May 2022 arXiv papers — page 134

Maksim Zhykhovich

We describe the J-invariant of a semi-simple algebraic group G over a generic splitting field of a Tits algebra of G in terms of the J-invariant over a base field.

Tony Lelièvre, Geneviève Robin, Inass Sekkat, Gabriel Stoltz

Molecular systems often remain trapped for long times around some local minimum of the potential energy function, before switching to another one -- a behavior known as metastability. Simulating transition paths linking one metastable state to another one is difficult by direct numerical methods. In view of the promises of machine learning techniques, we exp

ATLAS Collaboration

Measurements of single-, double-, and triple-differential cross-sections are presented for boosted top-quark pair-production in 13 $\text{TeV}$ proton-proton collisions recorded by the ATLAS detector at the LHC. The top quarks are observed through their hadronic decay and reconstructed as large-radius jets with the leading jet having transverse momentum ($p_

Ben Cameron, Aysu Gündoğan, Joe Sawada

A cut-down de Bruijn sequence is a cyclic string of length $L$, where $1 \leq L \leq k^n$, such that every substring of length $n$ appears at most once. Etzion [Theor. Comp. Sci 44 (1986)] gives an algorithm to construct binary cut-down de Bruijn sequences that requires $o(n)$ simple $n$-bit operations per symbol generated. In this paper, we simplify the alg

Mario Berta, Fernando G. S. L. Brandão, Gilad Gour, Ludovico Lami

We show that the proof of the generalised quantum Stein's lemma [Brand\~ao & Plenio, Commun. Math. Phys. 295, 791 (2010)] is not correct due to a gap in the argument leading to Lemma III.9. Hence, the main achievability result of Brand\~ao & Plenio is not known to hold. This puts into question a number of established results in the literature, in particular

Savvas Varsamopoulos, Evan Philip, Herman W. T. van Vlijmen, Sairam Menon

We propose a quantum algorithm for `extremal learning', which is the process of finding the input to a hidden function that extremizes the function output, without having direct access to the hidden function, given only partial input-output (training) data. The algorithm, called quantum extremal learning (QEL), consists of a parametric quantum circuit that i

Cequn Li, Yi-Fan Zhao, Alexander Vera, Omri Lesser

The introduction of superconductivity to the Dirac surface states of a topological insulator leads to a topological superconductor, which may support topological quantum computing through Majorana zero modes. The development of a scalable material platform is key to the realization of topological quantum computing. Here we report on the growth and properties

Zhuohong He, Ali Mottaghi, Aidean Sharghi, Muhammad Abdullah Jamal

Activity recognition in surgical videos is a key research area for developing next-generation devices and workflow monitoring systems. Since surgeries are long processes with highly-variable lengths, deep learning models used for surgical videos often consist of a two-stage setup using a backbone and temporal sequence model. In this paper, we investigate man

Shourya Verma

The analysis of electrocardiogram (ECG) signals can be time consuming as it is performed manually by cardiologists. Therefore, automation through machine learning (ML) classification is being increasingly proposed which would allow ML models to learn the features of a heartbeat and detect abnormalities. The lack of interpretability hinders the application of

Olivier Graf, Gustav Holzegel

We prove that there are no non-stationary (with respect to the Hawking vectorfield) real mode solutions to the Teukolsky equations on all $(3+1)$-dimensional subextremal Kerr-anti-de Sitter spacetimes. We further prove that stationary solutions do not exist if the black hole parameters satisfy the Hawking-Reall bound and $\left|a\sqrt{-\Lambda}\right|<\frac{

Viktor Stojkoski

Measures of economic mobility represent aggregate values for how individual wealth changes over time. As such, these measures may not describe the feasibility of a typical individual to change their wealth. To address this limitation, we introduce mixing, a concept from statistical physics, as a relevant phenomenon for quantifying how individuals move across

Swee Hong Chan, Igor Pak, Greta Panova

We explore inequalities on linear extensions of posets and make them effective in different ways. First, we study the Bj\"orner--Wachs inequality and generalize it to inequalities on order polynomials and their $q$-analogues via direct injections and FKG inequalities. Second, we give an injective proof of the Sidorenko inequality with computational complexit

Himangshu Barman, Mohamed Moussa, Homa Shababi, Anisur Rahaman

We study quantum gravity effects on the thermodynamic character and the radiation process of the thin accretion disks around Schwarzschild-like black hole. The quantum gravity correction is invoked through the framework of generalization of uncertainty which is equivalent to the renormalization group improved quantum gravity and maintain the limit of the asy

Waqar Hassan Khan, Md Al Imran, Ahmed Nafis Fuad, Mohammed Latif Siddiq

Bangladesh, a developing country with a large and dense population, has recently seen significant economic as well as technological developments. The growth of technology has resulted in a dramatic increase in the number of smartphone users in Bangladesh, and as such, mobile apps have become an increasingly important part of peoples&#39; life, even encompass

Hao Tang, Ariel Rebekah Barr, Guoqing Wang, Paola Cappellaro

Spin qubits associated with color centers are promising platforms for various quantum technologies. However, to be deployed in robust quantum devices, the variations of their intrinsic properties with the external conditions, and in particular temperature, should be known with high precision. Unfortunately, a predictive theory on the temperature dependence o

Guoqing Wang, Ariel Rebekah Barr, Hao Tang, Mo Chen

Solid-state spin defects, especially nuclear spins with potentially achievable long coherence times, are compelling candidates for quantum memories and sensors. However, their current performances are still limited by the decoherence due to the variation of their intrinsic quadrupole and hyperfine interactions. We propose an \textit{unbalanced echo} to overc

Joshua Isaacson, Yao Fu, C. -P. Yuan

The recent CDF $W$ mass measurement of 80,433 $\pm$ 9 MeV is the most precise direct measurement. However, this result deviates from the Standard Model predicted mass of 80,359.1 $\pm$ 5.2 MeV by $7σ$. The CDF experiment used an older version of the ResBos code that was only accurate at NNLL+NLO, while the ResBos2 code is able to make predictions at N${}^3$L

Yarden Sheffer, Raquel Queiroz, Ady Stern

Since the discovery of magic-angle twisted bilayer graphene (TBG), flat bands in Dirac materials have become a prominent platform for realizing strong correlation effects in electronic systems. Here we show that the symmetry group protecting the Dirac cone in such materials determines whether a Dirac band may be flattened by the tuning of a small number of p

Fulvio Paleari, Andrea Marini

The concept of \textit{optical} exciton - a photo-excited bound electron-hole pair within a crystal - is routinely used to interpret and model a wealth of excited-state phenomena in semiconductors. Beside originating sub-band gap signatures in optical spectra, optical excitons have also been predicted to condensate, diffuse, recombine, relax. However, all th

Lakshya Agarwal, Christopher M. Langlett, Shenglong Xu

In this work, we study quantum many-body teleportation, where a single qubit is teleported through a strongly-interacting quantum system, as a result of a scrambling unitary and local measurements on a few qubits. Usual many-body teleportation protocols require a double copy of the system, and backward time evolution, we demonstrate that teleportation is pos

Akira Kamatsuka, Takahiro Yoshida, Koki Kazama, Toshiyasu Matsushima

We propose an algorithm for computing Stratonovich&#39;s value of information (VoI) that can be regarded as an analogue of the distortion-rate function. We construct an alternating optimization algorithm for VoI under a general information leakage constraint and derive a convergence condition. Furthermore, we discuss algorithms for computing VoI under specif

Nora Bailey, Dan Fabrycky

The architecture of a planetary system can influence the habitability of a planet via orbital effects, particularly in the areas of stability and eccentricity. Some of these effects are readily apparent, particularly when they occur on short timescales that are easily numerically calculable. However, the appearance and evolution of life can take place on gig

Katherine Li, Yajuan Si

Health disparity research often evaluates health outcomes across demographic subgroups. Multilevel regression and poststratification (MRP) is a popular approach for small subgroup estimation due to its ability to stabilize estimates by fitting multilevel models and to adjust for selection bias by poststratifying on auxiliary variables, which are population c

Mohammadreza Ebrahimi, Yidong Chai, Hao Helen Zhang, Hsinchun Chen

Learning predictive models in new domains with scarce training data is a growing challenge in modern supervised learning scenarios. This incentivizes developing domain adaptation methods that leverage the knowledge in known domains (source) and adapt to new domains (target) with a different probability distribution. This becomes more challenging when the sou

Seongpyo Hong, Dong-Hee Kim

We study the logarithmic correction to the scaling of the first Lee-Yang (LY) zero in the classical $XY$ model on square lattices by using tensor renormalization group methods. In comparing the higher-order tensor renormalization group (HOTRG) and the loop-optimized tensor network renormalization (LoopTNR), we find that the entanglement filtering in LoopTNR

Yi Han

New quantitative propagation of chaos results for mean field diffusion are proved via local and global entropy estimates. In the first result we work on the torus and consider singular, divergence free interactions $K\in L^p$, $p>d$. We prove a $O(k^{2}/n^2)$ convergence rate in relative entropy between the $k$-marginal laws of the particle system and its li

Giuseppe Degrassi, Ramona Gröber, Marco Vitti, Xiaoran Zhao

We compute the QCD corrections at next-to-leading order for the process $gg \rightarrow ZH$, including both the virtual two-loop terms and real-emission contributions. The two-loop box diagrams in the virtual corrections are approximated analytically over the complete phase space, combining the results of an expansion in the limit of small transverse momentu

Xiao Zhang, Guangsha Shi, Joshua A. Leveillee, Feliciano Giustino

The absorption of light by free carriers in semiconductors results in optical loss for all photon wavelengths. Since free-carrier absorption competes with optical transitions across the band gap, it also reduces the efficiency of optoelectronic devices such as solar cells because it does not generate electron-hole pairs. In this work, we develop a first-prin

Zulun Zhu, Jiaying Peng, Jintang Li, Liang Chen

Graph Convolutional Networks (GCNs) achieve an impressive performance due to the remarkable representation ability in learning the graph information. However, GCNs, when implemented on a deep network, require expensive computation power, making them difficult to be deployed on battery-powered devices. In contrast, Spiking Neural Networks (SNNs), which perfor

Iacopo Tirelli, Andrea Ianiro, Stefano Discetti

We introduce a novel end-to-end approach to improving the resolution of PIV measurements. The method blends information from different snapshots without the need for time-resolved measurements on grounds of similarity of flow regions in different snapshots. The main hypothesis is that, with a sufficiently large ensemble of statistically-independent snapshots

A. Tiribocchi, M. Durve, M. Lauricella, A. Montessori

Active fluid droplets are a class of soft materials exhibiting autonomous motion sustained by an energy supply. Such systems have been shown to capture motility regimes typical of biological cells and are ideal candidates as building-block for the fabrication of soft biomimetic materials of interest in pharmacology, tissue engineering and lab on chip devices

Mulong Luo, G. Edward Suh

Path planning for autonomous driving with dynamic obstacles poses a challenge because it needs to perform a higher-dimensional search (with time-dimension) while still meeting real-time constraints. This paper proposes an algorithm-hardware co-optimization approach to accelerate path planning with high-dimensional search space. First, we reduce the time for

Shuai Zhao, Ravishankar Ramanathan, Yuan Liu, Paweł Horodecki

The device-independent paradigm has had spectacular successes in randomness generation, key distribution and self-testing, however most of these results have been obtained under the assumption that parties hold trusted and private random seeds. In efforts to relax the assumption of measurement independence, Hardy's non-locality tests have been proposed as id

Benedikt Jahnel, Jonas Köppl

We consider irreversible translation-invariant interacting particle systems on the $d$-dimensional cubic lattice with finite local state space, which admit at least one Gibbs measure as a time-stationary measure. Under some mild degeneracy conditions on the rates and the specification we prove, that zero relative entropy loss of a translation-invariant measu

Marc Mitjans, David M. Levine, Louis N. Awad, Roberto Tron

We tackle the problem of tracking the human lower body as an initial step toward an automatic motion assessment system for clinical mobility evaluation, using a multimodal system that combines Inertial Measurement Unit (IMU) data, RGB images, and point cloud depth measurements. This system applies the factor graph representation to an optimization problem th

Manuel Pratelli, Marinella Petrocchi

In today's era of information disorder, many organizations are moving to verify the veracity of news published on the web and social media. In particular, some agencies are exploring the world of online media and, through a largely manual process, ranking the credibility and transparency of news sources around the world. In this paper, we evaluate two proced

K. Peña Ramírez, L. C. Smith, S. Ramírez Alegría, A. -N. Chené

Open clusters are key coeval structures that help us understand star formation, stellar evolution and trace the physical properties of our Galaxy. In the past years, the isolation of open clusters from the field has been heavily alleviated by the access to accurate large-scale stellar parallaxes and proper motions along a determined line of sight. Still, the

Geoffrey R. Grimmett, Zhongyang Li

A necessary and sufficient condition is established for the strict inequality $p_c(G_*)<p_c(G)$ between the critical probabilities of site percolation on a quasi-transitive, plane graph $G$ and on its matching graph $G_*$. It is assumed that $G$ is properly embedded in either the Euclidean or the hyperbolic plane. When $G$ is transitive, strict inequality ho

Shuaifei Chen, Jiayi Zhang, Emil Björnson, Özlem Tuğfe Demir

Cell-free massive multiple-input multiple-output (CF mMIMO) systems are characterized by having many more access points (APs) than user equipments (UEs). A key challenge is to determine which APs should serve which UEs. Previous work has tackled this combinatorial problem heuristically. This paper proposes a sparse large-scale fading decoding (LSFD) design f

Yuesen Li, Shouxin Zong, Yanfei Shen, Zhiqiang Pu

Characterizing playing style is important for football clubs on scouting, monitoring and match preparation. Previous studies considered a player&#39;s style as a combination of technical performances, failing to consider the spatial information. Therefore, this study aimed to characterize the playing styles of each playing position in the Chinese Football Su

Masayuki Kuzuhara, Thayne Currie, Takuya Takarada, Timothy D. Brandt

We present the direct-imaging discovery of a substellar companion in orbit around a Sun-like star member of the Hyades open cluster. So far, no other substellar companions have been unambiguously confirmed via direct imaging around main-sequence stars in Hyades. The star HIP 21152 is an accelerating star as identified by the astrometry from the Gaia and Hipp

Martha Gavidia, Patrick Lee, Anna Feldman, Jing Peng

Euphemisms have not received much attention in natural language processing, despite being an important element of polite and figurative language. Euphemisms prove to be a difficult topic, not only because they are subject to language change, but also because humans may not agree on what is a euphemism and what is not. Nevertheless, the first step to tackling

Matteo Blamart, Hannah Fronenberg, Robert Brandenberger

We study the signal of cosmic string wakes present before the time of reionization in the cross-correlation signal of 21-cm redshift and B-mode CMB polarization maps. The specific non-Gaussian signal of strings in the position space cross-correlation maps can be extracted by means of a matched filtering analysis. Signals of strings with tension somewhat lowe

Bingsheng He, Feng Ma, Shengjie Xu, Xiaoming Yuan

The augmented Lagrangian method (ALM) is classic for canonical convex programming problems with linear constraints, and it finds many applications in various scientific computing areas. A major advantage of the ALM is that the step for updating the dual variable can be further relaxed with a step size in $(0,2)$, and this advantage can easily lead to numeric

Yujia Wang, Lu Lin, Jinghui Chen

Federated learning is a machine learning training paradigm that enables clients to jointly train models without sharing their own localized data. However, the implementation of federated learning in practice still faces numerous challenges, such as the large communication overhead due to the repetitive server-client synchronization and the lack of adaptivity

Min Yang, Guo Chen, Yin-Dong Zheng, Tong Lu

Temporal action detection (TAD) is extensively studied in the video understanding community by generally following the object detection pipeline in images. However, complex designs are not uncommon in TAD, such as two-stream feature extraction, multi-stage training, complex temporal modeling, and global context fusion. In this paper, we do not aim to introdu

Nikunjkumar Prajapati, Andrew Rotunno, Samuel Berweger, Matt Simons

We demonstrate the ability to receive live color analog television and video game signals with the use of the Rydberg atom receiver. The typical signal expected for traditional 480i NSTC format video signals requires a bandwidth of over 3 MHz. We determine the beam sizes, powers, and detection method required for the Rydberg atoms to receive this type of sig

Nicoló Scapin, Andreas D. Demou, Luca Brandt

We propose an analytical model to estimate the interface temperature $\Theta_{\Gamma}$ and the Nusselt number $Nu$ for an evaporating two-layer Rayleigh-B\'enard configuration in statistically stationary conditions. The model is based on three assumptions: (i) the Oberbeck-Boussinesq approximation can be applied to the liquid phase, while the gas thermophysi

Wenlin Chen, Austin Tripp, José Miguel Hernández-Lobato

We propose Adaptive Deep Kernel Fitting with Implicit Function Theorem (ADKF-IFT), a novel framework for learning deep kernel Gaussian processes (GPs) by interpolating between meta-learning and conventional deep kernel learning. Our approach employs a bilevel optimization objective where we meta-learn generally useful feature representations across tasks, in

Michael Ruzhansky, Bolys Sabitbek

Inthisnote,weprovetheblow-upofsolutionsofthesemilineardamped Klein-Gordon equation in a finite time for arbitrary positive initial energy on the Heisenberg group. This work complements the paper [21] by the first author and Tokmagambetov, where the global in time well-posedness was proved for the small energy solutions.

Stefano Lepri

We study a scalar harmonic network with pair interactions and a binary collision rule, exchanging the momenta of a randomly-chosen couple of sites. We consider the case of the isolated network where the total energy is conserved. In the first part, we recast the dynamics as a stochastic map in normal modes (or action-angle) coordinates and provide a geometri

Szymon Mieszczak, Maciej Krawczyk, Jarosław W. Kłos

We report on the evolution of the spin-wave spectrum under structural disorder introduced intentionally into one-dimensional magnonic quasicrystal. We study theoretically a system composed of ferromagnetic strips arranged in a Fibonacci sequence. We considered several stages of disorder in the form of phasonic defects, where different rearrangements of strip

Soutick Saha, Hye-ran Moon, Bumsoo Han, Andrew Mugler

Cell signaling networks are complex and often incompletely characterized, making it difficult to obtain a comprehensive picture of the mechanisms they encode. Mathematical modeling of these networks provides important clues, but the models themselves are often complex, and it is not always clear how to extract falsifiable predictions. Here we take an inverse

Zhe Du, Laura Balzano, Necmiye Ozay

Switched systems are capable of modeling processes with underlying dynamics that may change abruptly over time. To achieve accurate modeling in practice, one may need a large number of modes, but this may in turn increase the model complexity drastically. Existing work on reducing system complexity mainly considers state space reduction, yet reducing the num

R. Le Fournis, B. A. Van Tiggelen

We calculate the Abraham force and the Aharonov-Casher force exerted by the electromagnetic quantum vacuum on alkaline atoms in highly excited, long-living Rydberg states. Because of their high polarizability and long-life time such atoms are good candidates to observe these forces.

Bamdad Hosseini, Stefan Steinerberger

Let $X,Y$ be two finite sets of points having $\#X = m$ and $\#Y = n$ points with $μ= (1/m) \sum_{i=1}^{m} δ_{x_i}$ and $ν= (1/n) \sum_{j=1}^{n} δ_{y_j}$ being the associated uniform probability measures. A result of Birkhoff implies that if $m = n$, then the Kantorovich problem has a solution which also solves the Monge problem: optimal transport can be rea

Chirag Srivastava, Mahasweta Pandit, Ujjwal Sen

We consider a scenario where spatially separated observers share a genuinely multiparty entangled quantum state with each local observer possessing a single qubit. A particular qubit is acted upon by sequential and independent observers. We study the recycled detection of genuine multipartite entanglement of multiqubit states by any one of the sequential obs

Martijn Bartelds, Martijn Wieling

Deep acoustic models represent linguistic information based on massive amounts of data. Unfortunately, for regional languages and dialects such resources are mostly not available. However, deep acoustic models might have learned linguistic information that transfers to low-resource languages. In this study, we evaluate whether this is the case through the ta

Xianda Guo, Zheng Zhu, Tian Yang, Beibei Lin

Gait benchmarks empower the research community to train and evaluate high-performance gait recognition systems. Even though growing efforts have been devoted to cross-view recognition, academia is restricted by current existing databases captured in the controlled environment. In this paper, we contribute a new benchmark and strong baseline for Gait REcognit

Katrina Yezzi-Woodley, Jeff Calder, Mckenzie Sweno, Chloe Siewert

Within anthropology, the use of three-dimensional (3D) imaging has become increasingly common and widespread since it broadens the available avenues for addressing a wide range of key anthropological issues. The ease with which 3D models can be generated and shared has major impact on research, cultural heritage, education, science communication, and public

Daniele Binosi, Alessandro Pilloni, Ralf-Arno Tripolt

We apply a model-independent reconstruction method to experimental data in order to identify complex poles of overlapping resonances. The algorithm is based on the Schlessinger Point Method where data points are interpolated using a continued-fraction expression. Statistical uncertainties of the experimental data are propagated with resampling. In order to d

Daniela Di Donato

We introduce a notion of intrinsically Hölder graphs in metric spaces. Following a recent paper of Le Donne and the author, we prove some relevant results as the Ascoli-Arzelà compactness Theorem, Ahlfors-David regularity and the Extension Theorem for this class of sections. In the first part of this note, thanks to Cheeger theory, we define suitable sets in

Jinxing Yang, Jihong Yu, Shuai Wang, Hao Liu

To realize mmWave massive MIMO systems in practice, Beamspace MIMO with beam selection provides an attractive solution at a considerably reduced number of radio frequency (RF) chains. We propose low-complexity beam selection algorithms based on singular value decomposition (SVD). We first diagonalize the channel matrix by SVD, and the appropriate beams are s

Dong Zhou, Jie Cao, Huan Cui, Li-Xing Lin

Conventional computational ghost imaging (CGI) uses light carrying a sequence of patterns with uniform-resolution to illuminate the object, then performs correlation calculation based on the light intensity value reflected by the target and the preset patterns to obtain object image. It requires a large number of measurements to obtain high-quality images, e

Francesco Giovanni Celiberto, Michael Fucilla, Dmitry Yu. Ivanov, Mohammed M. A. Mohammed

We calculate the next-to-leading order correction to the impact factor (vertex) for the production of a forward Higgs boson, obtained in the infinite top-mass limit. We present the result both in the momentum representation and as superposition of the eigenfunctions of the leading-order BFKL kernel. This impact factor is a necessary ingredient for the descri

Hayato Chiba, Georgi S. Medvedev, Matthew S. Mizuhara

In this work, we analyze the Kuramoto model (KM) with inertia on a convergent family of graphs. It is assumed that the intrinsic frequencies of the individual oscillators are sampled from a probability distribution. In addition, a given graph, which may also be random, assigns network connectivity. As in the original KM, in the model with inertia, the weak c

Wang-Yan Liu, Li-Bao Fan, Ye-Xiong Zeng, Jin-Feng Huang

We study quantum thermalization and thermal entanglement in the open quantum Rabi model (QRM), in which a two-level system and a single-mode bosonic field are coupled to either two individual heat baths or a common heat bath. By treating the QRM as an effective multilevel system and deriving global quantum master equations in the eigenstate representation of

Filippo Bouchè, Salvatore Capozziello, Vincenzo Salzano, Keiichi Umetsu

Extended theories of gravity have been extensively investigated during the last thirty years, aiming at fixing infrared and ultraviolet shortcomings of General Relativity and of the associated $Λ$CDM cosmological model. Recently, non-local theories of gravity have drawn increasing attention due to their potential to ameliorate both the ultraviolet and infrar

Nicholas Loutrel, Nicolas Yunes

Spin precession in compact binaries is intricately tuned to the multipole structure of the underlying bodies. For black holes, violations of the no-hair theorems induced by modifications to general relativity correct the precession dynamics, which in turn imprints onto the amplitude and phase modulations of the gravitational waves emitted by the binary. Rece

Wei Wei, Huang Hengguan, Gu Xiangming, Wang Hao

Content mismatch usually occurs when data from one modality is translated to another, e.g. language learners producing mispronunciations (errors in speech) when reading a sentence (target text) aloud. However, most existing alignment algorithms assume that the content involved in the two modalities is perfectly matched, thus leading to difficulty in locating

Zhuocheng Xie, Dimitri Chauraud, Achraf Atila, Erik Bitzek

In Laves phases, synchroshear is the dominant basal slip mechanism. It is accomplished by the glide of synchro-Shockley dislocations. However, the atomic-scale mechanisms of motion of such zonal dislocations are still not well understood. In this work, using atomistic simulations, two 30\textdegree{} synchro-Shockley dislocations with different Burgers vecto

Aitazaz Ali Raja, Pierre Pinson, Jalal Kazempour, Sergio Grammatico

In many areas of industry and society, e.g., energy, healthcare, logistics, agents collect vast amounts of data that they deem proprietary. These data owners extract predictive information of varying quality and relevance from data depending on quantity, inherent information content, and their own technical expertise. Aggregating these data and heterogeneous

Ibrahim Akal, Taishi Kawamoto, Shan-Ming Ruan, Tadashi Takayanagi

We systematically study moving mirror models in two-dimensional conformal field theory (CFT). By focusing on their late-time behavior, we separate the mirror profiles into four classes, named type A (timelike) mirrors, type B (escaping) mirrors, type C (chasing) mirrors, and type D (terminated) mirrors. We analytically explore the characteristic features of

Tatsuki Kuwagaki

The notion of sheaf quantization has many faces: an enhancement of the notion of constructible sheaves, the Betti counterpart of Fukaya--Floer theory, a topological realization of WKB-states in geometric quantization. The purpose of this note is to give an introduction to the subject.

Zied Bouraoui, Sebastien Konieczny, Thanh Ma, Nicolas Schwind

This paper introduces a novel method for merging open-domain terminological knowledge. It takes advantage of the Region Connection Calculus (RCC5), a formalism used to represent regions in a topological space and to reason about their set-theoretic relationships. To this end, we first propose a faithful translation of terminological knowledge provided by sev

Zipeng Wang, Shina Tan

We define the three-body scattering hypervolume $D_F$ for identical spin-polarized fermions in two dimensions, by considering the wave function of three such fermions colliding at zero energy and zero orbital angular momentum. We derive the asymptotic expansions of such a wave function when three fermions are far apart or one pair and the third fermion are f

Mohammad Sababheh, Cristian Conde, Hamid Reza Moradi

The main goal of this work is to present new matrix inequalities of the Cauchy-Schwarz type. In particular, we investigate the so-called Lieb functions, whose definition came as an umbrella of Cauchy-Schwarz-like inequalities, then we consider the mixed Cauchy-Schwarz inequality. This latter inequality has been influential in obtaining several other matrix i

Yixuan Su, Tian Lan, Yahui Liu, Fangyu Liu

Generative language models (LMs) such as GPT-2/3 can be prompted to generate text with remarkable quality. While they are designed for text-prompted generation, it remains an open question how the generation process could be guided by modalities beyond text such as images. In this work, we propose a training-free framework, called MAGIC (iMAge-Guided text ge

Marcel Wienöbst, Max Bannach, Maciej Liśkiewicz

Counting and sampling directed acyclic graphs from a Markov equivalence class are fundamental tasks in graphical causal analysis. In this paper we show that these tasks can be performed in polynomial time, solving a long-standing open problem in this area. Our algorithms are effective and easily implementable. As we show in experiments, these breakthroughs m

Tobias Friedrich, Andreas Göbel, Nicolas Klodt, Martin S. Krejca

We study the SIRS process, a continuous-time Markov chain modeling the spread of infections on graphs. In this model, vertices are either susceptible, infected, or recovered. Each infected vertex becomes recovered at rate 1 and infects each of its susceptible neighbors independently at rate $λ$, and each recovered vertex becomes susceptible at a rate $\varrh

Dmitrii Usynin, Helena Klause, Johannes C. Paetzold, Daniel Rueckert

In federated learning for medical image analysis, the safety of the learning protocol is paramount. Such settings can often be compromised by adversaries that target either the private data used by the federation or the integrity of the model itself. This requires the medical imaging community to develop mechanisms to train collaborative models that are priv

Nava Leibovich, Jeremy Rothschild, Sidhartha Goyal, Anton Zilman

Structure, composition and stability of ecological populations are shaped by the inter- and intra-species interactions within these communities. It remains to be fully understood how the interplay of these interactions with other factors, such as immigration, control the structure, diversity and the long term stability of ecological systems in the presence o

Anasua Khan, Sarita Rajput, M. Anas, V. K. Malik

Combining experimental investigations and first-principles DFT calculations, we report physical and magnetic properties of Gd-substituted Y$_2$CoMnO$_6$ double perovskite, which are strongly influenced by antisite-disorder-driven spin configurations. On Gd doping, Co and Mn ions are present in mixed-valence (Co$^{3+}$, Co$^{2+}$, Mn$^{3+}$ and Mn$^{4+}$) sta

Théo Pinet, Yvan Saint-Aubin

The affine Temperley-Lieb algebra $\mathsf{a}\hskip-1.8pt\mathsf{TL}_{N}(β)$ is an infinite-dimensional algebra parametrized by a number $β\in \mathbb{C}$ and an integer $N\in \mathbb{N}$. It naturally acts on $(\mathbb{C}^2)^{\otimes N}$ to produce a family of representations labeled by an additional parameter $z\in\mathbb C^\times$. The structure of these

Héber H. Arcolezi, Jean-François Couchot, Sébastien Gambs, Catuscia Palamidessi

This paper introduces the multi-freq-ldpy Python package for multiple frequency estimation under Local Differential Privacy (LDP) guarantees. LDP is a gold standard for achieving local privacy with several real-world implementations by big tech companies such as Google, Apple, and Microsoft. The primary application of LDP is frequency (or histogram) estimati

Arshed Nabeel, Ashwin Karichannavar, Shuaib Palathingal, Jitesh Jhawar

Theoretical studies have shown that stochasticity can affect the dynamics of ecosystems in counter-intuitive ways. However, without knowing the equations governing the dynamics of populations or ecosystems, it is difficult to ascertain the role of stochasticity in real datasets. Therefore, the inverse problem of inferring the governing stochastic equations f

Kathrin Bringmann, Caner Nazaroglu

In 2015, Lovejoy and Osburn discovered twelve $q$-hypergeometric series and proved that their Fourier coefficients can be understood as counting functions of ideals in certain quadratic fields. In this paper, we study their modular and quantum modular properties and show that they yield three vector-valued quantum modular forms on the group $\Gamma_0 (2)$.

Hao Chen, Pengcheng Hou, Sheng Fang, Youjin Deng

The two-dimensional $q$-state clock model for $q \geq 5$ undergoes two Berezinskii-Kosterlitz-Thouless (BKT) phase transitions as temperature decreases. Here we report an extensive worm-type simulation of the square-lattice clock model for $q=$5--9 in a pair of flow representations, from the high- and low-temperature expansions, respectively. By finite-size

Nir Shlezinger, Yonina C. Eldar, Stephen P. Boyd

Decision making algorithms are used in a multitude of different applications. Conventional approaches for designing decision algorithms employ principled and simplified modelling, based on which one can determine decisions via tractable optimization. More recently, deep learning approaches that use highly parametric architectures tuned from data without rely

Matteo Martinelli, Francesca Scarcella, Natalie B. Hogg, Bradley J. Kavanagh

Primordial black holes (PBHs) are compact objects proposed to have formed in the early Universe from the collapse of small-scale over-densities. Their existence may be detected from the observation of gravitational waves (GWs) emitted by PBH mergers, if the signals can be distinguished from those produced by the merging of astrophysical black holes. In this

Arthur Moreau, Thomas Gilles, Nathan Piasco, Dzmitry Tsishkou

We propose a novel learning-based formulation for visual localization of vehicles that can operate in real-time in city-scale environments. Visual localization algorithms determine the position and orientation from which an image has been captured, using a set of geo-referenced images or a 3D scene representation. Our new localization paradigm, named Implici

Luis Cruz-Filipe, Kim S. Larsen, Fabrizio Montesi, Larisa Safina

Choreographies are global descriptions of interactions among concurrent components, most notably used in the settings of verification and synthesis of correct-by-construction software. They require a top-down approach: programmers first write choreographies, and then use them to verify or synthesize their programs. However, most software does not come with c

Felix Schremmer

We give new descriptions of the Bruhat order and Demazure products of affine Weyl groups in terms of the weight function of the quantum Bruhat graph. These results can be understood to describe certain closure relations concerning the Iwahori-Bruhat decomposition of an algebraic group. As an application towards affine Deligne-Lusztig varieties, we present a

Maximilian Graml, Maximilian Nitsch, Adrian Seith, Ferdinand Evers

High harmonic generation (HHG) is a versatile technique for probing ultrafast electron dynamics. While HHG is sensitive to the electronic properties of the target, HHG also depends on the waveform of the laser pulse. As is well known, (peak) positions, $ω$, in the high-harmonic spectrum can shift when the carrier envelope phase (CEP), $φ$ is varied. We deriv

Mikhail Khavronin, Dmitry Svintsov

We propose and theoretically substantiate a new method to study the non-local conductivity of two-dimensional electron systems (2DES) using the tools of near-field microscopy. We show that the height dependence of induced dipole moment of illuminated near-field probe is substantially different for various transport regimes of charge carriers in 2DES. For hyd

Marco Gaido, Sara Papi, Dennis Fucci, Giuseppe Fiameni

The primary goal of this FBK's systems submission to the IWSLT 2022 offline and simultaneous speech translation tasks is to reduce model training costs without sacrificing translation quality. As such, we first question the need of ASR pre-training, showing that it is not essential to achieve competitive results. Second, we focus on data filtering, showing t

Naoki Tsukamoto

We investigate the power of a collisional Penrose process with an unbound energy extraction from an extreme Reissner-Nordström black hole. This process takes infinite time in a time coordinate at a constant radial coordinate outside of the black hole. For black holes as a power plant, the power of the process for an observer far away from the black hole can

Smahane El-Halouy, Silvia Noschese, Lothar Reichel

Modeling complex systems that consist of different types of objects leads to multilayer networks, where nodes in the different layers represent different kind of objects. Nodes are connected by edges, which have positive weights. A multilayer network is associated with a supra-adjacency matrix. This paper investigates the sensitivity of the communicability i

S. Heinen, G. F. von Rudorff, O. A. von Lilienfeld

We use energies and forces predicted within response operator based quantum machine learning (OQML) to perform geometry optimization and transition state search calculations with legacy optimizers. For randomly sampled initial coordinates of small organic query molecules we report systematic improvement of equilibrium and transition state geometry output as

Michael J. Kewming, Mark T. Mitchison, Gabriel T. Landi

The parametrically pumped Kerr model describes a driven-dissipative nonlinear cavity, whose nonequilibrium phase diagram features both continuous and discontinuous quantum phase transitions. We consider the consequences of these critical phenomena for the fluctuations of the photocurrent obtained via continuous weak measurements on the cavity. Considering bo