November 2022 arXiv papers — page 130

Vaclav Skala

Numerical data processing is a key task across different fields of computer technology use. However, even simple summation of values is not precise due to the floating point representation use. This paper presents a practical algorithm for summation of values convenient for medium and large data sets. The proposed algorithm is simple, easy to implement. Its

Mansur Zhussupbekov, Greg W Burgreen, Jeongho Kim, James F Antaki

PediaFlow is a miniature mixed-flow ventricular assist device for neonates and toddlers. PediaFlow has a fully magnetically levitated rotor which improves biocompatibility, but the increased length of the rotor creates a long annular passage where fluid energy is lost. Therefore, a set of helical stator blades was proposed immediately after the impeller stag

Antonio D'Abbruzzo, Vasco Cavina, Vittorio Giovannetti

We introduce a new regularization of the Redfield equation based on a replacement of the Kossakowski matrix with its closest positive semidefinite neighbor. Unlike most of the existing approaches, this procedure is capable of retaining the time dependence of the Kossakowski matrix, leading to a completely positive divisible quantum process. Using the dynamic

Duc-Lam Duong, Tapio Helin, Jose Rodrigo Rojo-Garcia

We study stability properties of the expected utility function in Bayesian optimal experimental design. We provide a framework for this problem in a non-parametric setting and prove a convergence rate of the expected utility with respect to a likelihood perturbation. This rate is uniform over the design space and its sharpness in the general setting is demon

Glenn S. Orton, Arrate Antunano, Leigh N. Fletcher, James A. Sinclair

An essential component of planetary climatology is knowledge of the tropospheric temperature field and its variability. Previous studies of Jupiter hinted at periodic behavior that was non-seasonal, as well as dynamical relationships between tropospheric and stratospheric temperatures. However, these observations were made over time frames shorter than Jupit

Andrey Ignatov, Anastasia Sycheva, Radu Timofte, Yu Tseng

While neural networks-based photo processing solutions can provide a better image quality compared to the traditional ISP systems, their application to mobile devices is still very limited due to their very high computational complexity. In this paper, we present a novel MicroISP model designed specifically for edge devices, taking into account their computa

Di Zhang, Shun Zhou

In this talk, we present the results of the complete one-loop matching of the seesaw model onto its low-energy effective theory by integrating out three right-handed neutrinos at the one-loop level. We find that there are 31 independent dimension-6 (dim-6) operators (barring flavor structures and Hermitian conjugates) in the Warsaw basis, and the standard-mo

Harun Kir

The refined Humbert invariant is a positive definite quadratic form intrinsically attached to a curve $C$ of genus 2. This invariant is an algebraic generalization of the (usual) Humbert invariant. This invariant is useful because many geometric properties of $C$ are reflected in the arithmetic properties of this invariant. The purpose of this paper is to co

Anand Rangarajan, Pan He, Jaemoon Lee, Tania Banerjee

We seek to impose linear, equality constraints in feedforward neural networks. As top layer predictors are usually nonlinear, this is a difficult task if we seek to deploy standard convex optimization methods and strong duality. To overcome this, we introduce a new saddle-point Lagrangian with auxiliary predictor variables on which constraints are imposed. E

Charley Cummings

We show that the finitistic dimension conjecture holds for all finite dimensional algebras if and only if, for all finite dimensional algebras, the finitistic dimension of an algebra being finite implies that the finitistic dimension of its opposite algebra is also finite. We also prove the equivalent statement for injective generation.

Qi Fan, Mattia Segu, Yu-Wing Tai, Fisher Yu

Improving model's generalizability against domain shifts is crucial, especially for safety-critical applications such as autonomous driving. Real-world domain styles can vary substantially due to environment changes and sensor noises, but deep models only know the training domain style. Such domain style gap impedes model generalization on diverse real-world

Richard J. Licata, Piyush M. Mehta

The geospace environment is volatile and highly driven. Space weather has effects on Earth's magnetosphere that cause a dynamic and enigmatic response in the thermosphere, particularly on the evolution of neutral mass density. Many models exist that use space weather drivers to produce a density response, but these models are typically computationally expens

Kelsey Nelson, Pedro Moura, Javad Mohammadi

Electric vehicles (EVs) are becoming more commonplace in Texas, mainly due to their increasing attractiveness to consumers and pushes from the state's governing bodies to incentivize further adoption. Meanwhile, service from Texas's electric grid, ERCOT, has been seeing increases in power demand due to a growing population, increased air conditioning use, an

Michael Fucilla, Andrey V. Grabovsky, Lech Szymanowski, Emilie Li

We compute the next-leading-order cross-sections for diffractive electro- or photoproduction of a pair of hadrons with large $p_T$, out of a nucleus or a nucleon. A hybrid factorization is used, mixing collinear and small-$x$ factorizations, more precisely shockwave formalism. We demonstrate the cancellation of divergences and extract the finite parts of the

Fernando Moreno-Pino, María Martínez-García, Pablo M. Olmos, Antonio Artés-Rodríguez

Psychiatric patients' passive activity monitoring is crucial to detect behavioural shifts in real-time, comprising a tool that helps clinicians supervise patients' evolution over time and enhance the associated treatments' outcomes. Frequently, sleep disturbances and mental health deterioration are closely related, as mental health condition worsening regula

Naomi Andrew, Sam Hughes, Monika Kudlinska

We show that the homology torsion growth of a free-by-cyclic group with polynomially growing monodromy vanishes in every dimension independently of the choice of Farber chain. It follows that the integral torsion $\rho^\mathbb{Z}$ equals the $\ell^2$-torsion $\rho^{(2)}$ verifying a conjecture of L\"uck for these groups.

Alessandro Ferrari, Sébastien Laffitte, Mathieu Parenti, Farid Toubal

International taxation rules are outdated, allowing multinationals to shift profits to tax havens. This paper examines how tax reforms affect profit shifting and cross-country welfare. We propose a model that separates real economic profits from paper profits, introducing 'triangle identities' to estimate bilateral profit-shifting flows. Using macro- and fir

Michelle Kunimoto, Evan Tey, Willie Fong, Katharine Hesse

Light curves feature many kinds of variability, including instrumental systematics, intrinsic stellar variability such as pulsations, and flux changes caused by transiting exoplanets or eclipsing binary stars. Detrending is a key pre-planet-search data processing step that aims to remove variability not due to transits. This data release note describes impro

Michelle Kunimoto, Evan Tey, Willie Fong, Katharine Hesse

We present High-Level Science Products (HLSPs) containing light curves from MIT's Quick-Look Pipeline (QLP) from the second year of TESS' first Extended Mission (Sectors 40 - 55; 2021 July - 2022 September). In total, 12.2 million per-sector light curves for 5.7 million unique stars were extracted from 10-minute cadence Full-Frame Images (FFIs) and are made

Divesh Aggarwal, Rajendra Kumar

Recent work [BGS17,ABGS19] has shown SETH hardness of CVP in the $\ell_p$ norm for any $p$ that is not an even integer. This result was shown by giving a Karp reduction from $k$-SAT on $n$ variables to CVP on a lattice of rank $n$. In this work, we show a barrier towards proving a similar result for CVP in the $\ell_p$ norm where $p$ is an even integer. We s

Andrey Ignatov, Grigory Malivenko, Radu Timofte, Yu Tseng

The increased importance of mobile photography created a need for fast and performant RAW image processing pipelines capable of producing good visual results in spite of the mobile camera sensor limitations. While deep learning-based approaches can efficiently solve this problem, their computational requirements usually remain too large for high-resolution o

ALICE Collaboration

The ALICE experiment was proposed in 1993, to study strongly-interacting matter at extreme energy densities and temperatures. This proposal entailed a comprehensive investigation of nuclear collisions at the LHC. Its physics programme initially focused on the determination of the properties of the quark-gluon plasma (QGP), a deconfined state of quarks and gl

Martín Novoa-Brunet

We discuss the consequences of deviations from the Standard Model observed in $b\to s\mu^+\mu^-$ transitions for flavour-changing neutral-current processes involving down-type quarks and neutrinos. We work within an effective field theory approach respecting the SM gauge symmetry, including right-handed currents, a flavour structure based on approximate U(2)

Pushpa Kalauni, Kimball A Milton

We construct a supersymmetric quantum mechanical model in which the energy eigenvalues of the Hamiltonians are the products of Riemann zeta functions. We show that the trivial and nontrivial zeros of the Riemann zeta function naturally correspond to the vanishing ground state energies in this model. The model provides a natural form of supersymmetry.

Wilson Lough, Douglas B. Weibel, Saverio E. Spagnolie

The twisting and writhing of a cell body and associated mechanical stresses is an underappreciated constraint on microbial self-propulsion. Multi-flagellated bacteria can even buckle and writhe under their own activity as they swim through a viscous fluid. New equilibrium configurations and steady-state dynamics then emerge which depend on the organism's mec

Daniel Jadlovsky, Jiri Krticka, Ernst Paunzen, Vladimir Stefl

Betelgeuse is a pulsating red supergiant whose brightness is semi periodically variable and in February 2020 reached a historical minimum, the Great Dimming. The aims of this study are to characterize Betelgeuse's variability based on available archival data and to study possible causes of light variability. Many spectra, from ultraviolet and optical regions

Aarya Kumar, Siyu Peng, Vincent Tran

In this paper, we investigate generalizations of the Mahler-Popkens complexity of integers. Specifically, we generalize to $k$-th roots of unity, polynomials over the naturals, and the integers mod $m$. In cyclotomic rings, we establish upper and lower bounds for integer complexity, investigate the complexity of roots of unity using cyclotomic polynomials, a

Narasimha Chary Bonala, Stéphanie Cupit-Foutou

The Gromov width of a uniruled projective K\"ahler manifold can be bounded from above by the symplectic area of its minimal curves. We apply this result to toric varieties and thus get in this case upper bounds expressed in toric combinatorial invariants.

Chiaki Kobayashi, Ilya Mandel, Krzysztof Belczynski, Stephane Goriely

Comparing Galactic chemical evolution models to the observed elemental abundances in the Milky Way, we show that neutron star mergers can be a leading r-process site only if at low metallicities such mergers have very short delay times and significant ejecta masses that are facilitated by the masses of the compact objects. Namely, black hole-neutron star mer

Antonio Lei, Luochen Zhao

Let $K$ be an imaginary quadratic field where $p$ splits, $p\geq5$ a prime number and $f$ an eigen-newform of even weight and level $N>3$ that is coprime to $p$. Under the Heegner hypothesis, Kobayashi--Ota showed that one inclusion of the Iwasawa main conjecture of $f$ involving the Bertolini--Darmon--Prasanna $p$-adic $L$-function holds after tensoring by

Daniel Repp, Angela Barreda, Francesco Vitale, Isabelle Staude

Semiconductor nanowire lasers can be subject to modifications of their lasing threshold resulting from a variation of their environment. A promising choice is to use metallic substrates to gain access to low-volume Surface-Plasmon-Polariton (SPP) modes. We introduce a simple, yet quantitatively precise model that can serve to describe mode competition in nan

Liuquan Wang

Let $r\geq 1$ be a positive integer, $A$ a real positive semi-definite symmetric $r\times r$ rational matrix, $B$ a rational vector of length $r$, and $C$ a rational scalar. Nahm's problem is to find all triples $(A,B,C)$ such that the $r$-fold $q$-hypergeometric series $$f_{A,B,C}(q):=\sum_{n=(n_1,\dots,n_r)^\mathrm{T}\in (\mathbb{Z}_{\geq 0})^r} \frac{q^{\

Tipaluck Krityakierne, Thotsaporn Aek Thanatipanonda

In the classical coupon collector's problem, every box of breakfast cereal contains one coupon from a collection of n distinct coupons, each equally likely to appear. The goal is to find the expected number of boxes a player needs to purchase to complete the whole collection. In this work, we extend the classical problem to k players who compete with one ano

Stephan Wong, Jan Olthaus, Thomas K. Bracht, Doris E. Reiter

Identifying phases and analyzing the stability of dynamic states are ubiquitous and important problems which appear in various physical systems. Nonetheless, drawing a phase diagram in high-dimensional and large parameter spaces has remained challenging. Here, we propose a data-driven method to derive the phase diagram of lasing modes in topological insulato

Laurence Francis Lacey

An information entropy statistical methodology was used to evaluate the growth of the UK economy over the period 2000 to 2019, with an emphasis on the impact of labour productivity on gross domestic product (GDP) per capita and the average growth in real wages, during this time period. The growth of the UK economy over the period 2000 to 2019 can be describe

Chao-Qiang Geng, Chia-Wei Liu, Aowen Zhou, Xiao Yu

We study the semileptonic decays of $B_{cc}$ ${\rightarrow}$ $B_c\ell^+\nu_\ell$ with the bag model, where $\ell$ = $(e, \mu)$, $B_{cc}$ = $(\Xi_{cc}^{++}$, $\Xi_{cc}^+$, $\Omega_{cc}^+$), and $ B_c$ are the singly charmed baryons with $J^P= 1/2^+$. We obtain the decay widths of $\Gamma(\Xi_{cc}^{++}{\rightarrow}\Xi_c^+e^+\nu_e, \Xi_c^{\prime+}e^+\nu_e, \Lam

Marco Linton

We introduce two families of two-generator one-relator groups called primitive extension groups and show that a one-relator group is hyperbolic if its primitive extension subgroups are hyperbolic. This reduces the problem of characterising hyperbolic one-relator groups to characterising hyperbolic primitive extension groups. These new groups moreover admit e

Abbavaram Gowtham Reddy, Vineeth N Balasubramanian

Causal effect estimation from observational data is a central problem in causal inference. Methods based on potential outcomes framework solve this problem by exploiting inductive biases and heuristics from causal inference. Each of these methods addresses a specific aspect of causal effect estimation, such as controlling propensity score, enforcing randomiz

Ivan Fernandez, Christina Giannoula, Aditya Manglik, Ricardo Quislant

Time Series Analysis (TSA) is a critical workload to extract valuable information from collections of sequential data, e.g., detecting anomalies in electrocardiograms. Subsequence Dynamic Time Warping (sDTW) is the state-of-the-art algorithm for high-accuracy TSA. We find that the performance and energy efficiency of sDTW on conventional CPU and GPU platform

Loukas Ilias, Dimitris Askounis, John Psarras

Alzheimer's disease (AD) is a progressive neurological disorder, meaning that the symptoms develop gradually throughout the years. It is also the main cause of dementia, which affects memory, thinking skills, and mental abilities. Nowadays, researchers have moved their interest towards AD detection from spontaneous speech, since it constitutes a time-effecti

Lucas Hayne, Abhijit Suresh, Hunar Jain, Rahul Kumar

Linear classifier probes are frequently utilized to better understand how neural networks function. Researchers have approached the problem of determining unit importance in neural networks by probing their learned, internal representations. Linear classifier probes identify highly selective units as the most important for network function. Whether or not a

Steve Bako, Pradeep Sen, Anton Kaplanyan

Physically based rendering of complex scenes can be prohibitively costly with a potentially unbounded and uneven distribution of complexity across the rendered image. The goal of an ideal level of detail (LoD) method is to make rendering costs independent of the 3D scene complexity, while preserving the appearance of the scene. However, current prefiltering

Raphaël Clouâtre, Michael Hartz

Broadly speaking, this paper is concerned with dual spaces of operator algebras. More precisely, we investigate the existence of what we call Lebesgue projections: central projections in the bidual of an operator algebra that detect the weak-$*$ continuous part of the dual space. Associated to any such projection is a Lebesgue decomposition of the dual space

Konstantin Karchev, Noemi Anau Montel, Adam Coogan, Christoph Weniger

Analysis of galaxy--galaxy strong lensing systems is strongly dependent on any prior assumptions made about the appearance of the source. Here we present a method of imposing a data-driven prior / regularisation for source galaxies based on denoising diffusion probabilistic models (DDPMs). We use a pre-trained model for galaxy images, AstroDDPM, and a chain

Saadia Gabriel, Hamid Palangi, Yejin Choi

While a substantial body of prior work has explored adversarial example generation for natural language understanding tasks, these examples are often unrealistic and diverge from the real-world data distributions. In this work, we introduce a two-stage adversarial example generation framework (NaturalAdversaries), for designing adversaries that are effective

Atul Kedia, Marko Ristic, Richard O'Shaughnessy, Anjali B. Yelikar

The electromagnetic emission resulting from neutron star mergers have been shown to encode properties of the ejected material in their light curves. The ejecta properties inferred from the kilonova emission has been in tension with those calculated based on the gravitational wave signal and numerical relativity models. Motivated by this tension, we construct

Dimitrios Iliadis, Marcel Wever, Bernard De Baets, Willem Waegeman

As a result of the ever increasing complexity of configuring and fine-tuning machine learning models, the field of automated machine learning (AutoML) has emerged over the past decade. However, software implementations like Auto-WEKA and Auto-sklearn typically focus on classical machine learning (ML) tasks such as classification and regression. Our work can

Stephanie Soldavini, Donatella Sciuto, Christian Pilato

Optimizing data movements is becoming one of the biggest challenges in heterogeneous computing to cope with data deluge and, consequently, big data applications. When creating specialized accelerators, modern high-level synthesis (HLS) tools are increasingly efficient in optimizing the computational aspects, but data transfers have not been adequately improv

Lorenzo Lorenzetti

Functionalism is the view that being x is to play the role of x. This paper defends a functionalist account of three-dimensional entities in the context of Wave Function Realism (WFR), that can explain in detail how we can recover three-dimensional entities out of the wavefunction. In particular, the essay advocates for a novel version of WFR in terms of a f

Himani Garg, Lei Wang, Martin Andersson, Christer Fureby

Wall-bounded turbulence is relevant for many engineering and natural science applications, yet there are still aspects of its underlying physics that are not fully understood, particularly at high Reynolds numbers. In this study, we investigate fully-developed turbulent pipe flows at moderate-to-high friction velocity Reynolds numbers ($361 \leq Re_{\tau} \l

Behrouz Touri, Bahman Gharesifard

We introduce a class of distributed nonlinear control systems, termed as the flow-tracker dynamics, which capture phenomena where the average state is controlled by the average control input, with no individual agent has direct access to this average. The agents update their estimates of the average through a nonlinear observer. We prove that utilizing a pro

Stijn Cambie, Stephan Wagner

The problem of determining the maximum number of maximal independent sets in certain graph classes dates back to a paper of Miller and Muller and a question of Erd\H{o}s and Moser from the 1960s. The minimum was always considered to be less interesting due to simple examples such as stars. In this paper we show that the problem becomes interesting when restr

M. V. Rakhlin, A. I. Galimov, I. V. Dyakonov, N. N. Skryabin

The characteristics of a single-photon emitter based on a semiconductor quantum dot, such as their indistinguishability and brightness, depend on the stability of the recombination channel, which can switch spontaneously between exciton and trion. We show that dominant recombination through neutral exciton states can be achieved by careful control of the dop

Khang Hoang

We investigate native point defects and rare-earth (co)dopants in SrAl$_2$O$_4$ using hybrid density-functional defect calculations. Europium (Eu) and dysprosium (Dy) are found to be mixed valence and energetically most favorable at the Sr lattice sites. However, unlike Eu where both Eu$^{2+}$ and Eu$^{3+}$ can be realized in synthesis, Dy is stable predomin

Rui-Chun Xiao, Ding-Fu Shao, Wei Gan, Huan-Wen Wang

The relationship between magnetic order and the second harmonic generation (SHG) effect is a fundamental area of study in condensed matter physics with significant practical implications. In order to gain a clearer understanding of this intricate relation, this study presents a comprehensive classification scheme for the SHG effect in magnetically ordered ma

Noam Soker, Ealeal Bear

We argue that the core degenerate (CD) scenario of type Ia supernovae (SNe Ia) can explain the compact helium-rich circumstellar material (CSM) of SN 2020eyj. In the new channel of the CD scenario that we propose there are two major common envelope evolution (CEE) phases. After the white dwarf (WD) companion removes the hydrogen-rich envelope of the asymptot

Aditya Ranganathan, Dabao Guo, Alexander Heyde, Anupam Gupta

We investigate how a shepherd should move to effectively herd a flock towards a target. Using an agent-based (ABM) and a coarse-grained (ODE) model for the flock, we pose and solve for the optimal strategy of a shepherd that must keep the flock cohesive and coerce it towards a target. Three distinct strategies emerge naturally as a function of the scaled her

Gali Sheffi, Erez Petrank

Safe memory reclamation (SMR) schemes for concurrent data structures offer trade-offs between three desirable properties: ease of integration, robustness, and applicability. In this paper we rigorously define SMR and these three properties, and we present the ERA theorem, asserting that any SMR scheme can only provide at most two of the three properties.

Andrew Stamper, Abhinav Singh, James McCouat, Irina Voiculescu

Developmental dysplasia of the hip (DDH) is a condition in infants where the femoral head is incorrectly located in the hip joint. We propose a deep learning algorithm for segmenting key structures within ultrasound images, employing this to calculate Femoral Head Coverage (FHC) and provide a screening diagnosis for DDH. To our knowledge, this is the first s

Kristoffer Andersson, Alessandro Gnoatto, Marco Patacca, Athena Picarelli

The aim of this work is to propose an extension of the deep solver by Han, Jentzen, E (2018) to the case of forward backward stochastic differential equations (FBSDEs) with jumps. As in the aforementioned solver, starting from a discretized version of the FBSDE and parametrizing the (high dimensional) control processes by means of a family of artificial neur

Sonali Patnaik, Rajeev Singh

At the back of succeeding measurements of anomalies in semileptonic decays at LHCb and several collider experiments hinting at the possible violation of lepton flavor universality, we undertake a concise review of theoretical foundations of the tree- and loop-level $b$-hadron decays, $b \to c l \nu_l$ and $b \to s l^+ l^-$ along with experimental environment

Adrian Tormos, Dario Garcia-Gasulla, Victor Gimenez-Abalos, Sergio Alvarez-Napagao

In deep learning, transfer learning (TL) has become the de facto approach when dealing with image related tasks. Visual features learnt for one task have been shown to be reusable for other tasks, improving performance significantly. By reusing deep representations, TL enables the use of deep models in domains with limited data availability, limited computat

Shucong Zhang, Malcolm Chadwick, Alberto Gil C. P. Ramos, Sourav Bhattacharya

Personalised speech enhancement (PSE), which extracts only the speech of a target user and removes everything else from a recorded audio clip, can potentially improve users' experiences of audio AI modules deployed in the wild. To support a large variety of downstream audio tasks, such as real-time ASR and audio-call enhancement, a PSE solution should operat

Niamh O'Neill, Christoph Schran, Stephen J. Cox, Angelos Michaelides

Life on Earth depends upon the dissolution of ionic salts in water, particularly NaCl. However, an atomistic scale understanding of the process remains elusive. Simulations lend themselves conveniently to studying dissolution since they provide the spatio-temporal resolution that can be difficult to obtain experimentally. Nevertheless, the complexity of vari

Gaspar Galaz, David T. Frayer, Matias Blaña, J. Christopher Howk

We report on results from GBT/ARGUS $^{12}$CO(1-0) observations for the giant low surface brightness galaxy Malin 1, which allow us to determine an upper limit for its CO mass, and hence its molecular gas mass and molecular gas mass surface density $\Sigma_{H_2}$. Although we performed very deep observations through 17 hours on source integration time, reach

P. Barmby

Nearby galaxies provide populations of stellar and non-stellar sources at a common distance and in quantifiable environments. All are observed through the Milky Way foreground, with varying degrees of contamination that depend on observed Galactic latitude and the distance and size of the target galaxy. This work uses Gaia Data Release 3 (DR3) to identify fo

Markus Kängsepp, Meelis Kull

Autonomous driving systems must be capable of making quick decisions based on the perceived environment and specific driving conditions. Perception models in these systems perform well in detecting objects under favourable conditions but their performance deteriorates in poor visibility or with partly occluded objects. To reduce risks from undetected objects

Jincheng Dai, Sixian Wang, Ke Yang, Kailin Tan

The emerging field semantic communication is driving the research of end-to-end data transmission. By utilizing the powerful representation ability of deep learning models, learned data transmission schemes have exhibited superior performance than the established source and channel coding methods. While, so far, research efforts mainly concentrated on archit

Dirk Fahland

Event data is the basis for all process mining analysis. Most process mining techniques assume their input to be an event log. However, event data is rarely recorded in an event log format, but has to be extracted from raw data. Event log extraction itself is an act of modeling as the analyst has to consciously choose which features of the raw data are used

Yanru Chen, Yanan Zheng, Zhilin Yang

Few-shot named entity recognition (NER) targets generalizing to unseen labels and/or domains with few labeled examples. Existing metric learning methods compute token-level similarities between query and support sets, but are not able to fully incorporate label semantics into modeling. To address this issue, we propose a simple method to largely improve metr

Rei Sakuma, Yutaro Iiyama, Lento Nagano, Ryu Sawada

Super-resolution is a machine-learning technique in image processing which generates high-resolution images from low-resolution images. Inspired by this approach, we perform a numerical experiment of quantum machine learning, which takes low-resolution (low plane-wave energy cutoff) one-particle molecular wavefunctions in plane-wave basis as input and genera

D. Pfeiffer, F. Brunbauer, R. Hall-Wilton, M. Lupberger

The European Spallation Source (ESS) in Lund, Sweden will become the world's most powerful thermal neutron source. The Macromolecular Diffractometer (NMX) at the ESS requires three 51.2 x 51.2~cm$^{2}$ detectors with reasonable detection efficiency, sub-mm spatial resolution, a narrow point spread function (PSF) and good time resolution. This work presents m

Jonathan D'Emidio, Roman Orus, Nicolas Laflorencie, Fernando de Juan

The entanglement entropy is a unique probe to reveal universal features of strongly interacting many-body systems. In two or more dimensions these features are subtle, and detecting them numerically requires extreme precision, a notoriously difficult task. This is especially challenging in models of interacting fermions, where many such universal features ha

David Licht, Ryotaku Suzuki, Benson Way

We study black strings/funnels and other black hole configurations in AdS that correspond to different phases of the dual CFT in black hole backgrounds, employing different approaches at large $D$. We assemble the phase diagram of uniform and non-uniform black strings/funnels and study their dynamical stability. We also construct flowing horizons. Many of ou

Tal Peer, Simon Welker, Timo Gerkmann

Diffusion probabilistic models have been recently used in a variety of tasks, including speech enhancement and synthesis. As a generative approach, diffusion models have been shown to be especially suitable for imputation problems, where missing data is generated based on existing data. Phase retrieval is inherently an imputation problem, where phase informa

Hyeongju Choi, Apoorva Beedu, Harish Haresamudram, Irfan Essa

To properly assist humans in their needs, human activity recognition (HAR) systems need the ability to fuse information from multiple modalities. Our hypothesis is that multimodal sensors, visual and non-visual tend to provide complementary information, addressing the limitations of other modalities. In this work, we propose a multi-modal framework that lear

Ferdinand Ihringer, Jacques Verstraëte

A $(k; r, s; n, q)$-set (short: $(r,s)$-set) of $\mathrm{PG}(n, q)$ is a set of points $X$ with $|X| = k$ such that no $s$-space contains more than $r$ points of $X$. We investigate the asymptotic size of $(r, s)$-sets for $n$ fixed and $q \rightarrow \infty$. In particular, we show the existence of $(3, 2)$-sets of size $(1+o(1)) q^{3/2}$ for $n=6$, $(4, 2)

Andrei Variu, Cheng Zhao, Daniel Forero-Sánchez, Chia-Hsun Chuang

Baryonic Acoustic Oscillations (BAOs) studies based on the clustering of voids and matter tracers provide important constraints on cosmological parameters related to the expansion of the Universe. However, modelling the void exclusion effect is an important challenge for fully exploiting the potential of this kind of analyses. We thus develop two numerical m

M. Hellmuth, K. T. Huber, V. Moulton, G. E. Scholz

A split system $\mathcal S$ on a finite set $X$, $|X|\ge3$, is a set of bipartitions or splits of $X$ which contains all splits of the form $\{x,X-\{x\}\}$, $x \in X$. To any such split system $\mathcal S$ we can associate the Buneman graph $\mathcal B(\mathcal S)$ which is essentially a median graph with leaf-set $X$ that displays the splits in $\mathcal S$

Tirthankar Bhattacharyya, Sushil Singla

Marc Rieffel had introduced the notion of the quantum Gromov-Hausdorff distance on compact quantum metric spaces and found a sequence of matrix algebras that converges to the space of continuous functions on $2$-sphere in this distance. One finds applications of similar approximations in many places in the theoretical physics literature. In this paper, we ha

Tian Qian, Jose J. Fernandez-Melgarejo, David Zueco, Javier Molina-Vilaplana

A variational method for studying the ground state of strongly interacting quantum many-body bosonic systems is presented. Our approach constructs a class of extensive variational non-Gaussian wavefunctions which extend Gaussian states by means of nonlinear canonical transformations (NLCT) on the fields of the theory under consideration. We illustrate this m

Leonardo Castellani

We present a short review of the group-geometric approach to supergravity theories, from the point of view of recent developments. The central idea is the unification of usual diffeomorphisms, gauge symmetries and supersymmetries into superdiffeomorphisms in a supergroup manifold. The example of $N=1$ supergravity in $d=4$ is discussed in detail, and used to

Mattia Cielo, Gianpiero Mangano, Ofelia Pisanti

We investigate the impact of stochastic quantum noise due to trans--Planckian effects on the primordial power spectrum for gravity waves during inflation. Given an energy scale Lambda, expected to be close to the Planck scale m_Pl and larger than the Hubble scale H, this noise is described in terms of a source term in the evolution equation for comoving mode

Yuni Lai, Yulin Zhu, Wenqi Fan, Xiaoge Zhang

The robustness of recommender systems under node injection attacks has garnered significant attention. Recently, GraphRfi, a GNN-based recommender system, was proposed and shown to effectively mitigate the impact of injected fake users. However, we demonstrate that GraphRfi remains vulnerable to attacks due to the supervised nature of its fraudster detection

Jan Buzek, Junaid Hasan, Jason Liu, Michael Naehrig

Any pair of consecutive B-smooth integers for a given smoothness bound B corresponds to a solution (x, y) of the equation x^2 - 2Dy^2 = 1 for a certain square-free, B-smooth integer D and a B-smooth integer y. This paper describes algorithms to find such twin B-smooth integers that lie in a given interval by using the structure of solutions of the above Pell

Corentin Salaün, Iliyan Georgiev, Hans-Peter Seidel, Gurprit Singh

We propose a multi-class point optimization formulation based on continuous Wasserstein barycenters. Our formulation is designed to handle hundreds to thousands of optimization objectives and comes with a practical optimization scheme. We demonstrate the effectiveness of our framework on various sampling applications like stippling, object placement, and Mon

Shubham, Avinash Arya, Subarna Roy, Sridhar Jonnala

Industries must follow government rules and regulations around the world to classify products when assessing duties and taxes for international shipment. Harmonized System (HS) is the most standardized numerical method of classifying traded products among industry classification systems. A hierarchical ensemble model comprising of Bert-transformer, NER, dist

Rezaur Rashid, Jawad Chowdhury, Gabriel Terejanu

Causal structure learning from observational data remains a non-trivial task due to various factors such as finite sampling, unobserved confounding factors, and measurement errors. Constraint-based and score-based methods tend to suffer from high computational complexity due to the combinatorial nature of estimating the directed acyclic graph (DAG). Motivate

Ognjen Jovanovic, Francesco Da Ros, Darko Zibar, Metodi P. Yankov

End-to-end learning has become a popular method to optimize a constellation shape of a communication system. When the channel model is differentiable, end-to-end learning can be applied with conventional backpropagation algorithm for optimization of the shape. A variety of optimization algorithms have also been developed for end-to-end learning over a non-di

Cameron Lerch, Dayi Dong, Ian Abraham

In this paper, we address the problem of safe trajectory planning for autonomous search and exploration in constrained, cluttered environments. Guaranteeing safe (collision-free) trajectories is a challenging problem that has garnered significant due to its importance in the successful utilization of robots in search and exploration tasks. This work contribu

Helge Kristian Jenssen, Charis Tsikkou

Guderley's 1942 work on radial shock waves provides cases of self-similar Euler flows exhibiting blowup of primary (undifferentiated) flow variables: a converging shock wave invades a quiescent region, and the velocity and pressure in its immediate wake become unbounded at time of collapse. However, these solutions are of border-line physicality: the pressur

Thierry Desire Pomar, Ricci Erlandsen, Bowen Zhou, Leonid Iliushyn

Extraordinary magnetoresistance (EMR) is a geometric magnetoresistance effect occurring in hybrid devices consisting of a high-mobility material joined by a metal. The change in resistance can exceed 107% at room temperature when a magnetic field of 5 T is applied. Magnetic field sensors based on EMR hold the potential formeasuring weak magnetic fields with

Jihong Wang, Jerry Zhijian Yang, Jiwei Zhang

The stability and convergence analysis of high-order numerical approximations for the one- and two-dimensional nonlocal wave equations on unbounded spatial domains are considered. We first use the quadrature-based finite difference schemes to discretize the spatially nonlocal operator, and apply the explicit difference scheme to approximate the temporal deri

Adam Ball, Ray Secondo, Benjamin T. Diroll, Dhruv Fomra

Strong nonlinear materials have been sought after for decades for applications in telecommunications, sensing, and quantum optics. Gallium-doped zinc oxide is a II-VI transparent conducting oxide that shows promising nonlinearities similar to indium tin oxide and aluminum-doped zinc oxide for the telecommunications band. Here we explore its nonlinearities in

Jophin John, Michael Gerndt

Dynamic resource management opens up numerous opportunities in High Performance Computing. It improves the system-level services as well as application performance. Checkpointing can also be deemed as a system-level service and can reap the benefits offered by dynamism. A checkpointing system can have better resource availability by integrating with a mallea

Tao Liu, Kai Yu

DER is the primary metric to evaluate diarization performance while facing a dilemma: the errors in short utterances or segments tend to be overwhelmed by longer ones. Short segments, e.g., `yes' or `no,' still have semantic information. Besides, DER overlooks errors in less-talked speakers. Although JER balances speaker errors, it still suffers from the sam

Avner Peleg, Toan T. Huynh

We investigate the dynamics of fast two-pulse collisions in linear diffusion-advection systems with weak quadratic loss in spatial dimension 2. We introduce a two-dimensional perturbation method, which generalizes the perturbation method used for studying two-pulse collisions in spatial dimension 1. We then use the generalized perturbation method to show tha

Aishrila Mazumder, Abhirup Datta, Mayuri Sathyanarayana Rao, Arnab Chakraborty

Detection of the redshifted 21-cm signal of neutral hydrogen from the Cosmic Dawn and the Epoch of Reionization is one of the final frontiers of modern observational cosmology. The inherently faint signal makes it susceptible to contamination by several sources like astrophysical foregrounds and instrumental systematics. Nevertheless, developments achieved i

Engel Lefaucheux, Joël Ouaknine, David Purser, Mohammadamin Sharifi

We consider linear dynamical systems under floating-point rounding. In these systems, a matrix is repeatedly applied to a vector, but the numbers are rounded into floating-point representation after each step (i.e., stored as a fixed-precision mantissa and an exponent). The approach more faithfully models realistic implementations of linear loops, compared t

Morten Lüders

We study zero-cycles in families of rationally connected varieties. We show that for a smooth projective scheme over a henselian discrete valuation ring the restriction of relative zero cycles to the special fiber induces an isomorphism on Chow groups if the special fiber is separably rationally connected. We further extend this result to certain higher Chow