October 2023 arXiv papers — page 148

Huaixiu Steven Zheng, Swaroop Mishra, Xinyun Chen, Heng-Tze Cheng

We present Step-Back Prompting, a simple prompting technique that enables LLMs to do abstractions to derive high-level concepts and first principles from instances containing specific details. Using the concepts and principles to guide reasoning, LLMs significantly improve their abilities in following a correct reasoning path towards the solution. We conduct

Ali AhmadiTeshnizi, Wenzhi Gao, Madeleine Udell

Optimization problems are pervasive across various sectors, from manufacturing and distribution to healthcare. However, most such problems are still solved heuristically by hand rather than optimally by state-of-the-art solvers, as the expertise required to formulate and solve these problems limits the widespread adoption of optimization tools and techniques

David Andriot, George Tringas

We consider two extensions of the so-called DGKT solution, a 4d scale-separated anti-de Sitter (AdS) solution obtained as a compactification on a 6d torus orbifold. Each extension consists in a specific large $n$ expansion beyond the DGKT solution, where $n$ is the unbounded $F_4$-flux parameter. One of the extensions considered generalizes the known warped,

Sherry Yang, Yilun Du, Kamyar Ghasemipour, Jonathan Tompson

Generative models trained on internet data have revolutionized how text, image, and video content can be created. Perhaps the next milestone for generative models is to simulate realistic experience in response to actions taken by humans, robots, and other interactive agents. Applications of a real-world simulator range from controllable content creation in

Zeyu Jia, Gene Li, Alexander Rakhlin, Ayush Sekhari

We study the problem of agnostic PAC reinforcement learning (RL): given a policy class $\Pi$, how many rounds of interaction with an unknown MDP (with a potentially large state and action space) are required to learn an $\epsilon$-suboptimal policy with respect to $\Pi$? Towards that end, we introduce a new complexity measure, called the \emph{spanning capac

Shaopeng Fu, Di Wang

Adversarial training (AT) is a canonical method for enhancing the robustness of deep neural networks (DNNs). However, recent studies empirically demonstrated that it suffers from robust overfitting, i.e., a long time AT can be detrimental to the robustness of DNNs. This paper presents a theoretical explanation of robust overfitting for DNNs. Specifically, we

Arth Bohra, Govert Verkes, Artem Harutyunyan, Pascal Weinberger

Text classification is a well-studied and versatile building block for many NLP applications. Yet, existing approaches require either large annotated corpora to train a model with or, when using large language models as a base, require carefully crafting the prompt as well as using a long context that can fit many examples. As a result, it is not possible fo

Tanishq Kumar, Blake Bordelon, Samuel J. Gershman, Cengiz Pehlevan

We propose that the grokking phenomenon, where the train loss of a neural network decreases much earlier than its test loss, can arise due to a neural network transitioning from lazy training dynamics to a rich, feature learning regime. To illustrate this mechanism, we study the simple setting of vanilla gradient descent on a polynomial regression problem wi

Simeng Qiu, Hadi Amata, Wolfgang Heidrich

Directional information measurement has many applications in domains such as robotics, virtual and augmented reality, and industrial computer vision. Conventional methods either require pre-calibration or necessitate controlled environments. The state-of-the-art MoireTag approach exploits the Moire effect and QR-design to continuously track the angular shift

Timothy Draher, Tomas Polakovic, Yi Li, John Pearson

We introduce a design modification to conventional geometry of the cryogenic three-terminal switch, the nanocryotron (nTron). The conventional geometry of nTrons is modified by including parallel current-carrying channels, an approach aimed at enhancing the device's performance in magnetic field environments. The common challenge in nTron technology is to ma

Li He

In an era where the global population is aging significantly, cognitive impairments among the elderly have become a major health concern. The need for effective assistive technologies is clear, and facial recognition systems are emerging as promising tools to address this issue. This document discusses the development and evaluation of a new Multifunctional

Thiago J. Pinheiro dos Santos, Betul Orcan-Ekmekci, Walter G. Chapman, Philip M. Singer

Traditional theories of the NMR autocorrelation function for intramolecular dipole pairs assume single-exponential decay, yet the calculated autocorrelation of realistic systems display a rich, multi-exponential behavior resulting in anomalous NMR relaxation dispersion (i.e., frequency dependence). We develop an approach to model and interpret the multi-expo

Maryam Kheirandish, Shengfan Zhang, Donald G. Catanzaro, Valeriu Crudu

The use of Deep Neural Network (DNN) models in risk-based decision-making has attracted extensive attention with broad applications in medical, finance, manufacturing, and quality control. To mitigate prediction-related risks in decision making, prediction confidence or uncertainty should be assessed alongside the overall performance of algorithms. Recent st

Abhishek Oswal, Ananth N. Shankar, Xinwen Zhu, Anand Patel

We prove that Shimura varieties of abelian type satisfy a $p$-adic Borel-extension property over discretely valued fields. More precisely, let $\mathsf{D}$ denote the rigid-analytic closed unit disc and $\mathsf{D}^{\times} = \mathsf{D} \setminus \{0\}$, let $X$ be a smooth rigid-analytic variety, and let $S(G,\mathcal{H})_{\mathsf{K}}$ denote a Shimura vari

Pavel Denisov, Ngoc Thang Vu

A number of methods have been proposed for End-to-End Spoken Language Understanding (E2E-SLU) using pretrained models, however their evaluation often lacks multilingual setup and tasks that require prediction of lexical fillers, such as slot filling. In this work, we propose a unified method that integrates multilingual pretrained speech and text models and

Mehdi Frachet, Liran Wang, Wei Xia, Yanfeng Guo

The kagome materials AV4$_3$Sb$_5$ (A = K, Rb, Cs) host an intriguing interplay between unconventional superconductivity and charge-density-waves. Here, we investigate CsV$_3$Sb$_5$ by combining high-resolution thermal-expansion, heat-capacity and electrical resistance under strain measurements. We directly unveil that the superconducting and charge-ordered

Daniel Israel, Aditya Grover, Guy Van den Broeck

Backdoor adjustment is a technique in causal inference for estimating interventional quantities from purely observational data. For example, in medical settings, backdoor adjustment can be used to control for confounding and estimate the effectiveness of a treatment. However, high dimensional treatments and confounders pose a series of potential pitfalls: tr

Mathias Van Den Bossche, Philippe Grangier

We argue that a clear view on quantum mechanics is obtained by considering that the unicity of the macroscopic world is a fundamental postulate of physics, rather than an issue that must be mathematically justified or demonstrated. This postulate allows a framework in which quantum mechanics can be constructed, in a complete mathematically consistent way. Th

Dawoon E. Kim, Laura Di Gesu, Ioannis Liodakis, Alan P. Marscher

We conducted a polarimetry campaign from radio to X-ray wavelengths of the high-synchrotron-peak (HSP) blazar Mrk 421, including Imaging X-ray Polarimetry Explorer (IXPE) measurements on 2022 December 6-8. We detected X-ray polarization of Mrk 421 with a degree of $\Pi_{\rm X}$=14$\pm$1$\%$ and an electric-vector position angle $\psi_{\rm X}$=107$\pm$3$^{\ci

Charles Powell, Peter Haynes, John Taylor

We use large-eddy simulations to study the penetration of a buoyant plume carrying a passive tracer into a stably stratified layer with constant buoyancy frequency. Using a buoyancy-tracer volume distribution, we develop a method for objectively partitioning plume fluid in buoyancy-tracer space into three regions, each of which corresponds to a coherent regi

Gopal Bhatta, Sarvesh Gharat, Abhimanyu Borthakur, Aman Kumar

Machine learning has emerged as a powerful tool in the field of gamma-ray astrophysics. The algorithms can distinguish between different source types, such as blazars and pulsars, and help uncover new insights into the high-energy universe. The Large Area Telescope (LAT) on-board the Fermi Gamma-ray telescope has significantly advanced our understanding of t

Rishi Rao, Li Zhu

Heavy fermion materials have been a rich playground for strongly correlated physics for decades. However, engineering tunable and synthesizable heavy fermion materials remains a challenge. We strive to integrate heavy fermion properties into carbon boron clathrates as a universal structure which can host a diverse array of interesting physical phenomena. Usi

Elisabetta Carlini, Antonio Siconolfi

A new algorithm for time dependent Hamilton Jacobi equations on networks, based on semi Lagrangian scheme, is proposed. It is based on the definition of viscosity solution for this kind of problems recently given in. A thorough convergence analysis, not requiring weak semilimits, is provided. In particular, the check of the supersolution property at the vert

I. A. Aleksandrov, A. Kudlis, I. A. Shelykh

We revisit the problem of a two dimensional trion in an external magnetic field. We demonstrate that the approximations used previously for finding the energy spectrum of this system break down in the experimentally accessible range of magnetic fields. It is shown that the neglect of the Coulomb-induced mixing of different Landau levels corresponding to non-

Ching Fang, Kimberly L Stachenfeld

The ability to predict upcoming events has been hypothesized to comprise a key aspect of natural and machine cognition. This is supported by trends in deep reinforcement learning (RL), where self-supervised auxiliary objectives such as prediction are widely used to support representation learning and improve task performance. Here, we study the effects predi

Ion Simaciu, Gheorghe Dumitrescu, Zoltan Borsos, Viorel Drafta

The outcome of this paper was a shape of the interaction of two oscillating bubbles. This was done to express the secondary Bjerknes force using the Maxwell equations for a liquid. These subsequent equations were written for the quantities velocity, pressure, and density as deviations from steady state. Also, as it will show in the following rows, we found t

Alexander Iksanov, Valeriya Kotelnikova

In the Karlin infinite occupancy scheme, balls are thrown independently into an infinite array of boxes $1$, $2,\ldots$, with probability $p_k$ of hitting the box $k$. For $j,n\in\mathbb{N}$, denote by $\mathcal{K}^*_j(n)$ the number of boxes containing exactly $j$ balls provided that $n$ balls have been thrown. We call $\textit{small counts}$ the variables

Berk Ceylan

We prove that a simple closed plane curve with curvature at most 1 and diameter at least 4, surrounds two disjoint open unit disks. We also pose an open question relating the diameter lower bound to the length of the curve.

Hauke Gravenkamp, Bor Plestenjak, Daniel A. Kiefer

The dispersion curves of (elastic) waveguides frequently exhibit crossings and osculations (also known as veering, repulsion, or avoided crossing). Osculations are regions in the dispersion diagram where curves approach each other arbitrarily closely without ever crossing before veering apart. In semi-analytical (undamped) waveguide models, dispersion curves

Lorenzo Vianello, Emek Barış Küçüktabak, Matthew Short, Clément Lhoste

Sit-to-Stand (StS) is a fundamental daily activity that can be challenging for stroke survivors due to strength, motor control, and proprioception deficits in their lower limbs. Existing therapies involve repetitive StS exercises, but these can be physically demanding for therapists while assistive devices may limit patient participation and hinder motor lea

Andres M Bran, Philippe Schwaller

Language modeling has seen impressive progress over the last years, mainly prompted by the invention of the Transformer architecture, sparking a revolution in many fields of machine learning, with breakthroughs in chemistry and biology. In this chapter, we explore how analogies between chemical and natural language have inspired the use of Transformers to ta

MicroBooNE collaboration, P. Abratenko, O. Alterkait, D. Andrade Aldana

We present a set of new generalized kinematic imbalance variables that can be measured in neutrino scattering. These variables extend previous measurements of kinematic imbalance on the transverse plane, and are more sensitive to modeling of nuclear effects. We demonstrate the enhanced power of these variables using simulation, and then use the MicroBooNE de

Aleksei Ustimenko, Aleksandr Beznosikov

In this work, we consider rather general and broad class of Markov chains, Ito chains, that look like Euler-Maryama discretization of some Stochastic Differential Equation. The chain we study is a unified framework for theoretical analysis. It comes with almost arbitrary isotropic and state-dependent noise instead of normal and state-independent one as in mo

Aditya Kulkarni, Guruprasad Parasnis, Harish Balasubramanian, Vansh Jain

Lung diseases such as COVID-19, tuberculosis (TB), and pneumonia continue to be serious global health concerns that affect millions of people worldwide. In medical practice, chest X-ray examinations have emerged as the norm for diagnosing diseases, particularly chest infections such as COVID-19. Paramedics and scientists are working intensively to create a r

Derick Diana, Tim Gebbie

We extend a Discrete Time Random Walk (DTRW) numerical scheme to simulate the anomalous diffusion of financial market orders in a simulated order book. Here using random walks with Sibuya waiting times to include a time-dependent stochastic forcing function with non-uniformly sampled times between order book events in the setting of fractional diffusion. Thi

Md. Fahad Hossain Mishu, Rafia Rizwana Rahim, Md. Ashiqur Rahman

Numerous fires break out, especially from January to March every year, destroying thousands of shelters in the Rohingya Refugee Camps. In this study, a computational approach has been taken to analyze the fire dynamic behavior of informal settlements (ISs) in Rohingya Refugee Camps. The design parameters for the mathematical model are determined based on a c

Zhiyuan Zhao, Haoxin Liu, Alexander Rodriguez, B. Aditya Prakash

Time-series forecasting is a critical challenge in various domains and has witnessed substantial progress in recent years. Many real-life scenarios, such as public health, economics, and social applications, involve feedback loops where predictions can influence the predicted outcome, subsequently altering the target variable's distribution. This phenomenon,

Dhwani Vaishnav, Manimozhi Neethinayagam, Akanksha S Khaire, Mansi Vivekanand Dhoke

Consumer complaints are a crucial source of information for companies, policymakers, and consumers alike. They provide insight into the problems faced by consumers and help identify areas for improvement in products, services, and regulatory frameworks. This paper aims to analyze Consumer Complaints Dataset provided by Consumer Financial Protection Bureau (C

Swati Padhee, Tanvi Banerjee, Daniel M. Abrams, Nirmish Shah

Sickle Cell Disease (SCD) is a chronic genetic disorder characterized by recurrent acute painful episodes. Opioids are often used to manage these painful episodes; the extent of their use in managing pain in this disorder is an issue of debate. The risk of addiction and side effects of these opioid treatments can often lead to more pain episodes in the futur

Aristotelis Papatheodorou, Wolfgang Merkt, Alexander L. Mitchell, Ioannis Havoutis

The current state-of-the-art gradient-based optimisation frameworks are able to produce impressive dynamic manoeuvres such as linear and rotational jumps. However, these methods, which optimise over the full rigid-body dynamics of the robot, often require precise foothold locations apriori, while real-time performance is not guaranteed without elaborate regu

Suvechhya Lamichhane, Rupak Timalsina, Cody Schultz, Ilja Fescenko

Nitrogen-vacancy (NV) magnetometry offers an alternative tool to detect paramagnetic centers in cells with a favorable combination of magnetic sensitivity and spatial resolution. Here, we employ NV magnetic relaxometry to detect cytochrome C (Cyt-C) nanoclusters. Cyt-C is a water-soluble protein that plays a vital role in the electron transport chain of mito

Yuta Koike

Motivated by statistical analysis of latent factor models for high-frequency financial data, we develop sharp upper bounds for the spectral norm of the realized covariance matrix of a high-dimensional It\^o semimartingale with possibly infinite activity jumps. For this purpose, we develop Burkholder-Gundy type inequalities for matrix martingales with the hel

Detai Xin, Junfeng Jiang, Shinnosuke Takamichi, Yuki Saito

We present the JVNV, a Japanese emotional speech corpus with verbal content and nonverbal vocalizations whose scripts are generated by a large-scale language model. Existing emotional speech corpora lack not only proper emotional scripts but also nonverbal vocalizations (NVs) that are essential expressions in spoken language to express emotions. We propose a

Jozef Kratica, Vera Kovačević-Vujčić, Mirjana Čangalović

In this paper a new graph invariant based on the minimal hitting set problem is introduced. It is shown that it represents a tight lower bound for the doubly metric dimension of a graph. Exact values of new invariant for paths, stars, complete graphs and complete bipartite graph are obtained. The paper analyzes some tight bounds for the new invariant in gene

Jonathan Asher Pachter, Ying-Jen Yang, Ken A. Dill

Statistical physics aims to describe properties of macroscale systems in terms of distributions of their microscale agents. Its central tool is the maximization of entropy, a variational principle. We review the history of this principle, first considered as a law of nature, more recently as a procedure for inference in model-making. And while equilibria (EQ

Zhaoqi Li, Kevin Jamieson, Lalit Jain

Given a set of arms $\mathcal{Z}\subset \mathbb{R}^d$ and an unknown parameter vector $\theta_\ast\in\mathbb{R}^d$, the pure exploration linear bandit problem aims to return $\arg\max_{z\in \mathcal{Z}} z^{\top}\theta_{\ast}$, with high probability through noisy measurements of $x^{\top}\theta_{\ast}$ with $x\in \mathcal{X}\subset \mathbb{R}^d$. Existing (as

Milad Vazan, Fatemeh Sadat Masoumi, Ruizhi Ou, Reza Rawassizadeh

Fitness applications are commonly used to monitor activities within the gym, but they often fail to automatically track indoor activities inside the gym. This study proposes a model that utilizes pose estimation combined with a novel data augmentation method, i.e., rotation matrix. We aim to enhance the classification accuracy of activity recognition based o

Aihui Liu, Joar Axås, George Haller

We present a data-driven and interpretable approach for reducing the dimensionality of chaotic systems using spectral submanifolds (SSMs). Emanating from fixed points or periodic orbits, these SSMs are low-dimensional inertial manifolds containing the chaotic attractor of the underlying high-dimensional system. The reduced dynamics on the SSMs turn out to pr

Hauke Gravenkamp, Simon Pfeil, Ramon Codina

The Reynolds equation, combined with the Elrod algorithm for including the effect of cavitation, resembles a nonlinear convection-diffusion-reaction (CDR) equation. Its solution by finite elements is prone to oscillations in convection-dominated regions, which are present whenever cavitation occurs. We propose a stabilized finite-element method that is based

Xiaoli Hu, Naihong Hu, Bing Yu, Naihuan Jing

By revisiting the mathematical foundation of the uncertainty relation, skew information-based uncertainty sequences are developed for any two quantum channels. A reinforced version of the Cauchy-Schwarz inequality is adopted to improve the uncertainty relation, and a sampling technique of observables' coordinates is used to offset randomness in the inequalit

Tom Dove, Thomas Schick

Topological T-duality is a relationship between pairs (E, P ) over a fixed space X, where E over X is a principal torus bundle and P over E is a twist, such as a gerbe of principal PU(H)-bundle. This is of interest to topologists because of the T-duality transformation: a T-duality relation between pairs (E, P ) and (F, Q ) comes with an isomorphism (with de

Yordan D. Ignatov, Jonathan R. Pritchard, Yuqing Wu

A measurement of the 21-cm global signal would be a revealing probe of the Dark Ages, the era of first star formation, and the Epoch of Reionization. It has remained elusive owing to bright galactic and extra-galactic foreground contaminants, coupled with instrumental noise, ionospheric effects, and beam chromaticity. The simultaneous detection of a consiste

Simone Manti, Marco Miliucci, Alessandro Scordo, Roberto Bedogni

Determining the oxidation states of metals assumes great importance in various applications because a variation in the oxidation number can drastically influence the material properties. As an example, this becomes evident in edible liquids like wine and oil, where a change in the oxidation states of the contained metals can significantly modify both the ove

Siddharth D Jaiswal, Ankit Kumar Verma, Animesh Mukherjee

AI models have become extremely popular and accessible to the general public. However, they are continuously under the scanner due to their demonstrable biases toward various sections of the society like people of color and non-binary people. In this study, we audit three existing gender analyzers -- uClassify, Readable and HackerFactor, for biases against n

Peng Zhang, Ting Gao, Jin Guo, Jinqiao Duan

Early warning for epilepsy patients is crucial for their safety and well-being, in particular to prevent or minimize the severity of seizures. Through the patients' EEG data, we propose a meta learning framework to improve the prediction of early ictal signals. The proposed bi-level optimization framework can help automatically label noisy data at the early

Michel van Garrel, Navid Nabijou, Yannik Schuler

A bicyclic pair is a smooth surface equipped with a pair of smooth divisors intersecting in two reduced points. Resolutions of self-nodal curves constitute an important special case. We investigate the logarithmic Gromov-Witten theory of bicyclic pairs. We establish correspondences with local Gromov-Witten theory and open Gromov-Witten theory in all genera,

Yasin Dus, Georgiy Nefedov

The World Health Organization (WHO) estimated that approximately 1.4 million individuals worldwide died by suicide in 2022. This figure indicates that one person died by suicide every 20 s during the year. Globally, suicide is the tenth-leading cause of death, while it is the second-leading cause of death among young people aged 15329 years. In 2022, it was

Asako Sato, Kazuki Tokuda, Masahiro N. Machida, Kengo Tachihara

We present the detection of a secondary outflow associated with a Class I source, Ser-emb 15, in the Serpens Molecular Cloud. We reveal two pairs of molecular outflows consisting of three lobes, namely primary and secondary outflows, using ALMA 12CO and SiO line observations at a resolution of 318 au. The secondary outflow is elongated approximately perpendi

Joseph Bramante, Andrew Buchanan

A new approach is presented to compute entropy for massless scalar quantum fields. By perturbing a skewed correlation matrix composed of field operator correlation functions, the mutual information is obtained for disjoint spherical regions of size $r$ at separation $R$, including an expansion to all orders in $r/R$. This approach also permits a perturbative

Hao Li, Jie Zhu, Bo-Qiang Ma

The High Energy Stereoscopic System (H.E.S.S) Collaboration reported the discovery of a novel radiation component from the Vela pulsar by their Cherenkov telescopes. It is of great importance that gamma rays with energies of at least 20~TeV are recorded unexpectedly. The H.E.S.S Collaboration argued that such results may challenge the state-of-the-art models

Gaia Collaboration, Gaia Collaboration, M. Trabucchi, N. Mowlavi

The third Gaia Data Release (DR3) provided photometric time series of more than 2 million long-period variable (LPV) candidates. Anticipating the publication of full radial-velocity (RV) in DR4, this Focused Product Release (FPR) provides RV time series for a selection of LPVs with high-quality observations. We describe the production and content of the Gaia

Akhil Uniyal, Surajit Kalita, Sayan Chakrabarti

Fundamental constants are crucial for comprehending physical mechanisms, but their measurements contain uncertainties due to experimental limitations. We investigate the impact of system temperature on these uncertainties using nearby white dwarfs observed in the Gaia Early Data Release 3 (EDR3) survey. Using the structures of these white dwarfs, we show tha

Athena Karsa, Alasdair Fletcher, Gaetana Spedalieri, Stefano Pirandola

Quantum illumination (QI) and quantum radar have emerged as potentially groundbreaking technologies, leveraging the principles of quantum mechanics to revolutionise the field of remote sensing and target detection. The protocol, particularly in the context of quantum radar, has been subject to a great deal of aspirational conjecture as well as criticism with

Gokhan Alkac, Mehmet Kemal Gumus, Oguzhan Kasikci, Mehmet Ali Olpak

We propose a regularization procedure in the sourced Weyl double copy, a spinorial version of the classical double copy, such that it matches much more general results in the Kerr-Schild version. In the regularized Weyl double copy, the anti-de Sitter (AdS) and the Lifshitz black holes, which form the basis of the study of strongly coupled gauge theories at

Adrian Alan Pol, Ekaterina Govorkova, Sonja Gronroos, Nadezda Chernyavskaya

Unsupervised deep learning techniques are widely used to identify anomalous behaviour. The performance of such methods is a product of the amount of training data and the model size. However, the size is often a limiting factor for the deployment on resource-constrained devices. We present a novel procedure based on knowledge distillation for compressing an

Dipayan Saha, Shams Tarek, Katayoon Yahyaei, Sujan Kumar Saha

As the ubiquity and complexity of system-on-chip (SoC) designs increase across electronic devices, the task of incorporating security into an SoC design flow poses significant challenges. Existing security solutions are inadequate to provide effective verification of modern SoC designs due to their limitations in scalability, comprehensiveness, and adaptabil

Yingkai Sha, Ryan A. Sobash, David John Gagne

An ensemble post-processing method is developed for the probabilistic prediction of severe weather (tornadoes, hail, and wind gusts) over the conterminous United States (CONUS). The method combines conditional generative adversarial networks (CGANs), a type of deep generative model, with a convolutional neural network (CNN) to post-process convection-allowin

Wenjin Zhao, Bowen Shen, Zui Tao, Sunghoon Kim

The interaction of a lattice of localized magnetic moments with a sea of conduction electrons in Kondo lattice models induces rich quantum phases of matter, such as Fermi liquids with heavily renormalized electronic quasiparticles, quantum critical non-Fermi liquid metals and unconventional superconductors, among others. The recent demonstration of moir\'e K

B. C. Cornell, W. A. Atkinson

Domain wall morphologies in ferroelectrics are believed to be largely shaped by electrostatic forces. Here, we show that for conducting domain walls, the morphology also depends on the details of the charge-carrier band structure. For concreteness, we focus on transition-metal perovskites like BaTiO$_3$ and SrTiO$_3$. These have a triplet of $t_{2g}$ orbital

Gopal Yadav

As applications of arXiv:2004.07259, the first part of the thesis is based on (i) arXiv:2011.04660 wherein we computed the low energy coupling constants of SU(3) chiral perturbation theory at NLO in the chiral expansion in the chiral limit, from the type IIA string dual inclusive of ${\cal O}(R^4)$ corrections and found a novel HD-large-$N$ connection; (ii)

Robert-Jeron Reifert, Hayssam Dahrouj, Aydin Sezgin

Extended reality (XR) applications often perform resource-intensive tasks, which are computed remotely, a process that prioritizes the latency criticality aspect. To this end, this paper shows that through leveraging the power of the central cloud (CC), the close proximity of edge computers (ECs), and the flexibility of uncrewed aerial vehicles (UAVs), a UAV

Julius Julius, Nika Sokolova

We analyse the CFT-data of planar 4D $\mathcal{N} = 4$ Super-Yang-Mills theory at strong coupling. By combining spectral data extracted from integrability, with recent advances in computing the AdS Virasoro-Shapiro amplitude, we extract predictions for leading order OPE coefficients on entire Kaluza-Klein (KK-)towers of states. We observe that the appropriat

Erik Plauschinn, Lorenz Schlechter

We determine all flux vacua with flux numbers $N_{\rm flux}\leq 10$ for a type IIB orientifold-compactification on the mirror-octic three-fold. To achieve this, we develop and apply techniques for performing a complete scan of flux vacua for the whole moduli space - we do not randomly sample fluxes nor do we consider only boundary regions of the moduli space

Basabendu Barman, Nicolás Bernal, Javier Rubio

We show, within the single-field inflationary paradigm, that a linear non-minimal interaction $\xi\,M_P\,\phi\,R$ between the inflaton field $\phi$ and the Ricci scalar $R$ can result in successful inflation that concludes with an efficient heating of the Universe via perturbative decays of the inflaton, aided entirely by gravity. Considering the inflaton fi

Nikola Herceg, Tajron Jurić, Andjelo Samsarov, Ivica Smolić

We use the framework of Hopf algebra and noncommutative differential geometry to build a noncommutative (NC) theory of gravity in a bottom-up approach. Noncommutativity is introduced via deformed Hopf algebra of diffeomorphisms by means of a Drinfeld twist. The final result of the construction is a general formalism for obtaining NC corrections to the classi

F. D. Priestley, P. C. Clark, S. C. O. Glover, S. E. Ragan

Star formation activity in molecular clouds is often found to be correlated with the amount of material above a column density threshold of $\sim 10^{22} \, {\rm cm^{-2}}$. Attempts to connect this column density threshold to a ${\it volume}$ density above which star formation can occur are limited by the fact that the volume density of gas is difficult to r

Claudia Artiaco, Christoph Fleckenstein, David Aceituno Chávez, Thomas Klein Kvorning

During time evolution of many-body systems entanglement grows rapidly, limiting exact simulations to small-scale systems or small timescales. Quantum information tends however to flow towards larger scales without returning to local scales, such that its detailed large-scale structure does not directly affect local observables. This allows for the removal of

Celia Desgrange, Julien Milli, Gael Chauvin, Thomas Henning

The discovery of planets orbiting at less than 1 au from their host star and less massive than Saturn in various exoplanetary systems revolutionized our theories of planetary formation. The fundamental question is whether these close-in low-mass planets could have formed in the inner disk interior to 1 au, or whether they formed further out in the planet-for

Michael G. Jabbour, Leonardo Novo

It is well known in quantum optics that any process involving the preparation of a multimode gaussian state, followed by a gaussian operation and gaussian measurements, can be efficiently simulated by classical computers. Here, we provide evidence that computing transition amplitudes of Gaussian processes with a single-layer of non-linearities is hard for cl

Dongjun Li, Asad Hussain, Pratik Wagle, Yanbei Chen

General relativity, though the most successful theory of gravity, has been continuously modified to resolve its incompatibility with quantum mechanics and explain the origin of dark energy or dark matter. One way to test these modified gravity theories is to study the gravitational waves emitted during the ringdown of binary mergers, which consist of quasino

Siyao Xu, Hui Li

We investigate the role of the magnetohydrodynamic (MHD) turbulence measured by Voyager in the very local interstellar medium (VLISM) in modeling the Interstellar Boundary Explorer (IBEX) ribbon. We demonstrate that the mirroring by compressible modes of MHD turbulence dominates over that by the mean magnetic field. Based on the new mirror diffusion mechanis

Tianqi Chen, Tim Byrnes

Quantum state preparation plays a crucial role in several areas of quantum information science, in applications such as quantum simulation, quantum metrology and quantum computing. However, typically state preparation requires resources that scale exponentially with the problem size, due to their probabilistic nature or otherwise, making studying such models

M. Uldemolins, A. Mesaros, G. D. Gu, A. Palacio-Morales

Understanding the interplay between individual magnetic impurities and superconductivity is crucial for bottom-up construction of novel phases of matter. For decades, the description by Yu, Shiba and Rusinov (YSR) of single spins in a superconductor and its extension to include quantum effects has proven highly successful: the pair-breaking potential of the

Andrea Lapi, Lumen Boco, Marcos M. Cueli, Balakrishna S. Haridasu

[abridged] We propose a model of the Universe (dubbed $\eta$CDM) featuring a stochastic evolution of the cosmological quantities, that is meant to render small deviations from homogeneity/isotropy on scales of $30-50\, h^{-1}$ Mpc at late cosmic times, associated to the emergence of the cosmic web. Specifically, we prescribe that the behavior of the matter/r

Francesca Acanfora, Andrea Guerrieri, Kelian Häring, Denis Karateev

We study the space of $2\to 2$ scattering amplitudes of neutral Goldstone bosons in four space-time dimensions. We establish universal bounds on the first two non-universal Wilson coefficients of the low energy Effective Field Theory (EFT) for such particles. We reconstruct the analytic, crossing-symmetric, and unitary amplitudes saturating our bounds, and w

T. C. van Thiel, M. J. Weaver, F. Berto, P. Duivestein

Superconducting quantum processors have made significant progress in size and computing potential. However, the practical cryogenic limitations of operating large numbers of superconducting qubits are becoming a bottleneck for further scaling. Due to the low thermal conductivity and the dense optical multiplexing capacity of telecommunications fiber, convert

Aviral Prakash, Ish Gupta, Matteo Breschi, Rahul Kashyap

We study the detectability of postmerger QCD phase transitions in neutron star binaries with next-generation gravitational-wave detectors Cosmic Explorer and Einstein Telescope. We perform numerical relativity simulations of neutron star mergers with equations of state that include a quark deconfinement phase transition through either a Gibbs or Maxwell cons

Zhi-Qiang Gao, Yu-Ping Lin, Dung-Hai Lee

We propose the ``pair-breaking scattering interference" as a general source of coherence peak modulations in superconductors. Assuming this mechanism, we present a simple physical picture for the coherence peak modulations in overdoped cuprate Bi$_2$Sr$_2$Ca$_2$Cu$_3$O$_{10+\delta}$ (Bi-2223), ferromagnetic iron pnictide EuRbFe$_4$As$_4$ (Eu-1144), and kagom

Sumanta Chakraborty, Elisa Maggio, Michela Silvestrini, Paolo Pani

We develop a framework to compute the tidal response of a Kerr-like compact object in terms of its reflectivity, compactness, and spin, both in the static and the frequency-dependent case. Here we focus on the low-frequency regime, which can be solved fully analytically. We highlight some remarkable novel features, in particular: i) Even in the zero-frequenc

Farzan Vafa, David R. Nelson, Amin Doostmohammadi

Geometric confinement and topological constraints present promising means of controlling active materials. By combining analytical arguments derived from the Born-Oppenheimer approximation with numerical simulations, we investigate the simultaneous impact of confinement together with curvature singularity by characterizing the dynamics of an active nematic o

Bjoern Hassfeld, Arthur Hebecker, Johannes Walcher

We study bubble of nothing decays and their reverse processes, the creation of vacua through `bubbles of something', in models of the Universe based on string theory. From the four-dimensional perspective, the corresponding gravitational instantons contain an end-of-the-world (ETW) boundary or brane, realized by the internal manifold shrinking to zero size.

Maximilian Seitzer, Sjoerd van Steenkiste, Thomas Kipf, Klaus Greff

Visual understanding of the world goes beyond the semantics and flat structure of individual images. In this work, we aim to capture both the 3D structure and dynamics of real-world scenes from monocular real-world videos. Our Dynamic Scene Transformer (DyST) model leverages recent work in neural scene representation to learn a latent decomposition of monocu

Brandon Melcher, Arnab Pradhan, Scott Watson

We propose a cosmological lingering phase for the initial state prior to inflation which would help address the singularity problem of inflation. The universe begins with a constant (Hagedorn) temperature and then transitions into an inflationary universe while preserving the Null Energy Condition (NEC). In such a universe time is presumably emergent, callin

Nikola Herceg, Tajron Jurić, Andjelo Samsarov, Ivica Smolić

A quest for phenomenological footprints of quantum gravity is among the central scientific tasks in the rising era of gravitational wave astronomy. We study gravitational wave dynamics within the noncommutative geometry framework, based on a Drinfeld twist and newly proposed noncommutative Einstein equation, and obtain the leading quantum correction to Regge

Jonas Frerick, Joerg Jaeckel, Felix Kahlhoefer, Kai Schmidt-Hoberg

We note the possibility to perform a parametrically improved search for gauged baryon ($B$) and baryon minus lepton ($B-L$) Dark Photon Dark Matter (DPDM) using auxiliary channel data from LISA Pathfinder. In particular we use the measurement of the differential movement between the test masses (TMs) and the space craft (SC) which is nearly as sensitive as t

Yihan Wang, Rosalba Perna, Zhaohuan Zhu

The discovery of planetary systems beyond our solar system has challenged established theories of planetary formation. Planetary orbits display a variety of unexpected architectures, and free-floating planets appear ubiquitous. The recent detection of candidate Jupiter Mass Binary Objects (JuMBOs) by the James Webb Space Telescope (JWST) has added another pu

Christian Ferko, Alisha Gupta, Eashan Iyer

We quantize the ModMax oscillator, which is the dimensional reduction of the Modified Maxwell theory to one spacetime dimension. We show that the propagator of the ModMax oscillator satisfies a differential equation related to the Laplace equation in cylindrical coordinates, and we obtain expressions for the classical and quantum partition functions of the t

Maciej Kolanowski, Marija Tomašević

We study black holes in two and three dimensions that have spacelike curvature singularities behind horizons. The 2D solutions are obtained by dimensionally reducing certain 3D black holes, known as quantum BTZ solutions. Furthermore, we identify the corresponding dilaton potential and show how it can arise from a higher-dimensional theory. Finally, we show

Vincent Savignac, Eve J. Lee

Super-Earths and mini-Neptunes are the most common types of exoplanets discovered, yet the physics of their formation are still debated. Standard core accretion models in gas-rich environment find that typical mini-Neptune mass planets would blow up into Jupiters before the underlying disk gas dissipates away. The injection of entropy from the protoplanetary

Ofer Aharony, Anatoly Dymarsky, Alfred D. Shapere

We provide a precise relation between an ensemble of Narain conformal field theories (CFTs) with central charge $c=n$, and a sum of $(U(1) \times U(1))^n$ Chern-Simons theories on different handlebody topologies. We begin by reviewing the general relation of additive codes to Narain CFTs. Then we describe a holographic duality between any given Narain theory