April 2024 arXiv papers — page 54

Maeva Guerrier, Hassan Fouad, Giovanni Beltrame

Reinforcement learning is a powerful technique for developing new robot behaviors. However, typical lack of safety guarantees constitutes a hurdle for its practical application on real robots. To address this issue, safe reinforcement learning aims to incorporate safety considerations, enabling faster transfer to real robots and facilitating lifelong learnin

Johanna Knapp, Robert Pryor

A hybrid model is a fibration of a Landau-Ginzburg orbifold over a geometric base. We study B-type D-branes in hybrid models. Imposing B-type supersymmetry on the boundary action, we show that D-branes are specified by matrix factorisations in the fibre direction, together with some geometric data associated to the base. We also deduce conditions for the com

J. C. Bellizotti Souza, N. P. Vizarim, C. J. O. Reichhardt, C. Reichhardt

We use atomistic simulations to examine the sliding dynamics of a skyrmion in a two-dimensional system containing a periodic one-dimensional stripe pattern of variations between low and high values of the perpendicular magnetic anisotropy. The skyrmion changes in size as it crosses the interface between two anisotropy regions. Upon applying combined dc and a

Quinten Mortier, Lukas Devos, Lander Burgelman, Bram Vanhecke

We show how fermionic statistics can be naturally incorporated in tensor networks on arbitrary graphs through the use of graded Hilbert spaces. This formalism allows to use tensor network methods for fermionic lattice systems in a local way, avoiding the need of a Jordan-Wigner transformation or the explicit tracking of leg crossings by swap gates in 2D tens

Paige DeVries, Nina Tran, Keith Delk, Melanie Miga

In this study, we assess the usability of interactive personal assistants (IPAs), such as Amazon Alexa, in a simulated kitchen smart home environment, with deaf and hard of hearing users. Participants engage in activities in a way that causes their hands to get dirty. With these dirty hands, they are tasked with two different input methods for IPAs: American

F. Barzi, H. El Moumni, K. Masmar

Charged-flat black holes in the R\'enyi extended phase space demonstrate phase structures akin to those of a van der Waals fluid in four-dimensional spacetime and mirror the behaviors of Reissner-Nordstrom-Anti-de-Sitter black holes within the standard Gibbs-Boltzmann extended phase space. This study delves into the dynamics of states initially positioned wi

Aditi Vijayan, Mark R. Krumholz

The molecular phase of supernova-driven outflows originates from the cold, molecular gas in the disc of a star-forming galaxy, and may carry a substantial fraction of the wind mass flux in some galaxies, but it remains poorly understood. Observations of this phase come mostly from very nearby galaxies due its low surface brightness and covering fraction, and

Yanhui Guo, Shaoyuan Xu, Jinmiao Fu, Jia Liu

This paper introduces \textbf{Q-tuning}, a novel approach for continual prompt tuning that enables the lifelong learning of a pre-trained language model. When learning a new task, Q-tuning trains a task-specific prompt by adding it to a prompt queue consisting of the prompts from older tasks. To better transfer the knowledge of old tasks, we design an adapti

Armando Zhu, Keqin Li, Tong Wu, Peng Zhao

With wearing masks becoming a new cultural norm, facial expression recognition (FER) while taking masks into account has become a significant challenge. In this paper, we propose a unified multi-branch vision transformer for facial expression recognition and mask wearing classification tasks. Our approach extracts shared features for both tasks using a dual-

Nina Tran, Paige DeVries, Matthew Seita, Raja Kushalnagar

With the recent advancements in intelligent personal assistants (IPAs), their popularity is rapidly increasing when it comes to utilizing Automatic Speech Recognition within households. In this study, we used a Wizard-of-Oz methodology to evaluate and compare the usability of American Sign Language (ASL), Tap to Alexa, and smart home apps among 23 deaf parti

Mengzhao Jia, Zhihan Zhang, Wenhao Yu, Fangkai Jiao

Open-source multimodal large language models (MLLMs) excel in various tasks involving textual and visual inputs but still struggle with complex multimodal mathematical reasoning, lagging behind proprietary models like GPT-4V(ision) and Gemini-Pro. Although fine-tuning with intermediate steps (i.e., rationales) elicits some mathematical reasoning skills, the

Christopher König, Raamadaas Krishnadas, Efe C. Balta, Alisa Rupenyan

Controller tuning and parameter optimization are crucial in system design to improve closed-loop system performance. Bayesian optimization has been established as an efficient model-free controller tuning and adaptation method. However, Bayesian optimization methods are computationally expensive and therefore difficult to use in real-time critical scenarios.

Bowen Hou, Jinyuan Wu, Diana Y. Qiu

Representation learning for the electronic structure problem is a major challenge of machine learning in computational condensed matter and materials physics. Within quantum mechanical first principles approaches, Kohn-Sham density functional theory (DFT) is the preeminent tool for understanding electronic structure, and the high-dimensional wavefunctions ca

Hansi Zeng, Chen Luo, Hamed Zamani

This paper introduces PAG-a novel optimization and decoding approach that guides autoregressive generation of document identifiers in generative retrieval models through simultaneous decoding. To this aim, PAG constructs a set-based and sequential identifier for each document. Motivated by the bag-of-words assumption in information retrieval, the set-based i

Milos Dubajic, James R. Neilson, Johan Klarbring, Xia Liang

Empirical A-site cation substitution has advanced the stability and efficiency of hybrid organic-inorganic lead halide perovskites solar cells and the functionality of X-ray detectors. Yet, the fundamental mechanisms underpinning their unique performance remain elusive. This multi-modal study unveils the link between nanoscale structural dynamics and macrosc

Lorenzo Riva

This is the first part of a project aimed at formalizing Rozansky-Witten models in the functorial field theory framework. Motivated by work of Calaque-Haugseng-Scheimbauer, we construct a family of symmetric monoidal $(\infty,3)$-categories parametrized by an $\infty$-category with finite limits and a functor into symmetric monoidal $\infty$-categories, such

Vishakha Ramani, Ivan Seskar, Roy D. Yates

This paper investigates the optimization of memory sampling in status updating systems, where source updates are published in shared memory, and reader process samples the memory for source updates by paying a sampling cost. We formulate a discrete-time decision problem to find a sampling policy that minimizes average cost comprising age at the client and th

Vestislav Apostolov, Jeffrey Streets, Yury Ustinovskiy

Building on works of Boulanger and Goto, we show that Goto's scalar curvature is the moment map for an action of generalized Hamiltonian automorphisms of the associated Courant algebroid, constrained by the choice of an adapted volume form. We derive an explicit formula for Goto's scalar curvature, and show that it is constant for generalized K\"ahler-Ricci

Ezgi Ozyilkan, Fabrizio Carpi, Siddharth Garg, Elza Erkip

The relay channel, consisting of a source-destination pair and a relay, is a fundamental component of cooperative communications. While the capacity of a general relay channel remains unknown, various relaying strategies, including compress-and-forward (CF), have been proposed. For CF, given the correlated signals at the relay and destination, distributed co

Yanze Wu, Majdi Hochlaf, George C. Schatz

Excited atomic nitrogen atoms play an important role in plasma formation in hypersonic shock-waves, as happens during spacecraft reentry and other high velocity vehicle applications. In this study, we have thoroughly studied collision induced excitation (CIE) associated with two colliding nitrogen atoms in the N(4S), N(2D) and N(2P) states at collisions ener

Allison M. Carson, Jeffrey W. Banks, William D. Henshaw, Donald W. Schwendeman

New implicit and implicit-explicit time-stepping methods for the wave equation in second-order form are described with application to two and three-dimensional problems discretized on overset grids. The implicit schemes are single step, three levels in time, and based on the modified equation approach. Second and fourth-order accurate schemes are developed a

Yuchen Hou, Laya Pullela, Jiaxin Su, Sriya Aluru

Retinal implants are a promising treatment option for degenerative retinal disease. While numerous models have been developed to simulate the appearance of elicited visual percepts ("phosphenes"), these models often either focus solely on spatial characteristics or inadequately capture the complex temporal dynamics observed in clinical trials, which vary hea

Rahul Islam, Sang Won Bae

Early detection of depressive episodes is crucial in managing mental health disorders such as Major Depressive Disorder (MDD) and Bipolar Disorder. However, existing methods often necessitate active participation or are confined to clinical settings. Addressing this gap, we introduce PupilSense, a novel, deep learning-driven mobile system designed to discree

Chintan Shah, Steffen Kühn, Sonja Bernitt, René Steinbrügge

We used the monochromatic soft-x-ray beamline P04 at the synchrotron-radiation facility PETRA III to resonantly excite the strongest $2p-3d$ transitions in neon-like Ni XIX ions, $[2p^6]_{J=0} \rightarrow [(2p^5)_{1/2}\,3d_{3/2}]_{J=1}$ and $[2p^6]_{J=0} \rightarrow [(2p^5)_{3/2}\,3d_{5/2}]_{J=1}$, respectively dubbed 3C and 3D, achieving a resolving power o

Hikmat Khan, Nidhal Carla Bouaynaya, Ghulam Rasool

Artificial intelligence (AI) and neuroscience share a rich history, with advancements in neuroscience shaping the development of AI systems capable of human-like knowledge retention. Leveraging insights from neuroscience and existing research in adversarial and continual learning, we introduce a novel framework comprising two core concepts: feature distillat

Tadashi Fujioka

We prove that the extremal stratification of an Alexandrov space introduced by Perelman-Petrunin is a CS stratification in the sense of Siebenmann. We also show that every space of directions of an Alexandrov space without proper extremal subsets is homeomorphic to a sphere. In the polyhedral case, the same holds for every iterated space of directions.

Noel Teku, Sudarshan Adiga, Ravi Tandon

In this work, the problem of communicating decisions of a classifier over a noisy channel is considered. With machine learning based models being used in variety of time-sensitive applications, transmission of these decisions in a reliable and timely manner is of significant importance. To this end, we study the scenario where a probability vector (represent

Lucas Kaufmann, Richard Lärkäng, Elizabeth Wulcan

We provide global extensions of previous results about representations of characteristic classes of coherent analytic sheaves and of Baum-Bott residues of holomorphic foliations. We show in the first case that they can be represented by currents with support on the support of the given coherent analytic sheaf, and in the second case, by currents with support

Hunter Meyer, Joyoni Dey, Sydney Carr, Kyungmin Ham

X-ray grating interferometry allows for the simultaneous acquisition of attenuation, differential-phase contrast, and dark-field images, resulting from X-ray attenuation, refraction, and small-angle scattering, respectively. The modulated phase grating (MPG) interferometer is a recently developed grating interferometry system capable of generating a directly

Saeed Azad, Ziraddin Gulumjanli, Daniel R. Herber

Integration of various electricity-generating technologies (such as natural gas, wind, nuclear, etc.) with storage systems (such as thermal, battery electric, hydrogen, etc.) has the potential to improve the economic competitiveness of modern energy systems. Driven by the need to efficiently assess the economic feasibility of various energy system configurat

Raul Quiroga-Barranco, Armando Sanchez-Nungaray

For $\mathbb{B}^n$ the $n$-dimensional unit ball and $D_n$ its Siegel unbounded realization, we consider Toeplitz operators acting on weighted Bergman spaces with symbols invariant under the actions of the maximal Abelian subgroups of biholomorphisms $\mathbb{T}^n$ (quasi-elliptic) and $\mathbb{T}^n \times \mathbb{R}_+$ (quasi-hyperbolic). Using geometric sy

Yuying Li, Zeyan Liu, Junyi Zhao, Liangqin Ren

Generative AI models can produce high-quality images based on text prompts. The generated images often appear indistinguishable from images generated by conventional optical photography devices or created by human artists (i.e., real images). While the outstanding performance of such generative models is generally well received, security concerns arise. For

Zhiyang Chen, Ye Liu, Sidi Mohamed Beillahi, Yi Li

Smart contract transactions associated with security attacks often exhibit distinct behavioral patterns compared with historical benign transactions before the attacking events. While many runtime monitoring and guarding mechanisms have been proposed to validate invariants and stop anomalous transactions on the fly, the empirical effectiveness of the invaria

Iurii Karpenko, Alexander Lind, Martin Rohrmoser, Joerg Aichelin

We present a new model for jet quenching in a quark gluon plasma (QGP). The jet energy loss has two steps. The initial jet parton with a high virtuality loses energy by a perturbative vacuum parton shower modified by medium interactions until it becomes on shell. Subsequent energy loss originates from elastic and radiative collisions with the medium constitu

Jay Patwardhan, Zheheng Xiao

Generalizing prior work of Levine, we give infinitely many examples of pattern knots P such that P(K) is not slice in any rational homology 4-ball, for any companion knot K. To show this, we establish a closed formula for the concordance invariants tau and epsilon of a family of satellite knots obtained from generalized Mazur patterns. Our main computational

Soumyajit Sarkar, K. Murali, Hari M. Varma

We introduce a novel method to design and implement a tunable dynamical tissue phantom for laser speckle-based in-vivo blood flow imaging. This approach relies on Stochastic Differential Equations (SDE) to control a piezoelectric actuator which, upon illuminated with a laser source, generates speckles of pre-defined probability density function and auto-corr

Daria O. Ignatyeva, Nikolay A. Gusev, Anatoly K. Zvezdin, Vladimir I. Belotelov

We report a theoretical study of the phase diagram of a ferrimagnetic iron-garnet with uniaxial anisotropy near a magnetization compensation point in the presence of a two-component magnetic field. The study is performed based on a quasi-antiferromagnetic approximation. The number and stability of the equilibrium states of the Neel vector are analyzed using

Richard Stromer, Oskar Triebe, Chad Zanocco, Ram Rajagopal

Forecasts inform decision-making in nearly every domain. Forecasts are often produced by experts with rare or hard to acquire skills. In practice, forecasts are often used by domain experts and managers with little forecasting expertise. Our study focuses on how to design forecasting software that empowers non-expert users. We study how users can make use of

Giuseppe Bevilacqua, Valerio Biancalana, Yordanka Dancheva, Alessandro Fregosi

We introduce a methodology to calibrate in situ a set of coils generating bi- or tri-axial magnetic fields, at frequencies where a calibration performed under static conditions would be inaccurate. The methodology uses harmonic analysis of one component of the magnetization of an atomic sample whose spins adiabatically follow an ad hoc applied time-dependent

Haopeng Wang, Haiwei Dong, Abdulmotaleb El Saddik

A key challenge of 360$^\circ$ VR video streaming is ensuring high quality with limited network bandwidth. Currently, most studies focus on tile-based adaptive bitrate streaming to reduce bandwidth consumption, where resources in network nodes are not fully utilized. This article proposes a tile-weighted rate-distortion (TWRD) packet scheduling optimization

Jean-Christophe Pain

We present two integral representations of the logarithm of the Glaisher-Kinkelin constant. Both are based on a definite integral of $\ln[\Gamma(x + 1)]$, $\Gamma$ being the usual Gamma function. The first one relies on an integral representation of $\ln[\Gamma(x + 1)]$ due to Binet, and the second one results from the so-called Malmst\'en formula. The numer

Xiaodong Zhang

This paper explores the lowest data resolution at which the partial structure R1 (pR1) method can determine a small-molecule crystal structure. Three specific structures have been studied. For a structure having 4 S atoms out of total 32 atoms in its unit cell, the lowest structure-solvable resolution is 1.5 A, and at this resolution all the atoms are indivi

Ke Li

Decomposition has been the mainstream approach in classic mathematical programming for multi-objective optimization and multi-criterion decision-making. However, it was not properly studied in the context of evolutionary multi-objective optimization (EMO) until the development of multi-objective evolutionary algorithm based on decomposition (MOEA/D). In this

Wenxuan Jia, Victoria Xu, Kevin Kuns, Masayuki Nakano

Precision measurements of space and time, like those made by the detectors of the Laser Interferometer Gravitational-wave Observatory (LIGO), are often confronted with fundamental limitations imposed by quantum mechanics. The Heisenberg uncertainty principle dictates that the position and momentum of an object cannot both be precisely measured, giving rise t

Weijie Wang, Jichao Zhang, Chang Liu, Xia Li

Recently, diffusion models have made significant strides in synthesizing realistic 2D human images based on provided text prompts. Building upon this, researchers have extended 2D text-to-image diffusion models into the 3D domain for generating human textures (UV Maps). However, some important problems about UV Map Generative models are still not solved, i.e

Ronald Xie, Steven Palayew, Augustin Toma, Gary Bader

This paper outlines our submission to the MEDIQA2024 Multilingual and Multimodal Medical Answer Generation (M3G) shared task. We report results for two standalone solutions under the English category of the task, the first involving two consecutive API calls to the Claude 3 Opus API and the second involving training an image-disease label joint embedding in

Haixuan Huang, Tatiana de Picoli, Jukka I. Väyrynen

The superconducting diode effect -- the dependence of critical current on its direction -- can arise from the simultaneous breaking of inversion and time-reversal symmetry in a superconductor and has gained interest for its potential applications in superconducting electronics. In this letter, we study the effect in a two-dimensional topological insulator (2

Jiaqi Chen, Daniel Barath, Iro Armeni, Marc Pollefeys

Natural language interfaces to embodied AI are becoming more ubiquitous in our daily lives. This opens up further opportunities for language-based interaction with embodied agents, such as a user verbally instructing an agent to execute some task in a specific location. For example, "put the bowls back in the cupboard next to the fridge" or "meet me at the i

H. Backe, W. Lauth, P. Klag, Thu Nhi Tran Caliste

A 4-period diamond undulator with a thickness of 20 $\mu$m was produced with the method of Chemical Vapour Deposition (CVD), applying boron doping, on a straight diamond crystal with an effective thickness of 165.5 $\mu$m. A planar (110) channeling experiment was performed with the 855 MeV electron beam of the Mainz Microtron MAMI accelerator facility to obs

Arthur N. dos Santos, Bruno S. Masiero, Túlio C. L. Mateus

One key aspect differentiating data-driven single- and multi-channel speech enhancement and dereverberation methods is that both the problem formulation and complexity of the solutions are considerably more challenging in the latter case. Additionally, with limited computational resources, it is cumbersome to train models that require the management of large

Tongze Zhang, Tammy Chung, Anind Dey, Sang Won Bae

This study explores the possibility of facilitating algorithmic decision-making by combining interpretable artificial intelligence (XAI) techniques with sensor data, with the aim of providing researchers and clinicians with personalized analyses of cannabis intoxication behavior. SHAP analyzes the importance and quantifies the impact of specific factors such

Klaus Kirsten, Yoonweon Lee

On a compact Riemannian manifold $M$ with boundary $Y$, we express the log of the zeta-determinant of the Dirichlet-to-Neumann operator acting on $q$-forms on $Y$ as the difference of the log of the zeta-determinant of the Laplacian on $q$-forms on $M$ with absolute boundary conditions and that of the Laplacian with Dirichlet boundary conditions with some ad

J Green, Eve Emmanouilidou, Harry W. T. Morgan, William T. Laderer

Compared to time-reversal symmetry-protected Z2 topological insulators and Dirac/Weyl semimetals, there are significantly fewer candidates for topological crystalline insulators. SrAg4Sb2 is predicted to exhibit topological crystalline insulator behavior when considering spin-orbit coupling. In this study, we systematically investigate single crystals of SrA

Tahmim Hossain, Faisal Sayed, Solehin Islam

The shortage of nephrologists and the growing public health concern over renal failure have spurred the demand for AI systems capable of autonomously detecting kidney abnormalities. Renal failure, marked by a gradual decline in kidney function, can result from factors like cysts, stones, and tumors. Chronic kidney disease may go unnoticed initially, leading

David M. Malaspina, Robert E. Ergun, Iver H. Cairns, Benjamin Short

This work reports a novel plasma wave observation in the near-Sun solar wind: frequency-dispersed ion acoustic waves. Similar waves were previously reported in association with interplanetary shocks or planetary bow shocks, but the waves reported here occur throughout the solar wind sunward of $\sim 60$ solar radii, far from any identified shocks. The waves

Galina Nemova

The optical forces applied to a rare-earth doped optical dimer made of identical Yb3+:YAG nanospheres placed in the plane electromagnetic field propagating in vacuum has been theoretically considered. The electromagnetic fields at wavelengths 968 nm and 1030 nm have been normally and axially directed to the dimer axis. Wavelengths 968 nm and 1030 nm are reso

Dheeraj Tripathi, Chandan Bose, Sirshendu Mondal, J Venkatramani

This study focuses on discerning the role of structural parameters on the bifurcation characteristics and the underlying synchronization mechanism in an aeroelastic system undergoing nonlinear stall behaviour. To that end, wind tunnel experiments are performed on a NACA 0012 airfoil capable of undergoing bending (plunging) and torsional (pitching) oscillatio

Rubí E. Rodríguez, Anita M. Rojas

We give an effective procedure to explicitly find the decomposition of a polarized abelian variety into its simple factors if a period matrix is known. Since finding this datum is not easy, we also provide two methods to compute the period matrix for a polarized abelian variety, depending on the given geometric information about it. These results work partic

Duong Thuy Anh Nguyen, Mattia Bianchi, Florian Dörfler, Duong Tung Nguyen

Motivated by the complex dynamics of cooperative and competitive interactions within networked agent systems, multi-cluster games provide a framework for modeling the interconnected goals of self-interested clusters of agents. For this setup, the existing literature lacks comprehensive gradient-based solutions that simultaneously consider constraint sets and

Mohammad Amirabbasi, Peter Kratzer

The two-dimensional van der Waals (vdW) materials MPS_3(M = Mn, Fe, Co, Ni) display antiferromagnetic ordering of the magnetic moments at the transition metal ions. The possibility to exfoliate thin layers that preserve the magnetic order makes these materials interesting for numerous applications in devices that require integration of flexible patches of ma

Lili Wu, Ben Evans, Riashat Islam, Raihan Seraj

Discovering an informative, or agent-centric, state representation that encodes only the relevant information while discarding the irrelevant is a key challenge towards scaling reinforcement learning algorithms and efficiently applying them to downstream tasks. Prior works studied this problem in high-dimensional Markovian environments, when the current obse

V. Niarchos, C. Papageorgakis

We use Fourier Neural Operators (FNOs) to study the relation between the modulus and phase of amplitudes in $2\to 2$ elastic scattering at fixed energies. Unlike previous approaches, we do not employ the integral relation imposed by unitarity, but instead train FNOs to discover it from many samples of amplitudes with finite partial wave expansions. When trai

Érico Goulart, Eduardo Bittencourt

We demonstrate the existence of photon traps within the framework of nonlinear electrodynamics. The trapping mechanism is based on the fact that, for null background fields, the optical metric reduces to the Kerr-Schild form, which plays a prominent role in the context of black hole physics. We then construct explicit examples where photons are confined in a

Roman Fedorov, Alexander Soibelman, Yan Soibelman

Let $X$ be a smooth projective curve over a field of characteristic zero and let $\mathcal D$ be an effective divisor on $X$. We calculate motivic classes of various moduli stacks of parabolic vector bundles with irregular connections on $X$ and of irregular parabolic Higgs bundles on $X$ with poles bounded by $\mathcal D$ and with fully or partially fixed f

Sachin R. Pendse, Logan Stapleton, Neha Kumar, Munmun De Choudhury

The field of digital mental health is advancing at a rapid pace. Passively collected data from user engagements with digital tools and services continue to contribute new insights into mental health and illness. As the field of digital mental health grows, a concerning norm has been established -- digital service users are given little say over how their dat

Mohammed Abugurain, Shinkyu Park

This paper presents a framework that can interpret humans' navigation commands containing temporal elements and directly translate their natural language instructions into robot motion planning. Central to our framework is utilizing Large Language Models (LLMs). To enhance the reliability of LLMs in the framework and improve user experience, we propose metho

Jingxing Qian, Siqi Zhou, Nicholas Jianrui Ren, Veronica Chatrath

Autonomous robots navigating in changing environments demand adaptive navigation strategies for safe long-term operation. While many modern control paradigms offer theoretical guarantees, they often assume known extrinsic safety constraints, overlooking challenges when deployed in real-world environments where objects can appear, disappear, and shift over ti

Yohei Ema, Marcos A. G. Garcia, Wenqi Ke, Keith A. Olive

We consider the decay of the inflaton in Starobinsky-like models arising from either an $R+R^2$ theory of gravity or $N=1$ no-scale supergravity models. If Standard Model matter is simply introduced to the $R + R^2$ theory, the inflaton (which appears when the theory is conformally transformed to the Einstein frame) couples to matter predominantly in Standar

Augustin Toma, Ronald Xie, Steven Palayew, Patrick R. Lawler

Medical errors in clinical text pose significant risks to patient safety. The MEDIQA-CORR 2024 shared task focuses on detecting and correcting these errors across three subtasks: identifying the presence of an error, extracting the erroneous sentence, and generating a corrected sentence. In this paper, we present our approach that achieved top performance in

Jason Holmes, Hongying Feng, Lian Zhang, Michael Fix

This article examines the critical role of fast Monte Carlo dose calculations in advancing proton therapy techniques, particularly in the context of increasing treatment customization and precision. As adaptive radiotherapy and other patient-specific approaches evolve, the need for accurate and precise dose calculations, essential for techniques like proton-

Yaofeng Xie, Lingwei Kong, Kai Chen, Ziqiang Zheng

Learning-based underwater image enhancement (UIE) methods have made great progress. However, the lack of large-scale and high-quality paired training samples has become the main bottleneck hindering the development of UIE. The inter-frame information in underwater videos can accelerate or optimize the UIE process. Thus, we constructed the first large-scale h

Simon Chiche, Chao Zhang, Felix Schlüter, Kumiko Kotera

Next-generation radio experiments such as the Radio Detector of the upgraded Pierre Auger Observatory and the planned GRAND and BEACON arrays target the detection of ultra-high-energy particle air showers arriving at low elevation angles. These inclined cosmic-ray air showers develop higher in the atmosphere than vertical ones, enhancing magnetic deflections

Leonard C. Nielsen, Torne Tänzer, Irene Rodriguez-Fernandez, Paul Erhart

Small-angle scattering tensor tomography is a technique for studying anisotropic nanostructures of millimeter-sized samples in a volume-resolved manner. It requires the acquisition of data through repeated tomographic rotations about an axis which is subjected to a series of tilts. The tilt that can be achieved with a typical setup is geometrically constrain

Benjamin Gess, Kihoon Seong, Pavlos Tsatsoulis

We study asymptotic expansions of the Euclidean $\Phi^4_2$-measure in the low-temperature regime. In particular, this extends the asymptotic expansions of Gaussian function space integrals developed in Schilder (1966) and Ellis and Rosen (1982) to the singular setting, where the field is no longer a function, but just a distribution. As a consequence, we ded

Amirreza Hashemi, Sayantan Dutta, Bertrand Georgeot, Denis Kouame

Background noise in many fields such as medical imaging poses significant challenges for accurate diagnosis, prompting the development of denoising algorithms. Traditional methodologies, however, often struggle to address the complexities of noisy environments in high dimensional imaging systems. This paper introduces a novel quantum-inspired approach for im

Jinkang Guo, Oliver Hart, Chi-Fang Chen, Aaron J. Friedman

We provide a systematic framework for constructing generic models of nonequilibrium quantum dynamics with a target stationary (mixed) state. Our framework identifies (almost) all combinations of Hamiltonian and dissipative dynamics that relax to a steady state of interest, generalizing the Davies' generator for dissipative relaxation at finite temperature to

Henrik Holm, Peter Jorgensen

Injective resolutions of modules are key objects of homological algebra, which are used for the computation of derived functors. Semiinjective resolutions of chain complexes are more general objects, which are used for the computation of $\operatorname{Hom}$ spaces in the derived category $\mathscr{D}( A )$ of a ring $A$. Minimal semiinjective resolutions ha

Nils Siemonsen

We perform the first nonlinear and self-consistent study of the merger and ringdown of a black hole mimicking object with stable light rings. To that end, we numerically solve the full Einstein-Klein-Gordon equations governing the head-on collisions of a series of binary boson stars in the large-mass-ratio regime resulting in spinning horizonless remnants wi

Yurii Demydenko, Taras Vasiliev, Khrystyna O. Levchenko, Andrii V. Chumak

Brillouin light scattering (BLS) spectroscopy is a powerful tool for detecting spin waves in magnetic thin films and nanostructures. Despite comprehensive access to spin-wave properties, BLS spectroscopy suffers from the limited wavenumber of detectable spin waves and the typically relatively low sensitivity. In this work, we present the results of numerical

Shahab Jolani, Stef van Buuren

Imputation methods for dealing with incomplete data typically assume that the missingness mechanism is at random (MAR). These methods can also be applied to missing not at random (MNAR) situations, where the user specifies some adjustment parameters that describe the degree of departure from MAR. The effect of different pre-chosen values is then studied on t

Cyprien Arnold, Philippe Jouvet, Lama Seoud

Thermal imaging plays a crucial role in various applications, but the inherent low resolution of commonly available infrared (IR) cameras limits its effectiveness. Conventional super-resolution (SR) methods often struggle with thermal images due to their lack of high-frequency details. Guided SR leverages information from a high-resolution image, typically i

Piotr Błaszkiewicz, Piotr Kowalski

We show that the class of Krasner hyperfields is not elementary. To show this, we determine the rational rank of quotients of multiplicative groups in field extensions. Our argument uses Chebotarev's density theorem. We also discuss some related questions.

Dániel Nagy, Peter Reinholdt, Phillip W. K. Jensen, Erik Rosendahl Kjellgren

We test the performance of the Polarizable Embedding Variational Quantum Eigensolver Self-Consistent-Field (PE-VQE-SCF) model for computing electric field gradients with comparisons to conventional complete active space self-consistent-field (CASSCF) calculations and experimental results. We compute quadrupole coupling constants for ice VIII and ice IX. We f

Michele Bertoldo-Coêlho, Rogério Riffel, Marina Trevisan, Natacha Zanon Dametto

Most of the observed galaxies cannot be resolved into individual stars and are studied through their integrated spectrum using simple stellar populations (SSPs) models, with stellar libraries being a key ingredient in building them. Spectroscopic observations are increasingly being directed towards the near-infrared (NIR), where much is yet to be explored. S

Arthur G. Suvorov, Hao-Jui Kuan, Alexis Reboul-Salze, Kostas D. Kokkotas

Tidal resonances in the final seconds of a binary neutron-star inspiral can excite oscillation modes in one or both of the constituents to large amplitudes. Under favorable circumstances, resonant pulsations can overstrain the stellar crust and unleash a torrent of magnetoelastic energy that manifests as a gamma-ray ``precursor flare.'' We show that for real

Valeri Lozovski, Andrii V. Chumak

Brillouin light scattering (BLS) spectroscopy is an effective method for detecting spin waves in magnetic thin films and nanostructures. While it provides extensive insight into the properties of spin waves, BLS spectroscopy is impeded in many practical cases by the limited range of detectable spin wave wavenumbers and its low sensitivity. Here, we present a

Tyler Griggs, Xiaoxuan Liu, Jiaxiang Yu, Doyoung Kim

Large language models (LLMs) are increasingly integrated into many online services, yet they remain cost-prohibitive to deploy due to the requirement of expensive GPU instances. Prior work has addressed the high cost of LLM serving by improving the inference engine, but less attention has been given to selecting the most cost-efficient GPU type(s) for a spec

Ian Descamps, Sophia Jeon, N. G. Holmes, Rachel E. Scherr

In introductory physics laboratory instruction, students often expect to confirm or demonstrate textbook physics concepts (Wilcox & Lewandowski, 2017; Hu & Zwickl, 2017; Hu & Zwickl, 2018). This expectation is largely undesirable: labs that emphasize confirmation of textbook physics concepts are unsuccessful at teaching those concepts (Wieman & Holmes, 2015;

Jack Holligan, Huey-Wen Lin

We present a state-of-the-art calculation of the unpolarized pion valence-quark distribution in the framework of large-momentum effective theory (LaMET) with improved handling of systematic errors as well as two-loop perturbative matching. We use lattice ensembles generated by the MILC collaboration at lattice spacing $a\approx 0.09$~fm, lattice volume $64^3

Ya-Chi Chu, Luiz-Rafael Santos, Madeleine Udell

We present a new algorithm for convex separable quadratic programming (QP) called Nys-IP-PMM, a regularized interior-point solver that uses low-rank structure to accelerate solution of the Newton system. The algorithm combines the interior point proximal method of multipliers (IP-PMM) with the randomized Nystr\"om preconditioned conjugate gradient method as

Dinesh Cyril Selvaraj, Christian Vitale, Tania Panayiotou, Panayiotis Kolios

Intersection crossing represents one of the most dangerous sections of the road infrastructure and Connected Vehicles (CVs) can serve as a revolutionary solution to the problem. In this work, we present a novel framework that detects preemptively collisions at urban crossroads, exploiting the Multi-access Edge Computing (MEC) platform of 5G networks. At the

Mohan Dantam, Richard Mayr

We consider finite-state Markov decision processes with the combined Energy-MeanPayoff objective. The controller tries to avoid running out of energy while simultaneously attaining a strictly positive mean payoff in a second dimension. We show that finite memory suffices for almost surely winning strategies for the Energy-MeanPayoff objective. This is in con

Sunwoo Ha, Shayan Monadjemi, Alvitta Ottley

The increasing integration of artificial intelligence (AI) in visual analytics (VA) tools raises vital questions about the behavior of users, their trust, and the potential of induced biases when provided with guidance during data exploration. We present an experiment where participants engaged in a visual data exploration task while receiving intelligent su

Arnas Volčokas, Justin Ball, Stephan Brunner

Using local nonlinear gyrokinetic simulations, we demonstrate that turbulent eddies can extend along magnetic field lines for hundreds of poloidal turns in tokamaks with weak or zero magnetic shear $\hat{s}$. We observe that this parallel eddy length scales inversely with magnetic shear and at $\hat{s}=0$ is limited by the thermal speed of electrons $v_{th,e

MIT Hardness Group, Della Hendrickson, Andy Tockman

We study three problems related to the computational complexity of the popular game Minesweeper. The first is consistency: given a set of clues, is there any arrangement of mines that satisfies it? This problem has been known to be NP-complete since 2000, but our framework proves it as a side effect. The second is inference: given a set of clues, is there an

Tomas Brauner

This is a preprint of an open-access book published by Springer Cham. The book gives an up-to-date overview of the physics of spontaneously broken continuous symmetry from the point of view of effective field theory. Upon building up the necessary foundations, the text reviews the classification of Nambu-Goldstone bosons and then focuses on the construction

Julien Grange, Mathieu Lehaut

We study the reactive synthesis problem for distributed systems with an unbounded number of participants interacting with an uncontrollable environment. Executions of those systems are modeled by data words, and specifications are given as first-order logic formulas from a fragment we call prefix first-order logic that implements a limited kind of order. We

Andrés A. Plazas Malagón, Chris Waters, Alex Broughton, Eli Rykoff

The Vera C. Rubin Legacy Survey of Space and Time (LSST) will conduct an unprecedented optical survey of the southern sky, imaging the entire available sky every few nights for 10 years. To achieve its ambitious science goals of probing dark energy and dark matter, mapping the Milky Way, and exploring the transient optical sky, the systematic errors in the L

Yiming Wang, Shouvik Sur, Chandan Setty, Douglas Natelson

The nature of charge carriers in strange metals has become a topic of intense current investigation. Recent shot noise measurements in the quantum critical heavy fermion metal YbRh$_2$Si$_2$ revealed a suppression of the Fano factor that cannot be understood from electron-phonon scattering or strong electron correlations in a Fermi liquid, indicating loss of

Kaitao Meng, Christos Masouros, Athina P. Petropulu, Lajos Hanzo

Integrated sensing and communication (ISAC) networks are investigated with the objective of effectively balancing the sensing and communication (S&C) performance at the network level. Through the simultaneous utilization of multi-point (CoMP) coordinated joint transmission and distributed multiple-input multiple-output (MIMO) radar techniques, we propose an