July 2022 arXiv papers — page 138

I. Bonamassa, B. Gross, M. Laav, I. Volotsenko

Cascades are self-amplifying processes triggered by feedback mechanisms that may cause a substantial part of a macroscopic system to change its phase in response of a relatively small local event. The theoretical background for these phenomena is rich and interdisciplinary with interdependent networks providing a versatile "two-interactions" framework to stu

Sylwester J Rzoska, Aleksandra Drozd-Rzoska

The report presents results that can be considered as the reference for innovative generations of Supercritical Fluids (SCF), Liquid-Liquid (LL), and Liquid (L) extraction technologies. They are related to implementations of Critical Phenomena Physics for such applications not considered so far. For the gas-liquid critical point, the shift from SuperCritical

Stefan Lattner, Javier Nistal

Lossy audio codecs compress (and decompress) digital audio streams by removing information that tends to be inaudible in human perception. Under high compression rates, such codecs may introduce a variety of impairments in the audio signal. Many works have tackled the problem of audio enhancement and compression artifact removal using deep learning technique

G. Barrera, M. A. Högele, J. C. Pardo

This article establishes cutoff convergence or abrupt convergence of three statistical quantities for multivariate (Hurwitz) stable geometric Brownian motion: the autocorrelation function, the Wasserstein distance between the current state and its degenerate limiting measure, and, finally, anti-concentration probabilities, which yield a fine-tuned trade-off

A. Artemev, A. Belavin

In this article, we will show how to use Zamolodchikov's higher equations of motion in Liouville field theory to explicitly calculate $N$-point correlation numbers in minimal Liouville gravity for $N>4$. We find the explicit expression for the 5-point correlation numbers and compare it with calculations in the one-matrix models.

Alexey Kushnir, James Michelson

We explore the properties of optimal multi-dimensional auctions in a model where a single object of multiple qualities is sold to several buyers. Using simulations, we test some hypotheses conjectured by Belloni et al. [3] and Kushnir and Shourideh [7]. As part of this work, we provide the first open-source library for multi-dimensional auction simulations w

Raphael M. Tromer, Luiz A. Ribeiro Junior, Douglas S. Galvão

Closely packed quasi-hexagonal and quasi-tetragonal crystalline phase of C$_{60}$ molecules (named qHPC$_{60}$) was recently synthesized. Here, we used DFT simulations to investigate the electronic, optical, and mechanical properties of qHPC$_{60}$ monolayers. qHPC$_{60}$ has a moderate direct electronic bandgap, with anisotropic mechanical properties. Their

Clementa Alonso-González, Fernando Sanz Sánchez

Let $\xi$ be an analytic vector field in $\mathbb{R}^3$ with an isolated singularity at the origin and having only hyperbolic singular points after a reduction of singularities $\pi:M\to\mathbb{R}^3$. The union of the images by $\pi$ of the local invariant manifolds at those hyperbolic points, denoted by $\Lambda$, is composed of trajectories of $\xi$ accumu

Peter Frankl, Glenn Hurlbert

Given a graph $G$, let $\mu(G)$ denote the size of the smallest maximal independent set in $G$. A family of subsets is called a star if some element is in every set of the family. A split vertex has degree at least 3. Holroyd and Talbot conjectured the following Erd\H{o}s-Ko-Rado type statement about intersecting families of independent sets in graphs: if $1

Yotam Shapira, Sapir Cohen, Nitzan Akerman, Ady Stern

Entangling gates are an essential component of quantum computers. However, generating high-fidelity gates, in a scalable manner, remains a major challenge in all quantum information processing platforms. Accordingly, improving the fidelity and robustness of these gates has been a research focus in recent years. In trapped ions quantum computers, entangling g

Hongbin Chen, A. Liam Fitzpatrick, Emanuel Katz, Yuan Xin

We study Hamiltonian truncation in boosted frames. We consider the thermal and magnetic field deformations of the 2d Ising model using TCSA at finite momentum. We find that even with moderate momenta, the spectrum and time-dependent correlation functions become significantly less dependent on the volume of the system. This allows for a more reliable determin

Christian Hägg, Boris Shapiro, Michael Shapiro

The isodynamic points of a plane triangle are known to be the only pair of its centers invariant under the action of the Mobius group on the set of triangles. Generalizing this classical result, we introduce below the isodynamic map associating to a univariate polynomial of degree d at least 3 with at most double roots a polynomial of degree (at most) 2d-4 s

Trupti Patil, Sukanta Panda

In the present study, we investigate the interaction between dark energy and dark matter, particularly emphasizing the effects of curvature in the realm of Friedmann-Lemaitre-Robertson-Walker (FLRW) space-time. We examine the system by forming a dynamic set of equations for various critical points. Later, we study their stability characteristics and show tha

Guo-yuan Huang, Sudip Jana, Alvaro S. de Jesus, Farinaldo S. Queiroz

The Large Hadron electron Collider (LHeC) has been designed to push the field of deep inelastic scattering to the high energy and intensity frontier using an intense electron beam with a proton beam from the High Luminosity-Large Hadron Collider. However, LHeC is also a great laboratory for new physics. In this work, we propose a search for dark matter that

Ángel Arroyo, Pablo Blanc, Mikko Parviainen

We obtain an analytic proof for asymptotic H\"older estimate and Harnack's inequality for solutions to a discrete dynamic programming equation. The results also generalize to functions satisfying Pucci-type inequalities for discrete extremal operators. Thus the results cover a quite general class of equations.

Koustav Chandra, Juan Calderón Bustillo, Archana Pai, Ian Harry

Current matched-filter searches for gravitational waves from binary black-hole mergers compare the calibrated detector data to waveform templates that omit the higher-order mode content of the signals predicted by General Relativity. However, higher-order emission modes become important for highly inclined asymmetric sources with masses above $\simeq 100 M_\

M. Cvetic, C. N. Pope, B. F. Whiting, Haoyu Zhang

The mode stability of the Kerr black hole in four dimensions was demonstrated by Whiting in 1989, by separating the Teukolsky equation that describes gravitational perturbations and then transforming the radial and angular equations in such a way that the problem can be reformulated as a wave equation in an auxiliary spacetime in which the proof of stability

Dhyan Aranha, Adeel A. Khan, Alexei Latyntsev, Hyeonjun Park

Let $T$ be a split torus acting on an algebraic scheme $X$ with fixed locus $Z$. Edidin and Graham showed that on localized $T$-equivariant Chow groups, (a) push-forward $i_*$ along $i : Z \to X$ is an isomorphism, and (b) when $X$ is smooth the inverse $(i_*)^{-1}$ can be described via Gysin pullback $i^!$ and cap product with $e(N)^{-1}$, the inverse of th

Pilar Hernandez, Jacobo Lopez-Pavon, Nuria Rius, Stefan Sandner

We revisit the generation of a matter-antimatter asymmetry in the minimal extension of the Standard Model with two singlet heavy neutral leptons (HNL) that can explain neutrino masses. We derive an accurate analytical approximation to the solution of the complete linearized set of kinetic equations, which exposes the non-trivial parameter dependencies in the

Chinmayee Mishra, Stefan Ostermann, Farokh Mivehvar, B. Prasanna Venkatesh

Although crystallization is a ubiquitous phenomenon in nature, crystal formation and melting still remain fascinating processes with several open questions yet to be addressed. In this work, we study the emergent crystallization of a laser-driven dipolar Bose-Einstein condensate due to the interplay between long-range magnetic and effectively infinite-range

Dario De Santis, Donato Farina, Mohammad Mehboudi, Antonio Acín

We study how the number of employed modes impacts the ability to witness non-Markovian evolutions via correlation backflows in continuous-variable quantum dynamics. We first prove the existence of non-Markovian Gaussian evolutions that do not show any revivals in the correlations between the mode evolving through the dynamics and a single ancillary mode. We

Marco Simonte, Heinz Andernach, Marcus Brüggen, Dominik Schwarz

Giant radio galaxies (GRGs) are radio galaxies that have projected linear extents of more than 700 kpc or 1 Mpc, depending on definition. We have carried out a careful visual inspection in search of GRGs of the Bootes LOFAR Deep Field (BLDF) image at 150 MHz. We identified 74 GRGs with a projected size larger than 0.7 Mpc of which 38 are larger than 1 Mpc. T

David Rivera-Betancour, Matthieu Vilatte

We investigate the (conformally coupled) scalar field on a general Carrollian spacetime in arbitrary dimension. The analysis discloses electric and magnetic dynamics. For both, we provide the energy and the momenta of the field, accompanied by their conservation equations. We discuss the conservation and non-conservation properties resulting from the existen

Julia D. Hannukainen, Miguel F. Martinez, Jens H. Bardarson, Thomas Klein Kvorning

Local topological markers, topological invariants evaluated by local expectation values, are valuable for characterizing topological phases in materials lacking translation invariance. The Chern marker -- the Chern number expressed in terms of the Fourier transformed Chern character -- is an easily applicable local marker in even dimensions, but there are no

Lara Alegre, Jose Sabater, Philip Best, Rafaël I. J. Mostert

New-generation radio telescopes like LOFAR are conducting extensive sky surveys, detecting millions of sources. To maximise the scientific value of these surveys, radio source components must be properly associated into physical sources before being cross-matched with their optical/infrared counterparts. In this paper, we use machine learning to identify tho

Marc Mars, Carlos Peón-Nieto

We obtain a coordinate independent algorithm to determine the class of conformal Killing vectors of a locally conformally flat $n$-metric $\gamma$ of signature $(r,s)$ modulo conformal transformations of $\gamma$. This is done in terms of endomorphisms in the pseudo-orthogonal Lie algebra $\mathfrak{o}(r+1,s+1)$ up to conjugation of the its group $O(r+1,s+1)

Alexander Pickston, Joseph Ho, Andrés Ulibarrena, Federico Grasselli

Quantum conference key agreement (QCKA) allows multiple users to establish a secure key from a shared multi-partite entangled state. In a quantum network, this protocol can be efficiently implemented using a single copy of a N-qubit Greenberger-Horne-Zeilinger (GHZ) state to distil a secure N-user conference key bit, whereas up to N-1 entanglement pairs are

Imre Hagymási, Vincent Noculak, Johannes Reuther

We investigate the ground-state properties of the nearest-neighbor $S=1$ pyrochlore Heisenberg antiferromagnet using two complementary numerical methods, density-matrix renormalization group (DMRG) and pseudofermion functional renormalization group (PFFRG). Within DMRG, we are able to reliably study clusters with up to 48 spins by keeping 20 000 SU(2) states

Maurizio Firrotta, Vladimir Rosenhaus

We compute the amplitude for an excited string in any precisely specified state to decay into another excited string in any precisely specified state, via emission of a tachyon or photon. For generic and highly excited string states, the amplitude is a complicated function of the outgoing kinematic angle, sensitive to the precise state. We compute the square

Srimoyee Sen

I discretize axion string configuration coupled to a Dirac fermion, which in the continuum binds a massless chiral fermion in its core when the winding is one. I show that such a configuration can host one or more chiral fermions when regulated on the lattice. Realization of these chiral fermions relies on the presence of Wilson-like terms similar to the Wil

Ryota Shimada, Hideyuki Hotta, Takaaki Yokoyama

Solar magnetic fields comprise an 11-year activity cycle, represented by the number of sunspots. The maintenance of such a solar magnetic field can be attributed to fluid motion in the convection zone, i.e. a dynamo. This study conducts the mean-field analyses of the global solar dynamo simulation presented by Hotta et al. (2016). Although the study succeeds

Peizhi Mai, Benjamin E. Feldman, Philip W. Phillips

While the recent advances in topology have led to a classification scheme for electronic bands described by the standard theory of metals, a similar scheme has not emerged for strongly correlated systems such as Mott insulators in which a partially filled band carries no current. By including interactions in the topologically non-trivial Haldane model, we sh

Jubee Sohn, Margaret J. Geller, Mark Vogelsberger, Josh Borrow

We explore the redshift evolution of the dynamical properties of massive clusters and their brightest cluster galaxies (BCGs) at $z < 2$ based on the IllustrisTNG-300 simulation. We select 270 massive clusters with $M_{200} < 10^{14}~{\rm M}_{\odot}$ at $z = 0$ and trace their progenitors based on merger trees. From 67 redshift snapshots covering $z < 2$, we

Shreya Vardhan, Sašo Grozdanov, Samuel Leutheusser, Hong Liu

We present a formulation of magnetohydrodynamics which can be used to describe the evolution of strong magnetic fields in neutron star interiors. Our approach is based on viewing magnetohydrodynamics as a theory with a one-form global symmetry and developing an effective field theory for the hydrodynamic modes associated with this symmetry. In the regime whe

Ronny Frumkin, Eric Kuflik, Itay Lavie, Tal Silverwater

We study the general properties of the freezeout of a thermal relic. We give analytic estimates of the relic abundance for an arbitrary freezeout process, showing when instantaneous freezeout is appropriate and how it can be corrected when freezeout is slow. This is used to generalize the relationship between the dark mater mass and coupling that matches the

Paolo Suin, Steven N. Shore, Václav Pavlík

Context: Star clusters form within giant molecular clouds that are strongly altered by the feedback action of the massive stars, but the cluster still remains embedded in a dense, highly turbulent medium and interactions with ambient structures may modify its dynamical evolution from that expected if it were isolated. Aims: We aim to study coupling mechanism

Yann Gouttenoire

This book provides a thorough survey of the important questions at the interface between theoretical particle physics and cosmology. After discussing the theoretical and experimental physics revolution that led to the rise of the Standard Model in the past century, this volume reviews all major open puzzles, like the hierarchy problem, the small value of the

Makoto Miura

We discuss the problem on the connectedness of various webs of lattice polytopes by introducing a geometric point of view from the toric Mori theory. To this end, we provide a combinatorial description of toric Sarkisov links in terms of certain sets of lattice points, which we call primitive generating sets. In two dimensions, the description is further tra

Roberto Soria, Ruican Ma, Lian Tao, Shuang-Nan Zhang

We revisit various sets of published results from X-ray and optical studies of the Galactic black hole (BH) candidate MAXI J0637-430, which went into outburst in 2019. Combining the previously reported values of peak outburst luminosity, best-fitting radii of inner and outer accretion disk, viewing angle, exponential decay timescale and peak-to-peak separati

Joyce Lin, Jenny Wagner, Richard E. Griffiths

As established in previous papers of this series, observables in highly distorted and magnified multiple images caused by the strong gravitational lensing effect can be used to constrain the distorting properties of the gravitational lens at the image positions. If the background source is extended and contains substructure, like star forming regions, which

Guido Roberts-Borsani, Tommaso Treu, Charlotte Mason, Richard S. Ellis

The 100% detection rate of Ly$\alpha$ emission in a sample of four luminous $z\sim8$ galaxies with red Spitzer/IRAC colors suggests objects with unusual ionizing capabilities that created early ionized bubbles in a neutral era. Whether such bubbles reflect enhanced ionizing properties (nature) or an overdense environment (nurture), however, remains unclear.

J. Casares, T. Muñoz-Darias, M. A. P. Torres, D. Mata Sanchez

We present a new method to derive binary inclinations in quiescent black hole (BH) X-ray transients (XRTs), based on the depth of the trough (T) from double-peaked Ha emission profiles arising in accretion discs. We find that the inclination angle (i) is linearly correlated with T in phase-averaged spectra with sufficient orbital coverage (>~50 per cent) and

Silvan Fischbacher, Tomasz Kacprzak, Jonathan Blazek, Alexandre Refregier

Intrinsic alignment (IA) modelling and photometric redshift estimation are two of the main sources of systematic uncertainty in weak lensing surveys. We investigate the impact of redshift errors and their interplay with different IA models. Generally, errors on the mean $\delta_z$ and on the width $\sigma_z$ of the redshift bins can both lead to biases in co

Matthew Alessi, Ralph E. Pudritz

Recent surveys show that protoplanetary disks have lower levels of turbulence than expected based on their observed accretion rates. A viable solution to this is that magnetized disk winds dominate angular momentum transport. This has several important implications for planet formation processes. We compute the physical and chemical evolution of disks and th

Chitraang Murdia, Yasunori Nomura, Kyle Ritchie

We describe two different, but equivalent semiclassical views of black hole physics in which the equivalence principle and unitarity are both accommodated. In one, unitarity is built-in, while the black hole interior emerges only effectively as a collective phenomenon involving horizon (and possibly other) degrees of freedom. In the other, more widely studie

Michael S. Calzadilla, Michael McDonald, Megan Donahue, Brian R. McNamara

We present new, deep, narrow- and broad-band Hubble Space Telescope observations of seven of the most star-forming brightest cluster galaxies (BCGs). Continuum-subtracted [O II] maps reveal the detailed, complex structure of warm ($T \sim 10^4$ K) ionized gas filaments in these BCGs, allowing us to measure spatially-resolved star formation rates (SFRs) of ~6

Konstantin Pankrashkin, Marco Vogel

The spectral properties of two-dimensional Schr\"odinger operators with $\delta'$-potentials supported on star graphs are discussed. We describe the essential spectrum and give a complete description of situations in which the discrete spectrum is non-trivial but finite. A more detailed study is presented for the case of a star graph with two branches, in pa

Karl Krauth, Yixin Wang, Michael I. Jordan

Recommender systems play a key role in shaping modern web ecosystems. These systems alternate between (1) making recommendations (2) collecting user responses to these recommendations, and (3) retraining the recommendation algorithm based on this feedback. During this process the recommender system influences the user behavioral data that is subsequently use

Simon Caron-Huot, Frank Coronado, Anh-Khoi Trinh, Zahra Zahraee

How much spectral information is needed to determine the correlation functions of a conformal theory? We study this question in the context of planar supersymmetric Yang-Mills theory, where integrability techniques accurately determine the single-trace spectrum at finite 't Hooft coupling. Corresponding OPE coefficients are constrained by dispersive sum rule

Francisco M. Fernández

We show that the straightforward application of the discriminant to some physical problems may yield a trivial useless result. If the symmetry of the model matrix does not change with variations of the model parameter the discriminant may vanish for all values of the parameter due to degeneracy. We illustrate this problem by means of a simple $6\times6$ matr

Rohit Jena, Lukas Zhornyak, Nehal Doiphode, Pratik Chaudhari

Correctness of instance segmentation constitutes counting the number of objects, correctly localizing all predictions and classifying each localized prediction. Average Precision is the de-facto metric used to measure all these constituents of segmentation. However, this metric does not penalize duplicate predictions in the high-recall range, and cannot dist

Tian Tian, Kenny Young, Richard S. Sutton

Value iteration (VI) is a foundational dynamic programming method, important for learning and planning in optimal control and reinforcement learning. VI proceeds in batches, where the update to the value of each state must be completed before the next batch of updates can begin. Completing a single batch is prohibitively expensive if the state space is large

Samuel Goldstein, Minsu Park, Marco Raveri, Bhuvnesh Jain

We baseline with current cosmological observations to forecast the power of the Dark Energy Spectroscopic Instrument (DESI) in two ways: 1. the gain in constraining power of parameter combinations in the standard $\Lambda$CDM model, and 2. the reconstruction of quintessence models of dark energy. For the former task we use a recently developed formalism to e

Debarati Bhaumik, Diptish Dey, Subhradeep Kayal

Applications of multilevel models usually result in binary classification within groups or hierarchies based on a set of input features. For transparent and ethical applications of such models, sound audit frameworks need to be developed. In this paper, an audit framework for technical assessment of regression MLMs is proposed. The focus is on three aspects,

Weicai Ye, Xinyue Lan, Shuo Chen, Yuhang Ming

We present PVO, a novel panoptic visual odometry framework to achieve more comprehensive modeling of the scene motion, geometry, and panoptic segmentation information. Our PVO models visual odometry (VO) and video panoptic segmentation (VPS) in a unified view, which makes the two tasks mutually beneficial. Specifically, we introduce a panoptic update module

Anastasios N. Angelopoulos, Karl Krauth, Stephen Bates, Yixin Wang

When building recommendation systems, we seek to output a helpful set of items to the user. Under the hood, a ranking model predicts which of two candidate items is better, and we must distill these pairwise comparisons into the user-facing output. However, a learned ranking model is never perfect, so taking its predictions at face value gives no guarantee t

Benjamin Monmege, Julie Parreaux, Pierre-Alain Reynier

Weighted Timed Games (WTG for short) are the most widely used model to describe controller synthesis problems involving real-time issues. Unfortunately, they are notoriously difficult, and undecidable in general. As a consequence, one-clock WTGs have attracted a lot of attention, especially because they are known to be decidable when only non-negative weight

Bence Bécsy, Neil J. Cornish, Luke Zoltan Kelley

Hundreds of millions of supermassive black hole binaries are expected to contribute to the gravitational-wave signal in the nanohertz frequency band. Their signal is often approximated either as an isotropic Gaussian stochastic background with a power-law spectrum, or as an individual source corresponding to the brightest binary. In reality, the signal is be

Di Kang, Jiaxi Zhao, C. Tyler Dick, Xiang Liu

Built upon the risk analysis methodology (presented in the part I paper), this part II paper focuses on applying this methodology. Five illustrative scenarios were used to analyze the best or worst cases and compare the transportation risk differences between service options using unit trains and manifest trains. The comparison results indicate that if all t

Vatsal Panwar, Jean-Michel Désert, Kamen O. Todorov, Jacob L. Bean

Transmission spectra of exoplanets orbiting active stars suffer from wavelength-dependent effects due to stellar photospheric heterogeneity. WASP-19b, an ultra-hot Jupiter (T$_{eq}$ $\sim$ 2100 K), is one such strongly irradiated gas-giant orbiting an active solar-type star. We present optical (520-900 nm) transmission spectra of WASP-19b obtained across eig

Di Kang, Jiaxi Zhao, C. Tyler Dick, Xiang Liu

Transporting hazardous materials (hazmats) using tank cars has more significant economic benefits than other transportation modes. Although railway transportation is roughly four times more fuel-efficient than roadway transportation, a train derailment has greater potential to cause more disastrous consequences than a truck incident. Train types, such as uni

Ilya Grishkov, Roland Kromes, Thanassis Giannetsos, Kaitai Liang

This paper offers a prototype of a Hyperledger Fabric-IPFS based network architecture including a smart contract based encryption scheme that meant to improve the security of user's data that is being uploaded to the distributed ledger. A new extension to the self-encryption scheme was deployed by integrating data owner's identity into the encryption process

Jyong-Hao Chen

We introduce a simple framework for estimating lower bounds on the runtime of a broad class of adiabatic quantum algorithms. The central formula consists of calculating the variance of the final Hamiltonian with respect to the initial state. After examining adiabatic versions of certain keystone circuit-based quantum algorithms, this technique is applied to

Yibo Jiang, Victor Veitch

Real-world classification problems must contend with domain shift, the (potential) mismatch between the domain where a model is deployed and the domain(s) where the training data was gathered. Methods to handle such problems must specify what structure is common between the domains and what varies. A natural assumption is that causal (structural) relationshi

Tianyang Hu, Ruiqi Liu, Zuofeng Shang, Guang Cheng

Deep learning has gained huge empirical successes in large-scale classification problems. In contrast, there is a lack of statistical understanding about deep learning methods, particularly in the minimax optimality perspective. For instance, in the classical smooth decision boundary setting, existing deep neural network (DNN) approaches are rate-suboptimal,

Sina Chen, Ari Laor, Ehud Behar

Radio variability in some radio-quiet (RQ) active galactic nuclei suggests emission from regions close to the central engine, possibly the outer accretion disc corona. If the origins of the radio and the X-ray emission are physically related, their emission may be temporarily correlated, possibly with some time delays. We present the results of quasi-simulta

Jin Wan, Hui Yin, Zhenyao Wu, Xinyi Wu

Aiming to restore the original intensity of shadow regions in an image and make them compatible with the remaining non-shadow regions without a trace, shadow removal is a very challenging problem that benefits many downstream image/video-related tasks. Recently, transformers have shown their strong capability in various applications by capturing global pixel

Jie Li, Bo Yang, Wenbin Lin

The second post-Newtonian solution for the quasi-Keplerian motion of a test particle in the gravitational field of regular Bardeen black hole is derived. The solution is formulated in terms of the test particle's orbital energy and angular momentum, as well as the mass and magnetic charge of the Bardeen black hole. The leading effects of the magnetic charge

Daan Gordijn, Roland Kromes, Thanassis Giannetsos, Kaitai Liang

This work aims to provide a more secure access control in Hyperledger Fabric blockchain by combining multiple ID's, attributes, and policies with the components that regulate access control. The access control system currently used by Hyperledger Fabric is first completely analyzed. Next, a new implementation is proposed that builds upon the existing solutio

Nikolai Leopold

We study the time evolution of the Fr\"ohlich Hamiltonian in a mean-field limit in which many particles weakly couple to the quantized phonon field. Assuming that the particles are initially in a Bose-Einstein condensate and that the excitations of the phonon field are initially in a coherent state we provide an effective dynamics which approximates the time

Hasan Saad

In the 1960's, Birch proved that the traces of Frobenius for elliptic curves taken at random over a large finite field is modeled by the semicircular distribution (i.e. the usual Sato-Tate for non-CM elliptic curves). In analogy with Birch's result, a recent paper by Ono, the author, and Saikia proved that the limiting distribution of the normalized Frobeniu

Diptish Dey, Debarati Bhaumik

Despite the rising interest in chatbots, deployment has been slow in the retail sector. In the absence of comparative cross sector research on the user acceptance of chatbots in retail, we present a model and a research framework that proposes customer and chatbot antecedents using trust and customer satisfaction as relationship mediators and word of mouth a

Nuno Oliveira, Norberto Sousa, Isabel Praça

Electricity is a volatile power source that requires great planning and resource management for both short and long term. More specifically, in the short-term, accurate instant energy consumption forecasting contributes greatly to improve the efficiency of buildings, opening new avenues for the adoption of renewable energy. In that regard, data-driven approa

Ronaldo S. S. Vieira, Ricardo A. Mosna

There is a long tradition of studying chaotic trajectories in systems whose integrability is broken by means of an external perturbation. Here we explore a different route to chaos, in the dynamics of extended bodies, which arises due to finite-size corrections to the otherwise integrable motion of a test particle. We find that cyclic changes in the overall

Michał Buchała

For a given directed tree and weights associated with vertices from a subtree the completion problem is to determine if these weights may be completed in a way to obtain a bounded weighted shift on the whole tree, which possibly satisfies also some more restrictive conditions. In this paper we consider subnormal and completely hyper-expansive completion prob

Ashkan Irannezhad, Bauyrzhan K. Primkulov, Ruben Juanes, Benzhong Zhao

It is well-known that wettability exerts fundamental control over multiphase flow in porous media, which has been extensively studied in uniform-wet porous media. In contrast, multiphase flow in porous media with heterogeneous wettability (i.e., mixed-wet) is less well-understood, despite its common occurrence. Here, we study the displacement of silicone oil

Luka Milićević

We prove quantitative bounds for the inverse theorem for Gowers uniformity norms $\mathsf{U}^5$ and $\mathsf{U}^6$ in $\mathbb{F}_2^n$. The proof starts from an earlier partial result of Gowers and the author which reduces the inverse problem to a study of algebraic properties of certain multilinear forms. The bulk of the work in this paper is a study of the

Behrouz Zolfaghari, Abbas Yazdinejad, Ali Dehghantanha, Jacob Krzciok

In recent years, the existence of a significant cross-impact between Cloud computing and Internet of Things (IoT) has lead to a dichotomy that gives raise to Cloud-Assisted IoT (CAIoT) and IoT-Based Cloud (IoTBC). Although it is pertinent to study both technologies, this paper focuses on CAIoT, and especially its security issues, which are inherited from bot

Ioannis Caragiannis, Shivika Narang

We consider a novel setting where a set of items are matched to the same set of agents repeatedly over multiple rounds. Each agent gets exactly one item per round, which brings interesting challenges to finding efficient and/or fair {\em repeated matchings}. A particular feature of our model is that the value of an agent for an item in some round depends on

Alexey Milekhin

In the large $N$ limit a physical system might acquire a residual entropy at zero temperature even without ground state degeneracy. At the same time poles in the 2-point function might coalesce and form a branch cut. Both phenomena are related to a high density of states in the large $N$ limit. In this short note we address the question: does a branch cut in

Dirk Oliver Theis

Banchi & Crooks (Quantum, 2021) have given methods to estimate derivatives of expectation values depending on a parameter that enters via what we call a "perturbed" quantum evolution $x\mapsto e^{i(x A + B)/\hbar}$. Their methods require modifications, beyond merely changing parameters, to the unitaries that appear. Moreover, in the case when the $B$-term is

Tao Shen, Zhihang Hu, Siqi Sun, Di Liu

Accurate prediction of RNA three-dimensional (3D) structure remains an unsolved challenge. Determining RNA 3D structures is crucial for understanding their functions and informing RNA-targeting drug development and synthetic biology design. The structural flexibility of RNA, which leads to scarcity of experimentally determined data, complicates computational

Emir Baysazan, A. Nihat Berker, Hasan Mandal, Hakan Kaygusuz

Intercity travel is one of the most important parameters for combating a pandemic. The ongoing COVID-19 pandemic has resulted in different computational studies involving intercity connections. In this study, the effects of intercity connections during an epidemic such as COVID-19 are evaluated using a new network model. This model considers the actual geogr

Muhammad Wildan Oktavian, Novanto Yudistira, Achmad Ridok

Alzheimer's disease is a progressive neurodegenerative disorder that gradually deprives the patient of cognitive function and can end in death. With the advancement of technology today, it is possible to detect Alzheimer's disease through Magnetic Resonance Imaging (MRI) scans. So that MRI is the technique most often used for the diagnosis and analysis of th

Ashkan Mirzaei, Yash Kant, Jonathan Kelly, Igor Gilitschenski

Obtaining 3D object representations is important for creating photo-realistic simulations and for collecting AR and VR assets. Neural fields have shown their effectiveness in learning a continuous volumetric representation of a scene from 2D images, but acquiring object representations from these models with weak supervision remains an open challenge. In thi

Tiziano Guadagnino, Luca Di Giammarino, Giorgio Grisetti

Pose graph optimization is a non-convex optimization problem encountered in many areas of robotics perception. Its convergence to an accurate solution is conditioned by two factors: the non-linearity of the cost function in use and the initial configuration of the pose variables. In this paper, we present HiPE, a novel hierarchical algorithm for pose graph i

Jeong-Jae Kim, Yeseul Jeon, SuMin Yu, Junggu Choi

There have been several attempts to use deep learning based on brain fMRI signals to classify cognitive impairment diseases. However, deep learning is a hidden black box model that makes it difficult to interpret the process of classification. To address this issue, we propose a novel analytical framework that interprets the classification result from deep l

Yongming Rao, Zuyan Liu, Wenliang Zhao, Jie Zhou

In this paper, we present a new approach for model acceleration by exploiting spatial sparsity in visual data. We observe that the final prediction in vision Transformers is only based on a subset of the most informative tokens, which is sufficient for accurate image recognition. Based on this observation, we propose a dynamic token sparsification framework

Chih-Chung Hsu, Chi-Han Tsai, Guan-Lin Chen, Sin-Di Ma

Computed tomography (CT) imaging could be very practical for diagnosing various diseases. However, the nature of the CT images is even more diverse since the resolution and number of the slices of a CT scan are determined by the machine and its settings. Conventional deep learning models are hard to tickle such diverse data since the essential requirement of

Zhirui Hu, Peiyan Dong, Zhepeng Wang, Youzuo Lin

Model compression, such as pruning and quantization, has been widely applied to optimize neural networks on resource-limited classical devices. Recently, there are growing interest in variational quantum circuits (VQC), that is, a type of neural network on quantum computers (a.k.a., quantum neural networks). It is well known that the near-term quantum device

Daniel Zeng, Tailin Wu, Jure Leskovec

Visual relations form the basis of understanding our compositional world, as relationships between visual objects capture key information in a scene. It is then advantageous to learn relations automatically from the data, as learning with predefined labels cannot capture all possible relations. However, current relation learning methods typically require sup

Giovanni Bartolomeo, Mehdi Yosofie, Simon Bäurle, Oliver Haluszczynski

Edge computing seeks to enable applications with strict latency requirements by utilizing compute resources deployed closer to the users. The diverse, dynamic, and constrained nature of edge infrastructures necessitates a flexible orchestration framework that dynamically supports application QoS requirements. However, existing state-of-the-art orchestration

Haowei Xu, Hua Wang, Ju Li

Nonlinear optical (NLO) effects have attracted great interest recently. However, by far the computational studies on NLO use the independent particle approximation and ignore many-body effects. Here we develop a generic Green's function framework to calculate the NLO response functions, which can incorporate various many-body interactions. We focus on the el

Sunay Bhat, Jeffrey Jiang, Omead Pooladzandi, Gregory Pottie

Variational autoencoders (VAEs) and other generative methods have garnered growing interest not just for their generative properties but also for the ability to dis-entangle a low-dimensional latent variable space. However, few existing generative models take causality into account. We propose a new decoder based framework named the Causal Counterfactual Gen

Jérôme Poineau

We prove that the mutual energy (or the intersection product in the sense of Arakelov theory) of two dynamical systems associated to Latt\`es morphisms over $\mathbf{\bar Q}$ is uniformly bounded below and deduce a proof of a conjecture of Bogomolov-Fu-Tschinkel: the number of common images of torsion points of two non-isomorphic elliptic curves over $\mathb

Paul Albert, Eric Arazo, Noel E. O'Connor, Kevin McGuinness

Using search engines for web image retrieval is a tempting alternative to manual curation when creating an image dataset, but their main drawback remains the proportion of incorrect (noisy) samples retrieved. These noisy samples have been evidenced by previous works to be a mixture of in-distribution (ID) samples, assigned to the incorrect category but prese

Hadeel Elayan, Andrew W. Eckford, Raviraj Adve

It has been established that Terahertz (THz) band signals can interact with biomolecules through resonant modes. Specifically, of interest here, protein activation. Our research goal is to show how directing the mechanical signaling inside protein molecules using THz signals can control changes in their structure and activate associated biochemical and biome

Vetle W. Ingeberg, Pete Jones, Lumkile Msebi, Sunniva Siem

The nuclear level density (NLD) and $\gamma$-ray strength function ($\gamma$SF) of $^{63}\mathrm{Ni}$ have been investigated using the Oslo method. The extracted NLD is compared with previous measurements using particle evaporation and those found from neutron resonance spacing. The $\gamma$SF was found to feature a strong low energy enhancement that could b

Francesco Faccio, Vincent Herrmann, Aditya Ramesh, Louis Kirsch

Goal-conditioned Reinforcement Learning (RL) aims at learning optimal policies, given goals encoded in special command inputs. Here we study goal-conditioned neural nets (NNs) that learn to generate deep NN policies in form of context-specific weight matrices, similar to Fast Weight Programmers and other methods from the 1990s. Using context commands of the

Kenneth D. Harris

We describe a statistical test for association of two autocorrelated time series, one of which generated randomly at each time point from a known but possibly history-dependent distribution. The null hypothesis is that at each time point, the two variables are independent, conditional on history until that time point. We define a test statistic that is a mar