Papers

I present new results for the massive cusp anomalous dimension at four loops in QCD. I combine partial exact and conjectured analytical expressions with an approximation that is based on the asymptotic behavior of the cusp anomalous dimension to produce the newest estimates. Detailed comparisons are made with previous approximate results that highlight the robustness of the calculational approach.

We investigate the physical origin of the bimodality in bulge-dominated galaxies, originally identified by Sampaio et al. (2025), by combining non-parametric morphological metrics, structural scaling relations, stellar kinematics, and environmental trends across a wide redshift range ($0.2 < z < 2.4$). Using the MEGG-based hybrid classification pipeline applied to CANDELS imaging, we examine the distributions of morphological metrics for two families of bulge-dominated galaxies: G1, with high specific star formation rate (sSFR) distributions, similar to discs, and G2 with lower sSFR. We find that G1 galaxies occupy an intermediate position between discs and G2 spheroids in morphological metrics, and this behaviour persists up to $z = 1.4$. Fitting the Kormendy relation separately for each family, we find a persistent offset in the zero-point across all redshifts: G2 galaxies are systematically brighter in mean effective surface brightness at fixed effective radius, likely indicating higher central stellar densities. This offset is present in both observed and rest-frame magnitudes, and we argue that it reflects a genuine difference in assembly history. A cross-match with MUSE observations reveals that G1 galaxies have higher projected angular momentum than G2 galaxies, with G1 galaxies overlapping with the disc population, while G2 galaxies are more dispersion-dominated. The redshift evolution of morphological fractions shows that, at high stellar masses, the G2 fraction grows, while discs follow the opposite trend. In parallel, G1 remains a stable, lower-mass population consistent with secular bulge growth. Finally, within galaxy clusters, G1 galaxies are preferentially found at larger cluster-centric radii, suggesting that high-density environments amplify the bimodality by accelerating quenching.

AlGaAs/GaAs asymmetric coupled quantum wells (ACQWs) are promising platforms for enhanced second-order optical nonlinearities, with their performance strongly influenced by the structural quality of heterostructures. Flat interfaces, together with high compositional homogeneity, are generally desirable for optimizing device functionality. Here we show that sharp and flat AlGaAs/GaAs interface morphology dominates the second harmonic generation (SHG) response in AlGaAs/GaAs ACQWs, even when significant compositional fluctuations in Al/Ga occupancy are present within the AlGaAs layers. Using multislice electron ptychography, we resolve the three-dimensional (3D) interface morphology and compositional distribution in AlGaAs/GaAs ACQWs under distinct growth interruptions. Longer growth interruptions sharpen and flatten the AlGaAs/GaAs interfaces, but at the same time cause stronger compositional fluctuations in the AlGaAs layers. These findings clarify how growth interruption tunes quantum wells structures and provide direct guidance for quantum wells design in next-generation optoelectronic devices.

We study numerical observables relevant to delocalization in the three-dimensional Manhattan mirror model, also known as the K-lattice. Our principal experiment separates the locations of transmitting boundary channels from the routing between them. We derive an exact conditional comparison that preserves all transmission and reflection aperture sets, and find a statistically resolved deficit of physical transmission relative to this comparison. Nearby transmitting channels are themselves suppressed relative to a uniform subset with the same cardinality. A second experiment resolves the contribution of repeated vertices by their return age. The squared norm of the signed old-memory remainder is consistent with an inverse-square-root decay over the measured range. Annular experiments quantify decreasing continuation losses, while an initially apparent history dependence fails independent replication. Finally, a periodic configuration has a connected auxiliary contact graph but only finite routing cycles. These results identify estimates on reflection routing and adaptively selected revisit charges that may assist a rigorous proof. They do not establish an infinite-volume delocalized phase.

Recently, a hybrid qudit-qubit algorithm [1] was presented for solving the integer programming problem with a polynomial quantum advantage. In this work, we investigate the algorithm [1] to understand the role of qudits ($d$-dimensional quantum system) by conducting a comparative resource analysis with its qubit-only implementation and the classical simulability of the algorithm by exploring the entanglement structure. The resource analysis part is performed in terms of logical gate counts, and fault-tolerant physical resources, including non-Clifford gates. The hybrid qudit-qubit implementation has a more compact structure of the unitary operators as opposed to its qubit-only simulation which reduces the logical and fault-tolerant resource requirements. Two example problems, one with qutrits ($d=3$) and the other with ququint ($d=5$), when contrasted with their qubit-only implementation, within a simplified fault-tolerant resource model, showed $\sim 180 \times $ and $\sim 2220\times$ fewer total resource count, respectively. For the entanglement study, volume-law-like entropy growth and signatures of multi-partite entanglement is observed leading to increasing difficulty in the classical simulation of the algorithm. The algorithm generates synergistic tri-partite entanglement even for a quadratic problem, revealing that the algorithmic structure itself can generate higher-order entanglement in the system independent of the problem.

Purpose: Free-breathing multi-echo MRI enables hepatic PDFF/R2* quantification without breath-holds, but respiratory motion can affect R2* estimation through motion-induced field variations. We investigated whether respiratory motion sensitivity is reduced at 0.55T versus 3T and developed a time-resolved free-breathing 4D MRI approach without respiratory binning. Methods: A navigator-embedded multi-echo stack-of-stars sequence was implemented. Ten subjects were scanned during free breathing and deliberate bulk motion at both 3T and 0.55T. Data were reconstructed using motion-averaged, motion-resolved, and time-resolved approaches. Quantitative performance was also evaluated in a PDFF/R2* phantom using Cartesian and radial acquisitions. Results: Phantom experiments showed close radial-Cartesian agreement for R2* and PDFF at 3T. At 0.55T, R2* showed good agreement over the low-to-moderate range but higher uncertainty at high R2*, where larger radial-Cartesian PDFF differences were also observed. R2* was substantially less sensitive to respiratory motion at 0.55T than at 3T, whereas PDFF was relatively insensitive at both field strengths. Under bulk motion, time-resolved reconstruction provided robust R2* and PDFF measurements, with particularly high consistency between free-breathing and bulk-motion acquisitions at 0.55T. Conclusion: R2* quantification was less sensitive to respiratory motion at 0.55T than at 3T, while PDFF remained relatively insensitive. Time-resolved reconstruction provided additional robustness to bulk motion. Reduced susceptibility effects at 0.55T and time-resolved reconstruction may provide complementary advantages for motion-robust free-breathing hepatic R2* and PDFF quantification.

A spacetime seal, a cryptographic guarantee that a digital event has occurred at an approved location and time, can augment a digital signature with location attestation for legal, financial, and regulatory use cases. In adversarial settings any purely classical realization of such a seal can be spoofed. Quantum position verification (QPV) offers a physics-based solution, exploiting the no-cloning theorem and the no-signaling principle to certify a party's spacetime coordinates. While the feasibility of QPV has been recently shown via entanglement- and coherent light-based protocols, achieving loss tolerance for these schemes substantially increases implementation complexity at metropolitan scales. Here, we introduce and experimentally demonstrate a loss-tolerant QPV (LT-QPV) protocol whose security is independent of channel loss. We prove finite-size security against quantum polynomial-time entangled adversaries in the quantum random oracle model instantiated with cryptographically secure hash functions. Implemented entirely with commercial off-the-shelf components, our system certifies position within 22 minutes of net data collection time against a restricted adversary, with a clear path to real-time certification (<1s) with upgraded hardware. Our architecture, requiring only a single quantum verifier node alongside classical infrastructure, is naturally compatible with metropolitan-area quantum networks, establishing the foundations for scalable, physics-backed spacetime certification as a deployable service.

Obesity is a major risk factor for breast cancer, yet how obesity-associated changes in the physical properties of white adipose tissue (WAT) influence tumor invasion remains poorly understood. Here, we combine experimental and computational approaches to investigate this question. Using mouse models and human mastectomy samples, we show that obesity not only increases adipocyte size, but also asphericity. We observe that tumor-conditioned media drives lipid loss and dedifferentiation of adipocytes into myofibroblast-like cells in vitro and that adipocytes in high-fat diet-fed mice lose lipid at a faster rate than those in normal diet-fed mice in response to mammary tumors in vivo. We then develop discrete element method (DEM) simulations to understand how these obesity-induced changes in cell and tissue properties alter breast cancer invasion under high-fat and normal diet conditions. In DEM simulations, adipocytes are modeled as deformable polygons and polyhedra, and cancer cells are modeled as soft, adhesive disks and spheres in two and three dimensions, respectively. Invasion is driven by cancer cell proliferation and tumor-induced lipid loss is modeled as corresponding decreases in adipocyte size. DEM simulations indicate that obesity-associated increases in tissue pressure induce adipocyte deformation, consistent with elevated asphericity in experimental data. At small lipid loss rates, the degree of cancer invasion is only weakly affected by tissue pressure. However, at sufficiently large lipid loss rates, we find that tissue pressure accelerates cancer invasion. Together, these results suggest that lipid loss physically remodels WAT to facilitate breast cancer invasion, and that obesity may exacerbate this effect.

The ideas behind the screened hybrid functional HSE took shape in the early 2000s, about a quarter century ago. HSE was not explicitly designed to predict band gaps, although at the time we did recognize that hybrids could help address the band-gap problem. It was designed to make exact exchange affordable and physically defensible in extended systems. Keeping exact exchange at short range and screening it away at long range inverted the prescription developed for molecules. When HSE band gaps for ordinary semiconductors and selected metal oxides came out substantially closer to experiment than those obtained with conventional semilocal approximations, we were pleasantly surprised and encouraged by the path we had taken. The revision from HSE03 to HSE06 improved molecular thermochemistry while preserving the good accuracy for semiconductor gaps. The one-quarter exchange fraction was inherited unchanged from the successful unscreened PBE hybrid for molecules, rather than fitted to solids. HSE established a practical screened-hybrid approach for accurate band-gap calculations, expanding first-principles work in defect physics, photovoltaics, power electronics, and quantum information, among other areas. The first part of this Perspective recounts the decisions made at HSE's birth and their influence on subsequent developments. The second part assesses recent advances in semilocal and hybrid functionals against benchmarks on sets of solids. Recent meta-GGAs achieve HSE06-level accuracy for selected semiconductors, while dielectric-dependent and tuned hybrids address the limitations of fixed screening. These hybrid developments share with our early work on local hybrids and local range separation the aim of adapting exact exchange to the electronic environment. The comparisons assess band gaps alongside structures, energetics, computational cost, and transferability.

In the spirit of the Brown-Susskind conjecture, proven in \cite{haf} and \cite{li}, we study the growth of the dimension of the set of $n$-qubit unitaries which can be obtained as a product of a fixed number of $2$-qubit gates from a fixed set of pairs of qubits. We show that this dimension increases strictly when one more pair is added, for at least some choice of the $2$-qubit pairs at each step.

We report the synthesis and characterization of lanthanum nitride by direct reaction of lanthanum metal with high pressure nitrogen gas in a laser floating-zone furnace. Combined synchrotron X-ray and neutron diffraction measurement verifies a rocksalt structure with stoichiometry LaN$_{0.94}$, consistent with first principles prediction that LaN is dynamically unstable in the stoichiometric limit. Electrical transport, heat capacity, and magnetization measurements show that LaN$_{0.94}$ is metallic with a superconducting transition at $T_c=5.95$ K. Our data establish LaN as the first bulk superconducting member of the rare earth mononitride family and motivates future exploration of the series using the unique processing space afforded by high-pressure optical reactors.

Hybrid physics-machine-learning solvers improve under-resolved simulations by embedding trainable corrections into the time integration. During autoregressive inference, repeated solver-model interactions can amplify small errors, motivating multi-timestep solver-in-the-loop training. However, production solvers rarely expose the derivatives needed to backpropagate through such rollouts. We introduce Diff-NekRS, a scalable differentiable framework that embeds neural corrections directly in the GPU-accelerated NekRS incompressible-flow solver. NekRS computes the authoritative forward trajectory, a manually implemented exact discrete adjoint differentiates the supported fully discrete timestep, and LibTorch supplies neural vector-Jacobian products and parameter gradients. End-to-end Taylor and centered finite-difference tests verify the assembled gradient for two-dimensional cylinder flow (2Dcyl) and the three-dimensional Taylor-Green vortex (3DTGV) across five horizons and 12-1,020 MPI ranks. At 1,020 ranks, optimizer-enabled post-setup training updates retain 54.5%-78.0% and 80.7%-81.9% weak-scaling efficiency for 2Dcyl and 3DTGV, respectively. In 200-step autoregressive inference, the M = 50 model reduces the three-seed median terminal relative L2 velocity error by 59.2% for 2Dcyl and 12.1% for 3DTGV relative to the uncorrected coarse-grid P = 2 baseline, and retains wall-clock speedups of 5.38x and 2.49x, respectively, relative to the corresponding P = 7 configurations for equal simulated-time intervals. These results establish a verified and scalable path for multi-timestep solver-in-the-loop training that improves coarse-grid trajectory accuracy while retaining a speed advantage over the high-order reference

The classical theory of the wind-driven surface layer of a rotating ocean closes the momentum balance with a local flux-gradient law, in which the turbulent stress at a given depth is proportional to the shear at that depth. It predicts a surface current deflected forty-five degrees from the wind, which exceeds most direct measurements. This study asks what follows when locality is relaxed. Beginning from the exact integral relation between turbulent stress and mean shear, and requiring the memory kernel to carry no preferred vertical scale, we obtain a power-law kernel and therefore a stress law of fractional order. The resulting equation cannot be posed on the velocity, because the fractional derivative of a bounded profile vanishes at the surface, so the wind stress cannot be applied, while the alternative definition of the derivative leaves the surface current unbounded. Posed on the stress instead, the problem is solvable in closed form in Mittag-Leffler functions at every order between zero and one. The surface deflection then depends on the closure order alone and is smaller than forty-five degrees throughout, whereas the depth-integrated transport stays exactly normal to the wind, because that constraint follows from the momentum balance and not from the closure. The far field decays as a power law rather than exponentially, and its amplitude vanishes in the local limit, so that limit is singular. Under a suddenly applied stress the surface transient decays algebraically. Three independent algorithms agree closely, and no observational or model data are used.

In this work, we study the noisy truncated Hausdorff moment problem in the context of recovering parton distribution functions (PDFs) from their moments. We start by reviewing basics of the Hausdorff moment problem and analyze how the relation between the amount of moment data provided and the ability for $f(x)$ to be reconstructed varies across different classes of parton distribution functions; we then turn to using Bayesian methods centered around Gaussian Processes (GPs) to solve the moment problems. Standard aspects of Bayesian regression such as covariance kernel choice, analytical characterization of the posterior, hyperparameter sampling with Monte Carlo methods, and validation metrics are detailed. In addition to this, powerful novel tools, such as a method to correct for mean bias in posterior distributions, and a simple class of covariance kernels whose $x$ correlation length is learned during sampling are introduced. Finally, we test our framework on 5 datasets from valence, gluon, and sea quark phenomenological pion and nucleon PDF datasets, selected to reflect diversity in PDF behavior. We find that our GP framework robustly reconstructs PDFs given a moderate number of moments. Additionally, the novel tools developed in this work resolve persistent issues that would be difficult to address via conventional means. The presented framework can be readily applied to moments obtained via lattice Quantum Chromodynamics (LQCD) to reconstruct PDFs from theoretical first principles.

We construct boundary observables that retain memory for a quantified time window in quantum chains whose basis configurations carry a conserved ordered product of matrix labels. Under strong-irreducibility and proximality hypotheses on the label matrices, projective contraction of random matrix products localizes a conserved charge in the root-mean-square over uniform basis configurations. A finite-time inequality then converts readout overlap and reset leakage into a correlation bound: for a conserved reference observable $H$, a readout $F$, accumulated squared leakage $\mathcal B$, and the normalized Hilbert-Schmidt inner product, $\langle F,\Phi(F)\rangle\ge 2\langle H,F\rangle^2/(\|H\|_2^2+\mathcal B)-\|F\|_2^2$. Here $\Phi$ is a sequence of conserving channels and partial resets. The bound holds for each such circuit, without averaging its gates. It yields an exponential memory window in the distance from the noisy region, with quantitative corrections for spatially distributed noise and imperfect conservation. For a thirteen-state elementary-matrix model, exact polynomial certificates give root-mean-square localization error $e^{-r/1400}$ between the charge and its restriction to the last $r$ sites, and limiting variance at least $1/19$ for a rational charge. A related normalized-Gram charge gives an eight-site certificate retaining more than half the specified readout correlation through two boundary-reset rounds. Uniform depolarization imposes an inverse-noise-rate lifetime ceiling. A two-qubit IBM experiment illustrates the general reset inequality; it does not realize the matrix-product chain. We provide proofs, exact certificate programs, and an independent recount of the archived experimental outcomes.

We derive the renormalized local equation of motion for the gravitational self-force on a compact object moving through matter in a black-hole spacetime. We integrate out the environment and metric perturbations on a Schwinger–Keldysh contour, obtaining a causal effective action given by a sum of curved-spacetime Feynman diagrams organized by powers of the mass ratio and environmental density. At leading order, an environmental wake gravitationally backreacts on the worldline. The corresponding diagram contains a logarithmic ultraviolet divergence that renormalizes the leading dissipative fluid–particle coupling. We isolate the divergence with a local large-momentum expansion, in which the curved-spacetime retarded Green's function reduces to its flat tangent-space form. We translate the resulting singularity into a Barack–Ori mode-sum scheme, deriving an analytic puncture and regularization parameters for an ideal-fluid environment. Mode subtraction fixes the divergent part but not the finite Wilson coefficient. For collisionless dust, we determine this coefficient by matching to an exact near-zone calculation for a black hole moving through the medium. This gives a complete renormalization prescription suitable for numerical self-force calculations.

Quantum-enabled semantic communication networks (QESCs) leverage quantum technologies to transmit data meaning efficiently, yet face challenges from costly resources and noise. This letter introduces Quantum Markov Blankets (QMBs) to QESCs, a novel framework to isolate essential quantum information for semantic transmission. We prove QMBs' validity using quantum conditional mutual information, showing that they shield semantic content from irrelevant subsystems. An implementation strategy optimises QMB detection, reducing resource use. Simulations suggest that QMB-based QESCs cut qubit consumption by 50%-75% while enhancing fidelity compared with non-optimised quantum semantic schemes. Unlike classical approaches, QMBs offer inherent security by limiting an eavesdropper's access to classical data outside the blanket. We outline future directions, including real-time QMB adaptation. This work bridges quantum information theory and semantic communication, advancing resource-efficient and secure quantum networks.

We prove that learning an unknown mixed fermionic Gaussian state on $m$ modes to trace distance $\epsilon$ requires $\Omega(m^3/\epsilon^2)$ copies when measurements act on one copy at a time, even with arbitrary POVMs, fresh ancillas and classical adaptivity, but without quantum memory between copies. The bound holds for $0<\epsilon\le1/3600$ and separates this model from the known collective rate $\Theta(m^2/\epsilon^2)$. It follows from a uniform single-copy Fisher-information budget and a dimension-independent comparison between trace distance and Gaussian parameters. On covariance matrices of operator norm at most $1-c$, we prove a Frobenius-to-trace-norm continuity bound with constant $[2c(2-c)]^{-1/2}$; matchgate shadows then attain $O(m^3/(c\epsilon^2))$ copies. This also gives explicit error certificates for thermal free-fermion states. For a class of mixed passive bosonic Gaussian states with total mean photon number at most one, a reduction to bounded-block qudit tomography gives a single-copy lower bound $\Omega(m^3/(\epsilon^2\sqrt{\log(m/\epsilon)}))$, versus collective complexity $\Theta(m^2/\epsilon^2)$. These separations answer the mixed-state measurement-resource question posed by Chen et al. A two-mode example has optimal two-copy Fisher trace $5$, versus the separable ceiling $4$. An IBM replication gave a pre-registered witness lower bound $4.12$ at one-sided $95\%$ shot-noise confidence; its interpretation assumes the prescribed preparations and a common measurement channel and does not bound preparation systematics.

We investigate the dynamics of charged particles in the dipolar electromagnetic field generated by a stationary current loop around a static black hole in the Randall–Sundrum braneworld model. The current loop is located at the innermost stable circular orbit (ISCO) of the tidal charged black hole, and the azimuthal electromagnetic four-potential is obtained as an exact analytical solution of the Maxwell equations in the curved background. Starting from the Hamilton–Jacobi equation, we derive the effective potential for charged particle motion in both the interior and exterior regions of the current loop, and analyze the dependence of the ISCO radius, angular momentum, energy, and orbital frequency on the tidal charge parameter $b$ and the magnetic coupling parameter $\omega$. We further compute three fundamental frequencies and show that the dipolar loop field revives a nonzero nodal precession frequency even though the background is static and non-rotating. Using these frequencies we construct five twin-peak QPO models (RP, WD, and ER2–ER4) and perform a Markov chain Monte Carlo (MCMC) analysis to constrain the braneworld parameters $(b,\omega)$ from the observed twin-peak QPO frequencies of six black hole sources spanning three mass regimes: GRO~J1655–40, XTE~J1550–564, GRS~1915$+$105, H~1743$+$322, M82~X-1, and Sgr~A$^{*}$. Adopting the epicyclic-resonance ER4 model as the representative framework, we find moderate, non-negligible tidal charges $b\simeq0.3$–$1.0$, while the magnetic coupling remains consistent with zero, $|\omega|\lesssim0.05$. Our results therefore place upper bounds on the tidal charge and on the magnetic coupling strength from astrophysical QPO data.

The dynamics of interacting dipole skyrmion chains in a weak pinning landscape is studied through numerical solutions of the stochastic Thiele equation. Chains of different lengths with periodic boundary conditions are driven across quenched attractive pinning sites under different magnetic fields. A clear threshold spin current is identified as the critical depinning force. Three main results emerge: (i) for chains of 50 skyrmions or more, the depinning threshold is independent of chain length and remains close to one third of that of an isolated skyrmion. (ii) The transition rounding is only partly thermal: the width changes from w = 0.334 +/- 0.004 decades at T = 0 to 0.633 +/- 0.002 at 300 K, while the intrinsic Larkin correlation length remains about 2.6 bonds below kBT ~ V0/25. (iii) The width is nearly unchanged up to kBT ~ 0.14 V0, but increases almost fourfold by kBT ~ 0.23 V0, mainly through broadening of the creep regime. It is independent of chain length, ruling out finite-size rounding. Increasing the field from 30 to 40 mT changes the transition shape, widening its core by 26% while shortening the creep tails. For chains of about 200 skyrmions, depinning proceeds through a sequence of internal deformations - growth of the Larkin length and roughness, transient bond stretching, and subsequent recovery of mobility and Hall angle. These collective effects are relevant for skyrmion-based devices in which chains, rather than isolated textures, act as information carriers.

We benchmark classical optimization of a fixed low-depth Quantum Approximate Optimization Algorithm (QAOA) ansatz across four cost-Hamiltonian families at $N=12$, $p=3$, and $D=6$. Ten optimizers are compared over 25 independent runs under common ceilings of 10\,000 and 30\,000 function evaluations (FEs), first with exact statevector objectives and then with two additive observation-noise levels. Exact objectives favor multistart BFGS and multistart CMA-ES. Under noisy feedback, adaptive population methods become more competitive, but the ranking depends on whether performance is measured by the best exact point visited or by the point selected from noisy observations. A targeted extension over all three pre-screened instances per family confirms this regime change while showing that named adaptive-DE winners are instance dependent: jSO-lite leads low-noise oracle search, iL-SHADE high-noise oracle search, and L-SRTDE high-noise selected solutions in the equal-instance summaries. Bootstrap analysis quantifies a non-negligible high-noise search–selection gap, and a retrospective fixed-budget verification proxy shows that reserving a small measurement budget for final re-evaluation improves selected quality across all ten methods at 30\,000 FEs. A supplementary structure-aware study further shows that QAOA cross-depth restriction and continuous basin refinement are more useful in these conditions than standalone Monte Carlo tree-search selection. Overall, optimizer choice depends jointly on landscape structure, observation noise, and final-point identification.

We extend the Obukhov-Corrsin theory of scalar turbulence to compressible flows with spatially variable, anisotropic diffusivity. Combining density and diffusivity into a single positive matrix field, a transport landscape, permits an exact scale-by-scale balance in which the sign-indefinite commutator between filtering and diffusion is eliminated rather than estimated. If the density-weighted third-order velocity and scalar increments scale as $\ell^\alpha$ and $\ell^\beta$, respectively, we prove that anomalous scalar dissipation is impossible when $\alpha+2\beta>1$. Remarkably, this threshold is independent of the anisotropy and spatial regularity of the diffusivity, provided it remains uniformly elliptic. Codimension-one shocks in both velocity and scalar have $\alpha=\beta=1/3$ and therefore lie exactly at the critical threshold. For statistically stationary turbulence we further obtain an exact density-weighted constant-flux relation, providing a compressible analogue of the relation underlying Yaglom's law. The results apply directly to passive-scalar transport in both gases and magnetized plasmas and provide testable diagnostics for simulations of compressible magnetohydrodynamic turbulence. Because the same operator governs anisotropic heat conduction, the results carry over to the electron temperature of a magnetized plasma, and they imply that gradient statistics in such flows must be contracted with the transport landscape rather than with the density.

We compute the effective six-wave interaction in spatial and temporal Hamiltonian Dysthe equations and compare it with the complete degree-six coefficient of the deep-water Euler Hamiltonian. On every compact subset $K$ of a generic quadratic-dispersion resonance patch, exact resonances persist under a small cubic correction to the dispersion, and \[ W_6\bigl(\Phi_{\lambda,\varepsilon}(z)\bigr) =\varepsilon\frac{4BD}{aL(z)}+O_K(\varepsilon^2) \] uniformly in the resonance point $z$ and the deformation parameter $\lambda$. Here $L$ is the spectral diameter and $B,D$ are the local cubic and mean-flow coefficients. Thus $BD\ne0$ gives nonzero scattering on relatively open resonance sets. At the Craig–Guyenne–Sulem temporal coefficients, the corresponding exact Euler resonances satisfy \[ \frac{\mu}{4}W_6^{\rm E}\bigl(1+\mu\Psi_\mu(z)\bigr) =-\frac{8}{L(z)}+O_K(\mu), \] where $\mu$ is the relative bandwidth. The leading term comes from nine contractions of quartic vertices; every other connected degree-six contribution is uniformly bounded. We classify the coefficient values for which the generic six-wave coefficient vanishes identically; in the temporal case, this also gives cancellation on every non-permutation four-wave resonance. Outside these sets, the Zakharov–Schulman condition restricts every regular $C^3$ quadratic leading symbol to $\operatorname{span}\{1,k,\omega(k)\}$, the span of the symbols of wave action, momentum, and linear energy. Consequently the physical Dysthe models cannot support an inverse-scattering hierarchy with infinitely many linearly independent regular $C^3$ quadratic leading symbols. The cancellation sets contain known nonlinear Schrödinger, mixed Chen–Lee–Liu, Calogero–Moser derivative nonlinear Schrödinger, and Hirota representatives.

Quantum information processing requires efficient storage and manipulation of photonic states. In this work, we harness pre-created macroscopic spin coherence as an additional degree of freedom to control a cavity-assisted quantum memory. We derive equations of motion for such a memory that predict efficient emission and absorption of two-color fields under a generalized nonlocal spectral impedance-matching condition, which reduces to the well-known condition in the single-mode case. These equations reveal a new operating mechanism of cavity-assisted quantum memory wherein the controlled spin coherence couples the emitted spectral modes. As a result, our memory deterministically synthesizes arbitrary frequency-bin photonic qubits using simple radio-frequency rotations, while the temporal reversibility of the protocol provides perfect transformation of the qubit states. Our findings establish a unified platform bridging quantum storage with elementary signal processing for quantum networks based on spectral encoding of photonic qubits.

Biological materials such as the cytoskeleton and confluent cell monolayers are active, dense systems continuously subjected to internal stresses and strains, making their rheological characterization essential. While activity in soft matter can be modeled across multiple length scales, its mechanical consequences remain strongly model dependent and no unified theoretical framework has yet emerged. Here, we study the rheology of dense active amorphous materials using the Soft Glassy Rheology (SGR) model, incorporating activity at the mesoscopic scale of local elements as a stochastic strain rate that is persistent on some timescale $\tau_p$. We show that activity opens a long-time relaxation channel, driving a crossover from SGR-like power-law rheology to Maxwell-like behavior at the lowest frequencies. Combining analytical arguments in limiting regimes with numerical simulations, we characterize the resulting fluidisation time scale and its dependence on the activity parameters, which shows strong analogies with effective temperatures introduced elsewhere that similarly encode activity-induced fluidisation. Our active SGR model provides a minimal mesoscopic route to understanding how driving by activity modifies the rheology of dense amorphous materials.

We demonstrate a novel magnetometer that utilizes the Langevin nonlinear magnetization of superparamagnetic nanoparticles as the sensing medium. The magnetic sensor exploits the even-order harmonics of the magnetization response, particularly the second harmonic, which is proportional to the local magnetic field component. By remotely detecting the magnetization response, the magnetometer enables non-invasive, localized, and distributed magnetic field sensing without requiring wired connections, with a small sensing volume, which can be used for in situ biomedical sensing, geomagnetic monitoring, smart diagnostics, and distributed industrial sensing. In the linear operating regime, the magnetometer provides a measurement range of $\pm$ 0.2 mT and a high sensitivity of 10 pT/$\sqrt{Hz}$, while an extended operating mode allows measurements over a range exceeding $\pm$ 0.5 mT. The sensor offers a dynamic bandwidth from dc up to a few kilohertz, determined by the excitation frequency.

We present direct measurements of the thermal quenching factor (QF)for alpha-particles in Li2MoO4 scintillating crystals, conducted at base temperatures of 13 mK and 19 mK. Using gamma-calibration peaks from a 232Th source and alpha-lines from a surface 224Ra source, the QF_alpha was determined to range from 1.07 to 1.09 which is consistent with previous studies. A slight energy-dependent trend in QF_alpha was observed.

Occurrence rate estimates of small long-period planets rely on the radii of low signal-to-noise ratio transit candidates whose posteriors should be propagated into the population inference. These posteriors should include the error budget from all latent parameters and account for the effects of the correlated noise. Full Markov chain Monte Carlo fits with Gaussian processes take days of runtime per target, and provide information on latent parameters that will be marginalized over anyway. We present a method that computes the marginalized posterior of the planet-to-star radius ratio while sampling only a lower-dimensional effective parameter space. The 11-dimensional problem reduces to a 4-dimensional one, while the posterior retains the uncertainty budget of all the nuisance parameters, including eccentric orbits, stellar parameters, and limb darkening. The method operates on whitened light curves, mitigating biases due to correlated noise. We show that the posteriors are calibrated on simulated systems: the true radii have uniformly distributed p-values. Applied to 419 faint long-period Kepler Objects of Interest, the method yields radius ratios broadly consistent with the KOI table, although their differences exceed those expected from the reported uncertainties.

The depletion method (DM) enables the estimation of the acoustic nonlinearity parameter, B/A, in pulse-echo ultrasound using fundamental-band signals from low- and high-pressure acquisitions, but requires accurate knowledge of the acoustic-pressure scaling factor. This requirement limits experimental translation because of the slightly nonlinear scaling between excitation voltage set on the ultrasound system and pressure at the probe. We propose a complementary-aperture pulse sequence (CAPS) that recovers the linearly scaled low-pressure signal by coherently summing RF acquisitions from interleaved transmit subapertures whereas a full-aperture transmission provides the high-pressure signal maintaining the same excitation voltage configured in the ultrasound system. In silico phantoms of a homogeneous sample and a reference evaluated four aperture partitions of CAPS and compared them with the DM under relative scaling-factor errors from 0.01% to 10%. Using the DM, errors of 0.1% and 1% produced absolute B/A biases of up to 27.3% and 58.3%, respectively. CAPS yielded mean B/A values of 8.9 for a prescribed value of 9, with biases of less than 1.3% across all partitions, matching an ideally calibrated DM. These results demonstrate that CAPS preserves depletion-based B/A estimation without using the pressure scaling factor as a reconstruction input, supporting experimental and in vivo implementation without pressure-ratio calibration.

Quantum hashing is a well-known technique. In this paper, we present a new construction of a quantum hash function based on binary error-correcting codes. The construction of the quantum hash strongly resembles the quantum state preparation in QKD protocols (e.g., BB84 protocol) and can be implemented on current QKD-devices.