July 2023 arXiv papers — page 121

Valerio Bertacchi

The Belle II experiment at the SuperKEKB energy-asymmetric electron-positron collider is a substantial upgrade of the B factory facility at the Japanese KEK laboratory. Belle II collected a sample of $362~\mathrm{fb}^{-1}$ at the $\Upsilon(4S)$ resonance between 2019 and 2022, with a maximum peak luminosity of $4.7 \times 10^{34} \mathrm{cm}^{-2}s^{-1}$. Bel

Xiaotong Ji, Antonio Filieri

Safe exploration aims at addressing the limitations of Reinforcement Learning (RL) in safety-critical scenarios, where failures during trial-and-error learning may incur high costs. Several methods exist to incorporate external knowledge or to use proximal sensor data to limit the exploration of unsafe states. However, reducing exploration risks in unknown e

N. Anugu, F. Baron, D. R. Gies, C. Lanthermann

The cool hypergiant star RW Cephei is currently in a deep photometric minimum that began several years ago. This event bears a strong similarity to the Great Dimming of the red supergiant Betelgeuse that occurred in 2019-2020. We present the first resolved images of RW Cephei that we obtained with the CHARA Array interferometer. The angular diameter and Gaia

Corto Mascle, Anca Muscholl, Igor Walukiewicz

In parametric lock-sharing systems processes can spawn new processes to run in parallel, and can create new locks. The behavior of every process is given by a pushdown automaton. We consider infinite behaviors of such systems under strong process fairness condition. A result of a potentially infinite execution of a system is a limit configuration, that is a

Atul Ingle, David Maier

Single-photon cameras (SPCs) have emerged as a promising technology for high-resolution 3D imaging. A single-photon 3D camera determines the round-trip time of a laser pulse by capturing the arrival of individual photons at each camera pixel. Constructing photon-timestamp histograms is a fundamental operation for a single-photon 3D camera. However, in-pixel

Kianté Brantley, Zhichong Fang, Sarah Dean, Thorsten Joachims

The feedback that users provide through their choices (e.g., clicks, purchases) is one of the most common types of data readily available for training search and recommendation algorithms. However, myopically training systems based on choice data may only improve short-term engagement, but not the long-term sustainability of the platform and the long-term be

Nikhil Kotibhaskar, Chung-You Shih, Sainath Motlakunta, Anthony Vogliano

We propose and experimentally demonstrate an analog scheme for generating XY-type ($J_{ij}^x \sigma_x^i \sigma_x^j \;$ + $J_{ij}^y \sigma_y^i \sigma_y^j \;$) Hamiltonians on trapped ion spins with independent control over the $J_{ij}^x$ and $J_{ij}^y$ terms. The Ising-type interactions $\sigma_x^i \sigma_x^j \;$ and $\sigma_y^i \sigma_y^j \;$ are simultaneou

William Kong, Andrés Muñoz Medina, Mónica Ribero, Umar Syed

New regulations and increased awareness of data privacy have led to the deployment of new and more efficient differentially private mechanisms across public institutions and industries. Ensuring the correctness of these mechanisms is therefore crucial to ensure the proper protection of data. However, since differential privacy is a property of the mechanism

Cheongho Han, Youn Kil Jung, Ian A. Bond, Sun-Ju Chung

As a part of the project aiming to build a homogeneous sample of binary-lens (2L1S) events containing brown-dwarf (BD) companions, we investigate the 2021 season microlensing data collected by the Korea Microlensing Telescope Network (KMTNet) survey. For this purpose, we first identify 2L1S events by conducting systematic analyses of anomalous lensing events

Robin Vacus, Amos Korman

In group foraging situations, the conventional expectation is that increased food availability would enhance consumption, especially when animals prioritize maximizing their food intake. This paper challenges this conventional wisdom by conducting an in-depth game-theoretic analysis of a basic producer-scrounger model, in which animals must choose between in

Sudip Chakravarty

In this note I apply a theorem of Kohn to quantum oscillations in cuprates. I show that when combined with Gell-Mann and Low theorem, there is rigorous justification of quantum oscillations as in a Fermi liquid for cuprates. The Gell-Man-Low theorem is not perturbative, and applies more generally as long as the adiabatic evolution from an isolated non-degene

Riccardo Parosi, Mattia Risiglione, Darwin G. Caldwell, Claudio Semini

We propose a control pipeline for SAG (Searching, Approaching, and Grasping) of objects, based on a decoupled arm kinematic chain and impedance control, which integrates image-based visual servoing (IBVS). The kinematic decoupling allows for fast end-effector motions and recovery that leads to robust visual servoing. The whole approach and pipeline can be ge

Gal Shtendel, Dorian Florescu, Ayush Bhandari

Bandpass signals are an important sub-class of bandlimited signals that naturally arise in a number of application areas but their high-frequency content poses an acquisition challenge. Consequently, "Bandpass Sampling Theory" has been investigated and applied in the literature. In this paper, we consider the problem of modulo sampling of bandpass signals wi

Gabor Fodor, Marcos V. Conde

Deforestation estimation and fire detection in the Amazon forest poses a significant challenge due to the vast size of the area and the limited accessibility. However, these are crucial problems that lead to severe environmental consequences, including climate change, global warming, and biodiversity loss. To effectively address this problem, multimodal sate

Lee-Peng Teo

This is the first volume of a textbook for a two-semester course in mathematical analysis. This first volume is about analysis of functions of a single variable. The topics covered include completeness axiom, Archimedean property, sequentially compact subsets of $\mathbb{R}$, limits of functions, continuous functions, intermediate value theorem, extreme valu

Jiepeng Tang, Navneet Agrawal, Slawomir Stanczak, Jingge Zhu

In this paper, we present a coded computation (CC) scheme for distributed computation of the inference phase of machine learning (ML) tasks, specifically, the task of image classification. Building upon Agrawal et al.~2022, the proposed scheme combines the strengths of deep learning and Lagrange interpolation technique to mitigate the effect of straggling wo

Joao V. B. da Silva, Gabriel H. S. Aguiar, George E. A. Matsas

The main goal of this brief report is to provide some new insight into how promising the Schroedinger-Newton equation would be to explain the emergence of classicality. Based on the similarity of the Newton and Coulomb potentials, we add an electric self-interacting term to the Schroedinger-Newton equation for the hydrogen atom. Our results rule out the poss

Navneet Agrawal, Renato L. G. Cavalcante, Masahiro Yukawa, Slawomir Stanczak

This paper presents a decentralized algorithm for solving distributed convex optimization problems in dynamic networks with time-varying objectives. The unique feature of the algorithm lies in its ability to accommodate a wide range of communication systems, including previously unsupported ones, by abstractly modeling the information exchange in the network

Erdi Kara, T. L. Jackson, Chartese Jones, Reginald L. McGee

As an adoptive cellular therapy, Chimeric Antigen Receptor T-cell (CAR T-cell) therapy has shown remarkable success in hematological malignancies, but only limited efficacy against solid tumors. Compared with blood cancers, solid tumors present a unique set of challenges that ultimately neutralize the function of CAR T-cells. One such barrier is antigen hete

Brad Emmons, Xiao Xiao

The arithmetic derivative is a function from the natural numbers to itself that sends all prime numbers to $1$ and satisfies the Leibniz rule. The arithmetic partial derivative with respect to a prime $p$ is the $p$-th component of the arithmetic derivative. In this paper, we generalize the arithmetic partial derivative to $p$-adic fields (the local case) an

Weida Hu, Crystal L. Martin, Max Gronke, Simon Gazagnes

Lyman-alpha line profiles are a powerful probe of ISM structure, outflow speed, and Lyman continuum escape fraction. In this paper, we present the Ly$\alpha$ line profiles of the COS Legacy Archive Spectroscopic SurveY, a sample rich in spectroscopic analogs of reionization-era galaxies. A large fraction of the spectra show a complex profile, consisting of a

Troy Zada, Natalie Tam, Francois Barnard, Marlize Van Sittert

Rapid integration of large language models (LLMs) in health care is sparking global discussion about their potential to revolutionize health care quality and accessibility. At a time when improving health care quality and access remains a critical concern for countries worldwide, the ability of these models to pass medical examinations is often cited as a re

Andreas Bock, Colin J. Cotter, Robert C. Kirby

We study parameterisation-independent closed planar curve matching as a Bayesian inverse problem. The motion of the curve is modelled via a curve on the diffeomorphism group acting on the ambient space, leading to a large deformation diffeomorphic metric mapping (LDDMM) functional penalising the kinetic energy of the deformation. We solve Hamilton's equation

Siu Hang Man

We establish an upper bound on the number of real multiquadratic fields that admit a universal quadratic lattice of a given rank, or contain a given amount of indecomposable elements modulo totally positive units, obtaining density zero statements. We also study the structure of indecomposable elements in real biquadratic fields, and compute a system of inde

Gangwoo Kim, Hajung Kim, Lei Ji, Seongsu Bae

In this paper, we introduce CheXOFA, a new pre-trained vision-language model (VLM) for the chest X-ray domain. Our model is initially pre-trained on various multimodal datasets within the general domain before being transferred to the chest X-ray domain. Following a prominent VLM, we unify various domain-specific tasks into a simple sequence-to-sequence sche

Bhathiya Hemanthage, Christian Dondrup, Phil Bartie, Oliver Lemon

SimpleMTOD is a simple language model which recasts several sub-tasks in multimodal task-oriented dialogues as sequence prediction tasks. SimpleMTOD is built on a large-scale transformer-based auto-regressive architecture, which has already proven to be successful in uni-modal task-oriented dialogues, and effectively leverages transfer learning from pre-trai

J. Gomez-Enri, C. Gonzalez, M. Passaro, S. Vignudelli

In this work, we retracked altimeter waveforms of ESA satellites. ERS2 RA and Envisat RA2 from descending track 0360 over the eastern side of the Strait of Gibraltar using the Adaptive Leading Edge Subwaveform ALES retracker.

Ahmet Okutan, Ali Shokri, Viktoria Koscinski, Mohamad Fazelinia

Secure by Design has become the mainstream development approach ensuring that software systems are not vulnerable to cyberattacks. Architectural security controls need to be carefully monitored over the software development life cycle to avoid critical design flaws. Unfortunately, functional requirements usually get in the way of the security features, and t

S C Tiwari

The proposition that photon is a topological object (J. Math. Phys. 49, 032303, 2008) is given rigorous foundation based on pure vector field theory independent of the electromagnetic fields. Holomorphy of 4-dimensional space-time and the nature of topological obstructions are investigated to articulate singular vortex model for photon. The utility of the Eu

Xuechen Zhang, Mingchen Li, Xiangyu Chang, Jiasi Chen

The growth and diversity of machine learning applications motivate a rethinking of learning with mobile and edge devices. How can we address diverse client goals and learn with scarce heterogeneous data? While federated learning aims to address these issues, it has challenges hindering a unified solution. Large transformer models have been shown to work acro

Volkan Kumtepeli, Rebecca Perriment, David A. Howey

We present an approach for computationally efficient dynamic time warping (DTW) and clustering of time-series data. The method frames the dynamic warping of time series datasets as an optimisation problem solved using dynamic programming, and then clusters time series data by solving a second optimisation problem using mixed-integer programming (MIP). There

Thomas J. Maldonado, Dung N. Pham, Alessio Amaolo, Alejandro W. Rodriguez

By applying a hydrodynamic representation of non-relativistic scalar electrodynamics to the superconducting order parameter, we predict a negative (attractive) pressure between planar superconducting bodies. For conventional superconductors with London penetration depth $\lambda_\text{L} \approx 100 \text{ nm}$, the pressure reaches tens of $\text{N/mm}^2$ a

E. M. Lorits, E. A. Gubar

Evolutionary games are a developing sub-field of game theory. This branch of game theory is used in the study of the adaptation of large, but finite, populations of agents to changes in the environment. It assumes that each agent has no significant influence on the system. Many scientific areas use the theory of evolutionary games. In particular, it is used

J. Huang, Camen A. Royse, I. Arakelyan, J. E. Thomas

We systematically test a quasi-classical spin model of a large spin-lattice in energy space, with a tunable, reversible Hamiltonian and effective long-range interactions. The system is simulated by a weakly interacting Fermi gas undergoing perturbed quantum rewinding using radio-frequency(RF) pulses. The model reported here is found to be in a quantitative a

Fei Xue, Mark D. Stiles, Paul M. Haney

In ferromagnetic systems lacking inversion symmetry, an applied electric field can control the ferromagnetic order parameters through the spin-orbit torque. The prototypical example is a bilayer heterostructure composed of a ferromagnet and a heavy metal that acts as a spin current source. In addition to such bilayers, spin-orbit coupling can mediate spin-or

I. Alekseev, V. Belov, M. Danilov, D. Filosofov

The detector DANSS is located under n industrial nuclear reactor at Kalininskaya Nuclear Power Plant. This location provides ~ 50 m.w.e. reduction of the cosmic muon flux in the vertical direction, which places the experiment in an intermediate position between ground and underground experiments in terms of shielding from the cosmic rays. The detector DANSS

Eugene Lerman

In an earlier paper (arXiv:2212.11163) I constructed a complex of differential forms on a local $C^\infty$-ringed space. In this paper I define a sheaf of vector fields (``the tangent sheaf'') on a local $C^\infty$-ringed space, define contractions of vector fields and forms, Lie derivatives of forms with respect to vector fields, and show that the standard

Jérémy Neveu, Vincent Brémaud, Pierre Antilogus, Florent Barret

In the next decade, many optical surveys will aim to tackle the question of dark energy nature, measuring its equation of state parameter at the permil level. This requires trusting the photometric calibration of the survey with a precision never reached so far, controlling many sources of systematic uncertainties. The measurement of the on-site atmospheric

Tom Struck, Mats Volmer, Lino Visser, Tobias Offermann

Long-ranged coherent qubit coupling is a missing function block for scaling up spin qubit based quantum computing solutions. Spin-coherent conveyor-mode electron-shuttling could enable spin quantum-chips with scalable and sparse qubit-architecture. Its key feature is the operation by only few easily tuneable input terminals and compatibility with industrial

Jeffrey Galkowski, Maciej Zworski

Motivated by the study of flat bands in models of twisted bilayer graphene (TBG), we give abstract conditions which guarantee the existence of a discrete set of parameters for which periodic Hamiltonians exhibit flat bands. As an application, we show that a scalar operator derived from the chiral model of TBG has flat bands for a discrete set of parameters.

Fatemeh Abdollahi, Saqib Ameen, Matthew E. Taylor, Levi H. S. Lelis

This paper introduces a local search method for improving an existing program with respect to a measurable objective. Program Optimization with Locally Improving Search (POLIS) exploits the structure of a program, defined by its lines. POLIS improves a single line of the program while keeping the remaining lines fixed, using existing brute-force synthesis al

Zhun Yang, Adam Ishay, Joohyung Lee

Constraint satisfaction problems (CSPs) are about finding values of variables that satisfy the given constraints. We show that Transformer extended with recurrence is a viable approach to learning to solve CSPs in an end-to-end manner, having clear advantages over state-of-the-art methods such as Graph Neural Networks, SATNet, and some neuro-symbolic models.

Roberto Riganti, Luca Dal Negro

In this paper, we develop and employ auxiliary physics-informed neural networks (APINNs) to solve forward, inverse, and coupled integro-differential problems of radiative transfer theory (RTE). Specifically, by focusing on the relevant slab geometry and scattering media described by different types of phase functions, we show how the proposed APINN framework

Jonathan E. Dawson, Abdul N. Malmi-Kakkada

A variety of living and non-living systems exhibit collective motion. From swarm robotics to bacterial swarms, and tissue wound healing to human crowds, examples of collective motion are highly diverse but all of them share the common necessary ingredient of moving and interacting agents. While collective motion has been extensively studied in non-proliferat

Rubens O. Moraes, David S. Aleixo, Lucas N. Ferreira, Levi H. S. Lelis

This paper introduces Local Learner (2L), an algorithm for providing a set of reference strategies to guide the search for programmatic strategies in two-player zero-sum games. Previous learning algorithms, such as Iterated Best Response (IBR), Fictitious Play (FP), and Double-Oracle (DO), can be computationally expensive or miss important information for gu

El Mehdi Chouham, Jessica López Espejel, Mahaman Sanoussi Yahaya Alassan, Walid Dahhane

The field of programming has a diversity of paradigms that are used according to the working framework. While current neural code generation methods are able to learn and generate code directly from text, we believe that this approach is not optimal for certain code tasks, particularly the generation of classes in an object-oriented project. Specifically, we

Artem Bituitskii

This report contributes to the field of unsupervised domain adaptation by providing an analysis of existing methods, introducing a new approach, and demonstrating the potential for improving visual recognition tasks across different domains. The results of this study open up opportunities for further study and development of advanced methods in the field of

Roy T. Forestano, Konstantin T. Matchev, Katia Matcheva, Alexander Roman

Recent work has applied supervised deep learning to derive continuous symmetry transformations that preserve the data labels and to obtain the corresponding algebras of symmetry generators. This letter introduces two improved algorithms that significantly speed up the discovery of these symmetry transformations. The new methods are demonstrated by deriving t

Rémi Vaudaine, Pierre Borgnat, Paulo Goncalves, Rémi Gribonval

Pairwise temporal interactions between entities can be represented as temporal networks, which code the propagation of processes such as epidemic spreading or information cascades, evolving on top of them. The largest outcome of these processes is directly linked to the structure of the underlying network. Indeed, a node of a network at given time cannot aff

Ignacio A. Perez, Dana Ben Porath, Cristian E. La Rocca, Lidia A. Braunstein

While network abrupt breakdowns due to overloads and cascading failures have been studied extensively, the critical exponents and the universality class of such phase transitions have not been discussed. Here, we study breakdowns triggered by failures of links and overloads in networks with a spatial characteristic link length $\zeta$. Our results indicate t

John Moustakas, Dustin Lang, Arjun Dey, Stéphanie Juneau

We present the 2020 version of the Siena Galaxy Atlas (SGA-2020), a multi-wavelength optical and infrared imaging atlas of 383,620 nearby galaxies. The SGA-2020 uses optical $grz$ imaging over $\approx20,000$ deg$^{2}$ from the DESI Legacy Imaging Surveys Data Release 9 and infrared imaging in four bands (spanning 3.4-22 $\mu$m) from the six-year unWISE coad

Vincent Liu, Han Wang, Ruo Yu Tao, Khurram Javed

Catastrophic interference is common in many network-based learning systems, and many proposals exist for mitigating it. Before overcoming interference we must understand it better. In this work, we provide a definition and novel measure of interference for value-based reinforcement learning methods such as Fitted Q-Iteration and DQN. We systematically evalua

Ruben Wiersma, Ahmad Nasikun, Elmar Eisemann, Klaus Hildebrandt

We introduce a geometric multigrid method for solving linear systems arising from variational problems on surfaces in geometry processing, Gravo MG. Our scheme uses point clouds as a reduced representation of the levels of the multigrid hierarchy to achieve a fast hierarchy construction and to extend the applicability of the method from triangle meshes to ot

Amro Al-Baali, Thomas Hitchcox, James Richard Forbes

Correcting gradual position drift is a challenge in long-term subsea navigation. Though highly accurate, modern inertial navigation system (INS) estimates will drift over time due to the accumulated effects of sensor noise and biases, even with acoustic aiding from a Doppler velocity log (DVL). The raw sensor measurements and estimation algorithms used by th

Howard S. Cohl, Roberto S. Costas-Santos

We derive double-product representations of nonterminating basic hypergeometric series using diagonalization, a method introduced by Theo William Chaundy in 1943. We refer to this result as the $q$-Chaundy theorem and several limiting $q\to 1^{-}$ cases are considered. Using the $q$-Chaundy theorem, we explore properties of the symmetric and $q^{-1}$-symmetr

Mark Scanlon, Frank Breitinger, Christopher Hargreaves, Jan-Niclas Hilgert

The disruptive application of ChatGPT (GPT-3.5, GPT-4) to a variety of domains has become a topic of much discussion in the scientific community and society at large. Large Language Models (LLMs), e.g., BERT, Bard, Generative Pre-trained Transformers (GPTs), LLaMA, etc., have the ability to take instructions, or prompts, from users and generate answers and s

Kaiyi Guo, Ying Liang, Tianxing Ma

Controlling the metal-insulator transition in graphene-based material is a crucial topic as it directly impacts its potential applications. Inspired by recent experiments, we study the effects of doping and bond disorder on metal-insulator transition in graphene within the Hubbard model on a honeycomb lattice. By using the determinant quantum Monte Carlo met

Yoshua Bengio, Prateek Gupta, Lu Li, Soham Phade

The international community must collaborate to mitigate climate change and sustain economic growth. However, collaboration is hard to achieve, partly because no global authority can ensure compliance with international climate agreements. Combining AI with climate-economic simulations offers a promising solution to design international frameworks, including

Justin Malestein, Andrew Putman

For surface groups and right-angled Artin groups, we prove lower bounds on the shortest word in the generators representing a nontrivial element of the kth term of the lower central series.

Jonathan J. Foley, Jonathan F. McTague, A. Eugene DePrince

Polariton chemistry exploits the strong interaction between quantized excitations in molecules and quantized photon states in optical cavities to affect chemical reactivity. Molecular polaritons have been experimentally realized by the coupling of electronic, vibrational, and rovibrational transitions to photon modes, which has spurred tremendous theoretical

Mingjian Tuo, Fan Jiang, Xingpeng Li, Pascal Van Hentenryck

Day-ahead generation scheduling is typically conducted by solv-ing security-constrained unit commitment (SCUC) problem. However, with fast-growing of inverter-based resources, grid inertia has been dramatically reduced, compromising the dy-namic stability system. Traditional SCUC (T-SCUC), without any inertia requirements, may no longer be effective for rene

Johannes Treutlein

Evidential cooperation in large worlds (ECL) refers to the idea that humans and other agents can benefit by cooperating with similar agents with differing values in causally disconnected parts of a large universe. Cooperating provides agents with evidence that other similar agents are likely to cooperate too, resulting in gains from trade for all. This could

L. Arturo Ureña-López, Francisco X. Linares Cedeño

We present a numerical analysis of the cosmological evolution of scalar field dark matter (SFDM) in the Boltzmann code $\texttt{CLASS}$, based on a dynamical system analysis of previous works. We show a detailed study of the evolution of the different dynamical variables, and in particular of the energy density and its corresponding linear perturbations. The

Martin Lara, Elena Fantino, Hadi Susanto, Roberto Flores

The construction of an analytic orbit theory that takes into account the main effects of the Geopotential is notably simplified when splitting the removal of periodic effects in several stages. Conversely, this splitting of the analytical solution into several transformations reduces the evaluation efficiency for dense ephemeris output. However, the advantag

Cayenne Matt, Kayhan Gültekin, Joseph Simon

We examine the effect of supermassive black hole (SMBH) mass scaling relation choice on the inferred SMBH mass population since redshift $z \sim 3$. To make robust predictions for the gravitational wave background (GWB) we must have a solid understanding of the underlying SMBH demographics. Using the SDSS and 3D HST+CANDELS surveys for $0 < z < 3$ we evaluat

Qingtian Miao, Jayakrishnan M. P. Nair, Girish S. Agarwal

Bound states in continuum (BICs) are localized states of a system possessing significantly large life times with applications across various branches of science. In this work, we propose an expedient protocol to engineer BICs which involves the use of Kerr nonlinearities in the system. The generation of BICs is a direct artifact of the nonlinearity and the a

Branislav Rabatin, David C. Collins

In star-forming clouds, high velocity flow gives rise to large fluctuations of density. In this work we explore the correlation between velocity magnitude (speed) and density. We develop an analytic formula for the joint probability distribution (PDF) of density and speed, and discuss its properties. In order to develop an accurate model for the joint PDF, w

Ashley P. Fidler, Liying Chen, Alexander M. McKillop, Marissa L. Weichman

Polariton chemistry may provide a new means to control molecular reactivity, permitting remote, reversible modification of reaction energetics, kinetics, and product yields. A considerable body of experimental and theoretical work has already demonstrated that strong coupling between a molecular vibrational mode and the confined electromagnetic field of an o

Diego Guajardo

Given a Euclidean submanifold $\map{g}{M}{n}{\R^{n+p}}$, Chern and Kuiper provided inequalities between $\mu$ and $\nu_g$, the ranks of the nullity of $M^n$ and the relative nullity of $g$ respectively. Namely, they prove that $$\nu_g\leq\mu\leq\nu_g+p$$. In this work, we study the submanifolds with $\nu_g\neq\mu$. More precisely, we characterize locally the

Francisco X. Linares Cedeño, Ulises Nucamendi

With focus on the cosmological evolution of linear perturbations of matter and geometry, we calculate the equivalent expressions to that of the Newtonian and Synchronous gauges within the framework of Unimodular Gravity, being these two gauges commonly used and implemented in Boltzmann codes. An important aspect of our analysis is the inclusion of the energy

Simon DeDeo

This essay explores the impact of automated proof construction on three key areas of mathematical cognition: on how we judge the role one piece of mathematics plays in another, on how we make mistakes in reasoning about mathematical objects, and on how we understand what our theorems are truly about. It concludes by speculating on a new form of mathematical

Xinran Zhu, Hong Shui, Bodong Chen

The ability to synthesize information has emerged as a critical skill for success across various fields. However, within the field of education, there is a lack of systematic understanding and well-defined design infrastructures that address the mechanisms and processes of knowledge synthesis in collaborative learning settings. In this poster, we introduce a

Kelvin Kan, James G. Nagy, Lars Ruthotto

This paper introduces LSEMINK, an effective modified Newton-Krylov algorithm geared toward minimizing the log-sum-exp function for a linear model. Problems of this kind arise commonly, for example, in geometric programming and multinomial logistic regression. Although the log-sum-exp function is smooth and convex, standard line search Newton-type methods can

Jonathan Morag, Ido Irani, Nir Sapir, Eli Waxman

Light emission in the first hours and days following core-collapse supernovae (SNe) is dominated by the escape of photons from the expanding shock heated envelope. In a preceding paper, Paper I, we provided a simple analytic description of the time dependent luminosity, $L$, and color temperature, $T_{\rm col}$, valid up to H recombination ($T\approx0.7$ eV)

Deepak Dhar, R. Rajesh, Aanjaneya Kumar

This article contains our comments and views on the status of the current understanding of phase transitions in systems with only hard-core interactions, based on our work in this area. The equation of state for the hard sphere gas in $d$-dimensions is discussed. The universal repulsive Lee-Yang singularities in the complex activity plane, and its relation t

Woojoo Na, Abiy Tasissa

We introduce RACH-Space, an algorithm for labelling unlabelled data in weakly supervised learning, given incomplete, noisy information about the labels. RACH-Space offers simplicity in implementation without requiring hard assumptions on data or the sources of weak supervision, and is well suited for practical applications where fully labelled data is not av

Gaurav Bagwe, Xiaoyong Yuan, Miao Pan, Lan Zhang

Federated continual learning (FCL) learns incremental tasks over time from confidential datasets distributed across clients. This paper focuses on rehearsal-free FCL, which has severe forgetting issues when learning new tasks due to the lack of access to historical task data. To address this issue, we propose Fed-CPrompt based on prompt learning techniques t

Donna Tjandra, Jenna Wiens

Noisy training labels can hurt model performance. Most approaches that aim to address label noise assume label noise is independent from the input features. In practice, however, label noise is often feature or \textit{instance-dependent}, and therefore biased (i.e., some instances are more likely to be mislabeled than others). E.g., in clinical care, female

Thaddäus Wiedemer, Prasanna Mayilvahanan, Matthias Bethge, Wieland Brendel

Leveraging the compositional nature of our world to expedite learning and facilitate generalization is a hallmark of human perception. In machine learning, on the other hand, achieving compositional generalization has proven to be an elusive goal, even for models with explicit compositional priors. To get a better handle on compositional generalization, we h

Wladimir Silva

We propose a method to mitigate measurement errors in the distribution counts of a Quantum computer using image contrast filters. This work is similar to the method described by Gambetta and colleagues in [1]; however our technique does not use a linear system of equations, but an image contrast filter to mitigate the measurement noise. Furthermore this meth

Albara Ah Ramli, Xin Liu, Kelly Berndt, Chen-Nee Chuah

Estimation of temporospatial clinical features of gait (CFs), such as step count and length, step duration, step frequency, gait speed, and distance traveled, is an important component of community-based mobility evaluation using wearable accelerometers. However, accurate unsupervised computerized measurement of CFs of individuals with Duchenne muscular dyst

Adriana Manna, Júlia Koltai, Márton Karsai

Individuals socio-demographic and economic characteristics crucially shape the spread of an epidemic by largely determining the exposure level to the virus and the severity of the disease for those who got infected. While the complex interplay between individual characteristics and epidemic dynamics is widely recognized, traditional mathematical models often

Maarten Derickx, Filip Najman

Let $X_\Delta(N)$ be an intermediate modular curve of level $N$, meaning that there exist (possibly trivial) morphisms $X_1(N)\rightarrow X_\Delta(N) \rightarrow X_0(N)$. For all such intermediate modular curves, we give an explicit description of all primes $p$ such that $X_\Delta(N)_{\overline{\mathbb F}_p}$ is either hyperelliptic or trigonal. Furthermore

Timothée Fabre, Vincent Ragel

Order placement tactics play a crucial role in high-frequency trading algorithms and their design is based on understanding the dynamics of the order book. Using high quality high-frequency data and a set of microstructural features, we exhibit strong state dependence properties of the fill probability function. We train a neural network to infer the fill pr

Gustavo F. S. Alves, Chee Sheng Fong, Luighi P. S. Leal, Renata Zukanovich Funchal

In this letter we show that pseudoscalar meson leptonic decay data can be used to set stringent limits on the mass $m_{W_R}$ of a right-handed vector boson, such as the one that appears in left-right symmetric models. We have shown that for a heavy neutrino with a mass $m_N$ in the range $50<m_N/{\rm MeV} <1900$ one can constraint $m_{W_R} \lesssim (4-19)$ T

Zhizhi Kong, Corey J. Kaminsky, Catherine K. Groschner, Ryan A. Murphy

Some magnetic systems display a shift in the center of their magnetic hysteresis loop away from zero field, a phenomenon termed exchange bias. Despite the extensive use of the exchange bias effect, particularly in magnetic multilayers, for the design of spin-based memory/electronics devices, a comprehensive mechanistic understanding of this effect remains a

James B. Dent, Bhaskar Dutta, Adrian Thompson

Axions and axion-like pseudoscalar particles with dimension-5 couplings to photons exhibit coherent Primakoff scattering with ordered crystals at keV energy scales, making for a natural detection technique in searches for solar axions. We find that there are large suppressive corrections, potentially greater than a factor of $\mathcal{O}(10^3)$, to the coher

Krzysztof J. Ciosmak

We demonstrate that the Cartan-Thullen theorem and its generalisation to the context of generalised convexity, which we establish herein, can be regarded as consequences of the classical theorems of functional analysis: the Banach-Steinhaus theorem and the Banach-Alaoglu theorem. Furthermore, we characterise the domains of holomorphy, and their generalisatio

Alexander W. Bergman, Wang Yifan, Gordon Wetzstein

The ability to generate diverse 3D articulated head avatars is vital to a plethora of applications, including augmented reality, cinematography, and education. Recent work on text-guided 3D object generation has shown great promise in addressing these needs. These methods directly leverage pre-trained 2D text-to-image diffusion models to generate 3D-multi-vi

Shaokai Ye, Jessy Lauer, Mu Zhou, Alexander Mathis

The process of quantifying and analyzing animal behavior involves translating the naturally occurring descriptive language of their actions into machine-readable code. Yet, codifying behavior analysis is often challenging without deep understanding of animal behavior and technical machine learning knowledge. To limit this gap, we introduce AmadeusGPT: a natu

Jake Kettinger

The geproci property is a recent development in the world of geometry. We call a set of points $Z\subseteq\mathbb{P}_k^3$ an $(a,b)$-geproci set (for GEneral PROjection is a Complete Intersection) if its projection from a general point $P$ to a plane is a complete intersection of curves of degrees $a\leq b$. Nondegenerate examples known as grids have been kn

Simen Bruinsma, Alexander Schenkel, Benoit Vicedo

This paper studies the universal first-order Massey product of a prefactorization algebra, which encodes higher algebraic operations on the cohomology. Explicit computations of these structures are carried out in the locally constant case, with applications to factorization envelopes on $\mathbb{R}^m$ and a compactification of linear Chern-Simons theory on $

Vitaliy Sultanov, Maria Chekhova

Generation of entangled photons through spontaneous parametric down-conversion (SPDC) from ultrasmall sources like thin films, metasurfaces, or nanoantennas, offers unprecedented freedom in quantum state engineering. However, as the source of SPDC gets smaller, the role of photoluminescence increases, which leads to the contamination of two-photon states wit

Km Rubi, Denis R. Candido, Manish Dumen, Shengwei Zeng

The simultaneous occurrence of electric-field controlled superconductivity and spin-orbit interaction makes two-dimensional electron systems (2DES) constructed from perovskite transition metal oxides promising candidates for the next generation of spintronics and quantum computing. It is, however, essential to understand the electronic bands thoroughly and v

Debby Tran, Benjamin Williams, Emily Levesque, Margaret Lazzarini

The nearby face-on star forming spiral galaxy NGC 6946 is known as the Fireworks Galaxy due to its hosting an unusually large number of supernova. We analyze its resolved near-ultraviolet (NUV) stellar photometry measured from images taken with the Hubble Space Telescope's (HST) Wide Field Camera 3 (WFC3) with F275W and F336W filters. We model the color-magn

B. Ananthanarayan, Souvik Bera, Tanay Pathak

Motivated by the foundational work of Tarasov, who pointed out that the algebraic relations of the type considered here can lead to functional reduction of Feynman integrals, we suitably modify the original method to be able to implement and automatize it and present a $\textit{Mathematica}$ package $\texttt{AlgRel.wl}$. The purpose of this package is to hel

Ashwin Tunga, Zijing Zhao, Ankit Shukla, Wenjuan Zhu

In this work, we describe the charge transport in two-dimensional (2D) Schottky barrier field-effect transistors (SB-FETs) based on the carrier injection at the Schottky contacts. We first develop a numerical model for thermionic and field-emission processes of carrier injection that occur at a Schottky contact. The numerical model is then simplified to yiel

Sanjay Kariyappa, Leonidas Tsepenekas, Freddy Lécué, Daniele Magazzeni

The SHAP framework provides a principled method to explain the predictions of a model by computing feature importance. Motivated by applications in finance, we introduce the Top-k Identification Problem (TkIP), where the objective is to identify the k features with the highest SHAP values. While any method to compute SHAP values with uncertainty estimates (s

Aleksei Sorokin, Xinran Zhu, Eric Hans Lee, Bolong Cheng

Gradient boosted trees (GBTs) are ubiquitous models used by researchers, machine learning (ML) practitioners, and data scientists because of their robust performance, interpretable behavior, and ease-of-use. One critical challenge in training GBTs is the tuning of their hyperparameters. In practice, selecting these hyperparameters is often done manually. Rec

Michael E. Brown, Bryan J. Butler

We have used the Atacama Large Millimeter Array (ALMA) to measure precise absolute astrometric positions and detect the astrometric wobble of dwarf planet Orcus and its satellite Vanth over a complete orbit. We also place upper limits to the astrometric wobble induced by Dysnomia on dwarf planet Eris around its orbit. From the Vanth-Orcus barycentric motion,