Profit Puzzles or: Public Firm Profits Have Fallen

Carter Davis, Alexandre Sollaci & James Traina
We show that public firm profit rates fell by half since 1980. Inferred as the residual from the rise of US corporate profit rates in aggregate data, private firm profit rates doubled since 1980. Public firm financial returns matched their fall in profit rates, while public firm representativeness increased from 30% to 60% of the US capital stock. These results imply that time-varying selection biases in extrapolating public firms to the aggregate economy can be...

Unsupervised Severely Deformed Mesh Reconstruction (DMR) from a Single-View Image

Jie Mei, Jingxi Yu, Suzanne Romain, Craig Rose, Kelsey Magrane, Graeme LeeSon & Jenq-Neng Hwang
Much progress has been made in the supervised learning of 3D reconstruction of rigid objects from multi-view images or a video. However, it is more challenging to reconstruct severely deformed objects from a single-view RGB image in an unsupervised manner. Although training-based methods, such as specific category-level training, have been shown to successfully reconstruct rigid objects and slightly deformed objects like birds from a single-view image, they cannot effectively handle severely deformed objects and neither...

Canonical surgeries in rotationally invariant Ricci flow

Timothy Buttsworth, Maximilien Hallgren & Yongjia Zhang
We construct a rotationally invariant Ricci flow through surgery starting at any closed rotationally invariant Riemannian manifold. We demonstrate that a sequence of such Ricci flows with surgery converges to a Ricci flow spacetime in the sense of [32]. Results of Bamler-Kleiner [8] and Haslhofer [29] then guarantee the uniqueness and stability of these spacetimes given initial data. We simplify aspects of this proof in our setting, and show that for rotationally invariant Ricci flows,...

Improving Chest X-Ray Report Generation by Leveraging Warm-Starting

Aaron Nicolson, Jason Dowling & Bevan Koopman
Automatically generating a report from a patient's Chest X-Rays (CXRs) is a promising solution to reducing clinical workload and improving patient care. However, current CXR report generators, which are predominantly encoder-to-decoder models, lack the diagnostic accuracy to be deployed in a clinical setting. To improve CXR report generation, we investigate warm-starting the encoder and decoder with recent open-source computer vision and natural language processing checkpoints, such as the Vision Transformer (ViT) and PubMedBERT. To this...

On the Role of Longitudinal Currents in Radiating Systems of Charges

Nikita Nemkov & Vassili Fedotov
The time derivative of the charge density is linked to the current density by the continuity equation. However, it features only the longitudinal part of a current density, which is known to produce no radiation. This fact usually remains unnoticed though it poses a seemingly serious paradox, suggesting that the temporal variation of a charge density should be also irrelevant for radiation. We resolve this paradox by showing that the effective longitudinal currents are not...

The power of clockings

Antti Kuusisto
We investigate the expressive power of a Turing-complete logic based on game-theoretic semantics. By defining suitable fragments and variants of the logic, we obtain a range of natural characterizations for some fundamental families of model classes.

The Specialized High-Performance Network on Anton 3

Keun Sup Shim, Brian Greskamp, Brian Towles, Bruce Edwards, J. P. Grossman & David E. Shaw
Molecular dynamics (MD) simulation, a computationally intensive method that provides invaluable insights into the behavior of biomolecules, typically requires large-scale parallelization. Implementation of fast parallel MD simulation demands both high bandwidth and low latency for inter-node communication, but in current semiconductor technology, neither of these properties is scaling as quickly as intra-node computational capacity. This disparity in scaling necessitates architectural innovations to maximize the utilization of computational units. For Anton 3, the latest in a...

Generalised functional additive mixed models with compositional covariates for areal Covid-19 incidence curves

Matthias Eckardt, Jorge Mateu & Sonja Greven
We extend the generalised functional additive mixed model to include (functional) compositional covariates carrying relative information of a whole. Relying on the isometric isomorphism of the Bayes Hilbert space of probability densities with a subspace of the $L^2$, we include functional compositions as transformed functional covariates with constrained effect function. The extended model allows for the estimation of linear, nonlinear and time-varying effects of scalar and functional covariates, as well as (correlated) functional random effects,...

Physics-informed neural networks for modeling rate- and temperature-dependent plasticity

Rajat Arora, Pratik Kakkar, Biswadip Dey & Amit Chakraborty
This work presents a physics-informed neural network (PINN) based framework to model the strain-rate and temperature dependence of the deformation fields in elastic-viscoplastic solids. To avoid unbalanced back-propagated gradients during training, the proposed framework uses a simple strategy with no added computational complexity for selecting scalar weights that balance the interplay between different terms in the physics-based loss function. In addition, we highlight a fundamental challenge involving the selection of appropriate model outputs so that...

Estimation of Conditional Random Coefficient Models using Machine Learning Techniques

Stephan Martin
Nonparametric random coefficient (RC)-density estimation has mostly been considered in the marginal density case under strict independence of RCs and covariates. This paper deals with the estimation of RC-densities conditional on a (large-dimensional) set of control variables using machine learning techniques. The conditional RC-density allows to disentangle observable from unobservable heterogeneity in partial effects of continuous treatments adding to a growing literature on heterogeneous effect estimation using machine learning. %It is also informative of the...

The Compton Amplitude, lattice QCD and the Feynman-Hellmann approach

K. U. Can, A. Hannaford-Gunn, R. Horsley, Y. Nakamura, H. Perlt, P. E. L. Rakow, E. Sankey, G. Schierholz, H. Stüben, R. D. Young & J. M. Zanotti
A major objective of lattice QCD is the computation of hadronic matrix elements. The standard method is to use three-point and four-point correlation functions. An alternative approach, requiring only the computation of two-point correlation functions is to use the Feynman-Hellmann theorem. In this talk we develop this method up to second order in perturbation theory, in a context appropriate for lattice QCD. This encompasses the Compton Amplitude (which forms the basis for deep inelastic scattering)...

Learning Pixel Trajectories with Multiscale Contrastive Random Walks

Zhangxing Bian, Allan Jabri, Alexei A. Efros & Andrew Owens
A range of video modeling tasks, from optical flow to multiple object tracking, share the same fundamental challenge: establishing space-time correspondence. Yet, approaches that dominate each space differ. We take a step towards bridging this gap by extending the recent contrastive random walk formulation to much denser, pixel-level space-time graphs. The main contribution is introducing hierarchy into the search problem by computing the transition matrix between two frames in a coarse-to-fine manner, forming a multiscale...

Sparse grid implementation of a fixed-point fast sweeping WENO scheme for Eikonal equations

Zachary M. Miksis & Yong-Tao Zhang
Fixed-point fast sweeping methods are a class of explicit iterative methods developed in the literature to efficiently solve steady state solutions of hyperbolic partial differential equations (PDEs). As other types of fast sweeping schemes, fixed-point fast sweeping methods use the Gauss-Seidel iterations and alternating sweeping strategy to cover characteristics of hyperbolic PDEs in a certain direction simultaneously in each sweeping order. The resulting iterative schemes have fast convergence rate to steady state solutions. Moreover, an...

A Computation of the Action of the Morava Stabilizer Group on the Lubin-Tate Deformation Ring

André Davis
We compute recursive approximations of the action of the height $h \geq 2$ Morava stabilizer group on the associated Lubin-Tate deformation ring. We then specialize to the case $h=3$ and $p>2$ to calculate the action explicitly. These results are new for $h>2$ and agree with computations by Lader at height $h=2$.

Enabling Flexibility for Sparse Tensor Acceleration via Heterogeneity

Eric Qin, Raveesh Garg, Abhimanyu Bambhaniya, Michael Pellauer, Angshuman Parashar, Sivasankaran Rajamanickam, Cong Hao & Tushar Krishna
Recently, numerous sparse hardware accelerators for Deep Neural Networks (DNNs), Graph Neural Networks (GNNs), and scientific computing applications have been proposed. A common characteristic among all of these accelerators is that they target tensor algebra (typically matrix multiplications); yet dozens of new accelerators are proposed for every new application. The motivation is that the size and sparsity of the workloads heavily influence which architecture is best for memory and computation efficiency. To satisfy the growing...

Frequency-dependent Inter-pseudospin Solutions to Superconducting Strontium Ruthenate

Olivier Gingras, Nikita Allaglo, Reza Nourafkan, Michel Côté & André-Marie S. Tremblay
The lasting puzzle of the superconducting order parameter of Sr$_2$RuO$_4$ calls for theoretical studies that include seldom-considered effects. Here we include spin-orbit coupling effects on the electronic structure and then solve the linearized Eliashberg equation in a pseudospin basis, including the possibility that spin and charge fluctuations induce frequency-dependent superconducting order parameters. We find that spin-orbit coupling mixes even and odd contributions in orbital, spin and frequency spaces and that leading inter-pseudospin symmetries, B$_{1g}^+$ and...

Interacting Short Dipole Antennas

Sergio Cattani, C.H. Furukawa & F. D. Saad
This is a didactical text written to students of Physics and
Engineering to investigate the interchange of electromagnetic radiation
between two short dipole antennas. These phenomena can be observed in
lessons and public sessions in the "Laboratório de Demonstrações EWH" of
the Institute of Physics of the University of São Paulo (IFUSP).
Key words: short dipole antennas; emission and reception; essential aspects.

Retinal Vessel Segmentation with Pixel-wise Adaptive Filters

Mingxing Li, Shenglong Zhou, Chang Chen, Yueyi Zhang, Dong Liu & Zhiwei Xiong
Accurate retinal vessel segmentation is challenging because of the complex texture of retinal vessels and low imaging contrast. Previous methods generally refine segmentation results by cascading multiple deep networks, which are time-consuming and inefficient. In this paper, we propose two novel methods to address these challenges. First, we devise a light-weight module, named multi-scale residual similarity gathering (MRSG), to generate pixel-wise adaptive filters (PA-Filters). Different from cascading multiple deep networks, only one PA-Filter layer can...

Toward the discovery of matter creation with neutrinoless double-beta decay

Matteo Agostini, Giovanni Benato, Jason A. Detwiler, Javier Menéndez & Francesco Vissani
The discovery of neutrinoless double-beta decay could soon be within reach. This hypothetical ultra-rare nuclear decay offers a privileged portal to physics beyond the Standard Model of particle physics. Its observation would constitute the discovery of a matter-creating process, corroborating leading theories of why the universe contains more matter than antimatter, and how forces unify at high energy scales. It would also prove that neutrinos and anti-neutrinos are not two distinct particles, but can transform...

Hacking the Colony: On the Disruptive Effect of Misleading Pheromone and How to Defend Against It

Ashay Aswale, Antonio Lopez, Aukkawut Ammartayakun & Carlo Pinciroli
Ants have evolved to seek and retrieve food by leaving trails of pheromones. This mechanism has inspired several approaches to decentralized multi-robot coordination. However, in this paper, we show that pheromone trails are a fragile mechanism for coordination, and can be sabotaged to starve the colony. We introduce detractors: malicious agents that leave a misleading, but indistinguishable, trail of food pheromone to distract and trap cooperator ants in the nest. We analyze the effectiveness of...

A Challenge for Discrimination of Color-Singlet versus Color-Octet Quarkonium Production

Andrew J. Larkoski
The precise mechanism for production of quarkonium at hadron colliders is still an open question. Within non-relativistic quantum chromodynamics, quarkonium production cross sections can be factorized into short-distance, perturbative contributions and universal, non-perturbative, long-distance matrix elements, and then summed over quantum numbers of the heavy quark pair. In principle, at short-distances, the heavy quark pair can be either in a color-singlet or color-octet state, and it is desirable to establish the relative contributions to compare...

Position of the centroid of a planar convex body

Marek Lassak
It is well known that any planar convex body $A$ permits to inscribe an affine-regular hexagon $H_A$. We prove that the centroid of $A$ belongs to the homothetic image of $H_A$ with ratio $\frac{4}{21}$ and the center in the center of $H_A$. This ratio cannot be enlarged.

Budgeted Steiner Networks: Three Terminals with Equal Path Weights

Mario Szegedy & Jingjin Yu
Given a set of terminals in 2D/3D, the network with the shortest total length that connects all terminals is a Steiner tree. On the other hand, with enough budget, every terminal can be connected to every other terminals via a straight edge, yielding a complete graph over all terminals. In this work, we study a generalization of Steiner trees asking what happens in between these two extremes. Focusing on three terminals with equal pairwise path...

A Practical Guide to the Numerical Implementation of Tensor Networks I: Contractions, Decompositions and Gauge Freedom

Glen Evenbly
We present an overview of the key ideas and skills necessary to begin implementing tensor network methods numerically, which is intended to facilitate the practical application of tensor network methods for researchers that are already versed with their theoretical foundations. These skills include an introduction to the contraction of tensor networks, to optimal tensor decompositions, and to the manipulation of gauge degrees of freedom in tensor networks. The topics presented are of key importance to...

Incorporating Distributed DRL into Storage Resource Optimization of Space-Air-Ground Integrated Wireless Communication Network

Chao Wang, Lei Liu, Chunxiao Jiang, Shangguang Wang, Peiying Zhang & Shigen Shen
Space-air-ground integrated network (SAGIN) is a new type of wireless network mode. The effective management of SAGIN resources is a prerequisite for high-reliability communication. However, the storage capacity of space-air network segment is extremely limited. The air servers also do not have sufficient storage resources to centrally accommodate the information uploaded by each edge server. So the problem of how to coordinate the storage resources of SAGIN has arisen. This paper proposes a SAGIN storage...

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Affiliations

• University of Massachusetts Amherst
22
• National Institute for Demographic Studies
6
• Institute for Advanced Study
4
• Washington University in St. Louis
4
• National Institute for Materials Science
3
• Keele University
2
• University of Bayreuth
2
• Sewanee: The University of the South
2
• St. Francis College
1
• University of Strasbourg
1