November 2022 arXiv papers — page 2

Naman Saxena, Gorantla Sandeep, Pushpak Jagtap

Signal Temporal Logic (STL) is a powerful framework for describing the complex temporal and logical behaviour of the dynamical system. Numerous studies have attempted to employ reinforcement learning to learn a controller that enforces STL specifications; however, they have been unable to effectively tackle the challenges of ensuring robust satisfaction in c

Angeliki Menegaki, Clément Mouhot

This is a review based on the presentation done at the seminar Laurent Schwartz in December 2021. It is announcing results in the forthcoming [Menegaki-Mouhot-Marahrens'22]. This work presents a new simple quantitative method for proving the hydrodynamic limit of a class of interacting particle systems on lattices. We present here this method in a simplified

Michael te Vrugt, Jens Bickmann, Raphael Wittkowski

The study of active soft matter has developed into one of the most rapidly growing areas of physics. Field theories, which can be developed either via phenomenological considerations or by coarse-graining of a microscopic model, are a very useful tool for understanding active systems. Here, we provide a detailed review of a particular coarse-graining procedu

Zahi Hazan

We give a general identity relating Eisenstein series on general linear groups. We do it by constructing an Eisenstein series, attached to a maximal parabolic subgroup and a pair of representations, one cuspidal and the other a character, and express it in terms of a degenerate Eisenstein series. In the local fields analogue, we prove the convergence in a ha

Jochen Glück, Michael Kaplin

Relatively uniformly continuous (ruc) semigroups were recently introduced and studied by Kandi\'c, Kramar-Fijav\v{z}, and the second-named author, in order to make the theory of one-parameter operator semigroups available in the setting of vector lattices, where no norm is present in general. In this article, we return to the more standard Banach lattice set

Trey W. Jensen, Yacine Ali-Haïmoud

It is known that Primordial Black Holes (PBHs) can leave an imprint on Cosmic Microwave Background (CMB) anisotropy power spectra, due to their accretion-powered injection of energy into the recombining plasma. Here we study a qualitatively new CMB observable sourced by accreting PBHs: the temperature trispectrum or connected 4-point function. This non-Gauss

Yookoon Park, Mahmoud Azab, Bo Xiong, Seungwhan Moon

Cross-modal contrastive learning has led the recent advances in multimodal retrieval with its simplicity and effectiveness. In this work, however, we reveal that cross-modal contrastive learning suffers from incorrect normalization of the sum retrieval probabilities of each text or video instance. Specifically, we show that many test instances are either ove

S. P. Pogossian

In this paper, I re-examine the question of a possible explanation of the anomalous advance of Mercury's perihelion by the existence of the hypothetical planet Vulcan proposed by Le Verrier, whose orbit would be located inside the orbit of Mercury. My calculations are focused on the optimization of the orbital parameters of Vulcan in order to explain precise

Hao Ding, Jie Ying Wu, Zhaoshuo Li, Mathias Unberath

Purpose: Vision-based robot tool segmentation plays a fundamental role in surgical robots and downstream tasks. CaRTS, based on a complementary causal model, has shown promising performance in unseen counterfactual surgical environments in the presence of smoke, blood, etc. However, CaRTS requires over 30 iterations of optimization to converge for a single i

Tushar Agarwal, Nithin Sugavanam, Emre Ertin

Generative models learned from training using deep learning methods can be used as priors in inverse under-determined inverse problems, including imaging from sparse set of measurements. In this paper, we present a novel hierarchical deep-generative model MrSARP for SAR imagery that can synthesize SAR images of a target at different resolutions jointly. MrSA

Muhammad Islam, Mubashir Husain Rehmani, Jinjun Chen

The integration of permissioned blockchain such as Hyperledger fabric (HF) and Industrial internet of Things (IIoT) has opened new opportunities for interdependent supply chain partners to improve their performance through data sharing and coordination. The multichannel mechanism, private data collection and querying mechanism of HF enable private data shari

Catherine Zucker, João Alves, Alyssa Goodman, Stefan Meingast

Most of what we know about the formation of stars, and essentially everything we know about the formation of planets, comes from observations of our solar neighborhood within 2 kpc of the Sun. Before 2018, accurate distance measurements needed to turn the 2D Sky into a faithful 3D physical picture of the distribution of stars, and the interstellar matter tha

Afonso S. Bandeira, Dmitriy Kunisky, Dustin G. Mixon, Xinmeng Zeng

Given a finite group, we study the Gaussian series of the matrices in the image of its left regular representation. We propose such random matrices as a benchmark for improvements to the noncommutative Khintchine inequality, and we highlight an application to the matrix Spencer conjecture.

Antonio Pasqua, Saeed Noori Gashti

The primary purpose of this study is to investigate the constant-roll inflationary scenario with anisotropic conditions concerning the Einstein-aether Scalar-tensor cosmology in noncommutative phase space. We first introduce an Einstein-aether scalar-tensor cosmological model. In this structure, one can introduce an aether field with aether coefficients in t

Yvan Martel, Ivan Naumkin

For the critical one-dimensional nonlinear Schr\"odinger equation, we construct blow-up solutions that concentrate a soliton at the origin at the conformal blow-up rate, with a non-flat blow-up profile. More precisely, we obtain a blow-up profile that equals $|x|+i\kappa x^2$ near the origin, where $\kappa$ is a universal real constant. Such profile differs

Valentina Peirano, Mariano Méndez, Federico García, Tomaso Belloni

Characterising the fast variability in black-hole low-mass X-ray binaries (BHXBs) can help us understand the geometrical and physical nature of the innermost regions of these sources. Particularly, type-B quasi-periodic oscillations (QPOs), observed in BHXBs during the soft-intermediate state (SIMS) of an outburst, are believed to be connected to the ejectio

Christeen T. Jose

Auxiliary Learning is a machine learning approach in which the model acknowledges the existence of objects that do not come under any of its learned categories.The name Auxiliary learning was chosen due to the introduction of an auxiliary class. The paper focuses on increasing the generality of existing narrow purpose neural networks and also highlights the

Sascha Kurz

We consider the problem of error correction in a network where the errors can occur only on a proper subset of the network edges. For a generalization of the so-called Diamond Network we consider lower and upper bounds for the network's (1-shot) capacity for fixed alphabet sizes.

Qi Yang, Xin Yu, Ho Hin Lee, Leon Y. Cai

Objective: Thigh muscle group segmentation is important for assessment of muscle anatomy, metabolic disease and aging. Many efforts have been put into quantifying muscle tissues with magnetic resonance (MR) imaging including manual annotation of individual muscles. However, leveraging publicly available annotations in MR images to achieve muscle group segmen

Zhonglin Sun, Georgios Tzimiropoulos

Holistic methods using CNNs and margin-based losses have dominated research on face recognition. In this work, we depart from this setting in two ways: (a) we employ the Vision Transformer as an architecture for training a very strong baseline for face recognition, simply called fViT, which already surpasses most state-of-the-art face recognition methods. (b

Sebastian Bruggisser, Benedict von Harling, Oleksii Matsedonskyi, Geraldine Servant

The dilaton is predicted in various extensions of the standard model containing sectors with an approximate spontaneously-broken conformal invariance. As a Goldstone boson of a spontaneously broken symmetry, the dilaton can naturally be one of the lightest new physics particles, and therefore may be the first new physics imprint observed in collider experime

Divij Sharma, Thomas E. Collett, Eric V. Linder

Double source lensing provides a dimensionless ratio of distance ratios, a "remote viewing" of cosmology through distances relative to the gravitational lens, beyond the observer. We use this to test the cosmological framework, particularly with respect to spatial curvature and the distance duality relation. We derive a consistency equation for constant spat

Jose Luis Blázquez-Salcedo, Fech Scen Khoo

We calculate the spectrum of quasinormal modes of slowly rotating Kerr-Newman black holes. Using a perturbative double expansion method, second order in rotation and first order in non-radial perturbations, we obtain the system of equations that describe polar-led and axial-led perturbations. We analyse gravitational, electromagnetic and scalar fundamental m

Han Ma

The higher spin Kitaev model prominently features the extensive locally conserved quantities the same as the spin-$1/2$ Kitaev honeycomb model, although it is not exactly solvable. It remains an open question regarding the physical meaning of these conserved quantities in the higher spin model. In this Letter, by introducing a Majorana parton construction fo

Basabendu Barman, Debasish Borah, Suruj Jyoti Das, Rishav Roshan

We propose a new way of probing non-thermal origin of baryon asymmetry of universe (BAU) and dark matter (DM) from evaporating primordial black holes (PBH) via stochastic gravitational waves (GW) emitted due to PBH density fluctuations. We adopt a baryogenesis setup where CP violating out-of-equilibrium decays of a coloured scalar, produced non-thermally at

Aritra Ghosh, C. Megan Urry, Aayush Mishra, Laurence Perreault-Levasseur

We use the Galaxy Morphology Posterior Estimation Network (GaMPEN) to estimate morphological parameters and associated uncertainties for $\sim 8$ million galaxies in the Hyper Suprime-Cam (HSC) Wide survey with $z \leq 0.75$ and $m \leq 23$. GaMPEN is a machine learning framework that estimates Bayesian posteriors for a galaxy's bulge-to-total light ratio ($

Stefano Antonini, Petar Simidzija, Brian Swingle, Mark Van Raamsdonk

A large class of $\Lambda < 0$ cosmologies have big-bang / big crunch spacetimes with time-symmetric backgrounds and asymptotically AdS Euclidean continuations suggesting a possible holographic realization. We argue that these models generically have time-dependent scalar fields, and these can lead to realistic cosmologies at the level of the homogeneous bac

Minjia Shi, Yuhong Xia, Denis S. Krotov

If $S$ is a transitive metric space, then $|C|\cdot|A| \le |S|$ for any distance-$d$ code $C$ and a set $A$, ``anticode'', of diameter less than $d$. For every Steiner S$(t,k,n)$ system $S$, we show the existence of a $q$-ary constant-weight code $C$ of length~$n$, weight~$k$ (or $n-k$), and distance $d=2k-t+1$ (respectively, $d=n-t+1$) and an anticode $A$ o

Francisco Nogueras-Lara

The nuclear stellar disc (NSD) is a dense stellar structure at the centre of our Galaxy. Given its proximity, it constitutes a unique laboratory to understand other galactic nuclei. Nevertheless, the high crowding and extinction hamper its study, and even its morphology and kinematics are not yet totally clear. In this work we use NSD red clump stars, whose

Ranit Das, Gregor Kasieczka, David Shih

Choosing which properties of the data to use as input to multivariate decision algorithms -- a.k.a. feature selection -- is an important step in solving any problem with machine learning. While there is a clear trend towards training sophisticated deep networks on large numbers of relatively unprocessed inputs (so-called automated feature engineering), for m

Matteo Agostini, Frank F. Deppisch, Graham Van Goffrier

A large experimental program is being mounted to search for neutrinoless double-beta decay over the next decade. Multiple experiments using different target isotopes are being prepared to explore the whole parameter space allowed for inverted-ordered light neutrinos, and have the potential to make discoveries in several other scenarios, including normal-orde

Ronan Legin, Yashar Hezaveh, Laurence Perreault-Levasseur, Benjamin Wandelt

We report the application of implicit likelihood inference to the prediction of the macro-parameters of strong lensing systems with neural networks. This allows us to perform deep learning analysis of lensing systems within a well-defined Bayesian statistical framework to explicitly impose desired priors on lensing variables, to obtain accurate posteriors, a

Johanna Erdmenger, Marius Gerbershagen, Michal P. Heller, Anna-Lena Weigel

An important conjecture within the AdS/CFT correspondence relates holographic spacetime to the quantum computational complexity of the dual quantum field theory. However, the quantitative understanding of this relation is still an open question. In this work, we introduce and study a map between a computational complexity measure and its holographic counterp

Markus S. Kesselring, Julio C. Magdalena de la Fuente, Felix Thomsen, Jens Eisert

The manipulation of topologically-ordered phases of matter to encode and process quantum information forms the cornerstone of many approaches to fault-tolerant quantum computing. Here we demonstrate that fault-tolerant logical operations in these approaches can be interpreted as instances of anyon condensation. We present a constructive theory for anyon cond

Wen Wei Ho, Takashi Mori, Dmitry A. Abanin, Emanuele G. Dalla Torre

Time-periodic (Floquet) driving is a powerful way to control the dynamics of complex systems, which can be used to induce a plethora of new physical phenomena. However, when applied to many-body systems, Floquet driving can also cause heating, and lead to a featureless infinite-temperature state, hindering most useful applications. It is therefore important

Jose A. Benavides, Andrea Biviano, Mario G. Abadi

The study of cluster substructures is important for the determination of the cluster dynamical status, assembly history, and the evolution of cluster galaxies, and it allows to set of constraints on the nature of dark matter and cosmological parameters. We present and test DS+, a new method for the identification and characterization of group-sized substruct

Jacob McNamara, Matthew Reece

Parity and CP symmetries are broken in the world around us. Nonetheless, parity (or CP) may be a gauge symmetry which is higgsed in our universe. This is assumed in many scenarios for physics beyond the Standard Model, including the classic Nelson--Barr proposal for the Strong CP problem. Gauged parity can only arise in quantum gravity, where it corresponds

L. Barchiesi, M. Dessauges-Zavadsky, C. Vignali, F. Pozzi

GDS J033218.92-275302.7 (here GS-14) is a $z\sim5.5$ galaxy detected in [CII] as part of the ALPINE survey with unusual UV spectral features that have been interpreted as signatures of either a double stellar population or of an active galactic nucleus (AGN). We exploited the multi-wavelength coverage of GS-14 to investigate the properties and the origin of

Konstantinos Sfetsos, Konstantinos Siampos

We initiate the construction of integrable $\lambda$-deformed WZW models based on non-semisimple groups. We focus on the four-dimensional case whose underlying symmetries are based on the non-semisimple group $E_2^c$. The corresponding gravitational backgrounds of Lorentzian signature are plane waves which can be obtained as Penrose limits of the $\lambda$-d

Asimina Arvanitaki, Savas Dimopoulos

We argue that the reflection of relic neutrinos from the surface of the Earth results in a significant local $\nu-\bar{\nu}$ asymmetry, far exceeding the expected primordial lepton asymmetry. The net fractional electron neutrino number $\frac{n_{\nu_e}-n_{\bar{\nu}_e}}{n_{\nu_e}}$ is up to $\mathcal{O}(10^5) \sqrt{\frac{m_\nu}{0.1~\text{eV}}}$ larger than th

Patryk Iwanek, Radosław Poleski, Szymon Kozłowski, Igor Soszyński

We study the three-dimensional structure of the Milky Way using 65,981 Mira variable stars discovered by the Optical Gravitational Lensing Experiment (OGLE) survey. The spatial distribution of the Mira stars is analyzed with a model containing three barred components that include the X-shaped boxy component in the Galactic center (GC), and an axisymmetric di

Thayne Currie, G. Mirek Brandt, Timothy D. Brandt, Brianna Lacy

Direct imaging of gas giant exoplanets provides key information on planetary atmospheres and the architectures of planetary systems. However, few planets have been detected in blind surveys used to achieve imaging detections. Using Gaia and Hipparcos astrometry we identified dynamical evidence for a gas giant planet around the nearby star HIP 99770 and then

Diana Forbes, Christian Herwig, Yonatan Kahn, Gordan Krnjaic

We introduce a new search strategy for visibly decaying muonphilic particles using a proton beam spectrometer modeled after the SpinQuest experiment at Fermilab. In this setup, a ${\sim}$100 GeV primary proton beam impinges on a thick fixed target and yields a secondary muon beam. As these muons traverse the target material, they scatter off nuclei and can r

Thomas G. Williams, Jiayi Sun, Ashley T. Barnes, Eva Schinnerer

We combine JWST observations with ALMA CO and VLT-MUSE H$\alpha$ data to examine off-spiral arm star formation in the face-on, grand-design spiral galaxy NGC 628. We focus on the northern spiral arm, around a galactocentric radius of 3-4 kpc, and study two spurs. These form an interesting contrast, as one is CO-rich and one CO-poor, and they have a maximum a

Gabriel Loaiza-Ganem, Brendan Leigh Ross, Luhuan Wu, John P. Cunningham

Likelihood-based deep generative models have recently been shown to exhibit pathological behaviour under the manifold hypothesis as a consequence of using high-dimensional densities to model data with low-dimensional structure. In this paper we propose two methodologies aimed at addressing this problem. Both are based on adding Gaussian noise to the data to

Anton V. Afanasiev, Simona Mei, Hao Fu, Francesco Shankar

(Abridged) We study the galaxy mass-size relation in CARLA spectroscopically confirmed clusters at $1.4<z<2.8$, which span a total stellar mass $11.3<\mathrm{log}(M^c_*/M_{\odot})<12.6$ (halo mass $13.5 \lesssim \mathrm{log}(M^c_h/M_{\odot}) \lesssim 14.5$). Our main finding is that cluster passive ETG at $z \gtrsim 1.5$ with ${\rm log}(M/M_{\odot})>10.5$ ar

Jonah Herzog-Arbeitman, B. Andrei Bernevig, Zhi-Da Song

The topological phases of non-interacting fermions have been classified by their symmetries, culminating in a modern electronic band theory where wavefunction topology can be obtained (in part) from momentum space. Recently, Real Space Invariants (RSIs) have provided a spatially local description of the global momentum space indices. The present work general

James E. Owen, Douglas N. C. Lin

The Galactic Centre is known to have undergone a recent star formation episode a few Myrs ago, which likely produced many T Tauri stars hosting circumstellar discs. It has been suggested that these discs may be the compact and dusty ionized sources identified as ``G-clouds''. Given the Galactic Centre's hostile environment, we study the possible evolutionary

Ryan W. Pfeifle, Shobita Satyapal, Claudio Ricci, Nathan J. Secrest

The discovery over the last several decades of moderate luminosity AGNs in disk-dominated galaxies - which show no "classical" bulges - suggests that secular mechanisms represent an important growth pathway for supermassive black holes in these systems. We present new follow-up NuSTAR observations of the optically-elusive AGNs in two bulgeless galaxies, NGC

Sriyasriti Acharya, Bhargav Vaidya, Indu Kalpa Dihingia, Sushmita Agarwal

Blazars, a class of active galaxies whose jets are relativistic and collimated flows of plasma directed along the line of sight and are prone to a slew of magneto-hydrodynamic (MHD) instabilities. We aim to study the interplay of radiation and particle acceleration processes in regulating the multi-band emission and variability signatures from blazars. In pa

Enrica Bellocchi, Jesús Martín-Pintado, Fernando Rico-Villas, Sergio Martín

We have used ALMA imaging (resolutions 0.1\arcsec-0.4\arcsec) of ground and vibrationally excited lines of HCN and HC$_3$N toward the nucleus of NGC 4945 to trace the protostellar phase in Super Star Clusters (proto-SSC). Out of the 14 identified SSCs, we find that 8 are in the proto-SSC phase showing vibrational HCN emission with 5 of them also showing vibr

Yookoon Park, Chris Dongjoo Kim, Gunhee Kim

Variational autoencoders employ an amortized inference model to approximate the posterior of latent variables. However, such amortized variational inference faces two challenges: (1) the limited posterior expressiveness of fully-factorized Gaussian assumption and (2) the amortization error of the inference model. We present a novel approach that addresses bo

Matthew D. Blair, Xiaoqi Huang, Christopher D. Sogge

We obtain new improved spectral projection estimates on manifolds of non-positive curvature, including sharp ones for relatively large spectral windows for general tori. Our results are stronger than those in an earlier work of the first and third authors [6], and the arguments have been greatly simplified. We more directly make use of pointwise estimates th

Kieran A. Murphy, Dani S. Bassett

Interpretability is a pressing issue for machine learning. Common approaches to interpretable machine learning constrain interactions between features of the input, rendering the effects of those features on a model's output comprehensible but at the expense of model complexity. We approach interpretability from a new angle: constrain the information about t

Michael Fischer, Tobias Ritschel

Current differentiable renderers provide light transport gradients with respect to arbitrary scene parameters. However, the mere existence of these gradients does not guarantee useful update steps in an optimization. Instead, inverse rendering might not converge due to inherent plateaus, i.e., regions of zero gradient, in the objective function. We propose t

Jesse Heyninck, Ofer Arieli, Bart Bogaerts

Approximation fixpoint theory (AFT) is an abstract and general algebraic framework for studying the semantics of nonmonotonic logics. It provides a unifying study of the semantics of different formalisms for nonmonotonic reasoning, such as logic programming, default logic and autoepistemic logic. In this paper, we extend AFT to dealing with non-deterministic

Ekaterina Bogdanova, Dmitry Kubrak, Roman Travkin, Vadim Vologodsky

Let $X$ be a smooth symplectic variety over a field $k$ of characteristic $p>2$ equipped with a restricted structure, which is a class $[\eta] \in H^0(X, \Omega^1_X/d\mathcal O_X)$ whose de Rham differential equals the symplectic form. In this paper we construct a functorial in $(X, [\eta])$ formal quantization of the category $\mathrm{QCoh}(X)$ of quasi-coh

Minjung Son, Jeong Joon Park, Leonidas Guibas, Gordon Wetzstein

Generative models have shown great promise in synthesizing photorealistic 3D objects, but they require large amounts of training data. We introduce SinGRAF, a 3D-aware generative model that is trained with a few input images of a single scene. Once trained, SinGRAF generates different realizations of this 3D scene that preserve the appearance of the input wh

Keaton J. Burns, Daniel Fortunato, Keith Julien, Geoffrey M. Vasil

Polynomial spectral methods produce fast, accurate, and flexible solvers for broad ranges of PDEs with one bounded dimension, where the incorporation of general boundary conditions is well understood. However, automating extensions to domains with multiple bounded dimensions is challenging because of difficulties in imposing boundary conditions at shared edg

Nathan Pflueger, Noah Solomon

We analyze a family of graphs known as banana graphs, with two marked vertices, through the lens of Hurwitz-Brill-Noether theory. As an application, we construct explicit new examples of finite graphs which are Brill-Noether general. These are the first such examples since the analysis of chains of loops by Cools, Draisma, Payne and Robeva. The graphs constr

Xinyan Velocity Yu, Sewon Min, Luke Zettlemoyer, Hannaneh Hajishirzi

Information seeking users often pose questions with false presuppositions, especially when asking about unfamiliar topics. Most existing question answering (QA) datasets, in contrast, assume all questions have well defined answers. We introduce CREPE, a QA dataset containing a natural distribution of presupposition failures from online information-seeking fo

Yael Vinker, Yuval Alaluf, Daniel Cohen-Or, Ariel Shamir

In this paper, we present a method for converting a given scene image into a sketch using different types and multiple levels of abstraction. We distinguish between two types of abstraction. The first considers the fidelity of the sketch, varying its representation from a more precise portrayal of the input to a looser depiction. The second is defined by the

Souvik Dutta, Thomas Faulkner, Simon Lin

We consider the reflected entropy and the associated entanglement spectrum for free fermions reduced to two intervals in 1+1 dimensions. Working directly in the continuum theory the reflected entropy can be extracted from the spectrum of a singular integral equation whose kernel is determined by the known free fermion modular evolved correlation function. We

Andreas Bally, Yi Chung, Florian Goertz

We discuss the role of the top-quark Yukawa coupling $y_t$ concerning the hierarchy problem and construct an alternative scheme to the conventional solutions with top partners. In traditional models, like SUSY or composite Higgs, top partners cancel the top loop contribution to the Higgs quadratic term. The lack of evidence for such colored partners however

Ben Craps, Marine De Clerck, Alejandro Vilar López

Entwinement was first introduced as the CFT dual to extremal, non-minimal geodesics of quotiented AdS$_3$ spaces. It was heuristically meant to capture the entanglement of internal, gauged degrees of freedom, for instance in the symmetric product orbifold CFT of the D1/D5 brane system. The literature now contains different, and sometimes inequivalent, field

Davor Tolj, WenHua Bi, Yong Liu, Ivica Zivkovic

Dark blue single crystals of Al$_{1.75}^{3+}$ Ti$_{1.0}^{4+}$ Ti$_{0.25}^{3+}$O$_5$ were grown with a novel synthesis method based on the reaction of a Ti3+/Ti4+ containing langbeinite melt and Al$_2$O$_3$. The obtained needles crystallize in the pseudobrookite structure and undergo two reversible phase transitions from orthorhombic Cmcm to C2/m first and su

Chris Bühler, Tobias Ilg, Hans Peter Büchler

In one-dimension, quantum fluctuations prevent the appearance of long-range order in a supersolid, and only quasi long-range order can survive. We derive this quantum critical behavior and study its influence on the superfluid response and properties of the solid. The analysis is based on an effective low-energy description accounting for the two coupled Gol

Yikun Cheng, Pan Zhao, Naira Hovakimyan

Safe reinforcement learning (RL) with assured satisfaction of hard state constraints during training has recently received a lot of attention. Safety filters, e.g., based on control barrier functions (CBFs), provide a promising way for safe RL via modifying the unsafe actions of an RL agent on the fly. Existing safety filter-based approaches typically involv

Wenqi Cui, Linbin Huang, Weiwei Yang, Baosen Zhang

A key barrier to using reinforcement learning (RL) in many real-world applications is the requirement of a large number of system interactions to learn a good control policy. Off-policy and Offline RL methods have been proposed to reduce the number of interactions with the physical environment by learning control policies from historical data. However, their

Mary I. Letey, Zakhar Shumaylov, Fruzsina J. Agocs, Will J. Handley

We discuss the challenges of motivating, constructing, and quantizing a canonically normalized inflationary perturbation in spatially curved universes. We show that this has historically proved challenging due to the interaction of nonadiabaticity with spatial curvature. We construct a novel curvature perturbation that is canonically normalized in the sense

Martin Gallauer, Simon Pepin Lehalleur

We construct new six-functor formalisms capturing cohomological invariants of varieties with potentials. Starting from any six-functor formalism $C$, encoded as a coefficient system, we associate a new six-functor formalism $C_{\text{exp}}$. This requires in particular constructing the convolution product symmetric monoidal structure at the $\infty$-categori

Edgar Liberis, Nicholas D. Lane

Embedded and IoT devices, largely powered by microcontroller units (MCUs), could be made more intelligent by leveraging on-device deep learning. One of the main challenges of neural network inference on an MCU is the extremely limited amount of read-write on-chip memory (SRAM, < 512 kB). SRAM is consumed by the neural network layer (operator) input and outpu

José Miguel Zapata

In decision making under uncertainty and risk, worst-case risk assessments are often conducted using maxitive monetary risk measures. In this article, we study maxitive monetary risk measures on the space $L^0$ of all random variables identified modulo almost sure equality. We prove that a monetary risk measure is maxitive and continuous from below if and on

Hong-Ming Chiu, Richard Y. Zhang

Adversarial training is well-known to produce high-quality neural network models that are empirically robust against adversarial perturbations. Nevertheless, once a model has been adversarially trained, one often desires a certification that the model is truly robust against all future attacks. Unfortunately, when faced with adversarially trained models, all

Emily Hadley

Several policy options exist, or have been proposed, to further responsible artificial intelligence (AI) development and deployment. Institutions, including U.S. government agencies, states, professional societies, and private and public sector businesses, are well positioned to implement these policies. However, given limited resources, not all policies can

J. S. R. McCoombs, A. Zelenskiy, M. L. Plumer, B. W. Southern

We perform a symmetry analysis of the ABC-stacked kagome planes of Mn atoms common to the $L1_2$ Mn$_3$X and antiperovskite Mn$_3$AB alloys. In addition to the single-ion-anisotropy and Kitaev-type anisotropic exchange known to stabilize 120{\deg} spin structures in these materials, our analysis results in a staggered Dzyaloshinskii-Moriya interaction and fu

Andrey Nesterov

An asymptotic expansion with respect to a small parameter of a singularly perturbed system of hyperbolic equations, describing vibrations of two rigidly connected strings is constructed. Under certain conditions imposed on these problems, the principal term of the asymptotic expansion of the solution is described by the Korteweg-de Vries equation.

Luan Hoang

This paper is focused on the behavior near the extinction time of solutions of systems of ordinary differential equations with a sublinear dissipation term. Suppose the dissipation term is a product of a linear mapping $A$ and a positively homogeneous scalar function $H$ of a negative degree $-\alpha$. Then any solution with an extinction time $T_*$ behaves

James Nakamura, Shuang Liang, Geoffrey C. Gardner, Michael J. Manfra

The $\nu = 2/3$ fractional quantum Hall state is the hole-conjugate state to the primary Laughlin $\nu = 1/3$ state. We investigate transmission of edge states through quantum point contacts fabricated on a GaAs/AlGaAs heterostructure designed to have a sharp confining potential. When a small but finite bias is applied, we observe an intermediate conductance

Juliane Rosemeier, Terry Haut, Beth Wingate

The present study is an extension of the work done in Parareal convergence for oscillatory pdes with finite time-scale separation (2019), A. G. Peddle, T. Haut, and B. Wingate, [16], and An asymptotic parallel-in-time method for highly oscillatory pdes (2014), T. Haut and B. Wingate, [10], where a two-level Parareal method with averaging is examined. The met

Lorenzo Rimoldini, Berry Holl, Panagiotis Gavras, Marc Audard

Gaia DR3 contains 1.8 billion sources with G-band photometry, 1.5 billion of which with BP and RP photometry, complemented by positions on the sky, parallax, and proper motion. The median number of field-of-view transits in the three photometric bands is between 40 and 44 measurements per source and covers 34 months of data collection. We pursue a classifica

Alexey Yu. Miller

The present paper refers to the knot theory and is devoted to the study of global properties of Gordian graphs of various local moves. In 2005, Gambaudo and Ghys raised the question of the behavior at infinity of the crossing change Gordian graph. They proposed studying its "ends", that is, unbounded connected components of complements of bounded subsets. We

Ke Zhou, Jiaqi Li, Jiarong Hong, Samuel J. Grauer

Particle tracking velocimetry (PTV) is widely used to measure time-resolved, three-dimensional velocity and pressure fields in fluid dynamics research. Inaccurate localization and tracking of particles is a key source of error in PTV, especially for single camera defocusing, plenoptic imaging, and digital in-line holography (DIH) sensors. To address this iss

A. T. Bajkova, V. V. Bobylev

This paper provides a new catalog of orbits and their parameters for a practically complete list of currently known galactic globular clusters (GCs), compiled by Vasiliev (2019) based on the most accurate modern measurements of their velocities and positions. The integration of the orbits of 152 globular clusters for 5 Gyr backward was performed using the ne

Yu Yin, Kamran Ghasedi, HsiangTao Wu, Jiaolong Yang

Nerf-based Generative models have shown impressive capacity in generating high-quality images with consistent 3D geometry. Despite successful synthesis of fake identity images randomly sampled from latent space, adopting these models for generating face images of real subjects is still a challenging task due to its so-called inversion issue. In this paper, w

Max Vistrup

We present new techniques for synthesizing programs through sequences of mutations. Among these are (1) a method of local scoring assigning a score to each expression in a program, allowing us to more precisely identify buggy code, (2) suppose-expressions which act as an intermediate step to evolving if-conditionals, and (3) cyclic evolution in which we evol

Gyujin Oh

We formulate an analogue of the archimedean motivic action conjecture of Prasanna--Venkatesh for irregular cohomological automorphic forms on Shimura varieties, which appear on multiple degrees of coherent cohomology of Shimura varieties. Such multiple appearances are due to many infinity types in a single $L$-packet with equal minimal $K$-types. Accordingly

Dylan Auty, Krystian Mikolajczyk

While monocular depth estimation (MDE) is an important problem in computer vision, it is difficult due to the ambiguity that results from the compression of a 3D scene into only 2 dimensions. It is common practice in the field to treat it as simple image-to-image translation, without consideration for the semantics of the scene and the objects within it. In

Alessandro Prosperi

The existence of a (partial) market equilibrium price is proved in a complete, continuous time finite-agent market setting. The economic agents act as price takers in a fully competitive setting and maximize exponential utility from terminal wealth. As the number $N$ of economic agents goes to infinity, the BSDE system of $N$ equations characterizing the equ

Bo Chen, Matthew Hale

The Gaussian mechanism is one differential privacy mechanism commonly used to protect numerical data. However, it may be ill-suited to some applications because it has unbounded support and thus can produce invalid numerical answers to queries, such as negative ages or human heights in the tens of meters. One can project such private values onto valid ranges

Marc Kery, J. Andrew Royle, Tyler Hallman, W. Douglas Robinson

Point counts (PCs) are widely used in biodiversity surveys, but despite numerous advantages, simple PCs suffer from several problems: detectability, and therefore abundance, is unknown; systematic spatiotemporal variation in detectability produces biased inferences, and unknown survey area prevents formal density estimation and scaling-up to the landscape le

Keith G. Mills, Di Niu, Mohammad Salameh, Weichen Qiu

Evaluating neural network performance is critical to deep neural network design but a costly procedure. Neural predictors provide an efficient solution by treating architectures as samples and learning to estimate their performance on a given task. However, existing predictors are task-dependent, predominantly estimating neural network performance on image c

Haoyang Guo, Dmitry Kubrak, Artem Prikhodko

In this follow-up paper we show that smooth Hodge-proper stacks over $\mathcal O_K$ are $\mathbb Q_p$-locally acyclic: namely the natural map between \'etale $\mathbb Q_p$-cohomology of the algebraic and Raynaud generic fibers is an equivalence. This establishes the $\mathbb Q_p$-case of general conjectures made in our previous work. As a corollary, we get t

Keith G. Mills, Fred X. Han, Jialin Zhang, Fabian Chudak

Predicting neural architecture performance is a challenging task and is crucial to neural architecture design and search. Existing approaches either rely on neural performance predictors which are limited to modeling architectures in a predefined design space involving specific sets of operators and connection rules, and cannot generalize to unseen architect

Feng-Li Lin, Bo Ning, Yanbei Chen

Infalling matter may destroy a black hole and expose the naked singularity. Thus, Penrose proposed the weak cosmic censorship conjecture to avoid such a possibility. On the other hand, if the black hole is not destroyed by infalling matter, from the second law of black hole thermodynamics, the black hole entropy should increase due to the information carried

Eduard Tulchinskii, Kristian Kuznetsov, Laida Kushnareva, Daniil Cherniavskii

We apply topological data analysis (TDA) to speech classification problems and to the introspection of a pretrained speech model, HuBERT. To this end, we introduce a number of topological and algebraic features derived from Transformer attention maps and embeddings. We show that a simple linear classifier built on top of such features outperforms a fine-tune

Laura Eslava, Fernando Baltazar-Larios, Bor Reynoso

We propose a method for obtaining maximum likelihood estimates (MLEs) of a Markov-Modulated Jump-Diffusion Model (MMJDM) when the data is a discrete time sample of the diffusion process, the jumps follow a Laplace distribution, and the parameters of the diffusion are controlled by a Markov Jump Process (MJP). The data can be viewed as incomplete observation

Yugo Onishi, Liang Fu

Noncentrosymmetric quantum materials can convert AC input current into DC transverse current through the nonlinear Hall effect at zero magnetic field. We analyze the AC-DC power conversion efficiency of such ``Hall rectifier'' and suggest its application in wireless charging and energy harvesting. Our key observation is that the development of Hall voltage r

Girik Malik, Dakarai Crowder, Ennio Mingolla

Some recent artificial neural networks (ANNs) claim to model aspects of primate neural and human performance data. Their success in object recognition is, however, dependent on exploiting low-level features for solving visual tasks in a way that humans do not. As a result, out-of-distribution or adversarial input is often challenging for ANNs. Humans instead

Danny Weyns, Paris Avegriou, Radu Calinescu, Sara M. Hezavehi

Over the past two decades, researchers and engineers have extensively studied the problem of how to enable a software system to deal with uncertain operating conditions. One prominent solution to this problem is self-adaptation, which equips a software system with a feedback loop that resolves uncertainties during operation and adapts the system to deal with