November 2022 arXiv papers — page 122

Shimin Wang, Ya-Jun Pan, Martin Guay

This paper deals with the state estimation of linear time-invariant systems using distributed observers with local sampled-data measurement and aperiodic communication. Each observer agent perceives partial information of the system to be observed but does not satisfy the observability condition. Consequently, distributed observers are designed to exponentia

Hehui Zheng, Sebastian Pinzello, Barnabas Gavin Cangan, Thomas Buchner

The precise control of soft and continuum robots requires knowledge of their shape, which has, in contrast to classical rigid robots, infinite degrees of freedom. To partially reconstruct the shape, proprioceptive techniques use built-in sensors resulting in inaccurate results and increased fabrication complexity. Exteroceptive methods so far rely on expensi

Christiaan Swanepoel, Mathieu Fourment, Xiang Ji, Hassan Nasif

Probabilistic programming frameworks are powerful tools for statistical modelling and inference. They are not immediately generalisable to phylogenetic problems due to the particular computational properties of the phylogenetic tree object. TreeFlow is a software library for probabilistic programming and automatic differentiation with phylogenetic trees. It

Xingzhuo Chen, David J. Jeffery, Ming Zhong, Levi McClenny

We use physics informed neural networks (PINNs) to solve the radiative transfer equation and calculate a synthetic spectrum for a Type Ia supernova (SN~Ia) SN 2011fe. The calculation is based on local thermodynamic equilibrium (LTE) and 9 elements are included. Physical processes included are approximate radiative equilibrium, bound-bound transitions, and th

Tariq A. Alraqad, Igor Z. Milovanovic, Hicham Saber, Akbar Ali

Let $d_u$ be the degree of a vertex $u$ of a graph $G$. The atom-bond sum-connectivity (ABS) index of a graph $G$ is the sum of the numbers $(1-2(d_v+d_w)^{-1})^{1/2}$ over all edges $vw$ of $G$. This paper gives the characterization of the graph possessing the minimum ABS index in the class of all trees of a fixed number of pendent vertices; the star is the

Josh Alman, Yunfeng Guan, Ashwin Padaki

We give new, smaller constructions of constant-depth linear circuits for computing any matrix which is the Kronecker power of a fixed matrix. A standard argument (e.g., the mixed product property of Kronecker products, or a generalization of the Fast Walsh-Hadamard transform) shows that any such $N \times N$ matrix has a depth-2 circuit of size $O(N^{1.5})$.

Kevin Cheevers, Matei Radulescu

We first address the problem of initiation behind decaying shock waves analytically and numerically. The ignition along a particle path crossing the shock is analysed in terms of its volumetric expansion, evaluated as a function of the shock strength, decay rate, and curvature using the shock change equations. Closed form solutions are derived for 1-step and

William Thong, Jose Costa Pereira, Sarah Parisot, Ales Leonardis

Image quality assessment (IQA) forms a natural and often straightforward undertaking for humans, yet effective automation of the task remains highly challenging. Recent metrics from the deep learning community commonly compare image pairs during training to improve upon traditional metrics such as PSNR or SSIM. However, current comparisons ignore the fact th

Félix Thouin, David M. Myers, Ashutosh Patri, Bill Baloukas

In recent years, the large electric field enhancement and tight spatial confinement supported by the so-called epsilon-near-zero (ENZ) mode have attracted significant attention for the realization of efficient nonlinear optical devices. Here, we experimentally demonstrate a new type of antenna, termed an ENZ photonic gap antenna (PGA), which consists of a di

Shengchao Liu, David Vazquez, Jian Tang, Pierre-André Noël

We explore the downstream task performances for graph neural network (GNN) self-supervised learning (SSL) methods trained on subgraphs extracted from relational databases (RDBs). Intuitively, this joint use of SSL and GNNs should allow to leverage more of the available data, which could translate to better results. However, we found that naively porting cont

Zhen Li, Patrizio Graziosi, Neophytos Neophytou

Mobility is a key parameter for SnO2, which is extensively studied as a practical transparent oxide n-type semiconductor. In experiments, the mobility of electrons in bulk SnO2 single crystals varies from 70 to 260 cm2V-1s-1 at room temperature. Here, we calculate the mobility as limited by electron-phonon and ionized impurity scattering by coupling the Bolt

Daniel Murawski

We show that for every mean zero log-concave real random variable $X$ one has $\|X\|_p \leq \frac{p}{q} \|X\|_q$ for $p \geq q \geq 1$, going beyond the well-known case of symmetric random variables. We also prove that in the class of arbitrary log-concave real random variables for $p>q > 0$ the quantity $\|X\|_p / \|X\|_q$ is maximized for some shifted expo

Kaixiong Zhou, Zhenyu Zhang, Shengyuan Chen, Tianlong Chen

Quantum neural networks (QNNs), an interdisciplinary field of quantum computing and machine learning, have attracted tremendous research interests due to the specific quantum advantages. Despite lots of efforts developed in computer vision domain, one has not fully explored QNNs for the real-world graph property classification and evaluated them in the quant

Rebecca Lin, Marten H. van Kerkwijk, Robert Main, Nikhil Mahajan

The Crab Pulsar is the prime example of an emitter of giant pulses. These short, very bright pulses are thought to originate near the light cylinder, at $\sim\!1600{\rm\;km}$ from the pulsar. The pulsar's location inside the Crab Nebula offers an unusual opportunity to resolve the emission regions, using the nebula, which scatters radio waves, as a lens. We

Forrest Valdez, Viphretuo Mere, Xiaoxi Wang, Shayan Mookherjea

Broadband integrated thin-film lithium niobate (TFLN) electro-optic modulators (EOM) are desirable for optical communications and signal processing in both the O-band (1310 nm) and C-band (1550 nm). To address these needs, we design and demonstrate Mach-Zehnder (MZ) EOM devices in a hybrid platform based on TFLN bonded to foundry-fabricated silicon photonic

Alina Jade Barnett, Zhicheng Guo, Jin Jing, Wendong Ge

In intensive care units (ICUs), critically ill patients are monitored with electroencephalograms (EEGs) to prevent serious brain injury. The number of patients who can be monitored is constrained by the availability of trained physicians to read EEGs, and EEG interpretation can be subjective and prone to inter-observer variability. Automated deep learning sy

Friederike Groschupp, Mark Kuhne, Moritz Schneider, Ivan Puddu

Modern smartphones are complex systems in which control over phone resources is exercised by phone manufacturers, OS vendors, and users. These stakeholders have diverse and often competing interests. Barring some exceptions, users entrust their security and privacy to OS vendors (Android and iOS) and need to accept their constraints. Manufacturers protect th

Yakov Vaisbourd, Rustum Choksi, Ariel Goodwin, Tim Hoheisel

We explore a method of statistical estimation called Maximum Entropy on the Mean (MEM) which is based on an information-driven criterion that quantifies the compliance of a given point with a reference prior probability measure. At the core of this approach lies the MEM function which is a partial minimization of the Kullback-Leibler divergence over a linear

Peter V. Danchev, Patrick W. Keef

For Abelian p-groups, Goldsmith, Salce, et al., introduced the notion of minimal full inertia. In parallel to this, we define the concept of minimal characteristic inertia and explore those p-primary Abelian groups having minimal characteristic inertia. We establish the surprising result that, for each Abelian p-group A, the square A \oplus A has the minimal

Omanshu Thapliyal, Inseok Hwang

Network Control Systems (NCSs) pose unique vulnerabilities to cyberattacks due to a heavy reliance on communication channels. These channels can be susceptible to eavesdropping, false data injection (FDI), and denial of service (DoS). As a result, smarter cyberattacks can employ a combination of techniques to cause degradation of the considered NCS performan

Lifeng Han

With the fast development of Machine Translation (MT) systems, especially the new boost from Neural MT (NMT) models, the MT output quality has reached a new level of accuracy. However, many researchers criticised that the current popular evaluation metrics such as BLEU can not correctly distinguish the state-of-the-art NMT systems regarding quality differenc

Antonio Rodríguez-Sánchez, Simon Haller-Seeber, David Peer, Chris Engelhardt

Affordance detection from visual input is a fundamental step in autonomous robotic manipulation. Existing solutions to the problem of affordance detection rely on convolutional neural networks. However, these networks do not consider the spatial arrangement of the input data and miss parts-to-whole relationships. Therefore, they fall short when confronted wi

S. Lombeyda, S. G. Djorgovski, A. Tran, J. Liu

Use of online platforms for education is a vibrant and growing arena, incorporating a variety of software platforms and technologies, including various modalities of extended reality. We present our Enhanced Reality Teaching Concierge, an open networking hub architected to enable efficient and easy connectivity between a wide variety of services or applicati

James A. Michaelov, Benjamin K. Bergen

Are the predictions of humans and language models affected by similar things? Research suggests that while comprehending language, humans make predictions about upcoming words, with more predictable words being processed more easily. However, evidence also shows that humans display a similar processing advantage for highly anomalous words when these words ar

Daniel Fadel, Eric Loubeau, Andrés J. Moreno, Henrique N. Sá Earp

We develop an abstract theory of flows of geometric $H$-structures, i.e., flows of tensor fields defining $H$-reductions of the frame bundle, for a closed and connected subgroup $H\subset SO(n)$, on any connected and oriented $n$-manifold with sufficient topology to admit such structures. The first part of the article sets up a unifying theoretical framework

Casey Brinkman, James Cadman, Lauren Weiss, Eric Gaidos

Radial velocity (RV) measurements of transiting multiplanet systems allow us to understand the densities and compositions of planets unlike those in the Solar System. Kepler-102, which consists of 5 tightly packed transiting planets, is a particularly interesting system since it includes a super-Earth (Kepler-102d) and a sub-Neptune-sized planet (Kepler-102e

David M. Burn, Shilei Zhang, Gerrit van der Laan, Thorsten Hesjedal

Magnetic diffraction in combination with x-ray detected ferromagnetic resonance (DFMR) is a powerful technique for performing time-resolved measurements on individual spin textures. Here, we study the ferromagnetic resonance (FMR) modes of both the conical and field-polarized phases in the chiral magnet Cu$_2$OSeO$_3$. Following the identification of the FMR

Nets Hawk Katz, Shukun Wu, Joshua Zahl

We prove that every Kakeya set in $\mathbb{R}^3$ formed from lines of the form $(a,b,0) + \operatorname{span}(c,d,1)$ with $ad-bc=1$ must have Hausdorff dimension $3$; Kakeya sets of this type are called $SL_2$ Kakeya sets. This result was also recently proved by F\"assler and Orponen using different techniques. Our method combines induction on scales with a

Yoichiro Tsurimaki, Renwen Yu, Shanhui Fan

A system consisting of two slabs with different temperatures can exhibit a non-equilibrium lateral Casimir force on either one of the slabs when Lorentz reciprocity is broken in at least one of the slabs. This system constitutes a photonic heat engine that converts radiative heat into work done by the non-equilibrium lateral Casimir force. Reversely, by slid

Yi-Ting Tu, Sankar Das Sarma

We analyze a well-known experimental work [J. Crossno et al., Science 351, 1058 (2016)] which reported on the failure of the Wiedemann-Franz law in graphene at $T\sim 10$-$100\,\mathrm{K}$, attributing this failure to the non-Fermi liquid nature of the Dirac fluid associated with undoped intrinsic graphene. In spite of serious theoretical efforts, the report

Pål Østebø Andersen

Solutions are investigated for 1D linear counter-current spontaneous imbibition (COUSI). The diffusion problem is scaled to depend only on a normalized coefficient {\Lambda}_n (S_n ) with mean 1 and no other parameters. A dataset of 5500 functions {\Lambda}_n was generated using combinations of (mixed-wet and strongly water-wet) relative permeabilities, capi

Jussi Behrndt, Markus Holzmann, Christian Stelzer, Georg Stenzel

In this article we develop a systematic approach to treat Dirac operators $A_{\eta, \tau, \lambda}$ with singular electrostatic, Lorentz scalar, and anomalous magnetic interactions of strengths $\eta, \tau, \lambda \in \mathbb{R}$, respectively, supported on points in $\mathbb{R}$, curves in $\mathbb{R}^2$, and surfaces in $\mathbb{R}^3$ that is based on bou

Rakesh Vaideeswaran, Feng Gao, Abhinav Mathur, Govind Thattai

The domain of joint vision-language understanding, especially in the context of reasoning in Visual Question Answering (VQA) models, has garnered significant attention in the recent past. While most of the existing VQA models focus on improving the accuracy of VQA, the way models arrive at an answer is oftentimes a black box. As a step towards making the VQA

Ayan Chatterjee, Qingtao Cao, Amirhossein Sajadi, Babak Ravandi

Interactive programming environments are powerful tools for promoting innovative network thinking, teaching science of complexity, and exploring emergent phenomena. This paper reports on our recent development of the deterministic random walk model in NetLogo, a leading platform for computational thinking, eco-system thinking, and multi-agent cross-platform

Dufour Jean-Paul, Daniel Lehmann

For $(n+1)$-webs by curves in an ambiant $n$-dimensional manifold, we first define a generalization of the well known Blaschke curvature of the dimension two, which vanishes iff the web has the maximum possible rank which is one. But, contrary to the dimension two where all 3-webs of rank one are locally isomorphic, we prove that there are infinitely many cl

Saghar Irandoust, Thibaut Durand, Yunduz Rakhmangulova, Wenjie Zi

Transformers have become central to recent advances in computer vision. However, training a vision Transformer (ViT) model from scratch can be resource intensive and time consuming. In this paper, we aim to explore approaches to reduce the training costs of ViT models. We introduce some algorithmic improvements to enable training a ViT model from scratch wit

Sutapa Ghosh, Gadi Eisenstein

Dual comb spectroscopy (DCS) is a broadband technique offering high resolution and fast data acquisition. We describe a hybrid dual comb spectrometer comprising a broadband commercial fiber laser system offering a wide range of sample interrogation, and an actively mode locked semiconductor laser (MLL) having a widely tunable, relatively narrow spectrum. The

Gonzalo Muñoz, Joseph Paat, Felipe Serrano

The intersection cut framework was introduced by Balas in 1971 as a method for generating cutting planes in integer optimization. In this framework, one uses a full-dimensional convex $S$-free set, where $S$ is the feasible region of the integer program, to derive a cut separating $S$ from a non-integral vertex of a linear relaxation of $S$. Among all $S$-fr

Zishan Gu, Jintang Li, Liang Chen

Graph Neural Networks (GNNs) as deep learning models working on graph-structure data have achieved advanced performance in many works. However, it has been proved repeatedly that, not all edges in a graph are necessary for the training of machine learning models. In other words, some of the connections between nodes may bring redundant or even misleading inf

Tyler R. Scott, Ting Liu, Michael C. Mozer, Andrew C. Gallagher

Recent research in clustering face embeddings has found that unsupervised, shallow, heuristic-based methods -- including $k$-means and hierarchical agglomerative clustering -- underperform supervised, deep, inductive methods. While the reported improvements are indeed impressive, experiments are mostly limited to face datasets, where the clustered embeddings

Raj Sanjay Shah, Faye Holt, Shirley Anugrah Hayati, Aastha Agarwal

Millions of people participate in online peer-to-peer support sessions, yet there has been little prior research on systematic psychology-based evaluations of fine-grained peer-counselor behavior in relation to client satisfaction. This paper seeks to bridge this gap by mapping peer-counselor chat-messages to motivational interviewing (MI) techniques. We ann

Sivaprasad Omanakuttan, T. J. Volkoff

GKP codes encode a qubit in displaced phase space combs of a continuous-variable (CV) quantum system and are useful for correcting a variety of high-weight photonic errors. Here we propose atomic ensemble analogues of the single-mode CV GKP code by using the quantum central limit theorem to pull back the phase space structure of a CV system to the compact ph

Sanda Maria Avram, Mihai Oltean

Determining the author of a text is a difficult task. Here we compare multiple AI techniques for classifying literary texts written by multiple authors by taking into account a limited number of speech parts (prepositions, adverbs, and conjunctions). We also introduce a new dataset composed of texts written in the Romanian language on which we have run the a

Zhaojun Bai, Ding Lu

This paper concerns a class of monotone eigenvalue problems with eigenvector nonlinearities (mNEPv). The mNEPv is encountered in applications such as the computation of joint numerical radius of matrices, best rank-one approximation of third-order partial symmetric tensors, and distance to singularity for dissipative Hamiltonian differential-algebraic equati

Binghui Peng, Aviad Rubinstein

Dynamic algorithms come in three main flavors: $\mathit{incremental}$ (insertions-only), $\mathit{decremental}$ (deletions-only), or $\mathit{fully}$ $\mathit{dynamic}$ (both insertions and deletions). Fully dynamic is the holy grail of dynamic algorithm design; it is obviously more general than the other two, but is it strictly harder? Several works managed

V. Maitreyi, Suresh Elumalai, Selvaraj Balachandran

The recently developed atom-bond sum-connection (ABS) index is a variation of the well-studied graph-based molecular descriptors connectivity (Randic), atom-bond connectivity, and sum-connectivity indices.We present the minimum ABS index of trees with a given number of pendent vertices in this paper, which provides a solution to the problem proposed by A. Al

Runze Yu

We introduce an upper bound of the Betti numbers of a compact Riemannian manifold given integral bounds on the average of the lowest eigenvalues of the curvature operator. We then establish a new curvature condition for the Betti numbers to vanish using the Bochner technique. This generalizes results from Gallot and Petersen-Wink.

N. M. Artemov

The volume function defined by a domain in Euclidean space $\mathbb{R}^n$ is the function on the space of affine hyperplanes equal to volumes cut by these hyperplanes from the domain. The study of these functions originates from the works of Archimedes and Newton and is closely related to the theory of lacunas of hyperbolic partial differential equations.The

Abhishek Banerjee, Gilad Perez, Marianna Safronova, Inbar Savoray

We discuss models of ultralight scalar Dark Matter (DM) with linear and quadratic couplings to the Standard Model (SM). In addition to studying the phenomenology of linear and quadratic interactions separately, we examine their interplay. We review the different experiments that can probe such interactions and present the current and expected future bounds o

Wayne E. Dick

The main result is Theorem MAT 11 which states that every finite closure operator is the ground set of a matroid. Its base sets consist of nonredundant covers of of the closure. These are minimal subsets that determine the closure operator using a closure algorithm from the theory of relational databases. For each hereditary collection there is one flat clos

Zhuo Chen, Naoyuki Kanda, Jian Wu, Yu Wu

Self-supervised learning (SSL) methods such as WavLM have shown promising speech separation (SS) results in small-scale simulation-based experiments. In this work, we extend the exploration of the SSL-based SS by massively scaling up both the pre-training data (more than 300K hours) and fine-tuning data (10K hours). We also investigate various techniques to

Marijana Butorac, Slaven Kožić

We consider the standard modules of rectangular highest weights of affine Lie algebras in types $A_{2l-1}^{(2)}$ and $D_{l+1}^{(2)}$. By using vertex algebraic techniques we construct the combinatorial bases for standard modules and their principal subspaces and parafermionic spaces. Finally, we compute the corresponding character formulae and, as an applica

Manuel Stoeckl

Many problems on data streams have been studied at two extremes of difficulty: either allowing randomized algorithms, in the static setting (where they should err with bounded probability on the worst case stream); or when only deterministic and infallible algorithms are required. Some recent works have considered the adversarial setting, in which a randomiz

Yizhuang Liu, Maciej A. Nowak, Ismail Zahed

We analyze Mueller's QCD dipole wave function evolution in the double logarithm approximation (DLA). Using complex analytical methods, we show that the distribution of dipole in the wave function (gluon multiplicity distribution) asymptotically satisfies the Koba-Nielsen-Olesen (KNO) scaling, with a non-trivial scaling function $f(z)$ with $z=\frac n{\bar n}

Yash Deshmukh

We give a description of the Deligne-Mumford properad expressing it as the result of homotopically trivializing S1 families of annuli (with appropriate compatibility conditions) in the properad of smooth Riemann surfaces with parameterized boundaries. This gives an analog of the results of Drummond-Cole and Oancea--Vaintrob in the setting of properads. We al

William J. Wesley

Van der Waerden's theorem states that for any positive integers $k$ and $r$, there exists a smallest value $n = w(k,r)$, called the van der Waerden number, such that every $r$-coloring of $\{1,\dots,n\}$ contains a monochromatic $k$-term arithmetic progression. We consider two variants of van der Waerden numbers: the numbers $n = n(AP_D,k;r)$, the smallest v

Christopher Bryant, Zheng Yuan, Muhammad Reza Qorib, Hannan Cao

Grammatical Error Correction (GEC) is the task of automatically detecting and correcting errors in text. The task not only includes the correction of grammatical errors, such as missing prepositions and mismatched subject-verb agreement, but also orthographic and semantic errors, such as misspellings and word choice errors respectively. The field has seen si

Ye Liu, Semih Yavuz, Rui Meng, Dragomir Radev

Parsing natural language questions into executable logical forms is a useful and interpretable way to perform question answering on structured data such as knowledge bases (KB) or databases (DB). However, existing approaches on semantic parsing cannot adapt to both modalities, as they suffer from the exponential growth of the logical form candidates and can

Luca De Rosa, Dídac Martínez-Granado

Every geodesic current on a hyperbolic surface has an associated dual space. If the current is a lamination, this dual embeds isometrically into a real tree. We show that, in general, the dual space is a Gromov hyperbolic metric tree-graded space, and express its Gromov hyperbolicity constant in terms of the geodesic current. In the case of geodesic currents

Yuanchao Li, Peter Bell, Catherine Lai

As a sub-branch of affective computing, impression recognition, e.g., perception of speaker characteristics such as warmth or competence, is potentially a critical part of both human-human conversations and spoken dialogue systems. Most research has studied impressions only from the behaviors expressed by the speaker or the response from the listener, yet ig

Vikram Ravindranath, Yiqiu Han, Zhi-Cheng Yang, Xiao Chen

The intensely studied measurement-induced entanglement phase transition has become a hallmark of non-unitary quantum many-body dynamics. Usually, such a transition only shows up at the level of each individual quantum trajectory, and is absent for the density matrix averaged over measurement outcomes. In this work, we introduce a class of adaptive random cir

Ludwig Schneider, Juan de Pablo

Recent advances in nano-rheology require that new methods and models be developed to describe the equilibrium and non-equilibrium properties of entangled polymeric materials and their interfaces at a molecular level of detail. In this work we present a Slip-Spring (SLSP) model capable of describing the dynamics of entangled polymers at interfaces, including

Clément Berthiere, Benoit Estienne, Jean-Marie Stéphan, William Witczak-Krempa

Outcomes of measurements are characterized by an infinite family of generalized uncertainties, or cumulants, which provide information beyond the mean and variance of the observable. Here, we investigate the cumulants of a conserved charge in a subregion with corners. We derive nonperturbative relations for the area law, and more interestingly, the angle dep

Ratul Mahanta, Tanmoy Sengupta

We construct modular linear differential equations (MLDEs) w.r.t. subgroups of the modular group whose solutions are Virasoro conformal blocks appearing in the expansion of a crossing symmetric 4-point correlator on the sphere. This uses a connection between crossing transformations and modular transformations. We focus specifically on second order MLDEs wit

Nikita Golub

In this paper we introduce a generalisation of a covariant Grothendieck construction to the setting of sites. We study the basic properties of defined site structures on Grothendieck constructions as well as we treat the cohomological aspects of corresponding toposes of sheaves. Despite the fact that the toposes of $G$-equivariant sheaves $Sh_G(X)$ have been

Hongming Zhang, Wenlin Yao, Dong Yu

Event extraction (EE) is the task of identifying interested event mentions from text. Conventional efforts mainly focus on the supervised setting. However, these supervised models cannot generalize to event types out of the pre-defined ontology. To fill this gap, many efforts have been devoted to the zero-shot EE problem. This paper follows the trend of mode

Lotfi Ben-Jaffel, Gilda E. Ballester, Antonio García Muñoz, Panayotis Lavvas

The magnetosphere of an exoplanet has yet to be unambiguously detected. Investigations of star-planet interaction and neutral atomic hydrogen absorption during transit to detect magnetic fields in hot Jupiters have been inconclusive, and interpretations of the transit absorption non-unique. In contrast, ionized species escaping a magnetized exoplanet, partic

Kaanapuli Ramkumar, Swati Swagatika Mishra, Sudeep Bhattacharjee

In this study, the transport properties, such as diffusivity, viscosity, and thermal conductivity, of 4He at the gaseous phase are computed for state points in the temperature range of 10 K to 150 K and pressure range of 0.10 MPa (1 atm) to 0.21 MPa using classical and quantum frameworks. Within the classical molecular dynamics simulation (MDS), the Green-Ku

Jonathan P. Epperlein, Niall P. Hardy, Pol Mac Aonghusa, Ronan A. Cahill

Intraoperative assessment of tissue can be guided through fluorescence imaging which involves systemic dosing with a fluorophore and subsequent examination of the tissue region of interest with a near-infrared camera. This typically involves administering indocyanine green (ICG) hours or even days before surgery and intraoperative visualization at the time p

Rajibul Islam, Sougata Mardanya, Alexander Lau, Giuseppe Cuono

We study theoretically the interplay between magnetism and topology in three-dimensional HgTe/MnTe superlattices stacked along the (001) axis. Our results show the evolution of the magnetic topological phases with respect to the magnetic configurations. An axion insulator phase is observed for the antiferromagnetic order with the out-of-plane N\'eel vector d

Kevin Doherty, Cooper Simpson, Stephen Becker, Alireza Doostan

We present a new convolution layer for deep learning architectures which we call QuadConv -- an approximation to continuous convolution via quadrature. Our operator is developed explicitly for use on non-uniform, mesh-based data, and accomplishes this by learning a continuous kernel that can be sampled at arbitrary locations. Moreover, the construction of ou

Michael T. Murphy, Daniel A. Berke, Fan Liu, Chris Flynn

The fine structure constant, $\alpha$, sets the strength of the electromagnetic force. The Standard Model of particle physics provides no explanation for its value, which could potentially vary. The wavelengths of stellar absorption lines depend on $\alpha$, but are subject to systematic effects owing to astrophysical processes in stellar atmospheres. We mea

Srilekha Gandhari, Victor V. Albert, Thomas Gerrits, Jacob M. Taylor

Shadow tomography is a framework for constructing succinct descriptions of quantum states using randomized measurement bases, called classical shadows, with powerful methods to bound the estimators used. We recast existing experimental protocols for continuous-variable quantum state tomography in the classical-shadow framework, obtaining rigorous bounds on t

Chiara M. F. Mingarelli, J. Andrew Casey-Clyde

Pulsar timing arrays will be a window into the gravitational wave background

Francesco Bigazzi, Aldo L. Cotrone, Andrea Olzi

In single-flavor QCD, the low energy description of baryons as Skyrmions is not available. In this case, it has been proposed by Komargodski that baryons can be viewed as kinds of charged quantum Hall droplets, or "sheets". In this paper we propose a string theory description of the sheets in single-flavor holographic QCD, focusing on the Witten-Sakai-Sugimo

Emile Pangburn, Louis Haurie, Adeline Crépieux, Oladunjoye A. Awoga

We review all symmetry-allowed spin-singlet and spin-triplet superconducting (SC) order parameters in graphene ($s$-wave, $d$-wave, $p$-wave, and $f$-wave) generated by generic onsite, nearest-neighbor (NN), and next-to-nearest-neighbor (NNN) pairing interactions in a tight-binding model. For each pairing channel, we calculate both the band structure and the

Niklas Becker, Laura Sagunski

Intermediate Mass Ratio Inspirals (IMRIs) will be observable with space-based gravitational wave detectors such as the Laser Interferometer Space Antenna (LISA). To this end, the environmental effects in such systems have to be modeled and understood. These effects can include (baryonic) accretion disks and dark matter (DM) overdensities, so called spikes. F

David Berenstein, Robinson Mancilla

We revisit the problem of analytically computing the one point functions for scalar fields in planar AdS black holes of arbitrary dimension, which are sourced by the Weyl squared tensor. We analyze the problem in terms of power series expansions around the boundary using the method of Frobenius. We clarify the pole structure of the final answer in terms of o

Luc Builtjes, Sascha Caron, Polina Moskvitina, Clara Nellist

A major task in particle physics is the measurement of rare signal processes. Even modest improvements in background rejection, at a fixed signal efficiency, can significantly enhance the measurement sensitivity. Building on prior research by others that incorporated physical symmetries into neural networks, this work extends those ideas to include additiona

Viraj R. Karambelkar, Mansi M. Kasliwal, Nadejda Blagorodnova, Jesper Sollerman

Luminous red novae (LRNe) are transients characterized by low luminosities and expansion velocities, and are associated with mergers or common envelope ejections in stellar binaries. Intermediate-luminosity red transients (ILRTs) are an observationally similar class with unknown origins, but generally believed to either be electron capture supernovae (ECSN)

Shun-Yao Zhang, Dong Yuan, Thomas Iadecola, Shenglong Xu

Quantum many-body scarred systems host nonthermal excited eigenstates immersed in a sea of thermal ones. In cases where exact expressions for these special eigenstates are not known, it is computationally demanding to distinguish them from their exponentially many thermal neighbors. We propose a matrix-product-state (MPS) algorithm, dubbed DMRG-S, to extract

Asher Berlin, Jeff A. Dror, Xucheng Gan, Joshua T. Ruderman

The detection of massless kinetically-mixed dark photons is notoriously difficult, as the effect of this mixing can be removed by a field redefinition in vacuum. In this work, we study the prospect of detecting massless dark photons in the presence of a cosmic relic directly charged under this dark electromagnetism. Such millicharged particles, in the form o

Vladimir Bashmakov, Michele Del Zotto, Azeem Hasan, Justin Kaidi

We study the non-invertible symmetries of class $\mathcal{S}$ theories obtained by compactifying the type $\mathfrak{a}_{p-1}$ 6d (2,0) theory on a genus $g$ Riemann surface with no punctures. After setting up the general framework, we describe how such symmetries can be classified up to genus 5. Of central interest to us is the question of whether a non-inv

Gunnar F. Lange, Adrien Bouhon, Robert-Jan Slager

We study the relationship between projected momentum-space spin textures and Wilson loop winding, proving a map between band topology of and spin topology in certain restricted symmetry settings, relevant to fragile topology. Our results suggest that the spin gap may act as a smoking gun bulk indicator for fragile topology within specific scenarios.

Júlia Sisk-Reynés, Christopher S. Reynolds, Michael L. Parker, James H. Matthews

Axion-Like Particles (ALPs) are well-motivated extensions of the Standard Model of Particle Physics and a generic prediction of some string theories. X-ray observations of bright Active Galactic Nuclei (AGN) hosted by rich clusters of galaxies are excellent probes of very-light ALPs, with masses $\mathrm{log}(m_\mathrm{a}/\mathrm{eV}) < -12.0$. We evaluate t

Jesus Bonilla, Arturo de Giorgi, Maria Ramos

The neutral $B$-anomalies are analysed in terms of the tree-level exchange of a (pseudo)scalar gauge singlet $a$. Solutions to both $R_{K^{(*)}}$ central bin anomalies are found within $1\sigma$ for ${m_{a}^2 \in [{1.1},\,{6}]\,\text{GeV}^2}$, while the low $q^2$-bin anomaly can also be accounted for with masses close to the bin threshold. The impact of thes

K. W. Davis, K. Taggart, S. Tinyanont, R. J. Foley

We present optical and near-infrared (NIR) observations of the Type Icn supernova (SN Icn) 2022ann, the fifth member of its newly identified class of SNe. Its early optical spectra are dominated by narrow carbon and oxygen P-Cygni features with absorption velocities of 800 km/s; slower than other SNe Icn and indicative of interaction with a dense, H/He-poor

Jeffrey V. Backus, Marat Freytsis, Yuval Grossman, Stefan Schacht

$B^\pm \to DK^\pm$ transitions are known to provide theoretically clean information about the CKM angle $\gamma$, with the most precise available methods exploiting the cascade decay of the neutral $D$ into $CP$ self-conjugate states. Such analyses currently require binning in the $D$ decay Dalitz plot, while a recently proposed method replaces this binning

Claudio Ricci, Benny Trakhtenbrot

Active Galactic Nuclei (AGN) are known to show flux variability over all observable timescales and across the entire electromagnetic spectrum. Over the past decade, a growing number of sources have been observed to show dramatic flux and spectral changes, both in the X-rays and in the optical/UV. Such events, commonly described as "changing-look AGN", can be

Minghao Guo, James M. Stone, Chang-Goo Kim, Eliot Quataert

We present high-resolution, three-dimensional hydrodynamic simulations of the fueling of supermassive black holes in elliptical galaxies from a turbulent medium on galactic scales, taking M87* as a typical case. The simulations use a new GPU-accelerated version of the Athena++ AMR code, and span more than 6 orders of magnitude in radius, reaching scales simi

Andrey Gromov, Leo Radzihovsky

We review a burgeoning field of "fractons" -- a class of models where quasi-particles are strictly immobile or display restricted mobility that can be understood through generalized multipolar symmetries and associated conservation laws. Focusing on just a corner of this fast-growing subject, we will demonstrate how one class of such theories -- symmetric te

Kristian Mæland, Asle Sudbø

Topological superconductors are associated with the appearance of Majorana bound states, with promising applications in topologically protected quantum computing. In this Letter, we study a system where a skyrmion crystal is interfaced with a normal metal. Through interfacial exchange coupling, spin fluctuations in the skyrmion crystal mediate an effective e

Severin Lüst, Max Wiesner

We revisit moduli stabilization on Calabi-Yau manifolds with a discrete symmetry. Invariant fluxes allow for a truncation to a symmetric locus in complex structure moduli space and hence drastically reduce the moduli stabilization problem in its dimensionality. This makes them an ideal testing ground for the tadpole conjecture. For a large class of fourfolds

Joseph T. Iosue, Kunal Sharma, Michael J. Gullans, Victor V. Albert

We generalize the notion of quantum state designs to infinite-dimensional spaces. We first prove that, under the definition of continuous-variable (CV) state $t$-designs from Comm. Math. Phys. 326, 755 (2014), no state designs exist for $t\geq2$. Similarly, we prove that no CV unitary $t$-designs exist for $t\geq 2$. We propose an alternative definition for

Or Kedar, Jake P. Solomon

Let $L\subset X$ be a not necessarily orientable relatively $Pin$ Lagrangian submanifold in a symplectic manifold $X$. Evaluation maps of moduli spaces of $J$-holomorphic disks with boundary in $L$ may not be relatively orientable. To deal with this problem, we introduce the notion of an orientor. Interactions between the natural operations on orientors are

Connor Lawless, Angela Zhou

In this short technical note we propose a baseline for decision-aware learning for contextual linear optimization, which solves stochastic linear optimization when cost coefficients can be predicted based on context information. We propose a decision-aware version of predict-then-optimize. We reweigh the prediction error by the decision regret incurred by an

Christopher Carr, Greg L. Bryan, Drummond B. Fielding, Viraj Pandya

Galactic outflows driven by supernovae (SNe) are thought to be a powerful regulator of a galaxy's star-forming efficiency. Mass, energy, and metal outflows ($\eta_M$, $\eta_E$, and $\eta_Z$, here normalized by the star formation rate, the SNe energy and metal production rates, respectively) shape galaxy properties by both ejecting gas and metals out of the g

Marc G. Brouwers, Amy Bonsor, Uri Malamud

Polluted white dwarfs serve as astrophysical mass spectrometers - their photospheric abundances are used to infer the composition of planetary objects that accrete onto them. We show that due to asymmetries in the accretion process, the composition of the material falling onto a star may vary with time during the accretion of a single planetary body. Consequ

Marc G. Brouwers, Andrew M. Buchan, Amy Bonsor, Uri Malamud

Volatiles, notably water, are key to the habitability of rocky planets. The presence of water in planetary material can be inferred from the atmospheric oxygen abundances of polluted white dwarfs, but this interpretation is often complex. We study the accretion process, and find that ices may sublimate and accrete before more refractory minerals reach the st

Filip Sośnicki, Michał Mikołajczyk, Ali Golestani, Michał Karpiński

Light is a key information carrier, enabling worldwide high-speed data transmission through a telecommunication fibre network. This information-carrying capacity can be extended to transmitting quantum information (QI) by encoding it in single photons -- flying qubits. However, various QI-processing platforms operate at vastly different timescales. QI-proces