December 2023 arXiv papers — page 22

CMS Collaboration

A measurement is presented of the primary Lund jet plane (LJP) density in inclusive jet production in proton-proton collisions. The analysis uses 138 fb$^{-1}$ of data collected by the CMS experiment at $\sqrt{s}$ = 13 TeV. The LJP, a representation of the phase space of emissions inside jets, is constructed using iterative jet declustering. The transverse m

M. S. Soares, N. F. Svaiter, G. Menezes

We study the entanglement dynamics of accelerated atoms using the theory of open quantum systems. We consider two atoms travelling along different hyperbolic trajectories with different proper times. We use the generalized master equation to discuss the dynamics of a pair of dipoles interacting with the electromagnetic field. The fundamental role played by p

Chengshuai Shi, Ruida Zhou, Kun Yang, Cong Shen

Federated learning (FL) has demonstrated great potential in revolutionizing distributed machine learning, and tremendous efforts have been made to extend it beyond the original focus on supervised learning. Among many directions, federated contextual bandits (FCB), a pivotal integration of FL and sequential decision-making, has garnered significant attention

Stefania Bellavia, Francesco Della Santa, Alessandra Papini

This paper introduces novel alternate training procedures for hard-parameter sharing Multi-Task Neural Networks (MTNNs). Traditional MTNN training faces challenges in managing conflicting loss gradients, often yielding sub-optimal performance. The proposed alternate training method updates shared and task-specific weights alternately through the epochs, expl

Kacper Łodzikowski, Peter W. Foltz, John T. Behrens

We discuss the implications of generative AI on education across four critical sections: the historical development of AI in education, its contemporary applications in learning, societal repercussions, and strategic recommendations for researchers. We propose ways in which generative AI can transform the educational landscape, primarily via its ability to c

Ping-yeh Chiang, Yipin Zhou, Omid Poursaeed, Satya Narayan Shukla

Recently, Pyramid Adversarial training (Herrmann et al., 2022) has been shown to be very effective for improving clean accuracy and distribution-shift robustness of vision transformers. However, due to the iterative nature of adversarial training, the technique is up to 7 times more expensive than standard training. To make the method more efficient, we prop

Fatih Cagatay Akyon, Alptekin Temizel

This paper presents a comparative analysis of existing nudity classification techniques for classifying images based on the presence of nudity, with a focus on their application in content moderation. The evaluation focuses on CNN-based models, vision transformer, and popular open-source safety checkers from Stable Diffusion and Large-scale Artificial Intell

Changmao Li, Jeffrey Flanigan

Large language models (LLMs) offer impressive performance in various zero-shot and few-shot tasks. However, their success in zero-shot and few-shot settings may be affected by task contamination, a potential limitation that has not been thoroughly examined. This paper investigates how zero-shot and few-shot performance of LLMs has changed chronologically ove

Corto Mascle, Nathanaël Fijalkow, Guillaume Lagarde

We study the problem of learning linear temporal logic (LTL) formulas from examples, as a first step towards expressing a property separating positive and negative instances in a way that is comprehensible for humans. In this paper we initiate the study of the computational complexity of the problem. Our main results are hardness results: we show that the LT

Mariano Tepper, Ishwar Singh Bhati, Cecilia Aguerrebere, Mark Hildebrand

Modern deep learning models have the ability to generate high-dimensional vectors whose similarity reflects semantic resemblance. Thus, similarity search, i.e., the operation of retrieving those vectors in a large collection that are similar to a given query, has become a critical component of a wide range of applications that demand highly accurate and time

Thomas Koberda, J. de la Nuez González

We show that the first order theory of the homeomorphism group of a compact manifold interprets the full second order theory of countable groups of homeomorphisms of the manifold. The interpretation is uniform across manifolds of bounded dimension. As a consequence, many classical problems in group theory and geometry (e.g.~the linearity of mapping classes o

Susana Beatriz Araujo Furlan, Ezequiel Zubieta, Guillermo Gancio, Gustavo Esteban Romero

Currently, 6 out of 30 known magnetars had pulsed radio emission detected. In this work, we evaluated the possibility of detecting radio transient events from magnetars with the telescopes of the Instituto Argentino de Radioastronom\'ia (IAR). To this aim, we made daily observations of the magnetar XTE~J1810$-$197 from 02-Sep-22 to 30-Nov-22. We analysed the

Tiandong Wang, Sidney I. Resnick

Preferential attachment models of network growth are bivariate heavy tailed models for in- and out-degree with limit measures which either concentrate on a ray of positive slope from the origin or on all of the positive quadrant depending on whether the model includes reciprocity or not. Concentration on the ray is called full dependence. If there were a rel

Asim Khan, Umair Nawaz, Lochan Kshetrimayum, Lakmal Seneviratne

Tomato leaf diseases pose a significant challenge for tomato farmers, resulting in substantial reductions in crop productivity. The timely and precise identification of tomato leaf diseases is crucial for successfully implementing disease management strategies. This paper introduces a transformer-based model called TomFormer for the purpose of tomato leaf di

Ruqiao Xia, Nikita W. Almond, Stephen J. Kindness, Sergey A. Mikhailov

Effective control of terahertz radiation requires the development of efficient and fast modulators with a large modulation depth. This challenge is often tackled by using metamaterials, artificial sub-wavelength optical structures engineered to resonate at the desired terahertz frequency. Metamaterial-based devices exploiting graphene as the active tuneable

Ralph V. Chamberlin

In a 2023 Nature Communication, Dong claims that a disjoining chemical potential should be used instead of "Hill's nanothermodynamics" because Hill's subdivision potential "remains elusive to relate...to any experimental observables." Here, I remind readers of the 2000 Letter to Nature where Hill's ideas were adapted to provide improved agreement with the no

Zexu Li, Lei Fang

Human crowds exhibit a wide range of interesting patterns, and measuring them is of great interest in areas ranging from psychology and social science to civil engineering. While \textit{in situ} measurements of human crowd patterns require large amounts of time and labor to obtain, human crowd experiments may result in statistics different from those that w

Jorge Bellorin, Claudio Borquez, Byron Droguett

We compute the one-loop effective action of the Horava theory, in its nonprojectable formulation. We take the quantization of the (2+1)-dimensional theory in the Batalin-Fradkin-Vilkovisky formalism, and comment on the extension to the (3+1) case. The second-class constraints and the appropriate gauge-fixing condition are included in the quantization. The gh

Antonio Perez-Garrido

In this paper, we use differential forms to prove a number of theorems of integral vector calculus that are rarely found in textbooks. Two of them, as far as the author knows, have not been published before. Some possible applications to problems in physics are shared including a general approach for computing net forces and torques on current-carrying loops

Kushal Tibrewal, Katsumasa Tanaka, Philippe Ciais, Olivier Boucher

To assess the impact of potential future climate pledges after the first Global Stocktake, we propose a simple, transparent framework for developing emission and temperature scenarios by country. We show that current pledges with unconditional targets lead to global warming of 1.96 (1.39-2.6) degree C by 2100. Further warming could be limited through i) comm

Elliott Vest

Petyt-Spriano-Zalloum recently developed the notion of a \textit{curtain model}, which is a hyperbolic space associated to any CAT(0) space. It plays a similar role for CAT(0) spaces that curve graphs do for mapping class groups of finite-type surfaces. Those authors asked whether this curtain model is a quasi-isometry invariant, namely if quasi-isometric CA

V. K. Oikonomou, Gregory K. Kafanelis

In this work we consider the realization of a variant emergent Universe scenario in the context of $f(R)$ gravity. We use well-known reconstruction techniques existing in the literature, and we find the approximate form of the vacuum $f(R)$ that reproduces the specific variant emergent Universe scale factor in the large curvature approximation. As we show, i

Gauthier Wissocq, Rémi Abgrall

We extend to multi-dimensions the work of [1], where new fully explicit kinetic methods were built for the approximation of linear and non-linear convection-diffusion problems. The fundamental principles from the earlier work are retained: (1) rather than aiming for the desired equations in the strict limit of a vanishing relaxation parameter, as is commonly

Vikas Srivastava, Paresh Baidya, Sihem Mesnager, Debasish Roy

Audit logs are one of the most important tools for transparently tracking system events and maintaining continuous oversight in corporate organizations and enterprise business systems. There are many cases where the audit logs contain sensitive data, or the audit logs are enormous. In these situations, dealing with a subset of the data is more practical than

Pavel A. Andreev, Mariya Iv. Trukhanova

The multiferroics are the materials, where single cell of a magnetically order crystal forms an electric dipole moment. We derive equation for the evolution of the macroscopic density of the electric dipole moment (polarization of the system). The derivation is made within the "quantum hydrodynamic" method, which allows to derive equations for the evolution

Rubén Cordero, Luis A. Delgadillo

From a cosmological perspective, scalar fields are well-motivated dark matter and dark energy candidates. Several possibilities of neutrino couplings with a time-varying cosmic field have been investigated in the literature. In this work, we present a framework in which violations of Lorentz invariance (LIV) and $CPT$ symmetry in the neutrino sector could ar

Robert M. Guralnick, John Shareshian, Russ Woodroofe

We show that every finite simple group is generated invariably by a Sylow subgroup and a cyclic group. It follows that that the order complex of the coset poset of an arbitrary finite group has nontrivial reduced rational homology.

Tapaswini Mohanty, Vikas Srivastava, Sumit Kumar Debnath, Pantelimon Stanica

Secure multiparty computation (MPC) schemes allow two or more parties to conjointly compute a function on their private input sets while revealing nothing but the output. Existing state-of-the-art number-theoretic-based designs face the threat of attacks through quantum algorithms. In this context, we present secure MPC protocols that can withstand quantum a

Clay Cordova, Diego García-Sepúlveda

We derive new dualities of topological quantum field theories in three spacetime dimensions that generalize the familiar level-rank dualities of Chern-Simons gauge theories. The key ingredient in these dualities is non-abelian anyon condensation, which is a gauging operation for topological lines with non-group-like i.e. non-invertible fusion rules. We find

Shohei Saga, Maresuke Shiraishi, Kazuyuki Akitsu, Teppei Okumura

Primordial magnetic fields (PMFs) are one of the plausible candidates for the origin of the observed large-scale magnetic fields. While many proposals have been made for the generation mechanism of PMFs by earlier studies, it remains a subject of debate. In this paper, to obtain new insights into PMFs, we focus on the intrinsic alignments (IAs) of galaxies i

María José Domínguez Vázquez

The aim of this paper is to provide a classification of multilingual and plurilingual electronic lexicographic resources which would enable, one the one hand, the implementation of quantitative and qualitative criteria to produce a typological taxonomy of lexicographical tools, such as dictionaries, as opposed to platforms and websites and, on the other, the

Kathryn Haymaker, Hiram H. López, Beth Malmskog, Gretchen L. Matthews

Employing underlying geometric and algebraic structures allows for constructing bespoke codes for local recovery of erasures. We survey techniques for enriching classical codes with additional machinery, such as using lines or curves in projective space for local recovery sets or products of curves to enhance the availability of data.

Harold Benoit, Liangze Jiang, Andrei Atanov, Oğuzhan Fatih Kar

Supervised learning datasets may contain multiple cues that explain the training set equally well, i.e., learning any of them would lead to the correct predictions on the training data. However, many of them can be spurious, i.e., lose their predictive power under a distribution shift and consequently fail to generalize to out-of-distribution (OOD) data. Rec

Santhosh G S, Piyush Joshi, Ayan Barui, Prasanta K. Panigrahi

In this work, we have introduced two innovative quantum algorithms: the Direct Column Algorithm and the Quantum Backtracking Algorithm to solve N-Queens problem, which involves the arrangement of $N$ queens on an $N \times N$ chessboard such that they are not under attack from each other on the same row, column and diagonal. These algorithms utilizes Control

María José Domínguez Vázquez

The multilingual dictionary of noun valency Portlex is considered to be the trigger for the creation of the automatic language generators Xera and Combinatoria, whose development and use is presented in this paper. Both prototypes are used for the automatic generation of nominal phrases with their mono- and bi-argumental valence slots, which could be used, a

Aleksandr V. Pukhlikov

It is shown that hypersurfaces of degree $M$ in ${\mathbb P}^M$, $M\geqslant 5$, with at most quadratic singularities of rank at least 3, satisfying certain conditions of general position, are birationally superrigid Fano varieties and the complement to the set of such hypersurfaces is for $M\geqslant 8$ of codimension at least ${M-1 \choose 2} + 1$ with res

María José Domínguez Vázquez

This paper describes how the field of Combinatorial Semantics has contributed to the design of three prototypes for the automatic generation of argument patterns in nominal phrases in Spanish, French and German (Xera, Combinatoria and CombiContext). It also shows the importance of knowing about the argument syntactic-semantic interface in a production situat

Fabio Di Cosmo, Alberto Ibort, Giuseppe Marmo, Patrizia Vitale

We define the gauge potentials of Poisson electrodynamics as sections of a symplectic realization of the spacetime manifold and infinitesimal gauge transformations as a representation of the associated Lie algebroid acting on the symplectic realization. Finite gauge transformations are obtained by integrating the sections of the Lie algebroid to bisections o

Zhuoyang Ye

I use QAOA to solve the Hamiltonian Circle problem. First, inspired by Lucas, I define the QUBO form of Hamiltonian Cycle and transform it to a quantum circuit by embedding the problem of $n$ vertices to an encoding of $(n-1)^2$ qubits. Then, I calcluate the spectrum of the cost hamiltonian for both triangle case and square case and justify my definition. I

Daniel Ngo, Keegan Harris, Anish Agarwal, Vasilis Syrgkanis

Synthetic control methods (SCMs) are a canonical approach used to estimate treatment effects from panel data in the internet economy. We shed light on a frequently overlooked but ubiquitous assumption made in SCMs of "overlap": a treated unit can be written as some combination -- typically, convex or linear -- of the units that remain under control. We show

Zheng-Liang Liang, Lin Zhang

The Primakoff mechanism is one of the primary channels for the production of solar axion. In canonical estimation of the Primakoff photon-axion conversion rate, the recoil effect is neglected and a static structure factor is adopted. By use of the linear response theory, we provide a dynamic description of the solar Primakoff process. It is found that the co

Tathagata Ghosh, Surhud More, Sayantani Bera, Sukanta Bose

Gravitational waves (GWs) from the inspiral of binary compact objects offer a one-step measurement of the luminosity distance to the event, which is essential for the measurement of the Hubble constant, $H_0$, which characterizes the expansion rate of the Universe. However, unlike binary neutron stars, the inspiral of binary black holes is not expected to be

Dilip Kumar Ghosh, Purusottam Ghosh, Sk Jeesun, Rahul Srivastava

The current upper limit on $N_{\rm eff}$ at the time of CMB by Planck 2018 can place stringent constraints in the parameter space of BSM paradigms where their additional interactions may affect neutrino decoupling. Motivated by this fact in this paper we explore the consequences of light gauge boson ($Z'$) emerging from local $U(1)_X$ symmetry in $N_{\rm eff

S. A. Franchino-Viñas, C. García-Pérez, F. D. Mazzitelli, V. Vitagliano

In this letter, we prove the existence of resummed expressions for the diagonal of the heat kernel and the effective action of a quantum field which interacts with a scalar or an electromagnetic background. Working in an arbitrary number of spacetime dimensions, we propose an Ansatz beyond the Schwinger--DeWitt proposal, effectively resumming an infinite num

Leonardo Bonorino, Giovanni Nunes, Álvaro Ramos, Jaime Ripoll

We prove that $Sol_3$, the isometry group of the Minkowski plane, is non parabolic with respect to any left invariant metric.

Grigorios Giotopoulos, Hisham Sati

Most modern theoretical considerations of the physical world suggest that nature is: (1) field-theoretic, (2) smooth, (3) local, (4) gauged, (5) containing fermions, and (6) non-perturbative. Tautologous as this may sound to experts, it is remarkable that the mathematical notion of geometry which reflects all of these aspects - namely, ``supergeometric homot

Caleb Kim, Pai Li, Anshuman Mohan, Andrew Butt

Compilers for accelerator design languages (ADLs) translate high-level languages into application-specific hardware. ADL compilers rely on a hardware control interface to compose hardware units. There are two choices: static control, which relies on cycle-level timing; or dynamic control, which uses explicit signalling to avoid depending on timing details. S

Dang Ho Hai Nguyen, Lionel Schwartz

This note shows that the $n$-th homology suspension is surjective for certain quotients of finite $((Z/2)^n$-CW.complexes. This is true as soon as the equivariant $((Z/2)^n$-cohomology are quotients is a free $H^*$((Z/2)^n$-module. An application is given to certain Brown-Gitler spectrum.

Alfredo Guevara, Yangrui Hu

Quantum gravity in 4D asymptotically flat spacetimes features spontaneous symmetry breaking due to soft radiation hair, intimately tied to the proliferation of IR divergences. A holographic description via a putative 2D CFT is expected free of such redundancies. In this series of two papers, we address this issue by initiating the study of Quantum Error Corr

Olga Shapoval, Edoardo Zoni, Remi Lehe, Maxence Thevenet

This paper introduces a novel formulation of the Particle-In-Cell (PIC) method for the modeling of relativistic plasmas, which leverages the ability of the Pseudo-Spectral Analytical Time-Domain solver (PSATD) to handle arbitrary time dependencies of the charge and current densities during one PIC cycle. The new formulation is applied to a modified set of Ma

Ranveer Kumar Singh, Madhav Sinha

Frenkel, Lepowsky, and Meurman constructed a vertex operator algebra (VOA) associated to any even, integral, Euclidean lattice. In the language of physics, these are examples of chiral conformal field theories (CFT). In this paper, we define non-chiral vertex operator algebra and some associated notions. We then give a construction of a non-chiral VOA associ

Ding Ding, Zhao Yu, Yidun Wan

We develop a novel framework for describing quantum fluctuations in field theory, with a focus on cosmological applications. Our method uniquely circumvents the use of operator/Hilbert-space formalism, instead relying on a systematic treatment of classical variables, quantum fluctuations, and an effective Hamiltonian. Our framework not only aligns with stand

Xiaojian Du, Wenyang Qian

Thermalization of heavy quarks in the quark-gluon plasma (QGP) is one of the most promising phenomena for understanding the strong interaction. The energy loss and momentum broadening at low momentum can be well described by a stochastic process with drag and diffusion terms. Recent advances in quantum computing, in particular quantum amplitude estimation (Q

nCTEQ Collaboration, A. W. Denniston, T. Jezo, A. Kusina

We extend the QCD Parton Model analysis using a factorized nuclear structure model incorporating individual nucleons and pairs of correlated nucleons. Our analysis of high-energy data from lepton Deep-Inelastic Scattering, Drell-Yan and W/Z production simultaneously extracts the universal effective distribution of quarks and gluons inside correlated nucleon

Samsuzzaman Afroz, Suvodip Mukherjee

Gravitational waves (GWs) provide a new avenue to test Einstein's General Relativity (GR) using the ongoing and upcoming GW detectors by measuring the redshift evolution of the effective Planck mass proposed by several modified theories of gravity. We propose a model-independent, data-driven approach to measure any deviation from GR in the GW propagation eff

Jacob Dunefsky, Arman Cohan

A key goal of current mechanistic interpretability research in NLP is to find linear features (also called "feature vectors") for transformers: directions in activation space corresponding to concepts that are used by a given model in its computation. Present state-of-the-art methods for finding linear features require large amounts of labelled data -- both

Toshihiro Sato, Sonia Haddad, Ion Cosma Fulga, Fakher F. Assaad

While altermagnetic materials are characterized by a vanishing net magnetic moment, their symmetry in principle allows for the existence of an anomalous Hall effect (AHE). Here we introduce a model with altermagnetism in which the emergence of an AHE is driven by interactions. This model is grounded in a modified Kane-Mele framework with antiferromagnetic (A

E. L. Gagnon, D. Anbajagane, J. Prat, C. Chang

Spatial variations in survey properties due to selection effects generate substantial systematic errors in large-scale structure measurements in optical galaxy surveys on very large scales. On such scales, the statistical sensitivity of optical surveys is also limited by their finite sky coverage. By contrast, gravitational wave (GW) sources appear to be rel

Giuliano Giudici, Federica Maria Surace, Hannes Pichler

Quantum scars are special eigenstates of many-body systems that evade thermalization. They were first discovered in the PXP model, a well-known effective description of Rydberg atom arrays. Despite significant theoretical efforts, the fundamental origin of PXP scars remains elusive. By investigating the discretized dynamics of the PXP model as a function of

Daniele De Bernardis, Gian Marcello Andolina, Iacopo Carusotto

We theoretically study how the peculiar properties of the vacuum state of an ultra-strongly coupled system can affect basic light-matter interaction processes. In this unconventional electromagnetic environment, an additional emitter no longer couples to the bare cavity photons, but rather to the polariton modes emerging from the ultra-strong coupling. As su

Roberta Angius, Andriana Makridou, Angel M. Uranga

Dynamical cobordisms implement the swampland cobordism conjecture in the framework of effective field theory, realizing codimension 1 end of the world (ETW) branes as singularities at finite spacetime distance at which scalars diverge to infinite field space distance. ETW brane solutions provide a useful probe of infinity in moduli field spaces and the assoc

Hiroki Nagakura, Lucas Johns, Masamichi Zaizen

We present a new subgrid model for neutrino quantum kinetics, which is primarily designed to incorporate effects of collective neutrino oscillations into neutrino-radiation-hydrodynamic simulations for core-collapse supernovae and mergers of compact objects. We approximate the neutrino oscillation term in quantum kinetic equation by Bhatnagar-Gross-Krook (BG

Jaydeep Kumar Basak, Adrita Chakraborty, Chong-Sun Chu, Dimitrios Giataganas

By using the notion of fractional derivatives, we introduce a class of massless Lifshitz scalar field theory in (1+1)-dimension with an arbitrary anisotropy index $z$. The Lifshitz scale invariant ground state of the theory is constructed explicitly and takes the form of Rokhsar-Kivelson (RK). We show that there is a continuous family of ground states with d

Falk Hassler, Yuho Sakatani, Luca Scala

We define generalized dualities for heterotic and type I strings based on consistent truncations to half-maximal gauged supergravities in more than three dimensions. The latter are constructed from a generalized Scherk-Schwarz ansatz in heterotic double field theory that satisfies the strong constraint. Necessary and sufficient conditions on the resulting em

Nima Arkani-Hamed, Qu Cao, Jin Dong, Carolina Figueiredo

Recent years have seen the emergence of a new understanding of scattering amplitudes in the simplest theory of colored scalar particles - the Tr$(\phi^3)$ theory - based on combinatorial and geometric ideas in the kinematic space of scattering data. In this paper we report a surprise: far from the toy model it appears to be, the ''stringy'' Tr$(\phi^3)$ ampl

Masahiro Hotta, Sebastian Murk

Leggett-Garg inequalities place bounds on the temporal correlations of a system based on the principles of macroscopic realism $\textit{per se}$ and noninvasive measurability. Their conventional formulation relies on the ensemble-averaged products of observables measured at different instants of time. However, a complete description that enables a precise un

George N. Wong, Lev Arzamasskiy

Horizon-scale observations from the Event Horizon Telescope (EHT) have enabled precision study of supermassive black hole accretion. Contemporary accretion modeling often treats the inflowing plasma as a single, thermal fluid, but microphysical kinetic effects can lead to significant deviations from this idealized picture. We investigate how the helicity bar

Sondos Mahmoud Bsharat, Aidar Myrzakhan, Zhiqiang Shen

This paper introduces 26 guiding principles designed to streamline the process of querying and prompting large language models. Our goal is to simplify the underlying concepts of formulating questions for various scales of large language models, examining their abilities, and enhancing user comprehension on the behaviors of different scales of large language

Tai Wang, Xiaohan Mao, Chenming Zhu, Runsen Xu

In the realm of computer vision and robotics, embodied agents are expected to explore their environment and carry out human instructions. This necessitates the ability to fully understand 3D scenes given their first-person observations and contextualize them into language for interaction. However, traditional research focuses more on scene-level input and ou

Stefano Marti, Uwe von Lüpke, Om Joshi, Yu Yang

Mechanical degrees of freedom are natural candidates for continuous-variable quantum information processing and bosonic quantum simulations. These applications, however, require the engineering of squeezing and nonlinearities in the quantum regime. Here we demonstrate ground state squeezing of a gigahertz-frequency mechanical resonator coupled to a supercond

Saeed Saadatnejad, Yang Gao, Kaouther Messaoud, Alexandre Alahi

Accurate human trajectory prediction is crucial for applications such as autonomous vehicles, robotics, and surveillance systems. Yet, existing models often fail to fully leverage the non-verbal social cues human subconsciously communicate when navigating the space. To address this, we introduce Social-Transmotion, a generic Transformer-based model that expl

Lorenzo Del Re

Spontaneous symmetry breaking of interacting fermion systems constitutes a major challenge for many-body theory due to the proliferation of new independent scattering channels once absent or degenerate in the symmetric phase. One example is given by the ferro/antiferromagnetic broken symmetry phase (BSP) of the Hubbard model, where vertices in the spin-trans

Muhammad Asaduzzaman, Simon Catterall, Yannick Meurice, Ryo Sakai

We show how to construct a tensor network representation of the path integral for reduced staggered fermions coupled to a non-abelian gauge field in two dimensions. The resulting formulation is both memory and computation efficient because reduced staggered fermions can be represented in terms of a minimal number of tensor indices while the gauge sector can

Alen Senanian, Sridhar Prabhu, Vladimir Kremenetski, Saswata Roy

Quantum reservoir computing (QRC) has been proposed as a paradigm for performing machine learning with quantum processors where the training is efficient in the number of required runs of the quantum processor and takes place in the classical domain, avoiding the issue of barren plateaus in parameterized-circuit quantum neural networks. It is natural to cons

Fangjun Hu, Saeed A. Khan, Nicholas T. Bronn, Gerasimos Angelatos

Practical implementation of many quantum algorithms known today is limited by the coherence time of the executing quantum hardware and quantum sampling noise. Here we present a machine learning algorithm, NISQRC, for qubit-based quantum systems that enables inference on temporal data over durations unconstrained by decoherence. NISQRC leverages mid-circuit m

Ipsita Mandal

We consider a superconductor-barrier-superconductor configuration built with Rarita-Schwinger-Weyl semimetal, which features four bands crossing at a single nodal point. Assuming a homogeneous s-wave pairing in each superconducting region, and the barrier region created by applying a voltage of magnitude $V_0 $ across a piece of normal state semimetal, we ap

Priyanka Kaswan, Purbesh Mitra, Arunabh Srivastava, Sennur Ulukus

Gossiping is a communication mechanism, used for fast information dissemination in a network, where each node of the network randomly shares its information with the neighboring nodes. To characterize the notion of fastness in the context of gossip networks, age of information (AoI) is used as a timeliness metric. In this article, we summarize the recent wor

Sepideh Mosaferi, Mark S. Kaiser, Daniel J. Nordman

Nonparametric cointegrating regression models have been extensively used in financial markets, stock prices, heavy traffic, climate data sets, and energy markets. Models with parametric regression functions can be more appealing in practice compared to non-parametric forms, but do result in potential functional misspecification. Thus, there exists a vast lit

Guanqun Wang, Jiaming Liu, Chenxuan Li, Junpeng Ma

The burgeoning field of Multimodal Large Language Models (MLLMs) has exhibited remarkable performance in diverse tasks such as captioning, commonsense reasoning, and visual scene understanding. However, the deployment of these large-scale MLLMs on client devices is hindered by their extensive model parameters, leading to a notable decline in generalization c

Johanna Fink

This paper estimates how electricity price divergence within Sweden has affected incentives to invest in photovoltaic (PV) generation between 2016 and 2022 based on a synthetic control approach. Sweden is chosen as the research subject since it is together with Italy the only EU country with multiple bidding zones and is facing dramatic divergence in electri

Edgar Dobriban, Mengxin Yu

Quantifying the uncertainty of predictions is a core problem in modern statistics. Methods for predictive inference have been developed under a variety of assumptions, often -- for instance, in standard conformal prediction -- relying on the invariance of the distribution of the data under special groups of transformations such as permutation groups. Moreove

Mofetoluwa Adeyemi, Akintunde Oladipo, Ronak Pradeep, Jimmy Lin

Large language models (LLMs) have shown impressive zero-shot capabilities in various document reranking tasks. Despite their successful implementations, there is still a gap in existing literature on their effectiveness in low-resource languages. To address this gap, we investigate how LLMs function as rerankers in cross-lingual information retrieval (CLIR)

Baha Alturan, Ilker Turker

Earthquakes are evaluated among the most destructive disasters for human beings, as also experienced for Turkiye region. Data science has the property of discovering hidden patterns in case a sufficient volume of data is supplied. Time dependency of events, specifically being defined by co-occurrence in a specific time window, may be handled as an associate

Carlotta Giusti, Matteo Vorabbi, Paolo Finelli

We derived microscopic optical potentials (OPs) for elastic nucleon-nucleus scattering within the framework of chiral effective field theories at the first-order term of the spectator expansion of the Watson multiple-scattering theory and adopting the impulse approximation. Our OPs are derived by folding ab initio nuclear densities with a nucleon-nucleon NN

Gulsum Yigit, Mehmet Fatih Amasyali

Integrating adversarial machine learning with Question Answering (QA) systems has emerged as a critical area for understanding the vulnerabilities and robustness of these systems. This article aims to comprehensively review adversarial example-generation techniques in the QA field, including textual and multimodal contexts. We examine the techniques employed

Damian Sobota, Lyubomyr Zdomskyy

Improving a result of M. Talagrand, under the assumption of a weak form of Martin's axiom, we construct a totally disconnected compact Hausdorff space $K$ such that the Banach space $C(K)$ of continuous real-valued functions on $K$ is a Grothendieck space but there exists a sequence $(\mu_n)$ of Radon measures on $K$ such that $\mu_n(A)\to0$ for every clopen

Luciano E. Almeida, Douglas G. Macharet

This paper introduces an extension to the Orienteering Problem (OP), called Clustered Orienteering Problem with Subgroups (COPS). In this variant, nodes are arranged into subgroups, and the subgroups are organized into clusters. A reward is associated with each subgroup and is gained only if all of its nodes are visited; however, at most one subgroup can be

Purwoko Haryadi Santoso, Edi Istiyono, Haryanto, Heri Retnawati

Light phenomena conceptual assessment (LPCA) is a conceptual survey of light phenomena that has been recently established by the physics education research (PER) scholars. Studying the LPCA psychometric properties is always imperative to inform its measurement validity to potential LPCA users or beyond general educational researchers. Classical Test Theory (

Joshua Cooper, Utku Okur

We show that, in general, the characteristic polynomial of a hypergraph is not determined by its ``polynomial deck'', the multiset of characteristic polynomials of its vertex-deleted subgraphs, thus settling the ``polynomial reconstruction problem'' for hypergraphs in the negative. The proof proceeds by showing that a construction due to Kocay of an infinite

Qiaoyu Zheng, Weike Zhao, Chaoyi Wu, Xiaoman Zhang

Developing a generalist radiology diagnosis system can greatly enhance clinical diagnostics. In this paper, we introduce RadDiag, a foundational model supporting 2D and 3D inputs across various modalities and anatomies, using a transformer-based fusion module for comprehensive disease diagnosis. Due to patient privacy concerns and the lack of large-scale rad

Maryam Hadipour, Soroush Haseli, Saeed Haddadi

We investigate the relationship between quantum speed limit time and the non-Markovianity of an atom in structured environments. We show that there exists an inverse relation between them, which means that the non-Markovian feature of the quantum process leads to speedup of the process. Our results might shed light on the relationship between the speedup of

Yuhang He, Zhuangzhuang Dai, Long Chen, Niki Trigoni

In this paper, we study an underexplored, yet important and challenging problem: counting the number of distinct sounds in raw audio characterized by a high degree of polyphonicity. We do so by systematically proposing a novel end-to-end trainable neural network (which we call DyDecNet, consisting of a dyadic decomposition front-end and backbone network), an

Timo Spinde, Smi Hinterreiter, Fabian Haak, Terry Ruas

The way the media presents events can significantly affect public perception, which in turn can alter people's beliefs and views. Media bias describes a one-sided or polarizing perspective on a topic. This article summarizes the research on computational methods to detect media bias by systematically reviewing 3140 research papers published between 2019 and

Craig Hogan, Ohkyung Kwon, Stephan S. Meyer, Nathaniel Selub

Anisotropy of space-time is measured on the scale of the cosmic horizon, using the angular correlation function $C(\Theta)$ of cosmic microwave background (CMB) temperature at large angular separation $\Theta$. Even-parity correlation $C_{\rm even}(\Theta)$ is introduced to obtain a direct, precise measure of horizon-scale curvature anisotropy independent of

Leonid V. Kovalev

The existence of a median-type ternary operation on a metric space is known to have a number of implications for the geometry of the space. For such operations, if two of the three arguments coincide, they also coincide with the output of the operation. We consider ternary operations with the opposite property: if two of the arguments coincide, the output is

Mengyao Lyu, Yuhong Yang, Haiwen Hong, Hui Chen

The prevalent use of commercial and open-source diffusion models (DMs) for text-to-image generation prompts risk mitigation to prevent undesired behaviors. Existing concept erasing methods in academia are all based on full parameter or specification-based fine-tuning, from which we observe the following issues: 1) Generation alternation towards erosion: Para

Benjamin Clavié

As language-specific training data tends to be sparsely available compared to English, document retrieval in many languages has been largely relying on multilingual models. In Japanese, the best performing deep-learning based retrieval approaches rely on multilingual dense embedders, with Japanese-only models lagging far behind. However, multilingual models

Pierfrancesco Beneventano

This article examines the implicit regularization effect of Stochastic Gradient Descent (SGD). We consider the case of SGD without replacement, the variant typically used to optimize large-scale neural networks. We analyze this algorithm in a more realistic regime than typically considered in theoretical works on SGD, as, e.g., we allow the product of the le

Fahri Wisnu Murti, Samad Ali, Matti Latva-aho

Multi-access Edge Computing (MEC) can be implemented together with Open Radio Access Network (O-RAN) over commodity platforms to offer low-cost deployment and bring the services closer to end-users. In this paper, a joint O-RAN/MEC orchestration using a Bayesian deep reinforcement learning (RL)-based framework is proposed that jointly controls the O-RAN func

Sudip Dhakal, Dominic Carrillo, Deyuan Qu, Michael Nutt

In recent times, there has been a notable surge in multimodal approaches that decorates raw LiDAR point clouds with camera-derived features to improve object detection performance. However, we found that these methods still grapple with the inherent sparsity of LiDAR point cloud data, primarily because fewer points are enriched with camera-derived features f