May 2022 arXiv papers — page 152

R. Paul Horja, Ludmil Katzarkov

We discuss a categorical approach to the theory of discriminants in the combinatorial language introduced by Gelfand, Kapranov and Zelevinsky. Our point of view is inspired by homological mirror symmetry and provides $K$--theoretic evidence for a conjecture presented by Paul Aspinwall in a conference talk in Banff in March 2016 and later in a joint paper wit

Mitsuyoshi Kamba, Ryoga Shimizu, Kiyotaka Aikawa

We propose and demonstrate purely optical feedback cooling of neutral nanoparticles in an optical lattice to an occupation number of $0.85\pm0.20$. The cooling force is derived from the optical gradients of displaced optical lattices produced with two sidebands on the trapping laser. To achieve highly accurate position observations required for cooling near

Peter Grünwald

A standard practice in statistical hypothesis testing is to mention the p-value alongside the accept/reject decision. We show the advantages of mentioning an e-value instead. With p-values, it is not clear how to use an extreme observation (e.g. p $\ll \alpha$) for getting better frequentist decisions. With e-values it is straightforward, since they provide

Nicola Franco, Tom Wollschlaeger, Nicholas Gao, Jeanette Miriam Lorenz

In recent years, quantum computers and algorithms have made significant progress indicating the prospective importance of quantum computing (QC). Especially combinatorial optimization has gained a lot of attention as an application field for near-term quantum computers, both by using gate-based QC via the Quantum Approximate Optimization Algorithm and by qua

Horacio Falomir, Joaquin Liniado, Pablo Pisani

In this article we study two-dimensional Dirac Hamiltonians with non-commutativity both in coordinates and momenta from an algebraic perspective. In order to do so, we consider the graded Lie algebra $\mathfrak{sl}(2|1)$ generated by Hermitian bilinear forms in the non-commutative dynamical variables and the Dirac matrices in $2+1$ dimensions. By further def

Eric Larsen, Emma Frejinger, Bernard Gendron, Andrea Lodi

We propose a methodology at the nexus of operations research and machine learning (ML) leveraging generic approximators available from ML to accelerate the solution of mixed-integer linear two-stage stochastic programs. We aim at solving problems where the second stage is highly demanding. Our core idea is to gain large reductions in online solution time whi

A. P. Misra, G. Banerjee

The formation of thermoacoustic shocks is studied in a fluid complex plasma. The thermoacoustic wave mode can be damped (or anti-damped) when the contribution from the thermoacoustic interaction is lower (or higher) than that due to the particle collision and/or the kinematic viscosity. In the nonlinear regime, the thermoacoustic wave, propagating with the a

Emmanuel Kwarteng, Mumin Cebe

Implantable Medical Devices (IMD) is a fast pace growing medical field and continues to grow in the foreseeable future. Advancement in science and technology has led to the IMD devices offering advanced medical treatments. Modern IMDs can automatically monitor and manage different patients' health conditions without any manual intervention from medical profe

Manuj Verma, Amit Priyadarshi, Saurabh Verma

There are many research available on the study of real-valued fractal interpolation function and fractal dimension of its graph. In this paper, our main focus is to study the dimensional results for vector-valued fractal interpolation function and its Riemann-Liouville fractional integral. Here, we give some results which ensure that dimensional results for

Jannis Blauth, Stephan Held, Dirk Müller, Niklas Schlomberg

We develop theoretical foundations and practical algorithms for vehicle routing with time-dependent travel times. We also provide new benchmark instances and experimental results. First, we study basic operations on piecewise linear arrival time functions. In particular, we devise a faster algorithm to compute the pointwise minimum of a set of piecewise line

Yue Guan, Mohammad Afshari, Qifan Zhang, Panagiotis Tsiotras

In this work we present a hierarchical framework for solving discrete stochastic pursuit-evasion games (PEGs) in large grid worlds. With a partition of the grid world into superstates (e.g., "rooms"), the proposed approach creates a two-resolution decision-making process, which consists of a set of local PEGs at the original state level and an aggreg

Yanan Sun, Jian-Ping Lv

The recent discovery of extraordinary-log universality has generated intense interest in classical and quantum boundary critical phenomena. Despite tremendous efforts, the existence of quantum extraordinary-log universality remains extremely controversial. Here, by utilizing quantum Monte Carlo simulations, we study the quantum edge criticality of a two-dime

Chen Xu, Piji Li, Wei Wang, Haoran Yang

Maintaining a consistent persona is essential for building a human-like conversational model. However, the lack of attention to the partner makes the model more egocentric: they tend to show their persona by all means such as twisting the topic stiffly, pulling the conversation to their own interests regardless, and rambling their persona with little curiosi

Simon Huhn, Leon Merten Lohse, Jens Lucht, Tim Salditt

Based on phase retrieval, lensless coherent imaging and in particular holography offers quantitative phase and amplitude images. This is of particular importance for spectral ranges where suitable lenses are challenging, such as for hard x-rays. Here, we propose a phase retrieval approach for inline x-ray holography based on Tikhonov regularization applied t

Vytautas Tumas, Sean Rivera, Damien Magoni, Radu State

XRP Ledger is one of the oldest, well-established blockchains. Despite the popularity of the XRP Ledger, little is known about its underlying peer-to-peer network. The structural properties of a network impact its efficiency, security and robustness. We aim to close the knowledge gap by providing a detailed analysis of the XRP overlay network. In this paper

Kejia Zhang

Graph Nerual Networks (GNNs) are effective models in graph embedding. It extracts shallow features and neighborhood information by aggregating neighbor information to learn the embedding representation of different nodes. However, the local topology information of many nodes in the network is similar, the network obtained by shallow embedding represents the

Jia-Bao Liu, Lu-Lu Fang, Qian Zheng, Xin-Bei Peng

Spectrum graph theory not only facilitate comprehensively reflect the topological structure and dynamic characteristics of networks, but also offer significant and noteworthy applications in theoretical chemistry, network science and other fields. Let $L_{n}^{8,4}$ represent a linear octagonal-quadrilateral network, consisting of $n$ eight-member ring and $n

Oriel Kiss, Michele Grossi, Pavel Lougovski, Federico Sanchez

The variational quantum eigensolver (VQE) is an algorithm to compute ground and excited state energy of quantum many-body systems. A key component of the algorithm and an active research area is the construction of a parametrized trial wavefunction -- a so called variational ansatz. The wavefunction parametrization should be expressive enough, i.e. represent

Jason Gross, Andres Erbsen, Jade Philipoom, Rajashree Agrawal

Compilers are a prime target for formal verification, since compiler bugs invalidate higher-level correctness guarantees, but compiler changes may become more labor-intensive to implement, if they must come with proof patches. One appealing approach is to present compilers as sets of algebraic rewrite rules, which a generic engine can apply efficiently. Now

Vipin Singh Sehrawat, Foo Yee Yeo, Dmitriy Vassilyev

We introduce a novel method to derandomize the learning with errors (LWE) problem by generating deterministic yet sufficiently independent LWE instances that are constructed by using linear regression models, which are generated via (wireless) communication errors. We also introduce star-specific key-homomorphic (SSKH) pseudorandom functions (PRFs), which ar

Robin Marin, Håkan Runvik, Alexander Medvedev, Stefan Engblom

In an effort to provide regional decision support for the public healthcare, we design a data-driven compartment-based model of COVID-19 in Sweden. From national hospital statistics we derive parameter priors, and we develop linear filtering techniques to drive the simulations given data in the form of daily healthcare demands. We additionally propose a post

Sandeep Kumar Acharya, Jens Chluba

The Sunyaev-Zeldovich effect towards clusters of galaxies has become a standard probe of cosmology. It is caused by the scattering of photons from the cosmic microwave background (CMB) by the hot cluster electron gas. In a similar manner, other photon backgrounds can be scattered when passing through the cluster medium. This problem has been recently conside

Yaroslav Lutsyshyn, Francisco Navarrete, Dieter Bauer

We develop an algorithm to solve tridiagonal systems of linear equations, which appear in implicit finite-difference schemes of partial differential equations (PDEs), being the time-dependent Schrödinger equation (TDSE) an ideal candidate to benefit from it. Our N-shaped partition method optimizes the implementation of the numerical calculation on parallel a

Alexey Kalugin

In the present paper, we study a relation between the cohomology of moduli stacks of smooth and proper curves $\mathcal M_{g,n}$ and the cohomology of ribbon graph complexes. The main results of this work are proofs of T. Willwacher's conjecture and A. C$\check{\mathrm a}$ld$\check{\mathrm a}$raru's conjecture about the cohomology of the Bridgeland d

Antoine Amarilli, Mikaël Monet

We consider a weighted counting problem on matchings, denoted $\textrm{PrMatching}(\mathcal{G})$, on an arbitrary fixed graph family $\mathcal{G}$. The input consists of a graph $G\in \mathcal{G}$ and of rational probabilities of existence on every edge of $G$, assuming independence. The output is the probability of obtaining a matching of $G$ in the resulti

Yong-Hui Lin, Hans-Werner Hammer, Ulf-G. Meißner

Using dispersion theory, the electromagnetic Sigma-to-Lambda transition form factors are expressed as the product of the pion electromagnetic form factor and the $Σ\barΛ\toππ$ scattering amplitudes with the latter estimated from SU(3) chiral perturbation theory including the baryon decuplet as explicit degrees of freedom. The contribution of the $K\bar{K}$ c

Rafael Cerna Loli, Onur Dizdar, Bruno Clerckx, Cong Ling

Effective and adaptive interference management is required in next generation wireless communication systems. To address this challenge, Rate-Splitting Multiple Access (RSMA), relying on multi-antenna rate-splitting (RS) at the transmitter and successive interference cancellation (SIC) at the receivers, has been intensively studied in recent years, albeit mo

Tao Lu, Chunxu Liu, Youxin Chen, Gangshan Wu

Aggregating neighbor features is essential for point cloud classification. In the existing work, each point in the cloud may inevitably be selected as the neighbors of multiple aggregation centers, as all centers will gather neighbor features from the whole point cloud independently. Thus each point has to participate in the calculation repeatedly and genera

Eleni Chatzikyriakou, Junliang Wang, Lucas Mazzella, Antonio Lacerda-Santos

In quantum nanoelectronics, numerical simulations have become an ubiquitous tool. Yet the comparison with experiments is often done at a qualitative level or restricted to a single device with a handful of fitting parameters. In this work, we assess the predictive power of these simulations by comparing the results of a single model with a large experimental

Guillaume Boisseau, Chad Nester, Mario Román

We show that the category of optics in a monoidal category arises naturally from the free cornering of that category. Further, we show that the free cornering of a monoidal category is a natural setting in which to work with comb diagrams over that category. The free cornering admits an intuitive graphical calculus, which in light of our work may be used to

Jun Lu

The goal of this paper is to debunk and dispel the magic behind black-box optimizers and stochastic optimizers. It aims to build a solid foundation on how and why the techniques work. This manuscript crystallizes this knowledge by deriving from simple intuitions, the mathematics behind the strategies. This tutorial doesn't shy away from addressing both the f

Min-xin Huang

We propose a novel modular anomaly equation for the unflavored Schur index in the $\mathcal{N}=4$ $SU(N)$ super-Yang-Mills theory. The vanishing conditions overdetermine the modular ambiguity ansatz from the equation, thus together they are sufficient to recursively compute the exact Schur indices for all $SU(N)$ gauge groups. Using the representations as Ma

Huan Yin, Zhiyi Lin, Justin K. W. Yeoh

Conventional sensor-based localization relies on high-precision maps, which are generally built using specialized mapping techniques involving high labor and computational costs. In the architectural, engineering and construction industry, Building Information Models (BIM) are available and can provide informative descriptions of environments. This paper exp

Yuto Yamamoto

Let $\left\{ Z_t \right\}_t$ be a one-parameter family of complex hypersurfaces of dimension $d \geq 1$ in a toric variety. We compute asymptotics of period integrals for $\left\{ Z_t \right\}_t$ by applying the method of Abouzaid--Ganatra--Iritani--Sheridan, which uses tropical geometry. As integrands, we consider Poincar\'{e} residues of meromorphic $(d+1)

Pavol Matlovič, Adriana Pisarčíková, Juraj Tóth, Pavel Mach

The hydrogen emission from meteors is assumed to originate mainly from the meteoroid composition, making it a potential tracer of H$_{2}$O molecules and organic compounds. H$α$ line was previously detected in individual fireballs, but its variation in a larger meteor dataset and dependency on the dynamical origin and physical properties have not yet been stu

Pedro Cardoso, Renato De Paula, Patrícia Gonçalves

In this article we derive the fractional porous medium equation for any power of the fractional Laplacian as the hydrodynamic limit of a microscopic dynamics of random particles with long range interactions, but the jump rate highly depends on the occupancy near the sites where the interactions take place.

Shekhar Suman

Throughout this manuscript the zeros are counted with multiplicity. We denote by $N(T)$ the number of zeros $\rho$ of $\zeta(s)$ in the critical strip upto height $T$ where $T>3$ is not an ordinate of zero of $\zeta(s)$. Denote by $N_0(T)$ the number of zeros $\rho$ of $\zeta(s)$ on the critical line upto height $T$. We first show that there exists $\epsilon

Haifan Chen, Guozhi Dong, Wei Liu, Ziqing Xie

Second-order flows in this paper refer to some artificial evolutionary differential equations involving second-order time derivatives distinguished from gradient flows which are considered to be first-order flows. This is a popular topic due to the recent advances of inertial dynamics with damping in convex optimization. Mathematically, the ground state of a

V. A. Abalmasov, B. E. Vugmeister

We study the J1-J2 Ising model on the square lattice using the random local field approximation (RLFA) and Monte Carlo (MC) simulations for various values of the ratio p = J2/|J1| with antiferromagnetic coupling J2, ensuring spin frustration. RLFA predicts metastable states with zero order parameter (polarization) at low temperature for p \in (0,1). This is

Michael Bate, Gerhard Röhrle, Damian Sercombe, David I. Stewart

We describe a straightforward construction of the pseudo-split absolutely pseudo-simple groups of minimal type with irreducible root systems of type $BC_n$; these exist only in characteristic $2$. We also give a formula for the dimensions of their irreducible modules.

Muhammad Khalil

This paper presents a new strategy for simultaneously reducing energy consumption, transmission delays, and bit error rate in Unmanned Aerial Vehicle UAV networks. A UAV is fitted with a wireless Bidirectional Relay BR to enable coverage network extension and increase transmission throughput. The downside of the BR advantages is the delay in data transmissio

Eurico Dias, Duarte Raposo, Homa Esfahanizadeh, Alejandro Cohen

Ultra-reliability and low-latency are pivotal requirements of the new 6th generation of communication systems (xURLLC). Over the past years, to increase throughput, adaptive active antennas were introduced in advanced wireless communications, specifically in the domain of millimeter-wave (mmWave). Consequently, new lower-layer techniques were proposed to cop

Siddhartha Patra, Abhirup Mukherjee, Anirban Mukherjee, N. S. Vidhyadhiraja

We study the overscreened multi-channel Kondo (MCK) model using the recently developed unitary renormalization group (URG) technique. Our results display the importance of ground state degeneracy in explaining various important properties like the breakdown of screening and the presence of local non-Fermi liquids. The impurity susceptibility of the intermedi

Sourav Chakraborty, Avijeet Ghosh, Sujata Ghosh, François Schwarzentruber

Public observation logic (POL) is a variant of dynamic epistemic logic to reason about agent expectations and agent observations. Agents have certain expectations, regarding the situation at hand, that are actuated by the relevant protocols, and they eliminate possible worlds in which their expectations do not match with their observations. In this work, we

Jin-Wei Wang, Xiao-Jun Bi, Peng-Fei Yin, Zhao-Huan Yu

Recently, the CDF collaboration reported a new measurement of the $W$ boson mass $M_W = 80.4335 \pm 0.0094$ GeV, which shows a $\sim 7σ$ deviation from the standard model prediction $80.3545 \pm 0.0057$ GeV obtained by the electroweak (EW) global fit. This deviation can be explained by new physics generating moderate EW oblique parameters $S$, $T$, and $U$.

Zhiwei Hu, Víctor Gutiérrez-Basulto, Zhiliang Xiang, Xiaoli Li

Multi-hop reasoning over real-life knowledge graphs (KGs) is a highly challenging problem as traditional subgraph matching methods are not capable to deal with noise and missing information. To address this problem, it has been recently introduced a promising approach based on jointly embedding logical queries and KGs into a low-dimensional space to identify

Inge S. Helland

In this article, the notion of a mathematical model in science is attempted to be enlightened from several points of view. In particular, it is shown that mathematical models are introduced differently and used differently in different areas of science. In the present article the use of models in statistics is taken as a basis, but links are given to several

Matúš Benko, Patrick Mehlitz

During the last years, asymptotic (or sequential) constraint qualifications, which postulate upper semicontinuity of certain set-valued mappings and provide a natural companion of asymptotic stationarity conditions, have been shown to be comparatively mild, on the one hand, while possessing inherent practical relevance from the viewpoint of numerical solutio

Konrad Kollnig, Siddhartha Datta, Nigel Shadbolt

Desktop browser extensions have long allowed users to improve their experience online and tackle widespread harms on websites. So far, no equivalent solution exists for mobile apps, despite the fact that individuals now spend significantly more time on mobile than on desktop, and arguably face similarly widespread harms. In this work, we investigate mobile a

Kelvin Onggadinata, Pawel Kurzynski, Dagomir Kaszlikowski

An orthodox formulation of quantum mechanics relies on a set of postulates in Hilbert space supplemented with rules to connect it with classical mechanics such as quantisation techniques, correspondence principle, etc. Here we deduce a qubit and its dynamics straightforwardly from a discrete deterministic dynamics and conservation of the classical collision

Jonas K. Falkner, Daniela Thyssens, Lars Schmidt-Thieme

We propose a Large Neighborhood Search (LNS) approach utilizing a learned construction heuristic based on neural networks as repair operator to solve the vehicle routing problem with time windows (VRPTW). Our method uses graph neural networks to encode the problem and auto-regressively decodes a solution and is trained with reinforcement learning on the cons

Liangde Tao, Lin Chen, Lei Xu, Weidong Shi

The resilience of a voting system has been a central topic in computational social choice. Many voting rules, like plurality, are shown to be vulnerable as the attacker can target specific voters to manipulate the result. What if a local differential privacy (LDP) mechanism is adopted such that the true preference of a voter is never revealed in pre-election

Nicolas Champagnat, Sylvie Méléard, Sepideh Mirrahimi, Viet Chi Tran

We consider a stochastic model for the evolution of a discrete population structured by a trait with values on a finite grid of the torus, and with mutation and selection. Traits are vertically inherited unless a mutation occurs, and influence the birth and death rates. We focus on a parameter scaling where population is large, individual mutations are small

Ipsita Koley, Sunandan Adhikary, Rohit Rohit, Soumyajit Dey

Recent developments in the smart mobility domain have transformed automobiles into networked transportation agents helping realize new age, large-scale intelligent transportation systems (ITS). The motivation behind such networked transportation is to improve road safety as well as traffic efficiency. In this setup, vehicles can share information about their

Jean Alexandre, Janos Polonyi

A finite volume allows tunnelling between degenerate vacua in Quantum Field Theory, and leads to remarkable energetic features, arising from the competition of different saddle points in the partition function. We describe this competition for finite temperature at equilibrium, taking into account both static and (Euclidean) time-dependent saddle points. The

Sukanta Basu, Albert A. M. Holtslag

In this study, we utilize a novel approach to solve the Ekman equations for eddy viscosity profiles in the stable boundary layer. By doing so, a well-known expression for the stable boundary layer height by Zilitinkevich (Boundary-Layer Meteorology, 1972, Vol. 3, 141--145) is rediscovered.

Labh Singh, Monal Kashav, Surender Verma

In this work we have investigated the phenomenological consequences of two-zero textures of \textit{inverse} neutrino mass matrix ($M_ν^{-1}$) in light of the large mixing angle (LMA) and large mixing angle-\textit{dark} (LMA-D) solutions, later of which originates if neutrinos exhibit non-standard interactions with matter. Out of fifteen possibilities, only

Sándor J Kovács, Behrouz Taji

We develop a Hodge theoretic invariant for families of projective manifolds that measures the potential failure of an Arakelov-type inequality in higher dimensions, one that naturally generalizes the classical Arakelov inequality over regular quasi-projective curves. We show that for families of manifolds with ample canonical bundle this invariant is uniform

Jiangnan Li, Fandong Meng, Zheng Lin, Rui Liu

Conversational Causal Emotion Entailment aims to detect causal utterances for a non-neutral targeted utterance from a conversation. In this work, we build conversations as graphs to overcome implicit contextual modelling of the original entailment style. Following the previous work, we further introduce the emotion information into graphs. Emotion informatio

Vasileios Basiouris, George K. Leontaris

We investigate the low energy properties of an effective local model with flipped $SU(5)\times U(1)_χ$ gauge group, constructed within the framework of F-theory. Its origin is traced back to the $SO(10)$ symmetry -- associated with a geometric singularity of the compactification manifold -- broken by an internal flux which is turned on along the seven-brane

Benjamin Bach, Euan Freeman, Alfie Abdul-Rahman, Cagatay Turkay

This paper introduces design patterns for dashboards to inform dashboard design processes. Despite a growing number of public examples, case studies, and general guidelines there is surprisingly little design guidance for dashboards. Such guidance is necessary to inspire designs and discuss tradeoffs in, e.g., screenspace, interaction, or information shown.

Lukas Muttenthaler, Charles Y. Zheng, Patrick McClure, Robert A. Vandermeulen

A central goal in the cognitive sciences is the development of numerical models for mental representations of object concepts. This paper introduces Variational Interpretable Concept Embeddings (VICE), an approximate Bayesian method for embedding object concepts in a vector space using data collected from humans in a triplet odd-one-out task. VICE uses varia

Takahisa Iizuka, Hiroki Mori

This study investigated the effect of synthetic voice of conversational agent trained with spontaneous speech on human interactants. Specifically, we hypothesized that humans will exhibit more social responses when interacting with conversational agent that has a synthetic voice built on spontaneous speech. Typically, speech synthesizers are built on a speec

David Kiessling, Andrea Zanelli, Armin Nurkanović, Joris Gillis

In this paper, we propose a Feasible Sequential Linear Programming (FSLP) algorithm applied to time-optimal control problems (TOCP) obtained through direct multiple shooting discretization. This method is motivated by TOCP with nonlinear constraints which arise in motion planning of mechatronic systems. The algorithm applies a trust-region globalization stra

David Lobmaier, Rafael Konlechner, Stefan Schulte, Ingo Weber

Within this Technical Report, we present the full analysis of 61 routing protocols for Wireless Sensor Networks (WSNs) for the purposes of routing in Payment Channel Networks (PCNs). In addition, we present the full results of the implementation of the three algorithms E-TORA, TERP, and M-DART.

Will Johnson

We consider interpretable topological spaces and topological groups in a $p$-adically closed field $K$. We identify a special class of "admissible topologies" with topological tameness properties like generic continuity, similar to the topology on definable subsets of $K^n$. We show every interpretable set has at least one admissible topology, and ev

Yu Cheng, Bo Wang, Robby T. Tan

Monocular 3D human pose estimation has made progress in recent years. Most of the methods focus on single persons, which estimate the poses in the person-centric coordinates, i.e., the coordinates based on the center of the target person. Hence, these methods are inapplicable for multi-person 3D pose estimation, where the absolute coordinates (e.g., the came

Mike Kosek, Trinh Viet Doan, Simon Huber, Vaibhav Bajpai

The Domain Name System (DNS) is one of the most crucial parts of the Internet. Although the original standard defined the usage of DNS over UDP (DoUDP) as well as DNS over TCP (DoTCP), UDP has become the predominant protocol used in the DNS. With the introduction of new Resource Records (RRs), the sizes of DNS responses have increased considerably. Since thi

A. Kaps, A. Lauer, G. Camps-Valls, P. Gentine

Clouds play a key role in regulating climate change but are difficult to simulate within Earth system models (ESMs). Improving the representation of clouds is one of the key tasks towards more robust climate change projections. This study introduces a new machine-learning based framework relying on satellite observations to improve understanding of the repre

Ali Behrouz, Farnoosh Hashemi, Laks V. S. Lakshmanan

In applications such as biological, social, and transportation networks, interactions between objects span multiple aspects. For accurately modeling such applications, multilayer networks have been proposed. Community search allows for personalized community discovery and has a wide range of applications in large real-world networks. While community search h

Swapnil Barman

Investigation of the magnetic switching and magnetoresistive behaviour of nanoscale spin valve elements (SVs) of varying physical parameters such as shape, element size, dimensional aspect ratio, and array size is of vital importance for their application in future magnetic memory and storage devices. We have inspected the magnetic switching mechanism and ma

Corentin Dumery, François Protais, Sébastien Mestrallet, Christophe Bourcier

Polycube-maps are used as base-complexes in various fields of computational geometry, including the generation of regular all-hexahedral meshes free of internal singularities. However, the strict alignment constraints behind polycube-based methods make their computation challenging for CAD models used in numerical simulation via Finite Element Method (FEM).

Litan Kumar Das, Kumar Sankar Ray, Prakash Chandra Mali

The paper aims to develop a framework for coalgebraic fuzzy geometric logic by adding modalities to the language of fuzzy geometric logic. Using the methods of coalgebra, the modal operators are introduced in the language of fuzzy geometric logic. To define the modal operators, we introduce a notion of fuzzy-open predicate lifting. Based on coalgebras for an

Alice Bouillet

In this paper, we study moduli spaces of finite-dimensional Lie algebras with flat center, proving that the forgetful map from Lie p-algebras to Lie algebras is an affine fibration, and we point out a new case of existence of a p-mapping. Then we illustrate these results for the special case of Lie algebras of rank 3, whose moduli space we build and study ov

Olivier Carton, Sylvain Perifel

In this paper, we give a deterministic pushdown transducer and a normal sequence of digits compressed by it. This solves positively a question left open in a previous paper by V. Becher, P. A. Heiber and the first author.

Jannes Nys, Giuseppe Carleo

Through the introduction of auxiliary fermions, or an enlarged spin space, one can map local fermion Hamiltonians onto local spin Hamiltonians, at the expense of introducing a set of additional constraints. We present a variational Monte-Carlo framework to study fermionic systems through higher-dimensional (>1D) Jordan-Wigner transformations. We provide exac

Yusuf Turek, Janarbek Yuanbek, Ahmad Abliz

The transition from von Neumann's projective strong measurement to Aharonov's weak measurement has recently received large attention, theoretical and experimental. In this work, we present a general approach to describe the weak-to-strong measurement transition for Fock-state-based pointer pointer states, and analyze in some details the case of coher

Fangzhi Xu, Jun Liu, Qika Lin, Yudai Pan

Machine reading comprehension has aroused wide concerns, since it explores the potential of model for text understanding. To further equip the machine with the reasoning capability, the challenging task of logical reasoning is proposed. Previous works on logical reasoning have proposed some strategies to extract the logical units from different aspects. Howe

Rolf Andreasson, Robert J. Berman

Inspired by Fujita's algebro-geometric result that complex projective space has maximal degree among all K-semistable complex Fano varieties, we conjecture that the height of a K-semistable metrized arithmetic Fano variety X of relative dimension n is maximal when X is the projective space over the integers, endowed with the Fubini-Study metric. Our main res

Jakob Beise, Christian Glaser

Sensitivity to ultra-high-energy neutrinos ($E>10^{17}$eV) can be obtained cost-efficiently by exploiting the Askaryan effect in ice, where a particle cascade induced by the neutrino interaction produces coherent radio emission that can be picked up by antennas. As the near-surface ice properties change rapidly within the upper $\mathcal{O}$(100m), a good un

Arianne Meijer-van de Griend, Sarah Meng Li

Many quantum computers have constraints regarding which two-qubit operations are locally allowed. To run a quantum circuit under those constraints, qubits need to be mapped to different quantum registers, and multi-qubit gates need to be routed accordingly. Recent developments have shown that compiling strategies based on the Steiner tree provide a competiti

Ngoc Nhi Nguyen

We generalize the semiclassical Lp estimates of Koch, Tataru and Zworski in the setting of Schr{\"o}dinger operators with confining potentials to density matrices. This is motivated by the problem of the concentration of free fermionic particles in a trapping potential. Our proof relies on semiclassical and many-body tools. As an application, we provide boun

A. Zaccone

A recent Comment by W. T. Kranz is shown to be plagued by a serious mathematical error which makes its conclusions invalid.

Tomoaki Kumeda, Laura Laverdure, Karoliina Honkala, Marko M. Melander

The proton-coupled electron transfer (PCET) mechanism of the oxygen reduction reaction (ORR) is a long-standing enigma in electrocatalysis.

Hermann Kroll, Florian Plötzky, Jan Pirklbauer, Wolf-Tilo Balke

Knowledge bases allow effective access paths in digital libraries. Here users can specify their information need as graph patterns for precise searches and structured overviews (by allowing variables in queries). But especially when considering textual sources that contain narrative information, i.e., short stories of interest, harvesting statements from the

Aneesh P. Naik, Clare Burrage

The observed `planes of satellites' around the Milky Way and other nearby galaxies are notoriously difficult to explain under the $Λ$CDM paradigm. Here, we propose an alternative solution: domain walls arising in theories with symmetry-breaking scalar fields coupled to matter. Because of the matter coupling, satellite galaxies experience fifth forces as

Pandelis Dodos, Konstantinos Tyros

We obtain estimates for the Kolmogorov distance to appropriately chosen gaussians, of linear functions \[ \sum_{i\in [n]^d} θ_i X_i \] of random tensors $\boldsymbol{X}=\langle X_i:i\in [n]^d\rangle$ which are symmetric and exchangeable, and whose entries have bounded third moment and vanish on diagonal indices. These estimates are expressed in terms of intr

Ekim Yurtsever, Emeç Erçelik, Mingyu Liu, Zhijie Yang

State-of-the-art lidar-based 3D object detection methods rely on supervised learning and large labeled datasets. However, annotating lidar data is resource-consuming, and depending only on supervised learning limits the applicability of trained models. Self-supervised training strategies can alleviate these issues by learning a general point cloud backbone m

Nir Lazarovich, Yoav Moriah, Tali Pinsky

We prove that the knots and links that admit a 3-highly twisted irreducible diagram with more than two twist regions are hyperbolic. This should be compared with a result of Futer-Purcell for 6-highly twisted diagrams. While their proof uses geometric methods our proof is achieved by showing that the complements of such knots or links are unannular and atoro

Eyal Z. Goren, Ehud de Shalit

This paper is a continuation of [G-dS1]. We study foliations of two types on Shimura varieties $S$ in characteristic $p$. The first, which we call "tautological foliations", are defined on Hilbert modular varieties, and lift to characteristic $0$. The second, the "$V$-foliations", are defined on unitary Shimura varieties in characteristic $p$

Nicolò Oreste Pinciroli Vago, Piero Fraternali

Gravitational lensing is the relativistic effect generated by massive bodies, which bend the space-time surrounding them. It is a deeply investigated topic in astrophysics and allows validating theoretical relativistic results and studying faint astrophysical objects that would not be visible otherwise. In recent years Machine Learning methods have been appl

Heena Khanchandani, Dirk Ponge, Stefan Zaefferer, Baptiste Gault

High-manganese twinning-induced plasticity (TWIP) steels exhibit high strain hardening, high tensile strength, and high ductility, which make them attractive for structural applications. At low tensile strain rates, TWIP steels are prone to hydrogen embrittlement (HE). Here though, we study the hardening and strengthening resulting from electrochemical hydro

Adrien Banse, Zheming Wang, Raphaël M. Jungers

We consider stability analysis of constrained switching linear systems in which the dynamics is unknown and whose switching signal is constrained by an automaton. We propose a data-driven Lyapunov framework for providing probabilistic stability guarantees based on data harvested from observations of the system. By generalizing previous results on arbitrary s

Ya-Hsin Chang, Yun-Nung Chen

Spoken language understanding (SLU) is an essential task for machines to understand human speech for better interactions. However, errors from the automatic speech recognizer (ASR) usually hurt the understanding performance. In reality, ASR systems may not be easy to adjust for the target scenarios. Therefore, this paper focuses on learning utterance represe

Nan Hu, Xiaoqi Qin, Nan Ma, Yiming Liu

Intelligent edge network is maturing to enable smart and efficient transportation systems. In this letter, we consider unmanned aerial vehicle (UAV)-assisted vehicular networks where UAVs provide caching and computing services in complement with base station (BS). One major challenge is that vehicles need to obtain timely situational awareness via orchestrat

HeeSun Bae, Seungjae Shin, Byeonghu Na, JoonHo Jang

Noisy labels are inevitable yet problematic in machine learning society. It ruins the generalization of a classifier by making the classifier over-fitted to noisy labels. Existing methods on noisy label have focused on modifying the classifier during the training procedure. It has two potential problems. First, these methods are not applicable to a pre-train

Cheng Su, Xu-Tao Zeng, Yi Li, Nvsen Ma

Na$_{4-δ}$NiTeO$_{6}$ is a rare example in the transition-metal tellurate family of realizing an $S$ = 1 spin-chain structure. By performing neutron powder diffraction measurements, the ground-state magnetic structure of Na$_{4-δ}$NiTeO$_{6}$ is determined. These measurements reveal that below $T\rm_{N}$ ${\sim}$ 6.8(2) K, the Ni$^{2+}$ moments form a screwe

Zhuan Ye

Whether or not the classical solutions of the two-dimensional (2D) incompressible magnetohydrodynamics (MHD) equations with only Laplacian magnetic diffusion (without velocity dissipation) are globally well-posed is a difficult problem and remains completely open. In this paper, we establish the global regularity of solutions to the 2D incompressible MHD equ

Hyun Gyung Lee, Sooyoung Park, Meung Ho Seo, D. Cho

We propose a scheme that combines velocity-selective coherent population trapping (CPT) and Raman sideband cooling (RSC) for subrecoil cooling of optically trapped atoms outside the Lamb-Dicke regime. This scheme is based on an inverted $\mathsf{Y}$ configuration in an alkali-metal atom. It consists of a $Λ$ formed by two Raman transitions between the ground

Simon K. Schnyder, John J. Molina, Ryoichi Yamamoto, Matthew S. Turner

Epidemics of infectious diseases posing a serious risk to human health have occurred throughout history. During recent epidemics there has been much debate about policy, including how and when to impose restrictions on behaviour. Policymakers must balance a complex spectrum of objectives, suggesting a need for quantitative tools. Whether health services migh