Motivated by recent results in spin chains we study dissipation and relaxation in a two-dimensional holographic interface conformal field theory (ICFT) in which degrees of freedom on one side of the interface are coupled to an external bath, while the other side remains isolated. In the bulk description this setup is realized by gluing a supersymmetric Janus geometry to a BTZ black hole region, with the coupling implemented through a double-trace deformation. We determine the quasinormal modes in the bulk by solving the double-trace matching conditions of the system and bath. The lowest imaginary part of the modes defines a Liouvillian gap, and following earlier work in spin chains we introduce the dimensionless ratio crelax as a measure of interface-induced suppression of relaxation. Numerically we find that, crelax is independent of coupling details to the bath. It is a strong candidate for a universal interface observable characterizing dissipation and relaxation across the interface.

Asynchronous Many-Task (AMT) runtimes offer a productive alternative to the Message Passing Interface (MPI). However, the diverse AMT landscape makes fair comparisons challenging. Task Bench, proposed by Slaughter et al., addresses this challenge through a parameterized framework for evaluating parallel programming systems. This work integrates two recent cluster AMTs, Itoyori and ItoyoriFBC, into Task Bench for comprehensive evaluation against MPI and HPX. Itoyori employs a Partitioned Global Address Space (PGAS) model with RDMA-based work stealing, while ItoyoriFBC extends it with futurebased synchronization. We evaluate these systems in terms of both performance and programmer productivity. Performance is assessed across various configurations, including compute-bound kernels, weak scaling, and both imbalanced and communication-intensive patterns. Performance is quantified using application efficiency, i.e., the percentage of maximum performance achieved, and the Minimum Effective Task Granularity (METG), i.e., the smallest task duration before runtime overheads dominate. Programmer productivity is quantified using Lines of Code (LOC) and the Number of Library Constructs (NLC). Our results reveal distinct trade-offs. MPI achieves the highest efficiency for regular, communication-light workloads but requires verbose, lowlevel code. HPX maintains stable efficiency under load imbalance across varying node counts, yet ranks last in productivity metrics, demonstrating that AMTs do not inherently guarantee improved productivity over MPI. Itoyori achieves the highest efficiency in communication-intensive configurations while leading in programmer productivity. ItoyoriFBC exhibits slightly lower efficiency than Itoyori, though its future-based synchronization offers potential for expressing irregular workloads.

In random matrices with independent and continuous matrix entries, the degeneracy probability of the eigenvalues is known to be zero. In this paper, random matrices including discontinuous matrix entries are analyzed in order to observe how degeneracy is generated. Using Erdös-Rényi matching probability theory of random bipartite graphs, we asymptotically evaluate the degeneracy probability of such random matrices. As a result, due to accumulation of the eigenvalues to the origin, a positive degeneracy probability is found for eigenvalues of a sparse random matrix model.

We study the CHSH inequality from an informational, timing-sensitive viewpoint using game-theoretic probability, which avoids assuming an underlying probability space. The locality loophole and the measurement-dependence (``freedom-of-choice'') loophole are reformulated as structural constraints in a sequential hidden-variable game between Scientists and Nature. We construct a loopholes-closed game with capital processes that test (i) convergence of empirical conditional frequencies to the CHSH correlations and (ii) the absence of systematic correlations between measurement settings and Nature's hidden-variable assignments, and prove that Nature cannot satisfy both simultaneously: at least one capital process must diverge. This yields an operational winning strategy for Scientists and a game-theoretic probabilistic interpretation of experimentally observed CHSH violations.

In this paper, we explore the implications of the finiteness of complete intersection dimensions for RHom complexes and Ext modules. We prove various stability results and criteria for detecting finite complete intersection homological dimension of complexes and modules. In addition, we introduce and explore the concept of CI-perfect modules. We also study the vanishing of Ext when certain Hom module have finite complete intersection homological dimension. In this direction, we improve a result by Ghosh and Samanta, prove the Auslander-Reiten conjecture for finitely generated modules $M$ over a Noetherian local ring $R$ such that $\operatorname{Hom}_R(M,R)$ or $\operatorname{Hom}_R(M,M)$ has finite complete intersection injective dimension, and provide Gorenstein criteria.

Conformal novelty detection is a classical machine learning task for which uncertainty quantification is essential for providing reliable results. Recent work has shown that the BH procedure applied to conformal p-values controls the false discovery rate (FDR). Unfortunately, the BH procedure can lead to over-optimistic assessments near the rejection threshold, with an increase of false discoveries at the margin as pointed out by Soloff et al. (2024). This issue is solved therein by the support line (SL) correction, which is proven to control the boundary false discovery rate (bFDR) in the independent, non-conformal setting. The present work extends the SL method to the conformal setting: first, we show that the SL procedure can violate the bFDR control in this specific setting. Second, we propose several alternatives that provably control the bFDR in the conformal setting. Finally, numerical experiments with both synthetic and real data support our theoretical findings and show the relevance of the new proposed procedures.

This paper examines the simplest case of total differential equations that appears in the theory of foliation structures, without imposing the smoothness assumptions. This leads to a peculiar asymmetry in the differentiability of solutions. To resolve this asymmetry, this paper focuses on the differentiability of the integral manifold. When the system is locally Lipschitz, a solution is ensured to be only locally Lipschitz, but the integral manifolds must be $C^1$. When the system is $C^k$, we can only ensure the existence of a $C^k$ solution, but the integral manifolds must be $C^{k+1}$. In addition, we see a counterexample in which the system is $C^1$, but there is no $C^2$ solution. Moreover, we characterize a minimizer of an optimization problem whose objective function is a quasi-convex solution to a total differential equation. In this connection, we examine two necessary and sufficient conditions for the system in which any solution is quasi-convex.

We study settings in which a researcher has an instrumental variable (IV) and seeks to evaluate the effects of a counterfactual policy that alters treatment assignment, such as a directive encouraging randomly assigned judges to release more defendants. We develop a general and computationally tractable framework for computing sharp bounds on the effects of such policies. Our approach does not require the often tenuous IV monotonicity assumption. Moreover, for an important class of policy exercises, we show that IV monotonicity -- while crucial for a causal interpretation of two-stage least squares -- does not tighten the bounds on the counterfactual policy impact. We analyze the identifying power of alternative restrictions, including the policy invariance assumption used in the marginal treatment effect literature, and develop a relaxation of this assumption. We illustrate our framework using applications to quasi-random assignment of bail judges in New York City and prosecutors in Massachusetts.

The Krauss-Nasri-Trodden (KNT) model provides a unified framework for addressing the smallness of neutrino masses (by a three-loop radiative mechanism) and the dark matter abundance (via thermal freeze-out) simultaneously. In this work, we investigate the implications of renormalization group effects on the model's parameter space. To this end, we perform a Markov Chain Monte Carlo analysis to identify the viable regions of parameter space that is consistent with all the relevant experimental and theoretical constraints at low energies. We show that a significant portion of the low-energy viable region is incompatible with the vacuum stability conditions once the renormalization group effects are taken into account. Most of the remaining parameter space of the model can be probed in future charged lepton flavor violating experiments.

Quantum entanglement routing in dynamic Low Earth Orbit (LEO) satellite networks is important for achieving scalable and high-fidelity quantum communication. However, the dynamic characteristics of satellite network topology, limited quantum resources, and strict coherence time constraints pose significant challenges to reliable entanglement routing. An entanglement distribution analysis model for this unique environment is critical and helpful for entanglement routing research. We address the fundamental challenge of establishing and maintaining quantum entanglement links between satellites operating in free space, where links are subject to both transmission losses and quantum memory decoherence. This paper presents a comprehensive Markov chain model with a state space defined by link storage age and physical distance for analyzing entanglement distribution in noisy dynamic LEO satellite quantum networks. We construct transition matrices that capture system dynamics under varying request arrival rates, and derive analytical expressions for key performance metrics, including request satisfaction rate, average waiting time, link utilization efficiency, and average consumed link fidelity. Our analysis reveals that the critical trade-offs of higher request rates lead to faster link consumption with higher fidelity but potentially lower satisfaction rates, while lower request rates allow longer storage times at the cost of lower fidelity of increased decoherence effect. Moreover, this paper proves it is reasonable to leave out polarization rotation when the transmission distance is very short (40-50 km). In summary, this work provides theoretical foundations for designing and optimizing quantum entanglement distribution strategies in satellite networks, with applications to global-scale quantum communications.

We construct a manifestly covariant and coordinate-free plane-wave representation of scalar two-point functions in $d$-dimensional anti-de Sitter spacetime. The construction is based on a new class of holomorphic plane waves defined globally on the universal covering of the AdS via chiral cones in the complex null cone. Imposing AdS invariance, locality, positive definiteness and a spectral condition, we obtain integral representations as superpositions over relative homology cycles reproducing the standard maximally analytic solutions in terms of Legendre functions of the second kind. In Poincaré coordinates, the two-point functions diagonalize into a Kallen-Lehmann superposition of (d-1)-dimensional Minkowski correlators where the weight is a product of Bessel functions. This diagonalization clarifies the relation between Euclidean and Lorentzian AdS quantum field theory and allows Wick rotation of Euclidean Feynman diagrams to Lorentzian integrals supported on a single Poincare patch while preserving full AdS covariance.

Parallel programming remains one of the most challenging aspects of High-Performance Computing (HPC), requiring deep knowledge of synchronization, communication, and memory models. While modern C++ standards and frameworks like OpenMP and MPI have simplified parallelism, mastering these paradigms is still complex. Recently, Large Language Models (LLMs) have shown promise in automating code generation, but their effectiveness in producing correct and efficient HPC code is not well understood. In this work, we systematically evaluate leading LLMs including ChatGPT 4 and 5, Claude, and LLaMA on the task of generating C++ implementations of the Mandelbrot set using shared-memory, directive-based, and distributed-memory paradigms. Each generated program is compiled and executed with GCC 11.5.0 to assess its correctness, robustness, and scalability. Results show that ChatGPT-4 and ChatGPT-5 achieve strong syntactic precision and scalable performance.

The James Webb Space Telescope (JWST) has recently identified Abell 2744-QSO1 as a compact, metal-poor, black hole (BH) dominated galaxy at $z\simeq 7$. This system exhibits an extreme black-hole-to-stellar mass ratio and unusually low metallicity, posing significant challenges to BH seeding models. Motivated by these discoveries, we perform high-resolution cosmological simulations with a massive primordial black hole (PBH; $M_{\rm BH}=5\times10^7\,M_\odot$) seed, incorporating for the first time a fully coupled treatment of PBH accretion, BH feedback, and Population~III/II star formation and stellar feedback. Although PBHs accelerate structure formation through the seed effect, the associated strong thermal feedback from the accretion delays the onset of star formation to $z\lesssim 10$, producing short, bursty episodes throughout the subsequent evolution. PBH-driven outflows expel enriched gas from the nucleus, while sustained inflows from the intergalactic medium continuously replenish pristine material. This feedback-regulated cycle naturally yields low accretion rates ($\dot{m}_{\rm BH}/\dot{m}_{\rm edd} \sim 1-10\%$), subsolar metallicities ($Z/Z_\odot\lesssim10^{-2}$) and extreme $M_{\rm BH}/M_\star$ ratios during both the initial star-forming phase and the subsequent quenching phases, in excellent agreement with JWST observations. Our results demonstrate that massive PBHs offer a viable pathway for forming the most extreme high-redshift systems, providing a physically motivated explanation for the extraordinary properties of Abell 2744-QSO1, as a sub-class of the broader population of JWST-discovered "little red dots".

We investigate how deviations from the Bekenstein-Hawking entropy modify black-hole spacetimes through the recently proposed entropy-geometry correspondence. For four representative modified entropies, namely Barrow, Rényi, Kaniadakis, and logarithmic, we derive the corresponding effective metrics and analyze their thermodynamic and topological classification using the off-shell free energy and winding numbers. We show that Barrow and Rényi entropies yield a single unstable sector with global charge $W=-1$, while logarithmic and Kaniadakis corrections produce canceling defects with $W=0$, revealing topological structures absent in the Schwarzschild case. Using the modified metrics, we further calculate the photon-sphere radius and shadow size, showing that each modified entropy relation induces characteristic optical shifts. Thus, by comparing with Event Horizon Telescope observations of Sgr A$^\ast$, we extract new bounds on all entropy-deformation parameters. Our results demonstrate that thermodynamic topology, together with photon-sphere phenomenology, offers a viable way to test generalized entropy frameworks and probe departures from the Bekenstein-Hawking area law.

We develop a statistical framework for empirical Bayes learning from selectively reported confidence intervals, and apply it to provide context for interpreting results published in MEDLINE abstracts. We use a collection of 326,060 z-scores from MEDLINE abstracts (2000-2018) as the input for an empirical Bayes analysis, with publication bias as a key methodological challenge. We address publication bias through a selective tilting approach that extends empirical Bayes confidence intervals to truncated sampling. Our framework provides coverage guarantees for functionals including posterior estimands describing idealized replications and the symmetrized posterior mean, which we justify decision-theoretically as optimal among sign-equivariant (odd) estimators.

Let $L$ be a big and semipositive line bundle on a complex projective manifold $X$, and let $θ\in c_1(L)$ be a smooth semipositive representative. In the adjoint setting $H^0(X,L^k\otimes K_X)$, we prove that Donaldson's quantized Monge--Ampère energy converges to the Monge--Ampère energy for every bounded $θ$-plurisubharmonic function. This extends the quantization picture from the ample case to the big and semipositive setting, where smooth positive representatives are no longer available and non-pluripolar Monge--Ampère theory is required. The main new input is a comparison theorem between adjoint Bergman kernels and their small ample twists. As a consequence, we prove that the normalized adjoint Bergman measures converge weakly to the corresponding non-pluripolar Monge--Ampère measures. Our result partially answers a question of Berman--Freixas i Montplet concerning the convergence of quantized Monge--Ampère energies in the semipositive setting.

We introduce the Morph approximation, a class of product approximations of probability densities that selects low-order disjoint parameter blocks by maximizing the sum of their total correlations. We use the posterior approximation via Morph as the importance distribution in optimal bridge sampling. We denote this procedure by MorphZ, which serves as a post-processing estimator of the marginal likelihood. The MorphZ estimator requires only posterior samples, and is fully agnostic regarding the choice of sampler. We evaluate MorphZ's performance across statistical benchmarks, pulsar timing array (PTA) models, compact binary coalescence (CBC) gravitational-wave (GW) simulations and the GW150914 event. Across these applications, spanning low to high dimensionalities, MorphZ yields accurate evidence estimates at substantially reduced computational cost relative to standard approaches. We have found that when these approaches fail to provide accurate estimates, MorphZ has proven to either resolve the estimation failure or significantly improve the results. Its bridge sampling relative error diagnostic provides conservative uncertainty estimates. Because MorphZ operates directly on posterior draws, it complements exploration-oriented samplers by enabling fast and reliable evidence estimation, while it can be seamlessly integrated into existing inference workflows.

Using light to manipulate small particles is a powerful tool with numerous practical applications across biophysics and nanotechnology. This experimental technique has achieved significant performance gains by employing shaped wavefronts, most commonly generated with spatial light modulators. Wavefront shaping has also enabled the manipulation of seemingly arbitrary objects beyond the reach of conventional beams. Contrary to this established assumption, we show here the existence of a wide variety of objects resistant to manipulation, even with the optimal wavefront shaping protocol. The counterintuitive shapes of these objects are found using inverse design in two dimensions, providing a foundation for their natural extension to three dimensions. Specifically, we show that the maximal pulling force is reduced by up to four orders of magnitude, and the maximal trapping stiffness is reduced by up to nearly two orders of magnitude. Our findings could prove useful for the development of micromachines that require a predictable mechanical response to arbitrary waves.

We present Cyqlone, a solver for linear systems with a stage-wise optimal control structure that fully exploits the various levels of parallelism available in modern hardware. Cyqlone unifies algorithms based on the sequential Riccati recursion, parallel Schur complement methods, and cyclic reduction methods, thereby minimizing the required number of floating-point operations, while allowing parallelization across a configurable number of processors. Given sufficient parallelism, the solver run time scales with the logarithm of the horizon length (in contrast to the linear scaling of sequential Riccati-based methods), enabling real-time solution of long-horizon problems. Beyond multithreading on multi-core processors, implementations of Cyqlone can also leverage vectorization using batched linear algebra routines. Such batched routines exploit data parallelism using single instruction, multiple data (SIMD) operations, and expose a higher degree of instruction-level parallelism than their non-batched counterparts. This enables them to significantly outperform BLAS and BLASFEO for the small matrices that arise in optimal control. Building on this high-performance linear solver, we develop CyQPALM, a parallel and optimal-control-specific variant of the QPALM quadratic programming solver. It combines the parallel and vectorized linear algebra operations from Cyqlone with a parallel line search and parallel factorization updates, resulting in order-of-magnitude speedups over the state-of-the-art HPIPM solver. Open-source C++ implementations of Cyqlone and CyQPALM are available at https://github.com/kul-optec/cyqlone

We prove that the unitary Drinfeld center of a unitary tensor category is equivalente to the category of unitary bimodules for the canonical W*-algebra object, generalizing Müger's result to the non-fusion case. This is then used to express factorization homology in terms of C*-algebraic extensions of symmetric enveloping algebras and actions of Drinfeld dobules of compact quantum groups.

A density functional theory (DFT) framework is presented that links functional derivatives of free-energy functionals to non-linear static density response functions in quantum many-body systems. Within this framework, explicit expressions are derived for various higher-order response functions of systems that are homogeneous on average, including the first theoretical result for the cubic response at the first harmonic $χ_0^{(1,3)}(\vec{q})$. Specifically, our framework includes hitherto neglected mode-coupling effects that are important for the non-linear density response even in the presence of a single harmonic perturbation. We compare these predictions for $χ_0^{(1,3)}(\vec{q})$ to new Kohn-Sham DFT simulations, leading to excellent agreement between theory and numerical results. Exact analytical expressions are also obtained for the long-wavelength limits of the ideal quadratic and cubic response functions. Particular emphasis is placed on the connections between the third- and fourth-order functional derivatives of the non-interacting free-energy functional $F_s[n]$ and the ideal quadratic and cubic response functions of the uniform electron gas, respectively. These relations provide exact constraints that may prove useful for the future construction of improved approximations to $F_s[n]$, in particular for warm dense matter applications at finite temperatures. Here, we use this framework to assess several commonly employed approximations to $F_s[n]$ through orbital-free DFT simulations of the harmonically perturbed ideal electron gas. The results are compared with Kohn-Sham DFT calculations across temperatures ranging from the ground state to the warm dense regime. Additionally, we analyze in detail the temperature- and wavenumber-dependent non-monotonic behavior of the ideal quadratic and cubic response functions.

We explore the relation between quantum geometry in non-Hermitian systems and physically measurable phenomena. We highlight various situations in which the behavior of a non-Hermitian system is best understood in terms of quantum geometry, namely the notion of adiabatic potentials in non-Hermitian systems and the localization of Wannier states in periodic non-Hermitian systems. Further, we show that the non-Hermitian quantum metric appears in the response of the system upon time-periodic modulation, which one can use to experimentally measure the non-Hermitian quantum metric. We validate our results by providing numerical simulations of concrete exemplary systems.

Quantum geometry is a differential geometry based on quantum mechanics. It is related to various transport and optical properties in condensed matter physics. The Zeeman quantum geometry is a generalization of quantum geometry including the spin degrees of freedom. It is related to electromagnetic cross responses. Quantum geometry is generalized to non-Hermitian systems and density matrices. Especially, the latter is quantum information geometry, where the quantum Fisher information naturally arises as quantum metric. We apply these results to the $X$-wave magnets, which include $d$% -wave, $g$-wave and $i$-wave altermagnets as well as $p$-wave and $f$-wave magnets. They have universal physics for anomalous Hall conductivity, tunneling magneto-resistance and planar Hall effect. We also study magneto-optical conductivity, magnetic circular dichroism and Friedel oscillations in the $X$-wave magnets. Various analytic formulas are derived in the case of two-band Hamiltonians. This paper presents a review of recent progress together with some original results.

A physics-informed machine learning framework based on holomorphic neural networks is introduced for detecting cracks in two-dimensional solids from strain or displacement data. Crack detection is formulated as an inverse problem in which the crack size, orientation, and location are treated as unknowns. The problem is solved using genetic optimization, where the fitness function is evaluated by expressing the solution of the corresponding plane elasticity problem in terms of holomorphic potentials, which are then determined through the training of two holomorphic neural networks. As the potentials satisfy equilibrium and traction-free conditions along the crack faces a priori, the training proceeds quickly based solely on boundary information. Training efficiency is further improved by splitting the genetic search into long-range and short-range stages, enabling the use of transfer learning in the latter. The new strategy is tested on three benchmark problems, showing that an optimal number of training epochs exists that provides the best overall performance. A comparison is also made with a popular crack detection approach that uses XFEM to compute the model response. Under the assumption of identical stress-field representation accuracy, the proposed method is found to be between 7 and 23 times faster than the XFEM-based approach. Furthermore, the proposed method appears to be less sensitive to noise in the input data. Overall, the present findings demonstrate that combining genetic optimization with holomorphic neural networks and transfer learning offers a promising avenue for developing crack detection strategies with higher efficiency than those currently available.

In our recent work, we proposed Lightweight Speech Enhancement Guided Target Speech Extraction (LGTSE) and demonstrated its effectiveness in multi-speaker-plus-noise scenarios. However, real-world applications often involve more diverse and complex conditions, such as one-speaker-plus-noise or two-speaker-without-noise. To address this challenge, we extend LGTSE with a Cross-Condition Consistency learning strategy, termed TripleC Learning. This strategy is first validated under multi-speaker-plus-noise condition and then evaluated for its generalization across diverse scenarios. Moreover, building upon the lightweight front-end denoiser in LGTSE, which can flexibly process both noisy and clean mixtures and shows strong generalization to unseen conditions, we integrate TripleC learning with a proposed parallel universal training scheme that organizes batches containing multiple scenarios for the same target speaker. By enforcing consistent extraction across different conditions, easier cases can assist harder ones, thereby fully exploiting diverse training data and fostering a robust universal model. Experimental results on the Libri2Mix three-condition tasks demonstrate that the proposed LGTSE with TripleC learning achieves superior performance over condition-specific models, highlighting its strong potential for universal deployment in real-world speech applications.

One of the possible ways to detect the new physics phenomena particles is to investigate the weak gauge boson production as a result of hadron-hadron scattering. This study comprises the production of multiple weak gauge bosons as a result of hard scattering between the proton-proton beams at multi-TeV energies and integrated luminosity $\mathcal L =$ 3000 $fb ^{-1}$. The effective production cross-sections for pair, triple, and quartic scattering mechanisms have been computed as a function of $\sqrt s$. The center of mass energy has been varied from 8 TeV to 100 TeV to encompass the future collider capabilities. Out of all the studied processes, the triple scattering process $W^+W^-W^+$ has been chosen as the signal process based on the dominant cross-section. The background channels ZZZ, ZZZZ, $W^-ZZ$, $W^+ZZ$, $W^+W^-Z$, $W^+W^-ZZ$, $W^+W^-W^+W^-$, having comparatively lower cross-sections, have been selected from possible scattering mechanisms to investigate the effect of higher luminosity on the low production cross-section processes. We have investigated the different decay modes. For both lepton and hadron-specific decays of W and Z, the cumulative efficiencies for each signal and background process have been computed. In this study, we have successfully demonstrated an effective methodology for background suppression by systematically optimizing the signal-to-background ratio. The results indicate that, despite lower cross-sections for higher-order scattering, the distinct kinematic features enable effective signal isolation at future colliders.

Quantum high-harmonic generation (HHG) is a prominent and growing field of research with potential capabilities of providing high photon-number entangled states of light. However, there is an open debate regarding the theory level required for correctly describing the quantum aspects of HHG, such as squeezing or entanglement. Previous approaches either semi-classically sampled the quantum electromagnetic field distribution, or employed perturbation theory utilizing the semi-classical simulations as a starting point. Both of these schemes miss out key quantum-optical features as self-consistent numerical simulations of the electron-photon wavefunction are not performed at any stage. In this Letter, we develop a full quantum theory for multipartite entanglement in HHG, solving exactly the light-matter interaction Hamiltonian in a given Hilbert space, and employ it for evaluating the quantum correlations of emitted photons. We show that HHG entanglement oscillates with the driving laser power and exhibits multiple local maxima, which allows fine-tuning HHG entanglement. Such features arise for both above-threshold harmonics and between above- and below-threshold harmonics. By analyzing different types of atomic targets, we find that the long-range behavior of driven electrons can qualitatively change the resulting entanglement, potentially leading to non-universal behavior across systems. Lastly, we show that focal averaging over classical degrees of freedom in fact plays a key role in entanglement measures and can change the qualitative behavior of observables. Our work establishes the state-of-the art in exploring entanglement features in HHG, and paves way for analysis and engineering of entangled multi-photon states in the XUV and ultrafast regime for more complex matter systems.

Two photons from the ground state para-positronium annihilation are emitted in a maximally entangled singlet state of orthogonal polarizations. In case of the Compton scattering of both photons the phenomenon of quantum entanglement leads to a measurable increase in the azimuthal correlations of scattered photons, as opposed to a classical description treating the two scattering events as independent. The probability of the scattering of the system of the entangled photons is described by the Pryce-Ward cross section dependent on a difference of the azimuthal scattering angles in the fixed coordinate frame, while the independent scattering of single photons is described by the Klein-Nishina cross section dependent on the azimuthal angle relative to each photon's initial polarization. Since the singlet state of orthogonal polarizations is rotationally invariant, it does not carry any physical information on the initial polarizations of the single annihilation photons. In such bipartite state the angular origin for the Klein-Nishina cross section is undefined, making the Pryce-Ward and Klein-Nishina descriptions mutually exclusive. However, semi-classical simulations of the joint Compton scattering of entangled photons - implementing the Pryce-Ward cross section, but still treating the two photons as separate entities - can reconcile the Pryce-Ward correlations with the Klein-Nishina statistics for single photons by implementing a modified version of a scattering cross section presented in this work.

Colloidal gels form through the sol-gel transition of attractive particle suspensions, where local aggregation leads to a space-spanning network with solid-like properties. Their microstructure and mechanical properties are highly sensitive to external perturbations, which can substantially alter the pathway of network formation. Here, we investigate how nonlinear oscillatory shear affects the sol-gel transition of colloidal silica suspensions. Using large-amplitude oscillatory shear (LAOS), we vary both the strain amplitude and the duration of oscillatory forcing, varying between one and two times the gelation time. We find that sufficiently large strain amplitudes, or prolonged exposure to oscillations in the nonlinear regime, alter irreversibly the gel properties: the storage modulus $G'$ decreases while its frequency dependence remains unchanged. In contrast, the loss modulus $G''$, which decreases monotonically with frequency under quiescent gelation, exhibits an upturn at high frequencies when the gel is formed under strong oscillatory shear. The viscoelastic spectra of gels formed under quiescent conditions are well captured by a fractional Maxwell model, while gels formed under LAOS require an additional fractional element to account for damage-induced dissipation. Rheo-imaging experiments corroborate this interpretation by revealing the growth of cracks in gels formed under LAOS. We further show that these gels display a progressively more ductile nonlinear response for prolonged exposure to LAOS during gelation. These results demonstrate that the interplay between non-linear shear and gelation can permanently imprint a macroscopic fracture pattern into colloidal gels, offering a route to tune their viscoelastic properties.

The Changing-Look active galactic nucleus Mkn 590 is currently in a rejuvenated state, exhibiting a contemporaneous flux rise across X-rays, UV, optical and cm wavelengths. In this study, we present three new optical spectra obtained with the Nordic Optical Telescope, alongside three 1.4 GHz continuum measurements from the Giant Meterwave Radio Telescope, acquired since Nov. 2024. We identified a clear increase in the broad hydrogen Balmer line emission in the most recent observational epochs. Additionally, the core radio flux densities appear to track the overall X-ray variability, suggesting a possible connection between the accretion flow and jet activity. Based on these data, we aim to explore the evolution of the circumnuclear gas in this source and potential links between accretion and ejection activity.