August 2022 arXiv papers — page 58

Gilles Parez

We introduce a family of quantum R\'enyi fidelities and discuss their symmetry resolution. We express the symmetry-resolved fidelities as Fourier transforms of charged fidelities, for which we derive exact formulas for Gaussian states. These results also yield a formula for the total fidelities of Gaussian states, which we expect to have applications beyond

Zack Xuereb Conti, Ruchi Choudhary, Luca Magri

State-of-the-art machine-learning-based models are a popular choice for modeling and forecasting energy behavior in buildings because given enough data, they are good at finding spatiotemporal patterns and structures even in scenarios where the complexity prohibits analytical descriptions. However, their architecture typically does not hold physical correspo

Teruyuki Saito, Masayuki Matsuo

We formulate a microscopic theory to calculate cross section of the radiative neutron capture reaction on neutron-rich nuclei using the continuum random-phase approximation (cRPA) to the time-dependent density functional theory (TDDFT). With an intension of applying to the r-process, for which the statistical reaction model may not be appropriate, we describ

Alicia Y. Tsai, Laurent El Ghaoui

We address the problem of unsupervised extractive document summarization, especially for long documents. We model the unsupervised problem as a sparse auto-regression one and approximate the resulting combinatorial problem via a convex, norm-constrained problem. We solve it using a dedicated Frank-Wolfe algorithm. To generate a summary with $k$ sentences, th

Alkida Balliu, Sebastian Brandt, Manuela Fischer, Rustam Latypov

Locally Checkable Labeling (LCL) problems are graph problems in which a solution is correct if it satisfies some given constraints in the local neighborhood of each node. Example problems in this class include maximal matching, maximal independent set, and coloring problems. A successful line of research has been studying the complexities of LCL problems on

Rong-Jun Qin, Fan-Ming Luo, Hong Qian, Yang Yu

This paper addresses policy learning in non-stationary environments and games with continuous actions. Rather than the classical reward maximization mechanism, inspired by the ideas of follow-the-regularized-leader (FTRL) and mirror descent (MD) update, we propose a no-regret style reinforcement learning algorithm PORL for continuous action tasks. We prove t

Fengjiao Ma, Rainer Kaufmann, Jaroslaw Sedzicki, Zoltán Cseresnyés

Correlative light and electron microscopy is a powerful tool to study the internal structure of cells. It combines the mutual benefit of correlating light (LM) and electron (EM) microscopy information. However, the classical approach of overlaying LM onto EM images to assign functional to structural information is hampered by the large discrepancy in structu

Inwon Kim, Antoine Mellet

We study the incompressible limit of the porous medium equation with a reaction term that is non-monotone with respect to the pressure variable. More specifically we consider reaction terms that are either bistable or monostable. We show that this type of reaction term generates many interesting differences in the qualitative behavior of solutions, in contra

Deepak Maurya, Adarsh Barik, Jean Honorio

In this work, we propose a robust framework that employs adversarially robust training to safeguard the ML models against perturbed testing data. Our contributions can be seen from both computational and statistical perspectives. Firstly, from a computational/optimization point of view, we derive the ready-to-use exact solution for several widely used loss f

Vivek Semwal, Jayam Joshi, Shradha Mishra

We studied a collection of chiral active particles (CAP) on a two dimensional substrate using extensive numerical study. Particles interact through soft repulsive interaction. The activity and chirality of particles is tuned by varying their self-propulsion speed and angular velocity respectively. Kinetics and steady state properties of particles are studied

Yury Elkin, Vitaliy Kurlin

This paper is motivated by the k-nearest neighbors search: given an arbitrary metric space, and its finite subsets (a reference set R and a query set Q), design a fast algorithm to find all k-nearest neighbors in R for every point q in Q. In 2006, Beygelzimer, Kakade, and Langford introduced cover trees to justify a near-linear time complexity for the neighb

Han Sun, Zhaoxin Fan, Zhenbo Song, Zhicheng Wang

Monocular 3D object detection is a fundamental but very important task to many applications including autonomous driving, robotic grasping and augmented reality. Existing leading methods tend to estimate the depth of the input image first, and detect the 3D object based on point cloud. This routine suffers from the inherent gap between depth estimation and o

Tristan Buckmaster, Gonzalo Cao-Labora, Javier Gómez-Serrano

Building upon the pioneering work [Merle, Rapha\"el, Rodnianski, and Szeftel, Ann. of Math., 196(2):567-778, 2022, Ann. of Math., 196(2):779-889, 2022, Invent. Math., 227(1):247-413, 2022] we construct exact, smooth self-similar imploding solutions to the 3D isentropic compressible Euler equations for ideal gases for all adiabatic exponents $\gamma>1$. For t

Q. Tyrell Davis

John H. Conway's Game of Life, as well as cellular automata in the larger family of Life-like CA, are discrete: the cells have a binary state space and the birth and survival transition rules are 9-bits apiece. Inspired by Life, several projects have developed continuously-valued cellular automata frameworks in 2 dimensions. These CA systems are necessarily

Samuel Willian Schwertner Costiche, Carlos Henrique Coimbra-Araújo, Rodrigo André Schulz

The sensitive dependence of chaos on parameters is a topic of great interest in the study of integrability and stability of dynamical systems. Previous work has proposed ways to identify the sensitive dependence on parameters by topological criteria or large numerical simulations. In this paper, we show that when the Lyapunov exponents of the system vary wit

Jihwan Oh, Yehao Zhou

Building on our previous work [2109.01110], we will compute a new kind of $G_2$ instanton partition function. By doing so, we complete a set of building blocks of the instanton partition function associated with a large class of $G_2$ manifolds.

Valentina Ciccone, Felipe Gonçalves

We establish a sharp adjoint Fourier restriction inequality for the end-point Tomas-Stein restriction theorem on the circle under a certain arithmetic constraint on the support set of the Fourier coefficients of the given function. Such arithmetic constraint is a generalization of a $B_3$-set.

Zhong Li, Matthijs van Leeuwen

Event logs are widely used for anomaly detection and prediction in complex systems. Existing log-based anomaly detection methods usually consist of four main steps: log collection, log parsing, feature extraction, and anomaly detection, wherein the feature extraction step extracts useful features for anomaly detection by counting log events. For a complex sy

Soham Deshmukh, Charles Lee

Intent detection is a key part of any Natural Language Understanding (NLU) system of a conversational assistant. Detecting the correct intent is essential yet difficult for email conversations where multiple directives and intents are present. In such settings, conversation context can become a key disambiguating factor for detecting the user's request from

Pia Bredt, Wolfgang Kilian, Jürgen Reuter, Pascal Stienemeier

We present results on NLO electroweak (EW) corrections to multiple massive boson production processes at a future muon collider. Inclusive cross sections with $\mathcal{O}(\alpha)$ corrections for processes for up to four bosons in the final state as well as differential distributions for $HZ$ production are computed for $\sqrt{s}=3$, $10$ and $14$ TeV by us

L. Richard, Yu. V. Khotyaintsev, D. B Graham, C. T. Russell

Plasma jets are ubiquitous in the Earth's magnetotail. Plasma jet fronts (JFs) are the seat of particle acceleration and energy conversion. JFs are commonly associated with dipolarization fronts (DFs) representing solitary sharp and strong increases in the northward component of the magnetic field. However, MHD and kinetic instabilities can develop at JFs an

Can Zheng, Yanshan Wang, Xiaowei Jia

Semantic textual similarity (STS) in the clinical domain helps improve diagnostic efficiency and produce concise texts for downstream data mining tasks. However, given the high degree of domain knowledge involved in clinic text, it remains challenging for general language models to infer implicit medical relationships behind clinical sentences and output sim

Sumana Kumar, Sukanta Nandi, Vikash Mishra, Alok Shukla

Electrochemical capacitors with pure electric double layer capacitance are so far largely been limited to carbon materials only. Conventional metal oxides with Faradaic pseudocapacitance substantially suffer from material instability at high temperatures and thus there is a demand for novel metal oxides exhibiting thermally improved high electric double laye

Alberto Zingaro, Michele Bucelli, Ivan Fumagalli, Luca Dede'

A major challenge in the computational fluid dynamics modeling of the heart function is the simulation of isovolumetric phases when the hemodynamics problem is driven by a prescribed boundary displacement. During such phases, both atrioventricular and semilunar valves are closed: consequently, the ventricular pressure may not be uniquely defined, and spuriou

Nitish Chandrappa, Marc Bernacki

Numerous full-field numerical methods exist concerning the digital description of polycrystalline materials and the modeling of their evolution during thermomechanical treatments. However, these strategies are globally dedicated to the modeling of recrystallization and grain growth for single-phase materials, or to the modeling of phase transformations witho

Eldad Haber, Moshe Eliasof, Luis Tenorio

Estimating a Gibbs density function given a sample is an important problem in computational statistics and statistical learning. Although the well established maximum likelihood method is commonly used, it requires the computation of the partition function (i.e., the normalization of the density). This function can be easily calculated for simple low-dimensi

Zachary Charles, Kallista Bonawitz, Stanislav Chiknavaryan, Brendan McMahan

Federated learning (FL) is a framework for machine learning across heterogeneous client devices in a privacy-preserving fashion. To date, most FL algorithms learn a "global" server model across multiple rounds. At each round, the same server model is broadcast to all participating clients, updated locally, and then aggregated across clients. In this work, we

Hou Y. Yau

In this paper, we show that an oscillator in proper time can mimic a point mass at rest in general relativity. The spacetime outside this proper time oscillator is static and satisfies the Schwarzschild solution.

Roger F. Sewell

Two observational methods are currently being used to monitor post-deployment vaccine effectiveness: the obvious crude method comparing rate testing positive per head of vaccinated population with that rate per head of unvaccinated population; and the test-negative case control (TNCC) method. The two methods give very different results. We want to know wheth

Mark J. Crumpton, Yan V. Fyodorov, Pierpaolo Vivo

We compute analytically the probability distribution and moments of the sum and product of the non-zero eigenvalues and singular values of random matrices with (i) non-negative entries, (ii) fixed rank, and (iii) prescribed sums of the entries in each row. Applications of such matrices are discussed in the context of Markov chains, economics and social netwo

Di Peng, Ren-Shu Wang, Li-Na Zong, Xiao-Jia Chen

Pressure as a clean and efficient tool can bring about unexpected extraordinary physical and chemical properties of matters. The recent discoveries of superconductivity at nearly room temperature in hydrides highlight the power of pressure in this aspect. Capturing such Tc superconductivity at atmosphere pressure for the technological applications is highly

V. K. Suman, P. Sundaram, Soumyo Sengupta, Aditi Sengupta

The global spectral analysis (GSA) of numerical methods ensures that the dispersion relation preserving (DRP) property is calibrated in addition to ensuring numerical stability, as advocated in the von Neumann analysis. The DRP nature plays a major role where spatio-temporal dependence in the governing equation and boundary conditions has to be retained, suc

Naresh Kumar Gurulingan, Elahe Arani, Bahram Zonooz

Multi-task learning of dense prediction tasks, by sharing both the encoder and decoder, as opposed to sharing only the encoder, provides an attractive front to increase both accuracy and computational efficiency. When the tasks are similar, sharing the decoder serves as an additional inductive bias providing more room for tasks to share complementary informa

Lutz Duembgen, Klaus Nordhausen

We derive limiting distributions of symmetrized estimators of scatter, where instead of all $n(n-1)/2$ pairs of the $n$ observations we only consider $nd$ suitably chosen pairs, $1 \le d < \lfloor n/2\rfloor$. It turns out that the resulting estimators are asymptotically equivalent to the original one whenever $d = d(n) \to \infty$ at arbitrarily slow speed.

Changzhen Li, Jie Zhang, Shuzhe Wu, Xin Jin

Recently action recognition has received more and more attention for its comprehensive and practical applications in intelligent surveillance and human-computer interaction. However, few-shot action recognition has not been well explored and remains challenging because of data scarcity. In this paper, we propose a novel hierarchical compositional representat

Baghdasar Baghdasaryan, Carlos Sevilla-Gutiérrez, Fabian Steinlechner, Stephan Fritzsche

Spontaneous parametric down-conversion (SPDC) is a widely used source for photonic entanglement. Years of focused research have led to a solid understanding of the process, but a cohesive analytical description of the paraxial biphoton state has yet to be achieved. We derive a general expression for the spatio-temporal biphoton state that applies universally

Jérôme Claude, Maíra Dutra, Stephen Godfrey

Dark matter may consist of feebly interacting massive particles (FIMPs) that never thermalized with the cosmic plasma. Their relic density is achieved via freeze-in for a wide range of masses, significantly expanding the model space that can be tested compared to other production mechanisms. However, testing the tiny couplings required by freeze-in is challe

Nick Sauerwein, Francesca Orsi, Philipp Uhrich, Soumik Bandyopadhyay

All-to-all interacting, disordered quantum many-body models have a wide range of applications across disciplines, from spin glasses in condensed-matter physics, over holographic duality in high-energy physics, to annealing algorithms in quantum computing. Typically, these models are abstractions that do not find unambiguous physical realisations in nature. H

Beomseok Kang, Saibal Mukhopadhyay

Large multi-agent systems such as real-time strategy games are often driven by collective behavior of agents. For example, in StarCraft II, human players group spatially near agents into a team and control the team to defeat opponents. In this light, clustering the agents in the game has been used for various purposes such as the efficient control of the age

Yi Sun

Intermolecular hydrogen transfer free radical reactions are common in the combustion process and in a number of organic chemistry reactions. Therefore, evaluating the pressure and temperature-dependent rate constants of them is of great importance. Here, we present a tutorial on how a Master Equation model can be constructed to evaluate the rate constants of

Saurav Agarwal, Srinivas Akella

The line coverage problem involves finding efficient routes for the coverage of linear features by one or more resource-constrained robots. Linear features model environments like road networks, power lines, and oil and gas pipelines. Two modes of travel are defined for robots: servicing and deadheading. A robot services a feature if it performs task-specifi

Wei Huang, Xingyu Zhao, Gaojie Jin, Xiaowei Huang

Interpretability of Deep Learning (DL) is a barrier to trustworthy AI. Despite great efforts made by the Explainable AI (XAI) community, explanations lack robustness -- indistinguishable input perturbations may lead to different XAI results. Thus, it is vital to assess how robust DL interpretability is, given an XAI method. In this paper, we identify several

Yufeng Huang, Zhuo Chen, Jiaoyan Chen, Jeff Z. Pan

Multi-modal aspect-based sentiment classification (MABSC) is task of classifying the sentiment of a target entity mentioned in a sentence and an image. However, previous methods failed to account for the fine-grained semantic association between the image and the text, which resulted in limited identification of fine-grained image aspects and opinions. To ad

Georgios Iatropoulos, Johanni Brea, Wulfram Gerstner

We consider the problem of training a neural network to store a set of patterns with maximal noise robustness. A solution, in terms of optimal weights and state update rules, is derived by training each individual neuron to perform either kernel classification or interpolation with a minimum weight norm. By applying this method to feed-forward and recurrent

Thea Kozakis, João M. Mendonça, Lars A. Buchhave

Molecular oxygen (O2) paired with a reducing gas is regarded as a promising biosignature pair for the atmospheric characterization of terrestrial exoplanets. In circumstances when O2 may not be detectable in a planetary atmosphere (e.g., at mid-IR wavelengths) it has been suggested that ozone (O3), the photochemical product of O2, could be used as a proxy to

Zdravko Marinov, Alina Roitberg, David Schneider, Rainer Stiefelhagen

Modality selection is an important step when designing multimodal systems, especially in the case of cross-domain activity recognition as certain modalities are more robust to domain shift than others. However, selecting only the modalities which have a positive contribution requires a systematic approach. We tackle this problem by proposing an unsupervised

Li Zhang, Yuanjie Chen, Dong Pan, Shaoyun Huang

Semiconductor InSb nanosheet/hexagonal boron nitride (hBN)/graphite trilayers are fabricated, and single- and double-gate devices made from the trilayers are realized and characterized. The InSb nanosheets employed in the trilayer devices are epitaxially grown, free-standing, zincblende crystals and are in micrometer lateral sizes. The hBN and graphite flake

Ben Whewell, Ryan G. McClarren, Cory D. Hauck, Minwoo Shin

A collision-based hybrid algorithm for the discrete ordinates approximation of the neutron transport equation is extended to the multigroup setting. The algorithm uses discrete energy and angle grids at two different resolutions and approximates the fission and scattering sources on the coarser grids. The coupling of a collided transport equation, discretize

Thai-Nam Hoang, Sang Truong, Chris Schmidt

Wildfire forecasting has been one of the most critical tasks that humanities want to thrive. It plays a vital role in protecting human life. Wildfire prediction, on the other hand, is difficult because of its stochastic and chaotic properties. We tackled the problem by interpreting a series of wildfire images as a video and used it to anticipate how the fire

Shengshan Qin, Chen Fang, Fu-chun Zhang, Jiangping Hu

Spin-triplet superconductivity is known to be a rare quantum phenomenon. Here we show that nonsymmorphic crystalline symmetries can dramatically assist spin-triplet superconductivity in the presence of spin-orbit coupling. Even with a weak spin-orbit coupling, the spin-triplet pairing can be the leading pairing instability in a lattice with a nonsymmorphic s

Mohammadreza Amirian, Javier A. Montoya-Zegarra, Jonathan Gruss, Yves D. Stebler

With the spread of COVID-19 over the world, the need arose for fast and precise automatic triage mechanisms to decelerate the spread of the disease by reducing human efforts e.g. for image-based diagnosis. Although the literature has shown promising efforts in this direction, reported results do not consider the variability of CT scans acquired under varying

Nika Haghtalab, Thodoris Lykouris, Sloan Nietert, Alexander Wei

We study Stackelberg games where a principal repeatedly interacts with a non-myopic long-lived agent, without knowing the agent's payoff function. Although learning in Stackelberg games is well-understood when the agent is myopic, dealing with non-myopic agents poses additional complications. In particular, non-myopic agents may strategize and select actions

Wenjie Yin, Hang Yin, Kim Baraka, Danica Kragic

We present CycleDance, a dance style transfer system to transform an existing motion clip in one dance style to a motion clip in another dance style while attempting to preserve motion context of the dance. Our method extends an existing CycleGAN architecture for modeling audio sequences and integrates multimodal transformer encoders to account for music con

Debjyoti Bardhan, Supritha Bhowmick, Diptimoy Ghosh, Atanu Guha

The recoil threshold of Direct Detection experiments limits the mass range of Dark Matter (DM) particles that can be detected, with most DD experiments being blind to sub-MeV DM particles. However, these light DM particles can be boosted to very high energies via collisions with energetic Cosmic Ray electrons. This allows Dark Matter particles to induce dete

Mauricio Cruz Reyes, Richard I. Anderson

We have conducted a search for open clusters in the vicinity of classical Galactic Cepheids based on high-quality astrometry from the third data release (DR3) of the ESA mission Gaia to improve the calibration of the Leavitt law (LL). Our approach requires no prior knowledge of existing clusters, allowing us to both detect new host clusters and cross-check p

BESIII Collaboration, M. Ablikim, M. N. Achasov, P. Adlarson

The decay $D\to K^-\pi^+$ is studied in a sample of quantum-correlated $D\bar{D}$ pairs, based on a data set corresponding to an integrated luminosity of 2.93\,fb$^{-1}$ collected at the $\psi(3770)$ resonance by the BESIII experiment. The asymmetry between $C\!P$-odd and $C\!P$-even eigenstate decays into $K^-\pi^+$ is determined to be ${\cal A}_{K\pi} = 0.

Anirban Ghosh, Sudipta Mandal, Dipanjan Chakraborty

We have studied the persistence probability $p(t)$ of an active Brownian particle with shape asymmetry in two dimensions. The persistence probability is defined as the the probability of a stochastic variable that has not changed it's sign in the fixed given time interval. We have investigated two cases: diffusion of a free active particle and that of harmon

Vladimir Petrov Kostov

We prove that for $q\in (-1,0)\cup (0,1)$, the partial theta function $\theta (q,x):=\sum _{j=0}^{\infty}q^{j(j+1)/2}x^j$ has no zeros in the closed unit disk.

P. I. Cristofari, J. -F. Donati, T. Masseron, P. Fouqué

We describe advances on a method designed to derive accurate parameters of M dwarfs. Our analysis consists in comparing high-resolution infrared spectra acquired with the near-infrared spectro-polarimeter SPIRou to synthetic spectra computed from MARCS model atmospheres, in order to derive the effective temperature ($T_{\rm eff}$), surface gravity ($\rm \log

Juan Miguel Lopez Alcaraz, Nils Strodthoff

The imputation of missing values represents a significant obstacle for many real-world data analysis pipelines. Here, we focus on time series data and put forward SSSD, an imputation model that relies on two emerging technologies, (conditional) diffusion models as state-of-the-art generative models and structured state space models as internal model architec

Mustafa Yildirim, Ilker Oguz, Fabian Kaufmann, Marc Reig Escale

Modern machine learning models use an ever-increasing number of parameters to train (175 billion parameters for GPT-3) with large datasets to obtain better performance. Bigger is better has been the norm. Optical computing has been reawakened as a potential solution to large-scale computing through optical accelerators that carry out linear operations while

Lijin Wang, Grzegorz Szamel, Elijah Flenner

The scaling of the non-phononic spectrum for 2D systems has been recently debated. Here we provide evidence that the non-phononic spectrum $D_{ex}(\omega) \sim \omega^\beta$ where $\beta \approx 3.5$ and there is no clear evidence of a finite size effect in beta for systems greater than 100 particles.

Oren Bergman, Shinji Hirano

The space of ${\cal N}=4$ supersymmetric Yang-Mills theories exhibits an intricate structure of global one-form symmetries and $SL(2,\mathbb{Z})$ duality orbits. In this paper we study this structure from the point of view of the holographic dual Type IIB string theory. Generalizing work by Witten, we map the different theories based on the gauge algebras $s

Furong Fan, Yuanjie Chen, Dong Pan, Jianhua Zhao

We report on an experimental study of the spin-orbit interaction (SOI) in an epitaxially grown free-standing InAs nanosheet in a dual-gate field-effect device. Gate-transfer characteristic measurements show that independent tunings of the carrier density in the nanosheet and the potential difference across the nanosheet can be efficiently achieved with use o

Hongyu Zhou, Zheng Ge, Weixin Mao, Zeming Li

Currently, detecting 3D objects in Bird's-Eye-View (BEV) is superior to other 3D detectors for autonomous driving and robotics. However, transforming image features into BEV necessitates special operators to conduct feature sampling. These operators are not supported on many edge devices, bringing extra obstacles when deploying detectors. To address this pro

Filip Huško, Cedric G. Lacey

We use SWIFT, a smoothed particle hydrodynamics code, to simulate the evolution of bubbles inflated by active galactic nuclei (AGN) jets, as well as their interactions with the ambient intracluster medium (ICM). These jets inflate lobes that turn into bubbles after the jets are turned off (at $t=50$ Myr). Almost all of the energy injected into the jets is tr

Arpit Bansal, Eitan Borgnia, Hong-Min Chu, Jie S. Li

Standard diffusion models involve an image transform -- adding Gaussian noise -- and an image restoration operator that inverts this degradation. We observe that the generative behavior of diffusion models is not strongly dependent on the choice of image degradation, and in fact an entire family of generative models can be constructed by varying this choice.

D. Alvarez-Castillo

The study of the variation of fundamental constants through time or in localized regions of space is one of the goals of the Cosmic Ray Extremely Distributed Observatory which consists of multiple detectors over the Earth. In this paper, the various effects which can be potentially identified through cosmic rays detections by CREDO are presented.

Josh Hoffmann, David Sloan

There are many single field inflationary models that are consistent with the recent Planck 2018 measurements of the spectral index $n_s$ and tensor-to-scalar ratio $r$. Despite good agreement with observational data some of these models suffer from having unregularized potentials which would produce a collapsing universe shortly after the end of inflation. I

Yanru Xu, Shen Xu, Jingchao Zhang, Jianshu Gao

Along with device miniaturization, severe heat accumulation at unexpected nanoscale hotspots attracts wide attentions and urges efficient thermal management. Heat convection is one of the important heat dissipating paths but its mechanism at nanoscale hotspots is still unclear. Here shows the first experimental investigation of the convective heat transfer c

Alex Bespalov, Dirk Praetorius, Michele Ruggeri

This paper is concerned with the numerical approximation of quantities of interest associated with solutions to parametric elliptic partial differential equations (PDEs). The key novelty of this work is in its focus on the quantities of interest represented by continuously G\^ateaux differentiable nonlinear functionals. We consider a class of parametric elli

Akash Singh, K. P. Yogendran

In this article, we study the finite temperature properties of a 10-D version of a hardwall model for QCD. Introducing fundamental matter via probe D7-branes and separate cutoffs for the branes and the bulk, we present a detailed exploration of the phases for varying temperature and quark mass. Finite thermodynamic quantities are calculated using the procedu

Wojciech Górecki, Alberto Riccardi, Lorenzo Maccone

We provide the optimal measurement strategy for a class of noisy channels that reduce to the identity channel for a specific value of a parameter (spreading channels). We provide an example that is physically relevant: the estimation of the absolute value of the displacement in the presence of phase randomizing noise. Surprisingly, this noise does not affect

Kento Tsubouchi, Takahiro Sagawa, Nobuyuki Yoshioka

We present a unified approach to analyzing the cost of various quantum error mitigation methods on the basis of quantum estimation theory. By analyzing the quantum Fisher information matrix of a virtual quantum circuit that effectively represents the operations of quantum error mitigation methods, we derive for a generic layered quantum circuit under a wide

Mingran Kong, Shuichi Murakami, Tiantian Zhang

Excitons, which are composite boson quasi-particles composed of bound electrons and holes, have many fascinating properties and great potential in practical applications. Though experimental studies on exciton dynamics are well-developed, the ab initio simulation ones still remain vacant until two years ago. Here, we apply the density functional theory (DFT)

Yaosen Min, Ye Wei, Peizhuo Wang, Xiaoting Wang

Accurate prediction of protein-ligand binding affinities is an essential challenge in structure-based drug design. Despite recent advances in data-driven methods for affinity prediction, their accuracy is still limited, partially because they only take advantage of static crystal structures while the actual binding affinities are generally determined by the

Bruce Hoeneisen

The root-mean-square of non-relativistic warm dark matter particle velocities scales as $v_{h\textrm{rms}}(a) = v_{h\textrm{rms}}(1)/a$, where $a$ is the expansion parameter of the universe. This velocity dispersion results in a cut-off of the power spectrum of density fluctuations due to dark matter free-streaming. Let $k_\textrm{fs}(t_\textrm{eq})$ be the

Li Zhang, Dong Pan, Yuanjie Chen, Jianhua Zhao

A gated Hall-bar device is made from an epitaxially grown, free-standing InSb nanosheet on a hexagonal boron nitride (hBN) dielectric/graphite gate structure and the electron transport properties in the InSb nanosheet are studied by gate-transfer characteristic and magnetotransport measurements at low temperatures. The measurements show that the carriers in

Niklas Tausendpfund, Sebastian Diehl, Matteo Rizzi

We devise a number-conserving scheme for the realization of Majorana Zero Modes in an interacting fermionic ladder coupled by Aharonov-Bohm cages. The latter provide an efficient mechanism to cancel single-particle hopping by destructive interference. The crucial parity symmetry in each wire is thus encoded in the geometry of the setup, in particular, its tr

Davide Chiuchiu, Shrabani Mondal, Simone Pigolotti

Biological processes such as DNA replication, RNA transcription, and protein translation show remarkable speed and accuracy in selecting the right substrate from pools of chemically identical molecules. This result is obtained by nonequilibrium reactions that dissipate chemical energy. It is widely recognized that there must be a trade-off between speed, err

Maxwell Levine

Cummings, Foreman, and Magidor proved that Jensen's square principle is non-compact at $\aleph_\omega$, meaning that it is consistent that $\square_{\aleph_n}$ holds for all $n<\omega$ while $\square_{\aleph_\omega}$ fails. We investigate the natural question of whether this phenomenon generalizes to singulars of uncountable cofinality. Surprisingly, we show

Nicolò D'Anna, Dario Ferreira Sanchez, Guy Matmon, Jamie Bragg

The progress of miniaturisation in integrated electronics has led to atomic and nanometre-sized dopant devices in silicon. Such structures can be fabricated routinely by hydrogen resist lithography, using various dopants such as phosphorous and arsenic. However, the ability to non-destructively obtain atomic-species-specific images of the final structure, wh

M. N. M. van Lieshout, Z. Baki

The discovery of gas in Groningen in 1959 has been a massive boon to the Dutch economy. From the 1990s onwards though, gas production has led to induced seismicity. In this paper, we carry out a comprehensive exploratory analysis of the spatio-temporal earthquake catalogue. We develop a non-parametric adaptive kernel smoothing technique to estimate the spati

Vasileios Tsouvalas, Aaqib Saeed, Tanir Ozcelebi, Nirvana Meratnia

Federated Learning (FL) is a distributed machine learning paradigm that enables learning models from decentralized private datasets, where the labeling effort is entrusted to the clients. While most existing FL approaches assume high-quality labels are readily available on users' devices; in reality, label noise can naturally occur in FL and is closely relat

P. Mas-Buitrago, E. Solano, A. González-Marcos, C. Rodrigo

Ultracool dwarfs (UCDs) comprise the lowest mass members of the stellar population and brown dwarfs, from M7 V to cooler objects with L, T, and Y spectral types. Most of them have been discovered using wide-field imaging surveys, for which the Virtual Observatory (VO) has proven to be of great utility. We aim to perform a search for UCDs in the entire Javala

Dezhao Huang, Qiangsheng Sun, Zeyu Liu, Shen Xu

Gallium nitride (GaN) is a typical wide-bandgap semiconductor with a critical role in a wide range of electronic applications. Ballistic thermal transport at nanoscale hotspots will greatly reduce the performance of a device when its characteristic length reaches the nanometer scale, due to heat dissipation. In this work, we developed a tip-enhanced Raman th

Sichun Luo, Yuanzhang Xiao, Linqi Song

Federated recommendation applies federated learning techniques in recommendation systems to help protect user privacy by exchanging models instead of raw user data between user devices and the central server. Due to the heterogeneity in user's attributes and local data, attaining personalized models is critical to help improve the federated recommendation pe

Sunan He, Taian Guo, Tao Dai, Ruizhi Qiao

Image and language modeling is of crucial importance for vision-language pre-training (VLP), which aims to learn multi-modal representations from large-scale paired image-text data. However, we observe that most existing VLP methods focus on modeling the interactions between image and text features while neglecting the information disparity between image and

Zeev Nutov

In minimum power network design problems we are given an undirected graph $G=(V,E)$ with edge costs $\{c_e:e \in E\}$. The goal is to find an edge set $F\subseteq E$ that satisfies a prescribed property of minimum power $p_c(F)=\sum_{v \in V} \max \{c_e: e \in F \mbox{ is incident to } v\}$. In the Min-Power $k$ Edge Disjoint $st$-Paths problem $F$ should co

Po-Yi Liu, Chi-Hua Wang, Henghsiu Tsai

This paper presents a novel non-stationary dynamic pricing algorithm design, where pricing agents face incomplete demand information and market environment shifts. The agents run price experiments to learn about each product's demand curve and the profit-maximizing price, while being aware of market environment shifts to avoid high opportunity costs from off

Swamit Tannu, Poulami Das, Ramin Ayanzadeh, Moinuddin Qureshi

Quantum computers with hundreds of qubits will be available soon. Unfortunately, high device error-rates pose a significant challenge in using these near-term quantum systems to power real-world applications. Executing a program on existing quantum systems generates both correct and incorrect outcomes, but often, the output distribution is too noisy to disti

Takeshi Morita

The range of motion of a particle with certain energy $E$ confined in a potential is determined from the energy conservation law in classical mechanics. The counterpart of this question in quantum mechanics can be regarded as what the possible range of the expectation values of the position operator $ \langle x \rangle$ of a particle, which satisfies $E= \la

Omar Contigiani, Henk Hoekstra, Margot M. Brouwer, Andrej Dvornik

The masses of galaxy clusters can be measured using data obtained exclusively from wide photometric surveys in one of two ways: directly from the amplitude of the weak lensing signal or, indirectly, through the use of scaling relations calibrated using binned lensing measurements. In this paper, we build on a recently proposed idea and implement an alternati

Q. Faure, C. D. Dashwood, C. V. Colin, R. D. Johnson

We report a comprehensive experimental investigation of the magnetic structure of the cycloidal phase in Ca$_3$Ru$_2$O$_7$, which mediates the spin reorientation transition, and establishes its magnetic phase diagram. In zero applied field, single-crystal neutron diffraction data confirms the scenario deduced from an earlier resonant x-ray scattering study:

Na Li, Robert Ross

Confusion is a mental state triggered by cognitive disequilibrium that can occur in many types of task-oriented interaction, including Human-Robot Interaction (HRI). People may become confused while interacting with robots due to communicative or even task-centred challenges. To build a smooth and engaging HRI, it is insufficient for an agent to simply detec

Ting Bai, Alexander Johansson, Karl Henrik Johansson, Jonas Mårtensson

Truck drivers are required to stop and rest with a certain regularity according to the driving and rest time regulations, also called Hours-of-Service (HoS) regulations. This paper studies the problem of optimally forming platoons when considering realistic HoS regulations. In our problem, trucks have fixed routes in a transportation network and can wait at

George Z. Li

In this note, we present a simple differentially private algorithm for the global minimum cut problem using only one call to the exponential mechanism. This problem was first studied by Gupta et al. [2010], and they gave a differentially private algorithm with near-optimal utility guarantees. We improve upon their work in many aspects: our algorithm is simpl

Muhammad Azeem Akbar, Abeer Al-Sanad, Saima Rafi, Yuqing Wang

In modern software development world, experts are trying to provide the best solutions to their clients. To achieve this, the organizations opt for the agile software development process as it enables them to develop and deliver the product in-time and as per clients expectations. Consequently, in software engineering industry, the Global Software Developmen

Syver Døving Agdestein, Benjamin Sanderse

Simulating multi-scale phenomena such as turbulent fluid flows is typically computationally very expensive. Filtering the smaller scales allows for using coarse discretizations, however, this requires closure models to account for the effects of the unresolved on the resolved scales. The common approach is to filter the continuous equations, but this gives r

Bofeng Wu, Chao-Guang Huang

By applying the symmetric and trace-free formalism in terms of the irreducible Cartesian tensors, the metric for the external gravitational field of a spatially compact stationary source is provided in $F(X,Y,Z)$ gravity, a generic fourth-order theory of gravity, where $X:=R$ is Ricci scalar, $Y:=R_{\mu\nu}R^{\mu\nu}$ is Ricci square, and $Z:=R_{\mu\nu\rho\s