October 2022 arXiv papers — page 66

Silviu Pitis, Elliot Creager, Ajay Mandlekar, Animesh Garg

The number of states in a dynamic process is exponential in the number of objects, making reinforcement learning (RL) difficult in complex, multi-object domains. For agents to scale to the real world, they will need to react to and reason about unseen combinations of objects. We argue that the ability to recognize and use local factorization in transition dy

Nicholas A. Loehr

This paper gives bijective proofs of some novel coinversion identities first discovered by Ayyer, Mandelshtam, and Martin (arxiv:2011.06117) as part of their proof of a new combinatorial formula for the modified Macdonald polynomials $\tilde{H}_{\mu}$. Those authors used intricate algebraic manipulations of $q$-binomial coefficients to prove these identities

Craig D. Colquhoun, Hazel Jeffrey, Steve Greenland, Sonali Mohapatra

Quantum key distribution (QKD) is a theoretically proven future-proof secure encryption method that inherits its security from fundamental physical principles. Craft Prospect, working with a number of UK organisations, has been focused on miniaturising the technologies that enable QKD so that they may be used in smaller platforms including nanosatellites. Th

Wenjing Xu, Haiquan Zhao, Shaohui Lv

In recent years, the multitask diffusion least mean square (MD-LMS) algorithm has been extensively applied in the distributed parameter estimation and target tracking of multitask network. However, its performance is mainly limited by two aspects, i.e, the correlated input signal and impulsive noise interference. To overcome these two limitations simultaneou

Alexander Kochin

Mesoscale wave processes are a transport mechanism for the energy exchange between the troposphere and stratosphere, since the tropopause blocks such an exchange. It is believed that internal gravity waves (IGW) are the main wave process in the atmosphere. However, the explanation of the process of IGW occurrence cannot be considered sufficiently substantiat

Animikh Biswas, Zachary Bradshaw, Michael Jolly

We introduce a localized version of the nudging data assimilation algorithm for the periodic 2D Navier-Stokes equations in which observations are confined (i.e., localized) to a window that moves across the entire domain along a predetermined path at a given speed. We prove that, if the movement is fast enough, then the algorithm perfectly synchronizes with

Chien Hung Cho, Dominic W. Berry, Min-Hsiu Hsieh

Randomization has been applied to Hamiltonian simulation in a number of ways to improve the accuracy or efficiency of product formulas. Deterministic product formulas are often constructed in a symmetric way to provide accuracy of even order 2k. We show that by applying randomized corrections, it is possible to more than double the order to 4k + 1 (correspon

S. P. Fitzgerald, A. Bailey Hass, G. Díaz Leines, A. J. Archer

The time evolution of many physical, chemical, and biological systems can be modelled by stochastic transitions between the minima of the potential energy surface describing the system of interest. We show that in cases where there are two (or more) possible pathways that the system can take, the time available for the transition to occur is crucially import

Haoran Meng, Zheng Xin, Tianyu Liu, Zizhen Wang

While interacting with chatbots, users may elicit multiple intents in a single dialogue utterance. Instead of training a dedicated multi-intent detection model, we propose DialogUSR, a dialogue utterance splitting and reformulation task that first splits multi-intent user query into several single-intent sub-queries and then recovers all the coreferred and o

David Hovancik, Cinthia Piamonteze, Jiri Pospisil, Karel Carva

The existence of the V3+ ion orbital moment is the open issue of the nature of magnetism in the van der Waals ferromagnet VI3. The huge magnetocrystalline anisotropy in conjunction with the significantly reduced ordered magnetic moment compared to the spin-only value provides strong but indirect evidence of a significant V orbital moment. We used the unique

Yongwei Chen, Rui Chen, Jiabao Lei, Yabin Zhang

Creation of 3D content by stylization is a promising yet challenging problem in computer vision and graphics research. In this work, we focus on stylizing photorealistic appearance renderings of a given surface mesh of arbitrary topology. Motivated by the recent surge of cross-modal supervision of the Contrastive Language-Image Pre-training (CLIP) model, we

Chengdong Han, Wei Kou, Rong Wang, Xurong Chen

In this study, we try to extract $\omega n$, $\omega p$ and $\phi$N scattering lengths from the differential cross-section data of near-threshold $\omega$ and $\phi$ photoproductions not only to the energy at threshold t$_{thr}$, but also in t to t = 0. The incoherent data of $\omega$ and $\phi$ photoproductions on deuterium target for scattering length extr

Jeffrey Jiang, Omead Pooladzandi, Sunay Bhat, Gregory Pottie

A vast amount of expert and domain knowledge is captured by causal structural priors, yet there has been little research on testing such priors for generalization and data synthesis purposes. We propose a novel model architecture, Causal Structural Hypothesis Testing, that can use nonparametric, structural causal knowledge and approximate a causal model's fu

Thomas Chaplin, Heather A. Harrington, Ulrike Tillmann

Weighted digraphs are used to model a variety of natural systems and can exhibit interesting structure across a range of scales. In order to understand and compare these systems, we require stable, interpretable, multiscale descriptors. To this end, we propose grounded persistent path homology (GrPPH) - a new, functorial, topological descriptor that describe

Yijie Shen, Qiwen Zhan, Logan G. Wright, Demetrios N. Christodoulides

Spatiotemporal sculpturing of light pulse with ultimately sophisticated structures represents the holy grail of the human everlasting pursue of ultrafast information transmission and processing as well as ultra-intense energy concentration and extraction. It also holds the key to unlock new extraordinary fundamental physical effects. Traditionally, spatiotem

Yao Zhu, Xiaopeng Yuan, Yulin Hu, Tong Wang

Enabling ultra-reliable and low-latency communication services while providing massive connectivity is one of the major goals to be accomplished in future wireless communication networks. In this paper, we investigate the performance of a hybrid multi-access scheme in the finite blocklength (FBL) regime that combines the advantages of both non-orthogonal mul

Elena Meiser, Alexandra Alles, Samuel Selter, Marco Molz

Many car accidents are caused by human distractions, including cognitive distractions. In-vehicle human-machine interfaces (HMIs) have evolved throughout the years, providing more and more functions. Interaction with the HMIs can, however, also lead to further distractions and, as a consequence, accidents. To tackle this problem, we propose using adaptive HM

Émile Naquin, Maximilien Gadouleau

Finite dynamical systems (FDSs) are commonly used to model systems with a finite number of states that evolve deterministically and at discrete time steps. Considered up to isomorphism, those correspond to functional graphs. As such, FDSs have a sum and product operation, which correspond to the direct sum and direct product of their respective graphs; the c

Arnaud Pannatier, Kyle Matoba, François Fleuret

Real-world problems often involve complex and unstructured sets of measurements, which occur when sensors are sparsely placed in either space or time. Being able to model this irregular spatiotemporal data and extract meaningful forecasts is crucial. Deep learning architectures capable of processing sets of measurements with positions varying from set to set

Wanjun Zhong, Tingting Ma, Jiahai Wang, Jian Yin

This paper presents ReasonFormer, a unified reasoning framework for mirroring the modular and compositional reasoning process of humans in complex decision-making. Inspired by dual-process theory in cognitive science, the representation module (automatic thinking) and reasoning modules (controlled thinking) are decoupled to capture different levels of cognit

Andrea Gerbi, Renato Buzio, Cesar Gonzalez, Fernando Flores

We develop a phase-space ab-initio formalism to compute Ballistic Electron Emission Spectroscopy current-voltage I(V)'s in a metal-semiconductor interface. We consider injection of electrons into the conduction band for direct bias ($V>0$) and injection of holes into the valence band or injection of secondary Auger electrons into the conduction band for reve

Abrar Alali, Stephan Olariu, Shubham Jain

Recent statistics reveal an alarming increase in accidents involving pedestrians (especially children) crossing the street. A common philosophy of existing pedestrian detection approaches is that this task should be undertaken by the moving cars themselves. In sharp departure from this philosophy, we propose to enlist the help of cars parked along the sidewa

Yanfei Xiang, Xin Wang, Shu Hu, Bin Zhu

Reinforcement learning is applied to solve actual complex tasks from high-dimensional, sensory inputs. The last decade has developed a long list of reinforcement learning algorithms. Recent progress benefits from deep learning for raw sensory signal representation. One question naturally arises: how well do they perform concerning different robotic manipulat

Justin D. Finke, Soebur Razzaque

The preliminary detections of the gamma-ray burst 221009A up to 18 TeV by LHAASO and up to 251 TeV by Carpet 2 have been reported through Astronomer's Telegrams and Gamma-ray Coordination Network circulars. Since this burst is at redshift $z=0.1505$, these photons may at first seem to have a low probability to avoid pair production off of background radiatio

Dhananjay R. Thiruvady, Su Nguyen, Christian Blum, Andreas T. Ernst

Resource constrained project scheduling is an important combinatorial optimisation problem with many practical applications. With complex requirements such as precedence constraints, limited resources, and finance-based objectives, finding optimal solutions for large problem instances is very challenging even with well-customised meta-heuristics and matheuri

Luigi Berducci, Radu Grosu

The automatic synthesis of a policy through reinforcement learning (RL) from a given set of formal requirements depends on the construction of a reward signal and consists of the iterative application of many policy-improvement steps. The synthesis algorithm has to balance target, safety, and comfort requirements in a single objective and to guarantee that t

Antimo Marrazzo

Monolayer 1T'-WTe$_2$ has been the first two-dimensional crystal where a quantum spin Hall phase was experimentally observed. In addition, recent experiments and theoretical modeling reported the presence of a robust excitonic insulating phase. While first-principles calculations with hybrid functionals and several measurements at low temperatures suggest th

Alberto Lanconelli, Christopher S. A. Lauria

In the machine learning literature stochastic gradient descent has recently been widely discussed for its purported implicit regularization properties. Much of the theory, that attempts to clarify the role of noise in stochastic gradient algorithms, has widely approximated stochastic gradient descent by a stochastic differential equation with Gaussian noise.

Sanat Ghosh, Vilas Patil, Amit Basu, Kuldeep

Symmetry plays a critical role in determining various properties of a material. Semiconducting p-n junction diode exemplifies the engineered skew electronic response and is at the heart of contemporary electronic circuits. The non-reciprocal charge transport in a diode arises from doping-induced breaking of inversion symmetry. Breaking of time-reversal, in a

Elisa Bassignana, Max Müller-Eberstein, Mike Zhang, Barbara Plank

With the increase in availability of large pre-trained language models (LMs) in Natural Language Processing (NLP), it becomes critical to assess their fit for a specific target task a priori - as fine-tuning the entire space of available LMs is computationally prohibitive and unsustainable. However, encoder transferability estimation has received little to n

Sanat Ghosh, Digambar A. Jangade, Mandar M. Deshmukh

Superconducting nanowires are very important due to their applications ranging from quantum technology to astronomy. In this work, we implement a non-invasive process to fabricate nanowires of high-$T_\text{c}$ superconductor Bi$_2$Sr$_2$CaCu$_2$O$_{8+\delta}$ (BSCCO). We demonstrate that our nanowires can be used as bolometers in the visible range with very

Hoa T. Bui, Regina S. Burachik, Evgeni A. Nurminski, Matthew K. Tam

In this work, we consider a class of convex optimization problems in a real Hilbert space that can be solved by performing a single projection, i.e., by projecting an infeasible point onto the feasible set. Our results improve those established for the linear programming setting in Nurminski (2015) by considering problems that: (i) may have multiple solution

Wilfrid S. Kendall, Mateusz B. Majka, Aleksandar Mijatović

We study optimal Markovian couplings of Markov processes, where the optimality is understood in terms of minimization of concave transport costs between the time-marginal distributions of the coupled processes. We provide explicit constructions of such optimal couplings for one-dimensional finite-activity L\'evy processes (continuous-time random walks) whose

Diddigi Raghu Ram Bharadwaj, Lakshya Kumar, Saif Jawaid, Sreekanth Vempati

Sustaining users' interest and keeping them engaged in the platform is very important for the success of an e-commerce business. A session encompasses different activities of a user between logging into the platform and logging out or making a purchase. User activities in a session can be classified into two groups: Known Intent and Unknown intent. Known int

A. Turchi, E. Masciadri, C. Veillet

ALTA project has been active since 2016, providing, at LBT observatory site, forecasts of atmospheric parameters, such as temperature, wind speed and direction, relative humidity and precipitable water vapor, and optical turbulence parameters, such as seeing, wavefront coherence time and isoplanatic angle with the final goal to support nightly the science op

Zhibo Liu, Wei Xie, Akira Watanabe

The total and differential cross sections of elastic proton-proton and proton-antiproton scattering are studied in a holographic QCD model, considering the Pomeron and Reggeon exchanges in the Regge regime. In our model setup, the Pomeron and Reggeon exchanges are described by the Reggeized spin-2 glueball and vector meson propagators, respectively. How thos

Ilya Orson Sandoval, Panagiotis Petsagkourakis, Ehecatl Antonio del Rio-Chanona

Neural ordinary differential equations (Neural ODEs) define continuous time dynamical systems with neural networks. The interest in their application for modelling has sparked recently, spanning hybrid system identification problems and time series analysis. In this work we propose the use of a neural control policy capable of satisfying state and control co

A. Turchi, G. Agapito, E. Masciadri, O. Beltramo-Martin

Characterizing the PSF of adaptive optics instruments is of paramount importance both for instrument design and observation planning/optimization. Simulation software, such as PASSATA, have been successfully utilized for PSF characterization in instrument design, which make use of standardized atmospheric turbulence profiles to produce PSFs that represent th

Yukun Wang, Xinjian Liu, Shaoxuan Wang, Haoying Zhang

Entangled two-qubit states are the core building blocks for constructing quantum communication networks. Their accurate verification is crucial to the functioning of the networks, especially for untrusted networks. In this work we study the self-testing of two-qubit entangled states via steering inequalities, with robustness analysis against noise. More prec

Jenny Schmalfuss, Lukas Mehl, Andrés Bruhn

Current adversarial attacks for motion estimation (optical flow) optimize small per-pixel perturbations, which are unlikely to appear in the real world. In contrast, we exploit a real-world weather phenomenon for a novel attack with adversarially optimized snow. At the core of our attack is a differentiable renderer that consistently integrates photorealisti

Qazwan Abdullah, Nor Shahida Mohd Shah, Shipun Hamzah, Adeb Salh

Massive multiple-input multiple-output (MIMO) is a critical technology for future fifth-generation (5G) systems. Reduced pilot contamination (PC) enhanced system performance, and reduced inter-cell interference and improved channel estimation. However, because the pilot sequence transmitted by users in a single cell to neighboring cells is not orthogonal, ma

Katsuya Hashino, Daiki Ueda

Future gravitational wave observations are potentially sensitive to new physics corrections to the Higgs potential once the first-order electroweak phase transition arises. We study the SMEFT dimension-six operator effects on the Higgs potential, where three types of effects are taken into account: (i) SMEFT tree level effect on $\varphi^6$ operator, (ii) SM

A. Turchi, E. Masciadri, L. Fini

Forecast of optical turbulence and atmospheric parameters relevant for ground-based astronomy is becoming an important goal for telescope planning and AO instruments optimization in several major telescope. Such detailed and accurate forecast is typically performed with numerical atmospheric models. Recently short-term forecasts (a few hours in advance) are

Sebastian Monka, Lavdim Halilaj, Achim Rettinger

Current deep learning methods for object recognition are purely data-driven and require a large number of training samples to achieve good results. Due to their sole dependence on image data, these methods tend to fail when confronted with new environments where even small deviations occur. Human perception, however, has proven to be significantly more robus

Manuel Rigger, Zhendong Su

A test oracle determines whether a system behaves correctly for a given input. Automatic testing techniques rely on an automated test oracle to test the system without user interaction. Important families of automated test oracles include Differential Testing and Metamorphic Testing, which are both black-box approaches; that is, they provide a test oracle th

Santiago Giménez de Castro, Aires Ferreira, D. A. Bahamon

In recent years, Chebyshev polynomial expansions of tight-binding Green's functions have been successfully applied to the study of a wide range of spectral and transport properties of materials. However, the application of the Chebyshev approach to the study of quantum transport properties of noninteracting mesoscopic systems with leads has been hampered by

Jonathan Vance, Khaled Rasheed, Ali Missaoui, Frederick Maier

The alfalfa crop is globally important as livestock feed, so highly efficient planting and harvesting could benefit many industries, especially as the global climate changes and traditional methods become less accurate. Recent work using machine learning (ML) to predict yields for alfalfa and other crops has shown promise. Previous efforts used remote sensin

Kyung-Youn Kim, Lidan Wang

Let $Z=(Z^{1}, \ldots, Z^{d})$ be the d-dimensional L\'evy {process} where {$Z^i$'s} are independent 1-dimensional L\'evy {processes} with identical jumping kernel $ \nu^1(r) =r^{-1}\phi(r)^{-1}$. Here $\phi$ is {an} increasing function with weakly scaling condition of order $\underline \alpha, \overline \alpha\in (0, 2)$. We consider a symmetric function $J

Liz Kneale, Steve T Wilson, Tara Appleyard, James Armitage

Antineutrinos from a nuclear reactor comprise an unshieldable signal which carries information about the core. A gadolinium-doped, water-based Cherenkov detector could detect reactor antineutrinos for mid- to far-field remote reactor monitoring for non-proliferation applications. Two novel and independent reconstruction and analysis pathways have been develo

Naoki Yoshimaru, Tomohiro Masuda, Hyejin Hong, Yusei Tanaka

Various studies have been conducted on human-supporting robot systems. These systems have been put to practical use over the years and are now seen in our daily lives. In particular, robots communicating smoothly with people are expected to play an active role in customer service and guidance. In this case, it is essential to determine whether the customer i

Adeb Salh, Qazwan Abdullah, Ghasan Hussain, Razlai Ngah

In this article, we present a new approach to optimizing the energy efficiency of the cost-efficiency of quantized hybrid pre-encoding (HP) design. We present effective alternating minimization algorithms (AMA) based on the zero gradient method to produce completely connected structures (CCSs) and partially connected structures (PCSs). Alternative minimizati

Mikhail Khodak, Kareem Amin, Travis Dick, Sergei Vassilvitskii

When applying differential privacy to sensitive data, we can often improve performance using external information such as other sensitive data, public data, or human priors. We propose to use the learning-augmented algorithms (or algorithms with predictions) framework -- previously applied largely to improve time complexity or competitive ratios -- as a powe

Christian Bauer

Direct numerical simulations of turbulent open channel flow with friction Reynolds numbers of $Re_{\tau}=200,400,600$ are performed. Their results are compared with closed channel data in order to investigate the influence of the free surface on turbulent channel flows. The free surface affects fully developed turbulence statistics in so far that velocities

Shaolei Zhang, Shoutao Guo, Yang Feng

Simultaneous machine translation (SiMT) outputs the translation while receiving the source inputs, and hence needs to balance the received source information and translated target information to make a reasonable decision between waiting for inputs or outputting translation. Previous methods always balance source and target information at the token level, ei

Jianhua Yang

In this technical report, we would like to introduce our updates to YOWO, a real-time method for spatio-temporal action detection. We make a bunch of little design changes to make it better. For network structure, we use the same ones of official implemented YOWO, including 3D-ResNext-101 and YOLOv2, but we use a better pretrained weight of our reimplemented

Alona Zharova, Annika Boer, Julia Knoblauch, Kai Ingo Schewina

Understandable and persuasive recommendations support the electricity consumers' behavioral change to tackle the energy efficiency problem. Generating load shifting recommendations for household appliances as explainable increases the transparency and trustworthiness of the system. This paper proposes an explainable multi-agent recommendation system for load

Xinghan Liu, Emiliano Lorini, Antonino Rotolo, Giovanni Sartor

This paper brings together two lines of research: factor-based models of case-based reasoning (CBR) and the logical specification of classifiers. Logical approaches to classifiers capture the connection between features and outcomes in classifier systems. Factor-based reasoning is a popular approach to reasoning by precedent in AI & Law. Horty (2011) has dev

Masanori Hanada, Hiromasa Watanabe

The confinement/deconfinement transition in gauge theory plays important roles in physics, including the description of thermal phase transitions in the dual gravitational theory. Partial deconfinement implies an intermediate phase in which color degrees of freedom split into the confined and deconfined sectors. The partially-deconfined phase is dual to the

Wenzhi Yang, Yiming Liu, Guangming Pan, Wang Zhou

In this paper, we use the dimensional reduction technique to study the central limit theory (CLT) random quadratic forms based on sample means and sample covariance matrices. Specifically, we use a matrix denoted by $U_{p\times q}$, to map $q$-dimensional sample vectors to a $p$ dimensional subspace, where $q\geq p$ or $q\gg p$. Under the condition of $p/n\r

Léo Mathis, Michele Stecconi

We develop a calculus based on zonoids - a special class of convex bodies - for the expectation of functionals related to a random submanifold $Z$ defined as the zero set of a smooth vector valued random field on a Riemannian manifold. We identify a convenient set of hypotheses on the random field under which we define its zonoid section, an assignment of a

Roland Glück, Marian Körber

This paper is concerned with the automation and simulation of pick and place processes in the domain of CFK aircraft production. We introduce a workflow which starts from a CAD construction, extracts relevant data out of it, assigns grippers to the CFK pieces and schedules the single steps using a PDDL solver. Finally, the result is visualized in Blender whe

Zhen-Hua Zhu, Huaiyu Wu, Zhi-Hong Guan, Zhi-Wei Liu

This article targets at addressing the robust prescribed-time coordination control (PTCC) problems for single-integrator cooperative-antagonistic networks (CANs) with external disturbances under arbitrary fixed signed digraphs without any structural constraints. Toward this end, the PTCC problems for nominal single-integrator CANs without disturbances are fi

Arnaud Chéritat, Dimitri Le Meur

The lifted horn map of a holomorphic function with a simple parabolic point is well known to be a complete local conjugacy invariant; this is a classical result proved independently by \'Ecalle, Voronin, Martinet and Ramis. Lanford and Yampolski have shown that, if two functions $f_1, f_2$ with simple parabolic points at $z_1, z_2$ are globally conjugate on

Tejasvi Chauhan, Anjana Devanand, M. K. Roxy, Karumuri Ashok

Massive river interlinking projects are proposed to offset observed increasing trends of extremes, such as droughts and floods in India, the second highest populated country.These river interlinking projects involve water transfer from surplus to deficit river basins through reservoirs and canals, but without an in-depth understanding of the hydro-meteorolog

M. Środa, J. Mravlje, G. Alvarez, E. Dagotto

Spectroscopy experiments are routinely used to characterize the behavior of strongly correlated systems. An in-depth understanding of the different spectral features is thus essential. Here, we show that the spectrum of the multiorbital Hubbard model exhibits unique Hund \ms{bands} that occur at energies given only by the Hund coupling $J_\mathrm{H}$, as dis

Maria Saladina, Christopher Wöpke, Clemens Göhler, Ivan Ramirez

The density of states (DOS) is fundamentally important for understanding physical processes in organic disordered semiconductors, yet hard to determine experimentally. We evaluated the DOS by considering recombination via tail states and using the temperature and open-circuit voltage ($V_\mathrm{oc}$) dependence of the ideality factor in organic solar cells.

O. Balsalobre-Ruza, J. Lillo-Box, A. Berihuete, A. M. Silva

Ground-based observing time is precious in the era of exoplanet follow-up and characterization, especially in high-precision radial velocity instruments. Blind-search radial velocity surveys thus require a dedicated observational strategy in order to optimize the observing time, which is particularly crucial for the detection of small rocky worlds at large o

Dalma Bilbao, Hugo Aimar, Diego M. Mateos

In this paper we aim to use different metrics in the Euclidean space and Sobolev type metrics in function spaces in order to produce reliable parameters for the differentiation of point distributions and dynamical systems. The main tool is the analysis of the geometrical evolution of the hypergraphs generated by the growth of the radial parameters for a choi

J. Delos Reyes, T. Shardlow, M. B. Delgado-Charro, S. Webb

The global importance of effective and affordable pesticides to optimise crop yield and to support health of our growing population cannot be understated. But to develop new products or refine existing ones in response to climate and environmental changes is both time-intensive and expensive which is why the agrochemical industry is increasingly interested i

Yi Wang, Menghan Xia, Lu Qi, Jing Shao

Multimodal ambiguity and color bleeding remain challenging in colorization. To tackle these problems, we propose a new GAN-based colorization approach PalGAN, integrated with palette estimation and chromatic attention. To circumvent the multimodality issue, we present a new colorization formulation that estimates a probabilistic palette from the input gray i

Xiaotong Sun, Xi Chen, Charalampos Stasinakis, Georgios Sermpinis

Decentralized Autonomous Organization (DAO) provides a decentralized governance solution through blockchain, where decision-making process relies on on-chain voting and follows majority rule. This paper focuses on MakerDAO, and we find three voter coalitions after applying clustering algorithm to voting history. The emergence of a dominant voter coalition is

A. V. Rodina, E. L. Ivchenko

We have developed a theory of Raman scattering with single and double spin flips of localized resident electrons and holes as well as nonequilibrium localized excitons in semiconductor perovskite crystals under optical excitation in the resonant exciton region. Scattering mechanisms involving localized excitons, biexcitons and exciton polaritons as intermedi

Dong-Sig Han, Hyunseo Kim, Hyundo Lee, Je-Hwan Ryu

Recently, adversarial imitation learning has shown a scalable reward acquisition method for inverse reinforcement learning (IRL) problems. However, estimated reward signals often become uncertain and fail to train a reliable statistical model since the existing methods tend to solve hard optimization problems directly. Inspired by a first-order optimization

Junde Liu, Dongchen Huang, Yi-feng Yang, Tian Qian

Spectroscopic data may often contain unwanted extrinsic signals. For example, in ARPES experiment, a wire mesh is typically placed in front of the CCD to block stray photo-electrons, but could cause a grid-like structure in the spectra during quick measurement mode. In the past, this structure was often removed using the mathematical Fourier filtering method

Victoria Saravia, William Moraes, André Kelbouscas, Ricardo Grando

This work focuses on drones or UAVs (Unmanned Aerial Vehicles) for use in industry in general. These vehicles have a large number of uses and potential in the industry, as a tool for civil engineering, medicine, mining, among others. However, this vehicle is limited for use indoors due to the need for GPS and it does not work indoors. In this way, this work

V. A. Rubakov, C. Wetterich

The geometric concept of geodesic completeness depends on the choice of the metric field or "metric frame". We develop a frame-invariant concept of "generalised geodesic completeness" or "time completeness". It is based on the notion of physical time defined by counting oscillations for some physically allowed process. Oscillating solutions of wave functions

Kamil Khadiev, Nikita Savelyev, Mansur Ziatdinov, Denis Melnikov

The paper presents a technique for constructing noisy data structures called a walking tree. We apply it for a Red-Black tree (an implementation of a Self-Balanced Binary Search Tree) and a segment tree. We obtain the same complexity of the main operations for these data structures as in the case without noise (asymptotically). We present several application

Malte S. Kurz

Vine copulas are a flexible tool for high-dimensional dependence modeling. In this article, we discuss the generation of approximate model-X knockoffs with vine copulas. It is shown how Gaussian knockoffs can be generalized to Gaussian copula knockoffs. A convenient way to parametrize Gaussian copulas are partial correlation vines. We discuss how completion

Hiago Jacobs Sodre Pereira, Pablo Ezequiel Moraes, André Da Silva Kelbouscas, Ricardo Grando

The implementation of robots to enhance some processes has become popular in recent years due to the accelerated way of production in some factories. Within this context was where robotics has emerged, firstly with stationary robots and more recently mobile robots, namely aerial and terrestrial robots. They can be used for delimited processes within a functi

Qian-Wei Wang, Bowen Zhao, Mingyan Zhu, Tianxiang Li

Partial label learning (PLL) learns from training examples each associated with multiple candidate labels, among which only one is valid. In recent years, benefiting from the strong capability of dealing with ambiguous supervision and the impetus of modern data augmentation methods, consistency regularization-based PLL methods have achieved a series of succe

E. Domínguez, H. J. Kappen

In this paper we introduce an approximate method to solve the quantum cavity equations for transverse field Ising models. The method relies on a projective approximation of the exact cavity distributions of imaginary time trajectories (paths). A key feature, novel in the context of similar algorithms, is the explicit separation of the classical and quantum p

Philip Hackney, Joachim Kock

We introduce the notion of free decomposition spaces: they are simplicial spaces freely generated by their inert maps. We show that left Kan extension along the inclusion $j \colon \Delta_{\operatorname{inert}} \to \Delta$ takes general objects to M\"obius decomposition spaces and general maps to CULF maps. We establish an equivalence of $\infty$-categories

Philip Hackney, Joachim Kock

We show that, for any simplicial space $X$, the $\infty$-category of culf maps over $X$ is equivalent to the $\infty$-category of right fibrations over $\operatorname{sd}(X)$, the edgewise subdivision of $X$. (When $X$ is a Rezk complete Segal or 2-Segal space, $\operatorname{sd}(X)$ is the twisted arrow category of $X$.) We give two proofs of independent in

Mattias Nilsson, Olov Schelén, Anders Lindgren, Ulf Bodin

Increasing complexity and data-generation rates in cyber-physical systems and the industrial Internet of things are calling for a corresponding increase in AI capabilities at the resource-constrained edges of the Internet. Meanwhile, the resource requirements of digital computing and deep learning are growing exponentially, in an unsustainable manner. One po

Angeliki Menegaki

We consider the four waves spatial homogeneous kinetic equation arising in wave turbulence theory. We study the long-time behaviour and existence of solutions around the Rayleigh-Jeans equilibrium solutions. For cut-off'd frequencies, we show that for dispersion relations weakly perturbed around the quadratic case, the linearized operator around the Rayleigh

I. V. Anikin

We advocate the existence of a new type of $k_\perp$-dependent functions. In contrast to the well-known Boer-Mulders function, the presented new functions can be associated with the collective alignment of quark spin vectors. Moreover, the new functions are sensitive to the transverse motion of partons inside hadrons, which are linked to the spin alignment o

Fabian Zierler, Jong-Wan Lee, Axel Maas, Felix Pressler

We explore some aspects of $Sp(4)$ gauge theory with two fundamental fermions in the context of composite Goldstone Dark Matter. We present preliminary lattice results for the mass of the pseudoscalar iso-singlet meson $\eta'$ using unimproved Wilson fermions and the standard plaquette action. We find that the $\eta'$ is slightly heavier than the pseudoscala

Ankit Dhanuka, Kinjalk Lochan

Unruh deWitt detectors are important constructs in studying the dynamics of quantum fields in any geometric background. Curvature also plays an important role in setting up the correlations of a quantum field in a given spacetime. For instance, massless fields are known to have large correlations in de Sitter space as well as in certain class of Friedmann-Ro

Abhishek Singh

Fixed-point iteration algorithms like RTA (response time analysis) and QPA (quick processor-demand analysis) are arguably the most popular ways of solving schedulability problems for preemptive uniprocessor FP (fixed-priority) and EDF (earliest-deadline-first) systems. Several IP (integer program) formulations have also been proposed for these problems, but

I. Yu. Mogilnykh, K. V. Vorob'ev

We prove that any completely regular code with minimum eigenvalue in any geometric graph G corresponds to a completely regular code in the clique graph of G. Studying the interrelation of these codes, a complete characterization of the completely regular codes in the Johnson graphs J(n,w) with covering radius w-1 and strength 1 is obtained. In particular thi

Medet Nursultanov

We investigate the $L_p \mapsto L_q$ boundedness of the Fourier multipliers. We obtain sufficient conditions, namely, we derive Hormander and Lizorkin type theorems. We also obtain the necessary conditions. For $M$-generalized monotone functions, we obtain a criteria for boundedness of the corresponding Fourier multipliers.

Hamza Bouzid, Lahoucine Ballihi

Facial expression generation has always been an intriguing task for scientists and researchers all over the globe. In this context, we present our novel approach for generating videos of the six basic facial expressions. Starting from a single neutral facial image and a label indicating the desired facial expression, we aim to synthesize a video of the given

Edgar Andres Ruiz Guzman, Denis Lacroix

We present a new method to perform variation after projection in many-body systems on quantum computers that does not require performing explicit projection. The technique employs the notion of ``oracle'', generally used in quantum search algorithms. We show how to construct the oracle and the projector associated with a symmetry operator. The procedure is i

Eoin Farrell, Adam S. Jermyn, Matteo Cantiello, Daniel Foreman-Mackey

Stars are born with magnetic fields, but the distribution of their initial field strengths remains uncertain. We combine observations with theoretical models of magnetic field evolution to infer the initial distribution of magnetic fields for AB stars in the mass range of 1.6 - 3.4 M$_{\odot}$. We tested a variety of distributions with different shapes and f

Paweł A. Pierzchlewicz, R. James Cotton, Mohammad Bashiri, Fabian H. Sinz

Due to depth ambiguities and occlusions, lifting 2D poses to 3D is a highly ill-posed problem. Well-calibrated distributions of possible poses can make these ambiguities explicit and preserve the resulting uncertainty for downstream tasks. This study shows that previous attempts, which account for these ambiguities via multiple hypotheses generation, produce

Pavel Abolmasov, Omer Bromberg

Both the dynamics and the observational properties of relativistic jets are determined by their interaction with the ambient medium. A crucial role is played by the contact discontinuity at the jet boundary, which in the presence of jet collimation may become subject to Rayleigh-Taylor instability (RTI) and Richtmyer-Meshkov instability (RMI). Here, we study

Ankit Gupta, Ida-Maria Sintorn

Attention Branch Networks (ABNs) have been shown to simultaneously provide visual explanation and improve the performance of deep convolutional neural networks (CNNs). In this work, we introduce Multi-Scale Attention Branch Networks (MSABN), which enhance the resolution of the generated attention maps, and improve the performance. We evaluate MSABN on benchm

A. A. Vasilev, D. S. Saranin, P. A. Gostishchev, M. P. Tuhova

The long-term stability of halide perovskite solar cells (PSCs) remains the critical problem of this photovoltaic technology. Different structural defects formed in the thin-film perovskite films were considered as a main trigger for the decomposition of the absorber and corrosion of the interfaces in the device structure. The changes in the stability perfor

Alon Jacobson, Xiaozhe Hu

Fractional vector calculus is the building block of the fractional partial differential equations that model non-local or long-range phenomena, e.g., anomalous diffusion, fractional electromagnetism, and fractional advection-dispersion. In this work, we reformulate a type of fractional vector calculus that uses Caputo fractional partial derivatives and discr

Md Nurul Muttakin, Md Iqbal Hossain, Md Saidur Rahman

Overlapping community detection is a key problem in graph mining. Some research has considered applying graph convolutional networks (GCN) to tackle the problem. However, it is still challenging to incorporate deep graph convolutional networks in the case of general irregular graphs. In this study, we design a deep dynamic residual graph convolutional networ