Papers

We provide a rigorous Laughlin-pump argument that establishes the fractional quantization of the Hall conductance directly from the Laughlin state as a topological index. Our proof uses a recently defined index of a pair of pure states together with an infinite matrix product state analysis that is rigorous on a sufficiently thin cylinder. By virtue of the connection to an index, our result implies, in particular, that Laughlin states are representatives of topologically stable fractional quantum Hall phases.

This work introduces a frequency synchronization circuit model for analog vector-matrix multiplication in the frequency domain. The frequency synchronization is implemented by coupling oscillators through all-to-all connections. Each oscillator is implemented using complementary cross-coupled transconductance pairs and RC high-pass filters. In this work, the frequency synchronization is achieved not only using oscillators alone but also through a configuration in which oscillators and resonator models (i.e., MEMS/NEMS resonators) are combined. While addressing the frequency synchronization of all the coupled oscillators, a partial synchronization is also discussed by controlling the coupling strength of a selected subset of oscillators. This frequency synchronization analysis focuses on the small-signal analysis using analog circuit and resonator models, thereby enabling an understanding of the synchronized frequency defined by the parameters of the analog circuit and resonator models.

The way in which classical data are encoded into quantum states plays a significant role in both classification performance and quantum circuit complexity in Quantum Machine Learning. In this study, the effects of different quantum feature encoding strategies on Quantum Support Vector Machine performance were investigated using five binary classification datasets. In particular, the statistical relationships between features were incorporated into quantum circuits through \(RY(\theta)\) and controlled-\(RY(\theta)\) gates, and this approach was compared with conventional quantum feature maps. The results demonstrate that incorporating statistical relationships into the encoding process can influence classification performance. However, more complex and densely entangled circuits do not necessarily yield higher performance. In addition, a composite evaluation metric was employed to jointly assess predictive performance, generalization, and circuit cost. The findings across the five datasets indicate that the choice of quantum feature encoding strategy should account for the underlying structure of the data and that predictive performance should be evaluated together with quantum circuit complexity.

How do organisms navigate when the signals guiding them are noisy? Variance adaptation, the rescaling of sensitivity to noise, is common in sensory systems, but its role in navigation is unexplored. We introduce a minimal active Brownian particle whose run-and-tumble policy follows from an optimality principle. Variance adaptation emerges as part of this policy. Adaptation keeps chemotactic drift finite as noise grows, while a non-adaptive particle's collapses exponentially. Adaptation also carries a cost, degrading performance in quiet environments and requiring a tuned adaptation sensitivity.

Using advanced density functional theory, this study demonstrates the robust thermodynamic, structural, and dynamical stability of pristine, 3d-doped (Ti, Cr), and 4f-doped (Ce) transition metal trichlorides (MCl3). While standard generalized gradient approximation (GGA) incorrectly predicts metallic behavior, hybrid functional calculations successfully capture their semiconducting nature, yielding accurate band gaps of 2.54 eV (VCl3), 4.01 eV (CrCl3), and 2.61 eV (TiCl3). These materials exhibit intrinsic ferromagnetism, with CrCl3 displaying overlapping topological features in both its magnon and phonon dispersions along the high-symmetry K direction, which induces magnon-phonon coupling. Incorporating 3d dopants into VCl3 successfully tunes the bandgap (1.32 eV for Ti and 2.74 eV for Cr) without destroying ferromagnetism, while 4f Ce-doping in CrCl3 introduces localized states below the Fermi level that yield strong nearest-neighbor exchange coupling. Ultimately, this electronic and magnetic tunability highlights the potential of these 2D trichlorides in advanced spintronic functionalities.

Measurements of thermal X-ray flux emitted by neutron stars can constrain their radii and the equation of state of cold dense matter. Accurate flux modeling of rapidly rotating neutron stars requires an approximation for their oblate surface shape, usually given by a shape function. We examine the accuracy of five shape functions by comparing them against numerical relativistic stellar surfaces for seven representative equations of state over a broad range of compactness and spin. We characterize their errors in the surface radius and their derivative with respect to colatitude, test the extent of quasi-universality, and propagate these errors into the differential solid angle d{\Omega}, a geometric factor underlying the observed flux, under the oblate Schwarzschild approximation. We find that the shape functions produce distinct error patterns associated with their forms and parameter ranges. These errors remain structured in compactness, spin, and colatitude. Simple polynomial corrections substantially reduce the radius errors of several shape functions, with most corrected errors within approximately 0.5%. We show that errors in d{\Omega} may be understood as coming from an area contribution, which scales with twice the relative radius error, and a projection contribution controlled primarily by the error in the surface derivative. The projection contribution grows towards the limb, where small surface errors can produce much larger local errors in d{\Omega}. We provide a set of guidelines for the construction of improved quasi-universal shape functions that can be used in future radius estimation efforts. Our recommendations include that both the shape and its derivative be modeled accurately, that more accurate predictions of the polar radius be developed, and that the shape function be calibrated over the same compactness-spin range that is to be tested.

Topological quantum memories need decoders that are both reliable and scalable, but these goals compete: globally informed decoders are accurate near threshold yet expensive, while strictly local rules are fast but can miss long-range structure. Motivated by recent recoverability and mixed-state viewpoints, we make this tradeoff operational for the dephased toric code through a decoder-level local recoverability diagnostic. We compare global MWPM corrections to quasi-local corrections inside a target region and define a matching ratio $R_{\mathrm{match}}$, with mismatch $\epsilon_{\mathrm{match}}=1-R_{\mathrm{match}}$. Across geometry families, $\epsilon_{\mathrm{match}}$ shows strong buffer-controlled suppression and is well organized by a two-geometry scaling form. For scaled families, especially $a=b=d/8$, $R_{\mathrm{match}}$ exhibits a clear crossing and finite-size collapse near $p\!\sim\!0.09$, consistent with a growing recoverability scale near the decoding transition. We use this scaling to formulate an adaptive buffer-selection rule and to identify a distance-scaled initialization for a composite quasi-local RG decoder on the full torus. In the tuned family $a_0=b_0=d/8$, the resulting logical-failure curves show an apparent finite-size crossing at $p\simeq0.09$–$0.10$, below the conventional MWPM threshold scale. We focus on dephasing noise with perfect syndrome measurements to cleanly isolate the underlying behavior.

The United States allots USD 15 billion for lead service line replacement in proportion to documented lead, the largest of a growing class of environmental-indicator transfers. Reconstructed exactly, the rule prices looking below zero. Resolving an unknown pipe lowers a state's expected allotment in three of the eight jurisdictions we can measure above the statutory floor, and raises it in none. Below it the allotment cannot move. Systems filing nothing are scored lead-free. We prove no fixed formula on self-reported inventories can pay for need without punishing its measurement, so we made an audited one. The unique additive repair credits unknowns at a rate no filing can move, and is strategy-proof. Discovery is repriced from a median loss of USD 48.63 per line per year to zero. Allocation swings fall from 16.5% of the pool to 0.8%, for an audit costing 1.23% of annual funds. The formula's tilt toward vulnerable systems survives.

Hyperbolic materials, which exhibit an extreme form of birefringence enabling the volume confinement and frequency-dependent propagation of deeply sub-diffractional optical modes, offer the opportunity for extreme confinement via the stimulation polaritonic modes, with substantially higher confinement obtained through the efficient excitation of of the higher-order (shorter wavelength) hyperbolic polaritonic modes, which they can support. However, while these higher-order hyperbolic polaritons (HO-HPhPs) form high-momentum ray-like propagation within the bulk, efficient excitation of these modes, especially in contrast to the long-wavelength lower-momentum surface polariton propagating modes, has remained a challenge. Critically, the large momentum mismatch between these modes and free-space light, alongside the spatial mismatch between the sub-diffractional scatterer and the distinct modal distribution of HO-HPhPs, lead to a suppressed launching efficiency of these higher-order modes, limiting their use in nanophotonic applications. Here, we report the experimental observation of a 10-fold enhancement in the excitation efficiency of HO-HPhPs through the use of subsurface scatterers over traditional surface scattering (e.g. a flake edge or gold launcher) within single-crystalline {\alpha}-MoO3 slabs. We employ full-wave numerical simulations to investigate the role of the spatial overlap between HO-HPhP modal distributions and the scatterer placement upon excitation efficiency. Furthermore, we develop a generalized process using transfer matrix method to selectively design modal HO-HPhP excitation, which advances the capabilities of HPhP multiplexing for on-chip applications.

Quantum Yang-Mills theory in Euclidean AdS$_4$ with Neumann boundary conditions is studied as a function of the complex couplings $\frac{1}{g_\pm^2} \equiv \frac{1}{g^2}\mp \frac{i \theta }{8 \pi^2}$. We define a "self-dual limit" by $g_- \to 0$ with $g_+ ~{\rm fixed}$. We argue that the limiting theory is well-defined perturbatively and equivalent to the BF formulation of self-dual Yang-Mills theory with a particular boundary condition relating $B$ and $F$ at the boundary $\partial$AdS$_4$. $g_+$ is the loop-counting parameter of the self-dual theory. This is in stark contrast to flat space, where $\theta$ has no effect on perturbative dynamics. In the self-dual limit, it is shown that all tree-level zero-plus and single-plus boundary correlators vanish. A closed form expression is given for any number of gluons for the double-plus tree correlators. Finally, we show that in the flat space limit of AdS$_4$, the total energy poles in the tree boundary correlators correctly reduce to the single-minus gluon amplitudes.

Supermassive black holes (SMBHs) and their host-galaxies coevolve through channels such as hierarchical merging and AGN feedback, establishing tight scaling relations between SMBH masses and properties of the host-galaxy. These scaling relations, particularly those with host-galaxy bulge mass (M${_\text{b}}$) and stellar velocity dispersion ($\sigma$), are widely used to estimate SMBH masses. Galaxy mergers drive gas into the centers of galaxies, enhancing SMBH growth and stellar bulge growth but not necessarily in tandem, so it is necessary to determine if galaxies undergoing a merger still follow SMBH-host-galaxy scaling relations. In this study, we explore scaling relations in galaxy mergers by taking advantage of the well-established value-added catalogs in the Sloan Digital Sky Survey. These catalogs provide close galaxy pairs, AGN broad lines for SMBH mass measurements, and bulge-disk decomposed stellar masses. We compare SMBH mass estimates from M$_\bullet-$M${_\text{b}}$ to SMBH mass estimates from AGN broad lines and find that SMBH mass growth outpaces the bulge for AGN residing in the secondary (less massive) bulge and for smaller physical separations between galaxies in a pair. Using our full sample of close galaxy pairs, we find that M$_\bullet-$M${_\text{b}}$ and M$_\bullet- \sigma$ predict significantly different fractions of major and minor black hole mergers with M$_\bullet-$M${_\text{b}}$ predicting black hole mass ratios closer to 1:1 and $6-20\%$ more major mergers overall. These results have major implications, including for predictions of astrophysical gravitational-waves and high-redshift overmassive SMBHs.

In this thesis, we study the spectral properties of dynamically defined aperiodic metric and discrete graphs. Our goal is to determine to what extent spectral properties of discrete one-dimensional ergodic Schrödinger operators persist when the aperiodicity is manifested through the geometry rather than through a potential. The graphs considered here are inspired by one-dimensional aperiodic tilings, and are called tiling graphs and decorated $\mathbb{Z}$-graphs. For a large family of metric tiling graphs equipped with the standard Laplacian, we show that the spectrum is of zero Lebesgue measure, and is a generalized Cantor set up to a possible discrete set of energies. For decorated $\mathbb{Z}$-graphs, we further show that for a Baire-generic and Lebesgue almost-sure choice of the decoration edge lengths, the spectrum is a generalized Cantor set. We then study the integrated density of states (IDS) for metric and discrete decorated $\mathbb{Z}$-graphs. We prove a gap labelling theorem, which characterizes the set of possible values taken by the IDS inside spectral gaps. We show that the gap labels are contained in the Schwartzman group associated with the dynamical system generating the graph, up to a geometric scaling factor. Lastly, we consider the Dry Ten Martini Problem for discrete Sturmian decorated $\mathbb{Z}$-graphs, asking whether all possible values predicted by the gap labelling theorem are indeed attained by the IDS inside spectral gaps. We answer this question negatively, by identifying a large set of gap labels which are not attained due to jump discontinuities of the IDS. We then show that away from these jump discontinuities, the periodic approximants for Sturmian graphs display the same combinatorial structure as the standard Sturmian Hamiltonians, and use this to obtain an explicit characterization of the realized gap labels for Sturmian comb graphs.

Defects and their interaction with the semiconductor host lattice play an essential role in a variety of technologies. When a defect transitions between two electronic states, the lattice distorts in response. Large displacements occur near the defect, inducing displacements on neighboring atoms, and so on, producing small displacements on atoms hundreds of Ångströms from the defect. Describing these displacements accurately is challenging for first-principles calculations due to limited supercell sizes. Here we demonstrate a procedure to efficiently obtain dilute-limit atomic displacements, using information obtained in typical modest supercells. In our approach, the atomic displacements are first obtained in a small supercell and converted into a force difference under a harmonic potential energy surface. The force difference and phonon modes at different ${\bf q}$-points are then unfolded into the Born-von Kármán supercell to obtain the dilute-limit atomic displacements. We critically analyze the convergence behavior of the force difference and study possible electron density differences that give rise to those forces, arguing that modest supercells are sufficient for internal transitions and bound-exciton transitions. Two example applications of our approach are given: (1) we calculate the luminescence spectrum of the NV center in diamond and the T center in Si and (2) we obtain dilute-limit configuration coordinate diagrams for these defects. In particular, we find that coupling to acoustic phonon modes reduces the accepting-mode frequency in the configuration coordinate diagram. Our work provides the missing ingredients necessary to address truly dilute-limit transitions at defects.

We investigate thermodynamic criticality in a spatially flat Friedmann-Lemaître-Robertson-Walker universe with a non-extensive Loop Quantum Gravity inspired entropy on its apparent horizon. Using the full Kodama-Hayward temperature and the unified first law, we derive the modified Friedmann dynamics and construct the corresponding horizon equation of state. We see that a finite physical critical point only appears in the non-extensive branch $q>1$, while in the Bekenstein-Hawking limit $q\to1$, the critical point is continuously pushed to $v_c\to\infty$ and $T_c\to0$. Along the same spinodal curve, both the constant-pressure heat capacity and the isothermal compressibility become unbounded, and the extremum of this curve is located at the critical point. Below the critical temperature, the Gibbs free energy develops several thermodynamic branches, and the phase coexistence for different horizon states is verified by the equality of temperature, pressure, and Gibbs free energy. The critical exponents are $(\alpha_{cr},\beta_{cr},\gamma_{cr},\delta_{cr}) =(0,1/2,1,3)$, indicating that the system belongs to the standard mean-field universality class despite the non-algebraic form of the equation of state. The normalized Ruppeiner curvature diverges precisely on the spinodal curve and shows critical scaling $R_N\sim-|v-v_c|^{-4}$ on the critical isotherm, and $R_N\sim-|t|^{-2}$ on the critical isochore. Finally, the critical expansion scale is given by $H_c^2=2(\sqrt{5}-2)|\beta|$, which implies that the thermodynamic critical point occurs when the entropy deformation is of order unity. These results establish a self-consistent critical structure for the effective thermodynamic state space of the cosmological apparent horizon and retain the mean-field critical universality.

Quantum time-marching algorithms for transport PDEs often represent variable coefficients and forcing through register-expanding dilations, block-encoding oracles, or repeated postselection. We present an alternative algorithm for a forced variable-coefficient advection-diffusion equation in flow-inspired skew-symmetric form that incorporates spatially varying velocity, viscous dissipation, and persistent source injection with a peak logical requirement of $n_q+1$ qubits. A centered skew-symmetric discretization makes the advection operator strictly skew-Hermitian for arbitrary velocity profiles, enabling an ancilla-free unitary realization using a Gray-code Trotter sequence of controlled-$R_y$ rotations. Diffusion is applied in the Fourier basis through a uniformly controlled rotation on one postselected ancilla, which is measured, reset, and reused between the two diffusion half-steps, while the source is incorporated classically through second-order Strang splitting. Statevector simulations for $N=16$ and $32$ recover second-order temporal convergence against high-accuracy classical solutions, while Richardson extrapolation gives fourth-order accuracy and reduces kernel calls by factors of four to fourteen. Independent tests through $N=256$ confirm second-order spatial consistency. We further show that the per-step ancilla failure probability is proportional to the instantaneous viscous dissipation rate, making postselection cost self-regulating over a fifty-fold viscosity range. Stable evolution is demonstrated for $5\times10^4$ time steps without observable secular error growth, while Gray-code advection accounts for $71$–$95\%$ of transpiled controlled-NOT gates. The fixed-width kernel provides a qubit-efficient building block for near-term hardware studies, although classical readout and state re-preparation remain the main obstacles to coherent multistep evolution.

A new family of Darboux integrable partial differential equations is constructed. The minimal orders of integrals in both characteristics can simultaneously be arbitrarily high for equations within this family. This suggests that the complete list of Darboux integrable equations may contain substantially more equations than are currently known.

Silicon avalanche photodiodes provide a technologically mature platform for sensitive photodetection, but their spectral response is intrinsically limited by the silicon bandgap. Extending their operation into the infrared requires the integration of narrow-bandgap absorbers while preserving efficient avalanche multiplication and compatibility with silicon processing. Here, we propose and demonstrate a monolithic approach that combines direct, buffer-free growth of GeSn on silicon with a lateral thin-junction separate-absorption-multiplication architecture. The GeSn layer, with a Sn composition reaching 6 at.%, extends optical absorption to a wavelength of $2.6~\mu$m, while avalanche multiplication is spatially confined to an ion-implanted silicon lateral junction. This separation enables independent control of infrared absorption and carrier multiplication without the thick Ge virtual substrates conventionally used for GeSn epitaxy. GeSn-on-Si avalanche photodiodes exhibit low pre-breakdown dark current, stable breakdown at 72 V independent of device diameter, and clear infrared photoresponse extending beyond $2~\mu$m. At 78 K, the devices exhibit external quantum efficiency exceeding 100%, reaching 163% at $1.55~\mu$m, providing direct evidence of avalanche multiplication. These results establish direct integration of narrow-bandgap group-IV absorbers with silicon multiplication regions as a scalable strategy for extending the spectral reach of silicon avalanche photodetection, opening a route toward monolithic infrared detectors for sensing, imaging, communications, LiDAR, and quantum photonics

We consider two-loop corrections to two-point functions of protected scalar operators in ABJM theory. We infer a compact finite-rank formula valid for operators of arbitrary dimension and multi-trace structure. The result is governed by the exact tree-level metric and a simple kernel on the Young lattice, while the planar limit reduces to a simple partition-theoretic rule. The required integrals organize into uniformly transcendental combinations, providing evidence for uniform transcendentality of these protected two-point functions.

We present a quantitative study of laser absorption on the $5{^{2}}\mathrm{S}_{1/2} \rightarrow 5{^{2}}\mathrm{P}_{3/2}$ transition of silver in a hollow-cathode lamp. Spectra obtained using a weak probe are measured and compared to a simple theoretical model. We fit our results to extract an effective temperature and number density associated with the silver in the lamp and confirm that the spectra are dominated by Doppler broadening. We consider the broadening effect of collisions between silver and the neon buffer gas in the lamp, and establish that these effects are small but modify the optimum effective parameters for the model. Our work results in a simple, quantitative, and predictive model for laser absorption in the lamp.

Accreting X-ray pulsars have long been expected to show large linear polarisation below the cyclotron resonance. In the standard picture, this follows from two facts: radiative opacities in the strongly magnetised neutron star environment depend strongly on polarisation mode, and the emission comes from compact polar regions. The emerging radiation should therefore be locally polarised and add almost coherently, with a polarisation angle tracing the projected magnetic field as in the rotating-vector model. Recent X-ray polarimetric observations, instead, show modest polarisation fractions and position angle swings that often depart from this simple picture. Here we show that propagation through the magnetosphere of an accreting neutron star can naturally produce both effects. Using general-relativistic ray tracing and Stokes-parameter transport, we find that photons emitted from compact polar regions acquire ray-dependent polarisation angle offsets in two ways. First, nearly field-aligned trajectories can cross local non-adiabatic pockets inside the QED birefringent region. Second, photons that intersect the plasma-loaded accretion flow accumulate additional phase shifts between plasma normal modes. Both effects broaden the distribution of polarisation angles across the ray bundle and reduce the hotspot-integrated linear polarisation, while also producing systematic deviations from rotating-vector-model expectations. Magnetospheric propagation should therefore be treated as part of the polarimetric transfer problem in accreting X-ray pulsars, and may help explain the observed low polarisation fractions and anomalous angle swings.

In recent years, data-driven approaches emerged as alternatives to traditional physics-based retrievals, taking advantage of machine learning techniques such as learnable pseudoinverse, random forests, or deep learning architectures. Classical data-driven models generalize poorly to out-of-sample regimes, as they optimize over finite datasets without incorporating underlying physical laws. This often requires large models and extensive data to achieve reliability. Physics-Informed Neural Networks address this by embedding physical constraints into the learning process, enabling improved extrapolation. However, they requires substantial computational cost due to the need to solve governing equations at each training step. In this work, we introduce a novel deep learning architecture, based on latent twin approach, that balances model complexity, dataset size, and training cost, while providing a quantitative measure of data quality. This architecture is applied to IASI spectra, with the goal to assess the robustness of this method for retrieving atmospheric profiles, including temperature, water vapor, ozone, surface emissivity, and surface temperature, in real-world clear-sky conditions. The algorithm is first applied on synthetic radiances derived from the NWP SAF database using the fast radiative transfer code sigma-IASI/F2N. After validating the architecture on synthetic data, the algorithm is applied to IASI Level 1C observations, along with their corresponding Level 2 products which serve as reference to evaluate the reconstruction accuracy of the autoencoder-based retrieval. The retrieval performances are discussed along with possible strategies to provide an error analysis for the reconstructed thermodynamical profiles.

We investigate magnetospheric accretion in disc-fed X-ray pulsars assuming that the neutron star spin axis is not perpendicular to the disc plane. We focus on X-ray pulsars, where a geometrically thin disc is truncated far from the stellar surface the channelled part of the accretion flow is expected to be guided by the large-scale dipolar magnetic field after coupling to it near the disc-magnetosphere boundary. Using numerical simulations of plasma motion from the inner disc edge to the neutron star surface, we show that a finite inclination between the disc normal and the stellar spin axis leads to periodic modulation of the mass accretion rate onto the magnetic poles even for a steady mass supply through the disc. This purely geometrical effect arises because stellar rotation changes the orientation of the magnetosphere relative to the disc, producing phase-dependent mass loading of magnetic field lines. The amplitude and shape of the modulation are determined by the system geometry and by the ratio of the stellar spin period to the flow time through the magnetosphere. The resulting variability affects the structure and luminosity of emitting regions near the neutron star surface and leads to asymmetric X-ray pulse profiles. Even without intrinsic asymmetries of the emission regions, this mechanism breaks the time-reversal symmetry expected for stationary accretion and naturally contributes to the observed asymmetry of pulse profiles and phase-resolved spectral features. The effect may also be relevant for ULX pulsars, where intrinsic accretion rate modulation can help preserve strong pulsations in the presence of geometric beaming.

The inflation of a pre-existing, fluid-filled cavity is a timeless topic in the finite-deformation analysis of soft materials. However, classical solutions for cavity inflation rely on radially symmetric material properties, leaving unresolved the effects of non-radial stiffness heterogeneity that are commonly present in biological tissues and engineered soft materials. In this work, we investigate the quasi-static inflation of a pressurized cavity in a hyperelastic solid with shear modulus varying monotonically along a reference Cartesian direction. Finite-element simulations reveal that, beyond an initial small-inflation regime, the most pronounced symmetry-breaking response is the migration of the cavity toward the more compliant end of the material, while nonspherical distortion remains comparatively weak. To analytically quantify this migration-dominated response, we develop a Rayleigh–Ritz reduced-order framework to determine the strain-energy-minimizing migration amplitude for prescribed gradation parameters and inflation level. Without using fitted parameters, the Rayleigh–Ritz framework recovers key features of the cavity migration that are intimately linked to the mechanical gradation parameters. The identification of centroid migration as a salient geometric signal, together with the reduced-order prediction of its evolution, suggests a roadmap for inverse characterization of graded materials through cavity-inflation experiments.

Relativistic heavy-ion collisions are the only known means of creating the quark-gluon plasma, a deconfined state of QCD matter. Hydrodynamic modeling has established that this medium behaves as a strongly coupled, low-viscosity fluid, but typically assumes that its quark and gluon composition reaches chemical equilibrium by the onset of the hydrodynamic phase. This assumption remains uncertain: gluon-dominated initial states suggest that quark production continues well into the hydrodynamic stage, with potentially different rates for light and strange quarks. This dissertation develops a dynamical framework for light and strange quark chemical equilibration. Incomplete equilibration of each flavor is described through time-dependent quark fugacities that modify both the equation of state and the particlization of the medium. Implemented within a multistage framework of fluctuating initial conditions, viscous hydrodynamics, particlization, and hadronic transport, the model is used to study the effects of equilibration on the hydrodynamic evolution and on hadronic and electromagnetic observables. The framework is embedded within a Bayesian analysis in which Gaussian process emulators trained on the model calculations infer the initial light and strange quark fugacities, their equilibration timescales, and selected transport coefficients from Au+Au collision data at RHIC. The strange sector is found to begin substantially undersaturated, more suppressed than the light sector; the data further favor a slower approach to equilibrium for strangeness, though the timescales themselves remain weakly constrained. These results favor a quark-gluon plasma whose flavor composition is still approaching chemical equilibrium during the hydrodynamic phase rather than fixed at its outset, and motivate extensions to collision systems of differing size and energy.

Helicity amplitudes give the most complete description of a variety of scattering reactions used in studies of strong interactions, but they cannot be measured directly: experiments record bilinear combinations of them folded through a detector response, and conventional analyses recover them through multiple stages that introduce discrete ambiguities and require a separate extraction of the absolute cross sections. Here we replace that chain with a single Bayesian inference that determines the experimentally identifiable amplitude parameters directly from detector-level measurements. A score-based diffusion model, trained on a forward simulator, provides the full posterior in each kinematic bin, with the detector response carried by the forward model and positivity of the spin-density matrix guaranteed by the parameterization. The observable amplitude content in electroproduction of final particles grows with polarization of beams and targets, providing additional sensitivity to underlying phases. In simulation, the posterior achieves empirical coverage at or above the nominal level and delivers the angular observables and the separated contributions from longitudinal and transverse photons with their correlations retained. It transfers without retraining to a realistic detector response absent from training and remains reliable in the weakly constrained nucleon-helicity-flip sector, where per-bin likelihood maximization degrades. The result is a general framework for a broad class of inverse problems, phase retrieval, quantum-state tomography, and partial-wave analysis are further instances. Its core requires only a forward simulation of the complete measurement process, instrumental effects are handled within one statistically consistent posterior, applicable across exclusive vector-meson programs at Jefferson Lab, COMPASS, HERMES, and the future Electron-Ion Collider.

Quantum error correction (QEC) requires accurate and efficient decoders, yet belief propagation (BP), despite its linear decoding complexity, often provides insufficient logical accuracy on surface codes. We propose Logical Neural Belief Propagation (L-NBP), a BP-based neural decoder that redirects the decoding objective from physical-level to logical-level decoding. L-NBP uses a neural BP (NBP) module to produce posterior beliefs, which a logical classifier transforms into a continuous-valued soft syndrome for logical-operator prediction. Trained end-to-end by backpropagation, the NBP module learns soft syndromes that are favorable for logical classification. On surface codes, L-NBP matches or outperforms BP with ordered-statistics decoding (BP-OSD) and minimum-weight perfect matching (MWPM) while retaining the linear complexity of BP, and achieves a threshold of $17.5\%$ under depolarizing noise. Under circuit-level noise, L-NBP matches the accuracy of BP-OSD on the distance-$9$ surface code while requiring only $0.2\%$ of its complexity.

Diffusion-weighted MRI (dMRI) is a powerful tool for quantifying cellular microenvironment parameters. This study proposes a physics-assisted deep learning (DL)-based denoising framework designed to enhance dMRI signal quality and improve the robustness of subsequent biophysical model fitting. A dataset of paired noise-free and Rician-noise-corrupted dMRI signals was generated using the IMPULSED-dMRI signal model. Three denoising architectures were evaluated: Convolutional Neural Networks (CNN), Multilayer Perceptron (MLP), and Long Short-Term Memory (LSTM) networks. Denoised signals were then fitted to estimate cell diameter $d$, intracellular volume fraction $V_{\mathrm{in}}$, and extracellular apparent diffusion coefficient $D_\mathrm{ex}$. DL-based processing substantially improved dMRI signal denoising. The MLP and LSTM achieved similar performance, with the LSTM slightly better overall, and both outperformed the CNN. In the subsequent model fitting step, the LSTM produced modest reductions in parameter MAE. The dominant benefit was fitting stabilization, with the overall fitting failure rate reduced from 57.6% to 17.7%. The proposed framework improves dMRI signal quality and stabilizes subsequent IMPULSED-based microenvironmental parameter fitting.

Efficient exploration of the complex potential-energy landscapes of amorphous materials is central to computational structure discovery and refinement. Conventional Monte Carlo, reverse Monte Carlo, and related methods typically sample configuration space through small, local trial moves and may require millions to tens of millions of moves to converge. Here, we evaluate larger, nonlocal perturbations followed by local geometry relaxation as an alternative sampling strategy. We develop and test four perturbation types using amorphous Al$_2$O$_3$ as a model system. Among them, moving an oxygen atom to change the coordination numbers of two aluminum atoms, allows access to low-energy configurations with substantially fewer trial moves than a conventional Monte Carlo trajectory. These results suggest that relaxation-assisted nonlocal moves could reduce trapping in local minima and improve sampling in structure-search and reverse Monte Carlo workflows.

Deterministic Secure Quantum Communication (DSQC) is a quantum cryptographic technique engineered to transfer a message through a quantum channel, requiring an auxiliary classical channel for eavesdropping verification and decoding, but without prior key distribution. This article presents a theoretical high-dimensional prepare and measure DSQC protocol using the Reed-Solomon erasure coding to ensure data resilience to noise. This protocol offers the following benefits: it eliminates the need for quantum memory or entanglement, it can be built with commercially available technology, and its higher capacity improves the overall transmission rate.

Nambu–Jona-Lasinio (NJL) models of color-superconducting quark matter suffer from cutoff artifacts once temperature or quark chemical potential become comparable to the model cutoff. These artifacts can be removed employing a renormalization-group (RG) consistent regularization scheme. In this article we perform a systematic study of neutral beta-equilibrated quark matter within the three-flavor NJL model with RG consistent regularization. Varying the coupling constant in the scalar diquark channel, we map out the phase diagram in the plane of chemical potential and temperature, and identify the gapless domains. We particularly focus on the melting pattern of the color-flavor locked (CFL) phase. At larger couplings the CFL phase melts through a so-called $d$SC phase, as expected from leading-order Ginzburg–Landau analyses. Lowering the coupling, the phase structure becomes markedly richer: While at large densities the CFL phase still melts through a $dSC$ phase, we find a $uSC$ phase at lower chemical potential. These phases, $uSC$ and $dSC$ meet at a doubly critical point whose existence had been anticipated long ago but was never demonstrated explicitly in a model.