October 2022 arXiv papers — page 37

Rodrigo Benenson, Vittorio Ferrari

The prevailing paradigm for producing semantic segmentation training data relies on densely labelling each pixel of each image in the training set, akin to colouring-in books. This approach becomes a bottleneck when scaling up in the number of images, classes, and annotators. Here we propose instead a pointillist approach for semantic segmentation annotation

Anna Doležalová, Ilmari Kangasniemi, Jani Onninen

We study continuity properties of Sobolev mappings $f \in W_{\mathrm{loc}}^{1,n} (\Omega, \mathbb{R}^n)$, $n \ge 2$, that satisfy the following generalized finite distortion inequality \[\lvert Df(x)\rvert^n \leq K(x) J_f(x) + \Sigma (x)\] for almost every $x \in \mathbb{R}^n$. Here $K \colon \Omega \to [1, \infty)$ and $\Sigma \colon \Omega \to [0, \infty)$

Yixuan Su, Nigel Collier

Generating text with autoregressive language models (LMs) is of great importance to many natural language processing (NLP) applications. Previous solutions for this task often produce text that contains degenerative expressions or lacks semantic consistency. Recently, Su et al. introduced a new decoding method, contrastive search, based on the isotropic repr

José González Cabañas, Patricia Callejo, Rubén Cuevas, Steffen Svatberg

Energy is today the most critical environmental challenge. The amount of carbon emissions contributing to climate change is significantly influenced by both the production and consumption of energy. Measuring and reducing the energy consumption of services is a crucial step toward reducing adverse environmental effects caused by carbon emissions. Millions of

Oscar Vikström, Alexander Ilin

With the recent successful adaptation of transformers to the vision domain, particularly when trained in a self-supervised fashion, it has been shown that vision transformers can learn impressive object-reasoning-like behaviour and features expressive for the task of object segmentation in images. In this paper, we build on the self-supervision task of maske

Yongtao Liu, Jonghee Yang, Benjamin J. Lawrie, Kyle P. Kelley

Underlying the rapidly increasing photovoltaic efficiency and stability of metal halide perovskites (MHPs) is the advance in the understanding of the microstructure of polycrystalline MHP thin film. Over the past decade, intense efforts have aimed to understand the effect of microstructure on MHP properties, including chemical heterogeneity, strain disorder,

V. P. Nair

Edge modes in gauge theories, whose raison d'etre is in the nature of the test functions used for imposing the Gauss law, have implications in many physical contexts. I discuss two such cases: 1) how edge modes are related to the interface term in the BFK formula and how they generate the so-called contact term for entanglement entropy in gauge theories, 2)

Fazlourrahman Balouchzahi, Grigori Sidorov, Alexander Gelbukh

Hope is characterized as openness of spirit toward the future, a desire, expectation, and wish for something to happen or to be true that remarkably affects human's state of mind, emotions, behaviors, and decisions. Hope is usually associated with concepts of desired expectations and possibility/probability concerning the future. Despite its importance, hope

Steffen Borgwardt, Stephan Patterson

The computation of exact barycenters for a set of discrete measures is of interest in applications where sparse solutions are desired, and to assess the quality of solutions returned by approximate algorithms and heuristics. The task is known to be NP-hard for growing dimension and, even in low dimensions, extremely challenging in practice due to an exponent

Camille Stock, Pauline McGinnis, Alessio Caratti o Garatti, Antonella Natta

The process of accretion in classical T Tauri stars (CTTSs) has been observed to vary on different timescales. Studying this variability is vital to understanding a star's evolution and provides insight into the complex processes at work within. Understanding the dichotomy between continuum veiling and emission line veiling is integral to accurately measurin

Nicholas E. Fuhr, Mohamed Azize, David J. Bishop

The chemical activity of ionized hydrogen describes the potency of protons in solution and is used to define the pH with wide-ranging applications in biological and materials sciences. Measuring pH with graphene field-effect transistors (FETs) has been described in the past but has yet to be characterized with a monolayer hexagonal boron nitride (hBN) cappin

B. A. Zambrano-Luna, W. A. Zúñiga-Galindo

The p-adic cellular neural networks (CNNs) are mathematical generalizations of the neural networks introduced by Chua and Yang in the 80s. In this work we present two new types of CNNs that can perform computations with real data, and whose dynamics can be understood almost completely. The first type of networks are edge detectors for grayscale images. The s

Salvador Bará, Carmen Bao-Varela, Fabio Falchi

Light pollution can be rigorously described in terms of the volume concentration of anthropogenic photons (light quanta) in the terrestrial atmosphere. This formulation, consistent with the basic physics of the emission, scattering and absorption of light, allows one to express light pollution levels in terms of particle volume concentrations, in a completel

Pace P. Nielsen

We very slightly improve the leading constant of the (currently best) proven asymptotic zero-free region of the Riemann zeta-function, by using an easy improvement to a trigonometric polynomial.

Jamie M. Taylor, David Pardo, Ignacio Muga

When using Neural Networks as trial functions to numerically solve PDEs, a key choice to be made is the loss function to be minimised, which should ideally correspond to a norm of the error. In multiple problems, this error norm coincides with--or is equivalent to--the $H^{-1}$-norm of the residual; however, it is often difficult to accurately compute it. Th

Chenguang Wang, Xiao Liu, Dawn Song

We introduce a new open information extraction (OIE) benchmark for pre-trained language models (LM). Recent studies have demonstrated that pre-trained LMs, such as BERT and GPT, may store linguistic and relational knowledge. In particular, LMs are able to answer ``fill-in-the-blank'' questions when given a pre-defined relation category. Instead of focusing o

Xihao Xie, Jia Zhang, Rahul Ramachandran, Tsengdar J. Lee

As service-oriented architecture becoming one of the most prevalent techniques to rapidly deliver functionalities to customers, increasingly more reusable software components have been published online in forms of web services. To create a mashup, it gets not only time-consuming but also error-prone for developers to find suitable services from such a sea of

Ionut Chiose, Rares Rasdeaconu

We provide a new cohomological obstruction to the existence of astheno-Kahler metrics, and study relevant examples.

S. Grouffal, A. Santerne, V. Bourrier, X. Dumusque

The Rossiter-McLaughlin (RM) effect is a method that allows us to measure the orbital obliquity of planets, which is an important constraint that has been used to understand the formation and migration mechanisms of planets, especially for hot Jupiters. In this paper, we present the RM observation of the Neptune-sized long-period transiting planet HIP41378 d

Yufan Zhou, Chunyuan Li, Changyou Chen, Jianfeng Gao

Text-to-image generation models have progressed considerably in recent years, which can now generate impressive realistic images from arbitrary text. Most of such models are trained on web-scale image-text paired datasets, which may not be affordable for many researchers. In this paper, we propose a novel method for pre-training text-to-image generation mode

Tiger Yu-Yang Hsiao, Dan Coe, Abdurro'uf, Lily Whitler

MACS0647$-$JD is a triply-lensed $z\sim11$ galaxy originally discovered with the Hubble Space Telescope. Here we report new JWST imaging, which clearly resolves MACS0647$-$JD as having two components that are either merging galaxies or stellar complexes within a single galaxy. Both are very small, with stellar masses $\sim10^8\,M_\odot$ and radii $r<100\,\rm

Xin Shu, Mengxuan Niu, Yi Zhang, Wei Luo

In off-axis Quantitative Phase Imaging (QPI), artificial neural networks have been recently applied for phase retrieval with aberration compensation and phase unwrapping. However, the involved neural network architectures are largely unoptimized and inefficient with low inference speed, which hinders the realization of real-time imaging. Here, we propose a N

Archana Morye, Aditya Sarma Phukon, Devichandrika V

Projective modules are a link between geometry and algebra as established by the theorem of Serre-Swan. In this paper, we define the super analog of projective modules and explore this link in the case of some particular super geometric objects. We consider the tangent bundle over the supersphere and show that the module of vector field over a supersphere is

David J. Thompson, Alexander A. Moiseev

Electron-positron pair production is the essential process for high-energy gamma-ray astrophysical observations. Following the pioneering OSO-3 counter telescope, the field evolved into use of particle tracking instruments, largely derived from high-energy physics detectors. Although many of the techniques were developed on balloon-borne gamma-ray telescopes

Ekta Singh, Mike N. Pionteck, Sven Reitzig, Michael Lange

Structural strain severely impacts material properties such as the linear and non-linear optical response. Moreover, strain plays a key role, e.g., in the physics of ferroelectrics and in particular of their domain walls. $\mu$-Raman spectroscopy is a well-suited technique for the investigation of such strain effects, as it allows to measure the lattice dyna

Chung Ting Ma, Wei Zhou, S. Joseph Poon

In spintronics, it is important to be able to manipulate magnetization rapidly and reliably. Several methods can control magnetization, such as by applying current pulses or magnetic fields. An applied current can reverse magnetization with nanosecond speed through the spin torque effect. For faster switching, subpicosecond switching with femtoseconds laser

Patrik Gubeljak, Tianhui Xu, Lorenzo Pedrazzetti, Oliver J. Burton

Identification of non-amplified DNA sequences and single-base mutations is essential for molecular biology and genetic diagnostics. This paper reports a novel sensor consisting of electrochemically-gated graphene coplanar waveguides coupled with a microfluidic channel. Upon exposure to analytes, propagation of electromagnetic waves in the waveguides is modif

Kolter Bradshaw, Petr Cagas, Ammar Hakim, Bhuvana Srinivasan

When a plasma sheath forms next to a dielectric wall, material properties determine electron absorption and reflection from the surface, impacting the sheath formation and structure. The low energy regime of this interaction is often not considered rigorously in emissive sheath simulations, but may be modeled from quantum mechanical first principles, and has

Shunke Ai, He Gao

GRB 221009A is a bright Gamma-ray burst (GRB) with isotropic energy being larger than $10^{54} ~{\rm ergs}$. Its fairly low redshift makes it a promising candidate for high energy neutrino detection. However, a neutrino search for this GRB reported by the IceCube collaboration yielded a null result. In this paper, we utilize the upper limit from IceCube obse

Tivadar Pongó, Tamás Börzsönyi, Raúl Cruz Hidalgo

The discharge of elongated particles from a silo with rotating bottom is investigated numerically. The introduction of a slight transverse shear reduces the flow rate $Q$ by up to 70% compared to stationary bottom, but the flow rate shows a modest increase by further increasing the external shear. Focusing on the dependency of flow rate $Q$ on orifice diamet

Xianliang Gong, Shuo Feng, Yulin Pan

Testing and evaluation are expensive but critical steps in the development of connected and automated vehicles (CAVs). In this paper, we develop an adaptive sampling framework to efficiently evaluate the accident rate of CAVs, particularly for scenario-based tests where the probability distribution of input parameters is known from the Naturalistic Driving D

Tobias Esswein, Nicola A. Spaldin

Motivated by the recent experimental discovery of strongly surface-plane-dependent superconductivity at surfaces of KTaO$_3$ single crystals, we calculate the electron-phonon coupling strength, $\lambda$, of doped KTaO$_3$ along the reciprocal-space high-symmetry directions. Using the Wannier-function approach implemented in the EPW package, we calculate $\l

Zhaolin Wang, Xidong Mu, Yuanwei Liu

A bidirectional integrated sensing and communication (ISAC) system is proposed, in which a pair of transceivers carry out two-way communication and mutual sensing. Both full-duplex and half-duplex operations in narrowband and wideband systems are conceived for the bidirectional ISAC. 1) For the narrowband system, the conventional full-duplex and half-duplex

Pradyumna Reddy, Paul Guerrero, Niloy J. Mitra

Finding an unsupervised decomposition of an image into individual objects is a key step to leverage compositionality and to perform symbolic reasoning. Traditionally, this problem is solved using amortized inference, which does not generalize beyond the scope of the training data, may sometimes miss correct decompositions, and requires large amounts of train

Vladimir Bobkov, Sergey Kolonitskii

For a smooth bounded domain $\Omega$ and $p \geq q \geq 2$, we establish quantified versions of the classical Friedrichs inequality $\|\nabla u\|_p^p - \lambda_1 \|u\|_q^p \geq 0$, $u \in W_0^{1,p}(\Omega)$, where $\lambda_1$ is a generalized least frequency. We apply one of the obtained quantifications to show that the resonant equation $-\Delta_p u = \lamb

Erik Mainellis

We introduce an analogue of the famous Schur multiplier in the context of associative trialgebras, or triassociative algebras. The latter were first studied by Loday and Ronco in 2001, and are characterized by three operations and eleven relations. The paper highlights an extension-theoretic crossroads of multipliers, covers, and unicentral triassociative al

Nobuyuki Yoshioka, Tsuyoshi Okubo, Yasunari Suzuki, Yuki Koizumi

The intensive pursuit for quantum advantage in terms of computational complexity has further led to a modernized crucial question: {\it When and how will quantum computers outperform classical computers?} The next milestone is undoubtedly the realization of quantum acceleration in practical problems. Here we provide a clear evidence and arguments that the pr

Gregory Moille, Xiyuan Lu, Jordan Stone, Daron Westly

Dispersion engineering of microring resonators is crucial for optical frequency comb applications, to achieve targeted bandwidths and powers of individual comb teeth. However, conventional microrings only present two geometric degrees of freedom -- width and thickness -- which limits the degree to which dispersion can be controlled. We present a technique wh

K. R. Khusnutdinova, M. R. Tranter

Coupled Boussinesq equations describe long weakly-nonlinear longitudinal strain waves in a bi-layer with a soft bonding between the layers (e.g. a soft adhesive). From the mathematical viewpoint, a particularly difficult case appears when the linear long-wave speeds in the layers are significantly different (high-contrast case). The traditional derivation of

Mário Raia Neto, Daniela Pérez, Joaquín Pelle

We compute the shadow cast by a charged Morris-Thorne wormhole when the light source is a star located beyond the mouth which is opposite to the observer. First, we provide an extensive analysis of the geodesic properties of the spacetime, both for null and massive particles. The geometrical properties of this solution are such that independently of the view

Jessica Meier, Luka Zurak, Andrea Locatelli, Thorsten Feichtner

Plasmonic dimer antennas create strong field enhancement by squeezing light into a nanoscale gap. These optical hotspots are highly attractive for boosting nonlinear processes, such as harmonic generation, photoelectron emission, and ultrafast electron transport. Alongside large field enhancement, such phenomena often require control over the field asymmetry

Michele Invernizzi, Andreas Krämer, Cecilia Clementi, Frank Noé

We combine replica exchange (parallel tempering) with normalizing flows, a class of deep generative models. These two sampling strategies complement each other, resulting in an efficient strategy for sampling molecular systems characterized by rare events, which we call learned replica exchange (LREX). In LREX, a normalizing flow is trained to map the config

Reinhard Wiesmayr, Gian Marti, Chris Dick, Haochuan Song

Even though machine learning (ML) techniques are being widely used in communications, the question of how to train communication systems has received surprisingly little attention. In this paper, we show that the commonly used binary cross-entropy (BCE) loss is a sensible choice in uncoded systems, e.g., for training ML-assisted data detectors, but may not b

Yujia Qin, Cheng Qian, Jing Yi, Weize Chen

Recent years have witnessed the prevalent application of pre-trained language models (PLMs) in NLP. From the perspective of parameter space, PLMs provide generic initialization, starting from which high-performance minima could be found. Although plenty of works have studied how to effectively and efficiently adapt PLMs to high-performance minima, little is

Shenjie Huang, Cheng Chen, Mohammad Dehghani Soltani, Robert Henderson

The sensitivity of the optical wireless communication (OWC) can be effectively improved by employing the highly sensitive single-photon avalanche diode (SPAD) arrays. However, the nonlinear distortion introduced by the dead time strongly limits the throughput of the SPAD-based OWC systems. Optical orthogonal frequency division multiplexing (OFDM) can be empl

Simon R. Blackburn, Jessica Claridge

The Additive-Multiplicative Matrix Channel (AMMC) was introduced by Silva, Kschischang and K\"otter in 2010 to model data transmission using random linear network coding. The input and output of the channel are $n\times m$ matrices over a finite field $\mathbb{F}_q$. On input the matrix $X$, the channel outputs $Y=A(X+W)$ where $A$ is a uniformly chosen $n\t

Shubhayan Sarkar

In recent times, device-independent certification of quantum states has been one of the intensively studied areas in quantum information. However, all such schemes utilise projective measurements which are practically difficult to generate. In this work, we consider the one-sided device-independent (1SDI) scenario, and propose a self-testing scheme for the t

Po-Liang Chen, Tian-Yun Chang, Pei-Sin Chen, Alvin Hsien-Yi Chan

Modern infrared (IR) microscopy, communication, and sensing systems demand control of the spectral characteristics and polarization states of light. Typically, these systems require the cascading of multiple filters, polarization optics and rotating components to manipulate light, inevitably increasing their sizes and complexities. Here, we report two-termin

Jonas Blessing, Michael Kupper

Based on the Chernoff approximation, we provide a general approximation result for convex monotone semigroups which are continuous w.r.t. the mixed topology on suitable spaces of continuous functions. Starting with a family $(I(t))_{t\geq 0}$ of operators, the semigroup is constructed as the limit $S(t)f:=\lim_{n\to\infty}I(\frac{t}{n})^n f$ and is uniquely

Christoph Aistleitner, Bence Borda, Manuel Hauke

In this paper, we study distributional properties of the sequence of partial quotients in the continued fraction expansion of fractions $a/N$, where $N$ is fixed and $a$ runs through the set of mod $N$ residue classes which are coprime with $N$. Our methods cover statistics such as the sum of partial quotients, the maximal partial quotient, the empirical dis

Song He, Li Li, Zhibin Li, Shao-Jiang Wang

Understanding the nature of quantum chromodynamics (QCD) matter is important but challenging due to the presence of non-perturbative dynamics under extreme conditions. We construct a holographic model describing the gluon sector of QCD at finite temperatures in the non-perturbative regime. The equation of state as a function of temperature is in good accorda

Yu Deng, Bernd Hofmann, Frank Werner

There is extensive mathematical literature on the inverse problem of deautoconvolution for a function with support in the unit interval $[0,1] \subset \mathbb R$, but little is known about the multidimensional situation. This article tries to fill this gap with analytical and numerical studies on the reconstruction of a real function of two real variables ov

Kavya. R. Nair, M. S. Sunitha

Fuzzy incidence graphs (FIG) model real world problems efficiently when there is an extra attribute of vertex-edge relationship. The article discusses the operations on Fuzzy incidence graphs. The join, Cartesian product, tensor product, and composition of FIGs are explored. The study is concentrated mainly on strong fuzzy incidence graphs (SFIG). The idea o

Niseem Magdy

The Multi-Phase Transport model (AMPT) is used to study the final state effects on the Symmetric Correlations (SC), Asymmetric Correlations (ASC), Normalized Symmetric Correlations (NSC), and Normalized Asymmetric Correlations (NASC) in Au+Au collisions at 200~GeV. The correlators' sensitivity to non-flow effects associated with long- and short-range non-flo

Julien Hauret, Thomas Joubaud, Véronique Zimpfer, Éric Bavu

In this paper, we present Extreme Bandwidth Extension Network (EBEN), a Generative Adversarial network (GAN) that enhances audio measured with body-conduction microphones. This type of capture equipment suppresses ambient noise at the expense of speech bandwidth, thereby requiring signal enhancement techniques to recover the wideband speech signal. EBEN leve

Sepideh Kianfar, Jorrit Leenaarts, Sara Esteban Pozuelo, João M. da Silva Santos

Fibrils in the solar chromosphere carry transverse oscillations as determined from non-spectroscopic imaging data. They are estimated to carry an energy flux of several $\mathrm{kW~m}^{-2}$, which is a significant fraction of the average chromospheric radiative energy losses. We aim to determine oscillation properties of fibrils not only in the plane-of-the-

Xiantao Li

Quantum speedup for mixing a Markov chain can be achieved based on the construction of slowly-varying $r$ Markov chains where the initial chain can be easily prepared and the spectral gaps have uniform lower bound. The overall complexity is proportional to $r$. We present a multi-level approach to construct such a sequence of $r$ Markov chains by varying a r

Anne-Edgar Wilke

In this article, we first try to make the known analogy between convexity and plurisubharmonicity more precise. Then we introduce a notion of strict plurisubharmonicity analogous to strict convexity, and we show how this notion can be used to study the strong maximum modulus principle in Banach spaces. As an application, we define a notion of $L^p$ direct in

Jonathan B. Hill, Tianqi Li

We propose a covariance stationarity test for an otherwise dependent and possibly globally non-stationary time series. We work in a generalized version of the new setting in Jin, Wang and Wang (2015), who exploit Walsh (1923) functions in order to compare sub-sample covariances with the full sample counterpart. They impose strict stationarity under the null,

Marcelo Matheus Gauy, Marcelo Finger

This work explores speech as a biomarker and investigates the detection of respiratory insufficiency (RI) by analyzing speech samples. Previous work \cite{spira2021} constructed a dataset of respiratory insufficiency COVID-19 patient utterances and analyzed it by means of a convolutional neural network achieving an accuracy of $87.04\%$, validating the hypot

Sagar Sutradhar, Anirban Misra, Gourab Pal, Sayari Majumder

We present the design, implementation and detailed experimental characterization of two-dimensional Magneto-optical traps (MOT) of bosonic $^{23}$Na and $^{39}$K atoms for loading the cold atomic mixture in a dual-species 3DMOT with a large number of atoms. We report our various measurements pertaining to the characterisation of the two 2D$^+$MOTs via the ca

Qian Wang, Toby P. Breckon

Prior feature transformation based approaches to Unsupervised Domain Adaptation (UDA) employ the deep features extracted by pre-trained deep models without fine-tuning them on the specific source or target domain data for a particular domain adaptation task. In contrast, end-to-end learning based approaches optimise the pre-trained backbones and the customis

C. A. Escobar, A. Martín-Ruiz, M. Mondragón, R. Jáuregui

We study the propagation of structured optical scalar beams in a spacetime background parameterized by a second-rank symmetric tensor. An analytic expression for the Green's function in a cylindrical coordinate system is obtained for particular choices of such a tensor. This facilitates the numerical exploration of the propagation of apertured Gaussian beams

Xhevahire Tërnava, Mathieu Acher, Benoit Combemale

Numerous software systems are highly configurable through run-time options, such as command-line parameters. Users can tune some of the options to meet various functional and non-functional requirements such as footprint, security, or execution time. However, some options are never set for a given system instance, and their values remain the same whatever th

Bruno Cucco, Claudine Katan, Jacky Even, Mikael Kepenekian

Vacancy ordered halide double perovskites (VODP) have been widely explored throughout the past few years as promising lead-free alternatives for optoelectronic applications. Yet, the atomic-scale mechanisms that underlie their optical properties remain elusive. In this work, a throughout investigation of the excitonic properties of key members within the VOD

Ziyu Zhao, Yuqi Bai, Kun Kuang, Ruoxuan Xiong

Estimates of individual treatment effects from networked observational data are attracting increasing attention these days. One major challenge in network scenarios is the violation of the stable unit treatment value assumption (SUTVA), which assumes that the treatment assignment of a unit does not influence others' outcomes. In network data, due to interfer

E. Nocerino, C. Witteveen, S. Kobayashi, O. K. Forslund

Two$-$dimensional (2D) triangular lattices antiferromagnets (2D$-$TLA) often manifest intriguing physical and technological properties, due to the strong interplay between lattice geometry and electronic properties. The recently synthesized 2$-$dimensional transition metal dichalcogenide LiCrTe$_2$, being a 2D$-$TLA, enriched the range of materials which can

Amikam Patron

Attacks on networks is a very important issue in developing strategies of eradicating spreads of malicious phenomena in networks, such as epidemics and fake information, which are generally named in the research networks immunization. The traditional approach of evaluating the effectiveness of attacks on networks, is focused on measuring some macro parameter

Mark Rucker, Jordan T. Ash, John Langford, Paul Mineiro

This work introduces the Eigen Memory Tree (EMT), a novel online memory model for sequential learning scenarios. EMTs store data at the leaves of a binary tree and route new samples through the structure using the principal components of previous experiences, facilitating efficient (logarithmic) access to relevant memories. We demonstrate that EMT outperform

S. Moran, M. Fraser, R. Kotak, A. Pastorello

In this study we present the results of a five-year follow-up campaign of the long-lived type IIn supernova SN 2017hcc, found in a spiral dwarf host of near-solar metallicity. The long rise time (57 $\pm$ 2 days, ATLAS $o$ band) and high luminosity (peaking at $-$20.78 $\pm$ 0.01 mag in the ATLAS $o$ band) point towards an interaction of massive ejecta with

Jingcheng Lu, James D. Baeder

In this study we consider unconditionally non-oscillatory, high order implicit time marching based on time-limiters. The first aspect of our work is to propose the high resolution Limited-DIRK3 (L-DIRK3) scheme for conservation laws and convection-diffusion equations in the method-of-lines framework. The scheme can be used in conjunction with an arbitrary hi

Darren Banfield, Heather Leitch, Alastair Kay

We describe a method to use measurements and correction operations in order to implement the Clifford group in a stabilizer code, generalising a result from [Bombin,2011] for topological subsystem colour codes. In subsystem stabilizer codes of distance at least $3$ the process can be implemented fault-tolerantly. In particular this provides a method to imple

Ziwei Li, Winfried Sickel, Dachun Yang, Wen Yuan

In this article, we establish a characterization of the set $M(B^{0,b}_{p,\infty}(\mathbb{R}^n))$ of all pointwise multipliers of Besov spaces $B^{0,b}_{p,\infty}(\mathbb{R}^n)$ with only logarithmic smoothness $b\in\mathbb{R}$ in the special cases $p=1$ and $p=\infty$. As applications of these two characterizations, we clarify whether or not the three concr

Tong Cao, Jérémie Decouchant, Jiangshan Yu

We describe and analyze perishing mining, a novel block-withholding mining strategy that lures profit-driven miners away from doing useful work on the public chain by releasing block headers from a privately maintained chain. We then introduce the dual private chain (DPC) attack, where an adversary that aims at double spending increases its success rate by i

Aliakbar Daemi, Mike Miller Eismeier

In previous work, the second author defined 'equivariant instanton homology groups' $I^\bullet(Y,\pi;R)$ for a rational homology 3-sphere $Y$, a set of auxiliary data $\pi$, and a PID $R$. These objects are modules over the cohomology ring $H^{-*}(BSO_3;R)$. We prove that the equivariant instanton homology groups $I^\bullet(Y;R)$ are independent of the auxil

Gal Yona, Amir Feder, Itay Laish

An important component in deploying machine learning (ML) in safety-critic applications is having a reliable measure of confidence in the ML model's predictions. For a classifier $f$ producing a probability vector $f(x)$ over the candidate classes, the confidence is typically taken to be $\max_i f(x)_i$. This approach is potentially limited, as it disregards

Yangkun He, Zsolt Gercsi, Rui Zhang, Yu Kang

Metallic Mn-based alloys with a nearest-neighbor Mn-Mn distance greater than 0.4 nm exhibit large, well-localized magnetic moments. Here we investigate the magnetism of tetragonal Au4Mn with a Curie temperature of 385 K, where manganese has a spin moment of 4.1 muB and its orbital moment is quenched. Since 80% of the atoms are gold, the spin orbit interactio

Vinícius F. Dal Poggetto, Edson J. P. Miranda, José Maria C. Dos Santos, Nicola M. Pugno

Phononic crystals (PCs) are periodic structures obtained by the spatial arrangement of materials with contrasting properties, which can be designed to efficiently manipulate mechanical waves. Plate structures can be modeled using the Mindlin-Reissner plate theory and have been extensively used to analyze the dispersion relations of PCs. Although the analysis

Philipp Kuehn, Markus Bayer, Tobias Frey, Moritz Kerk

Computer Emergency Response Teams (CERTs) face increasing challenges processing the growing volume of security-related information. Daily manual analysis of threat reports, security advisories, and vulnerability announcements leads to information overload, contributing to burnout and attrition among security professionals. This work evaluates 196 combination

Stergios Koutsioumpas, Darren Banfield, Alastair Kay

We prove that the smallest distance 3 Quantum Error Correcting Code with a transversal gate outside the Clifford group is the well-known 15-qubit Reed-Muller code, also known as a tri-orthogonal code. Our result relies on fewer assumptions than previous works. We further extend this result by finding the minimal code that also possesses any other non Cliffor

Jake C. Forster, Daniel Badger, Kevin J. Hickson

Objective. Patients treated with radionuclide therapy may require restrictions on certain activities for a period of time following treatment to optimise protection of the public and ensure the legal dose limit is not exceeded. Software may be used to calculate necessary restriction periods for an individual based on longitudinal dose rate measurements from

Edo Cohen-Karlik, Itamar Menuhin-Gruman, Raja Giryes, Nadav Cohen

Overparameterization in deep learning typically refers to settings where a trained neural network (NN) has representational capacity to fit the training data in many ways, some of which generalize well, while others do not. In the case of Recurrent Neural Networks (RNNs), there exists an additional layer of overparameterization, in the sense that a model may

Thomas Führer

We study variants of the mixed finite element method (mixed FEM) and the first-order system least-squares finite element (FOSLS) for the Poisson problem where we replace the load by a suitable regularization which permits to use $H^{-1}$ loads. We prove that any bounded $H^{-1}$ projector onto piecewise constants can be used to define the regularization and

Zhen Li

Black holes provide a natural laboratory to study particle physics and astrophysics. When black holes are surrounded by matter fields, there will be plenty of phenomena which can have observational consequences, from which we can learn about the matter fields as well as black hole spacetime. In this work, we investigate the massive scalar field in the vicini

Wouter Haverals, Mike Kestemont

This study is devoted to two of the oldest known manuscripts in which the oeuvre of the medieval mystical author Hadewijch has been preserved: Brussels, KBR, 2879-2880 (ms. A) and Brussels, KBR, 2877-2878 (ms. B). On the basis of codicological and contextual arguments, it is assumed that the scribe who produced B used A as an exemplar. While the similarities

Yoav Len

We present a self-contained introduction to the theory of chip-firing games on metric graphs, as well as the more recent theory of tropical Prym varieties. We briefly discuss the connection between these notions and their algebraic counterparts and suggest various avenues for future research.

Sergey Bezuglyi, Palle E. T. Jorgensen

The purpose of the paper is a general analysis of path space measures. Our focus is a certain path space analysis on generalized Bratteli diagrams. We use this in a systematic study of systems of self-similar measures (the term ``IFS measures'' is used in the paper) for both types of such diagrams, discrete and continuous. In special cases, such measures ari

Ana Estrada-Real, Ioannis Paradisanos, Peter R. Wiecha, Jean-Marie Poumirol

Optical Mie resonators based on silicon nanostructures allow tuning of light-matter-interaction with advanced design concepts based on CMOS compatible nanofabrication. Optically active materials such as transition-metal dichalcogenide (TMD) monolayers can be placed in the near-field region of such Mie resonators. Here, we experimentally demonstrate and verif

Dimitri Jeltsema

Inspired by recent assertions that imply incorrectness of the classical constitutive relationship of time-varying capacitance, energetic and system-theoretic perspectives are invoked that, instead of incorrectness, show incompleteness of the associated one-port device model. Based on dissipativity and passivity theory, an energetic analysis is presented that

Kanishka Perera, Caterina Sportelli

We study some critical elliptic problems involving the difference of two nonlocal operators, or the difference of a local operator and a nonlocal operator. The main result is the existence of two nontrivial weak solutions, one with negative energy and the other with positive energy, for all sufficiently small values of a parameter. The proof is based on an a

C. Bastien, A. Scattina, C. Neal-Sturgess, R. Panno

This research proposes a new a numerical method to compute brain injury associated with concussion using the Peak Virtual Power method, using the THUMS 4.02 head model. The results indicate that mild and severe concussions could be prevented for lateral collisions and frontal impacts with PVP values lower than 0.928mW and 9.405mW, respectively, and no concus

Ajay Chawda, Stefanie Grimm, Marius Kloft

In this paper, we introduce the Vehicle Claims dataset, consisting of fraudulent insurance claims for automotive repairs. The data belongs to the more broad category of Auditing data, which includes also Journals and Network Intrusion data. Insurance claim data are distinctively different from other auditing data (such as network intrusion data) in their hig

Mohamed Khodeir, Atharv Sonwane, Ruthrash Hari, Florian Shkurti

PDDLStream solvers have recently emerged as viable solutions for Task and Motion Planning (TAMP) problems, extending PDDL to problems with continuous action spaces. Prior work has shown how PDDLStream problems can be reduced to a sequence of PDDL planning problems, which can then be solved using off-the-shelf planners. However, this approach can suffer from

Corey Arndt, Cody Crusenberry, Bozhi Heng, Rochelle Butler

Complex engineering models are typically computationally demanding and defined by a high-dimensional parameter space challenging the comprehensive exploration of parameter effects and design optimization. To overcome this curse of dimensionality and to minimize computational resource requirements, this research demonstrates a user-friendly approach to formul

Martina Basini, Mattia Udina, Matteo Pancaldi, Vivek Unikandanunni

The THz Kerr effect measures the birefringence induced in an otherwise isotropic material by a strong THz pulse driving the Raman-active excitations of the systems. Here we provide experimental evidence of a sizable Kerr response in insulating SrTiO3 due to infrared-active lattice vibrations. Such a signal, named ionic Kerr effect, is associated with the sim

Jian-Feng Mo, Weishan Zhu, Yang Wang, Lin Tang

The dispersion measure(DM) of fast radio burst encodes important information such as its distance, properties of intervening medium. Based on simulations in the Illustris and IllustrisTNG projects, we analyze the DM of FRBs contributed by the interstellar medium and circumgalactic medium in the hosts, $\rm{DM_{host}}$. We explore two population models - trac

Hao Liang, Zhi-Quan Luo

We study the regret guarantee for risk-sensitive reinforcement learning (RSRL) via distributional reinforcement learning (DRL) methods. In particular, we consider finite episodic Markov decision processes whose objective is the entropic risk measure (EntRM) of return. By leveraging a key property of the EntRM, the independence property, we establish the risk

Leandro M. Del Pezzo, Raul Ferreira

We study the possibility of non-simultaneous blow-up for positive solutions of a coupled system of two semilinear equations, $u_t = J*u-u+ u^\alpha v^p$, $v_t =\Delta v^+u^qv^\beta$, $p, q, \alpha, \beta>0$ with homogeneous Dirichlet boundary conditions and positive initial data. We also give the blow-up rates for non-simultaneous blow-up.

Naritaka Oshita, Daichi Tsuna

The measurability of multiple quasinormal (QN) modes, including overtones and higher harmonics, with the Laser Interferometer Space Antenna is investigated by computing the gravitational wave (GW) signal induced by an intermediate or extreme mass ratio merger involving a supermassive black hole (SMBH). We confirm that the ringdown of rapidly spinning black h

Jonas P. Pereira, Michał Bejger, Paweł Haensel, Julian Leszek Zdunik

It is currently unknown if neutron stars (NSs) are composed of nucleons only or are hybrid stars, i.e., in addition to nucleonic crusts and outer cores, they also possess quark cores. Quantum chromodynamics allows for such a possibility, but accurate calculations relevant for compact stars are still elusive. Here we investigate some crust-breaking aspects of