April 2023 arXiv papers — page 56

Andrea Aler Tubella, Dimitri Coelho Mollo, Adam Dahlgren Lindström, Hannah Devinney

Fairness is central to the ethical and responsible development and use of AI systems, with a large number of frameworks and formal notions of algorithmic fairness being available. However, many of the fairness solutions proposed revolve around technical considerations and not the needs of and consequences for the most impacted communities. We therefore want

David Ifeoluwa Adelani, Marek Masiak, Israel Abebe Azime, Jesujoba Alabi

African languages are severely under-represented in NLP research due to lack of datasets covering several NLP tasks. While there are individual language specific datasets that are being expanded to different tasks, only a handful of NLP tasks (e.g. named entity recognition and machine translation) have standardized benchmark datasets covering several geograp

Dave Costenaro

Income and wealth allocation are foundational components of how economies operate. These are complex distributions, and it is hard to get a real sense for their dynamics using simplifications like average or median. One metric that characterizes such distributions better is the Gini Index, which on one extreme is 0, a completely equitable distribution, and o

Huayu Li, Xiwen Chen, Gregory Ditzler, Janet Roveda

Knowledge distillation constitutes a potent methodology for condensing substantial neural networks into more compact and efficient counterparts. Within this context, softmax regression representation learning serves as a widely embraced approach, leveraging a pre-established teacher network to guide the learning process of a diminutive student network. Notab

J. Middelhuis, R. Lo Bianco, E. Scherzer, Z. A. Bukhsh

Efficient allocation of resources to activities is pivotal in executing business processes but remains challenging. While resource allocation methodologies are well-established in domains like manufacturing, their application within business process management remains limited. Existing methods often do not scale well to large processes with numerous activiti

Srimanta Maity, Garima Arora

The response of a two-dimensional plasma crystal to an externally imposed initial perturbation has been explored using molecular dynamics (MD) simulations. A two-dimensional (2D) monolayer of micron-sized charged particles (dust) is formed in the plasma environment under certain conditions. The particles interacting via Yukawa pair potential are confined in

Erika Benítez, Héctor Ibarra-Medel, Castalia Alenka Negrete, Irene Cruz-González

Triple AGN systems are expected to be the result of the hierarchical model of galaxy formation. Since there are very few of them confirmed as such, we present the results of a new study of the triple-AGN candidate SDSS J102700.40+174900.8 (center nucleus) through observations with $\it{GTC}$-$\it{MEGARA}$ Integral Field Unit. 1D and 2D analysis of the line r

V. Avila-Reese, H. Ibarra-Medel, I. Lacerna, A. Rodríguez-Puebla

Using spatially-resolved fossil record analysis on a large sample of 'red and dead' elliptical galaxies (classical ellipticals, CLEs) from the MaNGA/SDSS-IV DR15 survey, we reconstruct the archaeological evolution of their radial gradients in mass-to-luminosity ratio ($M/L$), $g-r$ color, and specific star formation (SF) rate. We also calculate other metrics

Katsushi Ikeuchi, Jun Takamatsu, Kazuhiro Sasabuchi, Naoki Wake

Utilizing a robot in a new application requires the robot to be programmed at each time. To reduce such programmings efforts, we have been developing ``Learning-from-observation (LfO)'' that automatically generates robot programs by observing human demonstrations. One of the main issues with introducing this LfO system into the domain of household tasks is t

Yiming Jiang, Jiangfan Zhang

Recently, blockchain has been applied in various fields to secure data exchanges and storage in decentralized systems. In a blockchain application where the task of the application which makes use of the data stored in a blockchain has to be accomplished by a time instant, the employed blockchain is essentially finitely-long. In this paper, we consider a gen

Brandon M. Matthews, Cooper Dix, Ohad Shemmer, Michael S. Brotherton

Quasars at $z~{\gtrsim}~1$ most often have redshifts measured from rest-frame ultraviolet emission lines. One of the most common such lines, C IV ${\lambda}1549$, shows blueshifts up to ${\approx}~5000~\rm{km~s^{-1}}$, and in rare cases even higher. This blueshifting results in highly uncertain redshifts when compared to redshift determinations from rest-fra

Jake Levinson, David Stapleton, Brooke Ullery

In this paper we study the degrees of irrationality of hypersurfaces of large degree in a complex projective variety. We show that the maps computing the degrees of irrationality of these hypersurfaces factor through rational fibrations of the ambient variety. As a consequence, we give tight bounds on the degree of irrationality of these hypersurfaces in ter

Siddhartha Solanki, Manohar lal, Vineet Kumar Agotiya

In this work, we have studied the dissociation behavior of 1S and 2S states of quarkonium using quasi-particle approach where the Debye mass depends on baryonic chemical potential. The binding energies of the quarkonium states has been obtained by using quasi-particle Debye mass which further depends on temperature and baryonic chemical potential ({mu}_b). T

Jian He, Chenxi Yang, Zhaoyuan He, Ghufran Baig

Deep neural networks (DNNs) have been widely used in various video analytic tasks. These tasks demand real-time responses. Due to the limited processing power on mobile devices, a common way to support such real-time analytics is to offload the processing to an edge server. This paper examines how to speed up the edge server DNN processing for multiple clien

Hui Jiang

Languages are not created randomly but rather to communicate information. There is a strong association between languages and their underlying meanings, resulting in a sparse joint distribution that is heavily peaked according to their correlations. Moreover, these peak values happen to match with the marginal distribution of languages due to the sparsity. W

Joshua J. Hibbard, David Rapetti, Jack O. Burns, Nivedita Mahesh

Accurate detection of the cosmological 21-cm global signal requires galactic foreground models which can remove power over ~$10^6$. Although foreground and global signal models unavoidably exhibit overlap in their vector-spaces inducing bias error in the extracted signal, a second source of bias and error arises from inadequate foreground models, i.e. models

Hamza Kheddar, Yassine Himeur, Ali Ismail Awad

Globally, the external internet is increasingly being connected to industrial control systems. As a result, there is an immediate need to protect these networks from a variety of threats. The key infrastructure of industrial activity can be protected from harm using an intrusion detection system (IDS), a preventive mechanism that seeks to recognize new kinds

Remco van der Hofstad, Seva Shneer

We study a model for the spread of fake news, where first a piece of fake news is spread from a location in a network, followed by a correction to the news. We assume that both the fake as well as correct news travel as first-passage percolations or SI epidemics with i.i.d.\ traversal times, possibly with different distributions and dependence. We make the (

Dong Won Lee, Yubin Kim, Rosalind Picard, Cynthia Breazeal

As we move closer to real-world AI systems, AI agents must be able to deal with multiparty (group) conversations. Recognizing and interpreting multiparty behaviors is challenging, as the system must recognize individual behavioral cues, deal with the complexity of multiple streams of data from multiple people, and recognize the subtle contingent social excha

Ekaterina Artemova, Barbara Plank

Bilingual word lexicons are crucial tools for multilingual natural language understanding and machine translation tasks, as they facilitate the mapping of words in one language to their synonyms in another language. To achieve this, numerous papers have explored bilingual lexicon induction (BLI) in high-resource scenarios, using a typical pipeline consisting

Faezeh Shirmohammadi, Deyan Draganov, Johno van IJsseldijk, Ranajit Ghose

The overburden structures often can distort the responses of the target region in seismic data, especially in land datasets. Ideally, all effects of the overburden and underburden structures should be removed, leaving only the responses of the target region. This can be achieved using the Marchenko method. The Marchenko method is capable of estimating Green'

Alexandra Kuznetsova

We study obstructions to rationality on a nodal Fano threefold $M$ that is a double cover of a smooth quadric threefold ramified over an intersection with a quartic threefold in $\mathbb{P}^4$. We prove that if $M$ admits an Artin--Mumford obstruction to rationality then it lies in one of three explicitly described families. Conversely, a general element of

Zachary Richards, Angela M. Kelly

The present study examined demographic and academic predictors of astronomy performance of community college students enrolled in astronomy courses in a large suburban community college. The theoretical framework was based upon a deconstructive approach for predicting community college performance whereby students academic pathways through higher education i

Gianluca Palermo, Gianmarco Accordi, Davide Gadioli, Emanuele Vitali

Today digital revolution is having a dramatic impact on the pharmaceutical industry and the entire healthcare system. The implementation of machine learning, extreme-scale computer simulations, and big data analytics in the drug design and development process offers an excellent opportunity to lower the risk of investment and reduce the time to the patient.

Franc Grootjen, Nikolai Schauer

This article describes an efficient way to implement the multiplication instructions for a RISCV processor. Instead of using three predefined IP blocks for signed, unsigned and mixed multiplication, this article presents a novel extension to the Baugh-Wooley multiplication algorithm which reduces area and power consumption with roughly a factor three.

Yue Zhang

The minimal volume of orientable hyperbolic manifolds with a given number of cusps has been found for $0,1,2,4$ cusps, while the minimal volume of 3-cusped orientable hyperbolic manifolds remains unknown. By using guts in sutured manifolds and pared manifolds, we are able to show that for an orientable hyperbolic 3-manifold with 3 cusps such that every secon

Guanfang Dong, Chenqiu Zhao, Xichen Pan, Anup Basu

The goal of moving object segmentation is separating moving objects from stationary backgrounds in videos. One major challenge in this problem is how to develop a universal model for videos from various natural scenes since previous methods are often effective only in specific scenes. In this paper, we propose a method called Learning Temporal Distribution a

Aishwarya Deep Shukla, Laksh Agarwal, Jie Mein, Goh

The proliferation of fake reviews of doctors has potentially detrimental consequences for patient well-being and has prompted concern among consumer protection groups and regulatory bodies. Yet despite significant advancements in the fields of machine learning and natural language processing, there remains limited comprehension of the characteristics differe

E. Guendelman

The specific model studied is in the context of the modified measure formulation the string or branes where tension appear as an additional dynamical degree of freedom . We then consider the signed reparametrization invariant volume element formulation of dynamical strings and branes and find that the dynamical tension can produce positive tensions or negati

Snigdha Das, Yabo Niu, Yang Ni, Bani K. Mallick

Posterior computation in hierarchical Dirichlet process (HDP) mixture models is an active area of research in nonparametric Bayes inference of grouped data. Existing literature almost exclusively focuses on the Chinese restaurant franchise (CRF) analogy of the marginal distribution of the parameters, which can mix poorly and has a quadratic complexity with t

S. S. Agaev, K. Azizi, B. Barsbay, H. Sundu

The fully heavy scalar tetraquarks $T_{\mathrm{4Q}}=QQ\overline{Q}\overline{Q }$, ($Q=c, b$) are explored in the context of QCD sum rule method. We model $ T_{\mathrm{4Q}}$ as diquark-antidiquark systems composed of pseudoscalar constituents, and calculate their masses $m^{(\prime)}$ and couplings $ f^{(\prime)}$ within the two-point sum rule approach. Our r

Tyler Moulton, Simon T Hodgkin, Gareth D Smith, Joshua T Briegal

The dipper is a novel class of young stellar object associated with large drops in flux on the order of 10 to 50 per cent lasting for hours to days. Too significant to arise from intrinsic stellar variability, these flux drops are currently attributed to disk warps, accretion streams, and/or transiting circumstellar dust. Dippers have been previously studied

Alan Q. Wang, Evan M. Yu, Adrian V. Dalca, Mert R. Sabuncu

We present KeyMorph, a deep learning-based image registration framework that relies on automatically detecting corresponding keypoints. State-of-the-art deep learning methods for registration often are not robust to large misalignments, are not interpretable, and do not incorporate the symmetries of the problem. In addition, most models produce only a single

Lev Sakhnovich

The oscillations described by periodic functions play an important role in many areas. In the present paper, we study periodic functions which belong to the class of the $n$-member chains. The self-intersection and local singular points of these periodic functions are constructed. We consider several classical curves in two and three dimensions. We also intr

G. C. Mancuso, D. Altamirano, P. Bult, J. Chenevez

We report the discovery of millihertz quasi-periodic oscillations (mHz QPOs) from the neutron star (NS) low-mass X-ray binary 4U 1730--22 using the Neutron Star Interior Composition Explorer (NICER). After being inactive for almost 50 years, 4U 1730--22 went into outburst twice between June and August 2021, and between February and July 2022. We analyse all

Raj Kumar Sadhu, Marine Luciano, Wang Xi, Cristina Martinez-Torres

Cells often migrate on curved surfaces inside the body, such as curved tissues, blood vessels or highly curved protrusions of other cells. Recent \textit{in-vitro} experiments provide clear evidence that motile cells are affected by the curvature of the substrate on which they migrate, preferring certain curvatures to others, termed ``curvotaxis". The origin

Daniel Sanz-Alonso, Nathan Waniorek

This paper analyzes a popular computational framework to solve infinite-dimensional Bayesian inverse problems, discretizing the prior and the forward model in a finite-dimensional weighted inner product space. We demonstrate the benefit of working on a weighted space by establishing operator-norm bounds for finite element and graph-based discretizations of M

Wim van Ackooij, Pedro Pérez-Aros, Claudia Soto

Probability functions appear in constraints of many optimization problems in practice and have become quite popular. Understanding their first-order properties has proven useful, not only theoretically but also in implementable algorithms, giving rise to competitive algorithms in several situations. Probability functions are built up from a random vector bel

Azadeh Aghaeeyan, Pouria Ramazi, Mark A. Lewis

Efficient coverage for newly developed vaccines requires knowing which groups of individuals will accept the vaccine immediately and which will take longer to accept or never accept. Of those who may eventually accept the vaccine, there are two main types: success-based learners, basing their decisions on others' satisfaction, and myopic rationalists, attend

Jan Křetínský, Tobias Meggendorfer, Maximilian Weininger

A classic solution technique for Markov decision processes (MDP) and stochastic games (SG) is value iteration (VI). Due to its good practical performance, this approximative approach is typically preferred over exact techniques, even though no practical bounds on the imprecision of the result could be given until recently. As a consequence, even the most use

Tanmoy Bhattacharya, Vincenzo Cirigliano, Rajan Gupta, Emanuele Mereghetti

We present a lattice QCD study of the contribution of the isovector quark chromo-electric dipole moment (qcEDM) operator to the nucleon electric dipole moments (nEDM). The calculation was carried out on four 2+1+1-flavor of highly improved staggered quark (HISQ) ensembles using Wilson-clover quarks to construct correlation functions. This clover-on-HISQ form

Zhiyuan Wang, Mingyue Tang, Maria A. Larrazabal, Emma R. Toner

Individuals high in social anxiety symptoms often exhibit elevated state anxiety in social situations. Research has shown it is possible to detect state anxiety by leveraging digital biomarkers and machine learning techniques. However, most existing work trains models on an entire group of participants, failing to capture individual differences in their psyc

Lev Spodyneiko

After projection to the lowest Landau level translational invariance and particle conservation combine into dipole symmetry. We show that the new symmetry forbids spontaneous $U(1)$ symmetry breaking at zero temperature. In the case of the spatially inhomogeneous magnetic field, where the translational invariance is absent, we show that the dipole symmetry d

Matteo Ravasi, Nick Luiken

Projection Over Convex Sets (POCS) is one of the most widely used algorithms in geophysical data processing to interpolate seismic data. Whilst usually described as a modification of the Gerchberg-Saxton algorithm, a formal understanding of the underlying objective function and its implication for the associated optimization process is lacking to date in the

Vincent Ouazan-Reboul, Ramin Golestanian, Jaime Agudo-Canalejo

Mixtures of particles that interact through phoretic effects are known to aggregate if they belong to species that exhibit attractive self-interactions. We study self-organization in a model metabolic cycle composed of three species of catalytically-active particles that are chemotactic towards the chemicals that define their connectivity network. We find th

A. V. Glushkov, K. G. Lebedev, A. V. Sabourov

Lateral distribution functions of particles in extensive air showers with the energy $E_0 \simeq 10^{19}$ eV recorded by ground-based and underground scintillation detectors with a threshold of $E_{\mu} \simeq 1.0 \times \sec\theta$ GeV at the Yakutsk array during the continuous observations from 1986 to 2016 have been analyzed using events with zenith angle

Yiming Xing, Georgios Fellouris

The problem of simultaneously testing the marginal distributions of sequentially monitored, independent data streams is considered. The decisions for the various testing problems can be made at different times, using data from all streams, which can be monitored until all decisions have been made. Moreover, arbitrary a priori bounds are assumed on the number

Md Zobaer Islam, Sabit Ekin, John F. O'Hara

The increasing demand for wireless sensing systems has led to the exploration of alternative technologies to overcome the spectrum scarcity of traditional approaches based on radio frequency (RF) waves or microwaves. Incoherent light sources such as light-emitting diodes (LED), paired with light sensors, have the potential to become an attractive option for

Jean-Sébastien Brouillon, Florian Dörfler, Giancarlo Ferrari-Trecate

The increasing availability of sensing techniques provides a great opportunity for engineers to design state estimation methods, which are optimal for the system under observation and the observed noise patterns. However, these patterns often do not fulfill the assumptions of existing methods. We provide a direct method using samples of the noise to create a

Jiří Balun, Tomáš Masopust, Petr Osička

Opacity is a property of privacy and security applications asking whether, given a system model, a passive intruder that makes online observations of system's behaviour can ascertain some "secret" information of the system. Deciding opacity is a PSpace-complete problem, and hence there are no polynomial-time algorithms to verify opacity under the assumption

Vesa Akerman, David Baines, Damien Daspit, Ulf Hermjakob

Efficiently and accurately translating a corpus into a low-resource language remains a challenge, regardless of the strategies employed, whether manual, automated, or a combination of the two. Many Christian organizations are dedicated to the task of translating the Holy Bible into languages that lack a modern translation. Bible translation (BT) work is curr

Ignacio Erazo

Increased data availability has stimulated the interest in studying sports prediction problems via analytical approaches; in particular, with machine learning and simulation. We characterize several models that have been proposed in the literature, all of which suffer from the same drawback: they cannot incorporate rational decision-making and strategies fro

J. K. Singh, Shaily, Anirudh Pradhan, Aroonkumar Beesham

In this paper, we consider a cosmological model in $ f(R, G) $ gravity in a flat space-time, where $ R $ is the Ricci scalar and $ G $ is the Gauss-Bonnet invariant. The function $ f(R, G) $ is taken as a linear combination of $ R $ and an exponential function of $ G $. We analyze the observational constraints under a power law cosmology which depends on two

TianZhang He, Adel N. Toosi, Negin Akbari, Muhammed Tawfiqul Islam

The rapid development of emerging vehicular edge computing (VEC) brings new opportunities and challenges for dynamic resource management. The increasing number of edge data centers, roadside units (RSUs), and network devices, however, makes resource management a complex task in VEC. On the other hand, the exponential growth of service applications and end-us

Di Wang, Jing Zhang, Bo Du, Liangpei Zhang

Hyperspectral image (HSI) classification is challenging due to spatial variability caused by complex imaging conditions. Prior methods suffer from limited representation ability, as they train specially designed networks from scratch on limited annotated data. We propose a tri-spectral image generation pipeline that transforms HSI into high-quality tri-spect

Sara Major, Aleksandar Tomašević

Populist rhetoric employed on online media is characterized as deeply impassioned and often imbued with strong emotions. The aim of this paper is to empirically investigate the differences in affective nonverbal communication of political leaders. We use a deep-learning approach to process a sample of 220 YouTube videos of political leaders from 15 different

Md. Adyelullahil Mamun, Hasnat Md. Abdullah, Md. Golam Rabiul Alam, Muhammad Mehedi Hassan

Human conversational styles are measured by the sense of humor, personality, and tone of voice. These characteristics have become essential for conversational intelligent virtual assistants. However, most of the state-of-the-art intelligent virtual assistants (IVAs) are failed to interpret the affective semantics of human voices. This research proposes an an

Sanghyun Jo, In-Jae Yu, Kyungsu Kim

Weakly-supervised semantic segmentation aims to reduce labeling costs by training semantic segmentation models using weak supervision, such as image-level class labels. However, most approaches struggle to produce accurate localization maps and suffer from false predictions in class-related backgrounds (i.e., biased objects), such as detecting a railroad wit

Claudia Quinteros Cartaya, Jonas Koehler, Wei Li, Johannes Faber

High rate Global Navigation Satellite System (HR GNSS) data can be highly useful for earthquake analysis as it provides continuous high-rate measurements of ground motion. This data can be used to estimate the magnitude, to assess the potential of an earthquake for generating tsunamis, and to analyze diverse parameters related to the seismic source. Particul

Pavel E. Dolgirev, Kushal Seetharam, Márton Kanász-Nagy, Carsten Robens

The Boltzmann equation is a powerful theoretical tool for modeling the collective dynamics of quantum many-body systems subject to external perturbations. Analysis of the equation gives access to linear response properties including collective modes and transport coefficients, but often proves intractable due to computational costs associated with multidimen

Sadia Humaira Salsabil, Golam Dastegir Al-Quaderi, M. R. C. Mahdy

The area of trapping the atoms or molecules using light has advanced tremendously in the last few decades. In contrast, the idea of controlling (not only trapping) the movement of atomic-sized particles using quantum mechanical matter waves is a completely new emerging area of particle manipulation. Though a single previous report has suggested the pulling o

N. Javanmardi, P. Borja, M. J. Yazdanpanah, J. M. A. Scherpen

In this paper, the notion of contraction is used to solve the trajectory-tracking problem for a class of mechanical systems. Additionally, we propose a dynamic extension to remove velocity measurements from the controller while rejecting matched disturbances. In particular, we propose three control designs stemming from the Interconnection and Damping Assign

Aranya Bhattacharya, Arpan Bhattacharyya, Ayan K. Patra

Recently, it has been argued in [1] that Jackiw-Teitelboim (JT) gravity can be naturally realized in the Karch-Randall braneworld in $(2+1)$ dimensions. Using the `complexity=volume' proposal, we studied this model and computed the holographic complexity of the JT gravity from the bulk perspective. We find that the complexity grows linearly with boundary tim

Dipankar Chakrabarti, Poonam Choudhary, Bheemsehan Gurjar, Raj Kishore

We formulate a light-front spectator model for the proton incorporating the gluonic degree of freedom. In this model, at high energy scattering of the proton, the active parton is a gluon and the rest is viewed as a spin-$\frac{1}{2}$ spectator with an effective mass. The light front wave functions of the proton are constructed using a soft wall AdS/QCD pred

Volodymyr Ihnatovych

The article reveals the error that in classical thermodynamics leads to the Gibbs paradox. The essence of the error lies in the fact that the entropy of an ideal gas is attributed to additive quantities, but it is not correct. The value of an additive quantity for a whole object is equal to the sum of its values for the parts of the object in any division of

Kaijie Yang, Zian Xu, Yanjie Feng, Frank Schindler

We studied electronic band structure and topological property of a topological insulator thin film under a moir\'e superlattice potential to search for two-dimensional (2D) $\mathbb Z_2$ non-trivial isolated mini-bands. To model this system, we assume the Fermi energy inside the bulk band gap and thus consider an effective model Hamiltonian with only two sur

Federico Rottoli, Sara Murciano, Pasquale Calabrese

The negativity Hamiltonian, defined as the logarithm of a partially transposed density matrix, provides an operatorial characterisation of mixed-state entanglement. However, so far, it has only been studied for the mixed-state density matrices corresponding to subsystems of globally pure states. Here, we consider as a genuine example of a mixed state the one

Cal Peyser, Michael Picheny, Kyunghyun Cho, Rohit Prabhavalkar

Unpaired text and audio injection have emerged as dominant methods for improving ASR performance in the absence of a large labeled corpus. However, little guidance exists on deploying these methods to improve production ASR systems that are trained on very large supervised corpora and with realistic requirements like a constrained model size and CPU budget,

S. H. Bruun, J. Hjorth, A. Agnello

Context. Large, high-dimensional astronomical surveys require efficient data analysis. Automatic fitting of lightcurve variability and machine learning may assist in identification of sources including candidate quasars. Aims. We aim to classify sources from the Palomar Transient Factory (PTF) as quasars, stars or galaxies, and to examine model performance u

Fan Zou, W. N. Brandt, Qingling Ni, Shifu Zhu

Active dwarf galaxies are important because they contribute to the evolution of dwarf galaxies and can reveal their hosted massive black holes. However, the sample size of such sources beyond the local universe is still highly limited. In this work, we search for active dwarf galaxies in the recently completed XMM-Spitzer Extragalactic Representative Volume

S. H. Bruun, A. Agnello, J. Hjorth

Context. Lightcurve variability is well-suited for characterising objects in surveys with high cadence and long baseline. This is especially relevant in view of the large datasets to be produced by the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST). Aims. We aim to determine variability parameters for objects in the Palomar Transient Factor

Tianzheng Guo, Xiaoyu Zou, Shalini Sundar, Xinqiao Jia

Recent advances recognize that the viscoelastic properties of epithelial structures play important roles in biology and disease modeling. However, accessing the viscoelastic properties of multicellular structures in mechanistic or drug-screening applications face challenges in repeatability, accuracy, and practical implementation. Here, we present a microflu

Benjamin J. Gibson, Gail Zasowski, Anil Seth, Aishwarya Ashok

We present analysis of nearly 1,000 near-infrared, integrated light spectra from APOGEE in the inner $\sim$7 kpc of M31. We utilize full spectrum fitting with A-LIST simple stellar population spectral templates that represent a population of stars with the same age, [M/H], and [$\alpha$/M]. With this, we determine the mean kinematics, metallicities, $\alpha$

Aleksander M. Kubicki, Alex May, David Pérez-Garcia

Within the setting of the AdS/CFT correspondence, we ask about the power of computers in the presence of gravity. We show that there are computations on $n$ qubits which cannot be implemented inside of black holes with entropy less than $O(2^n)$. To establish our claim, we argue computations happening inside the black hole must be implementable in a programm

Gian Gentinetta, David Sutter, Christa Zoufal, Bryce Fuller

Quantum support vector machines have the potential to achieve a quantum speedup for solving certain machine learning problems. The key challenge for doing so is finding good quantum kernels for a given data set -- a task called kernel alignment. In this paper we study this problem using the Pegasos algorithm, which is an algorithm that uses stochastic gradie

Yuguang Chen, Tucker Jones, Ryan Sanders, Dario Fadda

The heavy element content ("metallicity") of the Universe is a record of the total star formation history. Gas-phase metallicity in galaxies, as well as its evolution with time, is of particular interest as a tracer of accretion and outflow processes. However, metallicities from the widely-used electron temperature ($T_e$) method are typically ~2x lower than

Fernando Hidalgo-Pineda, Ryan Jeffrey Farber, Max Gronke

Rapidly outflowing cold H-I gas is ubiquitously observed to be co-spatial with a hot phase in galactic winds, yet the ablation time of cold gas by the hot phase should be much shorter than the acceleration time. Previous work showed efficient radiative cooling enables clouds to survive in hot galactic winds under certain conditions, as can magnetic fields ev

Travis S. Metcalfe, Klaus G. Strassmeier, Ilya V. Ilyin, Jennifer L. van Saders

During the first half of their main-sequence lifetimes, stars rapidly lose angular momentum to their magnetized winds, a process known as magnetic braking. Recent observations suggest a substantial decrease in the magnetic braking efficiency when stars reach a critical value of the Rossby number, the stellar rotation period normalized by the convective overt

Alfred Amruth, Tom Broadhurst, Jeremy Lim, Masamune Oguri

Unveiling the true nature of Dark Matter (DM), which manifests itself only through gravity, is one of the principal quests in physics. Leading candidates for DM are weakly interacting massive particles (WIMPs) or ultralight bosons (axions), at opposite extremes in mass scales, that have been postulated by competing theories to solve deficiencies in the Stand

Feige Wang, Jinyi Yang, Joseph F. Hennawi, Xiaohui Fan

We present the first results from the JWST ASPIRE program (A SPectroscopic survey of biased halos In the Reionization Era). This program represents an imaging and spectroscopic survey of 25 reionization-era quasars and their environments by utilizing the unprecedented capabilities of NIRCam Wide Field Slitless Spectroscopy (WFSS) mode. ASPIRE will deliver th

Julian Heeck, Jan Heisig, Anil Thapa

The nature of neutrino masses and the matter-antimatter asymmetry of our universe are two of the most important open problems in particle physics today and are notoriously difficult to test with current technology. Dirac neutrinos offer a solution through a leptogenesis mechanism that hinges on the smallness of neutrino masses and resultant non-thermalizatio

Soumi Ghosh, Manas Kulkarni, Sthitadhi Roy

The dynamics of non-Hermitian quantum systems have taken on an increasing relevance in light of quantum devices which are not perfectly isolated from their environment. The interest in them also stems from their fundamental differences from their Hermitian counterparts, particularly with regard to their spectral and eigenvector correlations. These correlatio

Muhammad Akram, Emilian Marius Nica, Yuan-Ming Lu, Onur Erten

We study the phase diagram of the Yao-Lee model with Kitaev-type spin-orbital interactions in the presence of Dzyaloshinskii-Moriya interactions and external magnetic fields. Unlike the Kitaev model, the Yao-Lee model can still be solved exactly under these perturbations due to the enlarged local Hilbert space. Through a variational analysis, we obtain a ric

Alexander P. Stephan, B. Scott Gaudi

For the majority of short period exoplanets transiting massive stars with radiative envelopes, the spin angular momentum of the host star is greater than the planetary orbital angular momentum. In this case, the orbits of the planets will undergo nodal precession, which can significantly impact the probability that the planets transit their parent star. In p

Pratyusava Baral, Soichiro Morisaki, Ignacio Magaña Hernandez, Jolien D. E. Creighton

Next-generation ground-based gravitational-wave detectors, such as Cosmic Explorer (CE), are expected to be sensitive to gravitational-wave signals with frequencies as low as 5 Hz, allowing signals to spend a significant amount of time in the detector frequency band. As a result, the effects caused by the rotation of the Earth become increasingly important f

Jinyi Yang, Feige Wang, Xiaohui Fan, Joseph F. Hennawi

Studies of rest-frame optical emission in quasars at $z>6$ have historically been limited by the wavelengths accessible by ground-based telescopes. The James Webb Space Telescope (JWST) now offers the opportunity to probe this emission deep into the reionization epoch. We report the observations of eight quasars at $z>6.5$ using the JWST/NIRCam Wide Field Sl

Syuhei Iguro, Teppei Kitahara, Martin S. Lang, Michihisa Takeuchi

In this article, we review and update implications of the muon anomalous magnetic moment (muon $g-2$) anomaly for two-Higgs-doublet models (2HDMs), which are classified according to imposed symmetries and their resulting Yukawa sector. In the minimal setup, the muon $g-2$ anomaly can be accommodated by the type-X (lepto-philic) 2HDM, flavor-aligned 2HDM (FA2

Weiguang Cao, Linhao Li, Masahito Yamazaki, Yunqin Zheng

We explore non-invertible symmetries in two-dimensional lattice models with subsystem $\mathbb Z_2$ symmetry. We introduce a subsystem $\mathbb Z_2$-gauging procedure, called the subsystem Kramers-Wannier transformation, which generalizes the ordinary Kramers-Wannier transformation. The corresponding duality operators and defects are constructed by gaugings

Claudio Chamon, Eduardo R. Mucciolo, Andrei E. Ruckenstein, Zhi-Cheng Yang

We propose a mechanism for reaching pseudorandom quantum states, computationally indistinguishable from Haar random, with shallow log-n depth quantum circuits, where n is the number of qudits. We argue that $\log n$ depth 2-qubit-gate-based generic random quantum circuits that are claimed to provide a lower bound on the speed of information scrambling, canno

Ian Banta, Timothy Cohen, Nathaniel Craig, Xiaochuan Lu

We revisit the effective field theory of the two Higgs doublet model at tree level. The introduction of a novel basis in the UV theory allows us to derive matching coefficients in the effective description that resum important contributions from the Higgs vacuum expectation value. The new basis typically provides a significantly better approximation of the f

Luc Darmé, Céline Degrande, Claude Duhr, Benjamin Fuks

We present an update of the Universal FeynRules Output model format, commonly known as the UFO format, that is used by several automated matrix-element generators and high-energy physics software. We detail different features that have been proposed as extensions of the initial format during the last ten years, and collect them in the current second version

Christopher E. O'Connor, Lars Bildsten, Matteo Cantiello, Dong Lai

About ten percent of Sun-like ($1$-$2 M_\odot$) stars will engulf a $1$-$10 M_{\rm J}$ planet as they expand during the red giant branch (RGB) or asymptotic giant branch (AGB) phase of their evolution. Once engulfed, these planets experience a strong drag force in the star's convective envelope and spiral inward, depositing energy and angular momentum. For t

M. Brüggen, E. Scannapieco, P. Grete

Motivated by observations of multiphase galaxy outflows, we explore the impact of isotropic and anisotropic electron thermal conduction on the evolution of radiatively-cooled, cold clouds embedded in hot, magnetized winds. Using the adaptive mesh refinement code AthenaPK, we conduct simulations of clouds impacted by supersonic and transonic flows with magnet

Luisa Lucie-Smith, Alexandre Barreira, Fabian Schmidt

We build a deep learning framework that connects the local formation process of dark matter halos to the halo bias. We train a convolutional neural network (CNN) to predict the final mass and concentration of dark matter halos from the initial conditions. The CNN is then used as a surrogate model to derive the response of the halos' mass and concentration to

Shalini Ganguly, Yuan Li, Valeria Olivares, Yuanyuan Su

The intracluster medium (ICM) in the centers of galaxy clusters is heavily influenced by the ``feedback'' from supermassive black holes (SMBHs). Feedback can drive turbulence in the ICM and turbulent dissipation can potentially be an important source of heating. Due to the limited spatial and spectral resolutions of X-ray telescopes, direct observations of t

Sandip Roy, Xuejian Shen, Mariangela Lisanti, David Curtin

Dark sector theories naturally lead to multi-component scenarios for dark matter where a sub-component can dissipate energy through self-interactions, allowing it to efficiently cool inside galaxies. We present the first cosmological hydrodynamical simulations of Milky Way analogues where the majority of dark matter is collisionless Cold Dark Matter (CDM), b

Peter B. Denton, Julia Gehrlein

Recent data from the ATOMKI group continues to confirm their claim of the existence of a new $\sim17$ MeV particle. We review and numerically analyze the data and then put into context constraints from other experiments, notably neutrino scattering experiments such as the latest reactor anti-neutrino coherent elastic neutrino nucleus scattering data and unit

Xianbiao Qi, Jianan Wang, Yihao Chen, Yukai Shi

We present a Lipschitz continuous Transformer, called LipsFormer, to pursue training stability both theoretically and empirically for Transformer-based models. In contrast to previous practical tricks that address training instability by learning rate warmup, layer normalization, attention formulation, and weight initialization, we show that Lipschitz contin

Salish Maharjan, Rui Cheng, Zhaoyu Wang

Fast and accurate estimation of sensitivity matrices is significant for the enhancement of distribution system modeling and automation. Analytical estimations have mainly focused on voltage magnitude sensitivity to active/reactive power injections for unbalance networks with Wye-connected loads and neglecting DERs' smart inverter functionality. Hence, this p

Xiangtai Li, Henghui Ding, Haobo Yuan, Wenwei Zhang

Visual segmentation seeks to partition images, video frames, or point clouds into multiple segments or groups. This technique has numerous real-world applications, such as autonomous driving, image editing, robot sensing, and medical analysis. Over the past decade, deep learning-based methods have made remarkable strides in this area. Recently, transformers,