approximations for the parameters as well as their uncertainties and covariances. Here we give such formulas, for the case of an exoplanet transiting a star with a uniform brightness distribution. When limb darkening is significant, our parameter sets are still useful, although our analytic formulas underpredict the covariances and uncertainties.
A modular-invariant modified Weierstrass sigma-function as a building block for lowest-Landau-level wavefunctions on the torus

A “modified” variant of the Weierstrass sigma, zeta, and elliptic functions is proposed whereby the zeta function is redefined by ζ(z) ↦ ζ(z) ≡ ζ(z)−γ2z, where γ2 is a lattice invariant related to the almost-holomorphic modular invariant of the quasi-modular-invariant weight-2 Eisenstein series. If ωi is a primitive half-period, ζ(ωi) = πωi*/A, where A is the area of the primitive cell of the lattice. The quasiperiodicity of the modified sigma function is much simpler than that of the original, and it becomes the building-block for the modular-invariant formulation of lowest-Landau-level wavefunctions on the torus. It is suggested that the “modified” sigma function is more natural than the original Weierstrass form, which was formulated before quasi-modular forms were understood. For the high-symmetry (square and hexagonal) lattices, the modified and original sigma functions coincide.A “modified” variant of the Weierstrass sigma, zeta, and elliptic functions is proposed whereby the zeta function is redefined by ζ(z) ↦ ζ(z) ≡ ζ(z)−γ2z, where γ2 is a lattice invariant related to the almost-holomorphic modular invariant of the quasi-modular-invariant weight-2 Eisenstein series. If ωi is a primitive half-period, ζ(ωi) = πωi*/A, where A is the area of the primitive cell of the lattice. The quasiperiodicity of the modified sigma function is much simpler than that of the original, and it becomes the building-block for the modular-invariant formulation of lowest-Landau-level wavefunctions on the torus. It is suggested that the “modified” sigma function is more natural than the original Weierstrass form, which was formulated before quasi-modular forms were understood. For the high-symmetry (square and hexagonal) lattices, the modified and original sigma functions coincide.
The affine Grassmannian and the Springer resolution in positive characteristic

An important result of Arkhipov–Bezrukavnikov–Ginzburg relates constructible sheaves on the affine Grassmannian to coherent sheaves on the dual Springer resolution. In this paper, we prove a positive-characteristic analogue of this statement, using the framework of ‘mixed modular sheaves’ recently developed by the first author and Riche. As an application, we deduce a relationship between parity sheaves on the affine Grassmannian and Bezrukavnikov’s ‘exotic t-structure’ on the Springer resolution.
LynyrdSkynyrd at WNUT-2020 Task 2: Semi-Supervised Learning for Identification of Informative COVID-19 English Tweets.

In this work, we describe our system for WNUT-2020 shared task on the identification of informative COVID-19 English tweets. Our system is an ensemble of various machine learning methods, leveraging both traditional feature-based classifiers as well as recent advances in pre-trained language models that help in capturing the syntactic, semantic, and contextual features from the tweets. We further employ pseudo-labelling to incorporate the unlabelled Twitter data released on the pandemic. Our best performing model achieves an F1-score of 0.9179 on the provided validation set and 0.8805 on the blind test-set.
Direct sum decomposability of polynomials and factorization of associated forms

We prove two criteria for direct sum decomposability of homogeneous polynomials. For a homogeneous polynomial with a non-zero discriminant, we interpret direct sum decomposability of the polynomial in terms of factorization properties of the Macaulay inverse system of its Milnor algebra. This leads to an if-and-only-if criterion for direct sum decomposability of such a polynomial, and to an algorithm for computing direct sum decompositions over any field, either of characteristic $0$ or of sufficiently large positive characteristic, for which polynomial factorization algorithms exist. For homogeneous forms over algebraically closed fields, we interpret direct sums and their limits as forms that cannot be reconstructed from their Jacobian ideal. We also give simple necessary criteria for direct sum decomposability of arbitrary homogeneous polynomials over arbitrary fields and apply them to prove that many interesting classes of homogeneous polynomials are not direct sums.
The three-fold theoretical basis of the Gravity Probe B gyro precession calculation

The Gravity Probe B (GP-B) experiment is complete and the results are in agreement with the predictions of general relativity (GR) for both the geodetic precession, 6.6 arcsec yr−1 to about 0.3%, and the Lense–Thirring precession, 39 marcsec to about 19%. This note is concerned with the theoretical basis for the predictions. The predictions depend on three elements of gravity theory, firstly that macroscopic gravity is described by a metric theory such as GR, secondly that the Lense–Thirring metric provides an approximate description of the gravitational field of the spinning Earth, and thirdly that the spin axis of a gyroscope is parallel displaced in spacetime, which gives its equation of motion. We look at each of these three elements to show how each is solidly based on previous experiments and well-tested theory. The agreement of GP-B with theory strengthens our belief that all three elements are correct and increases our confidence in applying GR to astrophysical phenomena. Conversely, if GP-B had not verified the predictions a major theoretical quandary would have occurred.