November 2022 arXiv papers — page 19

Xu Chen, Tianjian Jiang, Jie Song, Max Rietmann

Neural fields have revolutionized the area of 3D reconstruction and novel view synthesis of rigid scenes. A key challenge in making such methods applicable to articulated objects, such as the human body, is to model the deformation of 3D locations between the rest pose (a canonical space) and the deformed space. We propose a new articulation module for neura

Prakhyat Khati

Non-fungible tokens (NFTs) are unique digital items with blockchain managed ownership. Ethereum blockchain based smart contract created the environment for NFTs (ERC721) to reach its one of the most important future application domains. Non fungible tokens got more attention when the market saw record breaking sales in 2021. Virtually anything of value can b

Tahere Kashfi, Mahmood Roshan, Benoit Famaey

Bar formation in cosmological simulations of galaxy formation remains challenging. It was previously shown that the fraction of barred galaxies at low stellar masses ($M_*<10^{10.5} M_\odot$) in TNG50 is too low compared to observations. Here, we highlight another tension, also observed at higher stellar masses, namely that barred galaxies in TNG50 appear to

Natalia Chepiga, Nicolas Laflorencie

We study Majorana chain with the shortest possible interaction term and in the presence of hoping alternation. When formulated in terms of spins the model corresponds to the transverse field Ising model with nearest-neighbor transverse and next-nearest-neighbor longitudinal repulsion. The phase diagram obtained with extensive DMRG simulations is very rich an

Florinel-Alin Croitoru, Nicolae-Catalin Ristea, Dana Dascalescu, Radu Tudor Ionescu

We propose a very fast frame-level model for anomaly detection in video, which learns to detect anomalies by distilling knowledge from multiple highly accurate object-level teacher models. To improve the fidelity of our student, we distill the low-resolution anomaly maps of the teachers by jointly applying standard and adversarial distillation, introducing a

Rohan Kashyap

Deep Learning optimization involves minimizing a high-dimensional loss function in the weight space which is often perceived as difficult due to its inherent difficulties such as saddle points, local minima, ill-conditioning of the Hessian and limited compute resources. In this paper, we provide a comprehensive review of $14$ standard optimization methods su

Fengyu Zhang, Ashkan Panahi, Guangjun Gao

Considering the spectral properties of images, we propose a new self-attention mechanism with highly reduced computational complexity, up to a linear rate. To better preserve edges while promoting similarity within objects, we propose individualized processes over different frequency bands. In particular, we study a case where the process is merely over low-

Parthiv Haldar

S-matrix is one of the fundamental observables of the quantum theory of relativistic particles. There have been attempts to understand the quantum dynamics of relativistic particles abstractly in terms of S-matrix bypassing a Lagrangian formulation of quantum field theory. Equivalently, the space of possible S-matrices defines an abstract theory space. This

Rohan Kashyap, Vivek Kashyap, Narendra C. P.

Recent work has demonstrated substantial gains in pre-training large-language models (LLMs) followed by supervised fine-tuning on the downstream task. In this paper, we evaluate the performance of the GPT-neo model using $6$ commonsense reasoning benchmark tasks. We aim to examine the performance of smaller models using the GPT-neo models against several lar

Saptarshi Saha, Rangeet Bhattacharyya

Recent experiments show that periodic drives on dipolar systems lead to long-lived prethermal states. These systems are weakly coupled to the environment and reach prethermal states in a timescale much shorter than the timescale for thermalization. Such nearly-closed systems have previously been analyzed using Floquet formalism, which shows the emergence of

Stephen Gustafson, Takahisa Inui

We consider the nonlinear Schr\"{o}dinger equation with a repulsive Dirac delta potential in one dimensional Euclidean space. We classify the global dynamics of even solutions with the same action as the high-frequency ground state standing wave solutions.

Leo Ardon, Alberto Pozanco, Daniel Borrajo, Sumitra Ganesh

Reinforcement Learning (RL) algorithms are known to scale poorly to environments with many available actions, requiring numerous samples to learn an optimal policy. The traditional approach of considering the same fixed action space in every possible state implies that the agent must understand, while also learning to maximize its reward, to ignore irrelevan

Jiayi Sun, Wensheng Gan, Han-Chieh Chao, Philip S. Yu

The Internet of Behavior is a research theme that aims to analyze human behavior data on the Internet from the perspective of behavioral psychology, obtain insights about human behavior, and better understand the intention behind the behavior. In this way, the Internet of Behavior can predict human behavioral trends in the future and even change human behavi

Tanjib Khan, Tianbo Liu, Raza Sabbir Sufian

We present the first lattice QCD determination of the light cone gluon helicity correlation parton distribution function (PDF) with numerical evidence toward disfavoring negative gluon polarization in the nucleon. We present a solution for eliminating an inevitable contamination term that dominates the Euclidean correlations and makes determining gluon helic

Igor I. Zinchenko

We present a review of observational studies of high-mass star formation, based mainly on our own research. It includes surveys of high-mass star-forming regions in various molecular lines and in continuum, investigations of filamentary infrared dark clouds, which represent the earliest phases of massive star formation, detailed studies of individual high-ma

Pedro D. Alvarez, Cristóbal Corral, Jorge Zanelli

We present a three-parameter family of analytic black-hole solutions in the bosonic sector of a four-dimensional supersymmetric model with matter fields in the adjoint representation. The solutions are endowed with curvature and torsional singularities which are both surrounded by an event horizon. They are asymptotically Lorentz flat, representing the torsi

Syksy Rasanen, Yosef Verbin

We consider a formulation of gauge field theory where the gauge field $A_\alpha$ and the field strength $F_{\alpha\beta}$ are independent variables, as in the Palatini formulation of gravity. For the simplest gauge field action, this is known to be equivalent to the usual formulation. We add non-minimal couplings between $F_{\alpha\beta}$ and a scalar field,

Zihao Fu, Haoran Yang, Anthony Man-Cho So, Wai Lam

Fine-tuning pre-trained models has been ubiquitously proven to be effective in a wide range of NLP tasks. However, fine-tuning the whole model is parameter inefficient as it always yields an entirely new model for each task. Currently, many research works propose to only fine-tune a small portion of the parameters while keeping most of the parameters shared

André Benevides, Atish Dabholkar

We consider a scalar field coupled to massless fermions through Yukawa couplings, such as the Higgs field, in a Robertson-Walker spacetime. We compute the nonlocal quantum effective action as a functional of the background scalar field and the scale factor at one loop order by integrating the Weyl anomaly resulting from the fermions in the loop. We show that

En-Hung Chao, Harvey B. Meyer, Julian Parrino

The `intermediate window quantity' of the hadronic vacuum polarization contribution to the anomalous magnetic moment of the muon allows for a high-precision comparison between the data-driven approach and lattice QCD. The existing lattice results, which presently show good consistency among each other, are in strong tension with the data-driven determination

Tamanna Jain, Piero Rettegno, Michalis Agathos, Alessandro Nagar

We determine the general local-in-time effective-one-body (EOB) Hamiltonian for massless Scalar-Tensor (ST) theories at third post-Newtonian (PN) order. Starting from the Lagrangian derived in [Phys. Rev. D 99, 044047 (2019)], we map it to the corresponding ordinary Hamiltonian describing the two-body interaction in ST theories at 3PN level. Using a canonica

S. Gomé, L. S. Tuckerman, D. Barkley

Low Reynolds number turbulence in wall-bounded shear flows \emph{en route} to laminar flow takes the form of oblique, spatially-intermittent turbulent structures. In plane Couette flow, these emerge from uniform turbulence via a spatiotemporal intermittent process in which localised quasi-laminar gaps randomly nucleate and disappear. For slightly lower Reyno

Trang Tran

Blockchain technology has changed how people think about how they used to store and trade their assets, as it introduced us to a whole new way to transact: using digital currencies. One of the major innovations of blockchain technology is decentralization, meaning that traditional financial intermediaries, such as asset-backed security issuers and banks, are

Yichen Jiang, Xiang Zhou, Mohit Bansal

Recent datasets expose the lack of the systematic generalization ability in standard sequence-to-sequence models. In this work, we analyze this behavior of seq2seq models and identify two contributing factors: a lack of mutual exclusivity bias (i.e., a source sequence already mapped to a target sequence is less likely to be mapped to other target sequences),

Koray Aydoğan

It has recently been demonstrated that deep learning has significant potential to automate parts of the exoplanet detection pipeline using light curve data from satellites such as Kepler \cite{borucki2010kepler} \cite{koch2010kepler} and NASA's Transiting Exoplanet Survey Satellite (TESS) \cite{ricker2010transiting}. Unfortunately, the smallness of the avail

Thomas Mikal-Evans, Nikku Madhusudhan, Jason Dittmann, Maximilian N. Guenther

TOI-270d is a temperate sub-Neptune discovered by the Transiting Exoplanet Survey Satellite (TESS) around a bright (J=9.1mag) M3V host star. With an approximate radius of 2RE and equilibrium temperature of 350K, TOI-270d is one of the most promising small exoplanets for atmospheric characterisation using transit spectroscopy. Here we present a primary transi

Nansen Petrosyan, Vladimir Vankov

We generalise a theorem of Gersten on surjectivity of the restriction map in $\ell^{\infty}$-cohomology of groups. This leads to applications on subgroups of hyperbolic groups, quasi-isometric distinction of finitely generated groups and $\ell^{\infty}$-cohomology calculations for some well-known classes of groups. Along the way, we obtain hyperbolicity crit

M. R. Losada, A. T. Costa, B. Biel, J. Fernández-Rossier

We study indirect exchange interactions between localized spins of magnetic impurities in spin-valley coupled systems described with the Kane-Mele model. Our model captures the main ingredients of the energy bands of 1H transition metal dichalcogenides (TMDs) monolayers, such as 1H-MoS$_2$ and 1H-NbSe$_2$. To obtain the effective interactions, we use the exa

Jerome Detemple, Scott Robertson

We study a continuous time economy where agents have asymmetric information. The informed agent (``$I$''), at time zero, receives a private signal about the risky assets' terminal payoff $\Psi(X_T)$, while the uninformed agent (``$U$'') has no private signal. $\Psi$ is an arbitrary payoff function, and $X$ follows a time-homogeneous diffusion. Crucially, we

Samuel C. Y. Au, Xiao Yan, Sui Cheong Chan, Ying Lung Chan

Phase change under reduced environmental pressures is key to understanding liquid discharge and propulsion processes for aerospace applications. A representative case is the sessile water droplets exposed to high vacuum, which experience complex phase change and transport phenomena that behave so differently than that under the atmosphere. Here, we demonstra

Zherui Han, Changkyun Lee, Jiawei Song, Haiyan Wang

From ultraviolet to mid-infrared region, light-matter interaction mechanisms in semiconductors progressively shift from electronic transitions to phononic resonances and are affected by temperature. Here, we present a parallel temperature-dependent treatment of both electrons and phonons entirely from first principles, enabling the prediction of full-spectru

Yi Zhao, Wang-Chen Xue, Shao-Lin Xiong, Yuan-Hao Wang

Gravitational wave high-energy Electromagnetic Counterpart All-sky Monitor (GECAM) is a pair of microsatellites (i.e. GECAM-A and GECAM-B) dedicated to monitoring gamma-ray transients including gravitational waves high-energy electromagnetic counterparts, Gamma-ray Bursts, Soft Gamma-ray Repeaters, Solar Flares and Terrestrial Gamma-ray Flashes. Since launch

Amanda Burcroff

In this paper, we simplify and generalize formulas for the expansion of rank 2 cluster variables. In particular, we prove an equivalent, but simpler, description of the colored Dyck subpaths framework introduced by Lee and Schiffler. We then prove the conjectured bijectivity of a map constructed by Feiyang Lin between collections of colored Dyck subpaths and

Dmytro Kalpakchi, Johan Boye

This paper presents an evaluation of the quality of automatically generated reading comprehension questions from Swedish text, using the Quinductor method. This method is a light-weight, data-driven but non-neural method for automatic question generation (QG). The evaluation shows that Quinductor is a viable QG method that can provide a strong baseline for n

Haowen Lu, Liding Yao

Modified from the standard half-space extension via reflection principle, we construct a linear extension operator for the upper half space $\Bbb R^n_+$ that has the form $Ef(x)=\sum_{j=-\infty}^\infty a_jf(x',-b_jx_n)$ for $x_n<0$. We prove that $E$ is bounded in all $C^k$-spaces, Sobolev and H\"older spaces, Besov and Triebel-Lizorkin spaces, along with th

Jae Hee Lee, Michael Sioutis, Kyra Ahrens, Marjan Alirezaie

Knowledge about space and time is necessary to solve problems in the physical world: An AI agent situated in the physical world and interacting with objects often needs to reason about positions of and relations between objects; and as soon as the agent plans its actions to solve a task, it needs to consider the temporal aspect (e.g., what actions to perform

Dario Malchiodi, Davide Raimondi, Giacomo Fumagalli, Raffaele Giancarlo

Learned Bloom Filters, i.e., models induced from data via machine learning techniques and solving the approximate set membership problem, have recently been introduced with the aim of enhancing the performance of standard Bloom Filters, with special focus on space occupancy. Unlike in the classical case, the "complexity" of the data used to build the filter

Antonio Parziale, Monica Agrawal, Shalmali Joshi, Irene Y. Chen

A collection of the extended abstracts that were presented at the 2nd Machine Learning for Health symposium (ML4H 2022), which was held both virtually and in person on November 28, 2022, in New Orleans, Louisiana, USA. Machine Learning for Health (ML4H) is a longstanding venue for research into machine learning for health, including both theoretical works an

Oleksandr I. Malyi, Xin-Gang Zhao, Alex Zunger

Compounds having an odd number of electrons with the same orbital character in occupied and unoccupied band edge states would be expected to have band degeneracy at the Fermi energy, making such reference system metals. Yet, many ABO3 oxide perovskites with a magnetic 3d B-atom are, in fact, insulators both below and above the Neel temperature. These inconsi

Taehyun Kim, Jeongyoun Ahn, Sungkyu Jung

This work addresses a longstanding question in high-dimensional linear classification: Is perfect classification achievable in heterogeneous covariance structures? We focus on the phenomenon of data piling, where projected data points collapse onto discrete values. We provide a comprehensive characterization of two distinct types of data piling. The first ty

Teodora Reu

International initiatives such as METABRIC (Molecular Taxonomy of Breast Cancer International Consortium) have collected several multigenomic and clinical data sets to identify the undergoing molecular processes taking place throughout the evolution of various cancers. Numerous Machine Learning and statistical models have been designed and trained to analyze

Alberto Hernandez-Melian, Benjamin M. Huddart, Francis L. Pratt, Stephen J. Blundell

We present the results of a muon-spin relaxation ($\mu^{+}$SR) investigation of the crystalline organic radical compound 4-(2-benzimidazolyl)-1,2,3,5-dithiadiazolyl (HbimDTDA), in which we demonstrate the hysteretic magnetic switching of the system that takes place at $T = 274 \pm 11\,\mathrm{K}$ caused by a structural phase transition. Muon-site analysis us

Giacomo Carrara, Gláucia Murta, Federico Grasselli

Twin-Field Quantum Key Distribution (TF-QKD) enables two distant parties to establish a shared secret key, by interfering weak coherent pulses (WCPs) in an intermediate measuring station. This allows TF-QKD to reach greater distances than traditional QKD schemes and makes it the only scheme capable of beating the repeaterless bound on the bipartite private c

Marco Cè, Tim Harris, Ardit Krasniqi, Harvey B. Meyer

We investigate several aspects of chiral symmetry in QCD at a temperature of $T = 128\,\text{MeV}$. The study is based on a $24\times 96^3$ lattice-QCD ensemble with O($a$)-improved Wilson quarks and physical up, down and strange quark masses. The pion quasiparticle turns out to be significantly lighter than the zero-temperature pion mass, even though the co

Melody Wolk, Andy Applebaum, Camron Dennler, Patrick Dwyer

Advancements in reinforcement learning (RL) have inspired new directions in intelligent automation of network defense. However, many of these advancements have either outpaced their application to network security or have not considered the challenges associated with implementing them in the real-world. To understand these problems, this work evaluates sever

Shanshan Xu, Irina Broda, Rashid Haddad, Marco Negrini

Recent work has demonstrated that natural language processing techniques can support consumer protection by automatically detecting unfair clauses in the Terms of Service (ToS) Agreement. This work demonstrates that transformer-based ToS analysis systems are vulnerable to adversarial attacks. We conduct experiments attacking an unfair-clause detector with un

Pratik Mullick, Cécile Appert-Rolland, William H. Warren, Julien Pettré

For a group of pedestrians without any spatial boundaries, the methods of density estimation is a wide area of research. Besides, there is a specific difficulty when the density along one given pedestrian trajectory is needed in order to plot an `individual-based' fundamental diagram. We illustrate why several methods become ill-defined in this case. We then

Stefano Ansoldi, Takahiro Tanaka

There are several exotic tunneling processes that can be realized only by incorporating the effect of gravity. Here, we point out that we encounter difficulties in constructing the WKB wave function, once we try to describe quantum fluctuations around the semi-classical tunneling path. We present examples of pathology in the true vacuum decay/upward tunnelin

P. Tolias

The numerous idealizations that are involved in the exact microscopic statistical description of complex (dusty) plasmas are discussed in detail. The two prevailing approaches in the Klimontovich description of dusty plasmas are reviewed in a pedagogical manner. The continuous phase space approximation is introduced, within which the more rigorous treatment

Chathuranga Sirimanna, Ismail Soudi, Gojko Vujanovic, Wen-Jing Xing

The widespread notion that jets quenched in a Quark-Gluon-Plasma (QGP) are similar in their parton flavor composition to jets in vacuum is critically examined. We demonstrate that while the soft to semi-hard [low to intermediate transverse momentum ($p_T$)] sector of vacuum jets are predominantly bosonic i.e., composed of gluons, \emph{sufficiently} quenched

Kaira Samuel, Matthew LaRosa, Kyle McAlpin, Morgan Schaefer

Artificial intelligence (AI) has enormous potential to improve Air Force pilot training by providing actionable feedback to pilot trainees on the quality of their maneuvers and enabling instructor-less flying familiarization for early-stage trainees in low-cost simulators. Historically, AI challenges consisting of data, problem descriptions, and example code

Zitong Wang, Michael Hilke, Norm Fong, Guy Austing

We report on non-linear transport phenomena at high filling factor and DC current-induced electronic hydrodynamics in an ultra-high mobility (mu=20x10^6 cm^2/Vs) two-dimensional electron gas in a narrow (15 micron wide) GaAs/AlGaAs Hall bar for DC current densities reaching 0.67 A/m. The various phenomena and the boundaries between the phenomena are captured

Khoa Lê

For a general adapted integrable right-continuous with left limits (RCLL) process $(X_t)_{t\in[0,\tau]}$ taking values in a metric space $(\mathcal E,d)$, we show (among other things) that for every $m\in(1,\infty)$ $$ \frac{m-1}{2m-1}\|\sup_{t\in[0,\tau]}\mathbb{E}(d(X_{t-},X_\tau)|\mathcal F_t)\|_m\le \|\sup_{t\in[0,\tau]}d(X_0,X_t)\|_m\le c\frac{m^2}{m-1}

Xinrui Wang, Zhuoru Li, Xiao Zhou, Yusuke Iwasawa

Portrait Stylization aims to imbue portrait photos with vivid artistic effects drawn from style examples. Despite the availability of enormous training datasets and large network weights, existing methods struggle to maintain geometric consistency and achieve satisfactory stylization effects due to the disparity in facial feature distributions between facial

Michael Hartz

A non-self-adjoint operator algebra is said to be residually finite dimensional (RFD) if it embeds into a product of matrix algebras. We characterize RFD operator algebras in terms of their matrix state space, and moreover show that an operator algebra is RFD if and only if every representation can be approximated by finite dimensional ones in the point weak

Ed Bennett

As a fully computational discipline, Lattice Field Theory has the potential to give results that anyone with sufficient computational resources can reproduce, going from input parameters to published numbers and plots correct to the last byte. After briefly motivating and outlining some of the key steps in making lattice computations reproducible, this contr

Chiara Bellotti, Giuseppe Puglisi

The aim of this work is to illustrate a conditional result involving the exponential sums over primes in short intervals under the assumption that both the Generalized Riemann Hypothesis and the Density Hypothesis for Dirichlet $L$-functions are true.

Frédéric Prost

Inheritance is the fundamental building block of civilization. This is the addition of wealth, knowledge and properties over time that produce the society in which we are living. Every generation does not have to start from zero and can capitalize on the efforts of previous generations. Blockchain based assets are very efficiently and securely transferred be

Hanjing Zhou, Songsong Yan, Dongze Fan, Di Wang

Based on density functional theory and symmetry analysis, we present a comprehensive investigation of electronic structure, magnetic properties and possible structural distortion of magnetic kagome metal FeGe. We estimate the magnetic parameters including Heisenberg and Dzyaloshinskii-Moriya (DM) interactions, and find that the ferromagnetic nearest-neighbor

Xinshi Wang, Daniel Tang

Medical dialogue information extraction is becoming an increasingly significant problem in modern medical care. It is difficult to extract key information from electronic medical records (EMRs) due to their large numbers. Previously, researchers proposed attention-based models for retrieving features from EMRs, but their limitations were reflected in their i

Quinn Jarecki, Meredith Kupinski

Polarized light-matter interactions are mathematically described by the Mueller matrix (MM)-valued polarized bidirectional reflectance distribution function (pBRDF). A pBRDF is parameterized by 16 degrees of freedom that depend upon scattering geometry. A triple degenerate (TD) MM assumption reduces the degrees of freedom to eight: one for reflectance, six f

Vishaal Udandarao, Ankush Gupta, Samuel Albanie

Contrastive Language-Image Pre-training (CLIP) has emerged as a simple yet effective way to train large-scale vision-language models. CLIP demonstrates impressive zero-shot classification and retrieval on diverse downstream tasks. However, to leverage its full potential, fine-tuning still appears to be necessary. Fine-tuning the entire CLIP model can be reso

Tu Trinh, Haoyu Chen, Daniel S. Brown

We examine the problem of determining demonstration sufficiency: how can a robot self-assess whether it has received enough demonstrations from an expert to ensure a desired level of performance? To address this problem, we propose a novel self-assessment approach based on Bayesian inverse reinforcement learning and value-at-risk, enabling learning-from-demo

Hiroki Imai, Makoto Sakamoto, Maki Takeuchi, Yoshiyuki Tatsuta

We analyze the number of independent chiral zero modes and the winding numbers at the fixed points on $T^2/{\mathbb{Z}}_N$ ($N=2,3,4,6$) orbifolds with magnetic flux. In the case of $N=2$, we derive the index formula $n_{+}-n_{-}=M/2+(-V_{+}+V_{-})/4=M/2-V_{+}/2+1$ by using the trace formula, where $n_{\pm}$ are the numbers of the $\pm$ chiral zero modes and

Xiaoshu Ge, Chunping Zhong

In this paper, a class of holomorphic invariant metrics is introduced on the irreducible classical domains of type I-IV, which are strongly pseudoconvex complex Finsler metrics in the strict sense of M. Abate and G. Patrizio[2]. These metrics are of particular interest in several complex variables since they are holomorphic invariant complex Finsler metrics

Giovanni Barbarino, Vanni Noferini

We study the eigendecompositions of para-Hermitian matrices $H(z)$, that is, matrix-valued functions that are analytic and Hermitian on the unit circle $S^1 \subset \mathbb C$. In particular, we fill existing gaps in the literature and prove the existence of a decomposition $H(z)=U(z)D(z)U(z)^P$ where, for all $z \in S^1$, $U(z)$ is unitary, $U(z)^P=U(z)^*$

Elena Luna, Juan Carlos San Miguel, José María Martínez, Marcos Escudero-Viñolo

This letter focuses on the task of Multi-Target Multi-Camera vehicle tracking. We propose to associate single-camera trajectories into multi-camera global trajectories by training a Graph Convolutional Network. Our approach simultaneously processes all cameras providing a global solution, and it is also robust to large cameras unsynchronizations. Furthermore

Suraj Maurya, Rahul Nigam, Sashideep Gutti

In this article, we set up a variational problem to arrive at the equation of the maximal hypersurface in the interior of a spherically symmetric evolving trapped region. In the first part of the article, we present the Lagrangian and the corresponding Euler-Lagrange equations that maximize the interior volume of a trapped region that is formed dynamically d

Fatema Tuz Zohra Anny, Oahidul Islam

Sentiment analysis or opinion mining help to illustrate the phrase NLP (Natural Language Processing). Sentiment analysis has been the most significant topic in recent years. The goal of this study is to solve the sentiment polarity classification challenges in sentiment analysis. A broad technique for categorizing sentiment opposition is presented, along wit

O. V. Tarasov

The method for functional reduction of Feynman integrals, proposed by the author, is used to calculate one-loop integrals corresponding to diagrams with four external lines. The integrals that emerge from amplitudes for the scattering of light by light, the photon splitting in an external field and Delbr\"{u}ck scattering are considered. For master integrals

Chaoxi Fang, Jie Jiang, Ming Zhang

In the generalized off-shell free energy landscape, black holes can be treated as thermodynamic topological defects. The local topological properties of the spacetime can be reflected by the winding numbers at the defects, while the global topological nature can be classified by the topological number which is the sum of all local winding numbers. We propose

Henry Chiu, Rama Cont

We present a non-probabilistic, pathwise approach to continuous-time finance based on causal functional calculus. We introduce a definition of self-financing, free from any integration concept and show that the value of a self-financing portfolio is a pathwise integral (every self-financing strategy is a gradient) and that generic domain of functional calcul

Giuseppe Abbondanza, Andrea Grespi, Alfred Larsson, Lorena Glatthaar

The electrochemical growth of Au nanowires in a template of nano-porous anodic aluminum oxide was investigated in situ by means of grazing-incidence transmission small- and wide-angle x-ray scattering (GTSAXS and GTWAXS), x-ray fluorescence (XRF) and 2-dimensional surface optical reflectance (2D-SOR). The XRF and the overall intensity of the GTWAXS patterns

Michele Pini, Pierbiagio Pieri, Giancarlo Calvanese Strinati

The evolution of an attractive polarized two-component Fermi gas at zero temperature is analyzed as its polarization is progressively decreased, from full polarization (corresponding to the polaronic limit) down to a critical polarization when superfluidity sets in. This critical polarization and the nature of the associated superfluid instability are determ

Abhishek Sarkar

We explore complex Riemannian geometry and Hermitian metrics on complex algebraic varieties and analytic spaces, respectively. In particular, we introduce Hermitian metrics on holomorphic Lie algebroids and examine the associated characteristic foliation with its canonically induced inner product. Furthermore, we study hypercohomologies related to the leaf s

Ayantika Das, Arun Palla, Keerthi Ram, Mohanasankar Sivaprakasam

Anomaly detection in MRI is of high clinical value in imaging and diagnosis. Unsupervised methods for anomaly detection provide interesting formulations based on reconstruction or latent embedding, offering a way to observe properties related to factorization. We study four existing modeling methods, and report our empirical observations using simple data sc

Amirreza Zamani, Tobias J. Oechtering, Mikael Skoglund

A privacy mechanism design problem is studied through the lens of information theory. In this work, an agent observes useful data $Y=(Y_1,...,Y_N)$ that is correlated with private data $X=(X_1,...,X_N)$ which is assumed to be also accessible by the agent. Here, we consider $K$ users where user $i$ demands a sub-vector of $Y$, denoted by $C_{i}$. The agent wi

Lukáš Samuel Marták, Rainer Kelz, Gerhard Widmer

This paper describes several improvements to a new method for signal decomposition that we recently formulated under the name of Differentiable Dictionary Search (DDS). The fundamental idea of DDS is to exploit a class of powerful deep invertible density estimators called normalizing flows, to model the dictionary in a linear decomposition method such as NMF

José Francisco Reis

The Farrell-Jones conjecture for lax monoidal finitary localising invariants was recently proved by Bunke-Kasprowski-Winges. In this short note, making use of the theory of noncommutative motives, we prove that the lax monoidal assumption is not necessary.

Amon Lahr, Andrea Zanelli, Andrea Carron, Melanie N. Zeilinger

By enabling constraint-aware online model adaptation, model predictive control using Gaussian process (GP) regression has exhibited impressive performance in real-world applications and received considerable attention in the learning-based control community. Yet, solving the resulting optimal control problem in real-time generally remains a major challenge,

Grace Luo, Giscard Biamby, Trevor Darrell, Daniel Fried

We demonstrate how language can improve geolocation: the task of predicting the location where an image was taken. Here we study explicit knowledge from human-written guidebooks that describe the salient and class-discriminative visual features humans use for geolocation. We propose the task of Geolocation via Guidebook Grounding that uses a dataset of Stree

William He, Benjamin Rossman

We study the formula complexity of the word problem $\mathsf{Word}_{S_n,k} : \{0,1\}^{kn^2} \to \{0,1\}$: given $n$-by-$n$ permutation matrices $M_1,\dots,M_k$, compute the $(1,1)$-entry of the matrix product $M_1\cdots M_k$. An important feature of this function is that it is invariant under action of $S_n^{k-1}$ given by \[ (\pi_1,\dots,\pi_{k-1})(M_1,\dot

Julia A. Meister, Jack Sharp, and Yan Wang, Khuong An Nguyen

The unsustainable take-make-dispose linear economy prevalent in healthcare contributes 4.4% to global Greenhouse Gas emissions. A popular but not yet widely-embraced solution is to remanufacture common single-use medical devices like electrophysiology catheters, significantly extending their lifetimes by enabling a circular life cycle. To support the adoptio

Shilong Liu, Yaoyuan Liang, Feng Li, Shijia Huang

In this paper, we study the problem of visual grounding by considering both phrase extraction and grounding (PEG). In contrast to the previous phrase-known-at-test setting, PEG requires a model to extract phrases from text and locate objects from images simultaneously, which is a more practical setting in real applications. As phrase extraction can be regard

Aditi Basu Bal, Xiaoyang Guo, Tom Needham, Anuj Srivastava

This paper provides theoretical and computational developments in statistical shape analysis of shape graphs, and demonstrates them using analysis of complex data from retinal blood-vessel (RBV) networks. The shape graphs are represented by a set of nodes and edges (planar articulated curves) connecting some of these nodes. The goals are to utilize shapes of

Michele Mancarella, Nicola Borghi, Stefano Foffa, Edwin Genoud-Prachex

A joint fit of the mass and redshift distributions of the population of Binary Black Holes detected with Gravitational-Wave observations can be used to obtain constraints on the Hubble parameter and on deviations from General Relativity in the propagation of Gravitational Waves. We first present applications of this technique to the latest catalog of Gravita

Canhao Chen, Guan-Hua Huang, Zhigang Wu

We study theoretically the zero temperature intrinsic anomalous Hall effect in an experimentally realized 2D spin-orbit coupled Bose gas. For anisotropic atomic interactions and as the spin-orbit coupling strength increases, the system undergoes a ground state phase transition from states exhibiting a total in-plane magnetization to those with a perpendicula

Brynmor Haskell, Marco Antonelli, Pierre Pizzochero

We investigate the effect of a pinned superfluid component on the gravitational wave emission of a rotating neutron star. Pinning of superfluid vortices to the flux-tubes in the outer core (where the protons are likely to form a type-II superconductor) is a possible mechanism to sustain long-lived and non-axisymmetric neutron currents in the interior, that b

M. Bogoya, S. M. Grudsky, S. Serra-Capizzano

The present work is devoted to the eigenvalue asymptotic expansion of the Toeplitz matrix $T_{n}(a)$ whose generating function $a$ is complex valued and has a power singularity at one point. As a consequence, $T_{n}(a)$ is non-Hermitian and we know that the eigenvalue computation is a non-trivial task in the non-Hermitian setting for large sizes. We follow t

Michael Fürst, Priyash Bhugra, René Schuster, Didier Stricker

Object permanence is the concept that objects do not suddenly disappear in the physical world. Humans understand this concept at young ages and know that another person is still there, even though it is temporarily occluded. Neural networks currently often struggle with this challenge. Thus, we introduce explicit object permanence into two stage detection ap

Carmen Palomares, for DUNE Collaboration

The Deep Underground Neutrino Experiment (DUNE) is a dual-site experiment for long-baseline neutrino oscillation studies, able to resolve the neutrino mass hierarchy and measure $\delta_{CP}$. DUNE will also have sensitivity to supernova neutrinos and to processes beyond the Standard Model, such as nucleon decay searches. The Far Detector (FD) will consist o

Maithili Patel, Sonia Chernova

Proactive robot assistance enables a robot to anticipate and provide for a user's needs without being explicitly asked. We formulate proactive assistance as the problem of the robot anticipating temporal patterns of object movements associated with everyday user routines, and proactively assisting the user by placing objects to adapt the environment to their

Charlotte Wehner, Julian Merrick, Bradley Shirley, Brandon Weatherford

Presently, the manufacturing of active RF devices like klystrons is dominated by expensive and time consuming cycles of machining and brazing. In this article we characterize the RF properties of X-band klystron cavities and an integrated circuit manufactured with a novel additive manufacturing process. Parts are 3D printed in 316L stainless steel with direc

Sebastian Rickelhoff, Alexander Schnurr

In the development of stochastic integration and the theory of semimartingales, Markov processes have been a constant source of inspiration. Despite this historical interweaving, it turned out that semimartingales should be considered the `natural' class of processes for many concepts first developed in the Markovian framework. As an example, stochastic diff

Philipp Pilar, Niklas Wahlström

Physics-informed neural networks (PINNs) constitute a flexible approach to both finding solutions and identifying parameters of partial differential equations. Most works on the topic assume noiseless data, or data contaminated with weak Gaussian noise. We show that the standard PINN framework breaks down in case of non-Gaussian noise. We give a way of resol

Géza Ódor, Shengfeng Deng

The second-order Kuramoto equation describes synchronization of coupled oscillators with inertia, which occur in power grids for example. Contrary to the first-order Kuramoto equation it's synchronization transition behavior is much less known. In case of Gaussian self-frequencies it is discontinuous, in contrast to the continuous transition for the first-or

Manuel Brinker, Marc Thelen, Manfred May, Dagmar Rings

Macroscopic strain experiments revealed that Si crystals traversed by parallel, channel-like nanopores functionalized with the muscle polymer polypyrrole exhibit large and reversible electrochemo-mechanical actuation in aqueous electrolytes. On the microscopical level this system still bears open questions, as to how the electrochemical expansion and contrac

Giuseppe Gaetano Luciano

Flavor/mass dichotomy} for mixed fields is one of the most controversial issues in Quantum Field Theory. In this work we approach the problem by considering mixing of neutrinos and computing the transition amplitude for the paradigmatic neutron $\beta$-decay $n\,\rightarrow\, p \,+\,e^ \,+\,\bar\nu$. Calculations are developed by utilizing the following diff

Mehdi Testouri, Gamal Elghazaly, Raphael Frank

Automated Driving Systems (ADS) have rapidly evolved in recent years and their architecture becomes sophisticated. Ensuring robustness, reliability and safety of performance is particularly important. The main challenge in building an ADS is the ability to meet certain stringent performance requirements in terms of both making safe operational decisions and

Ajay Manicka, Andrew Stephan, Sriram Chari, Gemma Mendonsa

Technologies for sequencing (reading) and synthesizing (writing) DNA have progressed on a Moore's law-like trajectory over the last three decades. This has motivated the idea of using DNA for data storage. Theoretically, DNA-based storage systems could out-compete all existing forms of archival storage. However, a large gap exists between what is theoretical