We investigate the motion of charged particles evolving around a magnetized Kiselev black hole, in the weak magnetic field approximation. The effective potential allows us to study the bound motion and the stable circular orbits. We analyze the impact of combined quintessence and magnetic fields on the epicyclic frequencies. Finally, we examine the periapsis shift and gravitational Larmor precession pointing out differences from the Ernst or Kiselev spacetimes.

In the deletion channel, an important problem is to determine the number of subsequences derived from a string $U$ of length $n$ when subjected to $t$ deletions. It is well-known that the number of subsequences in the setting exhibits a strong dependence on the number of runs in the string $U$, where a run is defined as a maximal substring of identical characters. In this paper we study the number of subsequences of a non-binary string in this scenario, and propose some improved bounds on the number of subsequences of $r$-run non-binary strings. Specifically, we characterize a family of $r$-run non-binary strings with the maximum number of subsequences under any $t$ deletions, and show that this number can be computed in polynomial time.

We derive a general expression for the resummation of rapidity distributions for processes with a colorless final state, such as Drell-Yan or Higgs production, in the limit in which the center-of-mass energy goes on threshold, but with fixed rapidity of the Higgs or gauge boson in the partonic center-of-mass frame. The result is obtained by suitably generalizing the renormalization-group based approach to threshold resummation previously pursued by us. The ensuing expression is valid to all logarithmic orders but the resummation coefficients must be determined by comparing to fixed order results. We perform this comparison for the Drell-Yan process using the fixed-order next-to-next-to-leading (NNLO) result, thereby determining resummation coefficients up to next-to-next-to-leading logarithmic (NNLL) accuracy, for the quark-antiquark coefficient function in the quark nonsinglet channel. We provide a translation to direct QCD of a result for this resummation previously obtained using SCET methods, and we show that it agrees with our own.

The magic triangle due to Cvitanović and Deligne--Gross is an extension of the Freudenthal--Tits magic square of semisimple Lie algebras. In this paper, we identify all two-dimensional rational conformal field theories associated to the magic triangle. These include various Wess--Zumino--Witten (WZW) models, Virasoro minimal models, compact bosons and their non-diagonal modular invariants. At level one, we uncover a two-parameter family of fourth-order modular linear differential equation whose solutions yield the affine characters of all elements in the magic triangle. We further establish a universal coset relation for the whole triangle, generalizing the dual-pair structure with respect to $(E_8)_1$ in the Cvitanović--Deligne exceptional series. This coset structure determines the dimensions and degeneracies of all primary fields and leads to five atomic models from which all theories in the triangle can be constructed. At level two, we find that a distinghuished row of the triangle -- the subexceptional series -- exhibits emergent $N=1$ supersymmetry. The corresponding Neveu--Schwarz/Ramond characters satisfy a one-parameter family of fermionic modular linear differential equations. In addition, we find several new uniform coset constructions involving WZW models at higher levels.

Repository-level code completion benefits from retrieval-augmented generation (RAG). However, controlling cross-file evidence is difficult because chunk utility is often interaction-dependent: some snippets help only when paired with complementary context, while others harm decoding when they conflict. We propose RepoShapley, a coalition-aware context filtering framework supervised by Shapley-style marginal contributions. Our offline labeling module, ChunkShapley, estimates signed per-chunk effects via teacher-forced probing, feeds them into a lightweight surrogate game that captures saturation and interference, computes exact Shapley values for small retrieval sets, and selects a decoding-optimal coalition through bounded post-verification with the frozen generator. The verified keep/drop decisions and retrieval triggers are then distilled into a single model via discrete control tokens. Experiments across benchmarks and backbones show that RepoShapley improves completion quality while reducing harmful context and unnecessary retrieval.

Advanced speech synthesis technologies have enabled highly realistic speech generation, posing security risks that motivate research into audio deepfake detection (ADD). While state space models (SSMs) offer linear complexity, pure causal SSMs architectures often struggle with the content-based retrieval required to capture global frequency-domain artifacts. To address this, we explore the scaling properties of hybrid architectures by proposing XLSR-MamBo, a modular framework integrating an XLSR front-end with synergistic Mamba-Attention backbones. We systematically evaluate four topological designs using advanced SSM variants, Mamba, Mamba2, Hydra, and Gated DeltaNet. Experimental results demonstrate that the MamBo-3-Hydra-N3 configuration achieves competitive performance compared to other state-of-the-art systems on the ASVspoof 2021 LA, DF, and In-the-Wild benchmarks. This performance benefits from Hydra's native bidirectional modeling, which captures holistic temporal dependencies more efficiently than the heuristic dual-branch strategies employed in prior works. Furthermore, evaluations on the DFADD dataset demonstrate robust generalization to unseen diffusion- and flow-matching-based synthesis methods. Crucially, our analysis reveals that scaling backbone depth effectively mitigates the performance variance and instability observed in shallower models. These results demonstrate the hybrid framework's ability to capture artifacts in spoofed speech signals, providing an effective method for ADD.

We extend the previously developed [1] generally covariant formalism to include diffusion of conserved charges, and comment on the seming difference between the chemica potential term and the diffusion term

Information overload (IOL) is a well-known and devastating phenomenon that alters the performance of carrying out all types of tasks. It has been shown that in the media space, IOL can contribute to news fatigue and news avoidance, which often leads to the proliferation of fake news posts on social networks. However, there is a lack of automatic methods that can be used to track IOL in large datasets. In this study, we investigate whether the Gini index calculated from the distribution of topics obtained via the BERTopic model can be considered a proxy for IOL. We test our assumptions on a set of Reddit communities related to the COVID-19 pandemic and obtain a significant global correlation between the Gini index and the fraction of fake news detected by the FakeBERT classifier. However, at the community level, the correlation analysis results are ambiguous.

The coming decade will be crucial for determining the final design and configuration of a global network of next-generation (XG) gravitational-wave detectors, including the Einstein Telescope (ET) and Cosmic Explorer (CE). In this study, and for the first time, we assessed the performance of various network configurations using neural posterior estimation (NPE) implemented in Dingo-IS-a method based on normalizing flows and importance sampling that enables fast and accurate inference. We focused on a specific science case involving short-duration, massive and high-redshift binary black hole mergers with detector-frame chirp masses $> 100~\mathrm{M}_\odot$. These systems encompass early-Universe stellar and primordial black holes, as well as intermediate-mass black hole binaries, for which XG observatories are expected to deliver major discoveries. Validation against standard Bayesian inference demonstrates that NPE robustly reproduces complex and disconnected posterior structures across all network configurations. For a network of two misaligned L-shaped ET detectors (2L MisA), the posterior distributions on luminosity distance can become multimodal and degenerate with the sky position, leading to less precise distance estimates compared to the triangular ET configuration. However, the number of sky-location multimodalities is substantially lower than the eight expected with the triangular ET, resulting in improved sky and volume localization. Adding CE to the network further reduces sky-position degeneracies, and the better performance of the 2L MisA configuration over the triangle remains evident.

Much work has been devoted to bent functions in odd characteristic, but there still remains a gap between our knowledge of binary and nonbinary bent functions. In the first part of this paper, we attempt to partially bridge this gap by generalizing to any characteristic important properties known in characteristic two concerning the Walsh transform of derivatives of bent functions. Some of these properties generalize to all bent functions, while others appear to apply only to weakly regular bent functions. We deduce a method to obtain a bent function by adding a quadratic function to a weakly regular bent function. We also identify a particular class of bent functions possessing the property that every first-order derivative in a nonzero direction has a derivative (which is then a second-order derivative of the function) equal to a nonzero constant. We show that this property implies bentness and is shared in particular by all cubic bent functions. This generalizes to the odd characteristic the notion of cubic-like bent function, that was introduced and studied for binary functions by Irene Villa and the first author. In the second part of the paper, we provide (for the first time) a primary construction leading to an infinite class of cubic ternary vectorial bent functions that have only not weakly regular components. We show the bentness of the component functions by two approaches: by calculating the Walsh transform directly and by considering the second-order derivatives (and applying the results from the first part of the paper). We prove that they are not weakly regular by showing they do not have one of the properties that we proved in the first part of the paper for weakly regular bent functions.

We investigate the universal behaviour of a one-parameter generalisation of the six-vertex model on planar graphs, which we refer to as the seven-vertex model, or 7vM for quick reference. The 7vM is characterised by a temperature coupling and its continuum limit exhibits massive, dilute and dense phases similarly to the $O(n)$ loop model. However, there is an important distinction: the loop weights are no longer topological and the dynamics of the loops is now entangled with the local geometry of the lattice. From the dual matrix model we derive explicit expressions for the sphere and disk partition functions in the continuum limit. The disk partition function for fixed length is a deformation of the Bessel integral known as the Krätzel function. We argue that the 7v matrix model (7vMM) and Matrix Quantum Mechanics (MQM) provide two complementary non-perturbative realisations of sine-Liouville gravity. Specifically, we find that the continuum limits of 7vMM and MQM share the same classical spectral curve but describe two different types of branes in sine-Liouville gravity. The 7vMM precisely covers the range of parameters where the Minkowskian MQM lacks a simple interpretation in terms of multiple tachyon scattering. We investigate the flow relating the dilute and dense phases and argue that this flow is the gravitational analogue of the massless flow in the sine-Gordon model with imaginary mass coupling. The two endpoints of the flow are described by a free boson coupled to Liouville gravity and compactified on circles with two different radii.

Fluid ferroelectrics, a recently discovered class of liquid crystals that exhibit switchable, long-range polar order, offer opportunities in ultrafast electro-optic technologies, responsive soft matter, and next-generation energy materials. Yet their discovery has relied almost entirely on intuition and chance, limiting progress in the field. Here we develop and experimentally validate a deep-learning data-to-molecule pipeline that enables the targeted design and synthesis of new organic fluid ferroelectrics. We curate a comprehensive dataset of all known longitudinally polar liquid-crystal materials and train graph neural networks that predict ferroelectric behaviour with up to 95% accuracy and achieve root mean square errors as low as 11 K for transition temperatures. A graph variational autoencoder generates de novo molecular structures which are filtered using an ensemble of high-performing classifiers and regressors to identify candidates with predicted ferroelectric nematic behaviour and accessible transition temperatures. Integration with a computational retrosynthesis engine and a digitised chemical inventory further narrows the design space to a synthesis-ready longlist. 11 candidates were synthesised and characterized through established mixture-based extrapolation methods. From which extrapolated ferroelectric nematic transitions were compared against neural network predictions. The experimental verification of novel materials augments the original dataset with quality feedback data thus aiding future research. These results demonstrate a practical, closed-loop approach to discovering synthesizable fluid ferroelectrics, marking a step toward autonomous design of functional soft materials.

Existing approaches to modelling antibody concentration data are mostly based on finite mixture models that rely on the assumption that individuals can be divided into two distinct groups: seronegative and seropositive. Here, we challenge this dichotomous modelling assumption and propose a latent variable modelling framework in which the immune status of each individual is represented along a continuum of latent seroreactivity, ranging from minimal to strong immune activation. This formulation provides greater flexibility in capturing age-related changes in antibody distributions while preserving the full information content of quantitative measurements. We show that the proposed class of models can accommodate a large variety of model formulations, both mechanistic and regression-based, and also includes finite mixture models as a special case. We also propose a computationally efficient $L_2$-based estimator as an alternative to maximum likelihood estimation, which substantially reduces computational cost, and we establish its consistency. Through a case study on malaria serology, we demonstrate how the flexibility of the novel framework enables joint analyses across all ages while accounting for changes in transmission patterns. We conclude by outlining extensions of the proposed modelling framework and its relevance to other omics applications.

We introduce infrared finite, analytic, crossing symmetric, Regge behaved, and Lorentz invariant amplitudes $\mathcal{M}_{\mathcal {E}}$, labeled by the experimental energy resolution $\mathcal{E}$ for detecting soft photons and gravitons. For $\mathcal{E}$ exponentially smaller than any hard scale, they also satisfy unitarity and their associated cross sections reproduce the inclusive, infrared-finite cross sections of ordinary amplitudes. These properties make $\mathcal{M}_{\mathcal{E}}$ suitable for deriving infrared-safe positivity bounds on effective field theories in the presence of long-range forces even in $D=4$. As an illustration, we present explicit bounds in the low-energy theory of pions coupled to electromagnetism and gravity.

The indirect ground-based observations of cosmic rays through extensive air showers in modern experiments typically involve the use of Monte Carlo simulations to determine the characteristics of the primary particles. These simulations necessitate assumptions about particle interactions at energies that have not yet been experimentally probed, which introduces systematic uncertainties in key observables, particularly the number of muons. Current research on this uncertainty primarily focuses on hadronic interaction models, the dominant source of muon production. This study presents an approach that takes into account another significant mechanism for muon generation: photonuclear reactions. A robust heuristic technique has been developed to estimate the contribution of these interactions to the total number of muons over a wide range of extensive air shower parameters (including primary particle type, energy, and slant atmospheric depth) and photonuclear interaction models, with an absolute percentage error on the order of $10\%$ in the estimated number of muons. Furthermore, several potential applications of the suggested method in relation to modern challenges in extensive air shower physics are discussed.

We propose dressing factors for massive excitations of the worldsheet S matrix of $AdS_3\times S^3\times S^3\times S^1$ supported by mixed Ramond--Ramond and Neveu-Schwarz--Neveu-Schwarz flux, in the "string" and "mirror" kinematics. Our proposal is compatible with crossing and unitarity, and it reproduces the available perturbative results for any ratio of the two three-spheres' radii.

Optically active networks show feature-rich emission that depends on the fine details of their geometry, and find diverse applications in random lasers, sensing devices and photonics processors. In these and other systems, a thorough and predictive characterization of how the network geometry correlates with the resulting emission spectrum would be highly important, however such outright description is still lacking. In this work, we take a step toward filling this gap, by using the well-known Steady-State ab Initio Laser Theory equations to carry out an extensive set of statistical analyses and establish connections between the random network geometry and their ultimate emission spectrum. Our results show that edge crowding (abundance of short edges in the network) is key to tune the uniformity of the modal intensity distribution of the emission spectrum. A statistical framework for the comprehensive understanding of the network statistical properties is highly significant to establish precise design rules for network-based photonic devices and intelligent systems.

We present a tracker gas flow quality control method developed for the Mu2e straw tube tracker. Using time-dependent current measurements, we quantify the onset time of ionization gain induced by an 55Fe source during gas exchange, which is correlated to the gas conductance in the straw. This allows for the identification of channels with inadequate flow. This approach is broadly applicable to other gaseous detectors that require high-channel-count screening.

Measuring the electron neutrino mass is a long-standing objective and requires a high energy resolution of certain $β$-decay experiments, as well as a visible cosmic neutrino background (C$ν$B) spectrum. Many quantum mechanical and chemical effects could potentially impair the required resolution/visibility, e.g., the Coulomb interactions between the electrons in the $β$-decaying impurity and in the solid-state environment. We analyze the effect when hybridization is suppressed completely using a dielectric spacer, and also when hybridization is present up to the lowest nontrivial order in perturbation theory.

The Software Bill of Materials (SBOM) is a critical tool for securing the software supply chain (SSC), but its practical utility is undermined by inaccuracies in both its generation and its application in vulnerability scanning. This paper presents a large-scale empirical study on 2,414 open-source repositories to address these issues from a practical standpoint. First, we demonstrate that using lock files with strong package managers enables the generation of accurate and consistent SBOMs, establishing a reliable foundation for security analysis. Using this high-fidelity foundation, however, we expose a more fundamental flaw in practice: downstream vulnerability scanners produce a staggering 92.0\% false positive rate in our case study. We pinpoint the primary cause as the flagging of vulnerabilities within unreachable code. We then demonstrate that function call analysis can effectively prune 61.9\% of these false alarms. Our work validates a practical, two-stage approach for SSC security: first, generate an accurate SBOM using lock files and strong package managers, and second, enrich it with function call analysis to produce actionable, low-noise vulnerability reports that alleviate developers' alert fatigue.

New long range forces acting on ordinary matter are highly constrained. However it is possible such forces act on dark matter, as it is less constrained observationally. In this work, we consider dark matter to be made of light bosons, such as axions. We introduce a mediator that communicates a new force between dark matter particles, in addition to gravity. The mediator is taken to be light, but not massless, so that it can affect small scale galactic behavior, but not current cosmological behavior. As a concrete application of this idea, we analyze the effects on scalar dark matter solitons bound by gravitation, i.e., boson stars, which have been claimed to potentially provide cores of galaxies. We numerically determine the soliton's profiles in the presence of this new force. We also extend the analysis to multiple mediators. We show that this new force alters the relation between core density and core radius in a way that can provide improvement in fitting data to observed galactic cores, but for couplings of order the gravitational strength, the improvement is only modest.

In 1991, the Borweins established a cubic analogue of Jacobi's identity for theta functions, which is used by B.C. Berndt, S. Bhargava, and F.G. Garvan in the development of Ramanujan's cubic theory of elliptic functions. In 2013, D. Schultz discovered an identity for theta series in three variables which generalizes the Borweins' identity. In this article, we revisit Schultz's identity and present two distinct approaches to its derivation. Our investigation not only provides new proofs but also yields several new Schultz-type identities.

We study the contraction of Hodgkin-Huxley model and its role in the reliability of spike timings. Without input, the model is contractive in the region of physiological interest. With impulsive synaptic inputs, contraction is retained provided that the input events are sparse enough. Contraction is lost when the input firing rate is too high. Spike timings are shown to be reliable in the contracting regime.

People increasingly seek personal advice from large language models (LLMs), yet whether humans follow their advice, and its consequences for their well-being, remains unknown. In a longitudinal randomised controlled trial with a representative UK sample (N = 6,474), we found that up to 79% of participants who had a 20-minute discussion with one of three AI chatbots (GPT-4o, LLama-3.3-70B, Gemini 3 Pro) about health, careers or relationships subsequently reported following its advice. Advice-following remained above 60% even for high-stakes recommendations, suggesting that users only weakly calibrate their reliance on AI advice to potential consequences. Based on autograder evaluations of chat transcripts, LLM advice rarely violated safety best practice. However, when queried 2-3 weeks later, participants receiving personal advice from AI showed no sustained well-being benefits compared to a control group who discussed hobbies and interests with the same chatbots. These findings reveal that consumer LLMs exert substantial influence over real-world personal decisions without delivering measurable psychological benefits.

We derive the Tully-Fisher (TFR, $M_\ast-V_{\rm circ,f}$) and Fall (FR, $j_\ast-M_\ast$) relations at redshift $z = 0.9$ using a sample of 43 main-sequence disc galaxies with H$α$ IFU data and JWST/HST imaging. The strength of our analysis lies in the use of state-of-the-art 3D kinematic models to infer galaxy rotation curves, the inclusion and morphological modelling of NIR bands, and the use of SED modelling applied to our photometry measurements to estimate stellar masses. After correcting the inferred H$α$ velocities for asymmetric drift, we find a TFR of the form $\log(M_\ast / M_\odot) = a \log(V_{\rm circ,f} / 150~\mathrm{km\,s^{-1}}) + b$, with $a=3.82^{+0.55}_{-0.40}$ and $b=10.27^{+0.06}_{-0.07}$, as well as a FR of the form $\log(j_\ast / \mathrm{kpc\,km\,s^{-1}}) = a \log(M_\ast / 10^{10.5} M_\odot) + b$, with $a=0.44^{+0.06}_{-0.06}$ and $b=2.86^{+0.02}_{-0.02}$. Compared with their $z=0$ counterparts, we find moderate evolution in the TFR and strong evolution in the FR over the past 8 Gyr. We interpret our findings in the context of the galaxy-to-halo scaling parameters $f_{\rm M}=M_\ast/M_{\rm vir}$ and $f_{\rm j}=j_\ast/j_{\rm vir}$. We infer that $f_{\rm j}$ shows little redshift evolution and depends very weakly on $M_\ast$, with typical values around $f_{\rm j}\sim0.8$. As for $f_{\rm M}$, we find it to be higher and less dependent on $M_\ast$ at $z=0.9$ than at $z=0$. Interpreting our observed $f_{\rm M}-M_\ast$ relations within the Cold Dark Matter framework implies necessarily that the galaxy populations at $z=0.9$ and $z=0$ are not the progenitor/descendant of one another. The alternative scenario is that the $z=0.9$ relations are incorrect due to strong selection effects, unidentified systematics, or the possibility that H$α$ kinematics may not be a reliable dynamical tracer. Such problems would also affect previous studies on the same subject.

Within density-functional theory, Moreau-Yosida regularization enables both a reformulation of the theory and a mathematically well-defined definition of the Kohn-Sham approach. It is further employed in density-potential inversion schemes and, through the choice of topology for the density and potential space, can be directly linked to classical field theories. This perspective collects various appearances of the regularization technique within density-functional theory alongside possibilities for their future development.

The 1.8-2.3 μm band lies within the short-wavelength infrared (SWIR) region and serves as a key window for a wide range of applications, including quantum sensing, molecular spectroscopy, and free-space quantum and classical optical communication. Despite its significance, optical devices operating in this band still face two major challenges: chromatic aberration across the spectral range and difficulty of integration due to bulky optical elements. Metalenses are composed of subwavelength nanostructures that locally control the phase and group delay of light, enabling wavefront shaping and broadband dispersion compensation. These capabilities make them promising for infrared optical systems, particularly in focusing and imaging for compact devices. In this study, we propose a metalens design based on a CaF$_2$ substrate, where each nanocell consists of a silicon bar structure. These nanocells are periodically arranged with a 900~nm period, enabling control of dispersion and phase. By systematically finetuning the bar length and width, the design enables simultaneous dispersion compensation and phase modulation, achieving stable focusing performance over a broad spectral range. Finite-Difference Time-Domain (FDTD) simulations demonstrate effective suppression of chromatic aberration across 1800 - 2300 nm, with focal-length variation within 6% of the target value. We further analyze the polarization distribution across the focal spot and find a weak wavelength dependence of the degree of polarization (DoP), which we attribute to the spatially varying polarization state in the high-NA focal region together with the wavelength-dependent anisotropic response of the nanostructures. This design offers a compact, broadband, and high-performance approach for beam collimation and wavefront shaping in the SWIR band, showing promising potential for quantum communication and sensing systems.

Born-Infeld electrogravity is defined through a Lagrangian that couples gravity and electromagnetism within a single determinantal structure. The field equations are derived in Palatini's formalism, where the metric, connection, and vector potential are varied independently in the action. As a result, the gravitational sector reduces to Einstein's equations with a torsion-free, metric-compatible connection. The electrodynamic sector, in turn, admits two equivalent interpretations or $pictures$: it can be seen either as a standard Born-Infeld electrodynamics in an effective background geometry, or as an $anomalous$ Born-Infeld electrodynamics in the physical metric. We illustrate the dynamics by analyzing the horizon structure, the extremality conditions, and the thermodynamics of spherically symmetric dyonic solutions. Remarkably, in the small-charge limit, Born--Infeld electrogravity admits a fundamental extremal black hole whose mass and horizon area are determined exclusively by the Born--Infeld and Newton constants and the speed of light.

We propose Néel antiferromagnetic (AF) Mott insulators with a buckled honeycomb structure as potential candidates to host a high-temperature AF Chern insulator (AFCI). Using a generalized Kondo lattice model we show that the staggered potential induced by a perpendicular electric field due to the buckling can drive the AF Mott insulator to an AFCI phase. We address the temperature evolution of the Hall conductance and the chiral edge states. The quantization temperature $T_q$, below which the Hall conductance is quantized, depends essentially on the strength of the spin-orbit coupling and the hopping parameter, independent of the specific details of the model. The deviation of the Hall conductance from the quantized value $e^2/h$ above $T_q$ is found to be accompanied by a spectral broadening of the chiral edge states, reflecting a finite life-time, i.e., a decay. Using parameters typical for heavy transition-metal elements we predict that the AFCI can survive up to room temperature. We suggest Sr$_3$CaOs$_2$O$_9$ as a potential compound to realize a high-$T$ AFCI phase.

Parity mixing in photoionization, i.e. when emitted electrons have different parities but the same energy, causes interference observable only in angle-resolved measurements. The interference typically manifests as a symmetry violation in the photoelectron angular distributions. The traditional, based on HHG, RABBITT scheme with high-order harmonics separated by twice the seed field energy, precludes parity mixing. On the contrary, a free-electron laser provides a possibility to generate even harmonics. Using triple the fundamental frequency as a seed, one obtains a comb of alternating even and odd harmonics, separated by three times the initial frequency [Nature 578, 386-391 (2020)] (2-SB RABBITT). In this setup, there are two sidebands between the main photoelectron lines, versus one in the traditional scheme. In the paper, we examine the general properties of a two-sideband scheme and analyze the symmetry breakdown of photoelectron angular distributions for various polarization geometries of the incident pulse. We found a crucial difference in symmetries between 2-SB RABBITT and other photoionization schemes with parity mixing. Illustrative calculations are carried out for neon with pulse parameters typical for modern facilities. The possibility to reconstruct the temporal profile of the pulse from the angle-resolved measurements is discussed.