April 2023 arXiv papers — page 82

Dominik Braun

This master thesis deals with Blockchain Technology in mobile turn based peer to peer games. First, it investigates the capabilities of Blockchain Technology to be used for gaming applications. In this regard, among others, Proof-of-Mechanisms, Vote-based Consensus and several Performance Improvements are described. Second, several smart contracts are introd

Alex Simpson

This thesis operates within the framework of general relativity without curvature singularities. The motivation for this framework is explored, and several conclusions are drawn with a look towards future research. There are many ways to excise curvature singularities from general relativity; a full list of desirable constraints on candidate geometries is pr

Souvika Sarkar, Dongji Feng, Shubhra Kanti Karmaker Santu

Sentence encoders have indeed been shown to achieve superior performances for many downstream text-mining tasks and, thus, claimed to be fairly general. Inspired by this, we performed a detailed study on how to leverage these sentence encoders for the "zero-shot topic inference" task, where the topics are defined/provided by the users in real-time. Extensive

Nai-Bo Zhang, Bao-An Li

By inverting the observational data of several neutron star observables in the three dimensional parameter space of the constant speed of sound (CSS) model while fixing all hadronic Equation of State parameters at their currently known most probable values, we constrain the three parameters of the CSS model and their correlations. Using two lower radius limi

Petar Marević, David Regnier, Denis Lacroix

We show that collective multiphonon states in atomic nuclei emerge at high excitation energies when quantum fluctuations in the collective space are included beyond the independent-particle approximation. The quadrupole response of a nucleus is studied using an extension of the nuclear time-dependent density-functional theory that mixes several many-body tra

Randy S. Fishman

Unlike the Berry phase, the orbital angular momentum (OAM) of magnons with two-dimensional wavevector k in band n is not gauge invariant for arbitrary phase lambda_n(k). However, by integrating the OAM over the orientation $\phi $ of wavevector k, we construct a gauge-invariant function F_n(k). Like F_n(k), the average OAM for magnon band n in a circle of ra

Minning Zhu, Tzu-Wei Kuo, Chung-Tse Michael Wu

Owing to the data explosion and rapid development of artificial intelligence (AI), particularly deep neural networks (DNNs), the ever-increasing demand for large-scale matrix-vector multiplication has become one of the major issues in machine learning (ML). Training and evaluating such neural networks rely on heavy computational resources, resulting in signi

Nabil Kahale

We study the problem of estimating E(g(X)), where g is a real-valued function of d variables and X is a d-dimensional Gaussian vector with a given covariance matrix. We present a new unbiased estimator for E(g(X)) that combines the randomized dimension reduction technique with principal components analysis. Under suitable conditions, we prove that our algori

Fernando Barreiro Megino, Lincoln Bryant, Dirk Hufnagel, Kenyi Hurtado Anampa

The Large Hadron Collider (LHC) at CERN houses two general purpose detectors - ATLAS and CMS - which conduct physics programs over multi-year runs to generate increasingly precise and extensive datasets. The efforts of the CMS and ATLAS collaborations lead to the discovery of the Higgs boson, a fundamental particle that gives mass to other particles, represe

Martin Gugat, Jan Giesselmann

We consider a state estimation problem for gas flows in pipeline networks where hydrogen is blended into the natural gas. The flow is modeled by the quasi-linear isothermal Euler equations coupled to an advection equation on a graph. The flow through the vertices where the pipes are connected is governed by algebraic node conditions. The state is approximate

Waqar Ahmed, Pietro Morerio, Vittorio Murino

Existing Source-free Unsupervised Domain Adaptation (SUDA) approaches inherently exhibit catastrophic forgetting. Typically, models trained on a labeled source domain and adapted to unlabeled target data improve performance on the target while dropping performance on the source, which is not available during adaptation. In this study, our goal is to cope wit

Britta Späth

We determine the action of the automorphism group Aut$(G)$ on the set of irreducible characters Irr$(G)$ for all finite quasi-simple groups $G$. For groups of Lie type, this includes the construction of an Aut$(G)$-equivariant Jordan decomposition of characters (Theorem B). We prove a property called $A(\infty)$ which includes an extendibility statement, kno

Thanh-Dat Truong, Chi Nhan Duong, Pierce Helton, Ashley Dowling

The research in self-supervised domain adaptation in semantic segmentation has recently received considerable attention. Although GAN-based methods have become one of the most popular approaches to domain adaptation, they have suffered from some limitations. They are insufficient to model both global and local structures of a given image, especially in small

Alex V. Plyukhin

We consider a Brownian oscillator whose coupling to the environment may lead to the formation of a localized normal mode. For lower values of the oscillator's natural frequency, $\omega\le\omega_c$, the localized mode is absent and the unperturbed oscillator reaches thermal equilibrium. For higher values of $\omega>\omega_c$, when the localized mode is forme

Christopher C. Stark, Bin Ren, Meredith A. MacGregor, Ward S. Howard

HD 53143 is a mature Sun-like star and host to a broad disk of dusty debris, including a cold outer ring of planetesimals near 90 AU. Unlike most other inclined debris disks imaged at visible wavelengths, the cold disk around HD 53143 appears as disconnected "arcs" of material, with no forward scattering side detected to date. We present new, deeper Hubble S

Junehyoung Jeon, Boyuan Liu, Volker Bromm, Steven L. Finkelstein

Active galactic nuclei (AGN) in the early Universe are thought to be prominent sources of energy and ionizing photons that affected the growth of their host galaxy and their environment. However, it is still unclear how the supermassive black holes (SMBHs) that fuel these AGN grew to the observed high masses already at high redshifts. Observations of high-re

C. Aguiar, N. Dattani, I. Camps

To investigate the interaction between carbon and Mobius-type carbon nanobelts and nickel, cadmium, and lead nanoclusters, we utilized the semiempirical tight binding framework provided by xTB software. Through our calculations, we determined the lowest energy geometries, complexes stability, binding energy, and electronic properties. Our findings demonstrat

Sumit Dahal, Michael K. Brewer, Alex B. Akins, John W. Appel

We report on the disk-averaged absolute brightness temperatures of Venus measured at four microwave frequency bands with the Cosmology Large Angular Scale Surveyor (CLASS). We measure temperatures of 432.3 $\pm$ 2.8 K, 355.6 $\pm$ 1.3 K, 317.9 $\pm$ 1.7 K, and 294.7 $\pm$ 1.9 K for frequency bands centered at 38.8, 93.7, 147.9, and 217.5 GHz, respectively. W

Jie Gao, Yuchen Guo, Gionnieve Lim, Tianqin Zhang

Collaborative Qualitative Analysis (CQA) can enhance qualitative analysis rigor and depth by incorporating varied viewpoints. Nevertheless, ensuring a rigorous CQA procedure itself can be both demanding and costly. To lower this bar, we take a theoretical perspective to design the CollabCoder workflow, that integrates Large Language Models (LLMs) into key in

S. G. Vilhena, M. Dutra, O. Lourenço, P. J. Pompeia

This work investigates dark matter (DM) effects in compact objects in modified teleparallel gravity (MTG) in which a modification of Teleparallel Equivalent to General Relativity is used. We applied a tetrad to the modified field equations where a set of relations is found. The conservation equation allows us to rewrite our Tolman-Oppenheimer-Volkoff equatio

Navid Aftabi, Dan Li, Ph. D., Thomas Sharkey

Industrial Control Systems (ICSs) are widely used in critical infrastructures that face various cyberattacks causing physical damage. With the increasing integration of the ICSs and information technology (IT), ensuring the security of ICSs is of paramount importance. In an ICS, cyberattacks exploit vulnerabilities to compromise sensors and controllers, aimi

Evgenii Egorov, Roberto Bondesan, Max Welling

Quantum error correction is a critical component for scaling up quantum computing. Given a quantum code, an optimal decoder maps the measured code violations to the most likely error that occurred, but its cost scales exponentially with the system size. Neural network decoders are an appealing solution since they can learn from data an efficient approximatio

Nils Lukas, Florian Kerschbaum

Deepfakes refer to content synthesized using deep generators, which, when misused, have the potential to erode trust in digital media. Synthesizing high-quality deepfakes requires access to large and complex generators only a few entities can train and provide. The threat is malicious users that exploit access to the provided model and generate harmful deepf

Matouš Kozák, Martin Jureček

Antivirus developers are increasingly embracing machine learning as a key component of malware defense. While machine learning achieves cutting-edge outcomes in many fields, it also has weaknesses that are exploited by several adversarial attack techniques. Many authors have presented both white-box and black-box generators of adversarial malware examples ca

Neel Nagarajan, Christopher Sneden, Melike Afsar, Catherine A. Pilachowski

We have gathered optical-region spectra, derived model atmosphere parameters, and computed elemental abundances for 15 red giant stars in the open cluster NGC 7789. We focus on the light element group CNOLi that provides clues to evolutionary changes associated with internal fusion events and chemical mixing. We confirm and extend an early report that NGC 77

Shreya Wadehra, Roula Nassif, Stefan Vlaski

Classical paradigms for distributed learning, such as federated or decentralized gradient descent, employ consensus mechanisms to enforce homogeneity among agents. While these strategies have proven effective in i.i.d. scenarios, they can result in significant performance degradation when agents follow heterogeneous objectives or data. Distributed strategies

Wei Gao

Penetration depth (PD) is essential for robotics due to its extensive applications in dynamic simulation, motion planning, haptic rendering, etc. The Expanding Polytope Algorithm (EPA) is the de facto standard for this problem, which estimates PD by expanding an inner polyhedral approximation of an implicit set. In this paper, we propose a novel optimization

Ryan Bilotta

The approach of Gao, Jafferis, and Wall to perturbatively construct traversable wormholes has seen success in a number of black hole backgrounds, particularly BTZ and $AdS_2$, whereas historically most wormhole solutions have been either found to violate the achronal ANEC, violate a classical no-go theorem, or exist only in astrophysically irrelevant spaceti

Payam Abdisarabshali, Nicholas Accurso, Filippo Malandra, Weifeng Su

Federated learning (FL) is a popular distributed machine learning (ML) technique in Internet of Things (IoT) networks, where resource-constrained devices collaboratively train ML models while preserving data privacy. However, implementation of FL over 5G-and-beyond wireless networks faces key challenges caused by (i) dynamics of the wireless network conditio

D. Yaremchuk, O. Kalyuzhnyi, J. Ilnytskyi

We consider a functional surface comprising thermoresponsive polymer chains, the material that has found numerous technological and biomedical applications. However, to achieve the required time and length scales for computer modelling of such applications, one is compelled to use coarse-grained mesoscopic modelling approaches. The model used here is based o

Zahid Hasan, Masud Ahmed, Abu Zaher Md Faridee, Sanjay Purushotham

Novel Categories Discovery (NCD) facilitates learning from a partially annotated label space and enables deep learning (DL) models to operate in an open-world setting by identifying and differentiating instances of novel classes based on the labeled data notions. One of the primary assumptions of NCD is that the novel label space is perfectly disjoint and ca

N. O. Santos, Anzhong Wang

We present a brief review of exact solutions of cylindrical symmetric fields in General Relativity produced by different perfect fluid sources. These sources are assumed static, stationary, translating and collapsing. Properties of these fields are discussed and some important open questions are called the attention for future research.

Chenliang Huang, Tommi Koskinen, Panayotis Lavvas, Luca Fossati

In the near-UV and optical transmission spectrum of the hot Jupiter WASP-121b, recent observations have detected strong absorption features of Mg, Fe, Ca, and H$\alpha$, extending outside of the planet's Roche lobe. Studying these atomic signatures can directly trace the escaping atmosphere and constrain the energy balance of the upper atmosphere. To underst

Freddy Cachazo, Nick Early, Yong Zhang

In a recent paper, we defined generalized color orderings (GCO) and Feynman diagrams (GFD) to compute color-dressed generalized biadjoint amplitudes. In this work, we study the Cachazo-Early-Guevara-Mizera (CEGM) representation of generalized partial amplitudes and ``decoupling" identities. This representation is a generalization of the Cachazo-He-Yuan (CHY)

B. Sana, M. Barik, M. Pregelj, U. Jena

The interplay between competing degrees of freedom can stabilize non-trivial magnetic states in correlated electron materials. Frustration-induced strong quantum fluctuations can evade long-range magnetic ordering leading to exotic quantum states such as spin liquids in two-dimensional spin-lattices such as triangular and kagome structures. However, the expe

Jingrong Chen, Yongji Wu, Shihan Lin, Yechen Xu

Remote Procedure Call (RPC) is a widely used abstraction for cloud computing. The programmer specifies type information for each remote procedure, and a compiler generates stub code linked into each application to marshal and unmarshal arguments into message buffers. Increasingly, however, application and service operations teams need a high degree of visibi

Sizhe Wang, Wenwen Li, Zhining Gu

Knowledge graphs are a key technique for linking and integrating cross-domain data, concepts, tools, and knowledge to enable data-driven analytics. As much of the worlds data have become massive in size, visualizing graph entities and their interrelationships intuitively and interactively has become a crucial task for ingesting and better utilizing graph con

Lindsay R. House, Karl Gebhardt, Keely Finkelstein, Erin Mentuch Cooper

We present analysis using a citizen science campaign to improve the cosmological measures from the Hobby-Eberly Telescope Dark Energy Experiment (HETDEX). The goal of HETDEX is to measure the Hubble expansion rate, $H(z)$, and angular diameter distance, $D_A(z)$, at $z =$ 2.4, each to percent-level accuracy. This accuracy is determined primarily from the tot

Cyrus Mostajeran, Nathaël Da Costa, Graham Van Goffrier, Rodolphe Sepulchre

Differential geometric approaches to the analysis and processing of data in the form of symmetric positive definite (SPD) matrices have had notable successful applications to numerous fields including computer vision, medical imaging, and machine learning. The dominant geometric paradigm for such applications has consisted of a few Riemannian geometries asso

Boy Lankhaar, Richard Teague

Magnetic fields are predicted to have a crucial impact on the structure, evolution and chemistry of protoplanetary disks. However, a direct detection of the magnetic field towards these objects has yet to be achieved. In order to characterize protoplanetary disk magnetic fields, we investigate the impact of the Zeeman effect on the (polarized) radiative tran

Ioannis Dalianis, Andreas Goudelis, Dimitrios Karamitros, Pantelis Papachristou

The freeze-in mechanism has been shown to allow the simultaneous generation of cosmic dark matter and a viable matter-antimatter asymmetry in the universe. When the underlying interactions are described by higher-dimensional, non-renormalizable operators, the relevant freeze-in processes take place close to the highest considered cosmic temperatures. In this

A. Ashoorioon, A. Yousefi-Sostani

The universe's current acceleration is a pretty recent phenomenon in cosmological time scales. This means that the modes that have left our horizon since the beginning of the contemporary acceleration phase, have not really reached the exact IR limit. Noting this observation, we reconsider the possibility of having a ghost condensate as dark energy with a si

Malik Wagih, Christopher A. Schuh

A computational method is presented to measure the spectrum of segregation energies for an interstitial solute at grain boundaries (GBs) in a polycrystal. For the Pd-H system, that spectrum of GB interstitial segregation energies is found to consist of a mixture of two normal-like distributions, characteristic of GB octahedral and tetrahedral sites. We also

Boyuan Zhang, Jiannan Tian, Sheng Di, Xiaodong Yu

Today's graphics processing unit (GPU) applications produce vast volumes of data, which are challenging to store and transfer efficiently. Thus, data compression is becoming a critical technique to mitigate the storage burden and communication cost. LZSS is the core algorithm in many widely used compressors, such as Deflate. However, existing GPU-based LZSS

Mayank Ratan Bhardwaj, Bazil Ahmed, Prathik Diwakar, Ganesh Ghalme

Procuring agricultural inputs (agri-inputs for short) such as seeds, fertilizers, and pesticides, at desired quality levels and at affordable cost, forms a critical component of agricultural input operations. This is a particularly challenging problem being faced by small and marginal farmers in any emerging economy. Farmer collectives (FCs), which are coope

Nardjess Benoudina, Nassim Bessaad

In this paper, the new (2+1)-dimensional Burgers equation has been derived using the Burgers equation' recursion operator as follows \begin{equation*} u_{xt}+\left(u_{t}+uu_{x}-\nu u_{xx}\right)_{y}+3\left(u_{x}\partial_{x}^{-1}u_{y}\right)_{x}=0 \end{equation*} This nonlinear model is an interesting generalization of the Burgers equation. Because of its com

Alejandro Argaez-Garcia, Javier Diaz-Vargas, Luis Eli Pech-Moreno

We give sufficient conditions to determine the existence of nontrivial solutions to the Fermat equation $x^3+y^3=kz^3$ over $\mathbb{Q}(\sqrt{d})$ by constructing a relationship with the points on the elliptic curve $y^2=x^3-432d^3k^2$ over $\mathbb{Q}$ for certain $k\in\mathbb{N}$.

David Bauer, Qi Wu, Kwan-Liu Ma

Volume data is commonly found in many scientific disciplines, like medicine, physics, and biology. Experts rely on robust scientific visualization techniques to extract valuable insights from the data. Recent years have shown path tracing to be the preferred approach for volumetric rendering, given its high levels of realism. However, real-time volumetric pa

David Radke, Kyle Tilbury

Mixed incentives among a population with multiagent teams has been shown to have advantages over a fully cooperative system; however, discovering the best mixture of incentives or team structure is a difficult and dynamic problem. We propose a framework where individual learning agents self-regulate their configuration of incentives through various parts of

Friedemann Kemm

Many low-Mach or all-Mach number codes are based on space discretizations which in combination with the first order explicit Euler method as time integration would lead to an unstable scheme. In this paper, we investigate how the choice of a suitable explicit time integration method can stabilize these schemes. We restrict ourselves to some old prototypical

Mouhamed Moustapha Fall, Marco Ghimenti, Anna Maria Micheletti, Angela Pistoia

We consider the Dirichlet eigenvalues of the fractional Laplacian $(-\Delta)^s$, with $s\in (0,1)$, related to a smooth bounded domain $\Omega$. We prove that there exists an arbitrarily small perturbation $\tilde\Omega=(I+\psi)(\Omega)$ of the original domain such that all Dirichlet eigenvalues of the fractional Laplacian associated to $\tilde\Omega$ are si

Chengming Zhang, Shaden Smith, Baixi Sun, Jiannan Tian

Collaborative filtering (CF) has been proven to be one of the most effective techniques for recommendation. Among all CF approaches, SimpleX is the state-of-the-art method that adopts a novel loss function and a proper number of negative samples. However, there is no work that optimizes SimpleX on multi-core CPUs, leading to limited performance. To this end,

Jérôme Rutinowski, Sven Franke, Jan Endendyk, Ina Dormuth

This contribution analyzes the self-perception and political biases of OpenAI's Large Language Model ChatGPT. Taking into account the first small-scale reports and studies that have emerged, claiming that ChatGPT is politically biased towards progressive and libertarian points of view, this contribution aims to provide further clarity on this subject. For th

Patrick Kinnear

We determine the dimension of the Kauffman bracket skein module at generic $q$ for mapping tori of the 2-torus, generalising the well-known computation of Carrega and Gilmer. In the process, we give a decomposition of the twisted Hochschild homology of the $G$-skein algebra for $G = \mathrm{SL}_N$ or $\mathrm{GL}_N$, which is a direct summand of the whole sk

Bulat Gafarov

It is well known that in the presence of heteroscedasticity ordinary least squares estimator is not efficient. I propose a generalized automatic least squares estimator (GALS) that makes partial correction of heteroscedasticity based on a (potentially) misspecified model without a pretest. Such an estimator is guaranteed to be at least as efficient as either

Marcel Algueró, Aritra Biswas, Bernat Capdevila, Sébastien Descotes-Genon

We discuss the impact of the recent LHCb update on the two lepton-flavour universality ratios $R_K$ and $R_{K^*}$, and the CMS update of $B({B_s \to \mu^+\mu^-})$ regarding the possibility of New Physics in $b\to s\ell^+\ell^-$ decays. We perform global fits of the New Physics Wilson coefficients defined in the model-independent approach of the Weak Effectiv

Jonas Schwab, Francesco Parisen Toldin, Fakher F. Assaad

We investigate the ground state phase diagram of an SU($N$)-symmetric antiferromagnetic spin model on a square lattice where each site hosts an irreducible representation of SU($N$) described by a square Young tableau of $N/2$ rows and $2S$ columns. We show that negative sign free fermion Monte Carlo simulations can be carried out for this class of quantum m

Andreas Köpf, Yannic Kilcher, Dimitri von Rütte, Sotiris Anagnostidis

Aligning large language models (LLMs) with human preferences has proven to drastically improve usability and has driven rapid adoption as demonstrated by ChatGPT. Alignment techniques such as supervised fine-tuning (SFT) and reinforcement learning from human feedback (RLHF) greatly reduce the required skill and domain knowledge to effectively harness the cap

Sun-Woo Kim, Lewis J. Conway, Chris J. Pickard, G. Lucian Pascut

Nitrogen-doped lutetium hydride has recently been proposed as a near-ambient-conditions superconductor. Interestingly, the sample transforms from blue to pink to red as a function of pressure, but only the pink phase is claimed to be superconducting. Subsequent experimental studies have failed to reproduce the superconductivity, but have observed pressure-dr

Tommy Chi Ho Lau, Man Hoi Lee

Direct $N$-body simulations of a large number of particles, especially in the study of planetesimal dynamics and planet formation, have been computationally challenging even with modern machines. This work presents the combination of fully parallelized $N^2/2$ interactions and the incorporation of the GENGA code's close encounter pair grouping strategy to en

Pranav Nagarajan, Kareem El-Badry, Antonio C. Rodriguez, Jan van Roestel

We present multi-epoch spectroscopic follow-up of a sample of ellipsoidal variables selected from Gaia DR3 as candidates for hosting quiescent black holes (BHs) and neutron stars (NSs). Our targets were identified as BH/NS candidates because their optical light curves -- when interpreted with models that attribute variability to tidal distortion of a star by

Jian Huang, Bin Luo, W. N. Brandt, Pu Du

We report strong and rapid X-ray variability found from the super-Eddington accreting quasar SDSS J081456.10+532533.5 at $z=0.1197$. It has a black-hole mass of $2.7\times10^{7}{M_{\odot}}$ and a dimensionless accretion rate of $\approx4$ measured from reverberation-mapping observations. It showed weak X-ray emission in the 2021 February Chandra observation,

X. Hernandez

The {\it Gaia} eDR3 catalogue has recently been used to study statistically the internal kinematics of wide binary populations using relative velocities of the two component stars, $\Delta V$, total binary masses, $m_{B}$, and separations, $s$. For $s \gtrsim 0.01$ pc, these binaries probe the low acceleration $a \lesssim 2a_{0}$ regime where gravitational a

Domenik Ehlert, Arjen van Vliet, Foteini Oikonomou, Walter Winter

Over the last decade, observations have shown that the mean mass of ultra-high-energy cosmic rays (UHECRs) increases progressively toward the highest energies. However, the precise composition is still unknown, and several theoretical studies hint at the existence of a subdominant proton component up to the highest energies. Motivated by the exciting prospec

Kiril Hristov

We consider the general thermal asymptotically flat Kerr-Newman black holes in 4d Einstein-Maxwell theory. Even though their thermodynamics has been understood for decades, the Gibbs free energy and on-shell action are only known implicitly as functions of the standard chemical potentials. Using the so-called left and right moving (or holomorphic and anti-ho

Neil Dowling, Pavel Kos, Kavan Modi

We show that out-of-time-order correlators (OTOCs) constitute a probe for Local-Operator Entanglement (LOE). There is strong evidence that a volumetric growth of LOE is a faithful dynamical indicator of quantum chaos, while OTOC decay corresponds to operator scrambling, often conflated with chaos. We show that rapid OTOC decay is a necessary but not sufficie

Dan Mao, Debanjan Chowdhury

Inspired by the discovery of superconductivity in moir\'e materials with isolated narrow bandwidth electronic bands, here we analyze critically the question of what is the maximum attainable $T_c$ in interacting flat-band systems. We focus specifically on the low-energy effective theory, where the density-density interactions are projected to the set of part

Isabelle John, Tim Linden

The annihilation of TeV-scale leptophilic dark matter into electron-positron pairs (hereafter $e^+e^-$) will produce a sharp cutoff in the local cosmic-ray $e^+e^-$ spectrum at an energy matching the dark matter mass. At these high energies, $e^+e^-$ cool quickly due to synchrotron interactions with magnetic fields and inverse-Compton scattering with the int

Jed McKinney, Sinclaire M. Manning, Olivia R. Cooper, Arianna S. Long

A growing number of far-infrared bright sources completely invisible in deep extragalactic optical surveys hint at an elusive population of z>4 dusty, star-forming galaxies. Cycle 1 JWST surveys are now detecting their rest-frame optical light, which provides key insight into their stellar properties and statistical constraints on the population as a whole.

Hessamaddin Arfaei, Alek Bedroya, Mahdi Torabian

Motivated by string theory, we propose that non-local quantum corrections to large extremal black holes must be suppressed by local higher-derivative terms (classical corrections). We show that this condition implies the species bound in all even dimensions, is motivated by Weak Gravity Conjecture, and is necessary for the mild form of the Weak Gravity Conje

Anqi Mao, Mehryar Mohri, Yutao Zhong

Cross-entropy is a widely used loss function in applications. It coincides with the logistic loss applied to the outputs of a neural network, when the softmax is used. But, what guarantees can we rely on when using cross-entropy as a surrogate loss? We present a theoretical analysis of a broad family of loss functions, comp-sum losses, that includes cross-en

Jose Arita-Escalante, Tyler Parsotan, S. Bradley Cenko

Despite their discovery about half a century ago, the Gamma-ray burst (GRB) prompt emission mechanism is still not well understood. Theoretical modeling of the prompt emission has advanced considerably due to new computational tools and techniques. One such tool is the PLUTO hydrodynamics code, which is used to numerically simulate GRB outflows. PLUTO uses A

Benjamin D Woods, Mark Friesen

Common proposals for realizing topological superconductivity and Majorana zero modes in semiconductor-superconductor hybrids require large magnetic fields, which paradoxically suppress the superconducting gap of the parent superconductor. Although two-channel schemes have been proposed as a way to eliminate magnetic fields, geometric constraints make their i

Amol Sasane

The ring of periodic distributions on ${\mathbb{R}}^{\tt d}$ with usual addition and with convolution is considered. Via Fourier series expansions, this ring is isomorphic to the ring ${\mathcal{S}}'({\mathbb{Z}}^{\tt d})$ of all maps $f:{\mathbb{Z}}^{\tt d}\rightarrow \mathbb{C}$ of at most polynomial growth (i.e., there exist a real $M>0$ and a nonnegative

Paz Hashash, Arkady Poliakovsky

In this paper we analyse functions in Besov spaces $B^{1/q}_{q,\infty}(\mathbb{R}^N,\mathbb{R}^d),q\in (1,\infty)$, and functions in fractional Sobolev spaces $W^{r,q}(\mathbb{R}^N,\mathbb{R}^d),r\in (0,1),q\in [1,\infty)$. We prove for Besov functions $u\in B^{1/q}_{q,\infty}(\mathbb{R}^N,\mathbb{R}^d)$ the summability of the difference between one-sided ap

Mitali Bafna, Dor Minzer

We study the complexity of affine Unique-Games (UG) over globally hypercontractive graphs, which are graphs that are not small set expanders but admit a useful and succinct characterization of all small sets that violate the small-set expansion property. This class of graphs includes the Johnson and Grassmann graphs, which have played a pivotal role in recen

Jaemyoung Lee, J. Richard Bond, Pavel Motloch, Alexander van Engelen

Gravitational lensing deflects the paths of photons, altering the statistics of cosmic backgrounds and distorting their information content. We take the Cosmic Infrared Background (CIB), which provides plentiful information about galaxy formation and evolution, as an example to probe the effect of lensing on non-Gaussian statistics. Using the Websky simulati

Erik Wessel, Vasileios Paschalidis, Antonios Tsokaros, Milton Ruiz

We explore the effect magnetic fields have on self-gravitating accretion disks around spinning black holes via numerical evolutions in full dynamical magnetohydrodynamic spacetimes. The configurations we study are unstable to the Papaloizou-Pringle Instability (PPI). PPI-saturated accretion tori have been shown to produce gravitational waves, detectable to c

Yuewei Wen, Nhat-Minh Nguyen, Dragan Huterer

We propose and numerically validate a new fitting formula that is sufficiently accurate to model the growth of structure in Horndeski theories of modified gravity for upcoming Stage IV and V large-scale structure surveys. Based on an analysis of more than 18,000 Horndeski models and adopting the popular parameterization of the growth rate $f(z) = \Omega_{M}(

Bryan Brandt, Prithviraj Dasgupta

We consider the problem of synthetically generating data that can closely resemble human decisions made in the context of an interactive human-AI system like a computer game. We propose a novel algorithm that can generate synthetic, human-like, decision making data while starting from a very small set of decision making data collected from humans. Our propos

Chandrodoy Chattopadhyay, Josh Ott, Thomas Schaefer, Vladimir Skokov

We describe numerical simulations of the stochastic diffusion equation with a conserved charge. We focus on the dynamics in the vicinity of a critical point in the Ising universality class. The model we consider is expected to describe the critical dynamics near a possible QCD critical point if the coupling of the order parameter to the momentum density of t

Gen Li, Yuling Yan, Yuxin Chen, Jianqing Fan

This paper studies reward-agnostic exploration in reinforcement learning (RL) -- a scenario where the learner is unware of the reward functions during the exploration stage -- and designs an algorithm that improves over the state of the art. More precisely, consider a finite-horizon inhomogeneous Markov decision process with $S$ states, $A$ actions, and hori

Alessia Gerbasi, Arianna Dagliati, Giuseppe Albi, Mattia Chiesa

The standard non-invasive imaging technique used to assess the severity and extent of Coronary Artery Disease (CAD) is Coronary Computed Tomography Angiography (CCTA). However, manual grading of each patient's CCTA according to the CAD-Reporting and Data System (CAD-RADS) scoring is time-consuming and operator-dependent, especially in borderline cases. This

Antonio Laface, Alex Massarenti

We introduce the notion of ample body of a projective variety and use it to prove emptiness results for Terracini loci and specific identifiability results for toric and homogeneous varieties.

Chris Hamilton, Tobias Heinemann

The linear response of a stellar system's gravitational potential to a perturbing mass comprises two distinct contributions. Most famously, the system will respond by forming a polarization 'wake' around the perturber. At the same time, the perturber may also excite one or more 'Landau modes', i.e. coherent oscillations of the entire stellar system which are

Simon van Wageningen, Tamara Mchedlidze, Alexandru Telea

Planar drawings of graphs tend to be favored over non-planar drawings. Testing planarity and creating a planar layout of a planar graph can be done in linear time. However, creating readable drawings of nearly planar graphs remains a challenge. We therefore seek to answer which edges of nearly planar graphs create clutter in their drawings generated by mains

Nicolò Cangiotti, Stefano Grasso

RNA folding prediction remains challenging, but can be also studied using a topological mathematical approach. In the present paper, the mathematical method to compute the topological classification of RNA structures and based on matrix field theory is shortly reviewed, as well as a computational software, McGenus, used for topological and folding prediction

Angel Esteban Labrador Rivas, Taufik Abrão

This paper deals with the reliability of random access (RA) protocols for massive wireless smart grid communication (m-SGC). We propose and analyze an improved grant-free RA (GF-RA) protocol for critical SG applications under strict QoS m-SGC requirements. At first, we discuss the main features of the SG neighborhood area network (NAN) architecture. We explo

Lazaros Tsaloukidis, José J. Fernández-Melgarejo, Javier Molina-Vilaplana, Piotr Surówka

The mechanical properties of crystals on curved substrates mix elastic, geometric and topological degrees of freedom. In order to elucidate the properties of such crystals we formulate the low-energy effective action that combines metric degrees of freedom with displacement fields and defects. We propose dualities for elasticity coupled to curved geometry fo

Robert M. Pettit, Farhang Hadad Farshi, Sean E. Sullivan, Álvaro Véliz-Osorio

The ultimate realization of a global quantum internet will require advances in scalable technologies capable of generating, storing, and manipulating quantum information. The essential devices that will perform these tasks in a quantum network are quantum repeaters, which will enable the long-range distribution of entanglement between distant network nodes.

Vassil M. Vassilev

In these notes, using the method of differential constraints, novel exact kink-like solutions are obtained for certain classes of complex Ginzburg--Landau equations with cubic-quintic nonlinearity. The foregoing solutions are presented in terms of the Lambert W function.

Gisela N. Ortiz-Leon, Sergio A. Dzib, Laurent Loinard, Yan Gong

In this Letter, we report Very Long Baseline Array observations of 22 GHz water masers toward the protostar CARMA-6, located at the center of the Serpens South young cluster. From the astrometric fits to maser spots, we derive a distance of 440.7+/-3.5 pc for the protostar (1% error). This represents the best direct distance determination obtained so far for

Salvador Pineda, Juan Miguel Morales, Asunción Jiménez-Cordero

The design of new strategies that exploit methods from Machine Learning to facilitate the resolution of challenging and large-scale mathematical optimization problems has recently become an avenue of prolific and promising research. In this paper, we propose a novel learning procedure to assist in the solution of a well-known computationally difficult optimi

Vincent Cohen-Addad, Hung Le, Marcin Pilipczuk, Michał Pilipczuk

We prove that there is a randomized polynomial-time algorithm that given an edge-weighted graph $G$ excluding a fixed-minor $Q$ on $n$ vertices and an accuracy parameter $\varepsilon>0$, constructs an edge-weighted graph~$H$ and an embedding $\eta\colon V(G)\to V(H)$ with the following properties: * For any constant size $Q$, the treewidth of $H$ is polynomi

Pavan Poojar Kunal Aggarwal, Marina Manso Jimeno, Sairam Geethanath

We investigated the repeatability of image quality metrics such as SNR, image uniformity, and geometrical distortion at 0.05T over ten days and three sessions per day. The measurements included temperature, humidity, transmit frequency, off-resonance maps, and 3D turbo spin echo (TSE) images of an in vitro phantom. This resulted in a protocol with nine pulse

Cheng-Tai Lee, Matthias Merkel

Athermal (i.e. zero-temperature) under-constrained systems are typically floppy, but they can be rigidified by the application of external strain, which is theoretically well understood. Here and in the companion paper, we extend this theory to finite temperatures for a very broad class of under-constrained systems. In the vicinity of the athermal transition

Andrey Akinshin

In this paper, we consider a generic scheme that allows building weighted versions of various quantile estimators, such as traditional quantile estimators based on linear interpolation of two order statistics, the Harrell-Davis quantile estimator and its trimmed modification. The obtained weighted quantile estimators are especially useful in the problem of e

Cheng-Tai Lee, Matthias Merkel

Athermal (i.e. zero-temperature) under-constrained systems are typically floppy, but they can be rigidified by the application of external strain. Following our recently developed analytical theory for the athermal limit, here and in the companion paper, we extend this theory to under-constrained systems at finite temperatures. Close to the athermal transiti

Ugnė Čižikovienė, Viktor Skorniakov

Initially announced by Dorfman in 1943, (Binomial) Group Testing (BGT) was quickly recognized as a useful tool in many other fields as well. To apply any particular BGT procedure effectively, one first of all needs to know an important operating characteristic, the so called Optimal Cut-Point (OCP), describing the limits of its applicability. The determinati

Mofassir ul Islam Arif, Mohsan Jameel, Josif Grabocka, Lars Schmidt-Thieme

The strength of machine learning models stems from their ability to learn complex function approximations from data; however, this strength also makes training deep neural networks challenging. Notably, the complex models tend to memorize the training data, which results in poor regularization performance on test data. The regularization techniques such as L