Papers

This work presents deep learning models to predict magnetohydrodynamic equilibrium parameters and profiles for the ADITYA-U tokamak. A synthetic free-boundary equilibrium dataset consisting of 100,760 cases was generated using the pyIPREQ Grad-Shafranov solver, with inputs derived from 766 ADITYA-U plasma discharges and constrained to experimentally relevant circular limiter plasmas near the flat-top phase. Several deep learning approaches were investigated for predicting scalar equilibrium quantities, one-dimensional safety factor profiles and two-dimensional poloidal flux profiles. These approaches included Dense neural networks, principal component analysis based reduced-order models, one-dimensional and two-dimensional convolutional neural networks, and physics-informed neural networks incorporating Grad-Shafranov residual constraints. In addition, an inverse model was developed to estimate poloidal field coil currents from desired plasma equilibrium conditions. The results demonstrate that key equilibrium parameters and profiles can be accurately estimated within the operational domain represented by the dataset. The developed models provide a computationally efficient alternative to conventional equilibrium estimation and can be useful for real-time plasma control, rapid equilibrium analysis, and experimental planning in ADITYA-U operations.

The probabilistic nature of quantum measurement provides a direct window into the structure and complexity of many-body wave functions. When only part of a system is measured, the remaining degrees of freedom form an ensemble of post-measurement states whose statistical structure can reveal a stronger form of thermalization, known as deep thermalization. Recent numerical evidence suggests that this phenomenon is characterized by convergence of the projected ensemble to the Scrooge ensemble, a maximally random ensemble compatible with a given density matrix. In this Letter, we use the solvable Sachdev-Ye-Kitaev (SYK) model to unveil the mechanism by which the Scrooge ensemble emerges in many-body systems. By formulating measurement probabilities and post-measurement states in terms of path integrals, we analytically characterize all moments of the projected ensemble and show that they exactly match those of the Scrooge ensemble, even at short evolution times. We further connect this result to the saddle-point structure of the measurement path integral, which naturally generates the replica permutations underlying Scrooge statistics. Our results establish the solvable SYK model as a tractable setting for exploring universal statistics of quantum measurements in chaotic many-body dynamics.

We study the inverse problem of classical density functional theory for inhomogeneous fluids: finding the wall potential that produces a constant equilibrium density profile, i.e., a perfectly flat density distribution in the accessible region adjacent to a substrate. Within Rosenfeld's fundamental measure theory, we solve this problem for a one-component fluid in planar, spherical, and cylindrical geometries, considering both a hard-sphere fluid and a fluid with an additional truncated Lennard-Jones attraction treated at the mean-field level. Explicit analytical expressions are obtained for planar walls, while spherical walls also admit an analytical treatment in a more cumbersome form. The cylindrical case is treated numerically. The construction provides an explicit microscopic realization of structure-cancelling wall fields, related to flat-profile conditions that occur under special matching conditions in interfacial theories of wetting and drying. The theory also yields a compact collection of formulae for weighted densities and one-body direct correlation functions in the three fundamental geometries, providing useful reference expressions for density-functional implementations. The resulting analytic wall potentials are validated in independent density functional calculations, which confirm that the prescribed flat profiles are recovered within numerical accuracy.

We systematically investigated the magnetic, dielectric, and MD properties of BaFe12-xMexO19 ceramics prepared by a solid-state reaction method. The Ga3+ cations with a smaller radius preferentially substitute the Fe3+ ions in FeO6 octahedra while the In3+ cations with a larger radius tend to replace the Fe3+ ions in FeO5 bipyramids of R blocks, inducing different physical characteristics. The pure BaFe12O19 and Ga-doped samples show ferrimagnetism in the temperature range from 10 K to 300 K. The In-doped samples exhibit a transition from non-collinear magnetism to collinear ferrimagnetism. The dielectric decrease of pure BaFe12O19 at around 10-175 K is attributed to the quantum paraelectric state, and the shoulder peaks of loss at about 140-200 K are from electron hopping. The dipole glass state is responsible for the dielectric peak of Ga-doped samples at around 20-40 K. The dielectric increase and plateau of In-doped samples are mainly ascribed to the electron hopping at low temperatures. Their dielectric properties at high temperatures are all attributed to the interfacial polarization caused by the Maxwell-Wagner effect. The MD effect also has different origins for the various samples at low temperatures. For the pure BaFe12O19, the negative MD effect at extremely low temperatures and the positive MD effect after warming are ascribed to spin-phonon coupling and field-dependent electron hopping, respectively. The positive MD effect in Ga-doped hexaferrites results from the field-dependent electric dipoles inside FeO5 bipyramids. For the In-doped samples, the negative MD effect and subsequent transformation to the positive MD effect originate from the field-dependent non-collinear spin ordering and electron hopping, respectively. The MD effect at high temperatures is attributed to the combination of magnetoresistance and Maxwell-Wagner effects.

We establish a correspondence between two structures arising in the geometry of hyperplane arrangements: Euclidean $\vee$-systems and real polyhedral Kähler (PK) arrangements. We prove that every irreducible Euclidean $\vee$-system determines a real PK arrangement, and conversely that every real PK arrangement arises this way. As a consequence, we show that, up to equivalence, there are exactly three irreducible rank-three Euclidean $\vee$-systems whose vectors have equal length; their arrangements are the mirrors of the reflection groups of the regular tetrahedron, cube, and icosahedron. The correspondence also yields a description of the moduli space of Euclidean $\vee$-systems in a fixed projective class: it is homeomorphic to the relative interior of a polytope. We also give a direct proof that the hyperplane arrangement associated with a Euclidean $\vee$-system is simplicial. Among the currently known simplicial line arrangements, we identify precisely those that arise from $\vee$-systems. As a consequence, we prove that the Schreiber–Veselov catalog is complete for irreducible rank-three Euclidean $\vee$-systems with at most $27$ vectors.

In this work, we present the initial results of a compact fast-neutron detection system based on the EJ-276D plastic scintillator, a dual-channel readout using two silicon photomultipliers (SiPMs) with complementary cell geometries, and a data acquisition (DAQ) system built on the StemLab Red Pitaya FPGA platform. The system combines the pulse shape discrimination (PSD) capability of EJ-276D with custom, cost-effective analog front-end electronics and open-source DAQ firmware. Unlike traditional systems relying on bulky photomultiplier tubes or liquid scintillator detectors, our design is portable and scalable. It achieves a Figure of Merit of 1.61 in the 2.75–3.0\,MeV$_{ee}$ energy range, comparable to established setups, while requiring only a single +5\,V USB power source. The results demonstrate the potential of this approach for in-situ neutron detection in mixed radiation fields, with the FPGA programmability of the Red Pitaya enabling straightforward adaptation to diverse academic and industrial applications.

Observations show that stellar coronal mass ejection (CME) candidates display relatively lower kinetic energies compared to expectations from solar flare-CME relations extrapolated to the stellar regime. This behaviour was predicted by studies of magnetic confinement of CMEs by strong large-scale stellar magnetic fields. However, the possible promoting role of stronger small-scale magnetic fields has not yet been properly explored in previous studies. In this work, we present the first parametric study that simultaneously incorporates both the promoting and confining effects of magnetic field strength on CME dynamics. We perform CME simulations with scaled solar magnetograms spanning <B_star> = 1, 5, 10, 50, 100 B_sun and inserting flux ropes whose magnetic energy is set to scale as E_FR \propt <B_star>^2. Our results show that CME speed and mass increase with magnetic field strength in this restrictive scenario, approximately following v_CME \propt <B_star> and M_CME \propt <B_star>^1.5. These trends indicate that, within this idealized solar-scaled framework, increasing the magnetic field strength enhances the net promoting forces relative to the confining forces and drives faster, more massive CMEs. We further identify the upward Lorentz force as the dominant contributor to the acceleration and the mass enhancement. We also conducted additional cases with different flux rope energies that do not follow the above scaling assumption, and found that stronger flux ropes produce faster and more massive CMEs for each given stellar model. The adopted scaling assumptions are intended as a controlled parametric experiment rather than a realistic model of young solar-type stars, and future work using more realistic stellar magnetic maps will be required to determine which regions of the parameter space explored here are most relevant to active stars.

Significant effort has been devoted over the past decade to understanding whether quantum resources can provide advantages in distributed computing, and in particular whether they can help overcome locality constraints in networks, typically in Linial's LOCAL model. Recently, Coiteux-Roy~et~al.~(STOC 2024) showed that quantum resources do not help for 3-coloring unrooted trees: in particular, their lower bound holds in the stronger non-signaling model, which formalizes the principle of physical causality in distributed computing. The case of rooted trees, however, was left open by their work. For rooted trees, the deterministic Cole-Vishkin algorithm 3-colors $n$-node trees in $O(\log^\star n)$ rounds, matching Linial's classical $\Omega(\log^\star n)$ lower bound (FOCS 1987). In this paper, we show that any algorithm in quantum-LOCAL (without pre-shared entanglement) that properly 3-colors $n$-node rooted trees with probability at least ${1-O(1/\log n)}$ must perform $\Omega(\log^\star n)$ rounds. That is, quantum resources provide no advantage for 3-coloring rooted trees. To get this result, we show a lower bound of $\Omega(\log^\star \Delta)$ for 3-coloring any $\Delta$-ary tree with success probability at least $1-1/\Delta$. The proof uses a color lifting technique that bears similarity to Linial's original argument. We also show, as a separate result, that 2-coloring even-length $n$-node cycles with probability $1-O(1/n)$ requires $n/2-1$ rounds in the quantum-LOCAL model, even with pre-shared entangled states. This improves the previously known $\lceil (n-2)/4 \rceil$ lower bound of Gavoille, Kosowski, and Markiewicz (DISC 2009) by a factor of two, and shows that quantum algorithms cannot save even a single round over classical deterministic algorithms for 2-coloring even-length cycles.

Biological aging is conventionally indexed by chronological time, yet every organism is a physical system tracing a worldline through spacetime, so the time available to its metabolism is not coordinate time $t$ but relativistic proper time $\tau$. Building on the established Principle of Biological Time Equivalence (PBTE), whose thermodynamic foundation and aging dynamics are taken here as prior results \citep{TayeBook2026,TayeAging2026,TayeCardiac2026}, we ask how internal physiological time relates to the proper time of physics. The central result is that biological age is an entropy-production functional evaluated along the proper-time worldline, \begin{equation*} A_PBTE=\frac{1}{\Sigma_ref}\int_{\tau_0}^{\tau_1}\dot\Sigma_p(\tau)\,d\tau, \qquad \frac{dA_PBTE}{dt}=\frac{\dot\Sigma_p}{\gamma\,\Sigma_ref}, \end{equation*} where $\dot\Sigma_p$ is entropy production per unit proper time in the local rest frame and $\gamma$ the Lorentz factor.

Quantum architecture search for molecular ground-state estimation is commonly evaluated through energy accuracy, which does not describe circuit cost or the physical properties of the prepared state. We introduce HamQASBench, a structure-aware benchmark comprising eleven molecular Hamiltonians of up to fourteen qubits, selected using Hamiltonian and target-state properties and supplied with exact references. Its evaluation protocol combines energy accuracy and success rates with reference-relative circuit cost, local entropy profiles for non-degenerate targets, and state identification within degenerate ground subspaces. Experiments with five methods spanning four search paradigms reveal differences hidden by energy-only comparisons. On a near-product instance under the shallow search budget, the best outputs of all five methods reach chemical accuracy while using between two and sixty-two gates. Equal-energy outputs on a degenerate instance occupy distinct spin components. Local entropy profiles distinguish inaccurate outputs and show that entangling-gate counts need not reflect realized entanglement. Across the molecular instance ladder, product-state outputs can meet or miss chemical accuracy, motivating interpretation of success alongside target-state properties. These results support retaining energy as the task-success criterion while using circuit-cost and state diagnostics for more informative comparisons. The benchmark instances, references, evaluation implementation, and per-run data are released for reuse.

Addressing the unique requirements for a wide field of view and rapid response in soft X-ray polarization measurements of transient sources such as gamma-ray bursts, this paper proposes the design of a high-reliability CubeSat payload electronics system for dual-satellite cooperative observation. The system employs a Gas Microchannel Pixel Detector (GMPD) and a Topmetal-L sensor as its core components, forming a highly integrated, low-noise payload hardware platform. It achieves a field of view of 90$^\circ$ $\times$ 90$^\circ$, a sensitive area of 3.69 cm$^{2}$, and a power consumption of less than 6 W, operating within an energy range of 2–10 keV. The system incorporates autonomous high-voltage (HV) ramp-up/ramp-down control and a dual-protection mechanism based on count rate and discharge events, enabling in-orbit responses to risks such as the South Atlantic Anomaly and solar particle events. It also supports single-event upset detection and recovery, as well as in-orbit firmware upgrades. The communication interface adopts a redundant primary/backup Controller Area Network (CAN) bus design, with measured channel switching times of less than 100 ms, meeting the demands for real-time command interaction in dual-satellite coordination. By utilizing a large-array pixel sensor with region-of-interest readout and integrating an in-orbit track compression algorithm, the system significantly reduces data storage and downlink transmission resource burdens. Ground tests demonstrate an equivalent noise charge of 22.35 e$^{-}$, HV monitoring linearity better than $\pm$0.5%, and an output range extending to -5 kV. Thermal vacuum cycling tests show no performance degradation after five cycles between -5 $^\circ$C and 40 $^\circ$C. This work demonstrates the system's capability for autonomous observation, intelligent coordination, and reliable operation in complex space environments.

Crystallization from chemically complex mixtures is governed not only by thermodynamic stability but also by kinetic competition among structurally related components during nucleation and growth. When multiple compatible molecules compete for incorporation into early nuclei, the number of possible local recognition motifs can expand, delaying access to productive crystalline pathways. Here, we investigate this effect using supersaturated aqueous mixtures of the canonical nucleobases adenine (A), thymine (T), and uracil (U) as a minimal model for competitive supramolecular crystallization. Time-resolved turbidity measurements showed that ternary A+T+U mixtures crystallize more slowly and less efficiently than selected binary systems, despite containing individually crystallizable components. This inhibition is consistent with competition-induced kinetic frustration, where structurally similar hydrogen-bonding partners compete during early nucleation, delaying formation of a productive crystalline nucleus. We then show that preformed A+T crystalline seeds rescue ordered growth from the ternary mixture. Seeding sharply reduces the lag time, increases the apparent nucleation/onset rate, and redirects the solid product toward the A+T crystalline pathway, as confirmed by HPLC. Thus, the seed acts not only as a nucleation accelerator but as a selector of molecular composition and assembly trajectory within a multicomponent solution. We describe this process as kinetic compression: the reduction of accessible supramolecular assembly pathways through amplifications of selected productive growth pathways. These findings establish seeded crystallization as a mechanism for selecting compositional pathways in competitive molecular mixtures and suggest a physical route by which ordered molecular subsets can emerge from chemically complex environments.

Soft lattices combined with strong electron-phonon coupling in metal halide perovskites result in a complex interplay between electronic and lattice degrees of freedom. This interplay complicates the interpretation of time-resolved excitation spectra like pump-probe spectra. Here, we develop a first-principles approach that combines a nonequilibrium extension of the Bethe-Salpeter equation with ab initio molecular dynamics to resolve the origin of transient absorption. This approach can quantitatively disentangle electronic and thermal lattice contributions across femtosecond-to-picosecond timescales. Exemplified with \ce{CH3NH3PbBr3}, we find that on the femtosecond scale, both X-ray and optical transient absorption spectra are dominated by electronic contributions: Photoinduced Coulomb screening weakens the effective electron-hole interaction and blueshifts the excitonic resonances, whereas Pauli blocking is negligible. On the picosecond scale, thermal lattice contributions become essential, with distinct mechanisms dominating different spectral regions: Lattice vibrations lead to spectral redistribution in the X-ray transient absorption spectrum, whereas lattice expansion blueshifts the optical transient absorption spectrum.

Elastic $n$-$^{16}$O scattering at low energies is studied in the framework of cluster effective field theory. An evaluated data set of the total cross section of elastic $n$-$^{16}$O scattering at neutron energy, $0\le E_n\le 4$~MeV, is adopted from Evaluated Nuclear Data File (ENDF/B-VIII.0). We derive an expression for the $S$ matrices of the elastic scattering for seven spin-partial wave channels, $lj=s_{1/2}$, $p_{1/2}$, $p_{3/2}$, $d_{3/2}$, $d_{5/2}$, $f_{5/2}$, $f_{7/2}$, including one excited state and nineteen resonant states of $^{17}$O. Thirty-four parameters of the theory are fitted to the ENDF data, and we find that a plotted line, by using the fitted parameters, reproduces the ENDF data well. We discuss the uncertainties that may appear in the present approach from the fitted parameters of the resonant states with widths, larger than $\Gamma = 90$~keV. We also discuss the implications of the fitted values of energies and widths of the resonant states in the estimate of the astrophysical $S$ factor of $^{13}$C($\alpha$,$n$)$^{16}$O reaction at stellar energies.

While complex-pole hierarchical equations of motion (HEOM) have dramatically expanded the reach of numerically exact quantum dynamics simulations of open quantum systems, they suffer from numerical instabilities rooted in the non-Hermitian structure of their Liouvillian. Yet, the origin of this structure remains obscure. Here, we report a previously unknown gauge freedom in complex-pole HEOM: a continuous family of analytically equivalent Liouvillians, all encoding the same bath correlation function, whose numerical properties vary dramatically. This gauge controls both the eigenspectrum and non-normality of the hierarchy generator, revealing spectral divergence and non-normal error amplification as two distinct instability mechanisms. By optimizing this gauge, we introduce GO–HEOM, which eliminates divergences in strongly coupled Brownian oscillator environments and extends numerically exact simulations of sub-Ohmic dynamics – including through the delocalized-to-localized quantum phase transition – to previously inaccessible coupling strengths. Because this gauge transformation is independent of the bath-correlation decomposition scheme, our GO–HEOM becomes a general, broadly compatible strategy for accessing numerically exact quantum dynamics of open quantum systems over arbitrary coupling and highly non-Markovian regimes.

We present a Bayesian P-spline method for estimating the frequency-dependent cross-spectral density matrix of stationary multivariate time series. The inverse spectral matrix is parametrised through its frequency-varying Cholesky decomposition, which guarantees Hermitian positive definiteness at every frequency. Each real log-diagonal entry and each real and imaginary off-diagonal entry is given an independent penalised B-spline prior that controls smoothness. Inference uses a blocked, coarse-grained Whittle likelihood with safe-Bayes $\eta$-tempering to stabilise posterior calibration, sampled by the No-U-Turn Sampler from a variational initialisation. On synthetic VAR(2) benchmarks with known ground truth, the method recovers both diagonal and cross-spectral structure, attains near-nominal credible-interval coverage, and achieves a relative integrated squared (Frobenius) error (RISE) that decreases with sample size. We then apply the method to publicly released simulated LISA time-delay interferometry (TDI) data in two noise configurations. In the idealised symmetric case, the full multivariate model and a reduced model that assumes a diagonal AET noise covariance agree to within $\sim10^{-3}$ in RISE. Under realistic noise that is asymmetric across the six Movable Optical Sub-Assemblies (MOSAs), the AET-diagonal assumption fails by more than an order of magnitude in RISE ($\sim\!3.3\!\times\!10^{-2}$ versus $\sim\!10^{-3}$), whereas the full multivariate model recovers the cross-spectral structure.

Context: Thanks to helioseismology, the rotation profile of the Sun has been measured with great precision down to 20% of its total radius. This rotation profile is used as a calibration to infer the rotation of other stars as well as a test of angular momentum transport theory in stellar interiors. However, the deepest 20% of the layers remain out of reach of current observations, preventing astronomers to discriminate between currently competing angular momentum transport mechanisms. Aims: The main obstacle is that no global oscillations modes sensitive to rotation (non-zero degree l) reaching the solar core have been detected yet, as nonradial p modes cannot reach it and g modes are evanescent at the surface and still elude detection. In this work, we propose and examine a new method to constrain the rotation of the core of the Sun, which does not require direct observation of solar g modes. Methods: It is based on a recent prediction that g modes in the radiative interior couple with f modes in the outer parts of the star. These mixed f /g are at the same time sensitive to the rotation of the core and able to reach the surface. These modes can be used together to build average inversion kernels and perform an inversion of the rotation of the solar core. Results: We find that the oscillations' spectrum of the Sun should present 6 mixed f /g modes that can be used to measure the rotation rate of the Sun at r = 0.07 and 0.2R. We estimate that the uncertainty on the measurements should be small enough to distinguish between competing scenarios of angular momentum transport in the Sun.

Biological theory usually treats time as an external chronological variable against which growth, aging, and ecological change are parametrized. Yet living systems also generate an internal measure of duration through physiological cycling and irreversible entropy production, and the regularities of allometric lifespan scaling, biological clocks, life-history evolution, ecological synchronization, and disease are ordinarily studied in isolation rather than within a single thermodynamic internal-time framework. The Principle of Biological Time Equivalence (PBTE) proposes such a framework.

Assessing the significance of magnetic fields in high-mass star formation remains one of the most challenging topics in astrophysics. In this study, we present full polarization observations obtained from the Atacama Large Millimeter/Submillimeter Array (ALMA) of the high-mass star-forming region IRAS18360-0537. The polarized dust emission at 1.3 mm reveals a clear hourglass-shaped morphology of the magnetic field. Interestingly, the magnetic field orientation is nearly perpendicular to both the outflow and core rotation axes, while it aligns with the elongation of the core. This orientation poses challenges for interpretation, particularly in light of the strong magnetic field strength estimated using the Davis-Chandrasekhar-Fermi method. Several scenarios provide insights into the underlying reasons for this magnetic field morphology. A clear velocity gradient seen in high-density tracing of molecular spectral lines indicates that the core is fast-rotating. The curved outskirts of the magnetic fields coincide with the outflow cavity, suggesting a possible influence from the outflow. The accretion flows along the core's elongation are also notable. Our study shows that the morphology of the magnetic field is probably highly influenced by the gas bulk motions.

Understanding how nanoconfinement alters the dynamics of glass-forming aqueous electrolytes is essential for clarifying the interplay among ionic hydration, hydrogen-bond structure, and interfacial effects. Here, LiCl.6H2O was investigated in the bulk and under confinement in SBA-15 mesoporous silica with an average pore diameter of 8 nm. Differential scanning calorimetry, Raman spectroscopy, quasielastic neutron scattering, 1 H spin-lattice relaxation, and pulsed-fieldgradient NMR were combined to probe thermal behavior, hydrogen-bond structure, local mobility, and translational transport over complementary time and length scales. The calorimetric results show that LiCl.6H2O remains glass-forming under confinement, while its thermal signature of the glass transition becomes slightly broader and shifted upward relative to the bulk. Raman spectra in the O-H stretching region indicate that the concentrated LiCl solution possesses a weakened and less tetrahedrally connected hydrogen-bond network compared with bulk water. On the subnanosecond timescale, elastic fixed-window analysis reveals reduced mean-squared displacements under confinement, demonstrating suppressed motional amplitudes inside the pores. Inelastic fixed-window neutron scattering scans analyzed within a jump-diffusion framework yield lower effective translational diffusion coefficients and longer residence times for the confined liquid, indicating that confinement mainly hinders translational escape from transient local environments. 1 H relaxometry further shows that confinement broadens the distribution of local proton fluctuation times, while PFG-NMR confirms that the measured long-range water mobility in bulk LiCl.6H2O solution is reduced relative to bulk water. While the present data do not resolve distinct interfacial and pore-centered populations in confined LiCl.6H2O, its dynamics are markedly altered across timescales, from the glassy to the liquid state, resulting in slower, spatially constrained, and more heterogeneous motions.

We employ nonrelativistic quantum electrodynamics with a unified description of two-body systems with spin-0 or spin-1/2 constituents, arbitrary masses, and arbitrary magnetic moments in rotational states with $L>1$, to present state-of-the-art theoretical predictions for muonic, kaonic, and antiprotonic atoms that have recently been measured or are targeted by upcoming experiments. We show that the theoretical accuracy can further be improved, opening the possibility of using precision spectroscopy of muonic and hadronic atoms for high-accuracy determinations of nuclear charge radii and nuclear electric dipole polarizabilities, and for testing the existence of hypothetical long-range hadronic interactions.

Tetrahydrofuran (THF) is a benchmark guest for probing clathrate hydrate thermodynamics because a stoichiometric aqueous solution (THF.17H2O) forms structure-II (sII) hydrate at ambient pressure with a well-defined dissociation temperature. Here, we combine differential scanning calorimetry (DSC) and wide-angle X-ray scattering (WAXS) in bulk and confined media to resolve how composition, pore filling, and cooling rate govern hydrate formation in SBA-15 mesoporous silica. Bulk DSC establishes mass-balanced enthalpies for ice and sII hydrate and confirms reversible dissociation/melting temperatures. In confinement, the heating traces separate into a Gibbs-Thomson depressed ice melt (= -14.7 $\pm$ 0.2 {\textdegree}C), an in-pore hydrate dissociation (= -13.2 $\pm$ 0.2 {\textdegree}C). Confined hydrate appears only when two criteria are met: near-percolating filling ($\phi$ = 1.0 -1.1 cm3/g) and sufficient THF ($\ge$ 1:16 mol:mol). Cooling-rate experiments (1.0 vs 0.5 {\textdegree}C/min) demonstrate that slower precooling increases the confined-hydrate fraction and reduces confined ice without shifting equilibrium temperatures: at $\phi$ = 1.1, the hydrate enthalpy rises by ~60% at 1:11 and ~54% at 1:14, but by $\le$ 17% at 1:16. Temperature-cycling tests show invariant reheating peak positions, indicating that capillarity and composition, rather than kinetic history, fix the liquidus and dissociation temperatures. WAXS indicates that the phase formed in pores is crystallographically identical to bulk sII. Finally, the variation of melting points ($\Delta$T___) plotted against inverse pore radius follows the Gibbs-Thomson law for both ice melting and hydrate dissociation, quantitatively linking the observed shifts to crystalline size and clarifying how confinement, cooling rate, and composition govern the competition between hydrate formation and water crystallization.

The anomalous Hall effect in antiferromagnetic metals has attracted considerable attention. Most known realizations involve itinerant $d$ electrons that simultaneously mediate charge transport and magnetic order. Here, we focus on $f$-electron materials, where localized magnetic moments and conduction electrons are hosted in different orbitals. We develop a theoretical framework to describe the impact of localized antiferromagnetic order on itinerant electrons. Applying this approach to the recently discovered $4f$ antiferromagnetic metal $\mathrm{Ce}_{2}\mathrm{Cu}\mathrm{Ge}_{6}$, we identify the origin of both the intrinsic anomalous Hall conductivity and the spin splitting of the energy bands as spin-dependent intersite hopping induced by nonlocal Kondo exchange coupling, rather than a Zeeman-type effective field acting locally on the conduction electrons.

Altermagnets exhibit momentum-dependent spin splitting without net magnetization, providing a unique platform where magnetic order, electronic structure and lattice dynamics intertwine. Here, using first-principles calculations, we demonstrate that the prototypical altermagnets CrSb and MnTe host locally chiral phonon modes carrying finite phonon angular momentum with a six-lobes $f$-wave texture in momentum space. Our results show that the chiral lattice motion originates from the pnictogen/chalcogen sublattice, while the altermagnetic spin splitting is generated by the magnetic transition-metal atoms, indicating that chiral lattice dynamics and altermagnetic electronic states originate from different atomic sublattices of the same crystal. In pristine compounds, at each valley, inversion symmetry suppresses the net phonon angular momentum despite local circular atomic motion. We further demonstrate that isoelectronic symmetry lowering induced by chemical substitution lifts this cancellation and generates finite valley phonon chirality, while keeping the altermagnetic nature of the compounds intact. Most importantly, we reveal that chiral phonons couple to momentum-dependent spin-split electronic bands through momentum-dependent electron-phonon interaction, producing characteristic modifications of the electronic structure, possibly accessible by photoemission experiments. Our results establish altermagnets as a promising platform for chiral phononics and spin-selective lattice control.

This study investigates the nonlinear dynamics of a test particle near the traversable wormhole throat under an external harmonic potential. One-dimensional radial perturbation analysis shows that the particle is locally linearly stable at the equilibrium position. However, for two-dimensional and high-energy cases, the system exhibits a nonlinear response, leading to large-scale chaos. The analysis indicates that, if the particle is confined on one side of the wormhole, the Poincare section will still retain Kolmogorov-Arnold-Moser (KAM) tori under extremely high-energy conditions, which is distinct from the chaos caused by the event horizon in the black hole. By studying another set of shape functions, the universality of this phase space structure is confirmed. This research clarifies the unique nonlinear dynamical mechanism of a traversable wormhole. It provides a new criterion, based on chaotic dynamics, for identifying black hole mimickers in strong-field astrophysical observations.

Observations of the interstellar medium (ISM) at Far-infrared(FIR) and sub-millimetre (sub-mm) wavelengths reveal a complex filamentary structure of dust and gas, which plays a pivotal role in both low and high mass star formation. Large scale identification and characterization of filaments is crucial to establish a link between the ISM and the star formation. We present Sutra, a machine learning based framework that unifies filament identification and beam-scale physical characterization within a single automated pipeline. The framework employs a U-Net architecture to perform supervised segmentation on column density maps and is trained on five nearby (<500pc) molecular clouds from the Herschel Gould Belt Survey (HGBS), using consensus skeletons constructed from the union of filaments identified by DisPerSE and getsf. Rather than reproducing broad intensity-based masks, Sutra predicts crest-likelihood maps focused on filament spines. Beyond identification, Sutra characterizes the filaments at the beam resolution by extracting radial profiles perpendicular to the crest and deriving local structural parameters. The framework provides a parameter-free, computationally efficient approach for consistent filaments identification and systematic investigation of their local properties and shows stable behaviour across varying background conditions in controlled synthetic tests. We demonstrate its application on selected regions from Aquila, Orion and Polaris molecular clouds, and compare the derived filament characteristics with those obtained using existing algorithms. Sutra robustly recovers filamentary structures consistent with cylindrical profiles, including in relatively low-intensity and low-contrast environments, making it well suited for both region-specific studies and large-scale statistical analyses of early-stage star formation and ISM structure.

Fast radio bursts (FRBs) are luminous extragalactic radio transients whose physical origins remain uncertain. Using over one thousand non-repeating events from CHIME/FRB Catalog 2, we infer the intrinsic FRB demographics with a self-consistent framework that combines backward non-parametric inference and forward population synthesis while accounting for probabilistic dispersion measure–redshift estimates, baseband-to-catalog fluence corrections, and the latest fuzzy multidimensional selection function. We first apply a backward non-parametric method, the weighted Lynden–Bell $C^{-}$ estimator, to recover the intrinsic redshift and energy distributions without assuming any population model. Independently, we perform forward Monte Carlo population synthesis in observable dispersion measure–fluence space, treating candidate intrinsic redshift and energy distributions as population hypotheses and comparing the resulting selected synthetic catalogs with observations. We find that the intrinsic redshift distribution peaks at $z\sim1$, significantly lower than the cosmic star formation history (SFH) peak at $z\sim1.7$, indicating clear tension with a pure SFH-tracking scenario, suggesting that at least some FRBs are delayed with respect to SFH. The intrinsic energy distribution is consistent with a power law of index $\alpha\approx1.9$ and steepens at higher energies. We find no significant evidence for a redshift-energy distribution correlation.

Finite quantum environments can relax local probes without acting as canonical baths. We study this distinction for a probe qubit coupled to a programmable bath of ($N$) qubits under excitation-number-conserving dynamics. The conserved charge partitions the Hilbert space into sectors. We characterize probe-level bath emergence using the sector-resolved late-time population ($p_e^{(q)}$), the sector-memory variance ($M_N$), and a global Gibbs-fit error ($\Delta_G^{\mathrm{global}}$). Exact simulations with Haar-random pure states in each complete fixed-charge sector yield sector-dependent populations close to the maximally mixed-sector benchmark ($p_e^{(q)}=q/(N+1)$), producing a nonzero Gibbs obstruction. We then construct charge-preserving Floquet circuits using ($R_z$) phases and ($XX+YY$) exchange gates, validate them with ideal and noisy Qiskit simulations, and implement finite-depth experiments on IBM Fez. For ($N=4$) and ($\epsilon=0$), the hardware data give ($M_N \simeq 0.044$), ($\Delta_G^{\mathrm{global}} \simeq 0.558$), and charge preservation near 0.90 after readout mitigation. A paired symmetry-breaking scan using bath ($R_x(\epsilon)$) rotations reduces both diagnostics while increasing charge leakage, but does not erase sector ordering over the accessible depths. These results show that equilibration within constrained sectors is insufficient to produce a single sector-independent Gibbs state for the probe.

The use of machine learning techniques to approximate computationally expensive models has become increasingly prevalent in a wide variety of fields within astronomy. We discuss the implementation of emulators for 1-dimensional models in the context of the astrophysical numerical model reltrans, a black hole X-ray spectral model that models the effects of relativistically smeared emission from an accretion disk. We argue that the decision of whether and how to emulate should follow from a systematic characterisation of the target model, and we demonstrate a diagnostic workflow: examining how the spectrum varies with individual parameters. We adopt a modular strategy, emulating only the relativistically convolved reflection spectrum (1-10% of the total flux) rather than the full model. Using an operator-learning architecture with Fourier feature embeddings and FiLM conditioning, we reproduce the reflection spectrum to O(0.1)% precision across 0.1-100 keV with a 4-10x speed-up that scales considerably better under vectorised evaluation. This emulator, RTFAST2, recovers the true parameters of simulated observations without the systematic posterior biases of our previous work. We conclude that no architecture is universally transferable and bespoke emulators motivated by a model's specific structure are required. The modular approach taken in this work presents a promising strategy for future emulators of numerical models.

Pulse experiments in the temporal analysis of products (TAP) reactor are one of the most important methods for studying transient kinetics of gas-solid catalytic reactions. The Y-procedure (Yablonsky et al., Chem. Eng. Sci. 62, 6754, 2007) is a model-free analysis framework for inferring the relationship between the reaction-rate $R$ and the reactant concentration $C$ from measurements of the outlet flux of gas. While elegant in conception, its application is hindered by the amplification of measurement noise that results from having to backtrack diffusive transport from the outlet to the reaction zone. Here, we explicitly recognize the inverse problem inherent in the Y-procedure and treat it using well-developed tools from the field of inverse problems. While previous implementations of the Y-procedure used Fourier-based filtering, we do not pre-process the measurements with an ad hoc noise-filter. Instead, we use a basis of localized square pulses to formulate a discrete inverse problem, whose regularized solution is obtained via the truncated singular value decomposition (TSVD) method. This method requires one to select a cutoff mode number; while we show how the choice of this regularization parameter can be guided by a Picard plot, we also develop an objective selection strategy for state defining experiments, for which $R(C)$ is a single-valued function. We apply our proposed inverse-problem approach to synthetic data corresponding to linear and nonlinear reactions and compare the results with the Fourier-filtration method. The former produces better reconstructions of the $R$ vs $C$ relationship, especially for nonlinear reactions. Our work facilitates the automation of pulse response analyses and enables the application of other discrete inverse-problem techniques, such as Tikhonov regularization or machine-learning methods.