December 2023 arXiv papers — page 12

Malik Hassanaly, Peter J. Weddle, Ryan N. King, Subhayan De

To plan and optimize energy storage demands that account for Li-ion battery aging dynamics, techniques need to be developed to diagnose battery internal states accurately and rapidly. This study seeks to reduce the computational resources needed to determine a battery's internal states by replacing physics-based Li-ion battery models -- such as the single-pa

Sera Cremonini, Brian McPeak, Yuezhang Tang

The requirement that particles propagate causally on non-trivial backgrounds implies interesting constraints on higher-derivative operators. This work is part of a systematic study of the positivity bounds derivable from time delays on shockwave backgrounds. First, we discuss shockwaves in field theory, which are infinitely boosted Coulomb-like field configu

A. A. Kon'kov, A. E. Shishkov

We obtain a Dini type blow-up condition for global weak solutions of the differential inequality $$ \sum_{|\alpha| = m} \partial^\alpha a_\alpha (x, u) \ge g (|u|) \quad \mbox{in } {\mathbb R}^n, $$ where $m, n \ge 1$ are integers and $a_\alpha$ and $g$ are some functions.

Daniel Azses, Jonathan Ruhman, Eran Sela

Measurement-based quantum computation (MBQC) is a universal platform to realize unitary gates, only using measurements which act on a pre-prepared entangled resource state. By deforming the measurement bases, as well as the geometry of the resource state, we show that MBQC circuits always transmit and act on the input state but generally realize nonunitary l

Fabian Panse, Wolfram Wingerath, Benjamin Wollmer

Due to the increasing volume, volatility, and diversity of data in virtually all areas of our lives, the ability to detect duplicates in potentially linked data sources is more important than ever before. However, while research is already intensively engaged in adapting duplicate detection algorithms to the changing circumstances, existing test data generat

M. Gomilšek, T. J. Hicken, M. N. Wilson, K. J. A. Franke

Skyrmions are particle-like vortices of magnetization with non-trivial topology, which are usually stabilized by Dzyaloshinskii-Moriya interactions (DMI) in noncentrosymmetric bulk materials. Exceptions are centrosymmetric Gd- and Eu-based skyrmion-lattice (SkL) hosts with zero DMI, where both the SkL stabilization mechanisms and magnetic ground states remai

Lakshya Bhardwaj, Lea E. Bottini, Daniel Pajer, Sakura Schafer-Nameki

We provide a generalization of the Symmetry Topological Field Theory (SymTFT) framework to characterize phase transitions and gapless phases with categorical symmetries. The central tool is the club sandwich, which extends the SymTFT setup to include an interface between two topological orders: there is a symmetry boundary, which is gapped, and a physical bo

Zhenyuan Wang, Donghui Jeong

Revealing the large-scale structure from the 21cm intensity mapping surveys is only possible after the foreground cleaning. However, most current cleaning techniques relying on the smoothness of the foreground spectrum lead to a severe side effect of removing the large-scale structure signal along the line of sight. On the other hand, the clustering fossil,

P. Aromal, R. Srianand, P. Petitjean

We probe the small-scale absorption line variability using absorption depth based analysis of a sample of 64 ultra-fast outflow (UFO) C IV broad absorption line (BAL) quasars monitored using the Southern African Large Telescope. We confirm the strong monotonic increase in the strength of variability with increasing outflow velocity. We identify regions insid

Mila Winter-Granic, Cristobal Petrovich, Valentín Peña-Donaire, Chris Hamilton

Galactic centers are very dynamically active environments, often harbouring a nuclear star cluster and supermassive black hole at their cores. Binaries in these environments are subject to strong tidal fields that can efficiently torque its orbit, exciting near unity eccentricities that ultimately lead to their merger. In turn, frequent close interactions wi

Alexander Kruchkov, Shinsei Ryu

Topological invariants are fundamental characteristics reflecting global properties of quantum systems, yet their exploration has predominantly been limited to the static (DC) transport and transverse (Hall) channel. In this work, we extend the spectral sum rules for frequency-resolved electric conductivity $\sigma (\omega)$ in topological systems, and show

Gonçalo M. Quinta, Antonino Flachi

We develop a non-conventional description of the vacuum energy in quantum field theory in terms of quantum entropy. Precisely, we show that the vacuum energy of any non-interacting quantum field at zero temperature is proportional to the quantum entropy of the qubit degrees of freedom associated with virtual fluctuations. We prove this for fermions first, an

Adam Bzowski, Paul McFadden, Kostas Skenderis

We formulate a renormalisation procedure for IR divergences of tree-level in-in late-time de Sitter correlators. These divergences are due to the infinite volume of spacetime and are analogous to the divergences that appear in AdS dealt with by holographic renormalisation. Regulating the theory using dimensional regularisation, we show that one can remove al

P. S. Bhupal Dev, Sudip Jana, Yago Porto

We show that high-energy astrophysical neutrinos produced in the cores of heavily obscured active galactic nuclei (AGNs) can undergo strong matter effects, thus significantly influencing their source flavor ratios. In particular, matter effects can completely modify the standard interpretation of the flavor ratio measurements in terms of the physical process

Guglielmo Coloretti, Andreas Crivellin, Bruce Mellado

The LHC analyses of processes containing two or more leptons and missing energy, possibly in association with b-jets, show strong tensions with the Standard Model predictions and are known as multi-lepton anomalies. In particular, top-quark differential distributions point towards the associated production of new Higgs bosons decaying into bottom quarks and

Cecilia Giavoni, Stefan Hofmann, Maximilian Koegler

We show that quantum fields confined to Lorentzian histories of freely falling networks in Minkowski spacetime probe entanglement properties of vacuum fluctuations that extend unrestricted across spacetime regions. Albeit instantaneous field configurations are localized on one-dimensional edges, angular momentum emerges on these network histories and establi

Hayden Lee, Xinkang Wang

We present a classification of conformally-invariant three-point tensor structures in $d$ dimensions that parallels the classification of three-particle scattering amplitudes in $d+1$ dimensions. Using a set of canonically-normalized weight-shifting operators, we construct a basis of three-point structures involving conserved currents or stress tensors and n

Sparsh Gupta, Hari Kumar Yadalam, Manas Kulkarni, Camille Aron

We discuss how quantum jumps affect localized regimes in driven-dissipative disordered many-body systems featuring a localization transition. We introduce a deformation of the Lindblad master equation that interpolates between the standard Lindblad and the no-jump non-Hermitian dynamics of open quantum systems. As a platform, we use a disordered chain of har

Chin-Hsuan Wu, Yen-Chun Chen, Bolivar Solarte, Lu Yuan

We present iFusion, a novel 3D object reconstruction framework that requires only two views with unknown camera poses. While single-view reconstruction yields visually appealing results, it can deviate significantly from the actual object, especially on unseen sides. Additional views improve reconstruction fidelity but necessitate known camera poses. However

Yonglong Tian, Lijie Fan, Kaifeng Chen, Dina Katabi

We introduce SynCLR, a novel approach for learning visual representations exclusively from synthetic images and synthetic captions, without any real data. We synthesize a large dataset of image captions using LLMs, then use an off-the-shelf text-to-image model to generate multiple images corresponding to each synthetic caption. We perform visual representati

Sky CH-Wang, Benjamin Van Durme, Jason Eisner, Chris Kedzie

We design probes trained on the internal representations of a transformer language model to predict its hallucinatory behavior on three grounded generation tasks. To train the probes, we annotate for span-level hallucination on both sampled (organic) and manually edited (synthetic) reference outputs. Our probes are narrowly trained and we find that they are

Guhao Feng, Han Zhong

Reinforcement Learning (RL) encompasses diverse paradigms, including model-based RL, policy-based RL, and value-based RL, each tailored to approximate the model, optimal policy, and optimal value function, respectively. This work investigates the potential hierarchy of representation complexity -- the complexity of functions to be represented -- among these

Luca Di Luzio, Hector Gisbert, Gabriele Levati, Paride Paradisi

We review the physics case for CP-violating axions. In the first part, we focus on the Quantum Chromodynamics (QCD) axion and argue that new sources of CP violation beyond QCD misalign the axion solution to the strong CP problem and can manifest themselves via a tiny scalar axion-nucleon component. We hence highlight recent advancements in calculating this s

Guanqi Zhan, Chuanxia Zheng, Weidi Xie, Andrew Zisserman

This paper studies amodal image segmentation: predicting entire object segmentation masks including both visible and invisible (occluded) parts. In previous work, the amodal segmentation ground truth on real images is usually predicted by manual annotaton and thus is subjective. In contrast, we use 3D data to establish an automatic pipeline to determine auth

Mathias Becker, Emanuele Copello, Julia Harz, Carlos Tamarit

We study thermal corrections to a model of real scalar dark matter (DM) interacting feebly with a SM fermion and a gauge-charged vector-like fermion mediator. We employ the Closed-Time-Path (CTP) formalism for our calculation and go beyond previous works by including the full dependence on the relevant mass scales as opposed to using (non)relativistic approx

Andrzej Borowiec, Jerzy Kowalski-Glikman, Tomasz Trześniewski

In this paper, we find a class of Carrollian and Galilean contractions of (extended) BMS algebra in 3+1 and 2+1 dimensions. To this end, we investigate possible embeddings of 3D/4D Poincar\'{e} into the BMS${}_3$ and BMS${}_4$ algebras, respectively. The contraction limits in the 2+1-dimensional case are then enforced by appropriate contractions of its Poinc

Tycho F. A. van der Ouderaa, Markus Nagel, Mart van Baalen, Yuki M. Asano

State-of-the-art language models are becoming increasingly large in an effort to achieve the highest performance on large corpora of available textual data. However, the sheer size of the Transformer architectures makes it difficult to deploy models within computational, environmental or device-specific constraints. We explore data-driven compression of exis

Dantong Niu, Xudong Wang, Xinyang Han, Long Lian

Several unsupervised image segmentation approaches have been proposed which eliminate the need for dense manually-annotated segmentation masks; current models separately handle either semantic segmentation (e.g., STEGO) or class-agnostic instance segmentation (e.g., CutLER), but not both (i.e., panoptic segmentation). We propose an Unsupervised Universal Seg

Aleem Khan, Andrew Wang, Sophia Hager, Nicholas Andrews

Prior work in style-controlled text generation has focused on tasks such as emulating the style of prolific literary authors, producing formal or informal text, and mitigating toxicity of generated text. Plentiful demonstrations of these styles are available, and as a result modern language models are often able to emulate them, either via prompting or discr

Towaki Takikawa, Thomas Müller, Merlin Nimier-David, Alex Evans

Neural graphics primitives are faster and achieve higher quality when their neural networks are augmented by spatial data structures that hold trainable features arranged in a grid. However, existing feature grids either come with a large memory footprint (dense or factorized grids, trees, and hash tables) or slow performance (index learning and vector quant

Senqiao Yang, Tianyuan Qu, Xin Lai, Zhuotao Tian

While LISA effectively bridges the gap between segmentation and large language models to enable reasoning segmentation, it poses certain limitations: unable to distinguish different instances of the target region, and constrained by the pre-defined textual response formats. In this work, we introduce LISA++, an update to the existing LISA model, focusing on

Kohta Murase

Multiwavelength observations have revealed that dense, confined circumstellar material (CCSM) commonly exists in the vicinity of supernova (SN) progenitors, suggesting enhanced mass losses years to centuries before their core collapse. Interacting SNe, which are powered or aided by interaction with the CCSM, are considered to be promising high-energy multime

Artyom Eliseev, Denis Mazur

With the widespread adoption of Large Language Models (LLMs), many deep learning practitioners are looking for strategies of running these models more efficiently. One such strategy is to use sparse Mixture-of-Experts (MoE) - a type of model architectures where only a fraction of model layers are active for any given input. This property allows MoE-based lan

Xin An, Michał Spaliński

The strong longitudinal expansion characteristic of heavy-ion collisions leads to universal attractor behavior of the resulting drop of quark-gluon plasma (QGP) already at very early times. Assuming approximate boost invariance and neglecting transverse expansion at the initial time, we incorporate subsequent transverse dynamics of this system by linearizing

Fahimeh Hajari, Samaneh Malmir, Ehsan Mirsaeedi, Peter C. Rigby

Developer turnover is inevitable on software projects and leads to knowledge loss, a reduction in productivity, and an increase in defects. Mitigation strategies to deal with turnover tend to disrupt and increase workloads for developers. In this work, we suggest that through code review recommendation we can distribute knowledge and mitigate turnover while

Ce Zhang, Taixi Lu, Md Mohaiminul Islam, Ziyang Wang

We present LLoVi, a language-based framework for long-range video question-answering (LVQA). Unlike prior long-range video understanding methods, which are often costly and require specialized long-range video modeling design (e.g., memory queues, state-space layers, etc.), our approach uses a frame/clip-level visual captioner (e.g., BLIP2, LaViLa, LLaVA) co

Pradyumna Chari, Sizhuo Ma, Daniil Ostashev, Achuta Kadambi

Generative diffusion models can serve as a prior which ensures that solutions of image restoration systems adhere to the manifold of natural images. However, for restoring facial images, a personalized prior is necessary to accurately represent and reconstruct unique facial features of a given individual. In this paper, we propose a simple, yet effective, me

Stijn Cambie, Wouter Cames van Batenburg, Xuding Zhu

One of Thomassen's classical results is that every planar graph of girth at least $5$ is 3-choosable. One can wonder if for a planar graph $G$ of girth sufficiently large and a $3$-list-assignment $L$, one can do even better. Can one find $3$ disjoint $L$-colorings (a packing), or $2$ disjoint $L$-colorings, or a collection of $L$-colorings that to every ver

Rui Huang, Songyou Peng, Ayca Takmaz, Federico Tombari

Current 3D scene segmentation methods are heavily dependent on manually annotated 3D training datasets. Such manual annotations are labor-intensive, and often lack fine-grained details. Importantly, models trained on this data typically struggle to recognize object classes beyond the annotated classes, i.e., they do not generalize well to unseen domains and

Nora Brambilla, Viljami Leino, Julian Mayer-Steudte, Antonio Vairo

The static QCD force from the lattice can be used to extract $\Lambda_{\overline{\textrm{MS}}}$, which determines the running of the strong coupling. Usually, this is done with a numerical derivative of the static potential. However, this introduces additional systematic uncertainties; thus, we use another observable to measure the static force directly. Thi

Zhi Li, Zhu-Xi Luo

Symmetry is a powerful tool for understanding phases of matter in equilibrium. Quantum circuits with measurements have recently emerged as a platform for novel states of matter intrinsically out of equilibrium. Can symmetry be used as an organizing principle for these novel states, their phases and phase transitions? In this work, we give an affirmative answ

Jiuyao Lu, Daogao Liu, Zhanran Lin, Xiaomeng Wang

Randomized experiments are a crucial tool for causal inference in many different fields. Rerandomization addresses any covariate imbalance in such experiments by resampling treatment assignments until certain balance criteria are satisfied. However, rerandomization based on na\"ive acceptance-rejection sampling is computationally inefficient, especially when

Rohan Deb, Aadirupa Saha

We consider the problem of reward maximization in the dueling bandit setup along with constraints on resource consumption. As in the classic dueling bandits, at each round the learner has to choose a pair of items from a set of $K$ items and observe a relative feedback for the current pair. Additionally, for both items, the learner also observes a vector of

Long-Bin Chen, Wen Chen, Feng Feng, Yu Jia

We investigate the next-to-next-to-leading order (NNLO) QCD radiative corrections to the pion electromagnetic form factor with large momentum transfer. We explicitly verify the validity of the collinear factorization to two-loop order for this observable, and obtain the respective IR-finite two-loop hard-scattering kernel in the closed form. The NNLO QCD cor

Jyothir S, Siddhartha Jalagam, Yann LeCun, Vlad Sobal

The enduring challenge in the field of artificial intelligence has been the control of systems to achieve desired behaviours. While for systems governed by straightforward dynamics equations, methods like Linear Quadratic Regulation (LQR) have historically proven highly effective, most real-world tasks, which require a general problem-solver, demand world mo

Shing-Chi Leung, Ken'ichi Nomoto

The spectra of several galaxies, including extremely metal-poor galaxies (EMPGs) from the EMPRESS survey, have shown that the abundances of some Si-group elements differ from "spherical" explosion models of massive stars. This leads to the speculation that these galaxies have experienced supernova explosions with high asphericity, where mixing and fallback o

Clay Cordova, Giovanni Rizi

We construct examples of non-invertible global symmetries in two-dimensional superconformal field theories described by sigma models into Calabi-Yau target spaces. Our construction provides some of the first examples of non-invertible symmetry in irrational conformal field theories. Our approach begins at a Gepner point in the conformal manifold where the si

Yuyang Yin, Dejia Xu, Zhangyang Wang, Yao Zhao

Aided by text-to-image and text-to-video diffusion models, existing 4D content creation pipelines utilize score distillation sampling to optimize the entire dynamic 3D scene. However, as these pipelines generate 4D content from text or image inputs directly, they are constrained by limited motion capabilities and depend on unreliable prompt engineering for d

Liana Heuberger, Elana Kalashnikov

We introduce a new combinatorial structure of linked tableaux, which generalize the semi-standard tableaux that index a SAGBI basis of the Pl\"ucker coordinate ring of a flag variety. We show that linked tableaux index Domokos-Zubkov semi-invariants, which span the semi-invariant ring of a quiver. The semi-invariant ring of a quiver coincides in many cases w

Sílvia Casacuberta, Cynthia Dwork, Salil Vadhan

We present connections between the recent literature on multigroup fairness for prediction algorithms and classical results in computational complexity. Multiaccurate predictors are correct in expectation on each member of an arbitrary collection of pre-specified sets. Multicalibrated predictors satisfy a stronger condition: they are calibrated on each set i

Jorge Duque Franco, Roberto Villaflor Loyola

We show, for all $n\ge 2$ even and $d\ge 2+\frac{4}{n}$, that the moduli of smooth degree $d$ hypersurfaces of $\mathbb{P}^{n+1}$ contains infinitely many different Hodge loci whose Zariski tangent space has the same codimension as the Hodge locus of linear cycles. We construct the Hodge cycles determining those Hodge loci as joins of $0$-dimensional cycles

Federica Bianchi, Enrico Bassetti, Angelo Spognardi

Cyber ranges are virtual training ranges that have emerged as indispensable environments for conducting secure exercises and simulating real or hypothetical scenarios. These complex computational infrastructures enable the simulation of attacks, facilitating the evaluation of defense tools and methodologies and developing novel countermeasures against threat

Rainer Engelken

Training recurrent neural networks (RNNs) remains a challenge due to the instability of gradients across long time horizons, which can lead to exploding and vanishing gradients. Recent research has linked these problems to the values of Lyapunov exponents for the forward-dynamics, which describe the growth or shrinkage of infinitesimal perturbations. Here, w

Priyanka Kaswan, Sennur Ulukus

As the landscape of time-sensitive applications gains prominence in 5G/6G communications, timeliness of information updates at network nodes has become crucial, which is popularly quantified in the literature by the age of information metric. However, as we devise policies to improve age of information of our systems, we inadvertently introduce a new vulnera

Henrik Johansson, Gregor Kälin, Gustav Mogull, Bram Verbeek

We obtain a color-kinematics-dual representation of the two-loop four-vector amplitude a general renormalizable massless $\mathcal{N}=1$ SYM theory, including internal matter as chiral supermultiplets. The integrand is constructed to be compatible with dimensional regularization and supersymmetry by employing two strategies (implicitly defining our regulariz

Stanley K. Jensen, Sean D. Brittain, Andrea Banzatti, Joan R. Najita

We present high-resolution spectra and spectroastrometric (SA) measurements of fundamental rovibrational CO emission from nine nearby ($\lesssim$300 pc) protoplanetary disks where large inner dust cavities have been observed. The emission line profiles and SA signals are fit with a slab disk model that allows the eccentricity of the disk and intensity of the

F. J. Matute-Cañadas, L. Tosi, A. Levy Yeyati

We explore superconducting quantum circuits where several leads are simultaneously connected beyond the tunneling regime, such that the fermionic structure of Andreev bound states in the resulting multiterminal Josephson junction influences the states of the full circuit. Using a simple model of single channel contacts and a single level in the middle region

Kyle T. Munson, Riccardo Torsi, Fatimah Habis, Lysander Huberich

Substitutionally doped transition metal dichalcogenides (TMDs) are the next step towards realizing TMD-based field effect transistors, sensors, and quantum photonic devices. Here, we report on the influence of Re concentration on charge doping and defect formation in MoS2 monolayers grown by metal-organic chemical vapor deposition. Re-MoS2 films can exhibit

Tung X. Tran, Sarah R. Geller, Benjamin V. Lehmann, David I. Kaiser

Primordial black holes (PBHs) remain a viable dark matter candidate in the asteroid-mass range. We point out that in this scenario, the PBH abundance would be large enough for at least one object to cross through the inner Solar System per decade. Since Solar System ephemerides are modeled and measured to extremely high precision, such close encounters could

Rainer Engelken

Spiking Neural Networks (SNNs) are biologically-inspired models that are capable of processing information in streams of action potentials. However, simulating and training SNNs is computationally expensive due to the need to solve large systems of coupled differential equations. In this paper, we introduce SparseProp, a novel event-based algorithm for simul

Promit Panja, Jesse B. Hoagg, Sabur Baidya

Safe operations of UAVs are of paramount importance for various mission-critical and safety-critical UAV applications. In context of airborne target tracking and following, UAVs need to track a flying target avoiding collision and also closely follow its trajectory. The safety situation becomes critical and more complex when the flying target is non-cooperat

Sang-Eon Bak, Maulik Parikh, Sudipta Sarkar, Francesco Setti

We consider a congruence of null geodesics in the presence of a quantized spacetime metric. The coupling to a quantum metric induces fluctuations in the congruence; we calculate the change in the area of a pencil of geodesics induced by such fluctuations. For the gravitational field in its vacuum state, we find that quantum gravity contributes a correction t

Eylon Persky, Alan Fang, Xinyang Zhang, Carolina Adamo

We report an extensive study of the noncentrosymmetric half-Heusler superconductor YPtBi, revealing an unusual relation between bulk superconductivity and the possible appearance of surface superconductivity on the (111) oriented surface, at temperatures up to 3 times the bulk transition temperature. Transport measurements confirmed the low carrier density o

Marco Chiodaroli, Murat Gunaydin, Henrik Johansson, Radu Roiban

Scattering amplitudes in Yang-Mills-Einstein theories have been investigated mostly for compact gauge groups. While non-compact gauge groups are not physically viable in Yang-Mills theory, non-compact gaugings feature prominently in the supergravity literature, where any choice of perturbative vacuum spontaneously breaks the gauge group to a compact subgroup

Julian Chaidez, Shira Tanny

We formulate elementary SFT spectral invariants of a large class of symplectic cobordisms and stable Hamiltonian manifolds, in any dimension. We give criteria for the strong closing property using these invariants, and verify these criteria for Hofer near periodic systems. This extends the class of symplectic dynamical systems in any dimension that satisfy t

Tim G. J. Rudner, Freddie Bickford Smith, Qixuan Feng, Yee Whye Teh

Sequential Bayesian inference over predictive functions is a natural framework for continual learning from streams of data. However, applying it to neural networks has proved challenging in practice. Addressing the drawbacks of existing techniques, we propose an optimization objective derived by formulating continual learning as sequential function-space var

I. Amro, F. Fneish, R. Kansoh, A. Sabra

We design lenses composed of a combination of standard freeform refracting surface and flat metasurface refracting an arbitrary incident field into a collimated beam with a fixed direction. In the near-field case, we study the existence of such lenses refracting a bright object into a predefined image at the target.

Dmitry Miserev, Herbert Schoeller, Jelena Klinovaja, Daniel Loss

We present an analytic theory unraveling the microscopic mechanism of instabilities within interacting $D$-dimensional Fermi liquid. Our model consists of a $D$-dimensional electron gas subject to an instantaneous electron-electron interaction of a finite range exceeding the average inter-particle distance. Pair, charge and spin susceptibilities are evaluate

Zhi-Xing Zhang, Ren-You Zhang, Zhe Li, Shu-Xiang Li

We calculate the two-loop mixed QCD$\otimes$EW corrections for the charged Higgs boson pair production within the framework of four types of Two Higgs Doublet Models (THDMs) with the $Z_2$ symmetry. We analyze in detail the dependences of our results on physical parameters, including the charged Higgs mass, $\tan\beta$, the scattering angle, and the collidin

Julia Harz, Björn Herrmann, Michael Klasen, Karol Kovařík

We present DM@NLO, a Fortran 77 based program with a C++ interface dedicated to precision calculations of dark matter (DM) (co)annihilation cross-sections and elastic dark matter-nucleon scattering amplitudes in the Minimal Supersymmetric (SUSY) Standard Model (MSSM) at next-to-leading order (NLO) in perturbative (SUSY) QCD. If the annihilating initial parti

Trung Tuan Dao, Duc Hong Vu, Cuong Pham, Anh Tran

The existing facial datasets, while having plentiful images at near frontal views, lack images with extreme head poses, leading to the downgraded performance of deep learning models when dealing with profile or pitched faces. This work aims to address this gap by introducing a novel dataset named Extreme Pose Face High-Quality Dataset (EFHQ), which includes

Yiwei Chen, Yan Huang, Qingxin Li, Bingbing Tong

The fractional quantum Hall (FQH) states are exotic quantum many-body phases whose elementary charged excitations are neither bosons nor fermions but anyons, obeying fractional braiding statistics. While most FQH states are believed to have Abelian anyons, the Moore-Read type states with even denominators, appearing at half filling of a Landau level (LL), ar

Tomohiro Abe, K. S. Babu, Ajay Kaladharan

Theories in which the dark matter (DM) candidate is a fermion transforming chirally under a gauge symmetry are attractive, as the gauge symmetry would protect the DM mass. In such theories, the universe would have undergone a phase transition at early times that generated the DM mass upon spontaneous breaking of the gauge symmetry. In this paper, we explore

Frédéric Ouimet

In this short note, we present a refined approximation for the log-ratio of the density of the von Mises$(\mu,\kappa)$ distribution (also called the circular normal distribution) to the standard (linear) normal distribution when the concentration parameter \k{appa} is large. Our work complements the one of Hill (1976), who obtained a very similar approximati

Yannick Meurice, James Corona, Sergio Cantu, Fangli Liu

We review recent suggestions to quantum simulate scalar electrodynamics (the lattice Abelian Higgs model) in $1+1$ dimensions with rectangular arrays of Rydberg atoms. We show that platforms made publicly available recently allow empirical explorations of the critical behavior of quantum simulators. We discuss recent progress regarding the phase diagram of t

Leonardo C. Mihalcea, Hiroshi Naruse, Changjian Su

We prove a Chevalley formula to multiply the motivic Chern classes of Schubert cells in a generalized flag manifold $G/P$ by the class of any line bundle $\mathcal{L}_\lambda$. Our formula is given in terms of the $\lambda$-chains of Lenart and Postnikov. Its proof relies on a change of basis formula in the affine Hecke algebra due to Ram, and on the Hecke a

Tim G. J. Rudner, Zonghao Chen, Yee Whye Teh, Yarin Gal

Reliable predictive uncertainty estimation plays an important role in enabling the deployment of neural networks to safety-critical settings. A popular approach for estimating the predictive uncertainty of neural networks is to define a prior distribution over the network parameters, infer an approximate posterior distribution, and use it to make stochastic

Athanasios Bakopoulos, Nikos Chatzifotis, Theodoros Nakas

In this work, we delve into the model of the shift symmetric and parity-preserving Beyond Horndeski theory in all its generality. We present an explicit algorithm to extract static and spherically symmetric black holes with primary scalar charge adhering to the conservation of the Noether current emanating from the shift symmetry. We show that when the funct

Nikita Pospelov, Andrei Chertkov, Maxim Beketov, Ivan Oseledets

Elements of neural networks, both biological and artificial, can be described by their selectivity for specific cognitive features. Understanding these features is important for understanding the inner workings of neural networks. For a living system, such as a neuron, whose response to a stimulus is unknown and not differentiable, the only way to reveal the

Christian Ziegler, Quinn DuPont

This note and agenda serve as a cause for thought for scholars interested in researching Decentralized Autonomous Organizations (DAOs), addressing both the opportunities and challenges posed by this phenomenon. It covers key aspects of data retrieval, data selection criteria, issues in data reliability and validity such as governance token pricing complexiti

Tianyao Fang, Zheng-Cheng Gu

The topological aspects of Einstein gravity suggest that topological invariance could be a more profound principle in understanding quantum gravity. In this work, we explore a topological supergravity action that initially describes a universe without Riemann curvature, which seems trivial. However, we made a surprising discovery by introducing a small defor

Lorenzo Di Pietro, Victor Gorbenko, Shota Komatsu

We study finite-coupling effects of QFT on a rigid de Sitter (dS) background taking the $O(N)$ vector model at large $N$ as a solvable example. Extending standard large $N$ techniques to the dS background, we analyze the phase structure and late-time four-point functions. Explicit computations reveal that the spontaneous breaking of continuous symmetries is

Dongsheng Ding, Zhengyan Huan, Alejandro Ribeiro

We study a class of constrained reinforcement learning (RL) problems in which multiple constraint specifications are not identified before training. It is challenging to identify appropriate constraint specifications due to the undefined trade-off between the reward maximization objective and the constraint satisfaction, which is ubiquitous in constrained de

Nikolay Bogachev, Khusrav Yorov

In 1974, Kaplinskaja classified all simplicial straight hyperbolic Coxeter prisms. In this paper, we determine precisely which of these prisms are properly quasi-arithmetic or arithmetic. We also present some observations regarding commensurability classes and systoles of the associated orbifolds.

Volodymyr Bavula, K. Hakami

The aim of the paper is to study the ring of differential operators $\mathcal{D}(A(m))$ on the generalized multi-cusp algebra $A(m)$ where $m\in \mathbb{N}^n$ (of Krull dimension $n$). The algebra $A(m)$ is singular apart from the single case when $m=(1, \ldots , 1)$. In this case, the algebra $A(m)$ is a polynomial algebra in $n$ variables. So, the $n$'th W

Angtian Wang, Yuanlu Xu, Nikolaos Sarafianos, Robert Maier

Neural reconstruction and rendering strategies have demonstrated state-of-the-art performances due, in part, to their ability to preserve high level shape details. Existing approaches, however, either represent objects as implicit surface functions or neural volumes and still struggle to recover shapes with heterogeneous materials, in particular human skin,

Pierre Parutto, Jennifer Heck, Martin Heine, David Holcman

Formation, maintenance and physiology of high-density protein-enriched organized nanodomains, first observed in electron microscopy images, remains challenging to investigate due to their small sizes. However, these regions regulate molecular trafficking, assembly and sorting required for higher cell functions, such as communication or plastic changes. Over

John J. McCord, Shruti Dogra, Gheorghe Sorin Paraoanu

The measurement and characterization of noise is a flourishing area of research in mesoscopic physics. In this work, we propose interaction-free measurements as a noise-detection technique, exploring two conceptually different schemes: the coherent and the projective realizations. These detectors consist of a qutrit whose second transition is resonantly coup

Vladimir K. Dubovoy, Bernd Fritzsche, Bernd Kirstein, Conrad Mädler

In [19] there is an approach to the investigation of the pseudocontinuability of Schur functions in terms of Schur parameters. In particular, there was obtained a criterion for the pseudocontinuability of Schur functions and the Schur parameters of rational Schur functions were described. This approach is based on the description in terms of the Schur parame

The NA62 Collaboration

The NA62 experiment at CERN utilises a differential Cherenkov counter with achromatic ring focus (CEDAR) for tagging kaons within an unseparated monochromatic beam of charged hadrons. The CEDAR-H detector was developed to minimise the amount of material in the path of the beam by using hydrogen gas as the radiator medium. The detector was shown to satisfy th

Rania Amairi, Adlen Smiri, Sihem Jaziri

Bandgap engineering of low-dimensional materials forms a robust basis for advancements in optoelectronic technologies. Platinum diselenide (PtSe2) material exhibits a transition from semi-metal to semiconductor (SM-SC) when going from bulk to monolayer (ML). In this work, density functional theory (DFT) with various van der Waals (vdW) corrections has been t

Gianluca Degli Esposti, Greger Torgrimsson

We show how to use a worldline-instanton formalism to calculate, to leading order in the weak-field expansion, the momentum spectrum of nonlinear Breit-Wheeler pair production in fields that depend on time and one spatial coordinate. We find a nontrivial dependence on the width, $\lambda$, of the photon wave packet, and the existence of a critical point $\la

A. Salch

At large primes, the height $n$ Ravenel-May spectral sequence takes as input the cohomology of a certain solvable Lie $\mathbb{F}_p$-algebra, and produces as output the mod $p$ cohomology of the height $n$ strict Morava stabilizer group scheme. We construct simultaneous integral deformations of the height $n$ Morava stabilizer algebras and related objects, a

Matteo Piccolini, Marcin Karczewski, Andreas Winter, Rosario Lo Franco

We propose an interferometric scheme for generating the totally antisymmetric state of $N$ identical bosons with $N$ internal levels (generalized singlet). This state is a resource for various problems with dramatic quantum advantage. The procedure uses a sequence of Fourier multi-ports, combined with coincidence measurements filtering the results. Successfu

Ziheng Zhao, Yao Zhang, Chaoyi Wu, Xiaoman Zhang

This paper aims to build a model that can Segment Anything in 3D medical images, driven by medical terminologies as Text prompts, termed as SAT. Our main contributions are three-fold: (i) We construct the first multimodal knowledge tree on human anatomy, including 6502 anatomical terminologies; Then, we build the largest and most comprehensive segmentation d

Volodymyr Bavula, A. Al Khabyah

In \cite{BigAlg-3gen}, an explicit description of bi-quadratic algebras on three generators with PBW basis was obtained. There are four classes: I-IV. The aim of the paper is to study algebras that belong to one of the classes: class II.1. In this class, there are twelve distinct subclasses to consider. The aim of the paper is to study these algebras. In par

Stefan Pillwein, Alexander Hentschel, Markus Lukacevic, Przemyslaw Musialski

Elastic geodesic grids deploy from flat to spatial configurations via complex nonlinear motion that is difficult to represent robustly for simulation. We present a geometric guidance framework that discretizes deployment as synchronized, time-coupled deformation trajectories. Starting from inverse tracing -- collapsing the deployed structure with a lightweig

Daniel Potemkin, Carlos Soto, Ruipeng Li, Kevin Yager

The extraordinarily high X-ray flux and specialized instrumentation at synchrotron beamlines have enabled versatile in-situ and high throughput studies that are impossible elsewhere. Dexterous and efficient control of experiments are thus crucial for efficient beamline operation. Artificial intelligence and machine learning methods are constantly being devel

Hnin Pann Phyu, Razvan Stanica, Diala Naboulsi, Gwenael Poitau

Network slicing is essential for transforming future telecommunication networks into versatile service platforms, but it also presents challenges for sustainable network operations. While meeting the requirements of network slices incurs additional energy consumption compared to non-sliced networks, operators strive to offer diverse 5G and beyond services wh

Marco Fazzi, Suvendu Giri, Paul Levy

This paper contains two results of independent interest, the first being more mathematical in nature whereas the second more physical. We first show that the hierarchy of Higgs branch RG flows between the 6d $(1,0)$ SCFTs known as A-type orbi-instantons is given by the Hasse diagram of certain strata and transverse slices in the double affine Grassmannian of