Miracle-dz/UniFAR-FTUs huggingface dataset:
Stability of the Lanczos algorithm on matrices with regular spectral distributions

We study the stability of the Lanczos algorithm run on problems whose eigenvector empirical spectral distribution is near to a reference measure with well-behaved orthogonal polynomials. We give a backwards stability result which can be upgraded to a forward stability result when the reference measure has a density supported on a single interval with square root behavior at the endpoints. Our analysis implies the Lanczos algorithm run on many large random matrix models is in fact forward stable, and hence nearly deterministic, even when computations are carried out in finite precision arithmetic. Since the Lanczos algorithm is not forward stable in general, this provides yet another example of the fact that random matrices are far from"any old matrix", and care must be taken when using them to test numerical algorithms.
Ultra-low Precision Multiplication-free Training for Deep Neural Networks

The training for deep neural networks (DNNs) demands immense energy consumption, which restricts the development of deep learning as well as increases carbon emissions. Thus, the study of energy-efficient training for DNNs is essential. In training, the linear layers consume the most energy because of the intense use of energy-consuming full-precision (FP32) multiplication in multiply-accumulate (MAC). The energy-efficient works try to decrease the precision of multiplication or replace the multiplication with energy-efficient operations such as addition or bitwise shift, to reduce the energy consumption of FP32 multiplications. However, the existing energy-efficient works cannot replace all of the FP32 multiplications during both forward and backward propagation with low-precision energy-efficient operations. In this work, we propose an Adaptive Layer-wise Scaling PoT Quantization (ALS-POTQ) method and a Multiplication-Free MAC (MF-MAC) to replace all of the FP32 multiplications with the INT4 additions and 1-bit XOR operations. In addition, we propose Weight Bias Correction and Parameterized Ratio Clipping techniques for stable training and improving accuracy. In our training scheme, all of the above methods do not introduce extra multiplications, so we reduce up to 95.8% of the energy consumption in linear layers during training. Experimentally, we achieve an accuracy degradation of less than 1% for CNN models on ImageNet and Transformer model on the WMT En-De task. In summary, we significantly outperform the existing methods for both energy efficiency and accuracy.
Bridging the Generational Gap: Exploring How Virtual Reality Supports Remote Communication Between Grandparents and Grandchildren

When living apart, grandparents and grandchildren often use audio-visual communication approaches to stay connected. However, these approaches seldom provide sufficient companionship and intimacy due to a lack of co-presence and spatial interaction, which can be fulfilled by immersive virtual reality (VR). To understand how grandparents and grandchildren might leverage VR to facilitate their remote communication and better inform future design, we conducted a user-centered participatory design study with twelve pairs of grandparents and grandchildren. Results show that VR affords casual and equal communication by reducing the generational gap, and promotes conversation by offering shared activities as bridges for connection. Participants preferred resemblant appearances on avatars for conveying well-being but created ideal selves for gaining playfulness. Based on the results, we contribute eight design implications that inform future VR-based grandparent-grandchild communications.
Compression-driven viscous fingering in a radial Hele-Shaw cell

The displacement of a viscous liquid by a gas within a Hele-Shaw cell is a classical problem. The gas-liquid interface is hydrodynamically unstable, forming striking finger-like patterns that have attracted research interest for decades. Generally, both the gas and liquid phases are taken to be incompressible, with the capillary number being the key parameter that determines the severity of the instability. Here, we consider a radially outward displacement driven by the steady compression of a gas reservoir. The associated gas-injection rate is then unsteady due to the compressibility of the gas. We identify a second nondimensional parameter, the compressibility number, that plays a strong role in the development of the fingering pattern. We use an axisymmetric model to study the impact of compressibility number on the unsteady evolution of injection rate and gas pressure. We use linear stability analysis to show that increasing the compressibility number delays the onset of finger development relative to the corresponding incompressible case. Finally, we present and compare a series of experiments and fully nonlinear simulations over a broad range of capillary and compressibility numbers. These results show that increasing the compressibility number systematically decreases the severity of the fingering pattern at high capillary number. Our results provide an unprecedented comparison of experiments with simulations for viscous fingering, a comprehensive understanding of the role of compressibility in unstable gas-liquid displacement flows, and insight into a new mechanism for controlling the development of fingering patterns.
Expanding Explainability: From Explainable Artificial Intelligence to Explainable Hardware

The increasing opaqueness of AI and its growing influence on our digital society highlight the necessity for AI-based systems that are trustworthy, accountable, and fair. Previous research emphasizes explainability as a means to achieve these properties. In this paper, we argue that system explainability cannot be achieved without accounting for the underlying hardware on which all digital systems - including AI applications - are realized. As a remedy, we propose the concept of explainable hardware, and focus on chips - which are particularly relevant to current geopolitical discussions on (trustworthy) semiconductors. Inspired by previous work on Explainable Artificial Intelligence (XAI), we develop a hardware explainability framework by identifying relevant stakeholders, unifying existing approaches form hardware manufacturing under the notion of explainability, and discussing their usefulness to satisfy different stakeholders' needs. Our work lays the foundation for future work and structured debates on explainable hardware.
Revocable Cryptography from Learning with Errors

Quantum cryptography leverages many unique features of quantum information in order to construct cryptographic primitives that are oftentimes impossible classically. In this work, we build on the no-cloning principle of quantum mechanics and design cryptographic schemes with key-revocation capabilities. We consider schemes where secret keys are represented as quantum states with the guarantee that, once the secret key is successfully revoked from a user, they no longer have the ability to perform the same functionality as before. We define and construct several fundamental cryptographic primitives with key-revocation capabilities, namely pseudorandom functions, secret-key and public-key encryption, and even fully homomorphic encryption, assuming the quantum subexponential hardness of the learning with errors problem. Central to all our constructions is our approach for making the Dual-Regev encryption scheme (Gentry, Peikert and Vaikuntanathan, STOC 2008) revocable.
Vehicular Behavior-Aware Beamforming Design for Integrated Sensing and Communication Systems

Communication and sensing are two important features of connected and autonomous vehicles (CAVs). In traditional vehicle-mounted devices, communication and sensing modules exist but in an isolated way, resulting in a waste of hardware resources and wireless spectrum. In this paper, to cope with the above inefficiency, we propose a vehicular behavior-aware integrated sensing and communication (VBA-ISAC) beamforming design for the vehicle-mounted transmitter with multiple antennas. In this work, beams are steered based on vehicular behaviors to assist driving and meanwhile provide spectral-efficient uplink data services with the help of a roadside unit (RSU). Specifically, we first predict the area of interest (AoI) to be sensed based on the vehicles’ trajectories. Then, we formulate a VBA-ISAC beamforming design problem to sense the AoI while maximizing the spectral efficiency of uplink communications, where a trade-off factor is introduced to balance the communication and sensing performance. A semi-definite relaxation-based beampattern mismatch minimization (SDR-BMM) algorithm is proposed to solve the formulated problem. To reduce the hardware cost and power consumption, we further improve the proposed VBA-ISAC beamforming design by introducing the hybrid analog-digital (HAD) structure. Numerical results verify the effectiveness of VBA-ISAC scheme and show that the proposed beamforming design outperforms the benchmarks in both spectral efficiency and radar beampattern.
On the optimal switching level for an M/G/1 queueing system

A cost function is studied for an M/G/1 queueing model for which the service rate of the virtual waiting time process Ut for Ut K. The costs considered are costs for maintaining the service rate, costs for switching the service rate and costs proportional to the inventory Ut. The relevant cost factors for the system operating below level K differ from those when Ut > K. The cost function which is considered only for the stationary situation of the Ut-process expresses the average cost per unit time. The problem is to find that K for which the cost function reaches a minimum. Criteria for the possibly optimal cases are found; they have an interesting intuitive interpretation, and require the knowledge of only the first moment of the service time distribution.
Riemannian preconditioned algorithms for tensor completion via tensor ring decomposition

We propose Riemannian preconditioned algorithms for the tensor completion problem via tensor ring decomposition. A new Riemannian metric is developed on the product space of the mode-2 unfolding matrices of the core tensors in tensor ring decomposition. The construction of this metric aims to approximate the Hessian of the cost function by its diagonal blocks, paving the way for various Riemannian optimization methods. Specifically, we propose the Riemannian gradient descent and Riemannian conjugate gradient algorithms. We prove that both algorithms globally converge to a stationary point. In the implementation, we exploit the tensor structure and adopt an economical procedure to avoid large matrix formulation and computation in gradients, which significantly reduces the computational cost. Numerical experiments on various synthetic and real-world datasets -- movie ratings, hyperspectral images, and high-dimensional functions -- suggest that the proposed algorithms are more efficient and have better reconstruction ability than other candidates.
Optimal Control Framework for Multistage Endoreversible Engines with Heat and Mass Transfer

Abstract We develop a general optimal control framework for a difficult class of problems of work maximization in endoreversible multistage processes which yield mechanical work with finite rates and are characterized by multiple (vectorial) efficiencies. Bellman's method of dynamic programming is used either to construct his recurrence equation or to arrive at a discrete maximum principle of Pontryagin's type, in which a Hamiltonian is maximized with respect to controls. Both these algorithms are powerful computational tools which serve to maximize the power output and evaluate optimal controls. Equations of dynamics which follow from energy and matter balances and transfer equations are difference constraints for optimizing work. Irreversibilities caused by the energy and mass transport are essential. Variation of efficiencies is analyzed in terms of heat and mass fluxes as natural control variables. Enhanced bounds for the work released from an engine system or added to a heat-pump system are evaluated. Lagrangians and Hamiltonians of work functionals and discrete canonical equations are effective; they reach their continuous counterparts in the limit of an infinite number of stages. For a finite-time passage of a resource fluid between two given thermodynamic states, an optimal process is shown to be irreversible. Its optimal intensity is characterized well by the Hamiltonian H. Characteristic functions which describe extremal work are found numerically in terms of final states, process duration and number of stages. An extension of classical exergy to nonisothermal separation systems with a finite number of stages and finite holdup time of the resource fluid is one of the main results. This extended exergy simplifies to the classical thermal exergy in the limit of infinite duration and an infinite number of stages. The extended exergy exhibits a hysteretic property as a decrease of maximum work received from a multistage engine system and an increase of minimum work added to a heat-pump system, two properties which are particularly important in high-rate regimes. This work is a significant step towards a realistic theory of nonisothermal chemical engines.
The Lyα Reference Sample. XIV. Lyα Imaging of 45 Low-redshift Star-forming Galaxies and Inferences on Global Emission

We present Lyα imaging of 45 low-redshift star-forming galaxies observed with the Hubble Space Telescope. The galaxies have been selected to have moderate to high star formation rates (SFRs) using far-ultraviolet (FUV) luminosity and Hα equivalent width criteria, but no constraints on Lyα luminosity. We employ a pixel stellar continuum fitting code to obtain accurate continuum-subtracted Lyα, Hα, and Hβ maps. We find that Lyα is less concentrated than FUV and optical line emission in almost all galaxies with significant Lyα emission. We present global measurements of Lyα and other quantities measured in apertures designed to capture all of the Lyα emission. We then show how the escape fraction of Lyα relates to a number of other measured quantities (mass, metallicity, star formation, ionization parameter, and extinction). We find that the escape fraction is strongly anticorrelated with nebular and stellar extinction, weakly anticorrelated with stellar mass, but no conclusive evidence for correlations with other quantities. We show that Lyα escape fractions are inconsistent with common dust extinction laws, and discuss how a combination of radiative transfer effects and clumpy dust models can help resolve the discrepancies. We present an SFR calibration based on Lyα luminosity, where the equivalent width of Lyα is used to correct for nonunity escape fraction, and show that this relation provides a reasonably accurate SFR estimate. We also show stacked growth curves of Lyα for the galaxies that can be used to find aperture loss fractions at a given physical radius.
Multi-Agent Reinforcement Learning for Pragmatic Communication and Control

The automation of factories and manufacturing processes has been accelerating over the past few years, boosted by the Industry 4.0 paradigm, including diverse scenarios with mobile, flexible agents. Efficient coordination between mobile robots requires reliable wireless transmission in highly dynamic environments, often with strict timing requirements. Goal-oriented communication is a possible solution for this problem: communication decisions should be optimized for the target control task, providing the information that is most relevant to decide which action to take. From the control perspective, networked control design takes the communication impairments into account in its optmization of physical actions. In this work, we propose a joint design that combines goal-oriented communication and networked control into a single optimization model, an extension of a multiagent POMDP which we call Cyber-Physical POMDP (CP-POMDP). The model is flexible enough to represent several swarm and cooperative scenarios, and we illustrate its potential with two simple reference scenarios with a single agent and a set of supporting sensors. Joint training of the communication and control systems can significantly improve the overall performance, particularly if communication is severely constrained, and can even lead to implicit coordination of communication actions.
Griffiths phase in a facilitated Rydberg gas at low temperatures

The spread of excitations by Rydberg facilitation bears many similarities to epidemics. Such systems can be modeled with Monte-Carlo simulations of classical rate equations to great accuracy as a result of high dephasing. In this paper, we analyze the dynamics of a Rydberg many-body system in the facilitation regime in the limits of high and low temperatures. While in the high-temperature limit a homogeneous mean-field behaviour is recovered, characteristic effects of heterogeneity can be seen in a frozen gas. At large temperatures the system displays an absorbing-state phase transition and, in the presence of an additional loss channel, self-organized criticality. In a frozen or low-temperature gas, excitations are constrained to a network resembling an Erd\"os-Renyi graph. We show that the absorbing-state phase transition is replaced with an extended Griffiths phase, which we accurately describe by a susceptible-infected-susceptible model on the Erd\"os-Renyi network taking into account Rydberg blockade. Furthermore, we expand upon an existing macroscopic Langevin equation to more accurately describe the density of Rydberg atoms in the frozen and finite temperature regimes.
N=16 magicity revealed at the proton drip-line through the study of 35Ca

The last proton bound calcium isotope $^{35}$Ca has been studied for the first time, using the $^{37}$Ca($p, t$)$^{35}$Ca two neutron transfer reaction. The radioactive $^{37}$Ca nuclei, produced by the LISE spectrometer at GANIL, interacted with the protons of the liquid hydrogen target CRYPTA, to produce tritons $t$ that were detected in the MUST2 detector array, in coincidence with the heavy residues Ca or Ar. The atomic mass of $^{35}$Ca and the energy of its first 3/2$^+$ state are reported. A large $N=16$ gap of 4.61(11) MeV is deduced from the mass measurement, which together with other measured properties, makes $^{36}$Ca a doubly-magic nucleus. The $N = 16$ shell gaps in $^{36}$Ca and $^{24}$O are of similar amplitude, at both edges of the valley of stability. This feature is discussed in terms of nuclear forces involved, within state-of-the-art shell model calculations. Even though the global agreement with data is quite convincing, the calculations underestimate the size of the $N = 16$ gap in 36Ca by 840(110) keV.
$\mathbb{Z}_2$ Non-Hermitian skin effect in equilibrium heavy-fermions

We demonstrate that a correlated equilibrium $f$-electron system with time-reversal symmetry can exhibit a $\mathbb{Z}_2$ non-Hermitian skin effect of quasi-particles. In particular, we analyze a two-dimensional periodic Anderson model with spin-orbit coupling by combining the dynamical mean-field theory (DMFT) and the numerical renormalization group. We prove the existence of the $\mathbb{Z}_2$ skin effect by explicitly calculating the topological invariant and show that spin-orbit interaction is essential to this effect. Our DMFT analysis demonstrates that the $\mathbb{Z}_2$ skin effect of quasi-particles is reflected on the pseudo-spectrum. Furthermore, we analyze temperature effects on this skin effect using the generalized Brillouin zone technique, which clarifies that the skin modes are strongly localized above the Kondo temperature.
A Cooperative Content Dissemination Framework for Fog-Based Internet of Vehicles

As the fog-based internet of vehicles (IoV) is equipped with rich perception, computing, communication and storage resources, it provides a new solution for the bulk data processing. However, the impact caused by the mobility of vehicles brings a challenge to the content scheduling and resource allocation of content dissemination service. In this paper, we propose a time-varying resource relationship graph to model the intertwined impact of the perception, computation, communication and storage resources across multiple snapshots on the content dissemination process of IoV. Based on this graph model, the content dissemination process is modeled as a mathematical optimization problem, where the quality of service of both delay tolerant and delay sensitive services are considered. Owing to its NP-completeness, the optimization problem is decomposed into a joint link and subchannel scheduling subproblem and as well a joint power and flow control subproblem. Then, a cascaded low complexity scheduling algorithm is proposed for the joint link and subchannel scheduling subproblem. Moreover, a robust resource management algorithm is developed for the power and flow control subproblem, where the channel uncertainties in future snapshots are fully considered in the algorithm. Finally, we conduct simulations to show that the effectiveness of the proposed approaches outperforms other state-of-art approaches.
Swing amplification and the gaia phase spirals

We explore the interplay between in-plane and vertical dynamics in stellar discs within the framework of the shearing box approximation. Julian and Toomre used the shearing sheet to show that leading density waves are amplified as they swing into a trailing ones. We extend their formalism into the dimension perpendicular to the disc to obtain explicit solutions for the disc’s response to an impulsive, external excitation. An excitation that is is symmetric about the mid plane produces a density/breathing wave as well as two-armed phase spirals in the vertical phase space plane. On the other hand, an excitation that is antisymmetric about the mid plane leads to a bending wave and single-armed phase spirals. In either case, self-gravity plays a crucial role in driving the evolution of the disturbance and determining the amplitude and pitch angle of the ensuing spirals. We also show that when the disc is excited by a co-rotating cloud, it develops stationary phase spirals in the wake of the cloud. The results call into question simple kinematic arguments that have been used to determine the age of the phase spirals seen in the Gaia survey.
Protected Data Plane OS Using Memory Protection Keys and Lightweight Activation

Increasing data center network speed coupled with application requirements for high throughput and low latencies have raised the efficiency bar for network stacks. To reduce substantial kernel overhead in network processing, recent proposals bypass the kernel or implement the stack as user space OS service -- both with performance isolation, security, and resource efficiency trade-offs. We present Tardis, a new network stack architecture that combines the performance and resource efficiency benefits of kernel-bypass and the security and performance enforcement of in-kernel stacks. Tardis runs the OS I/O stack in user-level threads that share both address spaces and kernel threads with applications, avoiding almost all kernel context switch and cross-core communication overheads. To provide sufficient protection, Tardis leverages x86 protection keys (MPK) extension to isolate the I/O stack from application code. And to enforce timely scheduling of network processing and fine-grained performance isolation, Tardis implements lightweight scheduler activations with preemption timers.