Miracle-dz/UniFAR-FTUs huggingface dataset:
Simultaneous Reduced Basis Approximation of Parameterized Elliptic Eigenvalue Problems

The focus is on a model reduction framework for parameterized elliptic eigenvalue problems by a reduced basis method. In contrast to the standard single output case, one is interested in approximating several outputs simultaneously, namely a certain number of the smallest eigenvalues. For a fast and reliable evaluation of these input-output relations, we analyze a posteriori error estimators for eigenvalues. Moreover, we present different greedy strategies and study systematically their performance. Special attention needs to be paid to multiple eigenvalues whose appearance is parameter-dependent. Our methods are of particular interest for applications in vibro-acoustics.
Fast model averaging via buffered states and first-order accelerated optimization algorithms

In this letter, we study the problem of accelerating reaching average consensus over connected graphs in a discrete-time communication setting. Literature has shown that consensus algorithms can be accelerated by increasing the graph connectivity or optimizing the weights agents place on the information received from their neighbors. Here, instead of altering the communication graph, we investigate two methods that use buffered states to accelerate reaching average consensus over a given graph. In the first method, we study how convergence rate of the well-known first-order Laplacian average consensus algorithm changes when agreement feedback is generated from buffered states. For this study, we obtain a sufficient condition on the ranges of buffered state that leads to faster convergence. In the second proposed method, we show how the average consensus problem can be cast as a convex optimization problem and solved by first-order accelerated optimization algorithms for strongly-convex cost functions. We construct an accelerated average consensus algorithm using the so-called Triple Momentum optimization algorithm. The first approach requires less global knowledge for choosing the step size, whereas the second one converges faster in our numerical results by using extra information from the graph topology. We demonstrate our results by implementing the proposed algorithms in a Gaussian Mixture Model (GMM) estimation problem used in sensor networks.
Masked Contrastive Representation Learning

Masked image modelling (e.g., Masked AutoEncoder) and contrastive learning (e.g., Momentum Contrast) have shown impressive performance on unsupervised visual representation learning. This work presents Masked Contrastive Representation Learning (MACRL) for self-supervised visual pre-training. In particular, MACRL leverages the effectiveness of both masked image modelling and contrastive learning. We adopt an asymmetric setting for the siamese network (i.e., encoder-decoder structure in both branches), where one branch with higher mask ratio and stronger data augmentation, while the other adopts weaker data corruptions. We optimize a contrastive learning objective based on the learned features from the encoder in both branches. Furthermore, we minimize the $L_1$ reconstruction loss according to the decoders' outputs. In our experiments, MACRL presents superior results on various vision benchmarks, including CIFAR-10, CIFAR-100, Tiny-ImageNet, and two other ImageNet subsets. Our framework provides unified insights on self-supervised visual pre-training and future research.
Remarks on the equivalence between differential graded categories and A-infinity categories

We show that the homotopy theories of differential graded categories and $\mathrm{A}_\infty$-categories over a field are equivalent at the $(\infty,1)$-categorical level. The results are corollaries of a theorem of Canonaco-Ornaghi-Stellari combined with general relationships between different versions of $(\infty,1)$-categories.
Measurement of Branching Fractions and Rate Asymmetries in the Rare Decays B ->K(*) l+ l-

In a sample of 471 million BB events collected with the BABAR detector at the PEP-II e+e- collider we study the rare decays B ->K(*) l+ l-, where l+ l- is either e+e- or mu+mu-. We report results on partial branching fractions and isospin asymmetries in seven bins of di-lepton mass-squared. We further present CP and lepton-flavor asymmetries for di-lepton masses below and above the J/psi resonance. We find no evidence for CP or lepton-flavor violation. The partial branching fractions and isospin asymmetries are consistent with the Standard Model predictions and with results from other experiments.
Unimodal and Multimodal Representation Training for Relation Extraction

Multimodal integration of text, layout and visual information has achieved SOTA results in visually rich document understanding (VrDU) tasks, including relation extraction (RE). However, despite its importance, evaluation of the relative predictive capacity of these modalities is less prevalent. Here, we demonstrate the value of shared representations for RE tasks by conducting experiments in which each data type is iteratively excluded during training. In addition, text and layout data are evaluated in isolation. While a bimodal text and layout approach performs best (F1=0.684), we show that text is the most important single predictor of entity relations. Additionally, layout geometry is highly predictive and may even be a feasible unimodal approach. Despite being less effective, we highlight circumstances where visual information can bolster performance. In total, our results demonstrate the efficacy of training joint representations for RE.
SEARCHING FOR COOL DUST IN THE MID-TO-FAR INFRARED: THE MASS-LOSS HISTORIES OF THE HYPERGIANTS μ Cep, VY CMa, IRC+10420, AND ρ Cas

We present mid- and far-IR imaging of four famous hypergiant stars: the red supergiants μ Cep and VY CMa, and the warm hypergiants IRC +10420 and ρ Cas. Our 11–37 μm SOFIA/FORCAST imaging probes cool dust not detected in visual and near-IR imaging studies. Adaptive optics 8–12 μm imaging of μ Cep and IRC +10420 with MMT/MIRAC reveals extended envelopes that are the likely sources of these stars’ strong silicate emission features. We find μ Cep’s mass-loss rate to have declined by about a factor of five over a 13,000 year history, ranging from 5 × 10−6 down to ∼1× 10−6 M⊙ yr−1. The morphology of VY CMa indicates a cooler dust component coincident with the highly asymmetric reflection nebulae seen in the visual and near-IR. The lack of cold dust at greater distances around VY CMa indicates that its mass-loss history is limited to the last ∼1200 years, with an average rate of 6 × 10−4 M⊙ yr−1. We find two distinct periods in the mass-loss history of IRC +10420 with a high rate of 2 × 10−3 M⊙ yr−1 until approximately 2000 years ago, followed by an order of magnitude decrease in the recent past. We interpret this change as evidence of its evolution beyond the RSG stage. Our new infrared photometry of ρ Cas is consistent with emission from the expanding dust shell ejected in its 1946 eruption, with no evidence of newer dust formation from its more recent events.
Constraining the physical properties of Type II-Plateau supernovae using nebular phase spectra

Massive stars live fast and die young. They shine furiously for a few million years, during which time they synthesize most of the heavy elements in the universe in their cores. They end by blowing themselves up in a powerful explosion known as a supernova (SN). During this process, the core collapses to a neutron star or a black hole, while the outer layers are expelled with velocities of thousands of kilometers per second. The resulting fireworks often outshine the entire host galaxy for many weeks. The explosion energy is eventually radiated away, but powering of the newborn nebula continues by radioactive isotopes synthesized in the explosion. The ejecta are now quite transparent, and we can see the material produced in the deep interiors of the star. To interpret the observations, detailed spectral modeling is needed. This thesis aims to develop and apply state-of-the-art computational tools for interpreting and modeling SN observations in the nebular phase. This requires calculation of the physical conditions throughout the nebula, including non-thermal processes from the radioactivity, thermal and statistical equilibrium, as well as radiative transport. The inclusion of multiline radiative transfer, which we compute with a Monte Carlo technique, represents one of the major advancements presented in this thesis. On February 23 1987, the first SN observable by the naked eye since 1604 exploded, SN 1987A. Its proximity has allowed unprecedented observations, which in turn have lead to significant advancements in our understanding of SN explosions. As a first application of our model, we analyze the 44Tipowered phase (t & 5 years) of SN 1987A. We find that a magnetic field is present in the nebula, trapping the positrons that provide the energy input, and resulting in strong iron lines in the spectrum. We determine the 44Ti mass to 1.5(+0.5−0.5)*10−4 M⊙. From the near-infrared spectrum at an age of 19 years, we identify strong emission lines from explosively synthesized metals such as silicon, calcium, and iron. We use integral-field spectroscopy to construct three-dimensional maps of the ejecta, showing a morphology suggesting an asymmetric explosion. The model is then applied to the close-by and well-observed Type IIP SN 2004et, analyzing its ultraviolet to mid-infrared evolution. Based on its Mg I] 4571 A, Na I 5890, 5896 A, [O I] 6300, 6364 A, and [Ne II] 12.81 mm nebular emission lines, we determine its progenitor mass to be around 15 M⊙. We confirm that silicate dust, SiO, and CO have formed in the ejecta. Finally, the major optical emission lines in a sample of Type IIP SNe areanalyzed.We find that most spectral regions in Type IIP SNe are dominated by emission from the massive hydrogen envelope, which explains the relatively small variation seen in the sample. We also show that the similar line profiles seen from all elements suggest extensive mixing occurring in most hydrogenrich SNe.
From the atmosphere to the circumstellar environment in cool evolved stars

We discuss and illustrate contributions that optical interferometry has made on our current understanding of cool evolved stars. We include red giant branch (RGB) stars, asymptotic giant branch (AGB) stars, and red supergiants (RSGs). Studies using optical interferometry from visual to mid-infrared wavelengths have greatly increased our knowledge of their atmospheres, extended molecular shells, dust formation, and winds. These processes and the morphology of the circumstellar environment are important for the further evolution of these stars toward planetary nebulae (PNe) and core-collapse supernovae (SNe), and for the return of material to the interstellar medium.
Morphologies and Central Stars of Planetary Nebulae in the Galactic bulge from VLT, HST and Pan-STARRS imaging

This is the first in a series of papers that present sets of different results for 136 compact, known planetary nebulae within a 10 × 10 degree region of the Galactic bulge. We use a large, previously unpublished sample of our own extensive ESO 8-m VLT deep imaging and spectroscopic data. This is combined with archival deep Hubble Space Telescope imaging where available to provide a detailed morphological classification and study. The influence of angular resolution and sensitivity when assigning a morphology is discussed. A large fraction (68 per cent) of the sample are shown to be bipolars and the implications for this in the context of planetary nebulae progenitors are explored. Four new planetary nebula central stars are also identified which are not in Gaia. This is based on both Very Large Telescope (VLT) and deep archival Pan-STARRS broad-band imagery. Some 11 putative central stars previously reported, based on Gaia positions, are also not the true central star. In other cases, the Gaia central stars reported in the literature are actually based on the overall centroid position of a very compact planetary nebula rather than the actual central star within it. Gaia parallax distances and kinematic ages for PNe in this sample are provided where possible based on fresh angular size measures from the new VLT imagery and Gaia distances and literature expansion velocities when available. All these results are discussed within the context of the overall characteristics of the Galactic bulge and its planetary nebula population.
A Geometric Approach towards Inverse Kinematics of Soft Extensible Pneumatic Actuators Intended for Trajectory Tracking

Soft robots are interesting examples of hyper-redundancy in robotics. However, the nonlinear continuous dynamics of these robots and the use of hyper-elastic and visco-elastic materials make modeling these robots more complicated. This study presents a geometric inverse kinematics (IK) model for trajectory tracking of multi-segment extensible soft robots, where each segment of the soft actuator is geometrically approximated with a rigid links model to reduce the complexity. In this model, the links are connected with rotary and prismatic joints, which enable both the extension and rotation of the robot. Using optimization methods, the desired configuration variables of the soft actuator for the desired end-effector positions were obtained. Furthermore, the redundancy of the robot is applied for second task applications, such as tip angle control. The model’s performance was investigated through kinematics and dynamics simulations and numerical benchmarks on multi-segment soft robots. The results showed lower computational costs and higher accuracy compared to most existing models. The method is easy to apply to multi-segment soft robots in both 2D and 3D, and it was experimentally validated on 3D-printed soft robotic manipulators. The results demonstrated the high accuracy in path following using this technique.
Nilpotence order growth of recursion operators
in characteristic p

We prove that the killing rate of certain degree-lowering "recursion operators" on a polynomial algebra over a finite field grows slower than linearly in the degree of the polynomial attacked. We also explain the motivating application: obtaining a lower bound for the Krull dimension of a local component of a big mod-p Hecke algebra in the genus-zero case. We sketch the application for p=2 and p=3 in level one. The case p=2 was first established in by Nicolas and Serre in 2012 using different methods.
4DVarNet-SSH: end-to-end learning of variational interpolation schemes for nadir and wide-swath satellite altimetry

Abstract. The reconstruction of sea surface currents from satellite altimeter data is a key challenge in spatial oceanography, especially with the upcoming wide-swath SWOT (Surface Water and Ocean and Topography) altimeter mission. Operational systems, however, generally fail to retrieve mesoscale dynamics for horizontal scales below 100 km and timescales below 10 d. Here, we address this challenge through the 4DVarnet framework, an end-to-end neural scheme backed on a variational data assimilation formulation. We introduce a parameterization of the 4DVarNet scheme dedicated to the space–time interpolation of satellite altimeter data. Within an observing system simulation experiment (NATL60), we demonstrate the relevance of the proposed approach, both for nadir and nadir plus SWOT altimeter configurations for two contrasting case study regions in terms of upper ocean dynamics. We report a relative improvement with respect to the operational optimal interpolation between 30 % and 60 % in terms of the reconstruction error. Interestingly, for the nadir plus SWOT altimeter configuration, we reach resolved space–timescales below 70 km and 7 d. The code is open source to enable reproducibility and future collaborative developments. Beyond its applicability to large-scale domains, we also address the uncertainty quantification issues and generalization properties of the proposed learning setting. We discuss further future research avenues and extensions to other ocean data assimilation and space oceanography challenges.
DRAM Bender: An Extensible and Versatile FPGA-Based Infrastructure to Easily Test State-of-the-Art DRAM Chips

To understand and improve DRAM performance, reliability, security, and energy efficiency, prior works study characteristics of commodity DRAM chips. Unfortunately, state-of-the-art open source infrastructures capable of conducting such studies are obsolete, poorly supported, or difficult to use, or their inflexibility limits the types of studies they can conduct. We propose DRAM Bender, a new FPGA-based infrastructure that enables experimental studies on state-of-the-art DRAM chips. DRAM Bender offers three key features at the same time. First, DRAM Bender enables directly interfacing with a DRAM chip through its low-level interface. This allows users to issue DRAM commands in arbitrary order and with finer-grained time intervals compared to other open source infrastructures. Second, DRAM Bender exposes easy-to-use C++ and Python programm ing interfaces, allowing users to quickly and easily develop different types of DRAM experiments. Third, DRAM Bender is easily extensible. The modular design of DRAM Bender allows extending it to: 1) support existing and emerging DRAM interfaces and 2) run on new commercial or custom FPGA boards with little effort. To demonstrate that DRAM Bender is a versatile infrastructure, we conduct three case studies, two of which lead to new observations about the DRAM RowHammer vulnerability. In particular, we show that data patterns supported by DRAM Bender uncover a larger set of bit-flips on a victim row than those commonly used by prior work. We demonstrate the extensibility of DRAM Bender by implementing it on five different FPGAs with DDR4 and DDR3 support. DRAM Bender is freely and openly available at https://github.com/CMU-SAFARI/DRAM-Bender.
On a scenario of onset of strongly dissipative mixed dynamics

In this paper we present the scenario of the occurrence of strongly dissipative mixed dynamics in two-dimensional reversible diffeomorphisms, using as an example the system describing a motion of two point vortices under the influence of wave perturbation and shear flow. For mixed dynamics of this type the chaotic attractor intersects with the chaotic repeller, but their intersection forms a “thin” set. The main stage of this scenario is the appearance of homoclinic structures for a symmetric saddle orbit which arise after crisis of a homoclinic attractor and repeller.
On the origin of the flux ratio anomaly in quadruple lens systems

We explore the origin of flux ratio anomaly in quadruple lens systems. Using a semi-analytic method based on $N$-body simulations, we estimate the effect of possible magnification perturbation caused by subhaloes with a mass scale of <$\sim 10^9\,h^{-1} \textrm{M}_\odot$ in lensing galaxy haloes. Taking into account astrometric shifts, assuming that the primary lens is described by a singular isothermal ellipsoid, the expected change to the flux ratios per a multiply lensed image is just a few percent and the mean of the expected convergence perturbation at the effective Einstein radius of the lensing galaxy halo is $ 0.003$, corresponding to the mean of the ratio of a projected dark matter mass fraction in subhaloes at the effective Einstein radius $0.006$. In contrast, the expected change to the flux ratio caused by line-of-sight structures is typically $\sim 10$ percent and the mean of the convergence perturbation is $0.008$, corresponding to $0.017$. The contribution of magnification perturbation caused by subhaloes is $\sim 40$ percent of the total at a source redshift $z_S= 0.7$ and decreases monotonically in $z_S$ to $\sim 20$ percent at $z_S= 3.6$. Assuming statistical isotropy, the convergence perturbation estimated from observed 11 quadruple lens systems has a positive correlation with the source redshift $z_S$, which is much stronger than that with the lens redshift $z_L$. This feature also supports an idea that the flux ratio anomaly is caused mainly by line-of-sight structures rather than subhaloes. We also discuss about a possible imprint of line-of-sight structures in demagnification of minimum images due to locally underdense structures in the line of sight.
Development and Evaluation of the Institutionally Farmed Research On-line Repository and Management System (InFORMs) towards Knowledge-Sharing and Utilization

Summary Knowledge derived from scientific discoveries and experiments are essential drivers to information management. This study was geared at promoting institutionally-farmed researches as a critical driver to utilization and re-production of new knowledge thru the use of the developed web application, Institutionally-Farmed Research Online Repository and Management System using the SCRUM development methodology. Assessing the application’s compliance to ISO 25010 software quality characteristics, the study described the responses of consented participants after experiencing the use of the application in a certain duration. Key features that aids in the ease of use, access to, and management of the research resource emerged. From the responses, the developed application evidently suggests its usability and compliance to standards from the participants. The application was limited to showcasing all research resources produced in the University, in the last 10 years, after having gone through approval of the research review committee prior inclusion in the database. Maximizing the web application for knowledge-sharing and utilization is commended, advancing instruction and knowledge economy.
Thompson Sampling for High-Dimensional Sparse Linear Contextual Bandits

We consider the stochastic linear contextual bandit problem with high-dimensional features. We analyze the Thompson sampling algorithm using special classes of sparsity-inducing priors (e.g., spike-and-slab) to model the unknown parameter and provide a nearly optimal upper bound on the expected cumulative regret. To the best of our knowledge, this is the first work that provides theoretical guarantees of Thompson sampling in high-dimensional and sparse contextual bandits. For faster computation, we use variational inference instead of Markov Chain Monte Carlo (MCMC) to approximate the posterior distribution. Extensive simulations demonstrate the improved performance of our proposed algorithm over existing ones.
Optimal stopping of Gauss-Markov bridges

We solve the non-discounted, finite-horizon optimal stopping problem of a Gauss-Markov bridge by using a time-space transformation approach. The associated optimal stopping boundary is proved to be Lipschitz continuous on any closed interval that excludes the horizon, and it is characterized by the unique solution of an integral equation. A Picard iteration algorithm is discussed and implemented to exemplify the numerical computation and geometry of the optimal stopping boundary for some illustrative cases.
Are Front-running HFTs Harmful?

This paper is concerned with how a front-running high-frequency trader (HFT) inﬂuences the large trader: whether and under what conditions the latter is harmed or beneﬁted. We study, in the extended Kyle’s model, the interactions between a large informed trader and an HFT who can predict the former’s incoming order in some extent. Equilibria under various speciﬁc situations are discussed. We conclude that HFT always front-runs and the large trader could be favored in the following circumstances: (1) there is suﬃcient noise trading with HFT’s liquidity-consuming trading; (2) the noise trading with HFT’s liquidity-consuming trading is inadequate but HFT’s signal is vague enough. Besides, we explore the inﬂuences of market noise and signal noise on investors’ behavior and proﬁts. We ﬁnd surprisingly that (1) increasing the noise in HFT’s signal might decrease the large trader’s proﬁt; (2) when there are few market noises, although HFT nearly does nothing, the large trader is still hurt; (3) in any case, HFT will not front-run more than half of the large trader’s order.