The thermally reversible phase transitions in aqueous solutions of the triblock copolymers known as Pluronic and their related textures are well-researched. However, their corresponding rheological properties are less studied. In particular, their high-temperature behavior is difficult to access with classical rheology. Here we demonstrated that Diffusing Wave Spectroscopy (DWS)-based microrheology allows us to study the phase transition and the associated viscoelastic properties of Pluronic F127 solutions for temperatures from 5 C to 80 C. From the measured intensity-autocorrelation functions we can extract effective viscosities and determine the critical micellization temperature and concentration. Moreover,the high EO/PO (arm-to-core) ratio of F127 and its polydispersity play a critical role in the high-temperature re-entrant liquid phase, due to decreasing solubility of PEO along with the dehydration of the PPO core. The microscopic viscoelastic moduli G'(ω) and G''(ω) help to determine these phase transitions and provide mechanical properties in the solid phase that are not readily accessible with standard multi-particle tracking techniques due to limited Brownian motion.

We develop a domain-theoretic framework for imprecise probability reasoning and inference on general topological spaces with a countably based continuous lattice of open sets. We address two distinct forms of uncertainty: partial or incomplete event descriptions, and sets of probability distributions as represented by credal sets -- as well as their combination. Within this framework, we construct a theory of conditional probability and derive novel inference rules for performing Bayesian updating in the presence of these two complementary types of imprecision. These results are extended to a theory of conditional independence for imprecise probabilistic events. We also formulate logical predicates for conditional probability, Bayesian updating, and conditional independence, and we obtain the relevant soundness and completeness results. A key contribution is the construction of a Scott-continuous mapping from any credal set to the domain of intervals, providing a domain-theoretic realisation of classical results from capacity theory and Choquet integration. Finally, we introduce and study a new family of credal sets generated by iterated function systems with imprecise probability weights, broadening the scope of computationally tractable imprecise probabilistic models. The resulting computable framework unifies logical, topological, and measure-theoretic perspectives on uncertainty, supporting robust probabilistic inference under partial and set-valued information.

Nitrogen is a key element for building habitable worlds, yet only a small fraction of the available N-budget of planet-forming disks has been detected. In particular, the lack of any IR NH$_3$ detection is striking, as this molecule is predicted to be rather abundant in the warm, inner regions of protoplanetary disks, and therefore potentially readily incorporated into (giant) planets' atmospheres. We present a combined modeling and observational study of N-bearing molecules in planet-forming disks, using detailed thermo-chemical disk models that investigate the sensitivity of N-containing molecules to the bulk elemental composition of the disk. Our models predict a strong increase in HCN flux with high C/H, and conversely a strong increase in flux from NO when O/H is high. The flux from NH$_3$ is not very sensitive to O/H, but does decrease at high C/H due to competition with HCN. However, the absolute NH$_3$ flux predicted by our model is not large enough to be detected with JWST-MIRI, even when N/H is enhanced by an order of magnitude. The flux from NO, on the other hand, is potentially detectable, and could therefore provide further insights into the N-budget of the inner disk. Using a cross-correlation technique, we search for NH$_3$ and NO detections in three disks, GW Lup, Sz 98, and V1094 Sco. We do not find any NH$_3$ detections, and only one tentative NO detection in V1094 Sco, though this needs further study to be confirmed. Additionally, we demonstrate that future facilities in the FIR may provide a better opportunity to detect NH$_3$ and thereby draw a comparison to the NH$_3$ budget known to be present in interstellar ices.

Koopman operator-based methods enable data-driven bilinear representations of unknown nonlinear control systems. Accurate representations often demand significantly higher dimensions than the original system, making control design challenging. Control Lyapunov Functions (CLFs) are widely used for controller synthesis, with quadratic CLF candidates being the most common due to their simplicity. Yet, we show that this class is highly restrictive, especially when the state dimension is large: under mild conditions, their existence implies stabilizability of the bilinear system by a constant input -- that is, the control remains fixed over time. We establish this result by formulating a quadratically constrained quadratic program (QCQP) that exactly characterizes valid CLFs. Since QCQPs are NP-hard, we propose a convex semidefinite relaxation that offers a sufficient validity condition. For single-input systems, we prove that a quadratic CLF requires constant control stabilizability, and empirically demonstrate that this extends to high-dimensional multi-input systems in many cases.

Let $\mathcal{A}$ denote the class of analytic functions such that $f(0)=0$ and $f'(0)=1$ in the unit disk $\mathbb{D}:=\{z \in \mathbb{C}: |z|<1\}$. In this paper, we discuss the properties of a starlike subclass and compute its second and third Hankel determinants; where the class is defined as $\mathcal{S}^*(φ):=\{f\in\mathcal{A}:{zf'(z)}/{f(z)}\prec φ(z):=1+z+{m}/{n}\,\, z^2,\text{ such that } 2m \le n, \text{ where } m,n\in\mathbb{N}\}.$ Furthermore, we show that the bounds are sharp by determining the extremal functions for the Hankel determinants.

We establish a precise relationship between functor calculus and the projective dimension of multipersistence modules. Specifically, we develop a new notion of functor calculus for functors from posets, which detects vanishing total fibers of cubes. We give an explicit construction of the universal approximation functors of this functor calculus. We then use these approximations to prove two new theorems, providing necessary and sufficient conditions for an $n$-parameter multipersistence module to have projective dimension at most $n-1$ and at most $n-2$.

A simplified relativistic kinetic theory for gases with internal degrees of freedom, based on a BGK-type collision term, is considered. First the Boltzmann equation is rewritten in tetrad form and then thermal coefficients are determined to first order in the Chapman-Enskog expansion for general spacetimes. The results are used to construct a self-consistent system of first order differential equations, equivalent to the Einstein-Boltzmann system, for some spatially homogeneous models with viscosity and heat flow.

This paper presents a Semantic Feature Multiple Access (SFMA) framework for multi-user semantic communication in downlink wireless systems. By extending SwinJSCC to a two-user superimposition paradigm, SFMA enables simultaneous semantic transmission to multiple users over shared time-frequency resources. A key innovation is the Cross-User Attention (CUA) module, which facilitates controlled semantic feature exchange between paired users by leveraging inter-image similarity while mitigating interference. We formulate a joint user pairing and resource allocation problem to minimize global semantic distortion under constraints on bandwidth, end-to-end latency, and energy. This mixed-integer non-convex problem is decomposed into a Minimum-Weight Perfect Matching (MWPM) sub-problem and a convex bandwidth allocation feasibility check, with semi-closed-form bandwidth bounds derived from a strictly concave rate expression. A polynomial-time algorithm based on Blossom matching and bisection search is proposed. Extensive simulations on ImageNet-100 show that SFMA significantly improves reconstruction quality across pairing modes, and the proposed optimization effectively reduces overall distortion while satisfying physical-layer constraints.

We propose a Bayesian framework for planning simple step-stress accelerated life tests when items are subject to two independent competing failure modes We assume that the competing risks are independent, with lifetimes following Weibull distributions, and adopt the cumulative exposure model with a log-linear stress-life relationship to connect failure time distributions across stress levels. The optimality criterion is the preposterior variance of the $p$-th quantile of the lifetime distribution at use stress, evaluated without reliance on asymptotic approximations, making the methodology valid regardless of sample size. Building on the idea of quantile-based reparametrisation used in single-mode ALT \citep{zhang2006bayesian}, we extend this approach to the competing risks setting by reparametrising the model parameters for each failure mode to physically interpretable and approximately independent quantities, making it possible to elicit priors directly from engineering knowledge of device behaviour. Posterior inference is carried out using the No-U-Turn Sampler implemented in Stan, and the optimal design is located via Monte Carlo simulation over a grid of candidate designs. The methodology is illustrated on a real step-stress dataset for a solar lighting device subject to capacitor and controller failure modes. A comprehensive sensitivity analysis with respect to the quantile probability, the lower stress level, the prior hyperparameter specification, and the sample size shows that the optimal stress-change time is moderately sensitive to these inputs while the optimal lower stress level consistently favours operation close to use conditions, a finding that holds across all prior specifications considered.

Conventional polarimetry, including schemes leveraging entangled light, characterizes optical samples through linear transformations of polarization states. We introduce a two-photon probing approach in which both photons of an entangled pair interact with the same depolarizing medium simultaneously. In this regime, the transformation of the two-photon polarization correlations becomes quadratic in the Mueller matrix, enabling access to second-order polarization information beyond conventional polarimetry. We develop a theoretical framework linking the Mueller matrix to the evolution of the two-photon polarization correlation tensor and show that depolarization induces quadratic degradation of entanglement and state purity. Experiments using polarization-entangled photon pairs transmitted through controlled scattering media confirm the predicted response and reveal enhanced sensitivity to polarization scrambling compared with single-photon probing. These results establish two-photon probing as a higher-order quantum polarimetric modality for characterizing polarization channels.

We argue that Bonferroni correction is a better choice for online experimentation than it is commonly given credit for. The case rests on four considerations. First, it is the simplest broadly implementable FWER-controlling method that produces unconditional simultaneous confidence intervals for every metric. Second, in a well-specified decision framework, guardrail and quality metrics use intersection-union logic and cannot inflate the false positive rate, so the Bonferroni denominator is the number of success metrics only, not the total metric count. Third, it is uniquely tractable for pre-experiment sample size calculations. Fourth, we contextualise the power cost empirically. Drawing on a simulation study and an empirical analysis of 1,296 experiments run on Spotify's experimentation platform, Confidence, we show that the power loss relative to more sophisticated FWER methods depends on both how the correction family is specified and how many metrics are truly non-null. When guardrail metrics are incorrectly included in the family, Holm and Hommel are nearly indistinguishable from Bonferroni. When the family is correctly restricted to success metrics only, they gain roughly 4--5 percentage points in ship rate (the fraction of experiments where the treatment is deployed). When few metrics are truly non-null, the gap narrows to near zero regardless of method.

Integrated learning and communication (ILAC) unifies learned transceivers with radio resource management, where semantic feature multiple access (SFMA) enables paired users to superpose their learned representations over shared time-frequency resources. Unlike conventional multiple access schemes, SFMA interference arises in the learned feature space and depends jointly on the user pair, the transmit power, and the compression ratio. This coupling ties binary pairing decisions to continuous resource variables, yielding a mixed-integer non-convex optimization problem. To address this problem, we first propose similarity-conditioned SFMA (SC-SFMA), a Swin Transformer-based transceiver whose dual-conditioned similarity modulator (DC-SimM) gates cross-user feature fusion according to the inter-user semantic similarity. We then characterize the resulting pair-dependent interference by a bivariate logistic function parameterized by transmit power and compression ratio, thereby bridging the learned transceiver with network-level optimization. On this basis, we formulate a sum-rate maximization problem subject to per-user distortion, latency, energy, power, and bandwidth constraints. To solve this problem, we develop a three-block alternating optimization algorithm that integrates dual-decomposition-assisted compression ratio allocation, trust-region successive convex approximation (SCA) for joint power-bandwidth optimization, and dynamic feasible graph-based user pairing. Simulation results show that SC-SFMA achieves considerable peak signal-to-noise ratio (PSNR) and multi-scale structural similarity index measure (MS-SSIM) gains over deep joint source-channel coding (JSCC) and separation-based baselines. The proposed optimization framework attains significant sum rate improvements over conventional multiple access baselines.

Most detected transiting planets have orbits which would fit within the one of Mercury, exposing them to intense stellar irradiation and interactions that significantly alter their properties. In contrast, colder planets with longer orbital periods are less affected, offering crucial insights into their formation and migration histories. Characterizing transiting warm and temperate planets is a key missing piece in the exoplanet puzzle. Dedicated photometric and spectroscopic follow-up of transiting events detected in space-based photometric data opened the way to detecting long-period transiting exoplanets. The wealth of information available for these transiting planets makes them golden targets for in-depth characterization. For giant planets, combining precise masses, radii, and ages with state-of-the-art planetary evolution models allows the estimation of their planetary bulk compositions, a crucial element to explore their formation and evolution pathways. Furthermore, these planets are compelling candidates for hosting moons and circumplanetary rings-features that could illuminate dynamical histories, satellite formation processes, and even potential habitable environments.

This paper studies equality-constrained minimization problems through the lens of feedback control. We introduce a unified control-theoretic framework by showing that a PID feedback law acting on the dual variable induces the PID saddle-point flow (PID-SPF), a broad class of saddle-point dynamics associated with the augmented Lagrangian. This framework recovers several classical primal-dual flows as special cases. We prove that the equilibria of the proposed flow coincide with the stationary points of the original problem. Our analysis reveals how the feedback gains affect the optimization: integral action enforces constraint satisfaction, proportional action introduces the augmented Lagrangian structure, and derivative action modifies the geometry of the primal dynamics by inducing a state-dependent Riemannian metric. Moreover, for convex problems with affine constraints, we establish global exponential convergence by leveraging contraction theory for all admissible PID gains, providing in the process explicit bounds on the convergence rate. Finally, we validate our theoretical results on numerical examples including an application to bilevel optimization.

The 2025 UK National Astronomy Meeting (NAM) in Durham played host to a session titled "Unseen Astronomy", involving a variety of astronomy researchers in diverse fields. This unique meeting focussed on a number of novel projects exploring alternatives to purely visual means of display in Astronomy, encompassing spheres of education, communication and research, and straddling both accessible and general use applications. The successful inclusion of such a session at a major conference reflects the explosion of interest in multimodal astronomy in recent years, and hints at its transformative potential. Here, I aim to outline and motivate the topic of multi-modal science and consider its exciting potential. I will discuss this in the context of our own work in the area, the community building being undertaken to bring together researchers considering multi-modality, and efforts to impact astronomy at large.

Empty region graphs are graphs whose vertices are points in $\mathbb{R}^d$ and where two vertices are connected by an edge whenever some associated region does not contain any other vertices. We investigate the asymptotic behaviour of long edges in empty region graphs generated by a stationary Poisson process in $\mathbb{R}^d$. {Letting} the intensity of the underlying Poisson process tend to infinity, we consider the associated point process of edge midpoints, suitably transformed edge lengths, and directions of the edges. We prove that it converges in distribution to a Poisson process on $\mathbb{R}^d \times \mathbb{R}\times\mathbb{L}^d$, where $\mathbb{L}^d$ is the space of lines in $\mathbb{R}^d$ through the origin, and that the suitably transformed length of the longest edge with midpoint in an observation window converges in distribution to a Gumbel distributed random variable. Our approach yields explicit error bounds in Kantorovich--Rubinstein distance for the point process convergence {when restricting to an observation window} and in Kolmogorov distance for the maximal edge length. The results apply uniformly to a broad class of empty region graphs, including the Gabriel graph, the relative neighbourhood graph, the beta-skeleton graph, the Mastercard graph, and the Pacman graph.

This paper presents a novel method for evaluating second-order consistent hydrodynamic loads, which employs nonlinear wave and body kinematics. The pseudo-spectral formulation of nonlinear potential flow wave solvers is exploited, permitting the application of transfer functions on the nonlinear incident wave field. A closed-form expression is accordingly derived for the potential force component, which constitutes a generalisation of the Pinkster approximation to fully nonlinear waves. Moreover, the quadratic force component is reformulated to account for the total nonlinear body motion and velocity rather than their first-order counterparts. Hence, the traditional assumption that first-order body motions are significantly larger than the second-order components, which is violated in the case of moored floating structures, is circumvented. To this end, the radiation potential is treated in the time domain and is distinguished from the incident and scattering wave contributions, which are considered through wavenumber-domain transfer functions. An important advantage of the proposed approach is that it is established on the output of radiation-diffraction analysis in the frequency domain, and therefore is highly practical and efficient. Finally, the derived force model is coupled with a time-domain motion solver, which permits the consideration of the instantaneous body motion and velocity in the force calculation. The solver is employed to investigate the motions of a moored container ship, and the results demonstrate significant improvements over standard second-order radiation-diffraction theory.

We investigate the integration of Nesterov-type acceleration into primal-dual methods for structured convex optimization. While proximal splitting algorithms efficiently handle composite problems of the form $\min_x f(x)+g(x)+h(Kx)$, accelerating their convergence with respect to the smooth term $f$ is notoriously challenging due to the rotational dynamics in the primal-dual space. In this paper, we overcome this barrier by proposing the Accelerated Proximal Alternating Predictor-Corrector algorithm (APAPC), focusing on the setting where $g(x)=\frac{μ_g}{2}\|x\|^2$. Our analysis reveals that Nesterov momentum can be seamlessly integrated into a primal-dual forward-backward scheme by exploiting the strong convexity of the dual problem to stabilize the accelerated primal updates. Using a unified Lyapunov framework, we establish optimal $O(1/t^2)$ sublinear convergence rates, as well as accelerated linear convergence when $μ_g > 0$, across three regimes of dual strong convexity: (i) when $h$ is smooth, (ii) when the linear operator $K^*$ is bounded below, and (iii) for linearly constrained optimization. Furthermore, leveraging recent results on accelerated gradient descent, we characterize the weak convergence of the primal-dual iterates to a saddle-point solution.

As computational complexity in electromagnetics increases with frequency, full-wave solvers become computationally infeasible for electrically large problems. To address this limitation, we present a shooting and bouncing rays (SBR) method for efficiently modeling electromagnetic backscattering of metallic objects in the high-frequency regime. The method couples multi-reflection geometrical-optics ray transport with a physical optics surface integral discretized over ray tubes. To reduce the massive ray-surface intersection search space, we use a bounding volume hierarchy (BVH) and organize the computation as a trace-integrate pipeline. The ray tracing generates hit data, and the physical optics integral is evaluated over valid intersections only. Numerical accuracy is controlled through an incident-ray sampling rule that mitigates phase aliasing in the discretized physical optics integration. The method is accelerated on NVIDIA and AMD GPUs and parallelized with MPI. We validate against analytical Mie solutions for a perfectly electrically conducting (PEC) sphere and demonstrate applicability to a complex aircraft geometry for monostatic radar cross-section prediction.

Ultrafast optical excitation in charge-density wave (CDW) crystals can transiently suppress long-range order, driving the lattice toward higher symmetry on femtosecond timescales. Here, we formulate and implement a first-principles theory of light-induced melting of CDW order. The approach is based on the structural dynamics in the Heisenberg picture, and it explicitly accounts for quartic lattice anharmonicities, nonlinear electron-phonon interactions, and photoexcitation-induced modifications of the potential energy surface. We illustrate these concepts through first-principles calculations of the ultrafast melting of CDW order in monolayer TiSe$_2$ - a prototypical CDW crystal with a 2$\times$2 structural reconstruction. The simulations are in good agreement with existing experiments, and they capture the defining features of CDW melting, such as the damped coherent structural motion, the transient renormalization of the soft mode, and the restoration of CDW order over timescales of a few picoseconds. Besides identifying nonlinear electron-phonon interactions as the primary mechanism driving symmetry switching in CDW systems, our work establishes a generally applicable theoretical framework to treat quartic anharmonicities and light-induced phase transitions in first-principles ultrafast dynamics simulations.

This paper is devoted to the investigation of the backward problem for a multi-term time-fractional diffusion equation. Backward problems for fractional diffusion equations are typically studied using regularization methods due to their ill-posedness in the sense of Hadamard; that is, a small change in u(T) may lead to large changes in the initial data. Nevertheless, we show that if sufficiently smooth current data are considered, then the solution exists, is unique, and is stable. A principal difficulty in the analysis of the backward problem stems from the structure of the solution, in which the multinomial Mittag-Leffler function appears in the denominator. Accordingly, a precise characterization of the asymptotic behavior of this function is required. Such asymptotic properties are nontrivial and have been rigorously established in the authors' recent work, which serves as a fundamental basis for the present study. In addition, we investigate the conditional stability of the backward problem. It is shown that, although the problem is ill-posed in general, stability can be restored under an appropriate a priori bound imposed on the initial data. The main novelty of the paper lies in proving the best smoothing property of the solution, showing that it belongs to the domain of the operator A for any positive time.

Photoexcited hot carriers in solids can drive processes, such as photocatalytic reactions on the surface, beyond those available in thermal equilibrium. Hot-electron-mediated reaction pathways are limited by the thermalization of the nonequilibrium electron distribution through microscopic scattering events. Commonly, thermalization is exclusively attributed to electron-electron scattering, whereas electron-phonon scattering is considered relevant mainly for the energy equilibration with the lattice. With a kinetic model based on full Boltzmann collision integrals, we demonstrate that each scattering mechanism alone can thermalize the electron distribution, albeit along different trajectories in phase space. We find an opposite dependence on the excitation strength of the respective thermalization times and show that both processes can become comparable for weak excitations, corresponding to a sample temperature increase of a few Kelvin. Our results unravel the contributions of electron-electron and electron-phonon scattering to the thermalization across the full range of experimental excitation strengths up to the melting regime, thus facilitating the prediction of thermalization times for hot-carrier-based applications.

Large Language Models (LLMs) are increasingly deployed in settings where Chain-of-Thought (CoT) is interpreted by users. This creates a new safety risk: attackers may manipulate the model's observable CoT to make malicious behaviors. In open-weight ecosystems, such manipulation can be embedded in lightweight adapters that are easy to distribute and attach to base models. In practice, persistent CoT hijacking faces three main challenges: the difficulty of directly hijacking CoT tokens within one continuous long CoT-output sequence while maintaining stable downstream outputs, the scarcity of malicious CoT data, and the instability of naive backdoor injection methods. To address the data scarcity issue, we propose Multiple Reverse Tree Search (MRTS), a reverse synthesis procedure that constructs output-aligned CoTs from prompt-output pairs without directly eliciting malicious CoTs from aligned models. Building on MRTS, we introduce Two-stage Backdoor Hijacking (TSBH), which first induces a trigger-conditioned mismatch between intermediate CoT and malicious outputs, and then fine-tunes the model on MRTS-generated CoTs that have lower embedding distance to the malicious outputs, thereby ensuring stronger semantic similarity. Experiments across multiple open-weight models demonstrate that our method successfully induces trigger-activated CoT hijacking while maintaining a quantifiable distinction between hijacked and baseline states under our evaluation framework. We further explore a reasoning-based mitigation approach and release a safety-reasoning dataset to support future research on safety-aware and reliable reasoning. Our code is available at https://github.com/ChangWenhan/TSBH_official.

Purpose: Image reconstruction in challenging scenarios requires accurate characterisations of coil sensitivity profiles, local off-resonances (B0) and effective encoding fields. Reconstruction methods utilising all of this information rely on signal models that are not compatible with the classical Fourier/k-space interpretation of the coil data. Hence, the FFT and related techniques are no more applicable, rendering image reconstruction computationally demanding. Methods: This article contains a workflow for accurate sensitivity and B0 mapping as well as other required processing steps. An implementation of non-Fourier SENSE reconstruction is provide that is well suited for execution on a GPU using the FFT. Important practical aspects like stopping criteria and sources of image artifacts are analyzed and documented. Results: Highly performant image reconstruction could be demonstrated on a 2D and 3D spiral dataset. These datasets contain trajectories featuring readout durations up to 71.5ms and undersampling factors up to R = 7. Running the reconstruction on a GPU greatly boosts reconstruction speed. Stopping the reconstruction at the right moment is crucial for image quality. All methods included in this article are available in a public code repository. Conclusion: The provided implementation of non-Fourier SENSE reconstruction is highly performant. When it is executed on GPU, runtimes reach a duration feasible in practice. The presented workflow ensures robust and accurate computation of coil sensitive profiles and off-resonance maps.

Mixed-reference spin-flip time-dependent density functional theory (MRSF-TDDFT) has recently emerged as an attractive electronic-structure method for studying photochemical processes, given that it bridges the computational efficiency of single-reference approaches with the versatility of multireference methods. In the following, we critically assess the general applicability of MRSF-TDDFT to photochemistry and identify two important limitations. First, the doubly-excited configurations included in MRSF-TDDFT come at the cost of missing some singly-excited configurations. Second, MRSF-TDDFT provides unreliable excited-state energies when its triplet reference - a cornerstone of the method - abruptly changes its nature, e.g., when the T$_1$ and T$_2$ triplet states become nearly degenerate and exchange electronic character. This change of character of the triplet reference can induce discontinuities or sharp distortions in electronic potential energy curves of the response states in unsuspected regions of the nuclear configuration space. We propose strategies and diagnostics to detect these limitations in the exploration of potential energy surfaces and nonadiabatic molecular dynamics using MRSF-TDDFT.

We aim to provide a systematic and quantitative description of the hydrogenation network connecting HCN and HNC to methylamine on interstellar water ices, while identifying dominant pathways and bottlenecks. To this end, we performed a comprehensive quantum-chemical investigation of H-addition, H-abstraction, reactions with H2, and water-assisted H-transfer isomerization, covering intermediates linking HCN and HNC to CH3NH2. Calculations were carried out on amorphous solid water clusters of 14 molecules. Using benchmarked density functional theory, we derived activation barriers, elucidated mechanisms, and determined the binding energy distribution of H2CN and CNH2, also assessing deuterium substitution effects. H-addition reactions generally involve activation barriers, except for radical species. Considering both barrier heights and tunneling crossover temperatures, the most favorable sequence originates from HNC rather than HCN. The network evolves toward methanimine (H2CNH), the central species, or the singlet carbene HC:NH2, from which further hydrogenation leads to methylamine. Along these paths, several reactions are barrierless, while some H-abstraction processes compete with addition. Reactions involving H2 are uncommon, as most are endoergic. Deuterium substitution weakly affects classical barriers but significantly influences tunneling efficiencies. Our results support efficient formation of methanimine and methylamine from HNC on cold interstellar ices, with methanimine acting as a chemical sink, whereas HCN is less reactive and more likely to persist. These findings provide quantitative constraints for astrochemical models.

Hydrogen storage remains a key challenge for the development of a sustainable hydrogen energy system, where materials must satisfy requirements on storage capacity, thermodynamics, kinetics, and reversibility. Complex borohydrides are attractive due to their high hydrogen density, but their practical use is limited by slow hydrogen diffusion and unfavorable desorption thermodynamics. In this work, we present a first-principles study of pristine and Ti-doped MgB2H8 as a solid-state hydrogen storage material. Density functional theory calculations show that pristine MgB2H8 has a high gravimetric hydrogen capacity of about 14.9 wt percent, but also a relatively high hydrogen desorption enthalpy of about 42 kJ per mol H2 and diffusion barriers around 0.5 eV, which limit its performance at moderate temperatures. Substitutional doping with Ti at the Mg site improves these properties while maintaining structural stability. The doped system retains a high hydrogen capacity of about 10.4 wt percent and shows a reduced desorption enthalpy of about 36 kJ per mol H2, placing it within a favorable thermodynamic range for hydrogen release. Nudged elastic band calculations show a reduction in hydrogen migration barriers to about 0.38 eV, indicating improved diffusion kinetics. Phonon and elastic analyses confirm that Ti doping preserves stability. Electronic structure analysis shows that Ti 3d states near the Fermi level weaken B-H bonding and stabilize intermediate hydrogen configurations, explaining the improved behavior. These results identify Ti-doped MgB2H8 as a promising hydrogen storage material.

As the search for observable deviations from the Standard Model of particle physics remains to be of significant interest, effective field theory (EFT) continues to be a popular method to parametrize such effects. In this work, a first-time investigation is performed of the unique capability of measurements of charm quark associated Higgs boson production (cH) in proton-proton collisions at the CERN Large Hadron Collider to constrain a set of dimension-six EFT operators. The phenomenology of these operators is discussed and a proposed analysis strategy is presented, with a focus on $\mathrm{H}\rightarrow \mathrm{Z}\mathrm{Z}^{*}\rightarrow 4μ$ decays, using a generic detector simulation that is parametrized to reflect the response of the CMS detector at the LHC. From this, expected 95% CL upper limits are derived for the Wilson coefficients of individual operators by considering yield and shape effects in the spectra of the four-muon invariant mass $m_{4μ}$ and leading jet transverse momentum $p_{T}$. Scenarios with simultaneous contributions from two operators are also considered. Finally, potential analysis improvements that may be implemented in an experimental context are outlined.

We investigate the emergence of many-body dynamical localization (MBDL) in the Fock space of an interacting two-mode bosonic system subject to periodic driving. Using a mapping to the paradigmatic kicked-top model, we analyze the interplay between classical chaotic diffusion and quantum interference effects. While the mean-field (classical) dynamics exhibits bounded ergodic diffusion along the population imbalance axis, the quantum dynamics reveals strong suppression of transport in Fock space, in close analogy with Anderson localization in disordered lattices. We characterize the localization length, its scaling with particle number and driving parameters, and reveal the spectral crossover from random-matrix to Poisson statistics as the many-body ensemble localizes. We highlight the connection between MBDL and discrete time crystals. Our findings offer a promising avenue to study the Anderson transition in Fock space.

The most favorable structure of the synthesized TiCoSb half-Heusler alloy is explored theoretically and experimentally, and the best structure for thermoelectric conversion is reported. Rietveld refinement of the X-ray diffraction data employing four probable structures of the HH alloy is performed to obtain the best fit and identify the crystallized structure. However, microstructural characterization is performed using the energy dispersive X-ray spectroscopy and transmission electron microscopy to reveal the stoichiometry and Bragg reflection planes of the synthesized polycrystalline lattice structure of TiCoSb HH alloy. Theoretical investigation is performed by implementing the first principle calculation using the Full Potential Linearized Augmented Plane Wave method in the Quantum Espresso software package. The most probable structure is explored by estimating the minimum energy at equilibrium volume and electronic structure of the TiCoSb half-Heusler alloy of the four probable structures considered. The theoretical and experimental data are corroborated, and the most probable structure is identified for the crystallized TiCoSb HH alloy. The thermoelectric properties of the most probable structure are estimated.