Papers

Our work explores large-area CVD graphene as a scalable platform for photodetectors. We show that substrate-induced photogating in graphene/SiO$_2$/Si structures enables a photoconductivity signal in mono-, bi-, and trilayer CVD graphene. The devices respond to illumination with photon energies above the Si band gap and do not respond to telecom frequency, suggesting the photoconductivity mechanism through the photogating. Large sample area and gate voltage-dependent resistivity measurements allow us to prove the dominant role of the photogating directly, demonstrating similarity of the capacitive recharging current and the photoresponse. The sensitivity is the highest (995 A/W) for the monolayer graphene. Increasing the number of graphene layers reduces the sensitivity due to screening and parallel conduction, but can improve detectivity by lowering the noise level. The sensitivity of CVD graphene device depends on fabrication route of photolitography: device with metal contacts fabricated before graphene transfer show higher photoresponce. Thus, our work demonstrate the potential of industrially relevant CVD graphene for sensitive photogating-based photodetectors.

Following previous results recently obtained by us, on Information Geometry versus Geometrical Thermodynamics and on the exact calculation of partition functions for extended Souriau Gibbs distributions on Calabi Vesentini manifolds, we study the differential geometry of the corresponding thermo-metrics. A general intriguing scheme is discovered and put into evidence. A small yet significant difference, distinguishes the even from the odd dimensional instance of the microscopic CV manifolds. Apart from that the complete thermo-space is flat when no constraint is introduced. Freezing the magnetic fields, which can be done according to complicated combinatorials, forces the thermo-system to evolve on curved submanifolds of the thermo–space that have a structure depending only on the length of the $n-1$ chain of frozen contiguous magnetic fields. The behavior of Riemann tensor components for such spaces is codified by a symmetric matrix with peculiar behavior along special symmetrically arranged submanifolds that, might be responsible for the generation of curvature walls and for the categorical partitioning of the thermo space. The embedding of this curved submanifold into $\mathbb{R}^{2n-1}$ can be traced back to the vanishing of magnetic fields and, in this case, the flat metric on $\mathbb{R}^{2n-1}$ is the $\mathfrak{a}_{2n-1}$ simple Lie algebra Cartan matrix. In another version the flat embedding reveals the geometric interpretation of the $n$-manifold as a generalized translation hypersurface. The boundary at infinity has a hypercube structure whose face central points and vertices appear, numerically, to be the end-points of all geodesics depending only on their angular slope at the start. This general feature is reminiscent of the causal structure at infinity of Lorentzian space-times and of Penrose diagrams.

Among the other non-noble metals, lead (Pb) is a material of particular interest for plasmonic applications in the deep ultraviolet spectral region. However, experimental studies on its plasmonic performance have not yet been conducted. In this work, the dependence of the optical properties of spherical lead nanoparticles on their diameter is demonstrated. The plasmonic performance of chemically synthesized lead nanoparticles is evaluated at the single-particle level by means of a combination of scanning transmission electron microscopy and electron energy loss spectroscopy. Our findings demonstrate that these nanoparticles support localized surface plasmon resonances across the entire spectrum from near-infrared to deep-ultraviolet. This range was identified as the most extensive among all plasmonic elemental metals, extending to wavelengths below 200 nanometers. Consequently, lead nanoparticles exhibit stable plasmonic performance over a remarkably broad wavelength range, thereby substantiating their potential as a multispectral plasmonic platform.

In this work, we introduce a class of hybrid-parity sliding multiferroics in which the spontaneous ferroelectric polarization is coupled to certain nonrelativistic spin splitting components through interlayer sliding, allowing these components to be reversibly switched in an electrical way. Symmetry analysis identifies coplanar magnets as natural platforms for realizing this form of sliding multiferroicity. First-principles calculations establish bilayer VBr$_2$ as a representative example, demonstrating the coupled reversal of the out-of-plane ferroelectric polarization and the signs of both even- and odd-parity nonrelativistic spin splitting components via an interlayer-sliding pathway. The signs of these nonrelativistic spin splitting components are locked to the sliding-switchable ferroelectric polarization and encoded in the spin-current responses, providing a signature of the coupled ferroic switching. Our findings expand the scope of sliding multiferroics and the functionality of sliding ferroelectrics for low-energy, nonvolatile logic devices.

The Magnusian is a phase-space function that generates finite-time evolution through nested Poisson brackets. It is related to several familiar generators of classical dynamics, including the radial action, the eikonal phase and related quantities. In this work, we extend the Magnusian framework to systems with dissipation and nonlocal-in-time interactions using the in-in formalism, also known as the Schwinger-Keldysh or Galley formalism. This framework is particularly natural for binary dynamics, where integrating out the mediating gravitational field can produce both dissipative radiation-reaction effects and hereditary, nonlocal-in-time interactions. We derive the generalized Magnusian and show that it continues to generate finite-time evolution. As an application, we construct the Magnusian for Newtonian bound motion subject to the leading 2.5PN radiation-reaction force. The resulting generator defines a discrete evolution map from one cycle to the next and describes the evolution of the system in agreement with numerical solutions.

The blazar PKS 0346-27 at redshift z=0.991 is among the most distant extragalactic sources detected in very high energy gamma-rays. It underwent a major flare reaching TeV energies in November 2021. Recent modelling of its spectral energy distribution favoured a single-zone proton–synchrotron-dominated hadronic model with bulk Lorentz factor Gamma=10 over a single-zone leptonic jet model with much higher Gamma. Here we analyse archival radio data to give independent estimates of the jet bulk Lorentz factor. We present high-resolution radio imaging and brightness distribution modelling, as well as flare detection in long-term radio flux density monitoring data, and obtain Gamma<~10 values. This lends support to the hadronic model proposed for the PKS 0346-27 jet. Our results highlight the importance of long-term, very long baseline interferometry and total flux density monitoring in studying blazar jets.

Minimal unbiased compositional change generates the Gaussian source of the compact internal construction. We derive joint constraints on effective couplings and mass scales from its gauge and matter content, scalar sector, spectral endpoint and kinetic normalizations. Compatibility of source and colour screening selects three matter copies. Within the response family indexed by integers, shell support and position retention select the level R=5, whose transverse traceless endpoint equation has a unique positive root. Eliminating shared transfer parameters gives a relation among six geometric fermion masses. Bandwidth variation correlates the electron and electroweak scales, while two cosmological ratios are independent of the common neutrino mass normalization. Finite matching through one loop implements the generated Fermi, top and Higgs conditions in a common action. The absorptive top self energy gives the Born decay width as an additional output. The compact source covariance and positive RMS amplitude determine a local nonlinear flux that couples matter motion to source feedback. A model with an auxiliary radius admits autonomous source evolution, positive reduced propagation forms and a matter phase clock on a specified finite cosmological interval. Physical comparisons use the stated mass definitions, matching and thermal approximations. The fixed DESI DR2 distance comparison gives ḩi}^2 = 29.5087 for thirteen components and p=0.00554, indicating tension in the adopted cosmological mapping. Spectral tail and quadrature bounds control the finite response calculation.

Large ecosystems balance competition and cooperation, yet standard generalized Lotka–Volterra models make mutualism destabilizing by amplifying disorder and driving unbounded growth. We show that Monod-like saturation resolves this paradox: dynamical mean-field theory and random-matrix analysis reveal a broader stable phase and enhanced survival. Network architecture provides a second control mechanism, but nestedness offers no intrinsic stability advantage. Instead, it is a byproduct of degree distributions with high connectivity necessary for stability.

Heterogeneous density functional theory (DFT) calculations, particularly plane-wave implementations, introduce systematic formation energy errors ranging from tens to hundreds of meV/atom, depending on the selection of exchange-correlation functionals, kinetic energy cutoffs, pseudopotentials, and dispersion corrections. As demonstrated by the MatPES dataset, identical structures can exhibit an average energy discrepancy of 107 meV/atom between PBE and r2SCAN calculations. Such method-dependent discrepancies hinder the integration of multi-source DFT data, greatly limiting the scale and quality of datasets for training robust materials AI models. Here, we resolve this fundamental data silo barrier via graph-based transfer learning. Leveraging 380,190 structurally paired PBE-r2SCAN entries from the MatPES database, we train a structure-aware graph neural network to predict cross-functional energy residuals and align inconsistent DFT energy scales. By adopting GPTFF model architecture, the model converts conventional PBE energies to r2SCAN-level accuracy with a mean absolute error of 14.3 meV/atom, compared with 18.2 meV/atom achieved by CHGNet. This versatile approach effectively upgrades massive legacy PBE datasets to high-precision r2SCAN standards. It enables reliable predictions of phase stability, battery voltage profiles, and reaction thermodynamics, while allowing the integration of multi-source DFT data to advance the development of high-performance materials foundation models.

The Julia programming language is considered a strong contender as a future language for high-energy physics (HEP) computing. However, transitioning to the Julia ecosystem will be a long process and interoperability between Julia and C++ is required. So far several successful attempts have been made to wrap HEP C++ packages for use in Julia. It is also important to explore the reverse direction, allowing Julia code to be called from existing HEP codebases, written primarily in C++ and Python, which would significantly improve potential adoption of Julia code. With recent developments in Julia enabling it to produce statically compiled code, this approach is becoming increasingly feasible, and investigating this potential for the benefit of HEP community is the focus of this work. This work presents a case study of statically compiling the JetReconstruction.jl package - a highly performant, native Julia implementation of sequential jet reconstruction algorithms. Two different backends for Julia code compilation are compared: the existing PackageCompiler.jl and the new static compilation feature of Julia language, which is one of the major improvements in the Julia v1.12 release. The performance of the statically compiled JetReconstruction.jl is compared with both native Julia code and C++ FastJet.

We propose a fast laser pulse sequence for the generation of non-thermal Fock state mixtures of the motion of a trapped ion, targeted at displacement metrology beyond the standard quantum limit. Using a polaron-frame description of the ion-laser interaction, we identify a resonant operating point-zero detuning and a Rabi frequency matching the trap frequency-at which selective population trapping survives strong driving, enabling preparation speeds beyond the weak-driving limit of previous protocols without requiring ground-state cooling. We trace the residual infidelity at large Lamb-Dicke parameter $\eta$ to a single coherent process, the counter-rotating blue-sideband term neglected in the rotating-wave approximation, and show that it is suppressed by two routine calibrations: a percent-level refocusing of the pulse duration and a small compensating Bloch-Siegert detuning. Numerical simulations of the full sequence show that this refinement keeps the preparation error at or below the $10\%$ level up to $\eta\approx0.5$ and restores the displacement-sensing Fisher information that the uncorrected protocol loses at strong coupling, recovering up to 9 dB relative to the nominal sequence.

We analyze the semileptonic $B \to T\ell^+\ell^-$, $B \to T(\to PP)\ell^+\ell^-$, and $B \to T(\to PV)\ell^+\ell^-$ decays with $\ell=e,\mu,\tau$ based on flavor SU(3) analysis in the standard model ($T$ denotes the light tensor meson, $P$ denotes the light pseudoscalar meson, and $V$ denotes the light vector meson). The hadronic amplitudes of the $B \to T\ell^+\ell^-$ decays are related by the nonperturbative parameters, and all branching ratios of the $B \to T\ell^+\ell^-$ decays are obtained by the experimental data of the branching ratio of $B^0_s\to f^{\prime}_{2}(1525)\mu^+\mu^-$ in three cases, and then the branching ratios of the $B \to T(\to PP)\ell^+\ell^-$ and $B \to T(\to PV)\ell^+\ell^-$ decays are predicted by the narrow width approximation and further considering finite width effects of the intermediate resonances. Compared with the narrow width results, the finite width effects slightly reduce the branching fractions for most decays. However, sizeable finite width effects are found in some near threshold modes. For the subthreshold $K_2^*(1430)\to K\eta'$ relevant channels, the finite width of the tensor resonance can open a nonzero contribution. Compared with the measured $B \to PP\ell^+\ell^-$ and $B \to PV\ell^+\ell^-$ decays, we find that the branching ratios with the tensor resonance states are small. Therefore, other resonances, for example, the vector mesons, the scalar mesons, the axial-vector mesons or their excited states, might give the dominant contributions to the relevant decays. Our results might be tested in current and future experiments.

Classical early-warning signals assume that recovery slows near a tipping point, but in a well-studied CESM simulation of AMOC collapse, autocorrelation and variance decrease instead. We develop a preregistered diagnostic that uses only past data to estimate the slowest mode of a memory operator fitted to the evolving overturning structure. The operator ensemble produces an exploratory alarm 77 years before collapse, compared with 29 years for a physics-based freshwater-transport indicator. A blind test on the recovery branch does not validate the same timing rule, supporting interpretation of the diagnostic as a proximity measure rather than a universal clock. In nine additional simulations, it warns before all four finite-rate forced transitions but not before three rapid noise-induced collapses available only as scalar AMOC records. Matched ablations show that the signal depends on long-timescale memory and vertical overturning structure rather than trend, forcing, or multivariate information alone.

Problem 5 in Five Open Problems in Quantum Information Theory [PRX Quantum 3, 010101 (2022)], asks whether the two-ququart Werner state $\varrho(4,-\tfrac12)$ is two-copy distillable, where $\varrho(d,\alpha)=(I+\alpha F)/(d^2+\alpha d)$. We answer it in the negative. To this end, we show the following stronger statement: for all $C\in M_{d_1d_2}(\mathbb{C})$ of rank at most $r \le d_1 d_2$, $\mathrm{tr}_1(C)\|_F^2+\|\mathrm{tr}_2(C)\|_F^2 \le r\|C\|_F^2+\frac{1}{r}|\mathrm{tr}(C)|^2$. A result by Costa Rico on the equivalence of this inequality with two-copy undistillability at $r = 2$ then settles Problem 5: $\varrho(4,-\tfrac{1}{2})$ is not two-copy distillable. Furthermore, we show that $\varrho(d,\alpha)$ is two-copy undistillable for every $d\ge2$, if and only if $\alpha\ge-\tfrac{1}{2}$. Thus, the one and two-copy distillability regions of $\varrho(d,\alpha)$ coincide. These results have been found and written up with AI tools, pointing towards a structural change affecting the field of quantum information and computation.

Colliding winds in massive-star binaries generate non-thermal radio emission and an increased X-ray emission. We study the radio emission of the non-thermal emitter 9 Sgr, which is a long-period and highly eccentric binary. We conducted a monitoring campaign of 9 Sgr around its 2013 - 2014 periastron passage, obtaining radio, X-ray and optical spectroscopy data. In this paper, we analyse the radio data. The radio data at 3.6, 6 and 20 cm show a maximum near periastron. Other non-thermal radio emitters among O-type binaries have a minimum flux near periastron, because the synchrotron emission is absorbed by the free-free absorption in the two stellar winds. This is not the case for 9 Sgr, because even at periastron the orbital separation is sufficient to maintain the wind-wind collision and its associated synchrotron emission outside the effective free-free radius of both stars. Our standard modelling with a local magnetic field that decreases inversely proportional to the distance from the stars (1/r) fails to explain the observed fluxes. Instead, we need to adopt a local magnetic field that decreases faster than 1/r. While our model provides an acceptably good fit to the data, there is clearly still room for improvement. More advanced modelling should include magnetohydrodynamics and more detailed physics of the injection, acceleration and cooling of the relativistic electrons. Radio observations at orbital phases away from periastron can put further constraints on the models.

We formulate a statistical physics framework to model a networked stochastic dynamical system exhibiting bistability, driven by additive noise and social conformity. We apply this model to understand and mitigate AI-induced delusional spiraling-a phenomenon where algorithmic sycophancy from Large Language Models continuously reinforces inaccurate beliefs within a socially interacting society. By partitioning the network into a majority of regular agents and a minority of "aware" nodes (Teachers) placed at topological hubs, we use a degree-weighted mean-field approximation to reduce high-dimensional coupled Langevin equations into a single macroscopic drift equation. We provide a closed-form analytical derivation for the deterministic critical tipping time through a saddle-node bifurcation. We validate this analytical boundary using finite-size scaling and demonstrate a universal data collapse across diverse network topologies. Finally, we optimize an intervention strategy under a strict budget constraint that balances the topological footprint against driving velocity. We prove mathematically that under certain conditions, a highly concentrated, rapid intervention targeting massive hubs strictly outperforms a distributed, slow approach to rescue the network.

We present an all-to-all quantum-level crosstalk characterization of a commercial 16x16 MEMS optical switch for multi-user quantum communications using SNSPDs, correlating experimental data with a theoretical impact analysis on the decoy-state BB84 QKD protocol.

We describe and compare in this paper two common methods to measure the half-wave voltage (Vpi) of an electro-optical modulator versus RF frequency of the driving electronic signal. We detail the required calibration procedures when necessary and demonstrate the methods experimentally from 100MHz up to 40GHz. Guidelines are finally given to select the most appropriate method depending on the application and modulator characteristics.

The Planck all-sky surveys at (sub)millimeter wavelengths enable us to accurately determine the corresponding local luminosity functions up to the highest luminosities. The detected galaxies are strictly local, so evolutionary effects, which are known to be particularly strong at these wavelengths, are not a problem. However, previous studies have so far relied only on the Planck Early Release Compact Source Catalog (ERCSC) for this purpose. Another important improvement over earlier estimates is the availability of complete all-sky catalogs of galaxies within hundreds of megaparsecs, with redshift-independent distances for nearby objects, for which redshifts are not reliable distance estimators. In this paper we re-estimate the (sub)millimeter local luminosity functions using data from the Second Planck Catalog of Compact Sources, which supersedes the previously used ERCSC and contains far more sources and more accurate photometry. We computed the luminosity functions using both the classical $1/V_{\rm max}$ and the nonparametric kernel density estimation (KDE) method, which overcomes limitations of binning techniques. Our implementation of the KDE uses the $1/V_{\max}$ weighting to account for survey selection effects. We obtain Planck-based local luminosity functions at 857, 545, 353, and 217 GHz, as well as the total IR luminosity function and the dust mass function. We find significant differences from earlier estimates and discuss their possible origins.

Quadratic unconstrained binary optimization (QUBO) has emerged as a powerful framework for medical computing problems. Binary decision variables naturally represent clinical choices, making QUBO formulations well-suited for quantum annealing hardware. However, a fundamental scalability challenge limits practical deployment: problem size grows rapidly with input dimensionality, creating computational bottlenecks that restrict applications to simplified scenarios. This paper addresses this challenge through hierarchical problem reduction, as demonstrated in medical image segmentation, where pixel-level QUBO formulations create over 65,000 variables for a 256x256 image, forcing existing approaches to downsample to 42x42 resolution and discard 97% of pixel information. A superpixel-based QUBO framework is proposed using simple linear iterative clustering (SLIC) to group pixels into perceptually meaningful regions, then formulate segmentation as QUBO over a region adjacency graph (RAG) combining min-cut and smoothness objectives. Validation on INbreast mammography breast cancer images demonstrates a 4.2% improvement in segmentation quality (mean IoU 0.76 vs 0.73) with 33 computational speedup (0.67s vs 21.97s) and a 97.3% reduction in problem size (1764 to 48 variables), all achieved while processing full-resolution images rather than downsampled versions. The reduced problem size also fits well within current quantum annealer connectivity limits, removing the embedding overhead that has historically blocked direct deployment of pixel-level QUBO segmentation on quantum hardware.

Gas bubbles evolving on electrodes during water-electrolysis are blocking active reaction area, thus hindering mass transfer and raising Ohmic resistance. Unlike earlier models that prescribe a uniform current density on the wetted part of the electrode, we resolve the primary electric field, which allows the current density and the interfacial gas production to respond to the geometry of the electrode and the temporal evolution of the bubbles. Using three-dimensional geometrical volume-of-fluid (VOF) simulations with phase change in Basilisk, we examine the growth of single-bubbles on electrodes of different size and of multiple bubbles growing on arrays of catalytic electrode islands. The non-uniform current density and the associated Ohmic resistance significantly affect the growth dynamics. Unlike the case of a single bubble, the outer bubbles in case of electrode islands tend to drift outward during growth, thus delaying full electrode coverage and sustaining current. Footprint tracking and a theoretical analysis show that this drift is governed by the liquid advection driven by the growth of neighboring bubbles, scaling with their separation 1/d2, and modulated by the current-density asymmetry. These results show how electrode patterning and bubble spacing can be exploited to tailor the electric field distribution and reduce bubble-induced resistive losses during water electrolysis.

Young M-type stars exhibit frequent flares, which would seriously impact their habitable planets. Since stellar surfaces cannot be resolved, flare locations remain unknown. Here, by using the Mg I b emission line in LAMOST spectra, the location of a stellar flare from a young M dwarf is pinpointed at $ (-123.0^{+8.0}_{-5.8}, 80.5^{+2.9}_{-3.2})$ in degree in the polar region. Our method can be used to accurately locate stellar flares. This would enable us to assess the impact of stellar flares on planets more accurately and improve our understanding of stellar dynamo models.

Pre- and post-selection (PPS) paradoxes are striking demonstrations of quantum nonclassicality. Logical PPS paradoxes, where inferences made with the Aharonov-Bergmann-Lebowitz (ABL) rule are exactly 0 or 1, are linked to contextuality. Non-logical paradoxes lack this strong signature. In this work, we analyse more general, non-logical PPS scenarios involving mixed pre- and post-selected states. We show that two such scenarios, the $N$-box and quantum pigeonhole paradoxes, require coherence of both pre- and post-selected states in the basis of the intermediate measurement. This is done by showing each paradox holds if and only if there is weak-value anomaly for a single, paradox-specific operator, together with the fact that weak-value anomaly requires coherence. This clarifies the role of different notions of nonclassicality in these scenarios, highlighting the required quantitative departures from (strictly) classical explanations provided by incoherent sub-theories of quantum theory.

We develop from first principles the hydrodynamics of a two-dimensional chiral fluid, i.e. one carrying a net microscopic angular-momentum (spin) field. Enforcing angular-momentum conservation without imposing stress-tensor symmetry, we derive the full form of the stress tensor and of the spin flux, and we show that the entire chiral response is generated from the classical Newtonian one by a single operation of direct physical origin — the $90^{\circ}$ rotation through which chirality acts, mirrored at the particle level by transverse forces (Caprini & Marini Bettolo Marconi 2025). Applied to the irreducible (deviatoric) decomposition, the rotation assigns to each classical channel a chiral partner — pressure to chiral pressure, bulk and shear viscosities to their odd counterparts, the spin-flux gradient to its rotated image — one coefficient and one mechanical action per channel, with no further cross-couplings. In this representation the steady base states become elementary. Quiescent states are organised by a holomorphic chiral complex potential, the mechanical and chiral pressures forming a conjugate harmonic pair subject to a topological existence condition; inhomogeneous activity forces azimuthal flows; and a boundary-driven confined flow, the chiral Stokes cavity, obeys a modified Helmholtz–Poisson system, solved in closed form in a circular domain and numerically in a square one. A single dimensionless group controls both geometries and sets the crossover from a screened, single-vortex regime to a sequence of sign-reversing vortical structures. The theory yields quantitative predictions, amenable to direct comparison with experiments on air-fluidised chiral disks (López-Castaño et al. 2022), and recovers the phenomenological frameworks of the chiral-fluid literature as particular cases.

Lab-scale organic solar cells have shown high efficiency and strong potential for large-scale production. Among the fabrication techniques for upscaling production, roll-to-roll slot-die coating offers a cost-effective route toward scalable manufacturing. However, reliable in-line metrology is needed for real-time assessment and quality control of the coating during roll-to-roll manufacturing. In this work, we employ a hyperspectral camera for inline monitoring of P3HT and OIDTBR active layers in a roll-to-roll setup. Using multivariate curve resolution, we reliably resolved the spatial distribution of donor and acceptor contributions in the coating. Furthermore, by fitting the absorbance spectra of P3HT, we map the exciton bandwidth, providing insights into the polymer's aggregation and chain interactions. These results demonstrate the potential of hyperspectral imaging as a powerful tool for real-time monitoring and quality control in large-scale organic solar cell production.

We study the inflationary primordial perturbations in $\kappa$-Minkowski non-commutative space-time, a Lie-algebraic type deformation of canonical space-time motivated by quantum gravity scenarios. Employing the $\kappa$-deformed star product formalism, we construct the bilinear action for curvature perturbations and derive the $\kappa$-deformed Mukhanov-Sasaki equation and obtain the perturbative solutions. Further, we compute the primordial power spectrum and spectral index, showing that the leading order corrections to the power spectrum induces scale-dependent term proportional to $(\ln k)^2$. The spectral index also exhibits an explicit $\ln k$ dependence, which persists even when the slow-roll parameters are constant. We also perform a Bayesian MCMC analysis using ACT DR6 data and constrain the $\kappa$-deformation length scale to $\lambda=6.32^{+6.00}_{-4.30}\times10^{-30}m$ at $1\sigma$ CL, approximately four orders of magnitude larger than the Planck scale, demonstrating that the $\kappa$-deformed space-time offers a potential window into quantum gravity phenomenology through precision cosmology.

The vast chemical design space and complex, interdependent design variables make catalyst discovery for targeted properties highly labor- and resource-intensive. Although generative models have emerged as a promising solution, existing approaches are generally limited to single-property conditioning or narrow chemical spaces. Here, we present Catalyst Diffusion Transformer (CatDiT), a unified framework for inverse catalyst design that generates valid and novel structures ranging from intermetallic alloys to oxide surfaces. By learning compressed latent representations, CatDiT enables efficient training and rapid sampling while supporting simultaneous conditioning on adsorbate type, binding energy, and catalyst class. The model provides reliable control of discrete properties and directional control of continuous properties, enriching candidate pools for reaction-specific catalyst discovery. As a representative application, multi-conditional generation for the nitrogen reduction reaction (NRR) yields 28 density functional theory (DFT)-relaxed alloy candidates that satisfy the target activity window and lie above the pure-metal *N-*H scaling line, corresponding to a ~1.5-fold enrichment over the source distribution. These results establish CatDiT as a practical and scalable approach for property-directed catalyst inverse design and targeted catalyst generation.

We consider the interaction of dynamical quarks with the ensemble of oriented and nonoriented center vortices proposed to describe flux-tube formation between quark probes in pure Yang-Mills theory. The quark sector is described in terms of bosonized color currents. Within this fluid-like framework, the infrared vortex–monopole condensate restricts finite-energy configurations to be color neutral. Furthermore, neutral distributions of constituent color densities embedded in the condensate generate frustrated regions, providing a mechanism for their localization into finite-size configurations. The resulting picture is consistent with lattice evidence indicating that center vortices play a central role in shaping the hadron spectrum.

We are developing a new implementation of Compton imaging for nuclear medicine using a large volume of stacked monolithic silicon sensors. In this work we investigate how the spatial resolution is impacted by the pixel size, an important input to the design of the sensors. In general CMOS design is less challenging with larger pixels leaving more space for analog and digital electronics. On the other hand, spatial resolution is one of the key parameters that will impact the performance of the Compton imaging system. It is also important to consider the range of the recoil electron produced in Compton or photoelectric interactions, which impacts how accurately the interaction point can be estimated. The achievable resolution was evaluated with two interaction position reconstruction algorithms: one based on a Gaussian fit of the detected charge and a second based on the characteristic energy deposition along the electron track, with the former performing better at lower energies. Monte Carlo simulations were performed for 140 keV and 511 keV sources embedded in a water phantom, with pixel pitches ranging from 25 $\mu m$ to 250 $\mu m$. Energy-averaged in-plane resolution degraded from 8 $\mu m$ to 94 $\mu m$ as pixel size increased. The out-of-plane resolution was 216 $\mu m$ at low energies, limited by sensor thickness, and improved to 155 $\mu m$ at higher energies. The results suggest that pixel sizes in the order of 100 $\mu m$ can achieve spatial resolutions on the order of tens of micrometers.

Quantum computers are more widely available than ever, making the field more accessible and widespread. Practitioners are coming from a wide range of domains, conducting experiments and research using quantum computing approaches across a variety of problems. The current literature suggests that developers follow certain methodologies in quantum software development, often with a matching set of tools provided. Yet with the novel paradigm, there are areas that remain unaddressed in practices and tools. In this article, we go into the details of experiment tracking in quantum software development. We explain the basic concept of experiment tracking and detail how, in essence, quantum computing sets demands on tracking practices. Given the experimental state of hardware and the constantly evolving software, quantum execution must be monitored, marginal gains aggregated for the best outcome, and error sources detected. In our case study, quantum reservoir computing for chaotic time series data prediction with error mitigation, we present a detailed quantum software development process and describe how experiments can be tracked throughout development. We then generalize this knowledge into the broader quantum development process.