March 2023 arXiv papers — page 136

Alankrita Bhatt, Nika Haghtalab, Abhishek Shetty

We initiate the study of smoothed analysis for the sequential probability assignment problem with contexts. We study information-theoretically optimal minmax rates as well as a framework for algorithmic reduction involving the maximum likelihood estimator oracle. Our approach establishes a general-purpose reduction from minimax rates for sequential probabili

Meng Han, Jacqueline Fedyk, Jia-Bao Ji, Victor Despré

We report the experimental observation of quantum interference in the nuclear wave-packet dynamics driving ultrafast excitation-energy transfer in argon dimers below the threshold of interatomic Coulombic decay (ICD). Using time-resolved photoion-photoion coincidence spectroscopy and quantum dynamics simulations, we reveal that the electronic relaxation dyna

Alex Margolis, Sam Shepherd, Emily Stark, Daniel Woodhouse

We introduce the notion of graphical discreteness to group theory. A finitely generated group is graphically discrete if whenever it acts geometrically on a locally finite graph, the automorphism group of the graph is compact-by-discrete. Notable examples include finitely generated nilpotent groups, most lattices in semisimple Lie groups, and irreducible non

Zach Williams, Jushan Chen, Negar Mehr

In this work, we develop a scalable, local trajectory optimization algorithm that enables robots to interact with other robots. It has been shown that agents' interactions can be successfully captured in game-theoretic formulations, where the interaction outcome can be best modeled via the equilibria of the underlying dynamic game. However, it is typically c

Jimin Rhim, Sonya S. Kwak, Angelica Lim, Jason Millar

The role of robots is expanding from tool to collaborator. Socially assistive robots (SARs) are an example of collaborative robots that assist humans in the real world. As robots enter our social sphere, unforeseen risks occur during human-robot interaction (HRI), as everyday human space is full of uncertainties. Risk introduces an element of trust, so under

Fan Zhang, Aria Nosratinia

This paper studies MIMO relays with non-identical link coherence times, a frequently occurring condition when, e.g., the nodes in the relay channel do not all have the same mobility, or the scatterers around some nodes have different mobility compared with those around other nodes. Despite its practical relevance, this condition, known as coherence diversity

Anwesha Mohanty, Alistair Sutherland, Marija Bezbradica, Hossein Javidnia

Similar to the majority of deep learning applications, diagnosing skin diseases using computer vision and deep learning often requires a large volume of data. However, obtaining sufficient data for particular types of facial skin conditions can be difficult due to privacy concerns. As a result, conditions like Rosacea are often understudied in computer-aided

Bilal Porgali, Vítor Albiero, Jordan Ryda, Cristian Canton Ferrer

This paper introduces a new large consent-driven dataset aimed at assisting in the evaluation of algorithmic bias and robustness of computer vision and audio speech models in regards to 11 attributes that are self-provided or labeled by trained annotators. The dataset includes 26,467 videos of 5,567 unique paid participants, with an average of almost 5 video

Rebecca Dorn, Negar Mokhberian, Julie Jiang, Jeremy Abramson

Many openly non-binary gender individuals participate in social networks. However, the relationship between gender and online interactions is not well understood, which may result in disparate treatment by large language models. We investigate individual identity on Twitter, focusing on gender expression as represented by users chosen pronouns. We find that

Luis Apolo, Peng-Xiang Hao, Wen-Xin Lai, Wei Song

The $T\bar T$ deformation is a solvable irrelevant deformation whose properties depend on the sign of the deformation parameter $\mu$. In particular, $T\bar T$-deformed CFTs with $\mu<0$ have been proposed to be holographically dual to Einstein gravity where the metric satisfies Dirichlet boundary conditions at a finite cutoff surface. In this paper, we put

Alexandra Bremers, Maria Teresa Parreira, Xuanyu Fang, Natalie Friedman

For a robot to repair its own error, it must first know it has made a mistake. One way that people detect errors is from the implicit reactions from bystanders -- their confusion, smirks, or giggles clue us in that something unexpected occurred. To enable robots to detect and act on bystander responses to task failures, we developed a novel method to elicit

Marina Kounkel, Keivan G. Stassun, Lynne A. Hillenbrand, Jesús Hernández

We use TESS full-frame imaging data to investigate the angular momentum evolution of young stars in Orion Complex. We confirm recent findings that stars with rotation periods faster than 2 d are overwhelmingly binaries, with typical separations of tens of AU; such binaries quickly clear their disks, leading to a tendency for rapid rotators to be diskless. Am

Jan Nienhaus, Matthias Wink

We prove the existence of three non-round, non-isometric Einstein metrics with positive scalar curvature on the sphere $S^{10}.$ Previously, the only even-dimensional spheres known to admit non-round Einstein metrics were $S^6$ and $S^8.$

David E Speyer

This is a survey article on Richardson varieties and their combinatorics. A Richardson variety is the intersection, inside the flag manifold GL_n/B_+, of a Schubert cell (B_- u B_+)/B_+ and an opposite Schubert cell (B_+ w B_+)/B_+ (or the similar intersection of Schubert varieties). In this survey, we provide an overview of what is known about (1) homogeneo

Jurdana Masuma Iqrah, Younghyun Koo, Wei Wang, Hongjie Xie

Global warming is an urgent issue that is generating catastrophic environmental changes, such as the melting of sea ice and glaciers, particularly in the polar regions. The melting pattern and retreat of polar sea ice cover is an essential indicator of global warming. The Sentinel-2 satellite (S2) captures high-resolution optical imagery over the polar regio

M. Hagimoto, T. J. L. C. Bakx, S. Serjeant, G. J. Bendo

We analyse the molecular and atomic emission lines of 71 bright Herschel-selected galaxies between redshifts 1.4 to 4.6 detected by the Atacama Large Millimetre/submillimetre Array. These lines include a total of 156 CO, [C I], and H2O emission lines. For 46 galaxies, we detect two transitions of CO lines, and for these galaxies we find gas properties simila

Esra Adiyeke, Yuanfang Ren, Ziyuan Guan, Matthew M. Ruppert

Objectives: We aim to quantify longitudinal acute kidney injury (AKI) trajectories and to describe transitions through progressing and recovery states and outcomes among hospitalized patients using multistate models. Methods: In this large, longitudinal cohort study, 138,449 adult patients admitted to a quaternary care hospital between 2012 and 2019 were sta

Nishant Agarwal, Yi-Zen Chu

The in-in formalism and its influence functional generalization are widely used to describe the out-of-equilibrium dynamics of unitary and open quantum systems, respectively. In this paper, we build on these techniques to develop an effective theory of a quantum damped harmonic oscillator and use it to study initial state-dependence, decoherence, and thermal

Leandro Beraldo e Silva, Victor P. Debattista, Stuart R. Anderson, Monica Valluri

Many barred galaxies exhibit upturns (shoulders) in their bar major-axis density profile. Simulation studies have suggested that shoulders are supported by looped $x_1$ orbits, occur in growing bars, and can appear after bar-buckling. We investigate the orbital support and evolution of shoulders via frequency analyses of orbits in simulations. We confirm tha

Avishai Dekel, Kartick S. Sarkar, Yuval Birnboim, Nir Mandelker

JWST observations indicate a surprising excess of luminous galaxies at $z\sim 10$ and above, consistent with efficient conversion of the accreted gas into stars, unlike the suppression of star formation by feedback at later times. We show that the high densities and low metallicities at this epoch {\it guarantee} a high star-formation efficiency (SFE) in the

L. A. Harland-Lang

We present an updated theoretical treatment of ultraperipheral collisions (UPCs) of heavy ions, within the SuperChic Monte Carlo generator. This in particular accounts for mutual ion excitation through additional photon exchanges between the colliding ions. This effect occurs frequently in UPCs, and indeed can be (and has been) measured in data through the u

Calvin Hoffman, Nianyi Chen, Tiziana Di Matteo, Yueying Ni

We use the ASTRID cosmological hydrodynamic simulation to investigate the properties and evolution of triple and quadruple Massive Black Hole (MBH) systems at $z = 2-3$. Only a handful of MBH tuple systems have been detected to date. In ASTRID, we find $4\%$ of the $M_{\rm BH}>10^7\,M_\odot$ are in tuples with $\Delta r_{\rm max} < 200\,{\rm kpc}$. The tuple

Vijay Pal Singh, Luigi Amico, Ludwig Mathey

We investigate the demixing dynamics in a binary two-dimensional (2D) Bose superfluid using classical-field dynamics. By quenching the interspecies interaction parameter, we identify a strong and weak separation regime depending on the system temperature and the quench parameter. In the strong separation regime our results are in agreement with the inertial

Aleksander Lasek, Hugo V. Lepage, Kexin Zhang, Thierry Ferrus

We present a numerically-optimized multipulse framework for the quantum control of a single-electron charge qubit. Our framework defines a set of pulse sequences, necessary for the manipulation of the ideal qubit basis, that avoids errors associated with excitations outside the computational subspace. A novel control scheme manipulates the qubit adiabaticall

Ryohei Kobayashi, Taige Wang, Tomohiro Soejima, Roger S. K. Mong

A (2+1)D topologically ordered phase may or may not have a gappable edge, even if its chiral central charge $c_-$ is vanishing. Recently, it is discovered that a quantity regarded as a "higher" version of chiral central charge gives a further obstruction beyond $c_-$ to gapping out the edge. In this Letter, we show that the higher central charges can be char

Francesco Ubertosi, Myriam Gitti, Fabrizio Brighenti, Valeria Olivares

The investigation of the feedback cycle in galaxy clusters has historically been performed for systems where feedback is ongoing ("mature-feedback" clusters), that is where the central radio galaxy has inflated radio lobes, pushing aside the intracluster medium (ICM). In this pilot study we present results from "pre-feedback" clusters, where the central newl

Katja Fahrion, Guido De Marchi

We measure the extinction law in the 30 Dor star formation region in the Large Magellanic Cloud using Early Release Observations taken with Near-Infrared Camera (NIRCam) onboard the JWST, thereby extending previous studies with the Hubble Space Telescope to the infrared. We use red clump stars to derive the direction of the reddening vector in twelve bands a

Michele Cicoli, Joseph P. Conlon, Anshuman Maharana, Susha Parameswaran

We review applications of string theory to cosmology, from primordial times to the present-day accelerated expansion. Starting with a brief overview of cosmology and string compactifications, we discuss in detail moduli stabilisation, inflation in string theory, the impact of string theory on post-inflationary dynamics (reheating, moduli domination, kination

Herschel A. Chawdhry, Mathieu Pellen

Quantum computers are expected to give major speed-ups for the simulation of quantum systems. In this work, we present quantum gates that simulate the colour part of the interactions of quarks and gluons in perturbative quantum chromodynamics (QCD). As a first application, we implement these circuits on a simulated noiseless quantum computer and use them to

Henrik Schou Røising, Zhao Zhang

We study perfect matchings, or close-packed dimer coverings, of finite sections of the eleven Archimedean lattices and give a constructive proof showing that any two perfect matchings can be transformed into each other using small sets of local ring-exchange moves. This result has direct consequences for formulating quantum dimer models with a resonating val

Philip Schuster, Natalia Toro, Kevin Zhou

Powerful general arguments allow only a few families of long-range interactions, exemplified by gauge field theories of electromagnetism and gravity. However, all of these arguments presuppose that massless fields have zero spin scale (Casimir invariant) and hence exactly boost invariant helicity. This misses the most general behavior compatible with Lorentz

Cyril Creque-Sarbinowski, Stephon Alexander, Marc Kamionkowski, Oliver Philcox

We show that dynamical Chern-Simons (dCS) gravity imprints a parity-violating signal in primordial scalar perturbations. Specifically, we find that, after dCS amplifies one graviton helicity due to a tachyonic instability, the graviton-mediated correlation between two pairs of scalars develops a parity-odd component. This correlation, the primordial scalar t

Asimina Arvanitaki, Savas Dimopoulos

We propose structures of size between $\sim 1$ meter to 100 meters that drastically alter the local distribution of the Cosmic Neutrino Background ($C\nu B$). These structures have a shape reminiscent of a sea urchin: They consist of rods of width $w$ and length $L \gg w$ periodically arranged on the surface of sphere of radius $R\sim L$. Such a structure fu

Ammar Kirmani, Derek S. Wang, Pouyan Ghaemi, Armin Rahmani

Direct experimental detection of anyonic exchange statistics in fractional quantum Hall systems by braiding the excitations and measuring the wave-function phase is an enormous challenge. Here, we use a small, noisy quantum computer to emulate direct braiding within the framework of a simplified model applicable to a thin cylinder geometry and measure the to

Kaiyue Shen, Chen Guo, Manuel Kaufmann, Juan Jose Zarate

We present X-Avatar, a novel avatar model that captures the full expressiveness of digital humans to bring about life-like experiences in telepresence, AR/VR and beyond. Our method models bodies, hands, facial expressions and appearance in a holistic fashion and can be learned from either full 3D scans or RGB-D data. To achieve this, we propose a part-aware

Casey Jameson, Bora Basyildiz, Daniel Moore, Kyle Clark

The speed limit of quantum state transfer (QST) in a system of interacting particles is not only important for quantum information processing, but also directly linked to Lieb-Robinson-type bounds that are crucial for understanding various aspects of quantum many-body physics. For strongly long-range interacting systems such as a fully-connected quantum comp

Germán Kruszewski, Jos Rozen, Marc Dymetman

Pre-trained language models and other generative models have revolutionized NLP and beyond. However, these models tend to reproduce undesirable biases present in their training data. Also, they may overlook patterns that are important but challenging to capture. To address these limitations, researchers have introduced distributional control techniques. Thes

Jiarui Xu, Sifei Liu, Arash Vahdat, Wonmin Byeon

We present ODISE: Open-vocabulary DIffusion-based panoptic SEgmentation, which unifies pre-trained text-image diffusion and discriminative models to perform open-vocabulary panoptic segmentation. Text-to-image diffusion models have the remarkable ability to generate high-quality images with diverse open-vocabulary language descriptions. This demonstrates tha

Adam Samuels, Tereasa G. Brainerd

A recent observational study found that the projected spatial distributions of the satellites of bright, isolated host galaxies tend to be lopsided with respect to the locations of the hosts. Here, we examine the spatial distributions of the satellites of a large number of bright, isolated host galaxies that were obtained from mock redshift surveys of a LCDM

Haiming Yuan, Xian-Hui Ge, Keun-Young Kim, Chang-Woo Ji

We represent the first investigation of pole-skipping on both the gravity and field theory sides. In contrast to the higher dimensional models, there is no momentum degree of freedom in $(1+1)-$dimensional bulk theory. Thus, we then consider a scalar field mass as our degree of freedom for the pole-skipping phenomenon instead of momentum. The pole-skipping f

Eric Bahuaud, Christine Guenther, James Isenberg, Rafe Mazzeo

We prove that the Ricci flow for complete metrics with bounded geometry depends continuously on initial conditions for finite time with no loss of regularity. This relies on our recent work where sectoriality for the generator of the Ricci-DeTurck flow is proved. We use this to prove that for initial metrics sufficiently close in H\"older norm to a rotationa

Chenyi Gu, Z. H. Sun, G. Hagen, T. Papenbrock

We study entanglement entropies between the single-particle states of the hole space and its complement in nuclear systems. Analytical results based on the coupled-cluster method show that entanglement entropies are proportional to the particle number fluctuation and the depletion number of the hole space for sufficiently weak interactions. General arguments

Christopher A. Pattison, Anirudh Krishna, John Preskill

Constant-rate low-density parity-check (LDPC) codes are promising candidates for constructing efficient fault-tolerant quantum memories. However, if physical gates are subject to geometric-locality constraints, it becomes challenging to realize these codes. In this paper, we construct a new family of $[[N,K,D]]$ codes, referred to as hierarchical codes, that

Masahiro Kato, Shuting Wu, Kodai Kureishi, Shota Yasui

We address the issue of binary classification from positive and unlabeled data (PU classification) with a selection bias in the positive data. During the observation process, (i) a sample is exposed to a user, (ii) the user then returns the label for the exposed sample, and (iii) we however can only observe the positive samples. Therefore, the positive label

Shuxiang Cao, Mustafa Bakr, Giulio Campanaro, Simone D. Fasciati

Using quantum systems with more than two levels, or qudits, can scale the computation space of quantum processors more efficiently than using qubits, which may offer an easier physical implementation for larger Hilbert spaces. However, individual qudits may exhibit larger noise, and algorithms designed for qubits require to be recompiled to qudit algorithms

Marcelo Fiore, Zeinab Galal, Hugo Paquet

We introduce a bicategorical model of linear logic which is a novel variation of the bicategory of groupoids, profunctors, and natural transformations. Our model is obtained by endowing groupoids with additional structure, called a kit, to stabilize the profunctors by controlling the freeness of the groupoid action on profunctor elements. The theory of gener

Tin Kuculo

Recent work has utilised knowledge-aware approaches to natural language understanding, question answering, recommendation systems, and other tasks. These approaches rely on well-constructed and large-scale knowledge graphs that can be useful for many downstream applications and empower knowledge-aware models with commonsense reasoning. Such knowledge graphs

H. A. Borges, C. Pigozzo, P. Hepp, L. O. Baraúna

In this work we consider a class of interacting vacuum corresponding to a generalised Chaplygin gas (gCg) cosmology. In particular we analyse two different scenarios at perturbation level for the same background interaction characterised by the parameter $\alpha$: (i) matter that follows geodesics, corresponding to homogeneous vacuum, and (ii) a covariant an

Jesse C. Hoke, Matteo Ippoliti, Eliott Rosenberg, Dmitry Abanin

Measurement has a special role in quantum theory: by collapsing the wavefunction it can enable phenomena such as teleportation and thereby alter the "arrow of time" that constrains unitary evolution. When integrated in many-body dynamics, measurements can lead to emergent patterns of quantum information in space-time that go beyond established paradigms for

Arthur Kosmala, Johannes Gasteiger, Nicholas Gao, Stephan Günnemann

Neural architectures that learn potential energy surfaces from molecular data have undergone fast improvement in recent years. A key driver of this success is the Message Passing Neural Network (MPNN) paradigm. Its favorable scaling with system size partly relies upon a spatial distance limit on messages. While this focus on locality is a useful inductive bi

Richard I. Anderson, Nolan W. Koblischke, Laurent Eyer

The tip of the red giant branch (TRGB) is an important standard candle for determining luminosity distances. Although several $10^5$ small amplitude red giant stars (SARGs) have been discovered, variability was previously considered irrelevant for the TRGB as a standard candle. Here, we show that all stars near the TRGB are SARGs that follow several period-l

K. Beloy

We examine the effect of a parasitic rf magnetic field, attributed to ion trapping, on the highly anticipated nuclear clock based on $^{229}$Th$^{3+}$ [C. J. Campbell et al., Phys. Rev. Lett. 108, 120802 (2012)]. The rf magnetic field induces an ac Zeeman shift to the clock frequency. As we demonstrate, this shift threatens to be the dominant systematic freq

Matteo Antonio Inajetovic, Filippo Orazi, Antonio Macaluso, Stefano Lodi

The postulates of quantum mechanics impose only unitary transformations on quantum states, which is a severe limitation for quantum machine learning algorithms. Quantum Splines (QSplines) have recently been proposed to approximate quantum activation functions to introduce non-linearity in quantum algorithms. However, QSplines make use of the HHL as a subrout

Salvatore Virzì, Enrico Rebufello, Francesco Atzori, Alessio Avella

Bell inequalities are one of the cornerstones of quantum foundations, and fundamental tools for quantum technologies. Recently, the scientific community worldwide has put a lot of effort towards them, which culminated with loophole-free experiments. Nonetheless, none of the experimental tests so far was able to extract information on the full inequality from

Eric M. Rains

We prove (by a case-by-case analysis) a conjecture of Bernstein/Schwarzman to the effect that quotients of abelian varieties by suitable actions of (complex) reflection groups are weighted projective spaces, and show that this remains true after reduction to finite characteristic (including characteristics dividing the order of the group!). We also show that

Polina Petriakova, Arkady A. Popov, Sergey G. Rubin

This paper discusses the origin of the small parameters with the aim of explaining the Hierarchy problem. The flexible extra dimensions are an essential tool in the process by which physical parameters are formed. The evolution of a multidimensional metric starts at the Planck scale and is completed with the static extra-dimensional metric and the 4-dim de S

Bassel Heiba Elfeky, William M. Strickland, Jaewoo Lee, James T. Farmer

Quasiparticle (QP) effects play a significant role in the coherence and fidelity of superconducting quantum circuits. The Andreev bound states of high transparency Josephson junctions can act as low-energy traps for QPs, providing a mechanism for studying the dynamics and properties of both the QPs and the junction. We study the trapping and clearing of QPs

Andrea Ferraguti, Carlo Pagano

Andrews and Petsche proposed in 2020 a conjectural characterization of all pairs $(f,\alpha)$, where $f$ is a polynomial over a number field $K$ and $\alpha\in K$, such that the dynamical Galois group of the pair $(f,\alpha)$ is abelian. In this paper we focus on the case of unicritical polynomials $f$, and more general dynamical systems attached to sequence

Maria Axenovich, António Girão, Lawrence Hollom, Julien Portier

A graph is said to be interval colourable if it admits a proper edge-colouring using palette $\mathbb{N}$ in which the set of colours incident to each vertex is an interval. The interval colouring thickness of a graph $G$ is the minimum $k$ such that $G$ can be edge-decomposed into $k$ interval colourable graphs. We show that $\theta(n)$, the maximum interva

Yanhao Yang, Joseph Norby, Justin K. Yim, Aaron M. Johnson

Legged robots leverage ground contacts and the reaction forces they provide to achieve agile locomotion. However, uncertainty coupled with contact discontinuities can lead to failure, especially in real-world environments with unexpected height variations such as rocky hills or curbs. To enable dynamic traversal of extreme terrain, this work introduces 1) a

Jan Frahm, Polyxeni Spilioti

For any pseudo-Riemannian hyperbolic space $X$ over $\mathbb{R},\mathbb{C},\mathbb{H}$ or $\mathbb{O}$, we show that the resolvent $R(z)=(\Box-z\operatorname{Id})^{-1}$ of the Laplace-Beltrami operator $-\Box$ on $X$ can be extended meromorphically across the spectrum of $\Box$ as a family of operators $C_c^\infty(X)\to \mathcal{D}'(X)$. Its poles are called

Valeriy Bardakov, Tatyana Kozlovskaya, Olga Pochinka

Knots naturally appear in continuous dynamical systems as flow periodic trajectories. However, discrete dynamical systems are also closely connected with the theory of knots and links. For example, for Pixton diffeomorphisms, the equivalence class of the Hopf knot, which is the orbit space of the unstable saddle separatrix in the manifold $\mathbb{S}^2\times

Zhongyi Jiang, Min Zhu, Lu Lu

Geologic carbon sequestration (GCS) is a safety-critical technology that aims to reduce the amount of carbon dioxide in the atmosphere, which also places high demands on reliability. Multiphase flow in porous media is essential to understand CO$_2$ migration and pressure fields in the subsurface associated with GCS. However, numerical simulation for such pro

Hoang Hai Nguyen, Maurice Friedel, Rolf Findeisen

Predictive control, which is based on a model of the system to compute the applied input optimizing the future system behavior, is by now widely used. If the nominal models are not given or are very uncertain, data-driven model predictive control approaches can be employed, where the system model or input is directly obtained from past measured trajectories.

Gabriel Crudele, Peter Dukes, Jonathan A. Noel

A sequence $\pi_1,\pi_2,\dots$ of permutations is said to be "quasirandom" if the induced density of every permutation $\sigma$ in $\pi_n$ converges to $1/|\sigma|!$ as $n\to\infty$. We prove that $\pi_1,\pi_2,\dots$ is quasirandom if and only if the density of each permutation $\sigma$ in the set $$\{123,321,2143,3412,2413,3142\}$$ converges to $1/|\sigma|!

A. Ceretani, F. Falcini, R. Garra

We investigate the existence of exact solutions in closed form to a fractional version of the nonlinear Boussinesq equation for groundwater flow through an unconfined aquifer. We show this fractional equation appears naturally when the classical nonlinear Darcy's law is replaced by a space-fractional one. After a physical discussion on the fractional model,

M. Hörmann, K. P. Schmidt

We construct a projection-based cluster-additive transformation that block-diagonalizes wide classes of lattice Hamiltonians $\mathcal{H}=\mathcal{H}_0 +V$. Its cluster additivity is an essential ingredient to set up perturbative or non-perturbative linked-cluster expansions for degenerate excitation subspaces of $\mathcal{H}_0$. Our transformation generaliz

Shival Dasu, Hongki Jung, Zane Kun Li, José Madrid

We prove the sharp mixed norm $(l^2, L^{q}_{t}L^{r}_{x})$ decoupling estimate for the paraboloid in $d + 1$ dimensions.

Paul Hagemann, Sophie Mildenberger, Lars Ruthotto, Gabriele Steidl

Score-based diffusion models (SBDM) have recently emerged as state-of-the-art approaches for image generation. Existing SBDMs are typically formulated in a finite-dimensional setting, where images are considered as tensors of finite size. This paper develops SBDMs in the infinite-dimensional setting, that is, we model the training data as functions supported

Hiroshi Hirai, Harold Nieuwboer, Michael Walter

Interior-point methods offer a highly versatile framework for convex optimization that is effective in theory and practice. A key notion in their theory is that of a self-concordant barrier. We give a suitable generalization of self-concordance to Riemannian manifolds and show that it gives the same structural results and guarantees as in the Euclidean setti

Sakshi Gupta, Arnab Basak, Dibyendu Nandy

The magnetic activity of a star -- which modulates the stellar wind outflow -- shapes the immediate environments of orbiting planets and induces atmospheric loss thereby impacting their habitability. We perform a detailed parameter space study using three dimensional magnetohydrodynamic simulations to understand the effect of changing stellar wind magnetic f

Ozan Kılıç, Berrenur Saylam, Özlem Durmaz İncel

Sleep is among the most important factors affecting one's daily performance, well-being, and life quality. Nevertheless, it became possible to measure it in daily life in an unobtrusive manner with wearable devices. Rather than camera recordings and extraction of the state from the images, wrist-worn devices can measure directly via accelerometer, heart rate

Upasana Sridhar, Nicholai Tukanov, Elliott Binder, Tze Meng Low

Interest in deploying Deep Neural Network (DNN) inference on edge devices has resulted in an explosion of the number and types of hardware platforms to use. While the high-level programming interface, such as TensorFlow, can be readily ported across different devices, high-performance inference implementations rely on a good mapping of the high-level interfa

Miha Srdinšek, Michele Casula, Rodolphe Vuilleumier

The interplay of quantum and classical fluctuations in the vicinity of a quantum critical point (QCP) gives rise to various regimes or phases with distinct quantum character. In this work, we show that the R\'enyi entropy is a precious tool to characterize the phase diagram of critical systems not only around the QCP but also away from it, thanks to its capa

Yaqiong Li, Emily Biermann, Sigurd Naess, Simone Aiola

We conduct a systematic search for transients in three years of data (2017-2019) from the Atacama Cosmology Telescope (ACT). ACT covers 40 percent of the sky at three bands spanning from 77 GHz to 277 GHz. Analysis of 3-day mean-subtracted sky maps, which were match-filtered for point sources, yielded 29 transients detections. Eight of these transients are d

Florian Jaeckle, Fartash Faghri, Ali Farhadi, Oncel Tuzel

In many retrieval systems the original high dimensional data (e.g., images) is mapped to a lower dimensional feature through a learned embedding model. The task of retrieving the most similar data from a gallery set to a given query data is performed through a similarity comparison on features. When the embedding model is updated, it might produce features t

Chengyi Li, Bo-Qiang Ma

Previous studies on high-energy gamma-ray burst neutrinos from IceCube suggest a neutrino speed variation at the Lorentz violation~(LV) scale of $\sim 6.4\times 10^{17}$~GeV, with opposite velocity variances between neutrinos and antineutrinos. Within a space-time foam model, inspired by string theory, we develop an approach to describe the suggested neutrin

Y. Chen, Y. T. Tang, D. M. Collins, S. J. Clark

The industrialization of Laser Additive Manufacturing (LAM) is challenged by the undesirable microstructures and high residual stresses originating from the fast and complex solidification process. Non-destructive assessment of the mechanical performance controlling deformation patterning is therefore critical. Here, we use Dark Field X-ray Microscopy (DFXM)

Meysam Gheisarnejad, Mohammad-Hassan Khooban

While impressive progress has been already achieved in wide-bandgap (WBG) semicon-ductors such as 4H-SiC and GaN technologies, the lack of intelligent methodologies to control the gate drives prevented to the exploit the maximum potential of semiconductor chips, from obtaining the desired devices operations. Thus, a potent ongoing trend is to design a fast g

Priyanka B R, Biswajit Pandit, Rajeswari M

We consider class of integral sum graphs $H^{-i,s}_{m,j}$ subject to the conditions $-i<0<s$, $1\leq m < i$ and $1\leq j < s$ for all $i,s, m,j\in \mathbb{N}$. We apply edge-sum coloring and edge coloring on $H^{-i,s}_{m,j}$. Since the graphs fully depend on $i$ and $s$, therefore it is not easy to derive the theoretical as well as numerical results for all

Shaoteng Liu, Yuechen Zhang, Wenbo Li, Zhe Lin

This paper presents Video-P2P, a novel framework for real-world video editing with cross-attention control. While attention control has proven effective for image editing with pre-trained image generation models, there are currently no large-scale video generation models publicly available. Video-P2P addresses this limitation by adapting an image generation

Karima Abbas, Abdelaali Boudjemaa

We study the properties of self-bound liquid droplets of three-dimensional Bose mixtures in a weak random potential with Gaussian correlation function at both zero and finite temperatures. Using the Bogoliubov theory, we derive useful formulas for the ground-state energy, the equilibrium density, the depletion, and the anomalous density of the droplet. The q

Cody Hao Yu, Haozheng Fan, Guangtai Huang, Zhen Jia

As deep learning is pervasive in modern applications, many deep learning frameworks are presented for deep learning practitioners to develop and train DNN models rapidly. Meanwhile, as training large deep learning models becomes a trend in recent years, the training throughput and memory footprint are getting crucial. Accordingly, optimizing training workloa

Chung-hong Chan, David Schoch

A complete declarative description of the computational environment is often missing when researchers share their materials. Without such description, software obsolescence and missing system components can jeopardize computational reproducibility in the future, even when data and computer code are available. The R package rang is a complete solution for gen

Mahir Bilen Can

The parameters of the AG codes on general linear groups are found. The hyperplane sections having the minimum (or maximum) number of rational points are determined.

Zhuo Sun, Chris J. Oates, François-Xavier Briol

Control variates can be a powerful tool to reduce the variance of Monte Carlo estimators, but constructing effective control variates can be challenging when the number of samples is small. In this paper, we show that when a large number of related integrals need to be computed, it is possible to leverage the similarity between these integration tasks to imp

Richard Berkovits

In comparing the behavior of an energy spectrum to the predictions of random matrix theory one must transform the spectrum such that the averaged level spacing is constant, a procedure known as unfolding. Once energy spectrums belong to an ensemble where there are large realization-to-realization fluctuations the canonical methods for unfolding fail. Here we

Guilherme Pumi, Gladys Choque Ulloa, Taiane Schaedler Prass

Among the most important models for long-range dependent time series is the class of ARFIMA$(p,d,q)$ (Autoregressive Fractionally Integrated Moving Average) models. Estimating the long-range dependence parameter $d$ in ARFIMA models is a well-studied problem, but the literature regarding the estimation of $d$ in the presence of missing data is very sparse. T

Roberto C. Sundin, David Umsonst

In this paper, we address the lack of datasets for - and the issue of reproducibility in - collaborative SLAM pose graph optimizers by providing a novel pose graph generator. Our pose graph generator, kollagen, is based on a random walk in a planar grid world, similar to the popular M3500 dataset for single agent SLAM. It is simple to use and the user can se

Alice Contat, Nicolas Curien, Perrine Lacroix, Etienne Lasalle

We consider the problem of finding the initial vertex (Adam) in a Barab\'asi--Albert tree process $(\mathcal{T}(n) : n \geq 1)$ at large times. More precisely, given $ \varepsilon>0$, one wants to output a subset $ \mathcal{P}_{ \varepsilon}(n)$ of vertices of $ \mathcal{T}(n)$ so that the initial vertex belongs to $ \mathcal{P}_ \varepsilon(n)$ with probabi

Marco D'Alessandro, Alberto Alonso, Enrique Calabrés, Mikel Galar

Few-Shot Class Incremental Learning (FSCIL) is a challenging continual learning task, where limited training examples are available during several learning sessions. To succeed in this task, it is necessary to avoid over-fitting new classes caused by biased distributions in the few-shot training sets. The general approach to address this issue involves enhan

José T. Gálvez Ghersi, Jonathan Braden

Oscillons are localized field configurations oscillating in time with lifetimes orders of magnitude longer than their oscillation period. In this paper, we simulate non-travelling oscillons produced by deforming the breather solutions of the sine-Gordon model. Such a deformation treats the dimensionality of the model as a real parameter to produce sphericall

Mehran Attar, Walter Lucia

In this paper, we propose a novel approach for computing robust backward reachable sets from noisy data for unknown constrained linear systems subject to bounded disturbances. In particular, we develop an algorithm for obtaining zonotopic inner approximations that can be used for control purposes. It is shown that such sets, if built on an extended space inc

Junbo Zhang, Runpei Dong, Kaisheng Ma

Training a 3D scene understanding model requires complicated human annotations, which are laborious to collect and result in a model only encoding close-set object semantics. In contrast, vision-language pre-training models (e.g., CLIP) have shown remarkable open-world reasoning properties. To this end, we propose directly transferring CLIP's feature space t

Daniele Evangelista, Emilio Olivastri, Davide Allegro, Emanuele Menegatti

Hand-eye calibration is the problem of estimating the spatial transformation between a reference frame, usually the base of a robot arm or its gripper, and the reference frame of one or multiple cameras. Generally, this calibration is solved as a non-linear optimization problem, what instead is rarely done is to exploit the underlying graph structure of the

Lucy L. Gao, Jane J. Ye, Shangzhi Zeng, Julie Zhou

We typically construct optimal designs based on a single objective function. To better capture the breadth of an experiment's goals, we could instead construct a multiple objective optimal design based on multiple objective functions. While algorithms have been developed to find multi-objective optimal designs (e.g. efficiency-constrained and maximin optimal

Dian Wang, Xupeng Zhu, Jung Yeon Park, Mingxi Jia

Although equivariant machine learning has proven effective at many tasks, success depends heavily on the assumption that the ground truth function is symmetric over the entire domain matching the symmetry in an equivariant neural network. A missing piece in the equivariant learning literature is the analysis of equivariant networks when symmetry exists only

Daesoo Lee, Sara Malacarne, Erlend Aune

Time series generation (TSG) studies have mainly focused on the use of Generative Adversarial Networks (GANs) combined with recurrent neural network (RNN) variants. However, the fundamental limitations and challenges of training GANs still remain. In addition, the RNN-family typically has difficulties with temporal consistency between distant timesteps. Moti

Thomas P. Fay, David T. Limmer

In this paper we outline a physically motivated framework for describing spin-selective recombination processes in chiral systems, from which we derive spin-selective reaction operators for recombination reactions of donor-bridge-acceptor molecules, where the electron transfer is mediated by chirality and spin-orbit coupling. In general the recombination pro

Lilei Han, Zhaohua Lin, Qingqing Yin, Ming Tang

Many empirical studies have revealed that the occurrences of contacts associated with human activities are non-Markovian temporal processes with a heavy tailed inter-event time distribution. Besides, there has been increasing empirical evidence that the infection and recovery rates are time-dependent. However, we lack a comprehensive framework to analyze and