In this article we will discuss a few aspects of the spacetime description of matter and fields. In Section:1 we will discuss the completeness of real numbers in the context of an alternate definition of the straight line as a geometric continuum. According to this definition, points are not regarded as the basic constituents of a line segment and a line segment is considered to be a fundamental geometric object. This definition is in particular suitable to coordinatize different points on the straight line preserving the order properties of real numbers. Geometrically fundamental nature of line segments are required in physical theories like the string theory. We will discuss the cardinality of rational numbers in the later half of Section:1. We will first discuss what we do in an actual process of counting and define functions well-defined on the set of all positive integers. We will follow an alternate approach that depends on the Hausdorff topology of real numbers to demonstrate that the set of positive rationals can have a greater cardinality than the set of positive integers. This approach is more consistent with an actual act of counting used in statistical mechanics. This article indicates that the axiom of choice is a better technique to prove theorems that use second-countability. This is important for the metrization theorems and physics of spacetime. In Section:2 we will discuss an improved proof of the Poisson's equation. We will show that the self energy of a point charge can be zero in the potential approach to evaluate it. In Section:3 we will discuss a few aspects of the equivalence of the Schwarzschild coordinates and the Kruskal-Szekeres coordinates. In Section:4 we will make a few comments on general physics including the special theory of relativity and hydrodynamics.

We present the results of AGN--host-galaxy decomposition using JWST/NIRCam, HST/ACS, and HST/WFC3 imaging of the North Ecliptic Pole Time Domain Field (NEP-TDF). The light-profiles of 36 NIRCam-selected AGN candidates are modeled for measurement of their point sources, and point source-subtracted host-galaxy emission is used in SED modeling for star formation rate (SFR) estimation. Offsets from the canonical star-forming main sequence (SFMS) show that the host galaxies form two distinct groups distinguished by their star formation: a ``bridge'' between the moderate SFRs of radio sources and low SFRs of X-ray sources, and a cleanly-separated ``branch'' above $Δ\rm SFMS = -1$ whose SFR trends positively with AGN fraction. Branch galaxies include late-type galaxies with X-ray and radio detections and more dominant point sources that are most certainly AGN, while bridge galaxies have predominantly early-type morphologies with weaker point sources that may be due to compact stellar bulges. Both groups show evidence of recent transition between star formation and quiescence, but neither group shows preference for higher or lower stellar mass or redshift, suggesting that star formation in NIRCam-selected AGN-hosts is more strongly determined by AGN activity than by stellar mass.

We present a framework for generating lightcone simulations tailored to the analysis of Stage-IV cosmic shear data using Higher-Order Statistics (HOS). We revisit key design choices from previous simulation campaigns and re-optimize several internal parameters, benchmarking accuracy through changes in $χ^2$ of cosmic shear statistics under survey conditions mimicking 10 years of observations from the Legacy Survey of Space and Time (LSST). We find that discretizing the lightcone uniformly in scale factor yields higher accuracy than commonly adopted schemes such as uniform spacing in redshift or comoving distance. While $N_{\rm part} = 1024^3$ simulation particles (corresponding to a mass resolution of $m_{\rm part} = 2.08\times10^{10}M_\odot$) is sufficient to model two-point statistics up to $\ell = 5000$, we observed significant instabilities on our full suite of HOS as the number of mass shells used in the lightcone construction, $N_{\rm shells}$, is varied. In contrast, simulations with $N_{\rm part} = 2048^3$ particles ($m_{\rm part} = 2.60\times10^{9}M_\odot$) robustly reproduce all statistics considered. In this higher-resolution configuration, $N_{\rm shells}$ can be reduced to $\sim50$ with only minor deviations, no larger than $0.1-0.3σ$ relative to our highest-resolution case ($N_{\rm shells}\sim100$). This has been explicitly verified through a comparison between our fiducial lightcone production mode based on slicing particle snapshots and an exact lightcone mode where individual particle trajectories are solved for at runtime. We further show that the particle density per pixel can be downsampled by a significant amount for $z>1.5$, saving large computational resources with no impact on the resulting statistics. These results guide the design of upcoming simulation campaigns geared towards forward-modeling and emulation-based analyses of Stage-IV data.

Precision measurements of top-quark decays provide powerful probes of physics beyond the Standard Model (SM). While the impact of dimension-6 operators in the SM Effective Field Theory (SMEFT) has been extensively studied, the role of dimension-8 contributions remains largely unexplored, despite their potential importance as experimental precision improves. In this work, we present a combined analysis of dimension-6 and a representative subset of dimension-8 SMEFT effects using the W-boson helicity fractions in top-quark decays. We compute the leading-order contributions of these operators to the top-quark decay width and helicity fractions, and perform one-parameter and selected two-parameter $χ^{2}$ fits to the combined ATLAS and CMS measurements at a reference scale $Λ=1$~TeV. From the fit results, we find that the inclusion of dimension-8 contributions affects the allowed parameter space of several dimension-6 coefficients through non-trivial correlations and degeneracies. Since the leading dimension-8 contributions enter at the same order $\mathcal{O}(Λ^{-4})$ as the squared dimension-6 terms retained in our analysis, this highlights the importance of a consistent treatment of the EFT expansion when interpreting SMEFT constraints.

We investigate the impact of baryonic feedback on two-point and three-point correlation functions (2PCFs and 3PCFs hereafter, respectively) involving galaxy density fields (g) and weak lensing shear fields (G), from simulated photometric catalogs of galaxies. Specifically, we baryonify high-resolution simulation using a baryonic correction model (BCM) and explore the consequences down to sub-arcminute (arcmin) scales, varying two model parameters with the largest impact on our probes: $M_{\rm c}$, which governs the amount of gas expelled beyond the halo boundary, and $θ_{\rm ej}$, which encodes the maximal ejection radius relative to halo boundary. We create lensing maps and galaxy catalogs assuming survey properties of the upcoming Year-10 data for the Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST), and investigate the impact of baryonic feedback on the observed correlations, including the galaxy--galaxy--shear (ggG) and the galaxy--shear--shear (gGG) 3PCFs, which are measured, for the first time from simulations, with \textsc{TreeCorr}. Focusing on equilateral 3PCFs, we find that small scales are more heavily affected by baryonic effects than the corresponding 2PCFs, by up to 90 percent depending on the probe, redshift and BCM model. The galaxy--galaxy--galaxy (ggg) 3PCF is significantly affected at scales smaller than about 4 arcmin; a similar effect occurs at 10 arcmin for the ggG 3PCF, at 40 arcmin for the gGG 3PCF, and at about a degree for the shear--shear--shear (GGG) 3PCF. These four three-point statistics, which are collectively referred to as the $4\times3$PCFs, can be used at large scales to robustly constrain cosmological parameters. At smaller scales, their enhanced sensitivity to baryonic effects provides valuable leverage for constraining the BCM parameters and supplying informative priors. [Abridged]

Altermagnets are an emerging class of collinear antiferromagnets that exhibit unconventional spin-polarised electronic bands, potentially unlocking new functionalities that do not rely on spin-orbit coupling (SOC). Experimental signatures traditionally associated with spin polarisation, like X-ray magnetic circular dichroism (XMCD), are thus being used as a validation of altermagnetism. However, unlike altermagnetic spin-splitting, these responses require SOC and are not invariant under spin-space rotations. This brings into question the extent to which they can be considered direct signatures of altermagnetism. Here, we exploit the g-wave altermagnet $α$-Fe$_{2}$O$_{3}$ to demonstrate that XMCD is governed precisely by the spin-direction-induced symmetry breaking that altermagnetic spin groups are designed to ignore. Strikingly, the XMCD is highly anisotropic and is decoupled from the weak magnetic canting. We show that this anomalous XMCD can be described by on-site Faraday tensors capturing the locally uncompensated spin-orbital anisotropies - a scenario that can be applied to other altermagnets. Leveraging this, we reconstruct complete vectorial maps of nanoscale textures in $α$-Fe$_{2}$O$_{3}$ thin films, including domain walls and topological solitons, which are promising for building future spintronics and magnonics devices.

The crossword-like patterns of tiles in Scrabble form connected graphs of occupied sites on a square lattice. We find the most structureless description that reproduces means and covariances observed in real Scrabble games by adapting a maximum entropy approach to connected graphs. This pairwise model captures the data well, and predicts word-length statistics and geometric features of the Scrabble graphs correctly; in addition, the parameters of this model are interpretable and allow us to understand Scrabble playing strategies. Using this pairwise model, we calculate entropy differences and distinguishability of Scrabble graphs across languages, without having access to the letters on the tiles. Notably, we find that the entropy is predicted better by strategic gameplay -- such as word length on the board -- than lexicon size. Finally, we find that we can use the pairwise model to correctly assign Scrabble graphs to languages, avoiding explicit feature selection and at relatively low computational cost.

The cascaded variational quantum eigensolver (CVQE) circumvents the need for iterative communication between the quantum and classical processing units that is necessary in the conventional VQE algorithm. While CVQE offers complete freedom to choose the guiding state as input, not all guiding states suffice for solution accuracy, as well as resource efficiency. Our work presents a process based on trapezoidal-state preparation for selecting guiding states that yield accurate many-electron ground-state solutions with minimal resource consumption. By analyzing the state probability distributions at different stages of the CVQE calculations, we determine the optimal guiding-state parameters for given resource constraints. We demonstrate the process by comparing electronic energies along the minimal-energy path for a prototypical bimolecular reaction, $\mathrm{H}_2 + \mathrm{H}_2^+ \rightarrow \mathrm{H}_3^+ + \mathrm{H}$, using Noisy Intermediate-Scale Quantum (NISQ) computing.

We have developed Density Functional Tight Binding (DFTB) models for cerium that accurately predict both the electronic band structure and energetic ordering of different allotropes. We show that global optimization of the electronic confining potentials minimize the errors in the predicted Kohn-Sham energies while facilitating determination of a many-body repulsive energy. Our results illustrate the ability of DFTB to accurately reproduce complex f-electron interactions for multiple phases while leveraging minimal Density Functional Theory data.

Dislocation core chemistry in oxides critically influences mechanical behavior and functionality; yet the evolution of core chemistry during the dislocation motion in them has not been directly observed. Here, using SrTiO3 as a model material, we combine aberration-corrected scanning transmission electron microscopy and electron energy-loss spectroscopy with atomic-level molecular dynamics (MD) simulations to correlate the <110>{1-10} dislocation core structure, oxygen vacancy density, charge state, and mobility with each other. We find that the mechanically induced dislocation loops exhibit dissociated cores, whose oxygen vacancy density depends on the gliding distance: short loops are Ti-reduced and oxygen-deficient at the edge dislocation core, whereas longer loops remain close to stoichiometry in both the edge and screw components. MD simulations reveal that kink-assisted edge dislocation glide in SrTiO3 leaves oxygen-deficient trails behind, modulating the oxygen content inside the edge core. These results demonstrate that oxygen-vacancy evolution at the dislocation core intrinsically couples with plasticity in ionic crystals, suggesting a mechanism for oxygen vacancy-dependent dislocation mobility in plastically deformed oxides.

Complex contagions describe systems where the probability or rate of contagious transmission is a nonlinear function of the exposure to contagious agents. These models were first studied theoretically but have since been used to capture effects such as nonconformism, social reinforcement or peer pressure in empirical data. However, recent studies have shown that local correlations (e.g., group structure or temporal burstiness) and heterogeneity (e.g., diversity of parameters or covariates) can give the illusion of nonlinear effects even when the dynamics is actually linear. We briefly review these studies to inform a new model and explanation for these effective models of complex contagions. We find global threshold dynamics and superlinear complex contagions even in populations where agents are distributed across social groups described solely by linear or even sublinear contagions. This effect can be understood as a manifestation of Simpson's paradox. Incidence data from heterogeneous groups can look superlinear once averaged over all groups, since the sampling of groups represented at high incidence is biased towards those with stronger local transmission. We then define what we call a Simpson's contagion: a contagion process that looks superlinear when observed over an entire population, but is mechanistically linear or even sublinear in all of its subgroups. By exploring these Simpson's contagions over mathematical case studies, our work contributes to the growing body of literature on the ubiquity of threshold and complex contagions as effective models, and our results stress the pitfall of model selection that ignores correlations and heterogeneity in populations.

Characterizing quantum many-body phase structure is a major goal for quantum simulation. Here, we employ an unsupervised learning approach based on diffusion maps to learn phase transitions in bosonic lattice systems described by Bose-Hubbard type models, which can be realized in ultracold atoms and related quantum simulation platforms. We demonstrate that this approach identifies phase structure across distinct settings without prior knowledge of order parameters or handcrafted observables, including ground-state transitions involving symmetry-protected topological phases and nonequilibrium regimes distinguishing ergodic and many-body localized behavior. Our results indicate that the approach has the potential for direct application to experimentally accessible measurement data for learning quantum phases in current quantum simulators.

We investigate the physical origin and location of high-energy neutrino emission in active galactic nuclei (AGN) using the blazar GB6 J1542+6129 as a case study, testing whether neutrinos are produced in compact regions near the black hole or in parsec-scale jets. This question is central to understanding the conditions under which hadronic processes become efficient in AGN environments. We perform a multimessenger analysis combining ~17 years of Fermi-LAT gamma-ray data, including a 5% adaptively binned light curve and Bayesian block decomposition, with ~14 years of VLBI/MOJAVE observations to derive the Doppler factor evolution of the radio core. These are compared to the temporal properties of a suspected IceCube neutrino flare with a duration of $147^{+110}_{-25}$ days. We find that the suspected neutrino flare precedes both a gamma-ray flare and a pronounced increase in the VLBI core Doppler factor by ~1 year. This delay is consistent with the propagation time of a disturbance from the central engine to the 15GHz radio core. The duration of the post-flare gamma-ray activity is similar to that of the neutrino flare. The broadband gamma-ray spectral energy distributions remain consistent in shape across the full, flare, and post-flare intervals, indicating stable particle acceleration conditions. The temporal ordering favors neutrino production upstream of the VLBI core. GB6 J1542+6129 provides evidence for spatially separated neutrino and gamma-ray/radio emission regions in AGN. The observations are consistent with a disturbance-driven, multi-zone scenario in which neutrinos are produced in a compact, photon-rich region near the central engine, while the same disturbance later enhances Doppler-boosted leptonic emission at the parsec-scale VLBI core. These results demonstrate the power of multimessenger observations in constraining the origin of astrophysical neutrinos.

Let ${\mathcal H}_1$ be a finite dimensional complex Hilbert space. Let $ψ\mapsto Z(ψ)$ be a canonical anti-commutation relations (CAR) field over ${\mathcal H}_1$ acting irreducibly on a Hilbert space ${\mathord{\mathscr K}}$. The $*$-algebra ${\mathscr A}_{{\mathcal H}_1}$ generated by the $Z(ψ)$, $ψ\in {\mathcal H}_1$, is simply all operators on ${\mathscr K}$. However, the CAR field endows ${\mathscr A}_{{\mathcal H}_1}$ with additional structure, and we are concerned with quantum operations whose acting in harmony with this structure. In particular, there is a gauge automorphism group generated by ``second quantizing'' $ψ\mapsto e^{it}ψ$. The fixed point algebra of the gauge group, ${\mathscr G}_{{\mathcal H}_1}$, is a sub-algebra of ${\mathscr A}_{{\mathcal H}_1}$ studied by Araki and Wyss. It contains the density matrices of an important class of states, the gauge invariant Gaussian states, ${\mathfrak S}_{GIG}$. Our focus is on semigroups $\{e^{t{\mathscr L}}\}_{t\geq 0}$ of quantum operations on ${\mathscr A}_{{\mathcal H}_1}$ that map ${\mathfrak S}_{GIG}$ into itself. Each $e^{t{\mathscr L}}$ is one-to-one, and our first main result is a structure theorem forsuch quantum operations on ${\mathscr G}_{{\mathcal H}_1}$ that map ${\mathfrak S}_{GIG}$ into itself. We apply this to study semigroups of quantum operations on ${\mathscr G}_{{\mathcal H}_1}$ that map ${\mathfrak S}_{GIG}$ into itself. Our second main result is a structure theorem showing that they are parameterized by pairs $(G,A)$ where $G$ is a contraction semigroup generator on ${\mathcal H}_1$, and $0 \leq A \leq -G -G^*$. We then show that each of these semigroups has a natural extension to the full CAR algebra ${\mathscr A}_{{\mathcal H}_1}$. Further results are obtained under further assumptions on the pair $(G,A)$.

We study black hole formation and evaporation in a four-dimensional semiclassical model that preserves diffeomorphism invariance and reproduces the one-loop trace anomaly. Solving the quantum-corrected Einstein equations for the collapse of a spherically symmetric null shell, we follow the formation and evaporation of a black hole with back-reaction included. The semiclassical solutions develop a spacelike thunderbolt singularity that emerges after the apparent horizon has receded and extends far from the black hole where the semiclassical curvature is a priori expected to be parametrically small. This behavior arises from a nonlinear instability of the higher-derivative semiclassical equations and is generic in models with anomaly-induced quantum corrections. The thunderbolt signals a breakdown of semiclassical effective field theory over macroscopic distances and undermines the standard formulation of the black hole information paradox.

Discrete-time quantum walks provide a natural framework for quantum transport on complex networks. On regular structures, coin-walker entanglement has been widely used to characterize quantum transport and to support quantum algorithmic protocols. However, this notion relies on a fixed Hilbert space factorization separating coin and position and is therefore not directly applicable to more complex, irregular structures. Here we introduce an entanglement measure for general networks based on a bipartition that assigns each node two roles, acting as both a source and a target. The resulting bipartition defines the source-target entanglement, a measure for general networks, motivated by coin-walker entanglement. We show that the connectivity of the network imposes an upper bound on this entanglement and identify graph matchings as the underlying structure governing entanglement generation. We further illustrate that in random graphs improving graph connectivity reduces the attainable entanglement, establishing a structure-dependent constraint on quantum correlations.

In many-body quantum systems, unitary dynamics generically delocalize locally encoded information, causing single-site metrological sensitivity to vanish. We analytically demonstrate that a topological phase can prevent this dispersal. In the open Kitaev chain, a Majorana zero mode fixes the boundary quantum Fisher information (QFI) at a nonzero plateau that persists for times exponentially long in system size. We derive exact analytical expressions for the local QFI and identify the mechanism as the spatial separation of the two Majorana quadratures to opposite ends of the chain. This separation produces a boundary encoding-axis asymmetry that distinguishes topological boundary memory from a generic localized subgap signal. We show numerically that the asymmetry is robust to moderate quenched on-site disorder, while the boundary plateau remains visible under parity-preserving interactions in finite-size real-time simulations. The protocol requires only product-state initialization, Hamiltonian evolution, and single-site readout.

Transition region (TR) loops are arcade-like features in the solar transition region, with temperatures roughly between $2\times10^4$ K and $6\times10^5$ K. They are a fundamental building block of TR, which are results of the coupling between the magnetic field and the TR plasma. Their dynamics is closely related to the transport of energy and mass through the TR. Studies on this class of loops since the launch of the Interface Region Imaging Spectrograph (IRIS) have revealed that they are distinct from coronal loops. Observations have revealed that they are associated with many small-scale dynamic phenomena in the TR, from which one can infer the physics behind the energy and mass transfer in a magnetically confined environment at TR temperature. This review summarises the observational results of TR loops, showing their morphology, dynamics, plasma parameters, their relationship with flux emergence, their heating properties, and their implication in the heating of the solar atmosphere. This class of magnetic loops is much less well understood than their coronal counterparts. This review also concludes with several critical questions that need to be answered in the coming era with more advanced observational techniques and more precise and realistic simulations.

Supermassive black holes (SMBH, $M_{\rm{BH}} > 10^8 M_\odot$) powering luminous quasars already exist one billion years after the Big Bang, yet their connection to their star-forming host galaxies, their relation to the general galaxy population and their contribution to Reionisation remains deeply enigmatic. JWST is finding numerous Active Galactic Nuclei (AGN) in high-redshift galaxies with black hole masses that appear to be over-massive compared to their host's stellar mass, but rarely as massive as those found in luminous quasars. Here we report JWST/NIRSpec observations revealing overmassive SMBH in two ultra-luminous Lyman-$α$ emitters at $z\sim6.6$ that exhibit rare double-peaked Lyman-alpha profiles. The broad Balmer lines indicate black hole masses $M_{\rm{BH}}\simeq 2\times10^8 M_\odot$, matching that found in faint $z\sim 6-7$ quasars, and very high BH-to-stellar-mass ratio ($\sim 0.1-0.2$) that exceed the local relation by a factor $\sim$400-800. Stellar population modelling favours young ages ($<50$ Myr), inconsistent with the sustained average Eddington-rate accretion required to reach the observed BH masses by $z=6.6$. The double-peak Lyman-$α$ profiles require a large ionised bubble and high photoionisation rate that is consistent with the ionising output of quasars powered by black holes of similar mass, thus constraining the cessation of the last quasar episode to $<1$ Myr. We interpret both systems as post-quasar galaxies in which AGN feedback has delayed stellar mass assembly, and propose that episodic quasar activity partially explains the unexpected prevalence of large ionised bubbles deep into the Epoch of Reionisation.

Information sharing between individuals is crucial to improve performance in collective tasks. However, in a competitive world, individuals may be reluctant to share information with the others, and it is still unclear how the presence of strategic behaviors affects the collective performance of a group. In this study, we introduce an evolutionary game modeling the dynamics of individual behaviors in a collective estimation task. The individuals are organized in a network and have to guess the distribution of ball colors in a box. Each of them samples a given number of balls and can strategically decide whether to share or not this information with its neighbors. We develop a framework that allows to investigate analytically how the collective performance depends on the network structure. We find that the optimal network results from a trade-off between the sharing rate and the way the information is integrated in the network. We further reveal that there exists an intermediate average degree for each type of network maximizing the collective performance. In addition to the uniform case, we consider the case of non-homogeneous allocations of the number of individual samples, showing that the largest collective performance is obtained when the number of ball extracted by an individual is inversely proportional to its degree.

The Faddeev-Hopf model [1] supporting Hopfions was shown to emerge in the low-energy limit of four-dimensional scalar quantum electrodynamics (QED) with two charged scalar fields [2, 3]. Faddeev and Noemi conjectured that the Hopfions and Hopf-like solitons -- vortons -- can be based on a twisted toroidal structure inherent to QED [4-6]. This conjecture was discussed in detail in [2] in the approximation of negligibly small extrinsic curvature. Qualitative and semi-quantitative arguments were used to demonstrate the validity of the Faddeev-Noemi hypothesis. Here we further enhance the proof by applying a numerical analysis which confirms that large-size Hopf-like solitons exist as local energy minima in the full QED theory (in the Faddeev-Skyrme model they become topological solitons representing the global minima in the given topological sector).

We present a charged-current quasielastic neutrino-nucleus scattering model based on an unfactorized representation of the spectral function, employing relativistic momentum distributions for bound nucleons and the relativistic distorted-wave impulse approximation with an energy-dependent relativistic potential to describe the scattered nucleon. The model incorporates two-body meson-exchange currents contributing to one-particle-one-hole final states and tests several axial form factor parametrizations, including recent LQCD and MINERvA fits. It is implemented in the NEUT event generator and benchmarked against T2K and MINERvA $ν_μ$-$^{12}$C CC0$π$ measurements. We find that two-body meson-exchange currents lead to a sizeable increase of the total cross section, arising from an enhancement of the transverse response, which is the dominant component in charged-current neutrino scattering. On the other hand, recent fits of the axial form factor predict larger values than the standard dipole form, yielding a systematic enhancement of the cross section. The LQCD+MINERvA parametrization tends to overestimate the data, while the MINERvA-only fit provides a more moderate increase. Overall, no single configuration consistently provides the best agreement with the different datasets.

We report and analyse the classification performance of an experimental hybrid spatio-temporal photonic reservoir computer based upon a free-space VCSEL array. We demonstrate experimentally the enhancement of spatial-only reservoir operation, featuring the diffractive coupling of lasers in an external cavity, by exploiting up to 88 virtual nodes with time multiplexing. We analyse the dependance of performance on the spatial and virtual node number, and achieve an improvement for both spatial- and temporal-only reservoirs with a reduced test error of 0.026 in a classification task. Further, given the high bandwidth of the non-linear laser transformation, we demonstrate the expansion of a 12 spatial node network to a 968 node network, operating at an input time of 17.6ns, maintaining high processing speed and improving network scalability and performance.

Networked systems operating under intermittent adverse conditions and long memory can remain stable on average while exhibiting rare but extreme trajectory-level excursions. We study linear regime-switching network dynamics with Volterra-type memory, formulated through a finite-dimensional lifted ordinary differential equation embedding. Despite finite-horizon annealed boundedness, we show that quenched amplification emerges generically from the interaction of regime persistence, memory accumulation, and non-normal lifted operator geometry. A lower bound on burst-size distributions reveals power-law tails whose exponent is determined by the ratio between unfavorable dwell-time rates and an operator-defined instantaneous growth parameter. This parameter is computable online via the Euclidean logarithmic norm of the lifted operator, yielding a practical early-warning indicator. Building on this structure, we introduce a dynamic data-driven intervention strategy that enforces contraction on demand along rare amplification channels, thereby shaping or truncating tail risk without altering exogenous regime statistics or typical system behavior. The results provide a geometrically grounded and operationally actionable framework for understanding and mitigating extreme events in memory-driven regime-switching systems.

Quantum-gravity-induced entanglement of masses (QGEM) provides a phase-sensitive probe of extra-dimensional corrections to the Newtonian potential at submillimeter separations. We compare three representative Kaluza-Klein spectral scenarios: the Randall-Sundrum II (RSII) and Arkani-Hamed-Dimopoulos-Dvali (ADD) models, and the case of a gapped continuum modeled by a Pöschl-Teller potential. We evaluate the entangling phase, concurrence, and normalized phase-response profiles over $d=40$-$80\,μ\mathrm{m}$ using representative benchmark parameters guided by current short-range gravity tests. In this range, the signal exhibits a stable hierarchy: ADD $>$ gapped $>$ RSII. For conservative experimental parameters, the ADD signal surpasses the nominal entanglement threshold at smaller separations, whereas the gapped benchmark is resolvable only at the lower end of the window, and RSII remains below resolution. In a more optimistic near-term scenario, all three spectral signatures comfortably exceed the threshold. We further show that normalized distance scans of the phase response clearly separate the RSII benchmark from the ADD and gapped cases, whereas ADD and the gapped continuum remain nearly indistinguishable in normalized profile. QGEM phase observables therefore provide a complementary discriminator of Kaluza-Klein spectral structure at submillimeter scales.

We present a comprehensive theoretical study of the masses of possible baryonic and mesonic configurations containing a single top quark. Our analysis includes the baryons $Λ_t$, $Ξ_t$, $Σ_t$, $Ξ'_t$, $Ω_t$, $Ω_{tcc}$, and $Ω_{tbb}$, together with the pseudoscalar and vector mesons $T_{t\bar n}^{\mathrm{Ps}}$, $T_{t\bar n}^{\mathrm{V}}$, $T_{t\bar s}^{\mathrm{Ps}}$, $T_{t\bar s}^{\mathrm{V}}$, $T_{t\bar c}^{\mathrm{Ps}}$, $T_{t\bar c}^{\mathrm{V}}$, $T_{t\bar b}^{\mathrm{Ps}}$, and $T_{t\bar b}^{\mathrm{V}}$. Motivated in part by recent experimental indications of a pseudoscalar enhancement near the $t\bar t$ threshold reported by the CMS and ATLAS collaborations, this study is carried out within the framework of two-point QCD sum rules to determine the corresponding ground-state masses by including perturbative contributions and nonperturbative condensates up to dimension eight. For several channels, including the $Λ_t$, $Ξ_t$, $Σ_t$, $T_{t\bar b}^{\mathrm{Ps}}$, and $T_{t\bar b}^{\mathrm{V}}$ states, the extracted central masses lie slightly below the corresponding sums of constituent quark masses, which may indicate nontrivial binding dynamics or near-threshold multiquark configurations within the uncertainties of the method. Moreover, when the full theoretical uncertainties are taken into account in a conservative manner, a larger subset of the investigated states exhibits a consistent tendency toward weak binding behavior, suggesting that the possibility of loosely bound configurations cannot be excluded for most of the considered baryonic and mesonic channels. These results provide useful first-principles theoretical benchmarks for possible top-containing hadronic systems, which may support future searches at the LHC, along with sensitivity analyses for next-generation facilities such as the FCC.

Quantum machine learning is a promising field for efficiently learning features of a dataset to perform a specified task, such as classification. Interval bound propagation (IBP) is a popular certified training method in classical machine learning, where the lower and upper bounds are tracked throughout the model. These bounds are used during training to ensure that the model is certified to predict the correct label even under adversarial perturbations. While IBP is successful in classical domain, there are limited certified training efforts in quantum domain. In this paper, we present quantum interval bound propagation (QIBP) to establish a certified training routine for quantum machine learning, certifying the accuracy of models under adversarial perturbations. We implement QIBP using both interval and affine arithmetic to explore the tradeoffs between the two implementations in terms of accuracy and other design considerations. Extensive evaluation demonstrates that the resulting certified trained models have robust decision boundaries, guaranteed to predict the correct class for the samples within the trained adversarial robustness bounds.

Reliable control in motor imagery brain-computer interfaces (MI-BCIs) requires the precise decoding of user-specific neural rhythms, which vary significantly across individuals. The Common Spatial Pattern (CSP) algorithm is a cornerstone of MI-BCI decoding, yet its performance depends strongly on the spectral range of the input EEG data. Although Filter Bank CSP (FBCSP) extends this as a data-driven decoding framework, its frequency sub-bands are predefined rather than selected using subject-specific physiological criteria. This paper presents a proof-of-concept study of static functional connectivity (FC)-guided band selection for MI-BCI, demonstrated using a conventional FBCSP-based pipeline. The proposed method identifies the most discriminative spectral bands by calculating phase-based connectivity across four sensorimotor channels using wPLI, PLV, and PLI. Nine bands in a 4-40 Hz filter bank are ranked by the effect size of their hemispheric coupling differences and pruned to the top K bands for feature extraction and classification via FBCSP and a Support Vector Regressor. This framework was tested for K values ranging from 1 to 8 across the BCI Competition IV-2a (n = 9) and OpenBMI (n = 54) datasets. Performance was benchmarked against standard nine-band FBCSP and random ablation to determine the minimum number of bands (K*) required to maintain accuracy within a 2% baseline equivalence zone. Results show FC-guided selection can outperform random ablation and achieve near-baseline performance while reducing required CSP fits by 22.2% to 77.8%. PLV enables the most aggressive dimensionality reduction by prioritizing the μ and low-\b{eta} ranges, while wPLI demonstrates superior inter-session robustness by mitigating volume conduction. These findings establish FC-guided selection as a principled and interpretable alternative to heuristic filter bank designs.

The Traveling Salesman Problem (TSP) is a prototypical combinatorial optimization problem, but its quantum implementation is limited by the O(n^2)-qubit overhead of standard one-hot encodings. Here, we propose a resource-efficient variational quantum framework based on compact binary-register encoding, a permutation-preserving problem-inspired ansatz, and a complementary divide-and-conquer execution strategy. The compact encoding reduces the data-qubit requirement to O(n log n), while the divide-and-conquer formulation lowers the number of qubits required in each local hardware execution to the size of the largest subsystem. Numerical simulations on TSP instances with 4, 5, and 6 cities achieve best average success rates of 100%, 100%, and 95.5%, respectively. A local two-qubit implementation of the divide-and-conquer approximation is further evaluated for a 5-city TSP instance on SpinQ Gemini Pro and SpinQ Triangulum II NMR quantum computers. Taken together, the results indicate how compact encoding and divide-and-conquer execution with classical post-processing can be used to study small combinatorial optimization instances on resource-constrained quantum hardware.

Quintessential inflation models provide a framework that simultaneously describes inflation and dynamical dark energy, the latter of which has recently received growing support from DESI observations. A distinctive feature of these models is the kination phase after inflation, which enhances primordial gravitational waves at high frequencies. In this work, we study a class of alpha-attractor quintessential inflation models using a fully numerical approach that follows the scalar-field evolution from inflation to the dark-energy-dominated era, allowing us to compute with high precision both the dynamics of dark energy and the primordial gravitational wave spectrum. Using the latest observational data, including DESI and ACT, we constrain the model parameters and show that the model becomes disfavored once constraints from the gravitational-wave contribution to the effective number of relativistic degrees of freedom, Δ Neff, are included. This is because the model predicts a scalar spectral index ns that becomes too small to remain consistent with observations when the gravitational-wave abundance is constrained to stay below the Δ Neff bound. Finally, we present the resulting primordial gravitational wave power spectrum computed using our constrained parameter values, which highlights prospects for detection by future CMB B-mode experiments at low frequencies and by gravitational-wave interferometer experiments at high frequencies.