June 2022 arXiv papers — page 2

Gary Lazzaro, Jay Foraker, Rob Curry

After the COVID pandemic, student leadership development within the brigade of midshipmen at the United States Naval Academy (USNA) was severely degraded due to reduced student interaction from isolation and remote learning. Brigade leadership decided that reassignment of some students from their previous companies to new companies could facilitate new leade

Maurizio D'Arienzo, Simon Pietro Romano

Energy saving is currently one of the most challenging issues for the Internet research community. Indeed, the exponential growth of applications and services induces a remarkable increase in power consumption and hence calls for novel solutions which are capable to preserve energy of the infrastructures, at the same time maintaining the required Quality of

Minwoo Suh

We construct multi-charged $AdS_3\times{\Sigma}\times\Sigma_{\mathfrak{g}}$ and $AdS_2\times{\Sigma}\times\Sigma_{\mathfrak{g}}$ solutions from M5-branes and D4-branes wrapped on a direct product of spindle, ${\Sigma}$, and Riemann surface, $\Sigma_{\mathfrak{g}}$. Employing uplift formula, we obtain these solutions by uplifting the multi-charged $AdS_3\time

Kohsuke Sumiyoshi, Toru Kojo, Shun Furusawa

Neutron stars and supernovae provide cosmic laboratories of highly compressed matter at supra nuclear saturation density which is beyond the reach of terrestrial experiments. The properties of dense matter is extracted by combining the knowledge of nuclear experiments and astrophysical observations via theoretical frameworks. A matter in neutron stars is neu

Reza Yazdani Aminabadi, Samyam Rajbhandari, Minjia Zhang, Ammar Ahmad Awan

The past several years have witnessed the success of transformer-based models, and their scale and application scenarios continue to grow aggressively. The current landscape of transformer models is increasingly diverse: the model size varies drastically with the largest being of hundred-billion parameters; the model characteristics differ due to the sparsit

Aditya Chowdhury, Nissim Kanekar, Jayaram N. Chengalur

We describe the design, data analysis, and basic results of the Giant Metrewave Radio Telescope Cold-HI AT $z\approx1$ (GMRT-CAT$z$1) survey, a 510-hour upgraded GMRT HI 21 cm emission survey of galaxies at $z=0.74-1.45$ in the DEEP2 survey fields. The GMRT-CAT$z$1 survey is aimed at characterising HI in galaxies during and just after the epoch of peak star-

Viola De Renzis, Davide Gerosa, Geraint Pratten, Patricia Schmidt

Spin precession in merging black-hole binaries is a treasure trove for both astrophysics and fundamental physics. There are now well-established strategies to infer from gravitational-wave data whether at least one of the two black holes is precessing. In this paper we tackle the next-in-line target, namely the statistical assessment that the observed system

Rory Smith, Jong-Ho Shinn, Stephanie Tonnesen, Paula Calderon-Castillo

We present a new approach to observationally constrain where the tails of Jellyfish (JF) galaxies in groups and clusters first appear and how long they remain visible with respect to the moment of their orbital pericenter. This is accomplished by measuring the distribution of their tail directions with respect to their host's center, and their distribution i

Matan Ben Dov, David Shnaiderov, Adi Makmal, Emanuele G. Dalla Torre

A common requirement of quantum simulations and algorithms is the preparation of complex states through sequences of 2-qubit gates. For a generic quantum state, the number of gates grows exponentially with the number of qubits, becoming unfeasible on near-term quantum devices. Here, we aim at creating an approximate encoding of the target state using a limit

Matteo Fael, Fabian Lange, Kay Schönwald, Matthias Steinhauser

We consider Quantum Chromodynamics with external vector, axial-vector, scalar and pseudo-scalar currents and compute three-loop corrections to the corresponding vertex function taking into account massive quarks. We consider all non-singlet contributions as well as those singlet contributions where the external current couples to a massive quark loop. We app

Lingdong Kong, Jiawei Ren, Liang Pan, Ziwei Liu

Densely annotating LiDAR point clouds is costly, which restrains the scalability of fully-supervised learning methods. In this work, we study the underexplored semi-supervised learning (SSL) in LiDAR segmentation. Our core idea is to leverage the strong spatial cues of LiDAR point clouds to better exploit unlabeled data. We propose LaserMix to mix laser beam

Pieter W. Claeys, Marius Henry, Jamie Vicary, Austen Lamacraft

Dual-unitary circuits have emerged as a minimal model for chaotic quantum many-body dynamics in which the dynamics of correlations and entanglement remains tractable. Simultaneously, there has been intense interest in the effect of measurements on the dynamics of quantum information in many-body systems. In this work we introduce a class of models combining

Markus Frembs

We provide a new perspective on the close relationship between entanglement and time. Our main focus is on bipartite entanglement, where this connection is foreshadowed both in the positive partial transpose criterion due to Peres [A. Peres, Phys. Rev. Lett., 77, 1413 (1996)] and in the classification of quantum within more general non-signalling bipartite c

Martin Bauer, Patrick Foldenauer

Extensions of the Standard Model of particle physics with new Abelian gauge groups allow for kinetic mixing between the new gauge bosons and the hypercharge gauge boson, resulting in mixing with the photon. In many models the mixing with the hypercharge gauge boson captures only part of the kinetic mixing term with the photon, since the new gauge bosons can

Joris Witstok, Renske Smit, Roberto Maiolino, Nimisha Kumari

We present new [O III] 88 ${\rm \mu}$m observations of five bright $z \sim 7$ Lyman-break galaxies spectroscopically confirmed by ALMA through the [C II] 158 ${\rm \mu}$m line, unlike recent [O III] detections where Lyman-${\rm \alpha}$ was used. This nearly doubles the sample of Epoch of Reionisation galaxies with robust ($5 \sigma$) detections of [C II] an

Viktoria Kabel, Anne-Catherine de la Hamette, Esteban Castro-Ruiz, Časlav Brukner

Without a complete theory of quantum gravity, the question of how quantum fields and quantum particles behave in a superposition of spacetimes seems beyond the reach of theoretical and experimental investigations. Here we use an extension of the quantum reference frame formalism to address this question for the Klein-Gordon field residing on a superposition

Rui-Xing Zhang, Chao-Xing Liu

A lattice symmetry, if being nonsymmorphic, is defined by combining a point group symmetry with a fractional lattice translation that cannot be removed by changing the lattice origin. Nonsymmorphic symmetry has a substantial influence on both the connectivity and topological properties of electronic band structures in solid-state quantum materials. In this a

Jonathan W. Webb, Ittoop V. Puthoor, Joseph Ho, Jonathan Crickmore

A core principle of quantum theory is that non-orthogonal quantum states cannot be perfectly distinguished with single-shot measurements. However, it is possible to exclude a subset of non-orthogonal states without error in certain circumstances. Here we implement a quantum state elimination measurement which unambiguously rules out two of four pure, non-ort

Òscar L. Crosas, Gino Isidori, Javier M. Lizana, Nudzeim Selimovic

We analyze $K\to \pi \nu\bar \nu$ rates in a model with a TeV-scale leptoquark addressing $B$-meson anomalies, based on the flavor non-universal 4321 gauge group featuring third-generation quark-lepton unification. We show that, together with the tight bounds imposed by $\Delta F = 2$ amplitudes, the present measurement of $\mathcal{B}(K^+ \to \pi^+ \nu \bar

Bruno Tomasello, Dan Mannix, Stephan Geprägs, Timothy Ziman

Rare-earth iron garnets $R_{3}$Fe$_{5}$O$_{12}$ are fascinating insulators with very diverse magnetic phases. Their strong potential in spintronic devices has encouraged a renewal of interest in the study of their low temperature spin structures and spin wave dynamics. A striking feature of rare-earth garnets with $R$-ions exhibiting strong crystal-field eff

Paolo Molignini, Bastien Lapierre, R. Chitra, Wei Chen

In 2D semiconductors and insulators, the Chern number of the valence band Bloch state is an important quantity that has been linked to various material properties, such as the topological order. We elaborate that the opacity of 2D materials to circularly polarized light over a wide range of frequencies, measured in units of the fine structure constant, can b

Dhvani Doshi, Nicolas B. Cowan, Yi Huang

The James Webb Space Telescope (JWST) will provide an opportunity to investigate the atmospheres of potentially habitable planets. Aerosols, significantly mute molecular features in transit spectra because they prevent light from probing the deeper layers of the atmosphere. Earth occasionally has stratospheric/high tropospheric clouds at 15-20 km that could

Claire Marie Guimond, Oliver Shorttle, John F. Rudge

Nominally anhydrous minerals in rocky planet mantles can sequester oceans of water as a whole, giving a constraint on bulk water inventories. Here we predict mantle water capacities from the thermodynamically-limited solubility of water in their constituent minerals. We report the variability of mantle water capacity due to (i) host star refractory element a

Avik Banerjee, Toshali Mitra, Ayan Mukhopadhyay

One of the outstanding problems in the holographic approach to many-body physics is the explicit computation of correlation functions in nonequilibrium states. We provide a new and simple proof that the horizon cap prescription of Crossley-Glorioso-Liu for implementing the thermal Schwinger-Keldysh contour in the bulk is consistent with the Kubo-Martin-Schwi

Tongzhou Wang, Phillip Isola

Our world is full of asymmetries. Gravity and wind can make reaching a place easier than coming back. Social artifacts such as genealogy charts and citation graphs are inherently directed. In reinforcement learning and control, optimal goal-reaching strategies are rarely reversible (symmetrical). Distance functions supported on these asymmetrical structures

Tongzhou Wang, Simon S. Du, Antonio Torralba, Phillip Isola

The ability to separate signal from noise, and reason with clean abstractions, is critical to intelligence. With this ability, humans can efficiently perform real world tasks without considering all possible nuisance factors.How can artificial agents do the same? What kind of information can agents safely discard as noises? In this work, we categorize inform

Marius Dragoi, Elena Burceanu, Emanuela Haller, Andrei Manolache

Analyzing the distribution shift of data is a growing research direction in nowadays Machine Learning (ML), leading to emerging new benchmarks that focus on providing a suitable scenario for studying the generalization properties of ML models. The existing benchmarks are focused on supervised learning, and to the best of our knowledge, there is none for unsu

Andy Zou, Tristan Xiao, Ryan Jia, Joe Kwon

Forecasting future world events is a challenging but valuable task. Forecasts of climate, geopolitical conflict, pandemics and economic indicators help shape policy and decision making. In these domains, the judgment of expert humans contributes to the best forecasts. Given advances in language modeling, can these forecasts be automated? To this end, we intr

Peter Sokalski, Zherui Han, Gabriella Coloyan Fleming, Brandon Smith

Micro-Raman spectroscopy has become an important tool in probing thermophysical behavior in emerging functional materials such as two-dimensional (2D) layered structures. Localized heating by the focused Raman excitation laser beam is expected to produce both stress and nonequilibrium temperature distributions in the material. Here we investigate the effects

Ji Lin, Ligeng Zhu, Wei-Ming Chen, Wei-Chen Wang

On-device training enables the model to adapt to new data collected from the sensors by fine-tuning a pre-trained model. Users can benefit from customized AI models without having to transfer the data to the cloud, protecting the privacy. However, the training memory consumption is prohibitive for IoT devices that have tiny memory resources. We propose an al

Debasish Banerjee, Rajiv Gavai, Saumen Datta, Pushan Majumdar

The energy loss pattern of a low momentum heavy quark in a deconfined quark-gluon plasma can be understood in terms of a Langevin description. In thermal equilibrium, the motion can then be parametrized in terms of a single heavy quark momentum diffusion coefficient kappa, which needs to be determined nonperturbatively. In this work, we study the temperature

Donglai Xiang, Timur Bagautdinov, Tuur Stuyck, Fabian Prada

Despite recent progress in developing animatable full-body avatars, realistic modeling of clothing - one of the core aspects of human self-expression - remains an open challenge. State-of-the-art physical simulation methods can generate realistically behaving clothing geometry at interactive rates. Modeling photorealistic appearance, however, usually require

Siddhant Haldar, Vaibhav Mathur, Denis Yarats, Lerrel Pinto

Imitation learning holds tremendous promise in learning policies efficiently for complex decision making problems. Current state-of-the-art algorithms often use inverse reinforcement learning (IRL), where given a set of expert demonstrations, an agent alternatively infers a reward function and the associated optimal policy. However, such IRL approaches often

S. Basso, B. Salmaso, D. Spiga, M. Ghigo

The Beam Expander Testing X-ray facility (BEaTriX) is a unique X-ray apparatus now operated at the Istituto Nazionale di Astrofisica (INAF), Osservatorio Astronomico di Brera (OAB), in Merate, Italy. It has been specifically designed to measure the point spread function (PSF) and the effective area (EA) of the X-ray mirror modules (MMs) of the Advanced Teles

Changqing Wang, Ivan Gonin, Anna Grassellino, Sergey Kazakov

Frequency conversion between microwave and optical photons is a key enabling technology to create links between superconducting quantum processors and to realize distributed quantum networks. We propose a microwave-optical transduction platform based on long-coherence-time superconducting radio-frequency (SRF) cavities coupled to electro-optic optical caviti

A. Ballester-Bolinches, S. Y. Madanha, M. C. Pedraza-Aguilera, X . Wu

A classical result of Baer states that a finite group $ G $ which is the product of two normal supersoluble subgroups is supersoluble if and only if $ G' $ is nilpotent. In this article we show that if $ G=AB $ is the product of supersoluble (respectively, $ w $-supersoluble) subgroups $ A $ and $ B $, $ A $ is normal in $ G $, $ B $ permutes with every maxi

Zijie J. Wang, Alex Kale, Harsha Nori, Peter Stella

Machine learning (ML) interpretability techniques can reveal undesirable patterns in data that models exploit to make predictions--potentially causing harms once deployed. However, how to take action to address these patterns is not always clear. In a collaboration between ML and human-computer interaction researchers, physicians, and data scientists, we dev

Andi Gu, Lukasz Cincio, Patrick J. Coles

We study the problem of learning the parameters for the Hamiltonian of a quantum many-body system, given limited access to the system. In this work, we build upon recent approaches to Hamiltonian learning via derivative estimation. We propose a protocol that improves the scaling dependence of prior works, particularly with respect to parameters relating to t

Ahmet Inci, Siri Garudanagiri Virupaksha, Aman Jain, Ting-Wu Chin

As the machine learning and systems communities strive to achieve higher energy-efficiency through custom deep neural network (DNN) accelerators, varied precision or quantization levels, and model compression techniques, there is a need for design space exploration frameworks that incorporate quantization-aware processing elements into the accelerator design

Ziyan Yang, Kushal Kafle, Franck Dernoncourt, Vicente Ordonez

We propose a margin-based loss for tuning joint vision-language models so that their gradient-based explanations are consistent with region-level annotations provided by humans for relatively smaller grounding datasets. We refer to this objective as Attention Mask Consistency (AMC) and demonstrate that it produces superior visual grounding results than previ

Cesar Ceballos, Joseph Doolittle

A famous theorem in polytope theory states that the combinatorial type of a simplicial polytope is completely determined by its facet-ridge graph. This celebrated result was proven by Blind and Mani in 1987, via a non-constructive proof using topological tools from homology theory. An elegant constructive proof was given by Kalai shortly after. In their orig

Fan Li, Peng Ding, Fabrizia Mealli

This paper provides a critical review of the Bayesian perspective of causal inference based on the potential outcomes framework. We review the causal estimands, identification assumptions, the general structure of Bayesian inference of causal effects, and sensitivity analysis. We highlight issues that are unique to Bayesian causal inference, including the ro

Axel Brandenburg

The existence of an exponential growth phase during early stages of a pandemic is often taken for granted. However, for the 2019 novel coronavirus epidemic, the early exponential phase lasted only for about six days, while the quadratic growth prevailed for forty days until it spread to other countries and continued, again quadratically, but with a larger co

Anders V. Bjørlig, Dennis V. Christensen, Ricci Erlandsen, Nini Pryds

The two-dimensional electron system found between LaAlO3 and SrTiO3 hosts a variety of physical phenomena that can be tuned through external stimuli. This allows for electronic devices controlling magnetism, spin-orbit coupling, and superconductivity. Controlling the electron density by varying donor concentrations and using electrostatic gating are convenie

Rajat Arora

Traditional approaches based on finite element analyses have been successfully used to predict the macro-scale behavior of heterogeneous materials (composites, multicomponent alloys, and polycrystals) widely used in industrial applications. However, this necessitates the mesh size to be smaller than the characteristic length scale of the microstructural hete

Lijia Jiang, Jun-Hui Zheng

The Bose-Einstein condensate (BEC) of excited states, provides a different platform to explore the interplay between gravity and quantum physics. In this Letter, we study the response of excited-state BECs to an external gravitational field and their dynamics under gravity when space is expanding. We reveal the anomalous response of the center-of-mass of the

Urja Khurana, Ivar Vermeulen, Eric Nalisnick, Marloes van Noorloos

\textbf{Offensive Content Warning}: This paper contains offensive language only for providing examples that clarify this research and do not reflect the authors' opinions. Please be aware that these examples are offensive and may cause you distress. The subjectivity of recognizing \textit{hate speech} makes it a complex task. This is also reflected by differ

Xinyuan Shao, Marta Camps Santasmasas, Xiao Xue, Jiqiang Niu

Forests play an important role in influencing the wind resource in atmospheric boundary layers and the fatigue life of wind turbines. Due to turbulence, a difficulty in the simulation of the forest effects is that flow statistical and fluctuating content should be accurately resolved using a turbulence-resolved CFD method, which requires a large amount of co

Daniel Brito, Ana Pérez-Rodriguez, Ishwor Khatri, Carlos José Tavares

Topological insulators possess a non-conductive bulk and present surface states, henceforth, they are electrically conductive along their boundaries. Bismuth selenide ($Bi_2Se_3$) is one of the most promising topological insulators. However, a major drawback is its n-type nature arising from its natural doping, which makes the transport in the bulk dominant.

Nicholas Dent, Caleb M. Shor

For any positive integer $n$ along with parameters $\alpha$ and $\nu$, we define and investigate $\alpha$-shifted, $\nu$-offset, floor sequences of length $n$. We find exact and asymptotic formulas for the number of integers in such a sequence that are in a particular congruence class. As we will see, these quantities are related to certain problems of count

William R Coulton, Francisco Villaescusa-Navarro, Drew Jamieson, Marco Baldi

We investigate how much can be learnt about four types of primordial non-Gaussianity (PNG) from small-scale measurements of the halo field. Using the QUIJOTE-PNG simulations, we quantify the information content accessible with measurements of the halo power spectrum monopole and quadrupole, the matter power spectrum, the halo-matter cross spectrum and the ha

Dmitri Iouchtchenko, Jérôme F. Gonthier, Alejandro Perdomo-Ortiz, Roger G. Melko

It is believed that one of the first useful applications for a quantum computer will be the preparation of groundstates of molecular Hamiltonians. A crucial task involving state preparation and readout is obtaining physical observables of such states, which are typically estimated using projective measurements on the qubits. At present, measurement data is c

Yilun Du, Shuang Li, Joshua B. Tenenbaum, Igor Mordatch

Deep learning has excelled on complex pattern recognition tasks such as image classification and object recognition. However, it struggles with tasks requiring nontrivial reasoning, such as algorithmic computation. Humans are able to solve such tasks through iterative reasoning -- spending more time thinking about harder tasks. Most existing neural networks,

Harlin Lee, Aaqib Saeed

Sleep is particularly important to the health of infants, children, and adolescents, and sleep scoring is the first step to accurate diagnosis and treatment of potentially life-threatening conditions. But pediatric sleep is severely under-researched compared to adult sleep in the context of machine learning for health, and sleep scoring algorithms developed

Leanne P. Guy, Keith Bechtol, Jeffrey L. Carlin, Erik Dennihy

The Vera C. Rubin Observatory will advance many areas of astronomy over the next decade with its unique wide-fast-deep multi-color imaging survey, the Legacy Survey of Space and Time (LSST). The LSST will produce approximately 20TB of raw data per night, which will be automatically processed by the LSST Science Pipelines to generate science-ready data produc

Mouhamadou Hassane Saley, Abderrahim El Mouhafid, Ahmed Jellal, Ahmed Siari

We investigate the transport properties of charge carriers in AB bilayer graphene through a triple electrostatic barrier. We calculate the transmission and reflection using the continuity conditions at the interfaces of the triple barrier together with the transfer matrix method. First, we consider the case where the energy is less than the interlayer coupli

Haomiao Ni, Yuan Xue, Kelvin Wong, John Volpi

Accurate infarct segmentation in non-contrast CT (NCCT) images is a crucial step toward computer-aided acute ischemic stroke (AIS) assessment. In clinical practice, bilateral symmetric comparison of brain hemispheres is usually used to locate pathological abnormalities. Recent research has explored asymmetries to assist with AIS segmentation. However, most p

Kira Selby, Ahmad Rashid, Ivan Kobyzev, Mehdi Rezagholizadeh

We propose a general deep architecture for learning functions on multiple permutation-invariant sets. We also show how to generalize this architecture to sets of elements of any dimension by dimension equivariance. We demonstrate that our architecture is a universal approximator of these functions, and show superior results to existing methods on a variety o

Tariq Yasin, Harry Desmond, Julien Devriendt, Adrianne Slyz

We set constraints on the dark matter halo mass and concentration of ~22,000 individual galaxies visible both in HI (from the ALFALFA survey) and optical light (from the SDSS). This is achieved by combining two Bayesian models, one for the HI line width as a function of the stellar and neutral hydrogen mass distributions in a galaxy using kinematic modelling

Alexander F. Jercher, Daniele Oriti, Andreas G. A. Pithis

The causal structure is a quintessential element of continuum spacetime physics and needs to be properly encoded in a theory of Lorentzian quantum gravity. Established spin foam (and tensorial group field theory (TGFT)) models mostly work with relatively special classes of Lorentzian triangulations (e.g. built from spacelike tetrahedra only), obscuring the e

Maria Miscouridou, José A. Pineda-Pardo, Charlotte J. Stagg, Bradley E. Treeby

Model-based treatment planning for transcranial ultrasound therapy typically involves mapping the acoustic properties of the skull from an x-ray computed tomography (CT) image of the head. Here, three methods for generating pseudo-CT images from magnetic resonance (MR) images were compared as an alternative to CT. A convolutional neural network (U-Net) was t

Scott T. Alsid, Jennifer M. Schloss, Matthew H. Steinecker, John F. Barry

Quantum sensing of low-frequency magnetic fields using nitrogen-vacancy (NV) center ensembles has been demonstrated in multiple experiments with sensitivities as low as $\sim$1 pT/$\sqrt{\text{Hz}}$. To date, however, demonstrations of high-frequency magnetometry in the GHz regime with NV diamond are orders of magnitude less sensitive, above the nT/$\sqrt{\t

Chun-Wei Chen, Kabish Wisal, Yaniv Eliezer, A. Douglas Stone

High-power fiber laser amplifiers have enabled an increasing range of applications in industry, medicine and defense. The power scaling for narrow-band amplifiers is currently limited by the transverse modal instability. Various techniques have been developed to suppress the instability in a single or few-mode fiber in order to output a clean, collimated bea

Jialu Wang, Xin Eric Wang, Yang Liu

A variety of fairness constraints have been proposed in the literature to mitigate group-level statistical bias. Their impacts have been largely evaluated for different groups of populations corresponding to a set of sensitive attributes, such as race or gender. Nonetheless, the community has not observed sufficient explorations for how imposing fairness con

Yang Fu, Xiaolong Wang

6D object pose estimation is one of the fundamental problems in computer vision and robotics research. While a lot of recent efforts have been made on generalizing pose estimation to novel object instances within the same category, namely category-level 6D pose estimation, it is still restricted in constrained environments given the limited number of annotat

Alan D. Sokal

I present and discuss an extremely simple algorithm for expanding a formal power series as a continued fraction. This algorithm, which goes back to Euler (1746) and Viscovatov (1805), deserves to be better known. I also discuss the connection of this algorithm with the work of Gauss (1812), Stieltjes (1889), Rogers (1907) and Ramanujan, and a combinatorial i

Maitry Ronakbhai Trivedi, Zahra Rezaei Khavas, Paul Robinette

Human-Robot Interaction, in which a robot with some level of autonomy interacts with a human to achieve a specific goal has seen much recent progress. With the introduction of autonomous robots and the possibility of widespread use of those in near future, it is critical that humans understand the robot's intention while interacting with them as this will fo

Arif Ali Khan, Muhammad Azeem Akbar, Mahdi Fahmideh, Peng Liang

Artificial Intelligence (AI) solutions and technologies are being increasingly adopted in smart systems context, however, such technologies are continuously concerned with ethical uncertainties. Various guidelines, principles, and regulatory frameworks are designed to ensure that AI technologies bring ethical well-being. However, the implications of AI ethic

Pinaki Patra

A Charged harmonic oscillator in a magnetic field, Landau problems, and an oscillator in a noncommutative space, share the same mathematical structure in their Hamiltonians. We have considered a two-dimensional anisotropic harmonic oscillator (AHO) with arbitrarily time-dependent parameters (effective mass and frequencies), placed in an arbitrarily time-depe

George Barmpalias, Xiaoyan Zhang

We study effective randomness-preserving transformations of path-incompressible trees. Some path-incompressible trees with infinitely many paths do not compute perfect path-random trees with computable oracle-use. Sparse perfect path-incompressible trees can be effectively densified, almost surely. We characterize the branching density of path-random trees.

Esther Galby, Liana Khazaliya, Fionn Mc Inerney, Roohani Sharma

For a graph $G$, a subset $S \subseteq V(G)$ is called a \emph{resolving set} if for any two vertices $u,v \in V(G)$, there exists a vertex $w \in S$ such that $d(w,u) \neq d(w,v)$. The {\sc Metric Dimension} problem takes as input a graph $G$ and a positive integer $k$, and asks whether there exists a resolving set of size at most $k$. This problem was intr

Dejan Markovic, Alexandre Defossez, Alexander Richard

We present a single-stage casual waveform-to-waveform multichannel model that can separate moving sound sources based on their broad spatial locations in a dynamic acoustic scene. We divide the scene into two spatial regions containing, respectively, the target and the interfering sound sources. The model is trained end-to-end and performs spatial processing

Pasquale Bosso

Phenomenological studies of quantum gravity have proposed a modification of the commutator between position and momentum in quantum mechanics so to introduce a minimal uncertainty in position in quantum mechanics. Such a minimal uncertainty and the consequent minimal measurable length have important consequences on the dynamics of quantum systems. In the pre

Amartya Bose, Peter L. Walters

The recently introduced multisite tensor network path integral (MS-TNPI) method [Bose and Walters, J. Chem. Phys., 2022, 156, 24101.] for simulation of quantum dynamics of extended systems has been shown to be effective in studying one-dimensional systems. Quantum transport in these systems are typically studied at a constant temperature. However, temperatur

Guillaume Gbikpi-Benissan, Frederic Magoules

In this paper, we address the problem of designing a distributed application meant to run both classical and asynchronous iterations. MPI libraries are very popular and widely used in the scientific community, however asynchronous iterative methods raise non-negligible difficulties about the efficient management of communication requests and buffers. Moreove

Paolo Valente, Davide Annucci, Oscar Roberto Blanco Garcia, Marco Garattini

The idea of using fixed-target annihilations of a high-energy positron beam on a target for producing a new, very feebly interacting particle has been exploited by the PADME experiment at LNF using the extracted beam from the LINAC in the BTF facility. Extracting the beam from a synchrotron would improve by several orders of magnitude the duty-cycle of the L

Davide Stirparo, Beatrice Penna, Mohammad Kazemi, Ariona Shashaj

With the increase of digital data and social network platforms the impact of social media science in driving company decision related to product/service features and customer care operations is becoming more crucial. In particular, platform such as Twitter where people can share experience about almost everything can drastically impact the reputation and off

Guillaume Gbikpi-Benissan, Frederic Magoules

In this paper, we address the problem of detecting the moment when an ongoing asynchronous parallel iterative process can be terminated to provide a sufficiently precise solution to a fixed-point problem being solved. Formulating the detection problem as a global solution identification problem, we analyze the snapshot-based approach, which is the only one t

Antigone Lambert-Huyghe, Suzanne C. Madden, Vianney Lebouteiller, Frédéric Galliano

This study explores the link between the [OIII]88mu emission, a well-known tracer of HII regions, and 24mu continuum, often used to trace warm dust in the ionized phases of galaxies. We investigate the local conditions driving the relation between those tracers in the Magellanic Clouds, comparing observations with Cloudy models consisting of an HII region pl

Meixin Cheng, Kostyantyn Pichugin, Andr\e' Maas, Marika Schleberger

Here we report time-resolved broadband transient reflectivity measurements performed in a single crystal of SnS$_2$. We made use of time-domain Brillouin scattering and a broadband probe to measure the out-of-plane longitudinal sound velocity $v_L$ = (2950 $\pm$ 100) m s$^{-1}$, in this semiconducting two-dimensional transition metal dichalcogenide. Our stud

Simon Pietro Romano

UMPIRE provides seamless meeting interaction among remote and local participants. It uses the BFCP, an IETF standard for moderation.BFCP introduces automated floor control functions to a centralized conferencing environment. This article discusses the design and implementation of the UMPIRE system and highlights the most notable solutions we devised to handl

Federica Granese, Marine Picot, Marco Romanelli, Francisco Messina

Detection of adversarial examples has been a hot topic in the last years due to its importance for safely deploying machine learning algorithms in critical applications. However, the detection methods are generally validated by assuming a single implicitly known attack strategy, which does not necessarily account for real-life threats. Indeed, this can lead

Martin Balko, Steven Chaplick, Robert Ganian, Siddharth Gupta

An obstacle representation of a graph $G$ consists of a set of pairwise disjoint simply-connected closed regions and a one-to-one mapping of the vertices of $G$ to points such that two vertices are adjacent in $G$ if and only if the line segment connecting the two corresponding points does not intersect any obstacle. The obstacle number of a graph is the sma

Jeong-Seop Kim

In this short article, we determine the bigness of the tangent bundle $T_X$ of the projective bundle $X=\mathbb{P}_C(E)$ associated to a vector bundle $E$ on a smooth projective curve $C$.

Georges Comte, Immanuel Halupczok

We prove the nonarchimedean counterpart of a real inequality involving the metric entropy and measure geometric invariants $V_i$, called Vitushkin's variations. Our inequality is based on a new convenient partial preorder on the set of constructible motivic functions, extending the one considered by R. Cluckers and F. Loeser in Constructible motivic function

Isanka Garli Hevage, Akif Ibraguimov, Zeev Sobol

We consider the degenerate Einsteins Brownian motion model when the time interval of the moving particles before the collisions, is reciprocal to the number of particles per unit volume u(x,t), at the point of observation x at time t. The parameter 0 < tau < C, which controls the characteristics of the fluid, almost increases unboundedly, as u approaches 0.

Wayne Barrett, Thomas R. Cameron, Emily Evans, H. Tracy Hall

In this article, we extend the notion of the Laplacian spread to simple directed graphs (digraphs) using the restricted numerical range. First, we provide Laplacian spread values for several families of digraphs. Then, we prove sharp upper bounds on the Laplacian spread for all polygonal and balanced digraphs. In particular, we show that the validity of the

Moshe Sipper, Jason H. Moore, Ryan J. Urbanowicz

When seeking a predictive model in biomedical data, one often has more than a single objective in mind, e.g., attaining both high accuracy and low complexity (to promote interpretability). We investigate herein whether multiple objectives can be dynamically tuned by our recently proposed coevolutionary algorithm, SAFE (Solution And Fitness Evolution). We fin

Kai Zhen, Hieu Duy Nguyen, Raviteja Chinta, Nathan Susanj

We present a novel sub-8-bit quantization-aware training (S8BQAT) scheme for 8-bit neural network accelerators. Our method is inspired from Lloyd-Max compression theory with practical adaptations for a feasible computational overhead during training. With the quantization centroids derived from a 32-bit baseline, we augment training loss with a Multi-Regiona

Andrey Malinin, Andreas Athanasopoulos, Muhamed Barakovic, Meritxell Bach Cuadra

Distributional shift, or the mismatch between training and deployment data, is a significant obstacle to the usage of machine learning in high-stakes industrial applications, such as autonomous driving and medicine. This creates a need to be able to assess how robustly ML models generalize as well as the quality of their uncertainty estimates. Standard ML ba

Xuezhi Bian, Yanze Wu, Jonathan Rawlinson, Robert G. Littlejohn

Nuclear Berry curvature effects emerge from electronic spin degeneracy and canlead to non-trivial spin-dependent (nonadiabatic) nuclear dynamics. However, such effects are completely neglected in all current mixed quantum-classical methods such as fewest switches surface-hopping. In this work, we present a phase-space surface-hopping (PSSH) approach to simul

Fernanda Sánchez-Puig, Octavio Zapata, Omar K. Pineda, Gerardo Iñiguez

Criticality has been proposed as a mechanism for the emergence of complexity, life, and computation, as it exhibits a balance between robustness and adaptability. In classic models of complex systems where structure and dynamics are considered homogeneous, criticality is restricted to phase transitions, leading either to robust (ordered) or adaptive (chaotic

Yihui Quek, Eneet Kaur, Mark M. Wilde

There is a folkloric belief that a depth-$\Theta(m)$ quantum circuit is needed to estimate the trace of the product of $m$ density matrices (i.e., a multivariate trace), a subroutine crucial to applications in condensed matter and quantum information science. We prove that this belief is overly conservative by constructing a constant quantum-depth circuit fo

Tuhin Malik, B. K. Agrawal, Constança Providência

An ambitious goal of the astrophysical community is not only to constrain the equation of state (EOS) of neutron star (NS) matter by confronting it with astrophysics observations, but ultimately also to infer the NS composition. Nevertheless, the composition of the NS core is likely to remain uncertain unless we have an accurate determination of the nuclear

Hao Zhang, Parinaz Moazzezi, Juanjuan Ren, Brett Henderson

Perovskite quantum dots (PQDs) provide a robust solution-based approach to efficient solar cells, bright light-emitting devices, and quantum sources of light. Quantifying heterogeneity and understanding coupling between dots is critical for these applications. We use double-nanohole optical trapping to size individual dots and correlate to emission energy sh

Julian Baumstark, Tobias Jahnke

We consider semilinear hyperbolic systems with a trilinear nonlinearity. Both the differential equation and the initial data contain the inverse of a small parameter $\varepsilon$, and typical solutions oscillate with frequency proportional to $1/\varepsilon$ in time and space. Moreover, solutions have to be computed on time intervals of length $1/\varepsilo

Hyeon-Kyeong Shin, Hyewon Han, Doyeon Kim, Soo-Whan Chung

In this paper, we propose a novel end-to-end user-defined keyword spotting method that utilizes linguistically corresponding patterns between speech and text sequences. Unlike previous approaches requiring speech keyword enrollment, our method compares input queries with an enrolled text keyword sequence. To place the audio and text representations within a

Oliver Y. Chén

I discuss here three important roles where machine intelligence, brain and behaviour studies together may facilitate criminal law. First, predictive modelling using brain and behaviour data may support legal investigations by predicting categorical, continuous, and longitudinal legal outcomes of interests related to brain injury and mental illnesses. Second,

Yohan Brunebarbe

The moduli stacks of Calabi-Yau varieties are known to enjoy several hyperbolicity properties. The best results have so far been proven using sophisticated analytic tools such as complex Hodge theory. Although the situation is very different in positive characteristic (e.g. the moduli stack of principally polarized abelian varieties of dimension at least 2 c

Yanqin Jiang, Li Zhang, Zhenwei Miao, Xiatian Zhu

3D object detection in autonomous driving aims to reason "what" and "where" the objects of interest present in a 3D world. Following the conventional wisdom of previous 2D object detection, existing methods often adopt the canonical Cartesian coordinate system with perpendicular axis. However, we conjugate that this does not fit the nature of the ego car's p