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This article presents recent measurements by the ALICE Collaboration in proton--oxygen (pO), oxygen--oxygen (OO), and neon--neon (Ne--Ne) collisions delivered by the LHC in July 2025. Measurements of the primary charged-particle pseudorapidity density and the elliptic and triangular flow coefficients of charged particles are reported. Experimental evidence of the suppression of neutral pion yields in OO collisions relative to the proton--proton baseline is also discussed. Comparisons of these new data with theoretical models provide key input to understand particle production, collective phenomena, and parton energy loss in small collision systems.
Topological principles constitute at present an integral component of condensed matter physics, permeating the modern characterization of electronic states while also guiding materials design. In this brief Perspective, I highlight three research threads in single-particle topological band theory that have recently gained momentum: (i) the rise of the quantum geometric tensor, whose components can at present be directly accessed with optical probes; (ii) the notions of delicate and multigap topology, which fall outside the scope of tenfold way and symmetry-based indicators yet leave robust physical fingerprints; and (iii) the consideration of bundle gerbes, which capture formerly overlooked higher-form topological aspects of energy bands. These distinct directions have been elegantly woven together: delicate and multigap topological insulators have peculiar features in quantum geometry that can be conveniently captured by bundle gerbes. This viewpoint exposes the recently identified quantization of a non-linear optical response, and it invites deeper and systematic investigations into geometric and topological aspects of band structures beyond conventional Berryology.
In this talk we review recent perturbative and non-perturbative developments in Heavy Quark Effective Theory (HQET).
Low-scale leptogenesis is an attractive explanation for the observed baryon asymmetry of our universe that can be tested at a variety of laboratory experiments. In these proceedings, we review some recent advances in this field. In particular, we find that the viable parameter space is strongly enhanced, compared to the minimal case with two right-handed neutrinos, when a third generation is considered and explore the impact of such enhancement on the testability of the scenario. Finally, we also look at the impact of specific flavour and CP symmetries on said parameter space.
We discuss recent results obtained by the D0 experiment at the Fermilab Tevatron $p\bar p$ collider and recent combinations of CDF and D0 measurements. Regarding the top quark mass, we present recent measurements obtained at D0, the final Run~I+Run~II D0 combination, as well as the preliminary Run~I+Run~II CDF+D0 combination. We also discuss the combination of the CDF+D0 measurements of the $p\bar p \to t\bar t$ forward-backward asymmetry. We present the first measurement of the direct CP-violating charge asymmetry in $B^\pm$ mesons decaying to $μ^\pm D^{0} X$, and discuss the status of the recent evidence for a four-flavor tetraquark state seen at D0.
I review recent developments in POWHEG, a method for interfacing parton-shower generators with NLO QCD computations. I illustrate recent progress in understanding several features of the method, and in clarifying similarity and differences with respect to MC@NLO. Furthermore, I briefly describe a recently introduced framework, the POWHEG BOX, that allows the automatic POWHEG implementation of any given NLO calculation, and has been recently applied to Z+jet production and to Higgs production via vector-boson fusion.
In recent years, there are many progress made in Kähler geometry. In particular, the topics related to the problems of the existence and uniqueness of extremal Kähler metrics, as well as obstructions to the existence of such metrics in general Kähler manifold. In this talk, we will report some recent developments in this direction. In particular, we will discuss the progress recently obtained in understanding the metric structure of the infinite dimensional space of Kaehler potentials, and their applications to the problems mentioned above. We also will discuss some recent on Kaehler Ricci flow.
In recent years, considerable research has been dedicated to the application of neural models in the field of natural language generation (NLG). The primary objective is to generate text that is both linguistically natural and human-like, while also exerting control over the generation process. This paper offers a comprehensive and task-agnostic survey of the recent advancements in neural text generation. These advancements have been facilitated through a multitude of developments, which we categorize into four key areas: data construction, neural frameworks, training and inference strategies, and evaluation metrics. By examining these different aspects, we aim to provide a holistic overview of the progress made in the field. Furthermore, we explore the future directions for the advancement of neural text generation, which encompass the utilization of neural pipelines and the incorporation of background knowledge. These avenues present promising opportunities to further enhance the capabilities of NLG systems. Overall, this survey serves to consolidate the current state of the art in neural text generation and highlights potential avenues for future research and development in this
Kinetic equations of Vlasov type are in widespread use as models in plasma physics. A well known example is the Vlasov-Poisson system for collisionless, unmagnetised plasma. In these notes, we discuss recent progress on the quasineutral limit in which the Debye length of the plasma tends to zero, an approximation widely assumed in applications. The models formally obtained from Vlasov-Poisson systems in this limit can be seen as kinetic formulations of the Euler equations. However, rigorous results on this limit typically require a structural or strong regularity condition. Here we present recent results for a variant of the Vlasov-Poisson system, modelling ions in a regime of massless electrons. We discuss the quasineutral limit from this system to the kinetic isothermal Euler system, in a setting with rough initial data. Then, we consider the connection between the quasineutral limit and the problem of deriving these models from particle systems. We begin by presenting a recent result on the derivation of the Vlasov-Poisson system with massless electrons from a system of extended charges. Finally, we discuss a combined limit in which the kinetic isothermal Euler system is derived
Very recently the LHCb experiment released the first measurement of the ratio $R(Λ_c) = {\rm BR}(Λ_b \to Λ_cτ\barν_τ)/{\rm BR}(Λ_b \to Λ_cμ\barν_μ)$. Moreover, the BABAR experiment reported a new result of the leptonic decay ratio of Upsilon meson $Υ(3S)$, namely, $R_{Υ(3S)} = {\rm BR}(Υ(3S) \to τ^+τ^-)/{\rm BR}(Υ(3S) \to μ^+μ^-)$. Both measurements are below their corresponding Standard Model predictions (deficit), deviating by $\sim 1.1σ$ and $\sim 1.8σ$, respectively. Moreover, the LHCb recently presented the first search of the lepton flavor violating decay $B^0 \to K^{\ast 0}μ^\pmτ^\mp$. Motivated by these new data, in this work we study their impact on the phenomenology of the singlet vector leptoquark ($U_1$) model addressing the hints of lepton flavor universality violation in the semileptonic decays of $B$ mesons ($B$ meson anomalies), by carrying out a global fit analysis. In general, we found that a minimal version of the $U_1$ model with a mass of 1.8 TeV can successfully explain the $B$ meson anomalies, while being compatible with all other flavor observables and LHC bounds. Interestingly, our study shows that the new observables $R(Λ_c)$ and $R_{Υ(3S)}$ generate stron
Object detection serves as a significant step in improving performance of complex downstream computer vision tasks. It has been extensively studied for many years now and current state-of-the-art 2D object detection techniques proffer superlative results even in complex images. In this chapter, we discuss the geometry-based pioneering works in object detection, followed by the recent breakthroughs that employ deep learning. Some of these use a monolithic architecture that takes a RGB image as input and passes it to a feed-forward ConvNet or vision Transformer. These methods, thereby predict class-probability and bounding-box coordinates, all in a single unified pipeline. Two-stage architectures on the other hand, first generate region proposals and then feed it to a CNN to extract features and predict object category and bounding-box. We also elaborate upon the applications of object detection in video event recognition, to achieve better fine-grained video classification performance. Further, we highlight recent datasets for 2D object detection both in images and videos, and present a comparative performance summary of various state-of-the-art object detection techniques.
In this paper we survey the various erasure codes which had been proposed and patented recently, and along the survey we provide introductory tutorial on many of the essential concepts and readings in erasure and Fountain codes. Packet erasure is a fundamental characteristic inherent in data storage and data transmission system. Traditionally replication/ retransmission based techniques had been employed to deal with packet erasures in such systems. While the Reed-Solomon (RS) erasure codes had been known for quite some time to improve system reliability and reduce data redundancy, the high decoding computation cost of RS codes has offset wider implementation of RS codes. However recent exponential growth in data traffic and demand for larger data storage capacity has simmered interest in erasure codes. Recent results have shown promising results to address the decoding computation complexity and redundancy tradeoff inherent in erasure codes.
I discuss recent advances in the study of hydrogen reionization, focusing on progress that was achieved during the years 2010-2011. First, I discuss recent measurements of the progress of reionization. Next, I discuss recent observational constraints on the nature and abundance of the dominant ionizing sources. Finally, I discuss recent progress in modeling reionization. This review is written for an audience of astronomers who do not specialize in the high-redshift Universe.
In this paper, we review recent work in media forensics for digital images, video, audio (specifically speech), and documents. For each data modality, we discuss synthesis and manipulation techniques that can be used to create and modify digital media. We then review technological advancements for detecting and quantifying such manipulations. Finally, we consider open issues and suggest directions for future research.
Understanding inhomogeneous and anisotropic fluid flows require mathematical and computational tools that are tailored to such flows and distinct from methods used to understand the canonical problem of homogeneous and isotropic turbulence. We review some recent developments in the theory of inhomogeneous and anisotropic turbulence, placing special emphasis on several kinds of quasilinear approximations and their corresponding statistical formulations. Aspects of quasilinear theory that have received insufficient attention in the literature are discussed, and open questions are framed.
In this short note we briefly review some recent developments in understanding discrete torsion. Specifically, we give a short overview of the highlights of a group of recent papers which give the basic understanding of discrete torsion. Briefly, those papers observe that discrete torsion can be completely understood simply as the choice of action of the orbifold group on the B field. We summarize the main points of that work.
Recent progress in Lattice QCD is highlighted. After a brief introduction to the methodology of lattice computations the presentation focuses on three main topics: Hadron Spectroscopy, Hadron Structure and Lattice Flavor Physics. In each case a summary of recent computations of selected quantities is provided.
Baryogenesis via leptogenesis provides an appealing mechanism to explain the observed baryon asymmetry of the Universe. Recent refinements in the understanding of the dynamics of leptogenesis include detailed studies of the effects of lepton flavors and of the role possibly played by the lepton asymmetries generated in the decays of the heavier singlet neutrinos $N_{2,3}$. A review of these recent developments in the theory of leptogenesis is presented.
Multi-agent reinforcement learning (MARL) has long been a significant and everlasting research topic in both machine learning and control. With the recent development of (single-agent) deep RL, there is a resurgence of interests in developing new MARL algorithms, especially those that are backed by theoretical analysis. In this paper, we review some recent advances a sub-area of this topic: decentralized MARL with networked agents. Specifically, multiple agents perform sequential decision-making in a common environment, without the coordination of any central controller. Instead, the agents are allowed to exchange information with their neighbors over a communication network. Such a setting finds broad applications in the control and operation of robots, unmanned vehicles, mobile sensor networks, and smart grid. This review is built upon several our research endeavors in this direction, together with some progresses made by other researchers along the line. We hope this review to inspire the devotion of more research efforts to this exciting yet challenging area.
In recent years, researchers have proposed many deep learning (DL) methods for various tasks, and particularly face recognition (FR) made an enormous leap using these techniques. Deep FR systems benefit from the hierarchical architecture of the DL methods to learn discriminative face representation. Therefore, DL techniques significantly improve state-of-the-art performance on FR systems and encourage diverse and efficient real-world applications. In this paper, we present a comprehensive analysis of various FR systems that leverage the different types of DL techniques, and for the study, we summarize 168 recent contributions from this area. We discuss the papers related to different algorithms, architectures, loss functions, activation functions, datasets, challenges, improvement ideas, current and future trends of DL-based FR systems. We provide a detailed discussion of various DL methods to understand the current state-of-the-art, and then we discuss various activation and loss functions for the methods. Additionally, we summarize different datasets used widely for FR tasks and discuss challenges related to illumination, expression, pose variations, and occlusion. Finally, we di