The phase structure of the BCS-BEC crossover for neutron-proton superfluid in asymmetric nuclear matter is systematically investigated, with particular focus on the roles of the angle-dependent gap (ADG) and the Fulde-Ferrell-Larkin-Ovchinnikov (FFLO) states. Phase diagrams in the T-alpha, alpha-rho, and T-rho planes are constructed using both angle-averaged and angle-dependent gap treatments, enabling a unified analysis of the interplay between the FFLO pairing, ADG, and normal-superfluid phase separation (PS). The results confirm that the crossover is primarily density-driven. In the weak-coupling BCS regime, isospin asymmetry suppresses the stability of the homogeneous superfluid phase and drives the system toward PS, while the FFLO and ADG mechanisms partially alleviate this suppression. Although the ADG itself does not extend the asymmetry window for superfluidity, in combination with the FFLO state it enlarges the asymmetry range over which superfluidity survives and significantly reduces PS. At high density, these combined effects can nearly eliminate PS. However, as density decreases, ADG-induced suppression of PS is progressively weakened, due to both the reduced destructive effect of isospin asymmetry and the decreasing D-wave fraction in the 3SD1 channel. In general, the system evolves smoothly from a D-wave-dominated superfluid at high density to an S-wave superfluid at low density, with a corresponding weakening of ADG effects. Furthermore, the ADG lifts the orientational degeneracy of the FFLO state, resulting in two distinct FFLO-ADG phases separated by a first-order transition. In contrast, in the BEC regime, the FFLO and ADG states vanish, while the PS persists, leading to an inhomogeneous mixed phase at low temperatures and large asymmetries, where the superfluid component forms a BEC of deuterons.

We provide a systematic framework to investigate the magnetoplasmons of multilayer two-dimensional electron systems by using the Kac--Murdock--Szegő (KMS) Toeplitz matrix to consider interlayer Coulomb interactions. In the absence of interlayer tunneling, we show that the single-layer magnetoplasmon branch splits into $N$ collective modes -- one in-phase mode and $N-1$ out-of-phase modes -- and derive their asymptotic behaviors in the long-wavelength limit, as well as in the limit of large layer separation and strong magnetic fields. When interlayer tunneling is present, we clarify the magnetoplasmon dispersion, both qualitatively and quantitatively, by identifying the magnetoplasmon mode associated with each interband transition, as well as tunneling magnetoplasmons arising from interband transitions with the same Landau level index. Our study presents the hybridization between the modes governed by underlying symmetries, along with an enhanced tunneling magnetoplasmon gap exceeding the associated interband gap. The KMS-based analytic formalism thus provides a comprehensive physical understanding of magnetoplasmons in multilayer structures.

This article introduces a metamodel for the Business Model Canvas (BMC) using the Unified Modelling Language (UML), together with a dedicated Domain-Specific Modelling Language (DSML) tool. Although the BMC is widely adopted by both practitioners and scholars, significant challenges remain in formally modelling business models, particularly with regard to explicit specification of inter-component relationships, while preserving the simplicity that characterises the BMC. Addressing this tension between modelling rigour and practical relevance, this research adopts a Design Science Research approach to formally specify relationships among BMC components and to strengthen their theoretical grounding through an adaptation of the V 4 framework. The proposed metamodel consolidates BMC relationships into three core types: supports, determines, and affects, providing explicit semantics while remaining accessible to end users through graphical tooling. The findings highlight that formally specifying relationships significantly improves the interpretability and consistency of BMC representations. The proposed metamodel and tool offer a rigorous yet usable foundation for developing DSML-based BMC tools and for enabling systematic integration of the BMC into widely used software and enterprise modelling environments, thereby bridging business modelling and enterprise architecture practices for both academics and practitioners.

This paper investigates a multiple-input multipleoutput (MIMO) visible light communication (VLC) wiretap channel consisting of a transmitter, a legitimate receiver, and an eavesdropper. The optical input is subject to both peakand average-intensity constraints. By applying the generalized entropy-power inequality to truncated exponential inputs, we derive a novel closed-form expression for the achievable secrecy rate for general MIMO VLC configurations. To enhance transmission confidentiality, a fully-connected beamforming scheme is proposed, along with a low-complexity sub-connected alternative. Although the resulting beamforming design problems are nonconvex, they are efficiently addressed by transforming them into a sequence of convex subproblems solvable via the successive convex approximation framework. Numerical results demonstrate that the proposed schemes achieve significant secrecy performance improvements compared with the benchmark scheme.

For any type of fundamental groupoid scheme, we construct an algebraic cohomology theory for varieties with coefficients in the base field. This is a minor variant of étale cohomology, involving neither de Rham complexes nor hypercohomology. The main idea is to delegate the role of étale morphisms to fundamental groupoids, thereby bypassing the Grothendieck topology. To validate this theory, we prove a comparison theorem between the algebraically defined cohomology using the pro-algebraic fundamental groupoid over $\mathbb{C}$ and singular cohomology. Furthermore, our construction naturally extends to other types of fundamental groupoids, providing a uniform foundation for various cohomology theories.

In this whitepaper, we outline how recent technological advances and ongoing developments open qualitatively new science opportunities in cosmology, fundamental physics, and quantum astrophysics. First, intensity interferometry can contribute to one of the most foundational observables in cosmology: the expansion rate of the Universe. Its angular resolution allows it to resolve the angular extent of extragalactic objects such as supernovae or quasars; combined with a physical scale local to the source, this yields an angular diameter distance and hence a 'Hubble diagram'. Second, the nature of dark matter can be probed via the astrometric lensing signatures of tiny dark matter halos. Third, intensity interferometry gives direct access to second-order coherence properties of astrophysical emission, opening a window onto genuinely quantum aspects of astrophysical light.

Federated Learning has been popularized in recent years for applications involving personal or sensitive data, as it allows the collaborative training of machine learning models through local updates at the data-owners' premises, which does not require the sharing of the data itself. Considering the risk of leakage or misuse by any of the data-owners, many works attempt to protect their copyright, or even trace the origin of a potential leak through unique watermarks identifying each participant's model copy. Realistic accusation scenarios impose a black-box setting, where watermarks are typically embedded as a set of sample-label pairs. The threat of collusion, however, where multiple bad actors conspire together to produce an untraceable model, has been rarely addressed, and previous works have been limited to shallow networks and near-linearly separable main tasks. To the best of our knowledge, this work is the first to present a general collusion-resistant embedding method for black-box traitor tracing in Federated Learning: BlackCATT, which introduces a novel collusion-aware embedding loss term and, instead of using a fixed trigger set, iteratively optimizes the triggers to aid convergence and traitor tracing performance. Experimental results confirm the efficacy of the proposed scheme across different architectures and datasets. Furthermore, for models that would otherwise suffer from update incompatibility on the main task after learning different watermarks (e.g., architectures including batch normalization layers), our proposed BlackCATT+FR incorporates functional regularization through a set of auxiliary examples at the aggregator, promoting a shared feature space among model copies without compromising traitor tracing performance.

We theoretically investigate the collisions between ultracold polar molecules in the presence of two lasers ensuring a Raman resonant transition on individual molecules to suppress photon scattering, taking the example of bosonic $^{23}$Na$^{39}$K molecules. By varying laser detunings and intensities, we enable a repulsive long-range interaction potential between molecules. After solving a set of coupled Schrödinger equations with the Hamiltonian written in the basis of laser-dressed states of the molecule pair at infinite distance, we identify quasi-resonant conditions under which elastic collisions are favored over inelastic and reactive ones, by a factor of about 2, thus demonstrating a promising pathway for efficient two-photon optical shielding of ultracold molecular collisions. The results are analyzed in terms of scattering length of the colliding laser-dressed molecules, which exhibit prominent resonances assigned to the interaction of the entrance channel with other specific channels, consistent with the existence of a quasi-bound level of the long-range molecular pair induced by the lasers.

Fluorine-doped tin oxide (FTO) is a key transparent conductive oxide for photovoltaic and optoelectronic devices, yet its high reflectance limits light-trapping efficiency. This work demonstrates a simple DC plasma sputtering approach to deposit carbonaceous Al2O3 microdots on FTO under controlled Ar, O2, and Ar-O2 atmospheres. For plasma discharge in the normal mode, with plasma density 10^9 cm^-3 and temperature of 2 eV, Volmer-Weber growth produced discrete microdots whose size and distribution were tuned by gas composition: dense, uniform dots in Ar (approximately 0.89 um radius), agglomerated structures in O2, and intermediate morphologies in mixed atmospheres. Structural analysis confirmed Al2O3 formation with carbon incorporation, while SEM revealed morphology-driven optical behavior. UV-Vis measurements showed that Ar-O2 coatings achieved the lowest reflectance across the visible range, outperforming bare FTO and other conditions. These findings establish a clear link between sputtering parameters, surface morphology, and optical performance, offering a scalable route to anti-reflective, light-trapping coatings for next-generation solar cells and optoelectronic devices.

Controlling how an open photonic system exchanges energy with its environment-and in particular how it radiates into the far field-is a cornerstone of non-Hermitian wave physics and a key enabler for directional photonic functionalities. Here, we propose a new route to robust unidirectional emission based on the non-Hermitian hybridization of resonances localized in spatially separated layers of a hetero-bilayer photonic crystal. By tailoring the interlayer coupling, we engineer hybrid photonc bands that exhibit strong unidirectional radiation across a broad spectral and momentum range while maintaining theoretically high quality factors. This asymmetric emission is organized by a topological vortex in a pseudo-polarization field defined from the front/back intensity imbalance, which endows the directionality with robustness against perturbations. We further show that, by tuning the surrounding refractive index, this singularity can be displaced in parameter space, enabling reversible switching of the emission direction and a reconfigurable far-field response. This framework opens perspectives for topological photonic sensing and for directional and switchable light sources, including unidirectional lasing supported by high-quality-factor modes.

We study the spectral efficiency (SE) of a ratesplitting multiple access (RSMA) enabled multi-clustered cell-free (CF) massive multiple-input multiple-output (mMIMO) system. The access points (APs) in each cluster serve mobile user equipments (UEs) by employing RSMA. The UEs employ successive interference cancellation to decode their data. This work emphasizes the role of downlink (DL) pilots in realizing RSMA benefits in practical CF systems with spatially-correlated Rician channels which observe random phase shifts, pilot contamination, and channel aging due to UE mobility. We numerically show that DL pilots are required for RSMA in user-centric CF mMIMO systems with channel aging to outperform spatial division multiple access. We show that the degraded channel quality due to higher UE velocity and longer resource block lengths significantly reduces the RSMA SE. Increasing the number of clusters can compensate for the SE loss.

Generative recommendation (GenRec) models typically model user behavior via full attention, but scaling to lifelong sequences is hindered by prohibitive computational costs and noise accumulation from stochastic interactions. To address these challenges, we introduce Rec2PM, a framework that compresses long user interaction histories into compact Preference Memory tokens. Unlike traditional recurrent methods that suffer from serial training, Rec2PM employs a novel self-referential teacher-forcing strategy: it leverages a global view of the history to generate reference memories, which serve as supervision targets for parallelized recurrent updates. This allows for fully parallel training while maintaining the capability for iterative updates during inference. Additionally, by representing memory as token embeddings rather than extensive KV caches, Rec2PM achieves extreme storage efficiency. Experiments on large-scale benchmarks show that Rec2PM significantly reduces inference latency and memory footprint while achieving superior accuracy compared to full-sequence models. Analysis reveals that the Preference Memory functions as a denoising Information Bottleneck, effectively filtering interaction noise to capture robust long-term interests.

Integer linear programming (ILP) remains computationally challenging due to its NP-complete nature despite its central role in scheduling, logistics, and design optimization. We introduce a fully quantum Metropolis-Hastings algorithm for ILP that implements a coherent random walk over the discrete feasible region using only reversible quantum circuits, without quantum-RAM assumptions or classical pre/post-processing. Each walk step is a unitary update that prepares coherent candidate moves, evaluates the objective and constraints reversibly -- including a constraint-satisfaction counter to enforce feasibility -- and encodes Metropolis acceptance amplitudes via a low-overhead linearized rule. At the logical level, the construction uses $\mathcal{O}(n\log_2 N)$ qubits to represent $n$ integer variables over the interval $[-N,\,N-1]$, and the Toffoli-equivalent cost per Metropolis step grows linearly with the total logical qubit count. Using explicit ripple-carry adder constructions, we support linear objectives and mixed equality/inequality constraints. Numerical circuit-level simulations on a broad ensemble of randomly generated instances validate the predicted linear resource scaling and exhibit progressive thermalization toward low-cost feasible solutions under the annealing schedule. Overall, the method provides a coherent, resource-characterized baseline for fully quantum constraint programming and a foundation for incorporating additional quantum speedups in combinatorial optimization.

Odd-parity magnetism has attracted significant interest for its unconventional spin splitting. However, a concrete microscopic route for its realization remains elusive. In this work, we propose van der Waals heterostructures of stripe antiferromagnets (sAFMs) as an ideal platform for electrically controllable $p$-wave magnetism. In the sAFM/metal/sAFM structure, the leading RKKY-type exchange interaction is canceled due to the symmetry of the stacking pattern. This exposes a higher-order biquadratic interaction as a dominant contribution that drives a filling-controlled transition from a collinear phase to an orthogonal $p$-wave configuration. The resulting $p$-wave phase exhibits a gate-tunable Edelstein response, which originates from magnetic symmetry breaking rather than conventional relativistic spin-momentum locking and remains robust even under substantial spin-orbit coupling. Finally, we propose material candidates for the realization of our theory. Our results establish van der Waals heterostructures as a practical platform for non-relativistic spintronics with electric control of odd-parity spin textures.

Industrial recommendation systems typically involve multiple scenarios, yet existing cross-domain (CDR) and multi-scenario (MSR) methods often require prohibitive resources and strict input alignment, limiting their extensibility. We propose MTFM (Meituan Foundation Model for Recommendation), a transformer-based framework that addresses these challenges. Instead of pre-aligning inputs, MTFM transforms cross-domain data into heterogeneous tokens, capturing multi-scenario knowledge in an alignment-free manner. To enhance efficiency, we first introduce a multi-scenario user-level sample aggregation that significantly enhances training throughput by reducing the total number of instances. We further integrate Grouped-Query Attention and a customized Hybrid Target Attention to minimize memory usage and computational complexity. Furthermore, we implement various system-level optimizations, such as kernel fusion and the elimination of CPU-GPU blocking, to further enhance both training and inference throughput. Offline and online experiments validate the effectiveness of MTFM, demonstrating that significant performance gains are achieved by scaling both model capacity and multi-scenario training data.

The K-condition introduced by Shizuta and Kawashima provides a sufficient criterion for the global existence of smooth solutions to dissipative hyperbolic systems. For genuinely nonlinear characteristic fields, a weaker K-condition becomes necessary, although not sufficient. In this paper, we analyze this weaker K-condition through the study of acceleration waves propagating in an equilibrium state. We investigate two classes of hyperbolic models: one describing viscoelasticity with linear dissipation, and the other non-Newtonian fluids asymptotically converging to a power-law behavior. For viscoelastic models, the weaker K-condition is always satisfied and acceleration waves remain bounded. For non-Newtonian fluids, the validity of the condition depends on the power-law index $m$: it holds for Newtonian fluids ($m=1$), is violated for shear-thinning fluids ($m<1$), and leads to an instantaneous regularization of acceleration waves for shear-thickening fluids ($m>1$).

We investigate and generalise Levine sequences like A011784, A061892 and A061894 and develop an algebraic theory for them. We thereby also cover other fast growing sequences like A014644, which we call golombic due to their strong ties with Golomb's sequence A001462.

The X-ray output of low-metallicity starburst galaxies is a key component of stellar feedback, tracing the processes responsible for gas ionization and chemical enrichment. The integrated X-ray luminosity ($L_X$) from high-mass X-ray binaries in star-forming galaxies scales with both the star formation rate (SFR) and host-galaxy metallicity $Z$. Due to the inverse correlation between $L_X/\mathrm{SFR}$ and $Z$, the contribution of X-ray binaries to the ionizing photon budget is enhanced in metal-poor systems and may ionize He II in the surrounding interstellar medium, powering nebular He II $\lambda4686$ emission. The blue compact dwarf galaxy ESO 338-IG04 (ESO 338-4) provides a nearby laboratory for studying stellar feedback in a low-metallicity starburst, combining vigorous recent star formation, low metallicity ($12+\log(\mathrm{O/H})\approx7.9$), and a rich population of massive stellar clusters. We characterize the X-ray emission of ESO 338-4 and its halo using new deep Chandra and XMM-Newton observations. We analyze X-ray spectra, light curves, and images to constrain the nature of its X-ray sources. We identify five ultra-luminous X-ray sources (ULXs) and diffuse hot gas surrounding the galaxy. Two ULXs are spatially associated with stellar clusters. The total X-ray luminosity exceeds $10^{41}\,\mathrm{erg\,s^{-1}}$. The brightest source, ULX1, shows variability on day timescales and lacks a stellar-cluster counterpart. Photoionization modeling shows that X-ray sources significantly impact the ionizing photon budget; models with ULX1 as the ionizing source predict nebular He II $\lambda4686$ luminosities of $\sim10^{39}\,\mathrm{erg\,s^{-1}}$.

The $f(R, T)$ theory of gravity extends general relativity (GR) by allowing the gravitational Lagrangian to depend on both the Ricci scalar $R$ and the trace of the energy-momentum tensor $T$. The resulting matter-geometry coupling introduces additional dynamical effects that may account for the late-time acceleration of the universe without invoking dark energy. In the present work, we focus instead on the early-time regime and investigate the corresponding quantum cosmological dynamics. We analyze a Friedmann--Lemaitre--Robertson--Walker (FLRW) universe within the $f(R, T)$ framework, employing Schutz's perfect fluid formalism to extract a time parameter emerging from the matter sector itself. This approach is particularly well motivated in $f(R, T)$ gravity, where the coupling between geometry and the energy-momentum tensor's trace makes matter an active participant in the dynamics of spacetime and the evolution of cosmic time. The gravitational Hamiltonian, canonical momenta, and potential are derived, leading to the corresponding Schrödinger--Wheeler--DeWitt (SWDW) equation. The wave function of the universe is obtained for specific forms of $f(R, T)$, and the results are compared with previous studies in $f(R)$ and $f(R, T)$ models, highlighting the role of matter-geometry coupling in the emergence of quantum cosmological dynamics.

In [De Cesare, Rychkov (2025)], we revisited the $d=2+ε$ expansion in the $O(N)$ Non-Linear Sigma Model (NLSM), emphasizing the existence of a protected operator which is a closed form with $N-1$ indices. The scaling dimension of this operator stays exactly equal to $N-1$, independently of $ε$. Its existence is problematic for the identification of the NLSM fixed point in $d=2+ε$ with the Wilson-Fisher fixed point family obtained by analytically continuing from near $d=4$, which does not possess such a protected operator. Multiplet recombination is one scenario discussed in [De Cesare, Rychkov (2025)], which could allow to connect the two families continuously (although not analytically). In this scenario, the protected dimension is lifted at some critical value of $ε$, thanks to the short conformal multiplet of scaling dimension $N-1$ eating a long conformal multiplet of higher scaling dimension. In this followup work, we assess this scenario for the cases $N=3$ and $N=4$. We identify the lowest candidates for the long multiplet which could be eaten, and compute their one-loop anomalous dimensions. We find that at one loop, scaling dimensions of these candidates grow with $ε$, while it should decrease down to $N$ for the recombination to occur. We conclude that multiplet recombination is unlikely.

We present a finite schematic axiomatisation of quantum circuits over d-level systems (qudits), uniform in every finite dimension d >= 2. For each d we define a PROP equipped with a family of control functors, treating control as a primitive categorical constructor. Using a translation between qudit circuits and the LOPP calculus for linear optics based on d-ary Gray codes, we obtain for each d a finite set of local axiom schemata that is sound and complete for unitary d-level circuits: two circuits denote the same unitary if and only if they are inter-derivable using axioms involving at most three wires. The generators are compatible with standard universal qudit gate families, yielding a sound equational basis for circuit rewriting and optimisation-by-rewriting. Conceptually, this extends the qubit circuit completeness results of Clément et al.\ to arbitrary finite dimension, and instantiates the control-as-constructor approach of Delorme and Perdrix in this setting, while keeping the axiom shapes uniform in d.

As humans make ambitious efforts toward long-duration activities beyond Earth, new challenges will continue to emerge that highlight the need for governance frameworks capable of managing shared resources and technical standards in order to sustain human life in these hostile environments. Earth-based governance models of cooperative sovereignty can inform governance mechanisms for future Mars settlements, particularly regarding inter-settlement relations and the technical coordination required for multiple independent settlements to coexist. This study analyzes the International Telecommunication Union (ITU) and the Universal Postal Union (UPU), two of the oldest international organizations, which have successfully established evolving standards across sovereign nations. This analysis of the development and governance structures of these two organizations, and how they resolved key sovereignty issues, reveals principles that could be applicable to future settlements beyond Earth, particularly on Mars. Key insights include the strategic necessity of institutional neutrality, the management of asymmetric power relations, and the governance of shared resources under conditions of mutual vulnerability. The study distinguishes between a "Survival Layer" of technical standards essential for immediate safety and an "Operational Layer" governing economic and political activities, suggesting different governance approaches for each. Although some of these examples of cooperative sovereignty on Earth might not be sufficient for Mars due to its unique environment, lessons from the ITU and UPU case studies offer valuable strategies for designing flexible and sustainable governance models that can function from inception through explicit Earth-based coordination.

Automated software environment setup is a prerequisite for testing, debugging, and reproducing failures, yet remains challenging in practice due to complex dependencies, heterogeneous build systems, and incomplete documentation. Recent work leverages large language models to automate this process, but typically evaluates success using weak signals such as dependency installation or partial test execution, which do not ensure that a project can actually run. In this paper, we argue that environment setup success should be evaluated through executable evidence rather than a single binary signal. We introduce the Environment Maturity Hierarchy, which defines three success levels based on progressively stronger execution requirements, culminating in successful execution of a project's main entry point. Guided by this hierarchy, we propose HerAgent, an automated environment setup approach that incrementally constructs executable environments through execution-based validation and repair. We evaluate HerAgent on four public benchmarks, where it outperforms all related work, achieving up to 79.6\% improvement due to its holistic understanding of project structure and dependencies. On complex C/C++ projects, HerAgent surpasses prior approaches by 66.7\%. In addition, HerAgent uniquely resolves 11-30 environment instances across the benchmarks that no prior method can configure.

From ant-acacia mutualism to performative conflict resolution among Inuit, dedicated punishments between distinct subsets of a population are widespread and can reshape the evolutionary trajectory of cooperation. Existing studies have focused on punishments within a homogeneous population, paying little attention to cooperative dynamics in a situation where belonging to a subset is equally important to the actual strategy represented by an actor. To fill this gap, we here study a bipartite population where cooperator agents in a public goods game penalize exclusively those defectors who belong to the alternative subset. We find that cooperation can emerge and remain stable under symmetric intergroup punishment. In particular, at low punishment intensity and at a small value of the enhancement factor of the dilemma game, intergroup punishment promotes cooperation more effectively than a uniformly applied punishment. Moreover, intergroup punishment in bipartite populations tends to be more favorable for overall social welfare. When this incentive is balanced, cooperators can collectively restrain defectors of the alternative set via aggregate interactions in a randomly formed working group, offering a more effective incentive. Conversely, breaking the symmetry of intergroup punishment inhibits cooperation, as the imbalance creates an Achilles' heel in the enforcement structure. Our work, thus, reveals symmetry in intergroup punishment as a unifying principle behind cooperation across human and biological systems.

As the volume and complexity of nonclinical toxicology studies continue to increase, toxicologic pathology reporting faces persistent challenges, including fragmented sources of data (e.g., histopathology images, clinical pathology and other study data, adverse effects database, mechanistic literature), variable reporting timelines and heightened regulatory expectations. This white paper examines the emerging role of agentic artificial intelligence (AI) in addressing these issues through coordinated workflow orchestration, data integration, and pathologist-in-the-loop report generation. Based on a closed-door roundtable held during the 2025 Society of Toxicologic Pathology (STP) Annual Meeting and follow-on discussions, this paper synthesizes the perspectives of leading toxicologic pathologists, toxicologists, and AI developers. It outlines the key pain points in current reporting workflows, identifies realistic near-term use cases for agentic AI, and describes major adoption barriers including requirements for transparency, validation, and organizational readiness. A phased adoption roadmap and pilot design considerations are proposed to help support responsible evaluation and deployment of agentic AI system in nonclinical settings. The paper concludes by emphasizing the need for coordinated efforts across pharmaceutical organizations, CROs, academia, and regulators to establish shared standards, benchmarks, and governance frameworks that will lead to safe, transparent, and trustworthy integration of AI into toxicologic science.

Two known $q$-deformed (or `quantum') $7$-spheres, both denoted $\mathbb{S}^7_q$ in the literature, may be distinguished by the presence or absence of symmetry under $\mathrm{SU}_q(2)$. The quaternionic version of $\mathbb{S}^7_q$ has been shown by Brain and Landi to support such a symmetry. Here we show that this is not the case for the older $\mathbb{S}^7_q$ introduced by Vaksman and Soibelman: and as a consequence, these quantum $7$-spheres are not isomorphic.

We present sensipy, an open-source Python toolkit for simulating observations of transient astrophysical sources, particularly in the high-energy (HE, keV-GeV) and very-high-energy (VHE, GeV-TeV) gamma-ray ranges. The most explosive events in our universe are often short-lived, emitting the bulk of their energy in a relatively narrow time window. Due to often rapidly fading emission profiles, understanding how and when to observe these sources is crucial both to test theoretical predictions and efficiently optimize available telescope time. The information extracted from the tools included in sensipy can be used to help astronomers investigate the detectability of sources considering various theoretical assumptions about their emission processes and mechanisms. This information can further help to justify the feasibility of proposed observations, estimate detection rates (events/year) for various classes of sources, and provide scheduling insight in realtime during gamma-ray and multi-messenger observational campaigns.

The discovery of interstellar interlopers such as 1I/`Oumuamua, 2I/Borisov, and 3I/ATLAS have highlighted the necessity of understanding the dynamical pathways that eject small bodies from planetary systems into hyperbolic trajectories. In this paper we examine the orbital elements of particles in the restricted three-body problem prior to and post scattering onto hyperbolic trajectories by massive perturbers. Building on previous work, we calculate closed-form -- but approximate -- analytic criteria that map pre- to post-encounter orbital elements. An application of these equations demonstrates that ejection occurs most efficiently when the orbital eccentricity of the massless test particle exceeds a minimum threshold, $e\gtrsim0.4$. The primary driver of the final eccentricity is the component of the perturber-centric velocity projected along the direction of motion of the perturber. These analytic criteria are then benchmarked and validated against numerical simulations which demonstrate that they provide a reasonably good zeroth-order approximation for ejection behavior. However, system-specific cases will generally require numerical simulations in addition to this analytic construction. The methodology is applied to (i) the solar system and exoplanetary systems (ii) $β$ Pictoris and (iii) HR 8799 to evaluate the pre-scattering orbits of ejected particles. This method provides a transparent and computationally efficient tool for identifying orbits within a given system from which interstellar objects are efficiently ejected via a single scattering event from a massive perturber.

Multipartite entanglement determines the strength and range of interactions in many-body quantum systems. Yet, it is hard to evaluate it, due to the complex structures of quantum states. Here, we introduce a generic method to quantify the k <= N-partite entanglement of an N-particle system, by maximizing an arbitrary bipartite entanglement measure within subsystems of size up to k. The resulting classification of multipartite states captures their experimental cost: creating a k-partite entangled state requires at least k-1 two-particle entangling gates. Further, we analytically calculate the newly defined k-partite entanglement of formation, which generalizes an important bipartite entanglement measure, in several classes of states, including the W states of any dimension.

Sensory processing with neuromorphic systems is typically done by using either event-based sensors or translating input signals to spikes before presenting them to the neuromorphic processor. Here, we offer an alternative approach: direct analog signal injection eliminates superfluous and power-intensive analog-to-digital and digital-to-analog conversions, making it particularly suitable for efficient near-sensor processing. We demonstrate this by using the accelerated BrainScaleS-2 mixed-signal neuromorphic research platform and interfacing it directly to microphones and a servo-motor-driven actuator. Utilizing BrainScaleS-2's 1000-fold acceleration factor, we employ a spiking neural network to transform interaural time differences into a spatial code and thereby predict the location of sound sources. Our primary contributions are the first demonstrations of direct, continuous-valued sensor data injection into the analog compute units of the BrainScaleS-2 ASIC, and actuator control using its embedded microprocessors. This enables a fully on-chip processing pipeline$\unicode{x2014}$from sensory input handling, via spiking neural network processing to physical action. We showcase this by programming the system to localize and align a servo motor with the spatial direction of transient noise peaks in real-time.