Papers

In this thesis, quantum channels are studied from the point of view of Mathematics. We studied the CPTP (completely positive trace preserving) and UCPTP channels, the latter being the unital channels. In both cases, the sets are compact convex, so they are the closure of their extreme points. We constructed extreme CPTP maps for every possible rank. We also constructed extreme UCPTP maps with rank 2 for each possible dimension. For ranks of at least 3, we constructed extreme UCPTP maps for many dimensions and ranks. We also proved that the tensor product of extreme CPTP maps is an extreme CPTP map. For UCPTP maps, we proved that the same is not always true, with many counterexamples. It is known that the category of CPTP maps is semicartesian. We add to this a classification of binary products. We proved that products only exist in trivial cases. For binary coproducts, we obtained the dimensions they should have, if they exist. In both cases, topological techniques were used. For this reason, we also investigated the topology of the closure of the set of extreme points of the CPTP maps. Topological invariants can be computed from decompositions of a space such as CW structures. These are a type of decomposition in which the space is expressed as a gluing of balls. In the search for a CW structure for the closure of the set of extreme CPTP maps, we obtained a partial decomposition that resembles a CW structure of the complex projective space.

The advancement of modern integrated photonics is frequently bottlenecked by device design workflows that rely heavily on manual simulation and expert intuition. While inverse design offers an alternative, it remains constrained by expert supervision and a lack of end-to-end automation. To address these issues, we present VortexChat, an agentic framework for the autonomous, end-to-end inverse design of integrated photonic devices directly from natural language specifications. VortexChat couples a large language model (LLM) decision agent with topology generation, gradient-based refinement, and full-wave electromagnetic simulation. This closed-loop architecture enables the system to iteratively decompose design objectives, orchestrate computational tools, and update strategies based on feedback with minimal human intervention. Constrained by the absolute metrics of the Vortex100 Benchmark, VortexChat autonomously generates devices that strictly meet all predefined performance thresholds without any human-in-the-loop. As an experimental demonstration, we fabricated a broadband terahertz perfect vortex beam multiplexer, autonomously designed by VortexChat, with measurements confirming high-efficiency operation, high mode purity and low inter-channel crosstalk in agreement with full-wave simulations. These results demonstrate that an LLM agent can assume key aspects of expert decision-making in photonic inverse design while maintaining physical fidelity and fabrication feasibility, providing a scalable route towards autonomous design of complex integrated photonic systems.

Many scientific discovery problems require searching combinatorial hypothesis spaces under complex domain constraints. Reinforcement learning (RL) offers a promising approach, but existing methods rely on scalar rewards that provide limited information about why candidate solutions fail, leading agents to repeatedly explore invalid regions. We introduce Certification-Driven Reinforcement Learning (CDRL), a framework that leverages structured feedback from symbolic reasoning tools. When a candidate violates domain constraints, these tools produce certificates identifying the actions responsible for failure. CDRL converts these certificates into reusable constraints that eliminate classes of invalid solutions and guide exploration toward valid regions. We evaluate CDRL on neutrino flavor model discovery in theoretical particle physics, where the hypothesis space exceeds $10^{26}$ possible models, and compare it with the state-of-the-art RL approach previously used for this task. Across three theory spaces, CDRL achieves up to 1.95$\times$ higher valid model rates and up to 6.33$\times$ higher neutrino model rates while evaluating up to 4$\times$ fewer candidates. We further extract 40 interpretable rules from search trajectories using a post-hoc decision-tree framework and show that reusing them as soft constraints yields gains of up to 2$\times$ in valid model rates and 3$\times$ in neutrino model discovery across all three theory spaces. These results suggest that CDRL uncovers reusable structure in combinatorial search spaces and provides a general framework for scientific model discovery.

Reliable prediction of the energy confinement time is essential for magnetic-confinement fusion. Conventional power-law scalings provide constrained extrapolation trends but cannot represent complex nonlinearities, whereas neural networks interpolate accurately but may behave unpredictably outside the training distribution. We propose a unified power-law-anchored residual-learning framework in which a frozen empirical power-law scaling supplies the global trend and a nonlinear model learns only the systematic residual in logarithmic space. PLR-KAN is developed as the primary implementation, while a parameter-matched PLR-MLP serves as a controlled architecture replacement. Using the ITPA DB5.2.3 H-mode confinement database, we evaluate interpolation and parameter-defined held-out cohorts over ten complete training pipelines. PLR-KAN retains near-best interpolation accuracy, achieving R2=0.9671+/-0.0027, while substantially improving the stability of direct KAN under parameter-defined distribution shifts. It outperforms direct KAN across all five non-epsilon single-parameter-defined cohorts and the core-five joint cohort, reaching R2=0.9263+/-0.0157 in the latter. Results from PLR-MLP further demonstrate that the benefit of power-law anchoring is not specific to KAN, although the effectiveness of residual transfer remains architecture and direction dependent. As an exploratory extension, a Mahalanobis-distance-based prediction-time gate improves stability in selected shifted regions but is not universally beneficial and cannot compensate for missing device or physics-regime coverage. Overall, power-law-anchored residual learning provides a practical balance between nonlinear interpolation capability and empirically constrained extrapolation behavior.

We experimentally demonstrate continuous-angle logical $Z$ rotations in the $[[7,1,3]]$ Steane code on the IonQ Forte trapped-ion processor. A round of the protocol applies a transversal physical $Z$ rotation by $\theta$, followed by Steane syndrome extraction and decoding, which induces a syndrome-dependent logical $Z$ rotation. We analytically derive the effect of dephasing noise on the logical rotation angle and logical dephasing rate. Using logical Ramsey interferometry, we observe coherent syndrome-dependent logical rotations from a single round of the protocol. We find that the logical channel reconstructed from process tomography is a noisy logical $Z$ rotation well explained by a dephasing model. We further implement a two-round protocol applying physical rotations $+\theta$ and $-\theta$, and observe cancellation of the total logical angle with low logical dephasing for repeated trivial syndromes. This constitutes a proof-of-principle demonstration of continuously tunable non-Clifford logical gates by transversal rotations and standard error correction in a small quantum code.

Relativistic radio-galaxy jets are conventionally divided into two morphological classes: FR~I and FR~II. Among them, FR~I jets have relatively low radio luminosities and edge-darkened morphologies, indicating they undergo substantial deceleration and disruption on sub-kiloparsec to kiloparsec scales, often developing a turbulent and plume-like morphology. Here, we investigate the evolution of relativistic magnetized jets in stratified ambient media using 2D and 3D relativistic magnetohydrodynamic simulations with several ambient profiles. When the jet and ambient pressures are initially balanced, a Bondi-like atmosphere confines the jet to a broad parabolic shape ($R_j\propto z^{0.649\pm0.003}$) and produces a series of recollimation shocks. Over-pressured jets instead produce a conical shape and allow the development of the current-driven kink instability in the downstream. Based on the simulations, we derive a kink-stability criterion that depends primarily on the jet power and ambient pressure. We also calculate multi-frequency emission maps using a special relativistic radiative transfer code. Each recollimation shock appears as a bright knot, resembling the knot complex downstream of HST-1 of the M87 jet, whereas a jet with a single recollimation shock develops a bright feature close to its base and thus exhibits an FR~I-like morphology.

Microwave radiometer instruments are uniquely capable of studying volatile element abundances and heat/mass transport within the deep atmospheres of giant planets. The results of the Juno MWR experiment have challenged long-held assumptions regarding Jupiter's troposphere, and the inclusion of such an instrument on future missions to Saturn or the ice giants would similarly re-write our understanding of giant planet atmospheres. We present a high-level summary of the capabilities of microwave radiometers for the study of giant planet atmospheres, including a review of the various scientific motivations and current knowledge, concise statement of the fundamentals of radiometer remote sensing accessible at the systems-engineering level, and calculations which are of illustrative value in the design of future instruments.

While Digital sky surveys provide excellent throughput of image data and can cover a large footprint, their imaging power is normally inferior to that of space-based telescopes. Space-based telescopes, on the other hand, provide excellent imaging power and can image the deep Universe, but cannot provide the same throughput as advanced ground-based sky surveys. Here, we utilize generative AI to elevate the quality of galaxy images taken by ground-based telescopes to the level of details enabled by space telescopes. The solution is based on the nature of galaxy shapes, allowing generative AI trained on space-based images to convert weak signal into detailed and clear galaxy images. The method allows for combining the high throughput of ground-based sky surveys with the image quality of space-based telescopes. The source code for the method is available, as well as paired training data and a catalog of 63,202 galaxy images enhanced by the proposed method. We also provide a software tool that encapsulates the entire pipeline and the custom generative AI model to generate galaxy images with enhanced quality.

We consider the two-dimensional Dirac operator with constant magnetic field that is perturbed by a combination of electrostatic and Lorentz-scalar delta interactions with variable coefficients supported on a smooth closed curve. Self-adjointness is studied in the so called non critical and critical cases. In the non-critical case the essential spectrum is unchanged - it remains to be the set of the Landau-Dirac levels, the eigenvalues of infinite multiplicity of the unperturbed operator - while in the critical case an additional interval of essential spectrum emerges in the spectral gap containing zero. Our main result concerns the discrete spectrum in the non-critical case: using the pseudodifferential properties of the involved boundary integral operators, we show that the eigenvalues accumulate at each Landau-Dirac level at a rate governed by the logarithmic capacity of the curve. A novel and surprising phenomenon is the change in the side of the accumulation depending on the position relative to the critical value. As a byproduct, clusters of eigenvalues for a family of exterior boundary value problems are obtained via confining couplings; the infinite-mass boundary condition arises as a special case.

Surface hopping is an attractive mobility mode for small-body exploration, but designing fuel-optimal hops on asteroid 433~Eros requires solving a nonconvex optimal control problem with an irregular polyhedral gravity field, thrust–mass coupling, and collision-avoidance constraints. We show that a physics-informed Bayesian Optimization (BO) warm-start—a Gaussian-process search over a single Bézier control point that requires no offline training—provides a more reliable initialization for Sequential Convex Programming (SCP) than the standard straight-line guess. The straight chord penetrates the asteroid on every inter-site transfer considered here and degrades convergence. The physics-informed BO reference feeds an SCP stage in which a log-mass change of variables convexifies the thrust–mass coupling and nearest-facet half-spaces enforce collision avoidance, and an automated Pareto time-of-flight sweep selects fuel-priority solutions without introducing bilinear terms. Applied to all 20 ordered transfers among five representative surface sites and validated under 10 random seeds, the framework tracks every trajectory to meter-level terminal accuracy in closed-loop Monte Carlo simulation, completes a five-site tour for one fifth of the propellant budget, and reduces mean $\Delta V$ by roughly one third relative to an idealized two-impulse ballistic trajectory estimate. A straight-line ablation credits the warm-start with cutting the mean SCP iteration count from 8.8 to 5.9 and removing the one convergence failure. A target-perturbation analysis further shows that the solutions vary smoothly with the landing target, with no jumps between local basins.

Simulating a continuous-time quantum walk (CTQW) on a graph in the circuit model of quantum computing requires decomposing its Hamiltonian into terms that can be Trotterized into hardware-native gates. We consider two such decompositions: the standard Pauli decomposition and the recently introduced matching decomposition. Prior work suggests that the matching decomposition uses fewer CX gates on sparse graphs, while the Pauli decomposition uses fewer on denser graphs. Since CX gates dominate error and runtime on current hardware, we train machine learning models to predict, for a given graph, which of the two decompositions produces the smaller CX gate count. We train and evaluate on the complete population of all 11,117 connected eight-vertex graphs from Brendan McKay's database, so the class balance and overlap are measured directly rather than estimated. We use twelve features: ten topological properties of the graph and two that count the terms the Pauli and matching decompositions produce (n_Pauli and n_match), both computable without transpiling the simulation circuit. Standard topological properties alone provide little predictive power. Instead, the dominant signal comes from n_Pauli, a property of the Hamiltonian decomposition rather than an intrinsic property of the graph; degree variance is the only other feature that carries signal. Across a range of models the Matthews correlation coefficient (MCC) falls in a narrow band, from 0.569 untuned to 0.593 after tuning, so no single architecture stands out. We adopt a single-hidden-layer neural network at MCC 0.593. Applied frozen to a held-out, class-balanced test set of larger graphs (up to 256 vertices) from structured and Erdos-Renyi families, the model transfers, with MCC rising from 0.785 at N=8 to 1 at N>=64.

Hierarchical equations of motion(HEOM) provide exact dynamics of open quantum systems coupled to harmonic baths, but their computational cost becomes prohibitive for systems with many independent local environments. In this work, we develop a symmetry-adapted HEOM formalism to significantly reduce the computational cost for the permutationally invariant Holstein-Tavis-Cummings (HTC) model. The method removes redundant information in two stages. First, all auxiliary density operators (ADOs) related only by relabeling identical molecules and their bath channels are replaced by a single canonical occupation-pattern representative. Second, molecules with the same local hierarchy occupation produce repeated matrix elements within each representative, allowing only the distinct complex variables to be propagated instead of the full (N + 1) $\times$ (N + 1) ADO matrices. The resulting matrix-free equations are evaluated using precomputed connections and molecular multiplicities. At fixed hierarchy depth L and number of bath correlation exponentials m, the number of canonical representatives becomes independent of the ensemble size for N $\geq$ L and the number of unique variables saturates for N $\geq$ L + 2. The formulation easily extends to multiple-exponential bath decompositions, arbitrary initial density operators, static disorders, and cavity loss. Our benchmarks reproduce conventional HEOM dynamics while requiring far fewer propagated variables and substantially less memory.

A zero-dimensional (0D) multi-physics-constrained framework for parameter design and optimization of Stable Quasi-Isodynamic Designs (SQuIDs) is presented. Single- and multi-objective optimizations for three staged devices are carried out using an in-house stellarator 0D systems code: YF-1 for discharge demonstration, YF-2 for scientific break even, and YF-3 for a commercial demonstration plant. Pareto searches map the main design trade-offs across the three generations. The equal weight optima for YF-2 and YF-3 both lie in the electron-root favorable regime of the adopted root proxy: YF-2 recovers $Q_{phys} \sim 1$, while YF-3 reaches an ignited point at reactor scale. Future work will couple engineering feasibility and economic assessment modules for integrated plant evaluation.

We investigate the relativistic dynamics of network nonlocality in general $n$-local networks with chain and star topologies using the Unruh-DeWitt detector model. We show that the relativistic degradation of network nonlocality is strongly governed by the underlying topology. While chain networks suffer an irreversible sudden death of non-$n$-locality under relativistic motion, star networks exhibit remarkable resilience against relativistic decoherence. Most strikingly, a minimal star network with three peripheral nodes exhibits a remarkable sudden death-sudden birth transition of network nonlocality as the acceleration increases. This reentrant behavior reveals a dual role of the Unruh effect: it can both suppress and protect network nonlocality, offering a new perspective on the relativistic effects of acceleration on quantum networks. For larger star networks ($n>3$), non-$n$-local correlations persist over the entire acceleration regime. These insights provide valuable conceptual guidance for the structural optimization and design of acceleration-resilient architectures for future relativistic quantum communication and sensing protocols.

Transit Timing Variations (TTVs) are deviations from the time an observer would expect to see an exoplanet transit its host star. In multi-planetary systems, significant TTVs may indicate the presence of another body in the system gravitationally interacting with the transiting exoplanet. T. Holczer et al. (2016) catalogs 2599 Kepler Objects of Interest (KOIs) and provides a statistical analysis of their TTVs for candidates that have transited at least seven times. However, this conservative limit on the number of transits neglects long-period KOIs. Therefore, we extend the statistical analysis performed by T. Holczer et al. (2016) to the population of KOIs that have between three and six transits. We identify six KOIs, three of which have Kepler names (Kepler-103 c, Kepler-90 g, and Kepler-1662 c), with significant TTV signals that were originally overlooked by T. Holczer et al. (2016). Additionally, we search for trends regarding the planetary radius and orbital period of KOIs with significant TTVs. Through a survival analysis, we determine that planets with shorter orbital periods require larger TTV signals to be detected compared to longer period planets, regardless of planetary size. Uncovering trends in TTV statistics such as this one will provide targets for future forward modeling of planetary architectures.

Gaseous optics exhibit substantially higher laser-induced-damage thresholds than solid materials, enabling high-intensity operation without permanent degradation. In this Letter, we describe a gas-based beam dump and power meter that exploits the strong absorption of ozone in the Hartley band (200-320 nm). We develop and experimentally validate a model for ozone absorption that predicts the propagation length required for complete energy deposition and the resulting gas temperature rise. By calibrating the temperature rise against incident pulse energy, we demonstrate accurate millijoule-scale pulse energy measurements with an all-gas absorber. These results establish gas-phase absorbers as a scalable, debris-free platform for high-damage-threshold beam dumps and energy diagnostics for high-fluence lasers.

The detection of a stochastic gravitational-wave background (SGWB) is a primary science objective for the Laser Interferometer Space Antenna (LISA). However, extracting these signals is difficult because both the signal and the instrumental noise are stochastic and overlapping in the millihertz band. In this work, we present a Bayesian framework for the joint estimation of LISA noise and SGWB signals. Our approach models the LISA instrumental noise using flexible log-penalized splines, employing a roughness penalty to prevent overfitting while maintaining computational efficiency. For the SGWB, we compare a power-law model with a spline-based model and study how the choice of signal model and noise prior affects signal recovery and detection. Using simulated LISA data, we find that the power-law model gives tighter estimates when the signal follows the assumed shape. However, it fails to recover a localized spectral feature that is not described by a power law, causing the signal to be absorbed by the instrumental-noise spline. The fully spline-based model is less restrictive and successfully recovers such features. We also find that stronger prior information about the test-mass noise helps reduce the degeneracy between the noise and SGWB models at low frequencies, improving signal detection. These results reflect a single trade-off: added model flexibility reduces sensitivity when the assumed signal shape is correct, and prevents bias when it is not.

A Bell violation by material probes certifies nonlocal behavior, but it does not identify which internal subsystem carried or was measured to produce that behavior. We determine the additional information required to attribute such a violation to a gravitational field. For any setting-independent field-to-probe channel completed before the Bell settings are chosen, an entanglement-breaking channel makes all induced field measurements jointly measurable. A static Newtonian phase pickup belongs to this class, even with arbitrary adaptive probe control. Applied to a recent four-mass proposal, the claimed field-only measurements obey the stronger CHSH bound \(\sqrt2\), whereas the Bell-active operation is the source-to-probe instrument that includes the coherent source herald. At the published parameters, the observed flagged behavior is at least \(0.1630\) from the claimed field-detector family, exceeding its \(0.0898\) distance from Bell locality. We then incorporate a common field slice, gravitational constraints, dressing, detector backreaction, and coherent references into a robust certification theorem. The result isolates the minimum missing information: field-only factorization and a local measurement- incompatibility witness on each wing. More precise phase data cannot replace either requirement.

We develop a double-null framework for Cauchy-horizon dynamics in metric $f(R)$ gravity that separates ordinary mass inflation from scalaron cancellation and genuine escape from the blueshift instability. Starting from the exact spherical Hawking-mass transport equation, we show that a regular nondegenerate Cauchy horizon undergoes mass inflation whenever the effective longitudinal source is eventually nonnegative, uniformly dominates the mixed channel, and has a divergent blueshift-weighted integral. Hence bounded mass requires sufficiently strong blueshift-integrable suppression of this source or an independent competing channel. We then analyze the weaker branch in which the scalaron cancels only the leading Price-tail contribution. Under non-cancelling transverse and trace asymptotics, this forces $|R|\to\infty$ and an asymptotically linear high-curvature theory, $f(R)/R\to F_->0$, where $F_-\equiv\lim_{v\to\infty}f_R$. The curvature coefficient is fixed explicitly by the transverse asymptotics. For regular model classes with a finite high-curvature $f_{RR}$ limit one obtains $f_{RR}\to0$. More sharply, every eventually viable branch with $f_{RR}>0$ is forced to $R\to-\infty$ and $\Lambda_\infty>-1$; the standard scalaron mass parameter then diverges, while an additional differentiable rate condition yields $m_{\rm sc}^2\sim F/(3f_{RR})\to+\infty$. In the Einstein frame the scalaron null kinetic contribution is nonnegative, so the Jordan-frame cancellation cannot be interpreted as negative scalaron null energy. The result is a local rigidity classification rather than a global theorem of strong cosmic censorship.

Closed-loop discovery systems increasingly execute experiments and update decisions autonomously, turning record integrity into part of the experimental apparatus. We show that false-science induction arises when legitimate physical objects and measurements are paired incorrectly, driving neural surrogates to faithfully learn record-induced associations that do not correspond to the true object-outcome relationship while marginal data distributions remain unchanged. Across green fluorescent protein fitness and materials band-gap prediction loops, coherent paired misbinding systematically redirects experimental budgets toward low-performing basins, whereas same-volume random swaps have negligible effects. These observations identify error coherence, rather than raw error frequency, as the primary variable controlling this budget misallocation in the tested loops. The resulting binding identifiability boundary supports monitored-axis quarantines and feedback-conflict triage, which intercept over-concentrated proposals before execution and isolate the corrupted hypothesis axis.

Extreme events (EEs) in chaotic dynamics are rare broad excursions whose forecastability can be altered by dynamical noise. We investigate how noise changes EE occurrence and prediction skill across forecast horizons in a third-order autonomous chaotic flow. A single clean-data threshold is frozen for all realizations, broad events are defined by one maximum per excursion, and a future window W=15 is predicted from a 15-time-unit history using HistGradientBoosting with chronological data separation. As the forecast gap G between the observed history and the future event window increases, the clean Matthews correlation coefficient (MCC) decreases from 0.641 at G=0 to 0.165 at G=15. Noise dependence is evaluated with ten paired realizations at eight amplitudes. The mean short-horizon score increases from 0.456 in clean data to 0.546 at sigma=0.007; the paired gain is 0.0895 (95% CI 0.0494-0.1295; Holm-adjusted p=0.0234). Noise strongly increases EE occurrence while event amplitude and width remain comparatively stable. Equalizing positive training counts across noise levels substantially attenuates the short-horizon gain, whereas strong noise reduces intermediate-horizon skill. We term this horizon-dependent, nonuniform change in forecast skill noise-induced predictability redistribution (NIPR).

The dispersion interaction between two infinite sheets of graphene located on a substrate is considered based on the Lifshitz formula, taking temperature into account. The result is obtained in the form of a series that is easy to calculate. The influence of the interband conductivity of graphene, which turned out to be small, is examined.

Fusion research is progressing from physics-oriented experiments toward reactor-oriented engineering applications, placing increasing demands on the accuracy and reliability of neutron measurements. This review summarizes the current status and prospects of neutron detection and neutron/gamma discrimination technologies for fusion applications. The main sources, energy characteristics, and measurement requirements of fusion neutrons are first reviewed, with particular attention to 2.45 MeV D-D and 14.1 MeV D-T neutrons. Four principal neutron detection methods, including nuclear reaction, nuclear recoil, nuclear fission, and neutron activation, are discussed together with the operating characteristics and applicability of scintillation, gas, semiconductor, and other specialized detectors. The roles of neutron/gamma discrimination are then examined in plasma diagnostics, safe operation monitoring, radiation protection monitoring, and fusion reactor design. The review shows that different detection methods and detector types have distinct advantages and application boundaries, and no single detector provides an optimal solution for all fusion measurement tasks. Liquid scintillators and some organic crystals remain important for fast-neutron measurement and neutron/gamma discrimination, whereas gas and semiconductor detectors serve complementary roles in thermal-neutron monitoring, compact detection, radiation tolerance, and fast-neutron spectrometry. Future development is expected to focus on high-performance detectors, material damage assessment, intelligent real-time discrimination, and multi-detector coordination with system-level diagnostic integration.

The discovery of radar echoes from meteor trains at Jodrell Bank in 1945 marked the beginning of a new era in meteor astronomy and laid the foundations for the subsequent development of radio astronomy. This paper examines the close relationship between Bernard Lovell's emerging research group at Jodrell Bank and the British Astronomical Association (BAA) during the formative years, 1946-1951. It explores the contributions of the individuals who connected these two communities. Particular attention is given to the lives and scientific careers of Michael Ovenden, Gerald Hawkins, John Clegg, John Davies, Victor Hughes and Mary Almond, all of whom were BAA members. Their later achievements demonstrate the remarkable talents of this generation of scientists, whose work extended across radio astronomy, planetary science, palaeomagnetism, archaeomagnetism and computer science.

Using the Geant4 and OpenMC Monte Carlo codes, the energy spectra of moderated neutrons were studied in homogeneous uranium dicarbide and uranium dioxide media, as well as in heterogeneous uranium and carbon and thorium and carbon channel type fission structures with various compositions and lattice parameters. In homogeneous uranium dicarbide the spectral maximum lies in the from 20 to 50 keV range, which is important for the design of a prototype fast single channel reactor operating in the traveling wave fission mode with a soft fast neutron spectrum. A heterogeneous thorium and carbon medium that forms a thermal neutron spectrum has been identified, enabling the realization of a traveling wave mode of neutron nuclear fission on thermal neutrons. By varying channel lattice parameters and introducing burnable absorbers (Cd, In), the possibility of forming a super thermal neutron spectrum (from 1 to 20 eV) in a heterogeneous uranium and carbon medium was demonstrated. The results are useful for the development of nuclear transmutation reactors and next generation reactors operating in the traveling wave mode.

We investigate generalized Kennedy receivers for coherent-state BPSK communication over turbulent free-space optical channels. An ergodic mutual-information framework is developed to jointly optimize the receiver displacement and input prior probabilities under Gamma–Gamma fading.

We investigate the phase diagram of a non-Hermitian XY chain with staggered Dzyaloshinskii–Moriya (DM) interactions using quantum-information methods. Through an alternating local-spin-rotation transformation, the model is mapped onto a standard DM-free XY chain, and the resulting transformed Hamiltonian exhibits rotation–time-reversal ($\RT$) symmetry. Combining correlation-function analysis with known phase results of the standard XY chain, we construct the phase diagram for the present system. We further adopt quantum-information-based quantities to systematically assess their performance in characterizing quantum phase transitions within this non-Hermitian system. Our results show that single-site entanglement can only detect the Luttinger-liquid (LL)–paramagnetic (PM) phase transition, which corresponds to the exceptional boundary across which $\RT$ symmetry is restored. In contrast, quantum discord (QD) and quantum coherence (QC) identify both phase boundaries: in addition to locating the exceptional boundary, their second-order derivatives resolve the ferromagnetic (FM)–LL transition inside the $\RT$-broken region. Moreover, measurements of QC along different directions capture the DM-induced relative rotation between the two sublattices, thereby distinguishing the staggered-DM chain from a zero-DM chain with identical effective parameters.

We investigate the Lee–Yang zeros (LYZ) of inhomogeneous anisotropic XY spin chains with Dzyaloshinskii–Moriya (DM) interactions in the complex transverse-field plane, focusing on their fundamental connection to quantum phase transitions. We systematically study uniform chains, period-2 and period-3 modulated chains, and Fibonacci quasiperiodic chains of lengths 5 and 8. As the DM coupling strength $D$ increases, the LYZ exhibit qualitatively distinct topological evolutions on the complex plane: the complex zeros of the uniform chain collapse toward the real axis; periodic chains feature either bifurcation of closed zero contours before all zeros become real or a single re-emergence of complex zeros; quasiperiodic chains exhibit repeated annihilation and revival of complex zeros. Analytical derivations demonstrate that this diverse behavior originates from DM-induced shifts of folded bands and the modulation of zero positions by anisotropic pairing at particle–hole band crossings. Our results establish a direct correspondence between LYZ topology and band deformation: isolated contact points of zeros with the real axis correspond to discrete quantum critical fields, while continuous real-zero intervals directly identify gapless chiral phases. Accordingly, beyond locating phase boundaries, LYZ can distinguish characteristic phases and serve as an intuitive probe for band folding and phase diagram restructuring.

Excitation functions for the $^{nat}$Sr($d,x$) reactions producing $^{86m,g}$Y, $^{87m,g}$Y, and $^{88}$Y were measured up to 24-MeV deuteron energy using the stacked-foil technique and gamma-ray spectrometry. The $^{nat}$Sr targets were prepared using an inkjet printing method to ensure sufficient uniformity. To the best of our knowledge, this is the first experimental report of excitation functions measured using inkjet-printed targets, demonstrating the applicability of this technique to cross-section measurements. The measured cross sections were discussed in comparison with literature data and TENDL-2023 predictions. Our cross sections were generally consistent with those reported in the previous study, but were slightly higher in the threshold energy region. The TENDL-2023 library generally overestimates the experimental values. We report the experimental cross sections for the $^{nat}$Sr($d,x$)$^{86m}$Y reaction for the first time. These measured cross sections contribute to the refinement of nuclear reaction databases for practical applications.

Laser-induced-desorption quadrupole-mass-spectrometry (LID-QMS) diagnostics is considered as one of the candidate methods for the remote control of tritium inventory in the ITER first wall. Studies involving LID-QMS generally assume the circular shape of the laser spot on the analyzed surface. At the same time, the diagnostics laser source cannot be always positioned so as to irradiate tokamak tiles under normal angles, which results in the laser spot shape differing from the circular one. In this contribution, we analyze the tritium removal process under sample irradiation by an elliptic Gaussian laser beam, extending the results of our previous analysis [A.A. Stepanenko, Yu.M. Gasparyan, Physica Scripta 99 (8), 085604 (2025)]. The thermal desorption model governing the heat transport and tritium removal from the solid is formulated. The new analytical expression describing the sample temperature dynamics is derived. The developed model is used to examine the impact of the laser beam/spot ellipticity on the tritium desorption process from a tungsten sample. The conditions, under which the elliptic beam can be approximated with the circular one for the rapid assessment of the amount of desorbed tritium, are assessed.