We introduce a novel modeling pipeline for strongly lensed point sources, using the GIGA-Lens framework, running on four A100 GPUs via the JAX platform. Using simulations, we demonstrate accurate and precise recovery of image positions, fluxes, and time delays, together with inference of complex lens mass distributions -- including the mass density slope, $γ$ -- from images of lensed point sources alone. We further show that we can achieve statistical uncertainty of $\sim 3.6\%$ ($\sim 2.5\, \mathrm{km\, s^{-1}/Mpc}$) on $H_0$ from a single system, with full forward modeling, i.e., simultaneous inference of all lens model parameters together with $H_0$. We apply our pipeline to two well-studied lensed SNe Ia, Zwicky and iPTF16geu. For SN iPTF16geu, unlike previous modeling efforts, we model only the images of the lensed point source (the SN) and do not use the lensed images of the extended host-galaxy. Nevertheless, we are able to infer all of the mass parameters modeled in earlier studies, and our best-fit values, including $γ$, are fully consistent with published results. In the case of SN Zwicky, taking the same approach, however, we obtain an alternative best-fit model compared to published results, underscoring the importance of fully exploring the model parameter space.

Determining absolute neutrino masses remains a central challenge in particle physics. Relations among the neutrino mass-squared differences could facilitate this determination and shed additional light on the underlying mass-generation mechanism. Inspired by recent global fits of neutrino oscillation parameters, we propose a simple algebraic relation between $Δm^2_{21}$ and $Δm^2_{31}$. It provides a framework to analytically manipulate these parameters and admits specific physical interpretations. In particular, the results may point toward a vanishing $ν_1$ mass.

Monte Carlo simulations of optical photon transport are computationally prohibitive for large-scale optical systems including detector arrays and PET systems, restricting practical use to single-crystal studies. This work presents an enhanced conditional generative adversarial network (optiGAN) replacing optical simulations at the crystal array level, extending our single-crystal approach to a 3x3 BGO array. We enhance the Wasserstein-GAN framework with Fourier feature encoding, a learnable latent mapping network, and a physics-informed loss enforcing momentum conservation. Training data is reduced eight-fold by exploiting symmetry. Evaluation employs three studies: a full array evaluation testing generalization from the fundamental domain to the complete geometry, a high-resolution study probing out-of-distribution generalization to untrained positions, and a pencil beam $γ$-photon study assessing practical applicability for experimental detector characterization. Performance is benchmarked against GATE10/Geant4 ground truth, using intrinsic fluctuations between independent Monte Carlo runs as baseline. OptiGAN achieves sliced Wasserstein similarity within 3$σ$-agreement of the baseline across all conditions, demonstrating successful generalization to the full array. The model transitions from electron-emission training data to realistic $γ$-photon interactions, producing flood maps that reproduce characteristic patterns including photopeak clusters and inter-crystal scatter lines. This proof-of-concept demonstrates that physics-informed generative models can accurately simulate optical photon transport in segmented scintillator arrays. The reproduction of experimentally relevant flood map features validates optiGAN for PET detector development and establishes a foundation for models generalizing across diverse array configurations.

The Colours of the Outer Solar System Origins Survey (Col-OSSOS) measured the optical/NIR colours of a brightness-complete sample of Trans-Neptunian Objects (TNOs). Like previous surveys, this one found a bimodal colour distribution in TNOs, categorised as red and very red. Additionally, this survey proposed an alternative surface classification scheme: FaintIR and BrightIR. Cold classical TNOs mostly have very red or FaintIR surfaces, while dynamically excited TNOs show a mixture of surfaces. This likely indicates that formation locations and proximity to the Sun influenced surface characteristics and color changes. Our study combines the data from Col-OSSOS with two dynamical models describing the formation of the Kuiper belt during Neptune's migration. We investigate the proposed surface-colour changing line and explore the distribution of different surfaces within the primordial disk. By comparing radial colour transitions across various scenarios, we explore the origins of surface characteristics and their implications within the context of BrightIR and FaintIR classifications. Moreover, we extend our analysis to examine the distribution of these surface classes within the present-day Kuiper Belt, providing insights into the configuration of the early solar system's planetesimal disk prior to giant planet migration. We find that the most likely primordial disk compositions are inner neutral / outer red (with transition $30.0^{+1.1}_{-1.2}$ au), or inner BrightIR / outer FaintIR (with transition $31.5^{+1.1}_{-1.2}$ au).

The (holomorphic) partition function of the Euclidean BTZ black hole with boundary modulus $τ$, is the $S$-image of the Virasoro vacuum character, $χ_{\rm vac}(-1/τ)$. This object decomposes into primaries via the modular $S$-kernel: $χ_{\rm vac}\left(-\frac{1}τ\right)=\int_{0}^{\infty} dP S_{0P}(P,c)χ_P(τ)$. In this paper, we provide a bulk understanding of this spectral resolution using the Chern-Simons formulation of AdS$_3$ gravity with $two$ boundaries: an asymptotic torus and an excised Wilson line at the origin ("stretched horizon"). At infinity, we impose standard AdS$_3$ Drinfel'd-Sokolov (DS) gauge to obtain the Alekseev-Shatashvili (AS) boundary action for a coadjoint orbit. At the inner boundary, removing the Wilson line prepares the state at the cut as a sum over orbits of the $spatial$ cycle. Re-inserting a spatial holonomy Wilson line acts as a delta-function projector onto the corresponding primary, which together with boundary gravitons, reproduces the Virasoro character (e.g., of a conical defect). But we can also consider projectors onto the $conjugate$ basis $\tilde P$, of the dual cycle. A key observation is that this leads to $S$-kernels instead of delta functions, with the BTZ character arising when the dual cycle label is in the exceptional orbit. Our two-boundary construction provides a bulk understanding of BTZ entropy: holonomy zero modes at the horizon have an effective central charge $c_{\rm prim}=c-1$ from the kernel measure (primaries), while the universal Dedekind-$η$ in $χ_P(τ)$ contributes $c_{\rm desc}=1$ from boundary gravitons (descendants). Together, they reproduce the full Cardy entropy. While our methods are specific to AdS$_3$/CFT$_2$, they are an explicit illustration that smoothness of the (Euclidean) horizon may emerge from a $sum$ over bulk states which are manifestly unsmooth.

In this work, we study the Hamiltonian Decoded Quantum Interferometry (HDQI) for the general Hamiltonians $H=\sum_ic_iP_i$ on an $n$-qubit system, where the coefficients $c_i\in \mathbb{R}$ and $P_i$ are Pauli operators. We show that, given access to an appropriate decoding oracle, there exist efficient quantum algorithms for preparing the state $ρ_{\mathcal P}(H) = \frac{\mathcal P^2(H)}{\text{Tr}[\mathcal P^2(H)]}$, where $\mathcal P(H)$ denotes the matrix function induced by a univariate polynomial $\mathcal P(x)$. Such states can be used to approximate the Gibbs states of $H$ for suitable choices of polynomials. We further demonstrate that the proposed algorithms are robust to imperfections in the decoding procedure. Our results substantially extend the scope of HDQI beyond stabilizer-like Hamiltonians, providing a method for Gibbs-state preparation and Hamiltonian optimization in a broad class of physically and computationally relevant quantum systems.

Sub-Neptune planets are often modeled with a dense rocky or metal-rich interior beneath a thick hydrogen/helium (H/He) atmosphere; though their bulk densities could also be explained by a water-rich interior with a thin H/He atmosphere. Atmospheric composition provides a key mechanism to break this degeneracy between competing interior models. However, the overall composition of sub-Neptunes inferred from spectra obtained with the James Webb Space Telescope, remains debated in part due to differences in modeling assumptions. While previous studies explored parameter spaces such as stellar spectra, atmospheric metallicities, and carbon-to-oxygen ratios, they often assumed fixed intrinsic temperatures (Tint) and vertical eddy diffusion coefficients (Kzz) - two critical, yet poorly constrained, drivers of atmospheric chemistry. To address this, we present a self-consistent grid of models that covers the full plausible range of Tint (60 - 450 K) and Kzz (10^{5} - 10^{12} cm^2/s) using the open-source PICASO and VULCAN packages to better characterize sub-Neptune atmospheres. Focusing on K2-18b analogs, we demonstrate that Tint and Kzz significantly impact CH4, CO2, CO, NH3 and HCN abundances, with H2O being largely unaffected. Our work demonstrates that comprehensive parameter space exploration of thermal and mixing parameters is essential for accurate interpretation of sub-Neptune spectra, and that single-parameter assumptions can lead to misclassification of planetary interiors. We provide a diagnostic framework using multi-molecule observations to distinguish between competing atmospheric models and advance robust characterization of sub-Neptunes.

Quantum circuits naturally implement unitary operations on input quantum states. However, non-unitary operations can also be implemented through block encodings, where additional ancilla qubits are introduced and later measured. While block encoding has a number of well-established theoretical applications, its practical implementation has been prohibitively expensive for current quantum hardware. In this paper, we present practical and explicit block encoding circuits implementing matrix polynomial transformations of a target matrix. With standard approaches, block-encoding a degree-$d$ matrix polynomial requires a circuit depth scaling as $d$ times the depth for block-encoding the original matrix alone. By leveraging the recently introduced Fast One-Qubit Controlled Select LCU (FOQCS-LCU) framework, we show that the additional circuit-depth overhead required for encoding matrix polynomials can be reduced to scale linearly in $d$ with no dependence on system size or the cost of block encoding the original matrix. Moreover, we demonstrate that the FOQCS-LCU circuits and their associated matrix polynomial transformations can be controlled with negligible overhead, enabling efficient applications such as Hadamard tests. Finally, we provide explicit circuits for representative spin models, together with detailed non-asymptotic gate counts and circuit depths.

Accurately simulating long-time dynamics of many-body systems is a challenge in both classical and quantum computing due to the accumulation of Trotter errors. While low-order Trotter-Suzuki decompositions are straightforward to implement, their rapidly growing error limits access to long-time observables. We present a framework for constructing efficient high-order Trotter-Suzuki schemes by identifying their structure and directly optimizing their parameters over a high-dimensional space. This method enables the discovery of new schemes with significantly improved efficiency compared to traditional constructions, such as those by Suzuki and Yoshida. Based on the theoretical efficiency and practical performance, we recommend two novel highly efficient schemes at $4^{\textrm{th}}$ and $6^{\textrm{th}}$ order. We also demonstrate the effectiveness of these decompositions on the Heisenberg model and the quantum harmonic oscillator, and find that for a fixed final time they perform better across the computational cost. Even when using large time steps, they surpass established low-order schemes like the Leapfrog. Finally, we investigate the in-practice performance of different Trotter schemes and find the decompositions with more uniform coefficients tend to feature improved error accumulation over long times. We have included this observation into our choice of recommended schemes.

The impact of the symmetry energy on the properties of compact stars is analyzed considering constraints from nuclear physics and astrophysics. A compact star can be a neutron star composed only of nuclear matter or a hybrid star with a quark core. Two typical models (soft and stiff) are considered for the nuclear equation of state, and for the hybrid one, a parameterized first-order phase transition approach, completed with a linear quark matter equation of state, is implemented. We show that the phase transition reduces the tension between GW170817 and NICER observations, and we illustrate the impact of the symmetry energy for the understanding of the nature of the binary system in GW170817. We also confirm our previous findings that the GW170817 waveform is best described as a binary HS with a low-density onset of stiff quark matter. This could also be interpreted as a quarkyonic cross-over.

Genuine quantum interference between independent nonlinear processes of different order provides a route to coherent control that cannot be reduced to a classical field interference. Here we present an all-optical analogue of coherent carrier injection by exploiting interference between second- and third-order quantum nonlinear processes in an integrated photonic platform. Photon pairs generated via spontaneous parametric down-conversion and spontaneous four-wave mixing coherently contribute to the same final two-photon state, resulting in a phase-dependent modulation of both the generation rate and the spectral structure of the emitted biphoton state. We illustrate the features of such interference and how it can be used to shape biphoton wavefunctions and their quantum correlations. These results identify interference between nonlinear processes of different order as a distinct form of coherent quantum control within quantum nonlinear optics.

Fault-tolerant quantum computation (FTQC) is expected to address a wide range of computational problems. To realize large-scale FTQC, it is essential to encode logical qubits using quantum error-correcting codes. High-rate concatenated codes have recently attracted attention due to theoretical advances in fault-tolerant protocols with constant-space-overhead and polylogarithmic-time-overhead, as well as practical developments of high-rate many-hypercube codes equipped with a high-performance level-by-level minimum-distance decoder (LMDD). We propose a general, high-performance decoder for high-rate concatenated stabilizer codes that extends LMDD by leveraging the Chase algorithm to generate a suitable set of candidate errors. Our simulation results demonstrate that the proposed decoder outperforms conventional decoders for high-rate concatenated Hamming codes under bit-flip noise.

Magnetic skyrmions are topological quasiparticles potentially useful for memory and computing devices. Antiferromagnetic (AF) skyrmions present no transverse deflection, making them suitable candidates for data storage applications. After the discovery of skyrmions with length scales comparable to the lattice constant, several works presented quantum analogues of classical ferromagnetic skyrmions in spin systems. However, studies about quantum analogues of AF skyrmions are still lacking. Here, we explore the phases of the AF quantum spin-1/2 Heisenberg model with Dzyaloshinskii-Moriya interactions on the triangular lattice using the density matrix renormalization group (DMRG) algorithm. We study the magnetization profile, spin structure factor and quantum entanglement of the resulting ground states to characterize the corresponding phases and signal the emergence of quantum AF skyrmions. Our results support that three-sublattice quantum antiferromagnetic skyrmion textures are stabilized in a wide range of magnetic fields.

The detection of likely thermal ultraviolet emission from a few old neutron stars suggests that at least one internal heating mechanism is present in these stars. One proposed mechanism is rotochemical heating, in which the continuous contraction of the neutron star due to its spin-down produces chemical imbalances that induce Urca reactions, and the latter deposit heat in the neutron star core. If the protons in the star are superconducting, their energy gap suppresses the reactions, except in microscopic magnetized regions (such as quantized flux tubes) in which the protons act as if they were normal. Therefore, the strength of the internal magnetic field controls the rate at which reactions proceed and thus affects the thermal evolution of the neutron star. Here, we present the first comprehensive study of the effect of an internal magnetic field in the superconducting interior on rotochemical heating. We simulate the evolution of neutron stars for different internal magnetic field strengths and neutron energy gaps, comparing the results to Hubble Space Telescope observations of old neutron stars. All the observational data can be accounted for if the proton energy gap is large ($\sim 1.5\,\mathrm{MeV}$) and the neutron energy gap is small ($\lesssim 0.1\,\mathrm{MeV}$) or vanishing, while the millisecond pulsar PSR~J0437$-$4715 needs to have a very weak internal magnetic field. Our results suggest that neutron-star cores are characterized by a large proton pairing gap and a small or vanishing neutron gap, and that millisecond pulsars have very weak internal magnetic fields. Under these conditions, rotochemical heating alone can account for the observed thermal emission of old neutron stars.

This paper aims to first explain, somewhat more clearly, the Stochastic-Quantum correspondence put forward in by Barandes in 2023. Specifically, the quantum-mechanical bra-ket notation is used, illuminating some results of previous results. With this, we prove the six axioms of textbook quantum mechanics from a single axiom: every physical system evolves according to a, generally indivisible, stochastic law. Afterwards, we generalise the treatment to continuous bases, which showcases a problem with them, indicating that space (and other physical variables) may be discrete in nature. Some concrete examples are also given, including the generalisation to classical and quantum fields. Then, we treat some practical issues of this new stochastic approach, regarding the solving of problems in physics, which turns out to still be most tractable in the traditional way. Finally, we explain the classical limit, where a system of many particles is found to behave classically according to Newton's second law. Along with that, we present a way of solving the measurement problem, characterising what is an environment and a measuring device and explaining how the wavefunction collapse comes about. Specifically, it is found that what distinguishes an environment is its number of degrees of freedom, while a measuring device is a low-entropy type of environment.

Today, apart from some isolated R&D efforts, there are no gravitational wave (GW) experiments, yet which explore a large part of the vast frequency range above the LIGO/Virgo band. It is planned to establish an experiment at Deutsches Elektronen-Synchrotron (DESY) and at the Superconducting Quantum Materials and Systems (SQMS) Center at Fermi National Accelerator Laboratory (Fermilab) to search for high-frequency GWs in the frequency range of 10 kHz to 100 MHz. The basic idea is to use superconducting radiofrequency (SRF) cavities to detect tiny harmonic deformations induced by GWs which change the boundary conditions of the oscillating electromagnetic field. This paper summarizes the challenging environmental boundary requirements, and the R&D to operate a cavity using a low level RF (LLRF) system which pushes beyond state-of-the-art accuracy and resolutions and a seismic noise mitigated cryostat at 1.8 K. The focus of this paper is the warm and cold commissioning of a prototype cavity, built 20 years ago during the MAGO collaboration, and its first measurement in our collaborative research project.

One-dimensional kagome strip chains share much of the same frustrated structural motif as two-dimensional kagome antiferromagnets, making them valuable for deepening our understanding of kagome lattice magnetism. In this paper, we report the hydrothermal synthesis and detailed structural and property characterization of Na2Co3(AsO4)2(OH)2, a striped kagome system. The crystal structure was characterized using single crystal X-ray diffraction, which reveals that Na2Co3(AsO4)2(OH)2 crystallizes in the monoclinic crystal system C2/m. The structure features a one-dimensional kagome strip lattice built from Co2+ ions and undergoes an antiferromagnetic transition at TN = 14 K. The magnetic ground state at zero field was characterized using neutron powder diffraction. Below the magnetic transition, Na2Co3(AsO4)2(OH)2 orders into an antiferromagnetic structure with a k-vector (0.5, 0.5, 0.5). In the proposed model, the Co1 moment is predominantly confined to the ac-plane while the Co2 moment is primarily aligned along the b-axis. Two flat bands were observed in the inelastic neutron spectra below the magnetic transition at 5 and 10 meV. Inelastic neutron spectra were modeled with a Heisenberg Hamiltonian including three nearest-neighbor exchange interactions (J1, J2, J3) and strong single-ion anisotropy to stabilize the observed magnetic structure. Our study highlights the complexity of the Co2+-based kagome strip magnetic lattice compound Na2Co3(AsO4)2(OH)2, which provides an excellent platform to broaden our understanding of the frustrated kagome magnetic lattice space.

Pump-probe experiments performed on $\mathrm{K}_3\mathrm{C}_{60}$ have unveiled both optical and transport signatures of metastable light-induced superconductivity up to room temperature, far above $T_c$. Recent experiments have uncovered that excitation in the vicinity of $50 ~\textrm{meV}$ enables the observation of high temperature light-induced superconductivity at significantly lower fluences. Inspired by these experiments we develop a mechanism which can explain such a giant resonant enhancement of light-induced superconductivity. Within a minimal non-linear Holstein model, we show that resonantly driving optical Raman modes leads to a time-dependent electron-phonon coupling. Such a coupling then modulates the effective electron-electron attraction, with the strongest modulations occurring when the drive is resonant with the phonon frequency. These dynamical modulations of the pairing interactions lead to Floquet-BCS instabilities at temperatures far exceeding equilibrium $T_c$, as observed in experiments. We conclude by discussing the implications of our general analysis on the $\mathrm{K}_3\mathrm{C}_{60}$ experiments specifically and suggesting experimental signatures of our mechanism.

This paper presents a feasibility study demonstrating that quantum machine learning (QML) algorithms achieve competitive performance on real-world medical imaging despite operating under severe constraints. We evaluate Equilibrium Propagation (EP), an energy-based learning method that does not use backpropagation (incompatible with quantum systems due to state-collapsing measurements) and Variational Quantum Circuits (VQCs) for automated detection of Acute Myeloid Leukemia (AML) from blood cell microscopy images using binary classification (2 classes: AML vs. Healthy). Key Result: Using limited subsets (50-250 samples per class) of the AML-Cytomorphology dataset (18,365 expert-annotated images), quantum methods achieve performance only 12-15% below classical CNNs despite reduced image resolution (64x64 pixels), engineered features (20D), and classical simulation via Qiskit. EP reaches 86.4% accuracy (only 12% below CNN) without backpropagation, while the 4-qubit VQC attains 83.0% accuracy with consistent data efficiency: VQC maintains stable 83% performance with only 50 samples per class, whereas CNN requires 250 samples (5x more data) to reach 98%. These results establish reproducible baselines for QML in healthcare, validating NISQ-era feasibility.

We show that Schwarzschild primordial black holes (PBHs) formed in the radiation-dominated era can grow extremely rapidly through $\textit{radiative absorption}$ governed by the full Stefan-Boltzmann law. By introducing a principle of isonomy - ensuring identical particle species dependence for Hawking emission and absorption - we find that, whenever the temperature of the PBH environment is larger than the PBH horizon temperature, PBHs generically gain mass. In particular, for PBH masses following the critical collapse mass-scaling law with critical exponent $γ_\mathrm{crit}$, with $γ_\mathrm{crit} \in (0.33, 0.49)$, the aforementioned radiative absorption mass growth mechanism produces a striking effect: PBHs forming with a mass $10^6M_\odot$ during BBN can reach $\mathcal{O}(10^{10} M_\odot)$ within $\mathcal{O}(10^{6} \mathrm{s})$ ($\sim $ 58 days). Interestingly enough, small deviations from $γ_\mathrm{crit}$, depending itself on the number of relativistic species present in the primordial plasma, yield a continuous PBH mass spectrum providing us ultimately with a single, Standard-Model-based explanation for the origin of stellar-mass, intermediate-mass, and supermassive black holes (SMBHs), and naturally accounting for the early appearance of SMBHs. The Schwarzschild treatment presented here can be extended to spherically symmetric cosmological black holes, indicating that radiative absorption is a dominant and previously overlooked PBH growth channel in the early Universe.

Quantum computing requires the optimization of control pulses to achieve high-fidelity quantum gates. We propose a machine learning-based protocol to address the challenges of evaluating gradients and modeling complex system dynamics. By training a recurrent neural network (RNN) to predict qubit behavior, our approach enables efficient gradient-based pulse optimization without the need for a detailed system model. First, we sample qubit dynamics using random control pulses with weak prior assumptions. We then train the RNN on the system's observed responses, and use the trained model to optimize high-fidelity control pulses. We demonstrate the effectiveness of this approach through simulations on a single $ST_0$ qubit.

The identification of the first multi-phonon $γ$-vibrational bands in an odd-odd neutron-rich nucleus of the nuclear chart is presented. These high spin structures of hard to access $^{104}_{41}$Nb$_{63}$, produced in fission, were studied by combining a spectrometer with isotopic resolution coupled to a $γ$-ray tracking array and independently high-fold $γ$ coincidence measurements. Triaxial Projected Shell Model calculations for the high-spin states are in good agreement with the measured observables for the yrast, one-phonon and two-phonon $γ$ bands. The possibility of an oblate shape of an isomeric state and coexistence of triaxial and oblate configurations are investigated from the decay of the 141 keV isomer. The present work illustrates the robustness of vibration excitations in the presence of odd valence proton and neutron as well as the possibly coexisting shapes beyond the $N=60$ transitional region.

The marginal likelihood, or Bayesian evidence, is a crucial quantity for Bayesian model comparison but its computation can be challenging for complex models, even in parameters space of moderate dimension. The learned harmonic mean estimator has been shown to provide accurate and robust estimates of the marginal likelihood simply using posterior samples. It is agnostic to the sampling strategy, meaning that the samples can be obtained using any method. This enables marginal likelihood calculation and model comparison with whatever sampling is most suitable for the task. However, the internal density estimators considered previously for the learned harmonic mean can struggle with highly multimodal posteriors. In this work we introduce flow matching-based continuous normalizing flows as a powerful architecture for the internal density estimation of the learned harmonic mean. We demonstrate the ability to handle challenging multimodal posteriors, including an example in 20 parameter dimensions, showcasing the method's ability to handle complex posteriors without the need for fine-tuning or heuristic modifications to the base distribution.

Assessing whether a noisy quantum device can potentially exhibit quantum advantage is essential for selecting practical quantum utility tasks that are not efficiently verifiable by classical means. For optimization, a prominent candidate for quantum advantage, entropy benchmarking provides insights based concomitantly on the specifics of the application and its implementation, as well as hardware noise. However, such an approach still does not account for finite-shot effects or for quantum error mitigation (QEM), a key near-term error suppression strategy that reduces estimation bias at the cost of increased sampling overhead. We address this limitation by developing a benchmarking framework that explicitly incorporates finite-shot statistics and the resource overhead induced by QEM. Our framework quantifies quantum advantage through the confidence that an estimated energy lies within an interval defined by the best-known classical upper and lower bounds. Using a proof-of-principle numerical study of the two-dimensional Fermi-Hubbard model at size $8\times8$, we demonstrate that the framework effectively identifies noise and shot-budget regimes in which the probabilistic error cancellation (PEC), a representative QEM method, is operationally advantageous, and potential quantum advantage is not hindered by finite-shot effects. Overall, our approach equips end-users with a framework based on lightweight numerics for assessing potential practical quantum advantage in optimization on near-future quantum hardware, in light of the allocated shot budget.

We recently used a large set of Monte Carlo simulations of globular clusters (GCs) to define new fully empirical parameters (named A5, P5, and S2.5) able to trace the internal dynamical evolution of dense stellar systems. These parameters are specifically designed to quantify the steepness of the cumulative radial distribution of stars in the innermost region of the host system, which tends to progressively increase with dynamical aging due to core contraction. Following the original definitions, here we measure A5 and P5 in a sample of 40 Galactic GCs homogeneously surveyed through HST photometric observations. In agreement with the predictions of our simulations, the largest values of A5 and P5 are found for the most dynamically evolved GCs, i.e., those previously classified as post-core collapse systems based on the shape of their density profile, and those characterized by the shortest central relaxation times. Moreover, the new dynamical parameters here measured strongly correlate with A+rh, another fully empirical, independent parameter that traces the dynamical age of star clusters through the level of central segregation of blue straggler stars.

The high spin excited states of Lanthanum isotopes $^{140-143}$La, above the $N=82$ closed shell, have been populated in fission reactions. The prompt $γ$-ray transitions were measured using two complementary methods; a) in coincidence with the isotopically identified fragments produced in the fission of the $^{238}$U+$^{9}$Be system using the VAMOS++ and the AGATA spectrometers and b) high statistics three-fold $γ-γ-γ$ and four-fold $γ-γ-γ-γ$ coincidence data from the spontaneous fission of $^{252}$Cf using the Gammasphere. This work reports the first identification of a pair of parity doublet structures in $^{143}$La and the new high spin level structure in $^{140-142}$La from prompt $γ$-ray spectroscopy. The level structures are interpreted in terms of the systematics of neighbouring odd-$Z$ nuclei above $Z=50$ shell closure and large-scale shell model calculations. The present results indicate the presence of stable octupole deformation, in $^{143}$La. The excitation energy pattern and their comparison with neighbouring isotones, moving away from the N=82 closed shell, point towards a transition from single particle structures to an alternating parity rotational band structure in the La isotopic chain.

Cell motility underlies many biological processes, including cancer metastasis, bacterial infection, and evolutionary adaptation. We introduce a non-equilibrium single-cell motility model inspired by the generalized Langevin equation, which accounts for hydrodynamic friction and correlated propulsion force. From video microscopy of Chlamydomonas reinhardtii algae and Salmonella typhimurium bacteria we extract the propulsion-force dynamics on the single-cell level, which we find to exhibit multi-exponential correlations, not captured by literature non-equilibrium cell-motility models. Based on our data-driven model, we predict the effective cell diffusivities beyond experimentally resolved timescales and demonstrate a diffusivity maximum at intermediate solvent viscosity for both cell types. This means that cells adapt their propulsion-force characteristics according to the solvent viscosity. In addition, our model predicts the power output of single cells, which is on the order of aW for the salmonella and fW for the algae.

The era of multi-messenger astrophysics requires rapid and efficient follow-up of transient events, many of which, such as gravitational waves (GW), gamma-ray bursts (GRB), and high-energy neutrinos, suffer from poor sky localisation. We present tilepy, a Python-based software designed to optimize observation schedules for these events. We here detail the modular architecture of tilepy, which separates high-level scheduling logic from low-level tiling and pointing tools, enabling full adaptability for ground- and space-based observatories. Furthermore, we describe the integration of tilepy into the Astro-COLIBRI platform, providing the community with a user-friendly interface and API for triggering complex observation campaigns in real time.

In this letter we study renormalization group (RG) flows between 2d conformal field theories enjoying extended higher-spin $\mathcal{W}$-symmetry. We propose a new class of RG flows between the diagonal minimal models of $\mathcal{W}_N$-algebra that take the form $\mathcal{W}_N(p,q)\to\mathcal{W}_N(p,kp-q)$. These are obtained by matching the anomalies of the non-invertible symmetry ${\mathrm{Rep}}[SU(N)_{p-N}]$ (and its discrete quotients) that is preserved by special relevant primary fields. This large non-invertible symmetry includes the familiar $\mathbb{Z}_N$ symmetry of the minimal models. Our new flows furnish a significant generalization of the ones recently found in the case of Virasoro algebra, and include all previously known RG flows of $\mathcal{W}_N$. They have the remarkable property of being uniform in the rank $N$ of the $\mathcal{W}$-algebra.

The strong interaction - governed by Quantum Chromodynamics (QCD) - shapes the structure of the visible universe. At about 10 $μ$s after the big bang, the primordial matter made up of quarks and gluons plus leptons, photons and neutrinos, the quark-gluon plasma (QGP), became cool enough to create, in a phase transition, the protons and neutrons of ordinary matter, along with other strongly interacting unstable hadrons. This phase transition was predicted within the framework of QCD and has been studied in accelerator laboratories world-wide since about 40 years. This review will explore recent breakthroughs in the study of the QCD phase diagram. We will highlight measurements of particle production and fluctuations, and compare them to theoretical predictions. We summarize our current understanding of the QCD structure and outline future experimental opportunities with high energy nuclear collisions at fixed-target and collider facilities world-wide.