In professional sports, a team has clinched the playoffs if they are guaranteed a postseason spot, regardless of the outcomes of any remaining games. As the season progresses, sports fans and other stakeholders are interested in precisely when, and under what conditions, their team will clinch the playoffs. In this paper, we investigate playoff clinching in the context of the National Hockey League (NHL), where it is computationally challenging to produce clinching scenarios due, in part, to complex tie-breakers. We present an algorithm that determines under which combinations of game outcomes in the next $n$ days a team will clinch the playoffs (i.e., "$n$-day lookahead clinching"). Our approach is a custom tree search which employs various preprocessing techniques, pruning strategies, and node ordering heuristics to efficiently explore the space of possible outcomes. The tree search leverages a constraint programming (CP)-based subroutine for inference that determines if a team has clinched the playoffs for some snapshot in time of the regular season (i.e., "0-day lookahead clinching"). This CP subroutine aims to find a counter-example in which the team being evaluated is elimina
This short essay celebrates the mathematical meaning of Pi Day through Euler's formula \[ e^{ix}=\cos x+i\sin x, \] from which Euler's identity \[ e^{iπ}+1=0 \] follows immediately. We briefly note the historical background of the formula, usually traced to Euler's \emph{Introductio in analysin infinitorum} (1748), while also mentioning Roger Cotes's earlier precursor of 1714. We compare Euler's identity, in an explicitly analogical way, with several famous formulas in physics in order to highlight its remarkable compactness and conceptual richness. We then consider a number of joyful variations arising from the same Eulerian source, including the negative-angle case, prime-number multiples, the substitution $x=π/2$, and a functional-equation variation of the form \[ f(iπx)+1=0. \] This last variation leads naturally to a contrast between rigidity in the holomorphic setting and freedom in the discrete interpolation setting. The central aim is to organize these observations into two simple families of variations: geometric-angle variations and functional-equation variations. The earlier part of the exposition is intended to be accessible to motivated high-school students, while the
The Internet of Vehicles (IoV) is a crucial technology for Intelligent Transportation Systems (ITS) that integrates vehicles with the Internet and other entities. The emergence of 5G and the forthcoming 6G networks presents an enormous potential to transform the IoV by enabling ultra-reliable, low-latency, and high-bandwidth communications. Nevertheless, as connectivity expands, cybersecurity threats have become a significant concern. The issue has been further exacerbated by the rising number of zero-day (0-day) attacks, which can exploit unknown vulnerabilities and bypass existing Intrusion Detection Systems (IDSs). In this paper, we propose Zero-X, an innovative security framework that effectively detects both 0-day and N-day attacks. The framework achieves this by combining deep neural networks with Open-Set Recognition (OSR). Our approach introduces a novel scheme that uses blockchain technology to facilitate trusted and decentralized federated learning (FL) of the ZeroX framework. This scheme also prioritizes privacy preservation, enabling both CAVs and Security Operation Centers (SOCs) to contribute their unique knowledge while protecting the privacy of their sensitive data.
The $Γ$ growth model is an effective parameterization employed across various scientific disciplines and scales to depict growth. It has been demonstrated that the cosmic star formation rate density (CSFRD) can also be described broadly by this pattern, i.e. $\frac{dM(T)}{dT} = M_{z,0}\, \times \frac{β^α}{Γ(α)} \, T^{α-1} e^{-β\, T }$ M$_{\odot}$ Gyr$^{-1}$, where $M_{z,0}$ is the stellar mass at $z$ = 0, $α= 3.0$, $β= 0.5 $ Gyr$^{-1}$ and $T$ describes time. We use the identical $Γ$ growth pattern given by the CSFRD to extend the present day (z = 0) stellar mass bins $M_{\ast}(T)$ of the Galaxy Stellar Mass Function (GSMF) and investigate if we are able to reproduce observations for the high redshift GSMFs. Surprisingly, our scheme describes successfully the evolution of the GSMF over 13.5 Gyrs, especially for objects with intermediate and low masses. We observe some deviations that manifest {\it solely} at very high redshifts ($z > 1.5$, i.e. more than 9.5 Gyr ago) and {\it specifically} for very small and exceedingly massive objects. We discuss the possible solutions (e.g. impacts of mergers) for these offsets. Our formalism suggests that the evolution of the GSMF is set by s
We perform a search of double beta decay of $^{136}$Xe to the excited state, $0^+_1$, of $^{136}$Ba (2$νββ$-0$_1^+$), using the dual-phase xenon detector of PandaX-4T with the first 94.9-day commissioning data. The multi-site events are reconstructed up to the MeV energy scale, which helps to improve the background model significantly. The background contribution from the stainless steel platform outside PandaX-4T cryostat is evaluated for the first time. No significant evidence for 2$νββ$-$0_1^+$ is observed, resulting in a lower limit on half-life of $7.5 \times 10^{22}$ yr at the 90% confidence level. This is the first experimental limit on such a rare decay in a natural xenon-based detector.
We study the evolution of majority dynamics on Erdős-Rényi $G(n,p)$ random graphs. In this process, each vertex of a graph is assigned one of two initial states. Subsequently, on every day, each vertex simultaneously updates its state to the most common state in its neighbourhood. If the difference in the numbers of vertices in each state on day $0$ is larger than $ \max \left\{\frac{1}{\sqrt{p}} \exp\left[A\sqrt{\log \left(\frac{1}{p}\right)}\right] , Bp^{-3/2} n^{-1/2} \right\}$ for constants $A$ and $B$, we demonstrate that the state with the initial majority wins with overwhelmingly high probability. This extends work by Linh Tran and Van Vu (2023), who previously considered this phenomenon. We also study majority dynamics with a random initial assignment of vertex states. When each vertex is assigned to a state with equal probability, we show that unanimity occurs with high probability for every $p \geq λn^{-2/3}$, for some constant $λ$. This improves work by Fountoulakis, Kang and Makai (2020). Furthermore, we also consider a random initial assignment of vertex states where a vertex is slightly more likely to be in the first state than the second state. Previous work by Zehma
We investigate the stability of Milky Way analogs (MWAs) in the \texttt{TNG50} simulation against the growth of local axisymmetric instabilities, tracing their evolution from cosmic noon ($z=2.5$) to the present day ($z=0$). Using a two-component stability criterion that accounts for stars, gas, and the force field of the dark matter halo, we compute the net stability parameter ($Q_{T}$), the critical gas surface density ($Σ_{c}$), and the instability timescale ($τ$) for 10 barred and 10 unbarred MWAs. We find that these galaxies remain stable to axisymmetric instabilities at all epochs, with $Q_{T}^{\min}>2$. The stability levels increase toward higher redshift, where enhanced gas velocity dispersion counterbalances the destabilizing effect of larger gas fractions. Further, the barred MWAs consistently show lower $Q_{T}^{\min}$ than unbarred ones. The gas density remains subcritical ($Σ_{g}<Σ_{c}$) across radii and epochs, implying that local axisymmetric instabilities are not the primary channel for star formation. Growth timescales are short (a few Myr) in central regions but increase exponentially to several Gyr in the outer disc, naturally explaining the concentration of
We study the evolution of the progenitors of the present-day Green Valley (GV) galaxies across redshift $z=10-0$ using data from the EAGLE simulations. We identify the present-day green valley galaxies using entropic thresholding and track the evolution of the physical properties of their progenitors up to $z=10$. Our study identifies three distinct phases in their evolution: (i) an early growth phase ($z=10-6$), where progenitors are gas-rich, efficiently form stars, and experience AGN feedback regulating star formation in massive galaxies, (ii) a transition phase ($z=6-2$), marked by frequent interactions and mergers in higher-density environments, driving starbursts, depleting gas reservoirs, and strengthening correlations between cold gas and halo properties, and (iii) a quenching phase ($z=2-0$), dominated by environmental and mass-dependent processes that suppress star formation and deplete cold gas. Our analysis shows that at $z<1$, environmental factors and cold gas depletion dominate quenching, with tighter correlations between stellar mass, SFR, and cold gas content. The interplay between mass and environmental density during this period drives diverse and distinct evo
The `near-far' approach to studying reionization leverages the star formation histories of the Milky Way (MW) or Local Group (LG) galaxies, derived from resolved photometry, to infer the low-mass/faint-end of the stellar mass functions (SMFs) or the ultraviolet luminosity functions (UVLFs) of high-redshift galaxies ($z \gtrsim 6$), beyond the current JWST detection limits ($M_{\mathrm{UV}} \gtrsim -15$). Previous works considered only intact low-mass galaxies in the MW and LG, neglecting disrupted galaxies such as stellar streams and phase-mixed objects. Using the FIRE-2 simulations, we show that these disrupted galaxies contribute up to $\sim50\%$ of the total stellar mass budget of the proto-MW/LG at $z =6-9$. Including all the progenitors of these disrupted galaxies improves the normalization of the recovered SMFs/UVLFs by factors of $\sim2-3$ and reduces the halo-to-halo variation in the slope by $\sim20-40\%$. This enables robust constraints down to at least the resolution limit of the simulations, near $M_\star$ $\sim$ $10^{5}$ $M_\odot$ or $M_{\mathrm{UV}} \sim -10$ at $z \gtrsim 6$. We also show that `fossil record' reconstructions - which assume each present-day system des
Ponzi schemes, a form of scam, have been discovered in Ethereum smart contracts in recent years, causing massive financial losses. Existing detection methods primarily focus on rule-based approaches and machine learning techniques that utilize static information as features. However, these methods have significant limitations. Rule-based approaches rely on pre-defined rules with limited capabilities and domain knowledge dependency. Using static information like opcodes for machine learning fails to effectively characterize Ponzi contracts, resulting in poor reliability and interpretability. Moreover, relying on static information like transactions for machine learning requires a certain number of transactions to achieve detection, which limits the scalability of detection and hinders the identification of 0-day Ponzi schemes. In this paper, we propose PonziGuard, an efficient Ponzi scheme detection approach based on contract runtime behavior. Inspired by the observation that a contract's runtime behavior is more effective in disguising Ponzi contracts from the innocent contracts, PonziGuard establishes a comprehensive graph representation called contract runtime behavior graph (CRB
Recently, the first feature-rich NTFS implementation, NTFS3, has been upstreamed to Linux. Although ensuring the security of NTFS3 is essential for the future of Linux, it remains unclear, however, whether the most recent version of NTFS for Linux contains 0-day vulnerabilities. To this end, we implemented Papora, the first effective fuzzer for NTFS3. We have identified and reported 3 CVE-assigned 0-day vulnerabilities and 9 severe bugs in NTFS3. Furthermore, we have investigated the underlying causes as well as types of these vulnerabilities and bugs. We have conducted an empirical study on the identified bugs while the results of our study have offered practical insights regarding the security of NTFS3 in Linux.
Measurements of galaxy distributions at large cosmic distances capture clustering from the past. In this study, we use a cosmological model to translate these observations into the present-day galaxy distribution. Specifically, we reconstruct the 3D matter power spectrum at redshift $ z = 0 $ using Dark Energy Spectroscopic Instrument (DESI) Year 1 (DR1) galaxy clustering data and Cosmic Microwave Background (CMB) observations, assuming the $ Λ\text{CDM} $ model, and compare it to the result assuming the $ w_0w_a \text{CDM} $ model. Building on previous state-of-the-art methods, we apply Effective Field Theory (EFT) modelling of the galaxy power spectrum to account for small-scale effects in the 2-point statistics of galaxy data. The EFT approach offers a more robust methodology than traditional methods for modelling the galaxy power spectrum from galaxy clustering data, which can be used to test the consistency of the assumed cosmological model. By incorporating both CMB and galaxy clustering data across a range of redshifts, we can identify discrepancies between the datasets, which would indicate potential inaccuracies in the assumed expansion history. While previous studies have
Quantum spin ice (QSI) is an emblematic three-dimensional $U(1)$ quantum spin liquid (QSL) on the pyrochlore lattice that hosts gapless photon-like modes and spinon excitations. Despite its notable status and the current rise of strong material candidates Ce$_2$(Zr, Sn, Hf)$_2$O$_7$, there are still only a few analytical approaches to model the low-energy behavior of QSI. These analytical methods are essential to gain insight into the physical interpretation of measurements. We here introduce the self-consistent exclusive boson representation (SCEBR) to model emergent spinon excitations in QSI. By treating the presence of other emergent charges in an average way, the SCEBR extends the range of validity of the exclusive boson representation previously introduced by Hao, Day, and Gingras [Hao, Day, and Gingras, Physical Review B, 90, 214430 (2014)] to numerous cases of physical relevance. We extensively benchmark the approach and provide detailed analytical expressions for the spinon dispersion, the Bogoliubov transformation that diagonalizes the system, and the dynamical spin structure factor for 0- and $π$-flux QSI. Finite temperature properties are further investigated to highligh
LLMs have becoming increasingly powerful, both in their benign and malicious uses. With the increase in capabilities, researchers have been increasingly interested in their ability to exploit cybersecurity vulnerabilities. In particular, recent work has conducted preliminary studies on the ability of LLM agents to autonomously hack websites. However, these studies are limited to simple vulnerabilities. In this work, we show that LLM agents can autonomously exploit one-day vulnerabilities in real-world systems. To show this, we collected a dataset of 15 one-day vulnerabilities that include ones categorized as critical severity in the CVE description. When given the CVE description, GPT-4 is capable of exploiting 87% of these vulnerabilities compared to 0% for every other model we test (GPT-3.5, open-source LLMs) and open-source vulnerability scanners (ZAP and Metasploit). Fortunately, our GPT-4 agent requires the CVE description for high performance: without the description, GPT-4 can exploit only 7% of the vulnerabilities. Our findings raise questions around the widespread deployment of highly capable LLM agents.
We present the first X-ray polarization measurement of the neutron star low-mass X-ray binary and Z-source, GX 340$+$0, in the normal branch (NB) using a 200 ks observation with the Imaging X-ray Polarimetric Explorer (IXPE). This observation was performed in 2024 August. Along with IXPE, we also conducted simultaneous observations with NICER, AstroSat, Insight-HXMT, ATCA, and GMRT to investigate the broadband spectral and timing properties in the X-ray and radio wavelengths. During the campaign, the source traced a complete Z-track during the IXPE observation but spent most of the time in the NB. We measure X-ray polarization degree (PD) of $1.22\pm0.25\%$ in the 2-8 keV energy band with a polarization angle (PA) of $38\pm6^\circ$. The PD in the NB is observed to be weaker than in the horizontal branch (HB) but aligned in the same direction. The PD of the source exhibits a marginal increase with energy while the PA shows no energy dependence. The joint spectro-polarimetric modeling is consistent with the observed X-ray polarization originating from a single spectral component from the blackbody or the Comptonized emission while the disk emission does not contribute towards the X-r
Local gravitational instability (LGI) is considered crucial for regulating star formation and gas turbulence in galaxy discs, especially at high redshift. Instability criteria usually assume infinitesimally thin discs or rely on approximations to include the stabilising effect of the gas disc thickness. We test a new 3D instability criterion for rotating gas discs that are vertically stratified in an external potential. This criterion reads $Q_{\rm3D}<1$, where $Q_{\rm3D}$ is the 3D analogue of the Toomre parameter $Q$. The advantage of $Q_{\rm3D}$ is that it allows us to study LGI in and above the galaxy midplane in a rigorous and self-consistent way. We apply the criterion to a sample of 44 star-forming galaxies at $0\lesssim\mathrm{z}\lesssim5$ hosting rotating discs of cold gas. The sample is representative of galaxies on the main sequence at $\mathrm{z}\approx 0$ and includes massive star-forming and starburst galaxies at $1\lesssim\mathrm{z}\lesssim5$. For each galaxy, we first apply the Toomre criterion for infinitesimally thin discs, finding 10 unstable systems. We then obtain maps of $Q_{\rm 3D}$ from a 3D model of the gas disc derived in the combined potential of dark
The shape of the low-mass (faint) end of the galaxy stellar mass function (SMF) or ultraviolet luminosity function (UVLF) at z > 6 is an open question for understanding which galaxies primarily drove cosmic reionisation. Resolved photometry of Local Group low-mass galaxies allows us to reconstruct their star formation histories, stellar masses, and UV luminosities at early times, and this fossil record provides a powerful `near-far' technique for studying the reionisation-era SMF/UVLF, probing orders of magnitude lower in mass than direct HST/JWST observations. Using 882 low-mass (Mstar < 10^9 Msun) galaxies across 11 Milky Way- and Local Group-analogue environments from the FIRE-2 cosmological baryonic zoom-in simulations, we characterise their progenitors at z ~ 6 - 9, the mergers/disruption of those progenitors over time, and how well their present-day fossil record traces the high-redshift SMF. A present-day galaxy with Mstar ~ 10^5 Msun (10^9 Msun) had ~1 (~30) progenitors at z ~ 7, and its main progenitor comprised ~100% (~50%) of the total stellar mass of all its progenitors at z ~ 7. We show that although only ~ 15% of the early population of low-mass galaxies survive
We report a stable, low loss method for coupling light from silicon-on-insulator (SOI) photonic chips into optical fibers. The technique is realized using an on-chip tapered waveguide and a cleaved small core optical fiber. The on-chip taper is monolithic and does not require a patterned cladding, thus simplifying the chip fabrication process. The optical fiber segment is composed of a centimeter-long small core fiber (UHNA7) which is spliced to SMF-28 fiber with less than -0.1 dB loss. We observe an overall coupling loss of -0.64 dB with this design. The chip edge and fiber tip can be butt coupled without damaging the on-chip taper or fiber. Friction between the surfaces maintains alignment leading to an observation of +-0.1 dB coupling fluctuation during a ten-day continuous measurement without use of any adhesive. This technique minimizes the potential for generating Raman noise in the fiber, and has good stability compared to coupling strategies based on longer UHNA fibers or fragile lensed fibers. We also applied the edge coupler on a correlated photon pair source and observed a raw coincidence count rate of 1.21 million cps and raw heralding efficiency of 21.3%. We achieved a
Populations of stellar-mass black holes (BHs) in globular clusters (GCs) influence their dynamical evolution and have important implications on one of the main formation channels for gravitational wave sources. Inferring the size of these populations remains difficult, however. In this work, multimass models of 34 Milky Way GCs, first presented in Dickson et al., are used to explore the present-day BH populations. Direct constraints on both the total and visible mass components provided by several observables allow these models to accurately determine the distribution of the dark mass (including BHs) within clusters, as we demonstrate in a proof-of-concept fitting of the models to mock observations extracted from Monte Carlo cluster models. New constraints on the BH population retained to the present-day in each cluster are inferred from our models. We find that BH mass fractions ranging from 0 to 1 per cent of the total mass are typically required to explain the observations, except for Omega Cen, for which we infer a mass fraction above 5 per cent, in agreement with previous works. Relationships between the dark remnant populations and other cluster parameters are examined, demon