Papers

Silicon photomultipliers (SiPMs) are widely used in photon-counting applications, such as positron emission tomography or particle physics, where precise timestamps and photoelectron number information are both required. In this work, a Time-to-Digital Converter with amplitude measurement capabilities was designed using an Artix-7 XC7A35T FPGA. For amplitude measurements, the internal xADC of the FPGA was chosen over other alternatives for simplicity. This design has two channels and can operate in timestamp-only mode or timestamp + amplitude mode. In turn, channels can be operated independently or in coincidence. The Integral Non-Linearity and Differential Non-Linearity of the design were studied, along with its time resolution, which is $(19 \pm 1)$ ps. Using a CAEN DT5810 pulse emulator, the design was tested further in timing-only mode, timing + amplitude mode and in coincidence mode to showcase its performance when using Poisson distributed SiPM-like pulses of various amplitudes.

High-purity germanium (HPGe) detectors with thin amorphous-germanium (a-Ge) contacts can provide bipolar charge blocking and surface passivation while minimizing contact-related inactive thickness. We report the fabrication and characterization of a p-type inverted coaxial point-contact (ICPC) HPGe detector using thin a-Ge contacts in a wingless geometry that avoids the protective wing structure used in our previous prototype. The detector was fabricated from a USD-grown, zone-refined HPGe crystal and has a mass of 20.0~g. At 77~K, it exhibited picoampere-scale leakage current and an operational depletion voltage of approximately 440~V. Gamma-ray spectroscopy yielded energy resolutions of 1.75~keV FWHM at 59.5~keV and 3.19~keV FWHM at 662~keV. The calibrated charge-injection method gave an absolute capacitance of 0.496~pF, with an estimated method-level relative uncertainty of 6–8%, consistent with the 0.488~pF value obtained from electrostatic modeling with SolidStateDetectors.jl. With a $^{241}$Am source positioned inside the detector bore, the detector showed a source-correlated excess current and a broad degraded-alpha continuum centered near 3558~keV, demonstrating sensitivity to near-surface interactions. Because the source encapsulation, intervening materials, and near-surface charge-collection response were not independently characterized, the continuum is not used to infer a unique dead-layer thickness or energy-loss mechanism. The principal result is successful fabrication and stable sub-pF operation of a 20-g wingless thin-contact ICPC prototype.

The strong, tunable dipolar interactions of ultracold molecules make them a powerful platform for quantum many-body physics, but reaching degeneracy by evaporative cooling requires suppressing inelastic collisions. Microwave collisional shielding has enabled the preparation of degenerate Fermi gases and Bose-Einstein condensates of polar molecules, whereas static electric field shielding has been limited to fermionic species, which are less prone to inelastic loss. We demonstrate static-field Förster shielding of bosonic $^{23}$Na$^{87}$Rb molecules, suppressing two-body loss by up to four orders of magnitude. Within a bound-state-free electric-field window, three-body loss is also strongly suppressed, enabling efficient evaporation. Evaporating with an efficiency of 2.09(9), we increase the phase-space density of the gas by two orders of magnitude, reaching degeneracy with 7200(1000) molecules. We observe self-bound droplets at the end of evaporation over a wide range of field strengths, emerging from either degenerate or non-degenerate parent gases. We perform Path Integral Monte Carlo simulations, which suggest that the observed droplets are filamentary in nature, and find good agreement with the experimentally observed droplet formation temperatures. Our results establish Förster shielding as a single-field route to prepare degenerate gases and self-bound droplets of bosonic polar molecules.

Polluted white dwarfs provide a unique window into the composition of exoplanetary material, but interpreting their surface abundances requires a quantitative understanding of the mixing processes in their envelopes. Accretion of metal-rich debris onto hydrogen-rich white dwarfs drives thermohaline (fingering) convection in the underlying radiative zone. Previous studies have modeled this as enhanced diffusive transport, often inferring mass accretion rates, $\dot{M}_{\rm acc}$, that exceed constraints from X-ray observations. Here we develop a time-dependent model that treats thermohaline mixing as a propagating front whose evolution is coupled self-consistently to the surface abundance of heavy elements. We perform hydrodynamical simulations which demonstrate that thermohaline mixing drives the composition gradient towards marginal stability. Using this condition, we derive analytic solutions in shallow and deep stratification regimes, finding that the mixed layer depth, $h$, and surface abundance, $X_{\rm surf}$, both scale as $t^{1/2}$ at early times, transitioning to $h \propto t^{4/27}$ and $X_{\rm surf} \propto t^{10/27}$ at later times. The mixed layer reaches depths of only $\sim 100$ km over $10^5$ yr and, without gravitational settling, never reaches a steady state. Including settling leads to an equilibrium surface abundance scaling as $X_{\rm surf, eq} \propto \dot{M}_{\rm acc}^{30/43}$. Applied to G 29–38, the model matches the observed heavy-element abundance for $\dot{M}_{\rm acc} \sim 2\times 10^9$–$4\times 10^{9}~\mathrm{g~s^{-1}}$, in better agreement with X-ray constraints than prior estimates incorporating thermohaline mixing. We also present a general scaling relation for inferring accretion rates directly from observed surface abundances and stellar properties, giving a practical prescription for other polluted white dwarfs.

A multiple-scales asymptotic framework is employed to analyze the interaction between a field of small-scale convective circulations and the large-scale tropical circulation. Closed equations governing the large-scale flow are derived, providing a systematic closure for the influence of unresolved convection. The influence of unresolved convection enters through a non-local momentum diffusion operator that provides a first-principles representation of convective momentum transport and naturally couples the vertical baroclinic modes of the large-scale circulation. The classical Matsuno–Gill model is recovered as a limiting approximation in which the derived momentum transport operator reduces to the phenomenological damping introduced by Gill, thereby placing the classical theory on a systematic first-principles foundation. Two applications of the generalized theory are considered. First, steady-state circulations driven by localized equatorially symmetric heating are examined. Convectively induced vertical-mode coupling is shown to excite additional baroclinic modes beyond those directly forced, substantially modifying the vertical structure of the Walker circulation. Second, the equatorial wave spectrum is analyzed. The resulting eigenmodes comprise mixtures of the classical equatorial wave families, causing the dispersion relations to lose their distinct branch structure and exhibit systematic frequency shifts. These results demonstrate how convectively induced momentum transport systematically modifies both steady tropical circulations and equatorial wave dynamics.

Space-based liquid mirror telescopes (LMTs) have been recently proposed to overcome the scaling limits of traditional rigid mirrors. In these new space architectures, capillary forces would shape a reflective liquid into a spherical optical surface in microgravity. However, the equilibrium, stability, and dynamic behavior of such liquid interfaces under orbital perturbations remain largely uncharacterized. This study investigates the feasibility of space LMTs by combining axisymmetric capillary with thin-film models. Solar radiation pressure and self-gravitation are found to be the dominant perturbations in Sun–Earth L2 orbits, causing equilibrium deformations that exceed the $\lambda/20$ optical threshold at apertures above 0.86 m for visible ($\lambda = 380$ nm) and 1.58 m for near-infrared observatories ($\lambda = 2.5$ $\mu$m). Micrometeoroid impacts self-heal within seconds to minutes, settling after filling requires years to decades at large apertures, and propulsive maneuvers breach optical limits within seconds to hours. These results highlight the need for interface control in large-scale systems such as NASA's 50 m Fluidic Telescope (FLUTE). Thermocapillary actuation supports apertures of 2.3/8.0 m (VIS/NIR) at 100 $\mu$K and 10.6/37.7 m at 10 $\mu$K. Simultaneously, parasitic Marangoni flows impose sub-mK uniformity for NIR and 1–100 $\mu$K for visible operation on any capillary LMT. Departing the capillary regime by imposing a surface-normal settling acceleration, ranging from 39 mm s$^{-2}$ (NIR,5 m) to 17 m s$^{-2}$ (VIS,50 m), is the most promising route to tens of meters in aperture. This approach enables a passive implementation effectively suppressing perturbation induced interface distortions and thermal Marangoni flows. Keywords: Liquid mirror telescope, Optics, Space

We present an analytical investigation of the global helicity budget associated with the salt-fingering instability within the two-dimensional, three-component framework. Our analysis shows that in the region of parameter space corresponding to salt-fingering, helicity amplification occurs when the Rayleigh ratio–quantifying the relative strength of salinity to temperature gradients–exceeds a critical threshold. This finding provides a possible theoretical explanation for the spontaneous emergence of helicity, observed in recent numerical simulations.

We study how colloidal inclusions modify the formation energy of dislocation pairs in lamellar block copolymer systems. Using a hybrid particle/Ginzburg–Landau model, we calculate defect formation energies by comparing defect-free and defect-containing states with and without embedded colloids. Finite-size scaling is used to obtain formation energies in the thermodynamic limit. The effect of colloid insertion depends strongly on particle sizes and surface patterning. Homogeneous particles increasingly stabilize dislocation pairs with increasing particle sizes. Particles larger than one lamellar domain preferentially occupy the dislocation cores, where they replace strained polymer rather than deforming defect-free lamellae. The magnitude of this stabilization depends on surface affinity. Balanced Janus particles instead increase the formation energy, because their competing surface preferences cannot be satisfied simultaneously near the curved core. Varying the patch ratio interpolates between these limits. Surface patterning has little effect for particles smaller than one lamellar domain but changes the formation energy by several tens of $k_BT$ for larger particles. These results provide quantitative guidelines for controlling topological defect stability in lamellar block copolymer systems.

We investigate the Saha ionization equilibrium in the exterior Schwarzschild spacetime. Starting from the mass-shell condition for a massive particle, we derive the conserved energy associated with the timelike Killing symmetry and obtain its nonrelativistic limit in terms of the Schwarzschild lapse function. This energy is then incorporated into the Maxwell–Boltzmann distribution to construct the ionization balance as seen by an asymptotic observer. We show that the gravitational field modifies the Saha relation through the redshift of both the particle energies and the thermodynamic variables. By imposing the Tolman–Ehrenfest and Klein equilibrium conditions, the formulation expressed entirely in terms of locally measured quantities reduces to the standard flat-spacetime Saha equation. We further analyze the gravitational redshift of the ionization energy, the relative departure from the flat-spacetime ionization ratio, and the corresponding shift of the ionization fraction as a function of the asymptotic temperature. We also present the relativistic classical counterpart based on the Maxwell–Jüttner distribution and show explicitly that its leading correction is negligible in the temperature range where neutral hydrogen is appreciably abundant. These results provide a consistent description of ionization equilibrium in a static gravitational field and clarify the distinction between gravitational redshift effects and intrinsic modifications of local atomic physics.

Numerical simulations of elastic turbulence in parallel shear flows of polymer solutions indicate that the phenomena is associated with the formation and instability of exact coherent states dominated by thin sheets of polymer stress. However, these “arrowhead” structures are yet to be seen directly in experiments, where simultaneous velocity and polymer conformation measurements are challenging to obtain. Motivated by these challenges, we introduce a method for the prediction of the polymer conformation field given a time series of vorticity measurements. Our approach consists of two components: the first is a convolutional neural network architecture which takes vorticity fields and outputs a positive definite conformation tensor. The second is the adaptation of an assimilation-based training algorithm (Zhu & Page, 2026) which does not require a pre-generated `offline' library of reference conformation fields, but is trained only using the vorticity measurements. This is particularly important in viscoelastic problems, where the appropriate model and parameters to compare to the experiments may need to be determined as part of the solution. In training, measurements made on a time-marched network prediction are required to match the saved time series, while the output of the solver and network predictions at later times are required to be self-consistent. We apply these ideas to two-dimensional Kolmogorov flow in a range of regimes, from simple traveling waves to a fully chaotic state. In all cases, our method produces robust predictions of the polymer stretch, while standard, unregularised variational assimilation is ineffective. In the chaotic case we show that our networks generalise to much larger domains – without further optimisation – than the `minimal' units in which they were trained.

Quantum dot (QD) supraparticle lasers are promising platforms for microscale light sources and photonic labeling, yet their optical properties are set during assembly. Here we introduce QD colloidosomes, liquid-core/solid-shell supraparticles that combine whispering-gallery-mode optical feedback with stimulus-triggered structural collapse. Intact QD colloidosomes show cavity-defined lasing with fluence thresholds of ~2.8 mJ/cm2 and linewidths of 2.2-3.7 nm, demonstrating efficient light trapping without a solid core. We identify shell continuity as a critical determinant for whispering-gallery feedback and lasing by exploring a morphological continuum of suprastructures comprising solid supraparticles, colloidosomes, and microporous hollow shells. Intact colloidosomes support narrow cavity modes, whereas porous shells remain broadband even at high pump fluence. We show that colloidosomes can be driven to rupture and release payload through well-defined pathways, including meniscus-driven capillary failure, uniform heating, and localized near-infrared activation, thereby reconfiguring their optical response from cavity-defined lasing to broadband emission. These results establish QD colloidosomes as reconfigurable microlasers that couple optical-state switching and triggered release within a single self-assembled platform.

A core inverse problem in the experimental sciences is the inference of a hidden dynamical state from sparse or indirect measurements. There is a natural opportunity for deep learning methods here, but machine-learnt reconstruction methods typically require full state data for training. We present Trajectory-Consistent Network Training (TraCTra), a label-free framework that trains reconstruction networks using only partial observation sequences and a differentiable forward model. TraCTra requires the network reconstruction and dynamical evolution to be mutually consistent: network-predicted states are marched forward in time to match subsequent observations and to agree in the full state space with independent reconstructions at later times. Across four fluid systems, the same objective reconstructs three-dimensional turbulence from coarse-grained fields, velocity from observations of density fluctuations, and three-dimensional density and velocity from sequences of projected two-dimensional shadowgraphs, while also recovering global vorticity from observations confined to a small spatial window. TraCTra outperforms assimilation-only and physics-informed neural approaches, preserves dynamically important multiscale structure, and remains accurate beyond the optimisation window. It transfers to held-out times in the three-dimensional shadowgraph problem and, when trained across trajectories, generalises to unseen flows in the two-dimensional problem. The results establish trajectory consistency as a general supervision principle for reconstructing hidden dynamical states without full state training targets.

The downwash wake of a hovering quadrotor governs both the vehicle's own performance and the safe spacing of multi-rotor formations. Prior measurements have largely characterized the mean flow, using single-point anemometry, volumetric tracking, or planar cuts through part of the rotor system. Higher-order turbulent statistics of the merged wake, and how they relate to canonical jet scaling, have remained unresolved, particularly for small quadrotors at the low-Reynolds-number end of the size range. Here, we present a detailed particle image velocimetry (PIV) study of the downwash of a hovering Crazyflie 2.1 quadrotor (arm length, $l = 46$ mm), sampled along a diagonal cut, passing through rotors along the symmetry axis of the quadrotor, and a front-rotor cut, passing through adjacent rotors. The four rotor jets merge into a single column by $z/l \approx 5$, beyond which the mean velocity profiles progressively approach the canonical round-jet self-similar form, collapsing by $z/l \approx 13$ when scaled by the local centerline velocity and half-width. Centerline decay and half-width growth follow canonical scaling laws with an effective source diameter $D_\text{eff} = 2.29\,l$, effective Reynolds number $Re_{D_\text{eff}} = 3 \times 10^4$, at the low end of the range over which canonical jet scaling has been established, and spreading and decay constants nonetheless within the canonical round-jet range. Resolving both cuts shows that the turbulent normal stresses retain a bimodal, cut-dependent signature of the four-rotor source throughout the measurement domain.

Metaphotonic platforms based on quasi-bound states in the continuum (qBICs), harnessing strong near-field enhancement and deeply subwavelength field confinement, provide a versatile framework for surface-enhanced infrared absorption (SEIRA) spectroscopy. However, real-time molecular sensing in water using qBIC metasurfaces remains challenging. First, strong water absorption in the mid-infrared region damps qBICs and obscures weak analyte signals. Second, conventional metasurfaces rely on discrete arrays targeting individual wavelengths and coupling conditions, increasing the device footprint and fabrication effort required to match the qBIC to the molecular vibrational resonance. Here, we present a dual-gradient plasmonic qBIC metasurface with diamond-shaped resonators for in situ molecular vibrational sensing in water, where spatially encoded gradients in the scaling factor and asymmetry parameter independently control the qBIC spectral positions and radiative rates, respectively, across a 1000 um x 700 um footprint. Building on this capability, we experimentally monitor lipid vesicle dynamics in real time and resolve the carbonyl vibrational signature despite the unavoidable water absorption. We then directly identify the optimal sensing condition and track its evolution across the spatially encoded parameter space. The results establish a compact single-chip strategy that combines adsorption-kinetics monitoring, vibrational fingerprint detection, and on-chip optimization, opening opportunities for investigating biological dynamics under aqueous conditions.

We reformulate the relaxation problem in statistical mechanics by making explicit what are the operational objects subject to relaxation: the local time statistics of the recorded signal $Z(t)$. These local time statistics are simply the estimated histograms of observations $\{Z(t_i)\}_{i=1}^M$ performed at uniformly random times $\{t_i\}_{i=1}^M$ by a clockless observer. The subject of prediction is a belief about a future fresh out-of-sample reading of a measurement outcome whose distribution is inferred from the mathematical model believed to be true. For finite bounded systems of $N\ge 1$ degrees of freedom global irreversible relaxation of predictions can occur but special initial conditions exist. The form of the predictions depends on certain loss functions whose choice is up to the particular observer. Finally, entropy is given a learning interpretation as mutual information between the observer and the unknown past of the system under consideration and, in complete generality, its stationary value depends on the information available.

Ultrafast electron diffraction (UED) provides direct information on changes in molecular structure following photoexcitation, but identifying the individual vibrational motions contributing to these dynamics remains challenging. Here, we introduce frequency-resolved UED, where Fourier transformation of the time-dependent difference pair distribution function ($\Delta$PDF) gives a two-dimensional frequency-distance representation of the structural dynamics. We apply this approach to allene and 1,2-butadiene following photoexcitation to the $S_1(\pi\pi^*)$ state at 200 nm, using electron scattering signals simulated from previously-published ab initio multiple spawning trajectories (S. P. Neville et al., J. Chem. Phys., 2016, 144, 014305). We identify C=C stretching and CCC bending motions and the internuclear distances over which they contribute, and separate overlapping CH$_2$ vibrational motions. By changing the pump-probe delay range used for the Fourier transform, we identify when specific frequency components contribute during the excited-state dynamics. Methyl substitution reduces the C=C stretching and CCC bending frequencies and introduces an additional frequency component in 1,2-butadiene during the first 90 fs. We further show the importance of sub-20-fs, and ultimately few-femtosecond, temporal resolution for retrieving these frequency components. Frequency-resolved UED therefore provides the vibrational frequencies, internuclear distances, and reaction times associated with photoinduced structural dynamics.

Slow slip events within subduction zones offer a unique window into earthquake prediction. The subducting plate drives dehydration reactions in the fault, causing cyclical slip and observable surface displacements. Earthquake footprints can then be identified in these displacement series through coupling the multi-physics governing the subduction process with regional seismic activity. However, data noise and traditional filtering methods obscure the underlying mechanisms. Here, we alleviate this constraint with our physics-based attractor. By accounting for the physics of subduction paired with AI-assisted manifold detection, we are able to predict an earthquake in New Zealand's Hikurangi trench one week early. Additionally, predictability limits extend to 5-6 weeks with decadal repeatability, pointing to the fundamental determinism of the suggested mechanism through which physics-based seismic forecasting is possible.

The statistical description and acoustic diagnostics of anisotropic turbulence remain challenging. Real Schur flows (RSFs), prototype models of component-wise dimensionally reduced flows (CWDRFs), provide effective platforms for studying such problems. We combine absolute statistical equilibrium with the acoustic analogy to investigate helicity effects on the far-field directivity of sound radiated from three types of CWDRFs: two different RSFs, and a further reduction of them (liberated Schur flow). We evaluate the directivity from the vortex-sound source spectrum which is calculated with the Wick theorem from the absolute equilibirum Gaussian ensemble. Helicity amplifies the dimensional reduction induced anisotropy of the directivity functions across all CWDRFs, with distinct patterns.

We consider the difference between ensemble and volume average in cosmology. It is known that for sufficiently weak long-range correlations the root mean square of the difference, which we call ergodicity bias, decays like $R^{-3/2}$ in the limit of large volume $R^3$. We calculate the condition this imposes on the power spectrum of a Gaussian random field. We quantify the bias for finite $R$, and show that the $R\to\infty$ limit is of little relevance for cosmological observations when the measured scales and correlations extend to the size of the observable universe. We consider curvature, density, and velocity perturbations. On large scales the bias is important in all three cases. For the density perturbations, which are observationally the most relevant, the relative bias first exceeds 100% at the separation $r=177$ Mpc, and is larger than 100% for all $r>560$ Mpc. It should be taken into account when comparing ensemble and volume averages for large-scale structure. The bias is also large for the cosmic microwave background temperature perturbations on large angular scales, but this is not relevant for observations, as their analysis does not involve volume averaging.

Near-infrared (NIR) emitters in hexagonal boron nitride (hBN) have recently emerged as bright and spectrally stable light sources, but they have so far been found at locations set by the local defect environment rather than by design. Here we show that NIR emitters can be activated at predefined sites by combining single-shot femtosecond laser writing with annealing in an oxygen-rich environment. To our knowledge, this is the first demonstration of site-selective activation of NIR emitters in hBN. The written matrices are recovered in post-anneal photoluminescence maps, including in collection bands centred at 800 and 900 nm. Site-resolved spectra under 532, 635 and 785 nm excitation show narrow lines extending to 1 um; 83% of the spectra acquired at written sites under 785 nm excitation and 71% under 635 nm excitation contain at least one resolved peak above 810 nm. The integrated emission increases with writing-pulse energy over the range studied, and many sites host more than one emitter, which identifies lower writing energies as the route to single-emitter occupancy. Photon-correlation measurements on selected sites show antibunching, with a raw, uncorrected second-order correlation value g(2)(0) of 0.31 in a band centred at 850 nm. Spectral time series reveal bands that persist over the recorded intervals together with intermittent emission beyond 900 nm. Comparison with identically written, argon-annealed samples indicates that the annealing atmosphere controls the spectral range of the activated emitters, while the laser defines where they form.

High-accuracy measurement systems operating in complex operational environments, such as airborne and seaborne gravimetry, are severely affected by interacting external influences (disturbances) including temperature variations, inertial accelerations, and platform rotations. This work aims to develop and prove a general method for compensating such disturbances beyond the limits of conventional approaches. We present a general framework based on three pillars: a multi-sensor system, supervised machine learning, and a dedicated laboratory -training platform-. This measurement technique was investigated through two experimental case studies relevant to airborne and seaborne gravimetry: (i) temperature and thermal-gradient rejection in a high-sensitivity tri-axial accelerometer, and (ii) pitch and roll rejection for vertical acceleration estimation. The experiments highlighted that, although the general framework provides a useful guideline, its application to airborne and seaborne gravimetry is challenging and not straightforward, requiring the development of dedicated and innovative experimental solutions. This difficulty arises from the specific nature of the measurand-gravity-which cannot be easily varied under controlled conditions. In this work, we present a dedicated approach to addressing these challenges.

End-to-end weather forecasting systems produce skillful global gridded and station forecasts directly from raw Earth observations, replacing the numerical weather prediction pipeline, including data assimilation, at a fraction of its cost. These systems are deterministic and issue no uncertainty. Here we render the Aardvark Weather model probabilistic by attaching one stochastic mechanism to each component: learned, input-dependent noise at the observation encoder, capturing aleatoric uncertainty inherited from the observing system, and Monte Carlo dropout in the processor, capturing epistemic uncertainty in the learned dynamics. The resulting nested ensemble attributes forecast spread to the two sources through a law-of-total-variance decomposition, cross-checked by withholding observation streams. Probabilistic finetuning significantly improves the mean forecast, by 4.2% on average across variables and lead times. The ensemble is calibrated against ERA5 through the medium range (spread-skill ratio 0.98), keeps station RMSE within 2.4% of the deterministic model while beating it in CRPS at every lead time, and trails the operational ECMWF ensemble. The encoder branch behaves as observation-driven uncertainty. Component-attributed uncertainty makes end-to-end forecasts more transparent, a step toward observation-driven digital twins of the atmosphere.

Neutral atom qubits are one of the leading approaches for implementation of a large scale quantum computer. The original proposals for neutral atom qubits were formulated more than 25 years ago, with first demonstrations of a universal gate set following 10 years later. In the last few years the performance and scale of neutral atom qubit arrays has developed at a rapid pace leading to demonstrations of quantum algorithms, and logical qubits for fault tolerant error correction. This contribution reviews the physics of the neutral atom approach, surveys current capabilities, and provides an outlook for future progress.

Magnetic nanoparticles (MNP) can be used in magnetic immunoassays (MIA) by functionalizing them with antibodies. In homogeneous assays that follow a "mix-and-measure" approach, it is then sufficient to add the sample in question and evaluate the response of the MNPs using a magnetic measurement method. Magnetic Particle Spectroscopy (MPS) is a fast and sensitive method for this purpose, capable of determining the binding state by measuring changes in Brownian relaxation. For further analysis, alternating current susceptometry (ACS) is considered, although it is significantly more time-consuming and therefore no option for applications interested in point of care detection. In this study, we aim to further improve the approach of MIA evaluated by MPS. To this end, we use self-synthesized scFv fragments instead of whole IgG antibodies during functionalization in order to keep the size of the BNF-Dextran MNP with 80 nm nominal diameter as small as possible, which allows for greater relative size changes upon binding to an analyte. Virus-like particles (VLP) and the N protein of SARS-CoV-2, which were also produced in-house, are used as analytes. Due to multiple binding sites, these form cluster structures, which, in the case of VLP, were investigated in greater depth ACS to assess their field dependence. In addition, the sensitivity of the assays was analyzed as a function of MNP concentration, and the detection limit for both analytes was estimated. We found that, using scFv-functionalized MNPs, we were able to detect low concentrations of just 490 fM of SARS-CoV-2 VLP and 1.7 nM of the N protein. However, the slightly above-proportional increase in sensitivity as the MNP concentration decreases does not automatically imply a better detection limit.

We explore theoretically the formation and evolution of spatiotemporal vortex bullets, pulses confined in both space and time while carrying orbital angular momentum, inside a graded-index multimode fiber. Through a two-fold approach, combining variational analysis with full numerical simulations, we establish the existence of a bistable vortex soliton family, characterized by distinct radial and azimuthal quantum numbers. These wave packets exhibit a Laguerre-Gaussian multi-ring topology in their spatiotemporal structure. We identify the experimental conditions necessary for the generation of such structured states of light. A stability analysis based on Vakhitov-Kolokolov criteria reveals an upper limit for the propagation constant, below which vortex bullets are found to be stable. Stationary and non-stationary dynamics of vortex bullets with different topological charges are analyzed fully, exploiting analytical techniques that are supported by full numerical simulations. These results enhance our understanding of self-trapped, spatiotemporal vortex solitons in a graded-index medium and may lead to potential applications in the area of classical and quantum information processing.

We derive bounds on manipulating partially coherent microwaves with programmable scattering systems. We first consider the concentration of power from a partially coherent input into a single output port and derive a prototype-aware bound by combining multiport network theory (MNT) with semidefinite relaxation (SDR). We then address general coherency-matrix synthesis, deriving architecture-independent bounds on fidelity and useful strength, prototype-specific scalar refinements thereof, and fully prototype-aware SDR bounds on the useful-strength–fidelity Pareto frontier. The prototype-aware formulations account for mutual coupling, loss, discrete tunability, and static scattering. We evaluate the bounds on four experimental RIS-parametrized MIMO systems with up to 100 1-bit-programmable elements, using proxy-MNT models estimated from measurements. The resulting bounds are generally tight compared with feasible discrete-optimization outcomes. Interestingly, for coherency synthesis, the simpler bounds can in some cases be tighter than the fully prototype-aware bounds, highlighting their complementarity. Our results provide certified limits for wave-domain processing and harvesting of partially coherent microwaves.

Interstellar grains play key roles in star and planet formation, including the coupling of the gas to the magnetic field during the protostellar collapse. These roles depend on the local grain size distribution, which requires a multifluid treatment of charged dust. We aim to understand the fundamental physics of the dynamics of a dust distribution in interaction with the gas and the magnetic field. In particular, the purpose is to characterize the (de)coupling conditions of these different components. We provide a multifluid model of charged dust which accounts for the inertia of the grains. A chemical network is used to simulate the charge equilibrium in collapsing protostellar cores. We compute the Alfven modes and the magnetosonic modes to understand the coupling regimes between the gas, the dust fluids, and the magnetic field. We also analyze and compare to the predictions of existing models, that are the neutral dust multifluid and the standard non-ideal magnetohydrodynamics. The charged multifluid model agrees with non-ideal magnetohydrodynamics on the larger scales of a collapsing dense core and the forming disk, while we successfully extend to new regimes where the inertia of dust grains matters. We found that high charge-to-mass dust grains carry the propagation of magnetohydrodynamical waves in protostellar envelopes. We provide analytical expressions of the speed of these waves depending on the dust distribution. The magnetocompressive perturbations lead to local dust-to-gas ratio variations at au scales. A theoretical understanding of the dynamics of a charged dust distribution is provided in the linear regime. The closed set of magnetohydrodynamics equations can be implemented in numerical codes to explore nonlinear effects during the protostellar collapse such as turbulence, angular momentum transport and magnetic dust clumping.

The Poisson–Nernst–Planck (PNP) equations strongly couple ionic transport and electrostatic interactions through the Poisson equation, posing substantial numerical challenges under small permittivity and complex potential boundary conditions. Underlying these equations is a natural Wasserstein gradient-flow structure, in which the Poisson equation serves as a local realization of the nonlocal electrostatic interaction energy. Exploiting this structure, we formulate each time step as a constrained convex minimization problem where the ionic continuity equations and the Poisson equation are incorporated as linear constraints, allowing the concentrations, fluxes, and electrostatic potential to be updated simultaneously. The variational structure of the scheme intrinsically guarantees the dissipation of the original free energy, mass conservation, and nonnegativity of ionic concentrations under general electrostatic boundary conditions. Moreover, the framework is structurally modular: extending from classical to modified PNP models with steric interactions and concentration-gradient corrections requires only modifying the energy functional, while all structure-preserving properties are automatically retained. To efficiently solve the resulting large-scale constrained problems, we develop preconditioned and transformed primal–dual algorithms equipped with tailored fast dual solvers, namely DCT-based direct and Schur-complement iterative methods, that exploit the coupled block structure of the PDE constraints. Numerical experiments on classical and modified PNP systems demonstrate the accuracy and structure-preserving properties of the scheme, and show that the proposed algorithms converge reliably in strongly coupled small-permittivity regimes without significant growth in computational cost.

Bound states in the continuum (BICs) enable optical modes with ideally infinite radiative lifetimes despite lying within the radiation continuum. Radiation-matter interaction in periodically patterned planar waveguides embedding two-dimensional (2D) optically active excitations can be described quantum mechanically by diagonalizing a non-Hermitian operator, known as the Hopfield matrix, which can be generalized to incorporate independent photonic and excitonic losses into the polaritonic states. However, since 2D excitons undergo intrinsic wavevector-dependent radiative decay within the light cone, whether the Hopfield formalism can consistently account for this process while preserving polariton BICs has remained an open question. Here we show that a non-Hermitian Hopfield formalism incorporating excitonic radiative losses correctly captures the existence of genuine $k=0$ polariton BICs with diverging radiative lifetimes. The theory provides a unified microscopic framework for radiative excitons and polariton BICs, and an efficient predictive tool for designing photonic-crystal platforms coupled to quantum wells, transition-metal dichalcogenides, and other 2D excitonic materials.

Navigation in turbulence is challenging because local flow measurements provide limited information about favorable paths beyond the flow correlation scales. We investigate vertical navigation by swimmers in homogeneous isotropic turbulence and compare strategies using local flow information with strategies guided by high-performing trajectories. Compared with naive upward swimming, local strategies enhance the mean vertical velocity by about 10% of the root-mean-square flow velocity, while guidance by precalculated trajectories reaches enhancements of about 40%. This gain is limited by the time required to intercept favorable trajectories, particularly for slow swimmers. We then show that precalculated trajectories are unnecessary: swimmers can dynamically identify high-performing members of a swarm and use them as targets. For sufficiently fast swimmers, this collective strategy keeps much of the benefit of precalculated guidance using only the instantaneous swarm state. Our results demonstrate how distributed trajectory information can be used to overcome limitations of local sensing for navigation in turbulence.