Quantum chemistry and materials science are among the most promising areas for demonstrating algorithmic quantum advantage and quantum utility due to their inherent quantum mechanical nature. Still, large-scale simulations of quantum circuits are essential for determining the problem size at which quantum solutions outperform classical methods. In this work, we present a novel hybrid simulation approach, forming a hybrid of a fullstate and a Clifford simulator, specifically designed to address the computational challenges associated with the time evolution of quantum chemistry Hamiltonians. Our method focuses on the efficient emulation of multi-qubit rotations, a critical component of Trotterized Hamiltonian evolution. By optimizing the representation and execution of multi-qubit operations leveraging the Pauli frame, our approach significantly reduces the computational cost of simulating quantum circuits, enabling more efficient simulations. Beyond its impact on chemistry applications, our emulation strategy has broad implications for any computational workload that relies heavily on multi-qubit rotations. By increasing the efficiency of quantum simulations, our method facilitates more accurate and cost-effective studies of complex quantum systems. We quantify the performance improvements and computational savings for this emulation strategy, and we obtain a speedup of a factor $\approx 18$ ($\approx 22$ with MPI) for our evaluated chemistry Hamiltonians with 24 qubits. Thus, we evaluate our integration of this emulation strategy into the Intel Quantum SDK, further bridging the gap between theoretical algorithm development and practical quantum software implementations.

We have used data collected by the Birmingham Solar-Oscillations Network (BiSON) to perform a helioseismic diagnosis of changes to the Sun's internal structure between four successive solar cycle minima, beginning with the minimum at the end of cycle 21 and ending with the recent minimum at the beginning of cycle 25. The unique duration of the BiSON database makes such a study possible. We used the low-degree BiSON p-mode frequencies to constrain structural changes between minima in the layers above $\approx 0.9 R_{\odot}$. We accomplished this by examining variations in the HeII ionisation zone signature; and by inverting the frequency differences to infer changes in the sound speed. Additionally, we employed frequency differences between various solar models that had subtle modifications to their internal structures to facilitate analysis of the observations. We find evidence for small, but marginally significant, changes in structure between different minima. The HeII signature was larger, and the sound speed in the range $\approx 0.93$ to $0.97 R_{\odot}$ was slightly higher, during the cycle 23/24 minimum, than during the other minima. The cycle 23/24 minimum was the deepest, as measured by proxies of global solar activity. These findings are consistent with magnetic flux levels having been lower in this minimum than the others, resulting in a higher gas pressure, higher temperatures, and higher sound speed. Our results demonstrate the potential of using asteroseismic data to perform similar analyses on other solar-type stars.

Kolmogorov-Arnold Networks (KANs) require significantly smaller architectures compared to multilayer perceptron (MLP)-based approaches, while retaining expressive power through spline-based activations. Moving boundary problems are ubiquitous in physical systems, whose numerical solutions are quite complex. We propose a shallow KAN framework combined with a Level-set formulation that directly approximates the temperature distribution $T(\mathbf{x},t)$ and the moving interface $Γ(t)$, enforcing the governing PDEs, phase equilibrium, and Stefan condition through physics-informed residuals. Numerical experiments in one and two dimensions show that the framework achieves accurate reconstructions of both temperature fields and interface dynamics, highlighting the potential of KANs as a compact and efficient alternative for moving boundary PDEs. First, we validate the model with semi-infinite analytical solutions. Subsequently, the model is extended to 2D using a level-set based formulation for interface propagation, which is solved within the KAN framework. This work demonstrates that KANs are capable of solving complex moving boundary problems without the need for measurement data.

We present a generalized framework for $n$-photon processes involving a uniformly accelerated Unruh-DeWitt detector interacting with a massless scalar field. We utilize the $n^\text{th}$ order Dyson series to derive the final quantum state for an arbitrary number of interactions. Our analysis covers both even-order processes, which return the detector to its initial state, and odd-order processes, which result in a change of the detector's state. By employing a unified formalism and performing a complete, time-ordered integration, we obtain exact analytical expressions for the $n$-photon states. The results reveal a rich structure of resonant denominators corresponding to multi-particle processes, including new field-mediated resonances independent of the detector's energy gap for $n>2$. Crucially, the analysis of odd-order transitions reveals an exponential factor, $\exp(-πω/a)$, characteristic of the Unruh thermal bath. By considering processes starting from the detector's excited state, we demonstrate that the ratio of excitation to de-excitation amplitudes precisely recovers the Boltzmann factor, providing a higher-order confirmation of thermal detailed balance for the Unruh effect. This work provides a unified tool for studying multipartite entanglement and thermal phenomena in non-inertial frames.

Recently, a toolkit of highly symmetric techniques employing matrix inequalities has been developed to detect entanglement in various ways. Here we unifiedly explain in detail these methods, and expand them to a new family of positive maps with further detection capabilities. In the simplest case, we generalize the reduction map to detect more generic states using both multiple copies and local filters. Through the Choi-Jamiołkowski isomorphism, this family of maps leads to a construction of multipartite entanglement witnesses. Discussions and examples are provided regarding the detection of states with local positive partial transposition and the use of multiple copies.

We present the first measurement of nuclear recoils from solar $^8$B neutrinos via coherent elastic neutrino-nucleus scattering with the XENONnT dark matter experiment. The central detector of XENONnT is a low-background, two-phase time projection chamber with a 5.9 t sensitive liquid xenon target. A blind analysis with an exposure of 3.51 t$\times$yr resulted in 37 observed events above 0.5 keV, with ($26.4^{+1.4}_{-1.3}$) events expected from backgrounds. The background-only hypothesis is rejected with a statistical significance of 2.73 $σ$. The measured $^8$B solar neutrino flux of $(4.7_{-2.3}^{+3.6})\times 10^6 \mathrm{cm}^{-2}\mathrm{s}^{-1}$ is consistent with results from the Sudbury Neutrino Observatory. The measured neutrino flux-weighted CE$ν$NS cross section on Xe of $(1.1^{+0.8}_{-0.5})\times10^{-39} \mathrm{cm}^2$ is consistent with the Standard Model prediction. This is the first direct measurement of nuclear recoils from solar neutrinos with a dark matter detector.

Within the model of topological particles (MTP) we determine the interaction energy of monopole pairs, sources and sinks of a Coulombic field. The monopoles are represented by topological solitons of finite size and mass, described by a field without any divergences. We fix the soliton centres in numerical calculations at varying distance. Due to the finite size of the solitons we get deviations from the Coulomb potential at distances of a few soliton radii. We compare the numerical results for these deviations with the running of the coupling in perturbative QED.

We employ a simple model for nuclear modification of ordinary parton densities in a proton to evaluate the Transverse Momentum Dependent gluon and quark distributions in nuclei (nTMDs) within the popular Kimber-Martin-Ryskin/Watt-Martin-Ryskin approach. The model is based on a global analysis of available deep inelastic scattering data for different nuclear targets within the rescaling model, incorporating Fermi motion effects. The derived nTMDs are tested with latest CMS data on inclusive $b$-jet and $B^+$ meson production in proton-lead collisions collected at $\sqrt s = 5.02$ and $8.16$~TeV using the High Energy Factorization framework. We predict the corresponding nuclear medium modification factors to be about of $0.8 - 1.2$ in the probed kinematical region, which is consistent with other estimations. Specially we highlight a possibility to investigate the nuclear modification of parton densities by applying different cuts on the final states in such processes.

The Solar Hemispherical Helicity Rule(s) (SHHR) is a term used to represent a bias observed in proxies for the magnetic helicity in active regions at the solar surface. The SHHR states that predominantly negative magnetic helicity is observed in active regions in the northern hemisphere, whereas predominantly positive is found in the southern. The $Σ$-effect model of \cite{longcope1998flux} is one of the most cited models for the explanation of the SHHR. In this model, the magnetic structures derive the bias in their magnetic helicity from the kinetic helicity of the turbulent convection through which they travel, where the latter is handed owing to the rotational influence of the star. The original paper built an elegant mathematical model for the dynamics of thin flux tubes influenced by parameterized helical turbulence. Here, we attempt to explore the conceptual ideas of this original simplified model using fully-nonlinear, three-dimensional, Cartesian-domain simulations of isolated, finite cross-sectional, twisted magnetic flux structures rising though rotating, overshooting, turbulent compressible convection. We look for evidence of a correlation between the kinetic helicity content of the turbulence and the evolving magnetic helicity of the structures. We find little evidence of such a relationship, and do not even find any clear hemispheric dependence. Although these simulations are far from a perfect representation of the ideas, this work raises many questions about the potential efficacy of the $Σ$-effect in reality.

Motivated by earlier numerical evidence for a percolation-like transition in space-time jamming, we present an analytic description of the transient dynamics of the deterministic traffic model elementary cellular automaton rule 184 (ECA184). By exploiting the deterministic structure of the dynamics, we reformulate the problem in terms of a height function constructed directly from the initial condition, and obtain an equilibrium statistical mechanics-like description over the lattice configurations. This formulation allows macroscopic observables in space-time, such as the total jam delay and jam relaxation time, as well as microscopic jam statistics, to be expressed in terms of geometric properties of the height function. We thereby derive the associated scaling forms and recover the critical exponents previously observed in numerical studies. We discuss the physical implications of this space-time geometric approach.

We present the W-SLDA Toolkit, a general-purpose software package for simulating ultracold Fermi gases within the framework of density functional theory and its time-dependent extensions. The toolkit enables fully microscopic studies of interacting superfluid systems across the BCS-BEC crossover, including spin-imbalanced configurations and arbitrary external geometries. It provides both static and time-dependent solvers capable of describing a broad range of phenomena in one-, two-, and three-dimensional settings. In addition, the toolkit incorporates functionality for solving the standard Bogoliubov-de Gennes equations for fermions, extending its applicability to other physical systems such as superconductors. The code is implemented in C with GPU acceleration and is optimized for hybrid CPU/GPU execution on modern high-performance computing platforms. It ensures scalability on leadership-class supercomputers, enabling fully three-dimensional simulations with large atomic numbers, and allows for direct benchmarks of ultracold-atom experimental setups. Its modular architecture facilitates straightforward extensions, user customization, and seamless interoperability with other scientific software frameworks. Furthermore, an extensive collection of practical usage examples is provided through the integrated reproducibility packs functionality, ensuring transparency and reproducibility of computational results.

We propose a sensing scheme for detecting weak forces that achieves Heisenberg-limited sensitivity without relying on entanglement or other non-classical resources. Our scheme utilizes coherent averaging across a chain of N optomechanical cavities, unidirectionally coupled via a laser beam. As the beam passes through the cavities, it accumulates phase shifts induced by a common external force acting on the mechanical elements. Remarkably, this fully classical approach achieves the sensitivity scaling typically associated with quantum-enhanced protocols, providing a robust and experimentally feasible route to precision sensing. Potential applications range from high-sensitivity gravitational field measurements at the Large Hadron Collider to probing dark matter interactions and detecting gravitational waves. This work opens a new pathway for leveraging coherent light-matter interactions for force sensing.

Neural ordinary differential equations (neural ODEs) can effectively learn dynamical systems from time series data, but their behavior on graph-structured data remains poorly understood, especially when applied to graphs with different size or structure than encountered during training. We study neural ODEs ($\mathtt{nODE}$s) with vector fields following the Barabási-Barzel form, trained on synthetic data from five common dynamical systems on graphs. Using the $\mathbb{S}^1$-model to generate graphs with realistic and tunable structure, we find that degree heterogeneity and the type of dynamical system are the primary factors in determining $\mathtt{nODE}$s' ability to generalize across graph sizes and properties. This extends to $\mathtt{nODE}$s' ability to capture fixed points and maintain performance amid missing data. Average clustering plays a secondary role in determining $\mathtt{nODE}$ performance. Our findings highlight $\mathtt{nODE}$s as a powerful approach to understanding complex systems but underscore challenges emerging from degree heterogeneity and clustering in realistic graphs.

We investigate a non-singular cosmological scenario in which uniform-rate inflation is realised on an anisotropic Shtanov-Sahni braneworld. The model naturally resolves the initial singularity resulting in an infinite number of smooth non-singular bounces, while accommodating a phase of accelerated expansion driven by a scalar field rolling at a constant rate. The presence of a timelike extra dimension induces high-energy corrections to the effective Friedmann dynamics, allowing anisotropic shear to be dynamically suppressed near the bounce and rendering the background evolution stable. We derive the full background dynamics analytically and demonstrate that uniform-rate inflation can be consistently embedded within an anisotropic braneworld framework. Primordial scalar and tensor perturbations are analysed using the $δN$ formalism, ensuring that only physically relevant modes exiting the horizon during inflation contribute to observable quantities. Remarkably, we find that observational consistency can be achieved with different levels of anisotropy in the two different scenarios we consider, without compromising the smoothness or stability of the bounce. Our results establish uniform-rate inflation on an anisotropic braneworld as a robust and observationally viable alternative to standard inflationary cosmology, offering a compelling framework in which non-singular early-universe dynamics and precision cosmology can be consistently unified.

We report a significant increase in mid-infrared emission $\leq10$ $μ$m in a transitional disk. The 2024 JWST/MIRI observation of the disk around CVSO 1942 reveals flux increase by a factor of two at $λ\leq10$ $μ$m, compared to the near photospheric flux level observed with Spitzer/IRS in 2005. No significant change in flux at $\gtrsim15$ $μ$m is detected in the spectra. Comparing the MIRI/MRS spectrum and NEOWISE photometry, we found that this $\leq10$ $μ$m flux increase occurs on a timescale of 2 weeks and is consistent with the presence of warm (1,400 K), optically thick, large ($\gtrsim1$ $μ$m) dust grains near the dust sublimation radius. We propose that this rapid dust appearance may indicate in situ dust formation, possibly from planetesimal collisions in the inner disk.

We study the dimensionality of two-dimensional Kolmogorov flows over a wide range of Reynolds numbers and forcing wavenumbers $k_f=\{2,4,8\}$ using two complementary approaches: convolutional autoencoders and a Kaplan-Yorke estimation based on Lyapunov analysis. As the Reynolds number increases, two distinct transitions are observed: the first corresponds to the destabilization of a periodic orbit, while the second marks the saturation of the large-scale motions. When expressed in terms of the forcing Reynolds number, these transitions occur at nearly the same value for all forcing wavenumbers, suggesting a universal scaling with respect to the forcing scale. By filtering the data to retain only the large-scale range ($k < k_f$), we show that the dimensionality estimated by the autoencoders also saturates at the second transition, implying that once the large scales are fully developed, the subsequent increase in dynamical activity occurs predominantly at smaller scales. At higher Reynolds numbers, the Kaplan-Yorke dimension ceases to grow, revealing its limited sensitivity to the nonlinear interactions that dominate in this regime. Both the Kaplan-Yorke saturation dimension and the filtered large-scale dimensionalities exhibit a linear dependence on $k_f$, indicating that the number of active degrees of freedom scales with the forcing scale rather than with the total number of available Fourier modes.

We report the identification of two previously unrecognized interstellar meteor candidates in the NASA CNEOS fireball database. Using the empirically calibrated low-discrepancy uncertainty model of Peña-Asensio et al.\ (2025) for post-2018 CNEOS velocity accuracy (1$σ$: speed 0.55~km~s$^{-1}$, right ascension 1.35$^\circ$, declination 0.84$^\circ$), we transform CNEOS velocity vectors to heliocentric orbits and assess interstellar candidacy via $10^{6}$-draw Monte Carlo simulations. Two post-2018 events have heliocentric speeds robustly exceeding the Solar System escape speed. CNEOS-22 (2022-07-28; 6.0$^\circ$S, 86.9$^\circ$W; eastern tropical Pacific) has $v_{\rm hel}=46.98$~km~s$^{-1}$, exceeding escape by $Δ= 5.18 \pm 0.60$~km~s$^{-1}$ ($z_Δ=8.7σ$), with interstellar speed $v_{\infty,\odot}=21.5$~km~s$^{-1}$. CNEOS-25 (2025-02-12; 73.4$^\circ$N, 49.3$^\circ$E; Barents Sea) has $v_{\rm hel}=45.63$~km~s$^{-1}$, exceeding escape by $Δ= 3.22 \pm 0.58$~km~s$^{-1}$ ($z_Δ=5.5σ$), with $v_{\infty,\odot}=16.9$~km~s$^{-1}$. For both events, none of $10^{6}$ realizations yield a gravitationally bound orbit ($p_{\rm bound} < 3\times 10^{-6}$). The adopted error model would need to underestimate the true uncertainties by factors of 5--9 for either candidate to be marginally bound.

Topological insulators and skyrmion-hosting, chiral magnetic multilayers are two well-explored areas of modern condensed matter physics, each offering unique advantages for spintronics applications. In this paper, we demonstrate the optimization process for the growth of a Bi$_2$Se$_3$/buffer/[Pt/CoB/Ru]$_{\times N}$ heterostructure that combines these two material classes: the Bi$_2$Se$_3$ epilayer was grown by molecular beam epitaxy before transfer under ultrahigh vacuum to a separate growth chamber where the polycrystalline metallic multilayer was sputter deposited. The structure of the samples was characterized by co-fitted X-ray and polarized neutron reflectometry measurements and scanning transmission electron microscopy. Polarized neutron models and standard magnetometry show that a buffer layer exceeding a critical thickness is required to obtain the desired uniform, perpendicular magnetic anisotropy in every magnetic layer in the multilayer. Samples with both Ta and Mo buffers were used requiring thicknesses of 1.5 and 0.9 nm respectively. In minimizing the Bi$_2$Se$_3$ terracing, buffered samples yield well-defined, out-of-plane, magnetic domains suitable for spin-orbit torque induced manipulation as determined by X-ray photoemission electron microscopy.

Using polarization entangled photon pairs, we demonstrate a robust scheme for quantum illumination and ranging in a lossy environment. Entangled photon pairs are generated in a Sagnac interferometer configuration, yielding high-visibility two-photon polarization entanglement with a measured CHSH parameter of $S =2.802\pm0.002$. One of the photons from the entangled pair is retained as idler and the other one is directed into either of the two paths, namely reference and probe, of which probe is sent toward a distant object through a lossy free-space channel, and the reflected photons are collected after round-trip free-space propagation over distances approaching $1$ km. Remarkably, strong correlations are observed with CHSH values $S >2.6$ even when only a few tens of probe photons are returned, confirming the robustness of polarization entanglement under long-distance free-space propagation. This work reports the robustness of encoding photons in different basis before it is sent towards the object and recovery of polarization entanglement even after a kilometer-scale scattering from the objects, establishing a practical foundation for scalable quantum-assisted object detection and ranging.

It is demonstrated that, within the eikonal approach, the Coulomb corrections to the elastic electromagnetic non-flip and spin-flip proton--nucleus amplitudes are identical when the two amplitudes share the same exponential form factors. This result allows Coulomb corrections to be computed numerically, and with high precision, for both electromagnetic and hadronic elastic $p^{\uparrow}A$ amplitudes in the massless-photon limit, including the effects of soft magnetic photon exchange. The method relies on analytical expressions and numerical integrations over a finite impact-parameter range with nonsingular integrands, providing a practical and systematically controlled framework for phenomenological applications.

Microquasars are primary candidates for Galactic PeVatrons, yet their collective contribution to the cosmic ray (CR) ``knee" remains poorly understood. We investigate this contribution by simulating anisotropic diffusive propagation through the Galactic magnetic field (GMF). Our results demonstrate that the GMF establishes a transport regime where magnetic connectivity between sources and the solar neighborhood determines the local flux. Active sources aligned with local GMF lines, such as Cygnus X-1, exhibit significant flux enhancements, while magnetically disconnected sources, such as V616 Mon, are strongly suppressed. By integrating source evolution with anisotropic transport, we show that the observed proton bump at the CR ``knee" is best reproduced by the cumulative contribution of microquasar remnants, which is often dominated by a few nearby or recent events, rather than the active ones alone. We find that a harder injection spectrum allows CRs from remnants to reproduce the PeV bump after propagation, as low-energy CRs have sufficient time to accumulate while high-energy CRs escape the Galactic plane. Our findings suggest that the integrated history of microquasar remnants, governed by the interplay of source age and magnetic connectivity, is the primary driver populating the observed CR ``knee''.

Cooperative collective dynamics is a principal determinant of the ability of synthetic micromotors to perform specific functions. However, realizing controllable and predictable collective behavior in complex physiological environments remains a significant challenge. Here, we show that collections of enzyme-coated colloids can be designed as various chemical logic gates, which subsequently can be organized into functional logic circuits. These circuits take environmental information as input signals and process it to produce output chemical species needed to achieve specific goals. The chemical computation performed by the circuit endows the active colloidal system with the ability to sense its surroundings and autonomously coordinate its collective motion. The results of simulations of several examples are presented, where self-assembled colloidal circuits can identify invasive threats by their signals, produce and deliver chemicals to the targets to suppress their activity. The results of this work can aid in the design of experimental chemical logic circuits through micromotor self-assembly that autonomously respond to environmental cues to execute specific tasks.

The role of absorption in 3D electron diffraction is established through analytical theory, simulation, and dynamical refinement. A two-beam expression for the absorbed integrated intensity is derived, showing that for $t/ξ_g \ll 1$ reflections follow a uniform exponential decay set by the mean absorptive potential $U_0'$. Many-beam simulations demonstrate that neglecting absorption in dynamical refinement of integrated intensities incurs a residual that increases linearly with thickness and diverges near zone axes. Dynamical refinements were performed on CsPbBr$_3$, quartz, and borane, with the inclusion of absorption yielding an improvement in $R_{\mathrm{obs}}$ from $6.4$ to $5.3$ \% for CsPbBr$_3$ and negligible changes for quartz and borane. Absorption is therefore deemed negligible for routine refinement of integrated intensities except in high-$Z$ materials at thicknesses approaching $ξ_g$.

I argue that spacetime singularities entail no ontological commitment to material entities. First, I show that Penrose's singularity theorem is best understood as a theorem of incompleteness, it demonstrates the failure of specific spacetime models within General Relativity (or any theory incorporating the Raychaudhuri equation) under certain general conditions. Although this has been done before, I adopt a novel approach based on differentiating between physical and purely formal assumptions in the axiomatic foundation of general relativity. Next, I compare Penrose's result with Gödel's incompleteness theorem, highlighting key similarities and differences. Finally, I draw philosophical conclusions regarding the limits and prospects of our epistemic reconstructions of the physical world.

We present a data-driven reconstruction of the late-time expansion history and its implications for dark-energy dynamics. Modeling the reduced Hubble rate with a node-based Gaussian-process-kernel interpolant, we constrain the reconstruction using CC, Pantheon+ SNIa, BAO data from SDSS and DESI, transversal BAO data, and external $H_0$ priors (SH0ES and H0DN). Assuming GR at the background level, we map the reconstructed kinematics onto a dark-energy fluid and a scalar-field description, yielding the total potential and kinetic contributions that reproduce the inferred $H(z)$. To interpret the reconstruction, we consider both a minimal single-field model (canonical or phantom) and a two-field (quintom) system consisting of one canonical and one phantom scalar field (or families). Within the GR-based effective-fluid mapping, the inferred dark-energy density changes sign for all dataset combinations explored, transitioning from $ρ_{\rm DE}<0$ at higher redshift to $ρ_{\rm DE}>0$ toward the present, and defining a transition redshift $z_\dagger$ by $ρ_{\rm DE}(z_\dagger)=0$. A single canonical scalar cannot realize such a smooth evolution during expansion, whereas a phantom field or a two-field quintom framework can accommodate the required behavior; in particular, the two-field system permits smooth phantom-divide crossings at finite $ρ_{\rm DE}>0$ and distinguishes them from the separate notion of a density zero crossing. The reconstructed kinematics admit intermediate-redshift structure in some combinations, including hints of an additional accelerated-expansion interval around $z\sim 1.7$--$2.3$. The present-day equation of state remains close to a cosmological constant: combinations including supernovae give $w_0\simeq -1$, while combinations without supernovae but with an external $H_0$ prior show only a mild preference for $w_0<-1$ at the $\sim1.5$--$1.7σ$ level.

The black hole X-ray binary 4U 1755$-$338 underwent an outburst in 2020 after 25 years of quiescence. The comprehensive spectral analysis revealed that the system has a low interstellar neutral hydrogen column density of $0.34\pm0.01 \times$10$^{22}$ cm$^{-2}$. The outburst began with a low mass-accretion rate and was characterized as a low-luminosity outburst. The radius of the inner accretion disc remained constant throughout the outburst. Additionally, a growing neutral medium with constant density was detected in the local environment of 4U 1755$-$338.The hardness-intensity diagram (HID) did not follow the standard q-shaped pattern, indicating a non-canonical outburst. Instead, the HID showed a correlated evolution of hardness and source flux, suggesting a thermal disc origin of the flux. A wideband spectral analysis was performed using simultaneous NICER-NuSTAR data in two frameworks, based on kerrbb and bhspec. The results of bhspec (kerrbb) based modeling indicate that 4U 1755$-$338 is a high-inclination system, $67.44_{-3.03}^{+9.75}$ ($75.25_{-4.68}^{+5.59}$) degrees, and harbors a moderately spinning black hole with a spin parameter of $0.78_{-0.14}^{+0.02}$ ($0.50_{-0.43}^{+0.19}$) and a mass of $3.37_{-1.04}^{+0.45} (3.28_{-1.1}^{+1.7})M_{\odot}$ respectively. The inferred key parameters: black hole mass, spin, and system inclination are consistent across both modeling approaches. No reflection features were detected in the spectra of 4U 1755$-$338. The high spectral index, the blackbody nature ($L\propto T^4$) of the hardness ratio, the absence of reflection signatures, and the weak variability in the power density spectra indicate that the source remained in the high/soft state throughout the outburst.

We report results of one of the most sensitive pulsar surveys to date targeting the innermost region of the Galactic Center (GC) using the Robert C. Byrd Green Bank Telescope (GBT) at X-band (8--12GHz) using data from the Breakthrough Listen initiative. In total, we collected 9.5 hr of data covering the wider $\sim 8'$ diameter of the GC bulge, and 11 hr on the inner $1.4'$ region between 2021 May and 2023 December. We conducted a comprehensive Fourier-domain periodicity search targeting both canonical pulsars (CPs) and millisecond pulsars (MSPs), using constant and linearly changing acceleration searches to improve sensitivity to compact binaries. Assuming weak scattering, our searches reached luminosity limits of $L_{\rm min} \approx 0.14~{\rm mJy~kpc^{2}}$ for CPs and $L_{\rm min} \approx 0.26~{\rm mJy~kpc^{2}}$ for MSPs -- sensitive enough to detect the most luminous pulsars expected in the GC. Among 5,282 signal candidates, we identify an interesting 8.19 ms MSP candidate (DM of 2775 pc cm$^{-3}$), persistent in time and frequency across a 1-hr scan at a flux density of $S_{\rm min} \approx 0.007~{\rm mJy}$. We introduce a novel randomization test for evaluating candidate significance against noise fluctuations, including signal persistence via Kolmogorov-Smirnov tests and flux-vs-DM behavior. We are unable to make a definitive claim about the candidate due to a mixed degree of confidence from these tests and, more broadly, its non-detection in subsequent observations. This deepens the ongoing missing pulsar problem in the GC, reinforcing the idea that strong scattering and/or extreme orbital dynamics may obscure pulsar signals in this region.

Dynamic volumetric MRI provides valuable information on in vivo motion and biomechanics, with applications spanning cardiac, musculoskeletal, or pulmonary imaging, amongst others. Developing reconstruction methods for time-resolved volumetric MRI is challenging due to the inherently slow acquisition process of MRI, which makes it an active area of research. However, in vivo validation of these methods remains challenging due to the lack of publicly available datasets with fully sampled ground-truth images. Here, we present a publicly available in vivo dataset designed to facilitate the development and validation of dynamic volumetric MRI reconstruction algorithms. Controlled and repeatable deformations of the muscles in the thigh were induced using a pneumatic pressure cuff, enabling the acquisition of both undersampled dynamic data and fully sampled validation images. The dataset comprises multichannel undersampled k-space data from nine healthy volunteers across four different dynamic deformations, with fully sampled validation data for one deformation. Additionally, an anatomical reference scan and muscle segmentation masks are provided for each subject. To illustrate a possible image reconstruction and validation approach, a binning-based reconstruction was performed on the undersampled data from six dynamic repetitions. The resulting images were consistent with the corresponding fully sampled validation images. This dataset offers possibilities for validating and advancing time-resolved volumetric MRI reconstruction methods.

We study the motion of test particles around Kerr--Bertotti--Robinson (KBR) black hole (BH) and explore how the three defining parameters the mass $M$, rotation parameter $a$, and magnetic parameter $B$ influence their dynamics. We derive analytical expressions for the energy and angular momentum of stable equatorial circular orbits, along with the corresponding radial and latitudinal oscillation frequencies, as functions of $M$, $a$, and $B$. We also examine the key features of the quasi-periodic oscillations of test particles near stable circular orbits, including the precession effects such as periastron precession and the Lense-Thirring effect. Finally, we compare our results with those corresponding to the Kerr BH. We find that particle motion is strongly shaped by the BH parameters. Using a WKB approach, we also study scalar quasinormal modes of a rotating KBR BH in an external magnetic field and show that the magnetic field increases damping, while rotation and angular momentum mainly set the oscillation frequencies. Alternatively, general relativistic modelling of Bondi-Hoyle-Lyttleton (BHL) accretion onto a rapidly rotating KBR BH shows that two distinct physical structures emerge and cyclically transform into one another over time. These processes produce either a strongly oscillating flip-flop shock cone or a nearly stationary toroidal structure, with their formation governed by the black hole spin and magnetic curvature. Power spectral analysis shows that these configurations give rise to low and high-frequency quasi-periodic oscillations, offering a unified explanation for the multiple quasi-periodic oscillations observed in rapidly spinning X--ray binaries.

Functional connectivity estimates are highly sensitive to analysis choices and can be dominated by noise when the number of sampled time points is small relative to network dimensionality. This issue is particularly acute in fMRI, where scan resolution is limited. Because scan duration is constrained by practical factors (e.g., motion and fatigue), many datasets remain statistically underpowered for high-dimensional correlation estimation. We introduce a framework that combines diffusion-based structural coarse-graining with spectral noise filtering to recover statistically reliable functional networks from temporally limited data. The method reduces network dimensionality by grouping regions according to diffusion-defined communication. This produces coarse-grained networks with dimensions compatible with available time points, enabling random matrix filtering of noise-dominated modes. We benchmark three common FC pipelines against our approach. We find that raw-signal correlations are strongly influenced by non-stationary fluctuations that can reduce apparent inter-subject variability under limited sampling conditions. In contrast, our pipeline reveals a broader, multimodal landscape of inter-subject variability. These large-scale organization patterns are largely obscured by standard pipelines. Together, these results provide a practical route to reliable functional networks under realistic sampling constraints. This strategy helps separate noise-driven artifacts from reproducible patterns of human brain variability.