November 2022 arXiv papers — page 101

Alexander Dunlap, Yu Gu, Liying Li

In this paper, we study the localization length of the $1+1$ continuum directed polymer, defined as the distance between the endpoints of two paths sampled independently from the quenched polymer measure. We show that the localization length converges in distribution in the thermodynamic limit, and derive an explicit density formula of the limiting distribut

Zhilu Zhang, Rongjian Xu, Ming Liu, Zifei Yan

When taking photos under an environment with insufficient light, the exposure time and the sensor gain usually require to be carefully chosen to obtain images with satisfying visual quality. For example, the images with high ISO usually have inescapable noise, while the long-exposure ones may be blurry due to camera shake or object motion. Existing solutions

Mingyang Zhang, Ziqi Di, Maoguo Gong, Yue Wu

In recent years, research on hyperspectral image (HSI) classification has continuous progress on introducing deep network models, and recently the graph convolutional network (GCN) based models have shown impressive performance. However, these deep learning frameworks based on point estimation suffer from low generalization and inability to quantify the clas

Jared Duker Lichtman

We prove the infinitude of shifted primes $p-1$ without prime factors above $p^{0.2844}$. This refines $p^{0.2961}$ from Baker and Harman in 1998. Consequently, we obtain an improved lower bound on the the distribution of Carmichael numbers. Our main technical result is a new mean value theorem for primes in arithmetic progressions to large moduli. Namely, w

Nicholas Kluge Corrêa, Nythamar Fernandes De Oliveira

Counterfactuals have become an important area of interdisciplinary interest, especially in logic, philosophy of language, epistemology, metaphysics, psychology, decision theory, and even artificial intelligence. In this study, we propose a new form of analysis for counterfactuals: analysis by algorithmic complexity. Inspired by Lewis-Stalnaker's Nicholas Cor

Ronan Herry, Dominique Malicet, Guillaume Poly

We prove the strong form of the Gaussian product conjecture in dimension three. Our purely analytical proof simplifies previously known proofs based on combinatorial methods or computer-assisted methods, and allows us to solve the case of any triple of even positive integers which remained open so far.

Caitlin C. Doughty, Kristian M. Finlator

A growing population of metal absorbers are observed at z>5, many showing strong evolution in incidence approaching the epoch of hydrogen reionization. Follow-up surveys examining fields around these metals have resulted in galaxy detections but the direct physical relationship between the detected galaxies and absorbers is unclear. Upcoming observations wil

Linfeng Zhang, Yukang Shi, Hung-Shuo Tai, Zhipeng Zhang

Detecting 3D objects from multi-view images is a fundamental problem in 3D computer vision. Recently, significant breakthrough has been made in multi-view 3D detection tasks. However, the unprecedented detection performance of these vision BEV (bird's-eye-view) detection models is accompanied with enormous parameters and computation, which make them unafford

Maksim I. Paukov, Vladimir V. Starchenko, Dmitry V. Krasnikov, Gennady A. Komandin

For terahertz (THz) wave applications, tunable and rapid modulation is highly required. When studied by means of optical pump-terahertz probe spectroscopy, single-walled carbon nanotubes (SWCNTs) thin films demonstrated ultrafast carrier recombination lifetimes with a high relative change in the signal under optical excitation, making them promising candidat

Marcel Hirt, Axel Finke, Alexandros Beskos, Petros Dellaportas

DNA methylation is an important epigenetic mark that has been studied extensively for its regulatory role in biological processes and diseases. WGBS allows for genome-wide measurements of DNA methylation up to single-base resolutions, yet poses challenges in identifying significantly different methylation patterns across distinct biological conditions. We pr

Sonali Kaushik, Rajesh Kumar

The paper deals with the global existence and density conservation for the Safronov-Dubovski equation for three different coefficients $\phi$ such that $\phi_{i,j} \leq \frac{(i+j)}{\min\{i,j\}}$, $\phi_{i,j} \leq (i+j)$ and $\phi_{i,j} \leq (1+i+j)^{\alpha}$ $\forall$ $i,j \in \mathbb{N}$, $\alpha \in [0,1]$. The non-conservative approximation is applied to

Gernot Herbst, Rafal Madonski

Practical implementations of active disturbance rejection control (ADRC) will almost always take place in discretized form. Since applications may have quite different needs regarding their discrete-time controllers, this article summarizes and extends the available set of ADRC implementations to provide a suitable variant for as many as possible use cases.

Pierre Bousquet, Lorenzo Brasco, Chiara Leone

We pursue the study of a model convex functional with orthotropic structure and nonstandard growth conditions, this time focusing on the sub-quadratic case. We prove that bounded local minimizers are locally Lipschitz. No restriction on the ratio between the highest and the lowest growth rates are needed. The result holds also in presence of a non-autonomous

Francesca Gasparini, Alessandra Grossi

The aim of this work is to define a speech emotion recognition (SER) model able to recognize positive, neutral and negative emotions in natural conversations of Italian elderly people. Several datasets for SER are available in the literature. However most of them are in English or Chinese, have been recorded while actors and actresses pronounce short phrases

Razieh Emami, Richard Anantua, Angelo Ricarte, Sheperd S. Doeleman

We explore the plasma matter content in the innermost accretion disk/jet in M87* as relevant for an enthusiastic search for the signatures of anti-matter in the next generation of the Event Horizon Telescope (ngEHT). We model the impact of non-zero positron-to-electron ratio using different emission models including a constant electron to magnetic pressure (

Jiaru Li, Dong Lai

We present a new mechanism of generating large planetary eccentricities. This mechanism applies to planets within the inner cavities of their companion protoplanetary disks. A massive disk with an inner truncation may become eccentric due to non-adiabatic effects associated with gas cooling, and can retain its eccentricity in long-lived coherently-precessing

Yuming Du, Philippe Weinzaepfel, Vincent Lepetit, Romain Brégier

Robots with multi-fingered grippers could perform advanced manipulation tasks for us if we were able to properly specify to them what to do. In this study, we take a step in that direction by making a robot grasp an object like a grasping demonstration performed by a human. We propose a novel optimization-based approach for transferring human grasp demonstra

Krzysztof Maślanka

We construct certain entire function $\lambda(s)$ which for integer s coincides with the well-known Keiper-Li coefficients, i.e. $\lambda(n)={\lambda}_{n}$. This is an even function ${\lambda}(s)={\lambda}(-s)$ and has an infinitude of complex zeros exhibiting interesting distribution. Extensive tables of more than 3500 complex zeros of ${\lambda}(s)$ with p

Feihu Huang, Xinrui Wang, Junyi Li, Songcan Chen

Federated learning is a popular distributed and privacy-preserving learning paradigm in machine learning. Recently, some federated learning algorithms have been proposed to solve the distributed minimax problems. However, these federated minimax algorithms still suffer from high gradient or communication complexity. Meanwhile, few algorithm focuses on using

Chang-Bin Jeon, Hyeongi Moon, Keunwoo Choi, Ben Sangbae Chon

Separation of multiple singing voices into each voice is a rarely studied area in music source separation research. The absence of a benchmark dataset has hindered its progress. In this paper, we present an evaluation dataset and provide baseline studies for multiple singing voices separation. First, we introduce MedleyVox, an evaluation dataset for multiple

Violeta Menéndez González, Andrew Gilbert, Graeme Phillipson, Stephen Jolly

This paper proposes Sparse View Synthesis. This is a view synthesis problem where the number of reference views is limited, and the baseline between target and reference view is significant. Under these conditions, current radiance field methods fail catastrophically due to inescapable artifacts such 3D floating blobs, blurring and structural duplication, wh

Junu Kim, Kyunghoon Hur, Seongjun Yang, Edward Choi

Federated learning (FL) is the most practical multi-source learning method for electronic healthcare records (EHR). Despite its guarantee of privacy protection, the wide application of FL is restricted by two large challenges: the heterogeneous EHR systems, and the non-i.i.d. data characteristic. A recent research proposed a framework that unifies heterogene

Vladimir. M. Krasnov

Optimization of Josephson oscillators requires a quantitative understanding of their microwave properties. A Josephson junction has a geometry similar to a microstrip patch antenna. However, it is biased by a dc-current, distributed over the whole area of the junction. The oscillating electric field is generated internally via the ac-Josephson effect. In thi

Hadrien Notarantonio, Sergey Yurkevich

We study systems of $n \geq 1$ discrete differential equations of order $k\geq1$ in one catalytic variable and provide a constructive and elementary proof of algebraicity of their solutions. This yields effective bounds and a systematic method for computing the minimal polynomials. Our approach is a generalization of the pioneering work by Bousquet-M\'elou a

Yuzhou Peng

With the increasing amount of information on the Internet, recommender systems are becoming increasingly crucial in supporting people to find and explore relevant content. This is also true in the online recruitment space, with websites such as LinkedIn, Indeed.com, and Monster.com all using recommender systems. In online recruitment, it can often be challen

Syuan-Rong Syu, Chi-Han Peng

We propose a computational approach to find a minimal set of 360-degree camera placements that together sufficiently cover an indoor environment for the building documentation problem in the architecture, engineering, and construction (AEC) industries. Our approach, based on a simple integer programming (IP) problem formulation, solves very efficiently and g

Sophie Hall, Lukas Ortmann, Miguel Picallo, Florian Dörfler

Medical drug infusion problems pose a combination of challenges such as nonlinearities from physiological models, model uncertainty due to inter- and intra-patient variability, as well as strict safety specifications. With these challenges in mind, we propose a novel real-time Nonlinear Model Predictive Control (NMPC) scheme based on projected gradient desce

Enqiang Zhu, Xianhang Luo, Chanjuan Liu, Xiaolong Shi

DNA computing, a nontraditional computing mechanism, provides a feasible and effective method for solving NP-hard problems because of the vast parallelism and high-density storage of DNA molecules. Although DNA computing has been exploited to solve various intractable computational problems, such as the Hamiltonian path problem, SAT problem, and graph colori

Jingtao Fan, Suotang Jia

We study a three-level Dicke model in V-configuration under both closed and open conditions. With independently tunable co- and counter-rotating coupling strength of the interaction Hamiltonian, this model is a generalization of the standard Dicke model that features multiple distinct parameter regimes. Based on a mean-field approach and third quantization a

Dominic Rampas, Pablo Pernias, Marc Aubreville

Recent advancements in the domain of text-to-image synthesis have culminated in a multitude of enhancements pertaining to quality, fidelity, and diversity. Contemporary techniques enable the generation of highly intricate visuals which rapidly approach near-photorealistic quality. Nevertheless, as progress is achieved, the complexity of these methodologies i

Ved Prakash Gupta, Deepika Sharma

We show that all values in the interval $[0,\frac{\pi}{2}]$ can be attained as the interior angle between intermediate subalgebras (as introduced in [3]) of a certain inclusion of simple unital C*-algebras. We also calculate the interior angle between intermediate crossed product subalgebras of any inclusion of crossed product algebras corresponding to any a

Siddique Latif, Hafiz Shehbaz Ali, Muhammad Usama, Rajib Rana

Automated emotion recognition (AER) technology can detect humans' emotional states in real-time using facial expressions, voice attributes, text, body movements, and neurological signals and has a broad range of applications across many sectors. It helps businesses get a much deeper understanding of their customers, enables monitoring of individuals' moods i

Bowen Li, Thomas Lukasiewicz

Story visualization aims to generate a sequence of images to narrate each sentence in a multi-sentence story, where the images should be realistic and keep global consistency across dynamic scenes and characters. Current works face the problem of semantic misalignment because of their fixed architecture and diversity of input modalities. To address this prob

Eugene A. Feinberg, Rui Ding

This paper studies optimization of Conditional Value-at-Risk (CVaR) for Markov Decision Processes (MDPs) with finite state and action sets. It introduces the Dynamically augmented CVaR (DCVaR) risk measure and provides an algorithm for its optimization. This paper investigates a specially defined Robust MDP (RMDP), in which the state space is augmented with

Sebastian Hillbrecht, Paul Manns, Christian Meyer

This paper is concerned with an optimization problem that is constrained by the Kantorovich optimal transportation problem. This bilevel optimization problem can be reformulated as a mathematical problem with complementarity constraints in the space of regular Borel measures. Because of the non-smoothness induced by the complementarity relations, problems of

Yutong Li, Yuping Duan

Due to the development of deep learning-based denoisers, the plug-and-play strategy has achieved great success in image restoration problems. However, existing plug-and-play image restoration methods are designed for non-blind Gaussian denoising such as zhang et al (2022), the performance of which visibly deteriorate for unknown noises. To push the limits of

Jacob de Nobel, Anna V. Kononova, Jeroen Briaire, Johan Frijns

Performing simulations with a realistic biophysical auditory nerve fiber model can be very time consuming, due to the complex nature of the calculations involved. Here, a surrogate (approximate) model of such an auditory nerve fiber model was developed using machine learning methods, to perform simulations more efficiently. Several machine learning models we

Felicity Currie, Mark Basham, Laura Shemilt, Nick Lynch

Managing Research Data, and making it available for use/reuse by others in line with the UKRI Concordat on Open Research Data and FAIR principles, is a major issue for research-intensive organisations. In this case study we outline an institute-wide review of data management in practice, carried out at the Rosalind Franklin Institute (The Franklin) in partne

Perry Lam, Huayun Zhang, Nancy F. Chen, Berrak Sisman

Text-to-speech (TTS) models have achieved remarkable naturalness in recent years, yet like most deep neural models, they have more parameters than necessary. Sparse TTS models can improve on dense models via pruning and extra retraining, or converge faster than dense models with some performance loss. Thus, we propose training TTS models using decaying spars

Jan Lang, Zdeněk Mihula

The structure of non-compactness of optimal Sobolev embeddings of $m$-th order into the class of Lebesgue spaces and into that of all rearrangement-invariant function spaces is quantitatively studied. Sharp two-sided estimates of Bernstein numbers of such embeddings are obtained. It is shown that, whereas the optimal Sobolev embedding within the class of Leb

K. Irländer, J. Schnack

Magnetic molecules are investigated with respect to their usability as units in future quantum devices. In view of quantum computing, a necessary prerequisite is a long coherence time of superpositions of low-lying levels. In this article, we investigate by means of numerical simulations whether a toroidal structure of single-ion easy anisotropy axes is adva

Nikiforos Pittaras, Sean McGregor

While certain industrial sectors (e.g., aviation) have a long history of mandatory incident reporting complete with analytical findings, the practice of artificial intelligence (AI) safety benefits from no such mandate and thus analyses must be performed on publicly known ``open source'' AI incidents. Although the exact causes of AI incidents are seldom know

Francisco J. Fernández, F. Adrián F. Tojo, Carlos Villanueva

In this work we study some topological aspects of function spaces arising in Stieltjes differential calculus. Chief among them are compactness results related to the Ascoli-Arzel\`a and Kolmogorov-Riesz theorems, as well as their applications to Stieltjes-Sobolev spaces and decomposable functions.

Isobel M. Romero-Shaw, Nicholas Loutrel, Michael Zevin

[Abridged] Binary black holes may form and merge dynamically. These binaries are likely to become bound with high eccentricities, resulting in a burst of gravitational radiation at their point of closest approach. When such a binary is perturbed by a third body, the evolution of the orbit is affected, and gravitational-wave burst times are altered. The burst

Aditay Tripathi, Rishubh Singh, Anirban Chakraborty, Pradeep Shenoy

Recent work has shown that deep vision models tend to be overly dependent on low-level or "texture" features, leading to poor generalization. Various data augmentation strategies have been proposed to overcome this so-called texture bias in DNNs. We propose a simple, lightweight adversarial augmentation technique that explicitly incentivizes the network to l

G. L. Klimchitskaya, V. M. Mostepanenko, V. B. Svetovoy

It is well known that the Casimir force calculated at large separations using the Lifshitz theory differs by a factor of 2 for metals described by the Drude or plasma models. We argue that this difference is entirely determined by the contribution of transverse electric (s) evanescent waves. Taking into account that there is a lack of experimental informatio

Junyang Wang, Yi Zhang, Ming Yan, Ji Zhang

CLIP (Contrastive Language-Image Pre-Training) has shown remarkable zero-shot transfer capabilities in cross-modal correlation tasks such as visual classification and image retrieval. However, its performance in cross-modal generation tasks like zero-shot image captioning remains unsatisfied. In this work, we discuss that directly employing CLIP for zero-sho

Justin-Aurel Ulbrich, Carla Fernandez-Rico, Brian Rost, Jacopo Vialetto

Anisotropic colloidal particles exhibit complex dynamics which play a crucial role in their functionality, transport and phase behaviour. In this work, we investigate the two-dimensional diffusion of smoothly curved colloidal rods -- also known as colloidal bananas -- as a function of their opening angle, {\alpha}. We measure the translational and rotational

Wei Jiang, Jiayu Yang, Yongqi Zhai, Peirong Ning

Recently, learned image compression has achieved remarkable performance. The entropy model, which estimates the distribution of the latent representation, plays a crucial role in boosting rate-distortion performance. However, most entropy models only capture correlations in one dimension, while the latent representation contain channel-wise, local spatial, a

Thanh Huy Nguyen, Sophie Ricci, Andrea Piacentini, Raquel Rodriguez Suquet

Ensemble data assimilation in flood forecasting depends strongly on the density, frequency and statistics of errors associated with the observation network. This work focuses on the assimilation of 2D flood extent data, expressed in terms of wet surface ratio, in addition to the in-situ water level data. The objective is to improve the representation of the

Anar Dosi

The paper is devoted to noncommutative projective schemes within Kapranov's framework of noncommutative algebraic geometry. We classify all noncommutative projective schemes obtained from the differential chains in the universal enveloping algebra of the free nilpotent Lie algebra of index q generated by x_{0},...,x_{n}. The construction proposed allows us t

Cyril Grunspan, Ricardo Perez-Marco

It has been known for some time that the Nakamoto consensus as implemented in the Bitcoin protocol is not totally aligned with the individual interests of the participants. More precisely, it has been shown that block withholding mining strategies can exploit the difficulty adjustment algorithm of the protocol and obtain an unfair advantage. However, we show

Pranjal Aggarwal, Pasupuleti Chandana, Jagrut Nemade, Shubham Sharma

Since personal computers became widely available in the consumer market, the amount of harmful content on the internet has significantly expanded. In simple terms, harmful content is anything online which causes a person distress or harm. It may include hate speech, violent content, threats, non-hope speech, etc. The online content must be positive, upliftin

Thea A. Vedelaar, Thamir H. Hamoh, Felipe Perona Martinez, Mayeul Chipaux

The nitrogen-vacancy (NV) center in diamond is a powerful and versatile quantum sensor for diverse quantities. In particular, relaxometry (or T1), allows to detect magnetic noise at the nanoscale. While increasing the number of NV centers in a nanodiamond allows to collect more signal, a standardized method to extract information from relaxometry experiments

Dario Stuhne, Jelena Vuletic, Marsela Car, Matko Orsag

This paper presents a serial chain hinge support, a rigid but flexible structure that improves the mechanical performance and robustness of soft-fingered grippers. Gravity can reduce the integrity of soft fingers in horizontal approach, resulting in lower maximum payload caused by a large deflection of fingers. To substantiate our claim we performed several

Luigi Riso, Maria G. Zoia, Consuelo R. Nava

This paper proposes a new algorithm for an automatic variable selection procedure in High Dimensional Graphical Models. The algorithm selects the relevant variables for the node of interest on the basis of mutual information. Several contributions in literature have investigated the use of mutual information in selecting the appropriate number of relevant fe

Janin Heuer, Ngoc Mai Tran, Timo de Wolff

Circuit polynomials are a certificate of nonnegativity for real polynomials, which can be derived via a generalization of the classical inequality of arithmetic and geometric means. In this article, we show that similarly nonnegativity of symmetric real polynomials can be certified via a generalization of the classical Muirhead inequality. Moreover, we show

Alberto Montefusco, Upanshu Sharma, Oliver Tse

We introduce a variational structure for the Fourier-Cattaneo (FC) system which is a second-order hyperbolic system. This variational structure is inspired by the large-deviation rate functional for the Kac process which is closely linked to the FC system. Using this variational formulation we introduce appropriate solution concepts for the FC equation and p

Théo Verhelst, Denis Mercier, Jeevan Shrestha, Gianluca Bontempi

Counterfactuals are central in causal human reasoning and the scientific discovery process. The uplift, also called conditional average treatment effect, measures the causal effect of some action, or treatment, on the outcome of an individual. This paper discusses how it is possible to derive bounds on the probability of counterfactual statements based on up

Zhiheng Xi, Rui Zheng, Tao Gui, Qi Zhang

Adversarial training is one of the most powerful methods to improve the robustness of pre-trained language models (PLMs). However, this approach is typically more expensive than traditional fine-tuning because of the necessity to generate adversarial examples via gradient descent. Delving into the optimization process of adversarial training, we find that ro

Viktor Pěč, Vitaly A. Kudryavtsev

Muon-induced neutrons can lead to potentially irreducible backgrounds in rare event search experiments. We have investigated the implication of laboratory depth on the muon induced background in a future dark matter experiment capable of reaching the so-called neutrino floor. Our simulation study focuses on a xenon-based detector with 71 tonnes of active mas

Xiaoyu Zhu

In this paper, we construct, investigate and, in some cases, classify several new classes of (simple) modules over the Takiff $\mathfrak{sl}_{2}$. More precisely, we first explicitly construct and classify, up to isomorphism, all modules over the Takiff $\mathfrak{sl}_{2}$ that are $U\left(\overline{\mathfrak{h}}\right)$-free of rank one. These split into th

Richard Schoonhoven, Bram Veenboer, Ben van Werkhoven, Kees Joost Batenburg

Graphics Processing Units (GPUs) have revolutionized the computing landscape over the past decade. However, the growing energy demands of data centres and computing facilities equipped with GPUs come with significant capital and environmental costs. The energy consumption of GPU applications greatly depend on how well they are optimized. Auto-tuning is an ef

Rachid Benbrik, Mohammed Boukidi, Stefano Moretti

We study the phenomenology of charged Higgs bosons ($H^\pm$) and Vector-Like Quarks (VLQs), denoted as $T$, the latter possessing a charge identical to the top quark one, within the framework of the Two Higgs Doublet Model Type-II (2HDM-II). Upon examining two scenarios, one featuring a singlet $(T)$ (2HDM-II+$(T)$) and another a doublet $(TB)$ (2HDM-II+$(TB

Georgios Seitidis, Stavros Nikolakopoulos, Ioannis Ntzoufras, Dimitris Mavridis

The reliability of the results of network meta-analysis (NMA) lies in the plausibility of key assumption of transitivity. This assumption implies that the effect modifiers' distribution is similar across treatment comparisons. Transitivity is statistically manifested through the consistency assumption which suggests that direct and indirect evidence are in a

Jure Kališnik

We show that the Fr\'{e}chet space $\mathord{\mathcal{C}^{\infty}}(P)$ of smooth functions on the total space of a surjective submersion $\pi:P\to M$ is a reflexive $\mathord{\mathcal{C}^{\infty}_{c}}(M)$-module.

Qiangqiang Gu, Shishir Kumar Pandey

Spin-orbit coupling (SOC) drives interesting and non-trivial phenomena in solid state physics, ranging from topological to magnetic to transport properties. Thorough study of such phenomena often require effective models where SOC term is explicitly included. However, estimation of SOC strength for such models mostly depend on the spectroscopy experiments wh

Francesco Crocetti, G. Costante, M. L. Fravolini, P. Valigi

The accurate online estimation of the road-friction coefficient is an essential feature for any advanced brake control system. In this study, a data-driven scheme based on a MLP Neural Net is proposed to estimate the optimum friction coefficient as a function of windowed slip-friction measurements. A stochastic NN weights drop-out mechanism is used to online

Fei-Fei Wang, Yuan-Chuan Zou

It is possible that the astrophysical {samples} are polluted by some outliers, which might belong to a different sub-class. By removing the outliers, the underline statistical feature may be revealed. {A more reliable correlation can be used as a standard candle relation for the cosmological study.} We present outlier searching for gamma-ray bursts with Part

Philip Müller, Georgios Kaissis, Daniel Rueckert

Image-text contrastive learning has proven effective for pretraining medical image models. When targeting localized downstream tasks like semantic segmentation or object detection, additional local contrastive losses that align image regions with sentences have shown promising results. We study how local contrastive losses are related to global (per-sample)

Minmin Wang

It has been claimed in Aldous, Miermont and Pitman [PTRF, 2004] that all L\'evy trees are mixings of inhomogeneous continuum random trees. We give a rigorous proof of this claim in the case of a stable branching mechanism, relying on a new procedure for recovering the tree distance from the graphical spanning trees that works simultaneously for stable trees

Konstantin Bogdanov, Alexander Bufetov

The first result of the paper (Theorem 1.1) is an explicit construction of unimodal maps that are semiconjugate, on the post-critical set, to the circle rotation by an arbitrary irrational angle $\theta\in(3/5,2/3)$. Our construction is a generalization of the construction by Milnor and Lyubich [LM] of the Fibonacci unimodal maps semi-conjugate to the circle

Karl-Ludwig Besser, Eduard A. Jorswieck

QMKPy provides a Python framework for modeling and solving the quadratic multiple knapsack problem (QMKP). It is primarily aimed at researchers who develop new solution algorithms for the QMKP. QMKPy therefore mostly functions as a testbed to quickly implement novel algorithms and compare their results with existing ones. However, the package also already in

Eloi Ruiz-Gironés, Xevi Roca

We present a distributed parallel mesh curving method for virtual geometry. The main application is to generate large-scale curved meshes on complex geometry suitable for analysis with unstructured high-order methods. Accordingly, we devise the technique to generate geometrically accurate meshes composed of high-quality elements. To this end, we advocate for

Shun'ya Mizoguchi, Takumi Oikawa, Hitomi Tashiro, Shotaro Yata

We continue the study of a relationship between the instanton expansion of the Seiberg-Witten (SW) prepotential of $D = 4$, ${\cal N }= 2$ $SU(2)$ SUSY gauge theory and the monstrous moonshine. Extending the previous results, we show for the cases of $N_f=2$ and $3$ that $q=e^{2\pi i\tau}$, where $\tau$ is the complex gauge coupling, again has an expansion w

Karim M. Ibrahim, Elena V. Epure, Geoffroy Peeters, Gaël Richard

As music has become more available especially on music streaming platforms, people have started to have distinct preferences to fit to their varying listening situations, also known as context. Hence, there has been a growing interest in considering the user's situation when recommending music to users. Previous works have proposed user-aware autotaggers to

Carlo Alberto Barbano, Benoit Dufumier, Edouard Duchesnay, Marco Grangetto

Building accurate Deep Learning (DL) models for brain age prediction is a very relevant topic in neuroimaging, as it could help better understand neurodegenerative disorders and find new biomarkers. To estimate accurate and generalizable models, large datasets have been collected, which are often multi-site and multi-scanner. This large heterogeneity negativ

Gopal Priyadarshi, Abdul Halim

In this paper, we propose a hybrid collocation method based on finite difference and Haar wavelets to solve nonlocal hyperbolic partial differential equations. Developing an efficient and accurate numerical method to solve such problem is a difficult task due to the presence of nonlocal boundary condition. The speciality of the proposed method is to handle i

Mingjie Wang, Jianxiong Guo, Weijia Jia

Federated Learning (FL) is a decentralized learning method used to train machine learning algorithms. In FL, a global model iteratively collects the parameters of local models without accessing their local data. However, a significant challenge in FL is handling the heterogeneity of local data distribution, which often results in a drifted global model that

Emil Vinas Boström, Adithya Sriram, Martin Claassen, Angel Rubio

Harnessing the enhanced light-matter coupling and quantum vacuum fluctuations resulting from mode volume compression in optical cavities is a promising route towards functionalizing quantum materials and realizing exotic states of matter. Here, we extend cavity quantum electrodynamical materials engineering to correlated magnetic systems, by demonstrating th

Fabio Caleffi, Massimo Capone, Iacopo Carusotto

We develop a Gutzwiller theory for the non-equilibrium steady states of a strongly-interacting photon fluid driven by a non-Markovian incoherent pump. In particular, we explore the collective excitation modes across the out-of-equilibrium Mott/superfluid transition, characterizing the diffusive Goldstone mode in the superfluid phase and the particle/hole exc

Jean-Rémy Conti, Stéphan Clémençon

The ROC curve is the major tool for assessing not only the performance but also the fairness properties of a similarity scoring function. In order to draw reliable conclusions based on empirical ROC analysis, accurately evaluating the uncertainty level related to statistical versions of the ROC curves of interest is absolutely necessary, especially for appli

A. Bonsor, T. Lichtenberg, J. Drazkowska, A. M. Buchan

The timing of formation for the first planetesimals determines the mode of planetary accretion and their geophysical and compositional evolution. Astronomical observations of circumstellar discs and Solar System geochronology provide evidence for planetesimal formation during molecular cloud collapse, much earlier than previously estimated. Here, we present

Leon Sixt, Tim Landgraf

Saliency methods attempt to explain deep neural networks by highlighting the most salient features of a sample. Some widely used methods are based on a theoretical framework called Deep Taylor Decomposition (DTD), which formalizes the recursive application of the Taylor Theorem to the network's layers. However, recent work has found these methods to be indep

K. Hidaka, H. Eberl, E. Ginina

We study the CP-even neutral Higgs boson decays $h \to c \bar{c}, b \bar{b}, b \bar{s}, \gamma \gamma, g g$ in the Minimal Supersymmetric Standard Model (MSSM) with general quark flavor violation (QFV), identifying the h as the Higgs boson with a mass of 125 GeV. We compute the widths of the h decays to $c \bar c, b \bar b, b \bar s (s \bar b)$ at full one-l

Paolo Micheletti, Urban Senica, Andres Forrer, Sara Cibella

Quantum Cascade Lasers (QCL) constitute an intriguing opportunity for the production of on-chip optical Dissipative Kerr Solitons (DKS): self-organized optical waves which can travel while preserving their shape thanks to the interplay between Kerr effect and dispersion. Originally demonstrated in passive microresonators, DKS were recently observed in mid-IR

Simon Schardt, Sabine C. Fischer

During development, spatio-temporal patterns ranging from checkerboard to engulfing occur with precise proportions of the respective cell fates. Key developmental regulators are intracellular transcriptional interactions and intercellular signaling. We present an analytically tractable mathematical model based on signaling that reliably generates different c

Laurens D. M. Peters, Tanner Culpitt, Erik I. Tellgren, Trygve Helgaker

The Berry curvature is essential in Born$-$Oppenheimer molecular dynamics, describing the screening of the nuclei by the electrons in a magnetic field. Parts of the Berry curvature can be understood as the external magnetic field multiplied by an effective charge so that the resulting Berry force behaves like a Lorentz force during the simulations. Here we i

Fabian Germ, István Gyöngy

The filtering equations associated to a partially observed jump diffusion model $(Z_t)_{t\in [0,T]}=(X_t,Y_t)_{t\in [0,T]}$, driven by Wiener processes and Poisson martingale measures are considered. Building on results from two preceding articles on the filtering equations, the regularity of the conditional density of the signal $X_t$, given observations $(

Wuji Zhu

Federated learning refers to conducting training on multiple distributed devices and collecting model weights from them to derive a shared machine-learning model. This allows the model to get benefit from a rich source of data available from multiple sites. Also, since only model weights are collected from distributed devices, the privacy of those data is pr

W. Wongcharoenbhorn

In this note, we prove by using T. Estermann's and S. Dimitrov's arguments with an elementary inequality that there are infinitely many $n$ for which all of the numbers $n^2+1,n^2+2$ and $n^2+3$ are squarefree. We also improve the error term slightly in the case of two consecutive numbers of the same form, so that we are able to prove the following asymptoti

Guido Martinelli, Silvano Simula, Ludovico Vittorio

In this contribution we analyse the heavy-to-light $B$ decays through the Dispersive Matrix method, which can be applied to any semileptonic decays of hadrons once lattice QCD computations of the hadronic Form Factors and of the relevant susceptibilities are available. We will explicitly discuss the application of the Dispersive Matrix approach to both $B \t

Jenny Tang, Hannah Shoemaker, Leah Teffera, Eleanor Birrell

As technology and technology companies have grown in power, ubiquity, and societal influence, some companies -- and notably some mobile apps -- have come to be perceived as privacy threats. Prior work has considered how various factors impact perceptions of threat, including social factors, political speech, and user-interface design. In this work, we invest

Xin Wang

Generative adversarial networks are generative models that are capable of replicating the implicit probability distribution of the input data with high accuracy. Traditionally, GANs consist of a Generator and a Discriminator which interact with each other to produce highly realistic artificial data. Traditional GANs fall prey to the mode collapse problem, wh

Vincent Rivasseau

We construct cumulants up to a finite order of a tensor field theory perturbed by a quartic term, nicknamed the $T_3^4$ model. The method we use is the multi-scale loop vertex expansion. We prove analyticity and Borel summability of the cumulants up to finite order.

Thomas Berger, Feliks Nüske

We study tracking control for stochastic differential equations of Langevin type and describe a new conceptual approach to the sampling problem for those systems. The objective is to guarantee the evolution of the mean value in a prescribed performance funnel around a given sufficiently smooth reference signal. To achieve this objective we design a novel fun

V. Vlaminck, L. Temdie, V. Castel, M. B. Jungfleisch

We present a near-field diffraction model for spin waves in perpendicularly magnetized films applicable in any geometries of excitation fields. This model relies on Kalinikos-Slavin formalism to express the dynamic susceptibility tensor in k-space, and calculate the diffraction patterns via inverse 2D-Fourier transform of the response functions. We show an e

D. -H. -Minh Nguyen, Chiara Devescovi, Dung Xuan Nguyen, Hai Son Nguyen

The chiral surface states of Weyl semimetals have an open Fermi surface called Fermi arc. At the interface between two Weyl semimetals, these Fermi arcs are predicted to hybridize and alter their connectivity. In this letter, we numerically study a one-dimensional (1D) dielectric trilayer grating where the relative displacements between adjacent layers play

Abhik Kumar Saha, Deb Shankar Ray, Bimalendu Deb

We analyze the phase diffusion, quantum fluctuations and their spectral features of an one-dimensional Bose-Josephson junction (BJJ) coupled to a bosonic heat bath. We show the dependence of the phase diffusion coefficient on the on-site interaction parameter $U$ and the temperature in zero-phase and $\pi$-phase modes. We find that in the $\pi$-phase mode, t

Peter Strong, Jim Q. Smith

Several structure-learning algorithms for staged trees, asymmetric extensions of Bayesian networks, have been proposed. However, these either do not scale efficiently as the number of variables considered increases, a priori restrict the set of models, or they do not find comparable models to existing methods. Here, we define an alternative algorithm based o