March 2023 arXiv papers — page 8

Weina Jin, Xiaoxiao Li, Ghassan Hamarneh

Explainable artificial intelligence (XAI) is motivated by the problem of making AI predictions understandable, transparent, and responsible, as AI becomes increasingly impactful in society and high-stakes domains. The evaluation and optimization criteria of XAI are gatekeepers for XAI algorithms to achieve their expected goals and should withstand rigorous i

Anqi Feng, Yuan Xue, Yuli Wang, Chang Yan

Data-driven thalamic nuclei parcellation depends on high-quality manual annotations. However, the small size and low contrast changes among thalamic nuclei, yield annotations that are often incomplete, noisy, or ambiguously labelled. To train a robust thalamic nuclei parcellation model with noisy annotations, we propose a label propagation algorithm based on

Anaïs Andrillon, Lucie Biard, Shing M. Lee

Dose-finding clinical trials in oncology aim to estimate the maximum tolerated dose (MTD), based on safety traditionally obtained from the clinician's perspective. While the collection of patient-reported outcomes (PROs) has been advocated to better inform treatment tolerability, there is a lack of guidance and methods on how to use PROs for dose assignments

D. Ghio, A. L. M. Aragon, I. Biazzo, L. Zdeborova

We consider a class of spreading processes on networks, which generalize commonly used epidemic models such as the SIR model or the SIS model with a bounded number of re-infections. We analyse the related problem of inference of the dynamics based on its partial observations. We analyse these inference problems on random networks via a message-passing infere

Finlay G. C. Hudson, William A. P. Smith

In this paper, we introduce a novel method for zero-shot, cross-domain image retrieval. Our key contribution is a test-time Iterative Cluster-free Re-ranking process that leverages gallery-gallery feature information to establish semantic links between query and gallery images. This enables the retrieval of relevant images even when they do not exhibit simil

Paul R. Dawson, Matthew P. Miller

To assist in the planning of in situ loading, HEDM experiments by generating synthetic diffraction images of virtual samples in loaded and unloaded states. The user designates a target grain in the virtual sample and specifies the set of reflections for which images are to be generated. The code generates several intermediate images, including: (1) the point

Naresh Saha, Baranana Roy, Avinash Khare

Propagation characteristics of the chirped dissipative solitary waves are investigated within the framework of higher order complex cubic quintic Ginzburg Landau equation. Potentially rich set of exact chirped dissipative pulses, such as, bright, dark, grey, antidark, kink, antikink are derived in the presence of the self steepening, self frequency shift and

Sachin J. Valera

We present the teleportation and superdense coding protocols for a family of anyon theories coming from Tambara-Yamagami categories, of which the lowest rank theories describe Ising anyons. In contrast to the usual approach to anyonic computation, we relax the requirement that we should be able to braid anyons. This is motivated by the goal of designing basi

Seunghwi Kim, Yu-Gui Peng, Simon Yves, Andrea Alù

Abbe diffraction limit fundamentally bounds the resolution of conventional optical imaging and spectroscopic systems. Along the years, several schemes have been introduced to overcome this limit, each offering opportunities and trade-offs. Metamaterials have been proposed as a promising platform in this context, in principle enabling superlenses capable of d

P. Rubí Pantaleón-Mondragón, Abraham Martín del Campo

Foliations in the complex projective plane are uniquely determined by their singular locus, which is in correspondence with a zero-dimensional ideal. However, this correspondence is not surjective. We give conditions to determine whether an ideal arises as the singular locus of a foliation or not. Furthermore, we give an effective method to construct the fol

Yang Jeong Park, Daniel Kaplan, Zhichu Ren, Chia-Wei Hsu

We investigate whether large language models can perform the creative hypothesis generation that human researchers regularly do. While the error rate is high, generative AI seems to be able to effectively structure vast amounts of scientific knowledge and provide interesting and testable hypotheses. The future scientific enterprise may include synergistic ef

Mark Popinchalk

Humans like to party, and New Year celebrations are a great way to do that. However New Years celebrations that rely on an orbital year don't line up with those that use a Lunar Calendar, as there are currently 12.368 synodic months (moonths) in a year. There is cyclostratigraphic, paleontological, and tidal rhythmite data that reveal that over billions of y

Gorkem Can Ates, Prasoon Mohan, Emrah Celik

We propose Dual Cross-Attention (DCA), a simple yet effective attention module that is able to enhance skip-connections in U-Net-based architectures for medical image segmentation. DCA addresses the semantic gap between encoder and decoder features by sequentially capturing channel and spatial dependencies across multi-scale encoder features. First, the Chan

Raja Kumar

Existing conversational models are handled by a database(DB) and API based systems. However, very often users' questions require information that cannot be handled by such systems. Nonetheless, answers to these questions are available in the form of customer reviews and FAQs. DSTC-11 proposes a three stage pipeline consisting of knowledge seeking turn detect

Johann Bouwer, Daniel N. Wilke, Schalk Kok

Recent developments in surrogate construction predominantly focused on two strategies to improve surrogate accuracy. Firstly, component-wise domain scaling informed by cross-validation. Secondly, regression to construct response surfaces using additional information in the form of additional function-values sampled from multi-fidelity models and gradients. C

Stefanos Georgiadis, Ansgar Jüngel

The dynamics of multicomponent gas mixtures with vanishing barycentric velocity is described by Maxwell-Stefan equations with mass diffusion and heat conduction. The equations consist of the mass and energy balances, coupled to an algebraic system that relates the partial velocities and driving forces. The global existence of weak solutions to this system in

Luke S. Baker, Saif R. Kazi, Anatoly Zlotnik

The blending of hydrogen generated using clean energy into natural gas pipeline networks is proposed in order to utilize existing energy systems for their planned lifetimes while reducing their reliance on fossil fuels. We formulate a system of partial differential equations (PDEs) that govern the flow dynamics of mixtures of gases in pipeline networks under

Shai Gertler, Zeyu Kuang, Colin Christie, Owen D. Miller

Physical design refers to mathematical optimization of a desired objective (e.g. strong light--matter interactions, or complete quantum state transfer) subject to the governing dynamical equations, such as Maxwell's or Schrodinger's differential equations. Computing an optimal design is challenging: generically, these problems are highly nonconvex and findin

Josep Fontana-McNally, Eva Miranda, Cédric Oms, Daniel Peralta-Salas

In this short note, we prove that singular Reeb vector fields associated with generic $b$-contact forms have either (at least) $2N$ or an infinite number of escape orbits, where $N$ denotes the number of connected components of the critical set.

Mathias Drton, Hongjian Shi, David Strieder

Invited discussion for Stat of "A note on universal inference" by Timmy Tse and Anthony Davison (2022)

Aiyu Cui, Sen He, Tao Xiang, Antoine Toisoul

Virtual try-on, i.e making people virtually try new garments, is an active research area in computer vision with great commercial applications. Current virtual try-on methods usually work in a two-stage pipeline. First, the garment image is warped on the person's pose using a flow estimation network. Then in the second stage, the warped garment is fused with

B. T. Blue, R. Tsuchikawa, A. Ahmadi, Z. Zhang

Previous gate-dependent conductance measurements of metallic carbon nanotubes have revealed unexplainable conductance suppressions, occurring at two different gate voltages. These were previously attributed to the gate-dependency of contact resistance. Our gate-dependent conductivity measurements on a metallic nanotube with known chirality show that these bi

Milan Kornjača, Rebecca Flint

The hidden order phase of URu$_2$Si$_2$ has eluded identification for over thirty-five years. A compelling proposal that explains the Ising heavy-fermion nature of the material is \emph{hastatic order}: a symmetry breaking heavy-Fermi liquid arising from a spinorial microscopic hybridization. The original hastatic proposal cannot microscopically model the pr

Nicolas Chagnet, Koenraad Schalm

We study charged hydrodynamics in a periodic lattice background. Fluctuations are Bloch waves rather than single momentum Fourier modes. At boundaries of the unit cell where hydrodynamic fluctuations are formally degenerate with their Umklapped copy, level repulsion occurs. Novel mode mixings between charge, sound, and their Umklapped copies appear at finite

Srujan Meesala, Steven Wood, David Lake, Piero Chiappina

Modern computing and communication technologies such as supercomputers and the internet are based on optically connected networks of microwave frequency information processors. In recent years, an analogous architecture has emerged for quantum networks with optically distributed entanglement between remote superconducting quantum processors, a leading platfo

Aarohi Srivastava, David Chiang

In this work, we induce character-level noise in various forms when fine-tuning BERT to enable zero-shot cross-lingual transfer to unseen dialects and languages. We fine-tune BERT on three sentence-level classification tasks and evaluate our approach on an assortment of unseen dialects and languages. We find that character-level noise can be an extremely eff

Pete Riley, M. A. Reiss, C. Mostl

Accurately predicting the z-component of the interplanetary magnetic field, particularly during the passage of an interplanetary coronal mass ejection (ICME), is a crucial objective for space weather predictions. Currently, only a handful of techniques have been proposed and they remain limited in scope and accuracy. Recently, a robust machine learning (ML)

Pawel Rochowski

The idea behind the research presented is based upon apparently contradictory experimental results obtained here by means of photoacoustics modalities for the same drug donor/acceptor membrane system, serving as a surrogate for a transdermal delivery system. The first modality allowed for the monitoring of the total amount of mass uptake (m(t)-type data), wh

Iosif Bena, Mariana Graña, Thomas Van Riet

We attempt to review all trustworthy and well-controlled de Sitter compactifications of string theory.

Lars Gottesbüren, Tobias Heuer, Nikolai Maas, Peter Sanders

Balanced hypergraph partitioning is an NP-hard problem with many applications, e.g., optimizing communication in distributed data placement problems. The goal is to place all nodes across $k$ different blocks of bounded size, such that hyperedges span as few parts as possible. This problem is well-studied in sequential and distributed settings, but not in sh

Christian Böhning, Hans-Christian Graf von Bothmer, Yuri Tschinkel

We study equivariant birationality from the perspective of derived categories. We produce examples of nonlinearizable but stably linearizable actions of finite groups on smooth cubic fourfolds.

Nicolas Crampé, Luc Frappat, Loïc Poulain d'Andecy, Eric Ragoucy

We propose a definition by generators and relations of the rank $n-2$ Askey-Wilson algebra $\mathfrak{aw}(n)$ for any integer $n$, generalising the known presentation for the usual case $n=3$. The generators are indexed by connected subsets of $\{1,\dots,n\}$ and the simple and rather small set of defining relations is directly inspired from the known case o

Yupeng Yao, Alexander P. Ji, Sergey E. Koposov, Guilherme Limberg

Very metal-poor stars ($\rm[Fe/H] < -2$) in the Milky Way are fossil records of early chemical evolution and the assembly and structure of the Galaxy. However, they are rare and hard to find. Gaia DR3 has provided over 200 million low-resolution ($R \approx 50$) XP spectra, which provides an opportunity to greatly increase the number of candidate metal-poor

Joshua Pilipovsky, Panagiotis Tsiotras

This paper studies the problem of steering the distribution of a linear time-invariant system from an initial normal distribution to a terminal normal distribution under no knowledge of the system dynamics. This data-driven control framework uses data collected from the input and the state and utilizes the seminal work by Willems et al. to construct a data-b

Thomas Lew, Riccardo Bonalli, Marco Pavone

We study the convex hulls of reachable sets of nonlinear systems with bounded disturbances and uncertain initial conditions. Reachable sets play a critical role in control, but remain notoriously challenging to compute, and existing over-approximation tools tend to be conservative or computationally expensive. In this work, we characterize the convex hulls o

Charles C. Cowley, Robert E. Stencel

Sun-like dwarf stars in the solar neighborhood reflect ages, an ``average'' chemical evolution, and departures from that average. We show the chemical, and kinematic properties of four groups of Sunlike dwarfs form a continuum related to age. We plot [Fe/H] vs. age, as well as kinematical values for the four groups. The vertical (negative) scatter in [Fe/H]

Dinshaw S. Balsara, Deepak Bhoriya, Chi-Wang Shu, Harish Kumar

Higher order finite difference Weighted Essentially Non-Oscillatory (WENO) schemes have been constructed for conservation laws. For multidimensional problems, they offer high order accuracy at a fraction of the cost of a finite volume WENO or DG scheme of comparable accuracy. This makes them quite attractive for several science and engineering applications.

Bodo Lampe

Quark and lepton masses and mixings are considered in the framework of the microscopic model. The most general ansatz for the interactions among tetrons leads to a Hamiltonian $H_T$ involving Dzyaloshinskii-Moriya (DM), Heisenberg and torsional isospin forces. Diagonalization of the Hamiltonian provides for 24 eigenvalues which are identified as the quark an

Nicola Muca Cirone, Maud Lemercier, Cristopher Salvi

Motivated by the paradigm of reservoir computing, we consider randomly initialized controlled ResNets defined as Euler-discretizations of neural controlled differential equations (Neural CDEs), a unified architecture which enconpasses both RNNs and ResNets. We show that in the infinite-width-depth limit and under proper scaling, these architectures converge

Nicholas Milikich

The cooperative management of rice terraces in Bali reveals an interesting phenomenon that stems from the feedback loop between human decisions and the ecosystem process. In particular, spatial patterning is observed, which is heavily reliant on the farmer's decision to plant crops as well as the response from the physical environment like pest damage and wa

Yi-Ru Wang, Gui-Bin Liu

The study of topological semimetals has been extended to more general topological nodal systems such as metamaterials and artificial periodic structures. Among various nodal structures, triply degenerate nodal line (TNL) is rare and hence lack of attention. In this work, we have proposed a simple tight-binding model which hosts a topological non-trivial TNL.

Brittany Burdette, Caleb Falcione, Cameron Hale, John Mayer

We study the correspondence between unicritical laminations and maximally critical laminations with rotational and identity return polygons. Laminations are a combinatorial and topological way to study Julia sets. Laminations give information about the structure of parameter space of degree $d$ polynomials with connected Julia sets.

Nicholas Milikich, Joshua Johnson

With the advent of fast-paced information dissemination and retrieval, it has become inherently important to resort to automated means of predicting stock market prices. In this paper, we propose Taureau, a framework that leverages Twitter sentiment analysis for predicting stock market movement. The aim of our research is to determine whether Twitter, which

Sérgio V. M. C. B. Xavier, Haroldo C. D. Lima Junior, Luís C. B. Crispino

We investigate the shadow of an exact black hole solution of Einstein's equations recently proposed by Cardoso et al., to describe a supermassive black hole immersed in a dark matter halo. We analyze and discuss the light rings and the gravitational lensing of this spacetime comparing them with an isolated Schwarzschild black hole. Using backward ray-tracing

Anna Parlak

A pseudo-Anosov flow on a hyperbolic 3-manifold dynamically represents a face F of the Thurston norm ball if the cone on F is dual to the cone spanned by homology classes of closed orbits of the flow. Fried showed that for every fibered face of the Thurston norm ball there is a unique, up to isotopy and reparametrization, flow which dynamically represents th

Joseph Sullivan, Rui Wen, Andrew C. Potter

We introduce a class of models, dubbed paired twist-defect networks, that generalize the structure of Kitaev's honeycomb model for which there is a direct equivalence between: i) Floquet codes (FCs), ii) adiabatic loops of gapped Hamiltonians, and iii) unitary loops or Floquet-enriched topological orders (FETs) many-body localized phases. This formalism allo

Harry Fluck, Xiaolong Li

This article aims to understand the behavior of the curvature operator of the second kind under the Ricci flow in dimension three. First, we express the eigenvalues of the curvature operator of the second kind explicitly in terms of that of the curvature operator (of the first kind). Second, we prove that $\a$-positive/$\a$-nonnegative curvature operator of

Jacobo Troncoso, Claudio A. Cerdeiriña

A spin-1 Ising model incorporating positional order to a standard lattice gas with no attractive interactions is introduced and found to be consistent with all known attributes of the freezing transition of the hard-sphere system. Implementation of attractive interactions in a fairly natural way then allows every aspect of the phase diagram of a simple subst

Muntabir Hasan Choudhury, Lamia Salsabil, Himarsha R. Jayanetti, Jian Wu

Metadata quality is crucial for digital objects to be discovered through digital library interfaces. However, due to various reasons, the metadata of digital objects often exhibits incomplete, inconsistent, and incorrect values. We investigate methods to automatically detect, correct, and canonicalize scholarly metadata, using seven key fields of electronic

Manisha, Aditya Chandra Mandal, Mohit Rathor, Zeev Zalevsky

We propose and demonstrate a holographic imaging scheme exploiting random illuminations for recording hologram and then applying numerical reconstruction and twin removal. We use an in-line holographic geometry to record the hologram in terms of the second-order correlation and apply the numerical approach to reconstruct the recorded hologram. The twin image

Ben Hersey, Gregory G. Smith, Alexandre Zotine

We highlight some features of the SimplicialComplexes package in Macaulay2.

Noah Fleischmann, Walter Bennette, Nathan Inkawhich

Machine learning models deployed in the open world may encounter observations that they were not trained to recognize, and they risk misclassifying such observations with high confidence. Therefore, it is essential that these models are able to ascertain what is in-distribution (ID) and out-of-distribution (OOD), to avoid this misclassification. In recent ye

Farouk Mokhtar, Joosep Pata, Javier Duarte, Eric Wulff

The particle-flow (PF) algorithm, which infers particles based on tracks and calorimeter clusters, is of central importance to event reconstruction in the CMS experiment at the CERN LHC, and has been a focus of development in light of planned Phase-2 running conditions with an increased pileup and detector granularity. In recent years, the machine learned pa

Alejandro Puente-Castro, Daniel Rivero, Eurico Pedrosa, Artur Pereira

Path Planning methods for autonomous control of Unmanned Aerial Vehicle (UAV) swarms are on the rise because of all the advantages they bring. There are more and more scenarios where autonomous control of multiple UAVs is required. Most of these scenarios present a large number of obstacles, such as power lines or trees. If all UAVs can be operated autonomou

Jorge Cuadra, Miguel Vergara, Bruno Escárate, Josué Sandoval

Astronomical images can be fascinating to the general public, but the interaction is typically limited to contemplation. Numerical simulations of astronomical systems do permit a closer interaction, but are generally unknown outside the research community. We are developing "Protoplanet Express", a video game based on hydrodynamical simulations of protoplane

Ilmari Kangasniemi, Jani Onninen

We prove a far-reaching generalization of Rickman's Picard theorem for a surprisingly large class of mappings, based on the recently developed theory of quasiregular values. Our results are new even in the planar case.

Ben Johns

Epsilon-near-zero (ENZ) materials have recently emerged as a promising platform for infrared nanophotonics. A significant challenge in the design of ENZ-based optics is to control the dispersion of ENZ modes, which otherwise have a flat profile near the ENZ frequency. Strong coupling with an optical cavity is a promising approach to ENZ dispersion engineerin

Aman Madaan, Niket Tandon, Prakhar Gupta, Skyler Hallinan

Like humans, large language models (LLMs) do not always generate the best output on their first try. Motivated by how humans refine their written text, we introduce Self-Refine, an approach for improving initial outputs from LLMs through iterative feedback and refinement. The main idea is to generate an initial output using an LLMs; then, the same LLMs provi

Mayank Soni, Vincent Wade

Large Language Models (LLMs) have gathered significant attention due to their impressive performance on a variety of tasks. ChatGPT, developed by OpenAI, is a recent addition to the family of language models and is being called a disruptive technology by a few, owing to its human-like text-generation capabilities. Although, many anecdotal examples across the

Oscar R. Navarrete-Parra, Victor Uc-Cetina, Jorge Reyes-Magana

In this paper, we propose a methodology to align a medium-sized GPT model, originally trained in English for an open domain, to a small closed domain in Spanish. The application for which the model is finely tuned is the question answering task. To achieve this we also needed to train and implement another neural network (which we called the reward model) th

Mia Garrard, Hanson Wang, Ben Letham, Shaun Singh

Many organizations measure treatment effects via an experimentation platform to evaluate the casual effect of product variations prior to full-scale deployment. However, standard experimentation platforms do not perform optimally for end user populations that exhibit heterogeneous treatment effects (HTEs). Here we present a personalized experimentation frame

Danyang Liu, Frank Keller

Characters are essential to the plot of any story. Establishing the characters before writing a story can improve the clarity of the plot and the overall flow of the narrative. However, previous work on visual storytelling tends to focus on detecting objects in images and discovering relationships between them. In this approach, characters are not distinguis

Abhishek Moitra, Abhiroop Bhattacharjee, Youngeun Kim, Priyadarshini Panda

The hardware-efficiency and accuracy of Deep Neural Networks (DNNs) implemented on In-memory Computing (IMC) architectures primarily depend on the DNN architecture and the peripheral circuit parameters. It is therefore essential to holistically co-search the network and peripheral parameters to achieve optimal performance. To this end, we propose XPert, whic

Pablo de Castro, Felipe Urbina, Ariel Norambuena, Francisca Guzmán-Lastra

Motile organisms can form stable agglomerates such as cities or colonies. In the outbreak of a highly contagious disease, the control of large-scale epidemic spread depends on factors like the number and size of agglomerates, travel rate between them, and disease recovery rate. While the emergence of agglomerates permits early interventions, it also explains

Rhydian Windsor, Amir Jamaludin, Timor Kadir, Andrew Zisserman

This paper explores training medical vision-language models (VLMs) -- where the visual and language inputs are embedded into a common space -- with a particular focus on scenarios where training data is limited, as is often the case in clinical datasets. We explore several candidate methods to improve low-data performance, including: (i) adapting generic pre

Gerui Zhang, Xiongfei Zhao, Yain-Whar Si

Increasing popularity of trading digital assets can lead to significant delays in Blockchain networks when processing transactions. When transaction fees become miners' primary revenue, an imbalance in reward may lead to miners adopting deviant mining strategies. Scaling the block capacity is one of the potential approaches to alleviate the problem. To addre

Yik Lun Kei, Hangjian Li, Yanzhen Chen, Oscar Hernan Madrid Padilla

This paper studies the unsupervised change point detection problem in time series of networks using the Separable Temporal Exponential-family Random Graph Model (STERGM). Inherently, dynamic network patterns are complex due to dyadic and temporal dependence, and change points detection can identify the discrepancies in the underlying data generating processe

Jean-François Fortin, Kuver Sinha

Missions like NASA's Imaging X-ray Polarimetry Explorer (IXPE) are poised to provide an unprecedented view of the Universe in polarized X-rays. Polarization probes physical anisotropies, a fact exploited by particle physicists to look for the anisotropic $a\boldsymbol{E}\cdot\boldsymbol{B}$ operator in the axion-like-particle (ALP) Lagrangian. Such studies h

Ulrich K. Beckering Vinckers, Álvaro de la Cruz-Dombriz, Anupam Mazumdar

We examine the quantum gravitational entanglement of two test masses in the context of linearized General Relativity with specific non-local interaction with matter. To accomplish this, we consider an energy-momentum tensor describing two test particles of equal mass with each possessing some non-zero momentum. After discussing the quantization of the linear

Puspendu Roy, Pijush K. Ghosh

We consider equal-mass periodic Toda oscillators with balanced loss-gain for two and three particles. The two-particle system is integrable with the Hamiltonian and the genralized total momentum being two integrals of motion. The model in its full generality is not amenable to exact analytic solutions, and investigated numerically showing existence of regula

Hiroyuki Kaneko, Shoya Tokita, Nario Kuno

We present ALMA observations of a diffuse gas tracer, CO(J = 1-0), and a warmer and denser gas tracer, CO(J = 3-2), in the overlapping region of interacting galaxies NGC 4567/4568, which are in the early stage of interaction. To comprehend the impact of galaxy interactions on molecular gas properties, we focus on interacting galaxies during the early stage a

Lisa McBride, Michael Pagano

The immense popularity of spheroid-based scored events (colloquially ``football games'') motivates the desire to better understand the underlying mechanisms affecting their outcomes. By construction of these events, participants must distinguish the spheroidal ball from not only the background, but also their team and enemy players, which are marked by self-

Dominik Batić, Felix Holm, Ege Özsoy, Tobias Czempiel

Automated endoscopy video analysis is a challenging task in medical computer vision, with the primary objective of assisting surgeons during procedures. The difficulty arises from the complexity of surgical scenes and the lack of a sufficient amount of annotated data. In recent years, large-scale pretraining has shown great success in natural language proces

Diego H. Correa, Alberto Faraggi, Wolfgang Mück, Leopoldo A. Pando Zayas

We consider two-point correlators of local operator insertions in a system of two Wilson-Maldacena loops in ${\cal N}=4$ supersymmetric Yang-Mills theory on both sides of the AdS/CFT correspondence. On the holographic side the correlator of two Wilson-Maldacena loops is given by a classical string world-sheet which in one phase connects two asymptotically Ad

Fabian Esser, Maeve Madigan, Veronica Sanz, Maria Ubiali

In this paper we explore the coupling of a light axion-like particle (ALP) to top quarks. We use high-energy LHC probes, and examine both the direct probe to this coupling in associated production of a top-pair with an ALP, and the indirect probe through loop-induced gluon fusion to an ALP leading to top pairs. Using the latest LHC Run II data, we provide th

Aamna Ahmed, Nilanjan Roy, Auditya Sharma

We study the effects of quasiperiodic Aubry-Andr\'e (AA) disorder and interactions on a one-dimensional all-band-flat (ABF) diamond chain. We consider the application of disorder in two ways: a symmetric one, where the same disorder is applied to the top and bottom sites of a unit cell, and an antisymmetric one, where the disorder applied to the top and bott

Mahdi Qezlou, Simeon Bird, Adam Lidz, Guochao Sun

We forecast the prospects for cross-correlating future line intensity mapping (LIM) surveys with the current and future Ly-$\alpha$ forest data. We use large cosmological hydrodynamic simulations to model the expected emission signal for the CO rotational transition in the COMAP LIM experiment at the 5-year benchmark and the Ly-$\alpha$ forest absorption sig

Yi-Ming Wu, Yuxuan Wang

We present a theory for charge-$4e$ superconductivity as a leading low-temperature instability with a nontrivial $d$-wave symmetry. We show that in several microscopic models for the pair-density-wave (PDW) state, when the PDW wave vectors connect special parts of the Fermi surface, the predominant interaction is in the bosonic pairing channel mediated by ex

Shahar Hod

Far away observers can in principle bound from below the dimensionless maximum-density parameter $\Lambda\equiv4\pi R^2\rho_{\text{max}}$ of a compact star by measuring the gravitational redshift factor $z\equiv\nu_{\text{e}}/\nu_{\infty}-1$ of photons that were emitted from the {\it surface} of the star: $\Lambda\geq{3\over2}[1-(1+z)^{-2}]$ [here $R$ is the

Wei Xia, Jie Zou, Xingze Qiu, Feng Chen

Amidst the rapid advancements in experimental technology, noise-intermediate-scale quantum (NISQ) devices have become increasingly programmable, offering versatile opportunities to leverage quantum computational advantage. Here we explore the intricate dynamics of programmable NISQ devices for quantum reservoir computing. Using a genetic algorithm to configu

Ste Berta, Avril de Poisson, Kriemhild von Scherz, Saul Fools

In the last few decades, reading the literature, we realized that we Astronomers have a strong preference to undertake very ambitious projects, and search for answers to the most fundamental questions in the history of the entire Universe. After running multiple times into such cardinal quest, the curiosity became no more sustainable and we had to find out.

Floor S. Broekgaarden, Sharan Banagiri, Ethan Payne

How many gravitational-wave observations from double compact object mergers have we seen to date? This seemingly simple question surprisingly yields a somewhat ambiguous answer that depends on the chosen data-analysis pipeline, detection threshold and other underlying assumptions. To illustrate this we provide visualizations of the number of existing detecti

Guo-Yi Zhu, Nathanan Tantivasadakarn, Simon Trebst

Monitored quantum circuits allow for unprecedented dynamical control of many-body entanglement. Here we show that random, measurement-only circuits, implementing the competition of bond and plaquette couplings of the Kitaev honeycomb model, give rise to a structured volume-law entangled phase with subleading $L \ln L$ liquid scaling behavior. This interactin

Rachel Losacco, Zachary Claytor

The lower limit on the chicken density function (CDF) of the observable Universe was recently determined to be approximately 10$^{-21}$ chickens pc$^{-3}$. For over a year, however, the scientific community has struggled to determine the upper limit to the CDF. Here we aim to determine a reasonable upper limit to the CDF using multiple observational constrai

Qicheng Zhang, Karl Battams, Quanzhi Ye, Matthew M. Knight

Sunskirting asteroid (3200) Phaethon has been repeatedly observed in STEREO HI1 imagery to anomalously brighten and produce an antisunward tail for a few days near each perihelion passage, phenomena previously attributed to the ejection of micron-sized dust grains. Color imaging by the SOHO LASCO coronagraphs during the 2022 May apparition indicate that the

Jasleen Matharu, Adam Muzzin, Ghassan Sarrouh, Gabriel Brammer

We present the first results on the spatial distribution of dust attenuation at $1.0<z<2.4$ traced by the Balmer Decrement, H$\alpha$/H$\beta$, in emission-line galaxies using deep JWST NIRISS slitless spectroscopy from the CAnadian NIRISS Unbiased Cluster Survey (CANUCS). H$\alpha$ and H$\beta$ emission line maps of emission-line galaxies are extracted and

Justin Kaidi, Kantaro Ohmori, Yuji Tachikawa, Kazuya Yonekura

The common statement that any consistent quantum gravity theory contains dynamical objects with all possible charges suggests that there are still a number of hitherto-unidentified branes in string theory. Here we give the exact worldsheet description of near-horizon limits of non-supersymmetric $p$-branes in ten-dimensional $\mathrm{Spin}(32)/\mathbb{Z}_2$

Ian J. M. Crossfield

The newfound ability to detect SO2 in exoplanet atmospheres presents an opportunity to measure sulfur abundances and so directly test between competing modes of planet formation. In contrast to carbon and oxygen, whose dominant molecules are frequently observed, sulfur is much less volatile and resides almost exclusively in solid form in protoplanetary disks

Alessia Platania, Jaime Redondo-Yuste

Local higher-derivative corrections to the Einstein-Hilbert action yield sub-leading corrections to the Bekenstein-Hawking area law. Here we show that if the quantum effective action comprises a certain class of infrared non-localities, the entropy of large black holes generally diverges to either positive or negative infinity. In such theories, large spheri

Ruixiang Jiang, Can Wang, Jingbo Zhang, Menglei Chai

Neural implicit fields are powerful for representing 3D scenes and generating high-quality novel views, but it remains challenging to use such implicit representations for creating a 3D human avatar with a specific identity and artistic style that can be easily animated. Our proposed method, AvatarCraft, addresses this challenge by using diffusion models to

Xuanyao Chen, Zhijian Liu, Haotian Tang, Li Yi

High-resolution images enable neural networks to learn richer visual representations. However, this improved performance comes at the cost of growing computational complexity, hindering their usage in latency-sensitive applications. As not all pixels are equal, skipping computations for less-important regions offers a simple and effective measure to reduce t

Daniel Bolya, Judy Hoffman

The landscape of image generation has been forever changed by open vocabulary diffusion models. However, at their core these models use transformers, which makes generation slow. Better implementations to increase the throughput of these transformers have emerged, but they still evaluate the entire model. In this paper, we instead speed up diffusion models b

Fabio Tosi, Alessio Tonioni, Daniele De Gregorio, Matteo Poggi

We introduce a novel framework for training deep stereo networks effortlessly and without any ground-truth. By leveraging state-of-the-art neural rendering solutions, we generate stereo training data from image sequences collected with a single handheld camera. On top of them, a NeRF-supervised training procedure is carried out, from which we exploit rendere

Tzeviya Sylvia Fuchs, Yedid Hoshen

Unsupervised word segmentation in audio utterances is challenging as, in speech, there is typically no gap between words. In a preliminary experiment, we show that recent deep self-supervised features are very effective for word segmentation but require supervision for training the classification head. To extend their effectiveness to unsupervised word segme

Weihua Chen, Xianzhe Xu, Jian Jia, Hao luo

Human-centric visual tasks have attracted increasing research attention due to their widespread applications. In this paper, we aim to learn a general human representation from massive unlabeled human images which can benefit downstream human-centric tasks to the maximum extent. We call this method SOLIDER, a Semantic cOntrollable seLf-supervIseD lEaRning fr

Juan Urrutia, Ville Vaskonen, Hardi Veermäe

We study gravitational wave microlensing by primordial black holes (PBHs), accounting for the effect of a particle dark matter minihalo surrounding them. Such minihaloes are expected when PBHs make up only a fraction of all dark matter. We find that the LIGO-Virgo detections imply a $1\sigma$ bound on the abundance of PBHs heavier than $50 M_{\odot}$. The ne

Zichen Zhang, Luca Weihs

Episodic training, where an agent's environment is reset after every success or failure, is the de facto standard when training embodied reinforcement learning (RL) agents. The underlying assumption that the environment can be easily reset is limiting both practically, as resets generally require human effort in the real world and can be computationally expe

Wen Wang, Yan Jiang, Kangyang Xie, Zide Liu

Large-scale text-to-image diffusion models achieve unprecedented success in image generation and editing. However, how to extend such success to video editing is unclear. Recent initial attempts at video editing require significant text-to-video data and computation resources for training, which is often not accessible. In this work, we propose vid2vid-zero,

Hung-Yu Tseng, Qinbo Li, Changil Kim, Suhib Alsisan

Novel view synthesis from a single image has been a cornerstone problem for many Virtual Reality applications that provide immersive experiences. However, most existing techniques can only synthesize novel views within a limited range of camera motion or fail to generate consistent and high-quality novel views under significant camera movement. In this work,

Lingdong Kong, Youquan Liu, Xin Li, Runnan Chen

The robustness of 3D perception systems under natural corruptions from environments and sensors is pivotal for safety-critical applications. Existing large-scale 3D perception datasets often contain data that are meticulously cleaned. Such configurations, however, cannot reflect the reliability of perception models during the deployment stage. In this work,