For ultracold neutrons with a kinetic energy below 10 neV, strong scattering, characterized by $2\pi l_{c} / \lambda\leq 1$, can be obtained in metamaterials of C and $^7$Li. Here $l_{c}$ and $\lambda$ are the coherent scattering mean free path and the neutron wavelength, respectively. UCN interferometry and high-resolution spectroscopy (nano-electronvolt to pico-electronvolt resolution) in parallel waveguide arrays of neutronic metamaterials are given as examples of new experimental possibilities.

Controlling the temporal mode shape of quantum light pulses has wide ranging application to quantum information science and technology. Techniques have been developed to control the bandwidth, allow shifting in the time and frequency domains, and perform mode-selective beam-splitter-like transformations. However, there is no present scheme to perform targeted multimode unitary transformations on temporal modes. Here we present a practical approach to realize general transformations for temporal modes. We show theoretically that any unitary transformation on temporal modes can be performed using a series of phase operations in the time and frequency domains. Numerical simulations show that several key transformations on temporal modes can be performed with greater than 95% fidelity using experimentally feasible specifications.

Monte Carlo simulations are performed to study structure and dynamics of a protein CoVE in random media generated by a random distribution of barriers at concentration c with a coarse-grained model in its native (low temperature) and denatured (high temperature) phase. The stochastic dynamics of the protein is diffusive in denature phase at low c, it slows down on increasing c and stops moving beyond a threshold (cth = 0.10). In native phase, the protein moves extremely slow at low c but speeds up on further increasing c in a characteristic range (c = 0.10 - 0.20) before getting trapped at high c (cth = 0.30). The radius of gyration (Rg) of CoVE shows different non-monotonic dependence on c (increase followed by decay) in native and denature phase with a higher and sharper rate of change in farmer. Effective dimension (D) of CoVE is estimated from the scaling of structure factor: in denatured phase, D = 2 (a random coil conformation) at low c (= 0.01 - 0.10) with appearance of some globularization i.e. D ? 2.3, 2.5 at higher c (= 0.2, 0.3). Increasing c seems to reduce the globularity (D = 3) of CoVE in native phase.

The governing mechanistic behaviour of Directed Energy Deposition Additive Manufacturing (DED-AM) is revealed by a combined in situ and operando synchrotron X-ray imaging and diffraction study of a nickel-base superalloy, IN718. Using a unique process replicator, real-space phase-contrast imaging enables quantification of the melt-pool boundary and flow dynamics during solidification. This imaging knowledge informed precise diffraction measurements of temporally resolved microstructural phases during transformation and stress development with a spatial resolution of 100 $\mu$m. The diffraction quantified thermal gradient enabled a dendritic solidification microstructure to be predicted and coupled to the stress orientation and magnitude. The fast cooling rate entirely suppressed the formation of secondary phases or recrystallisation in the solid-state. Upon solidification, the stresses rapidly increase to the yield strength during cooling. This insight, combined with IN718 $'$s large solidification range suggests that the accumulated plasticity exhausts the alloy$'$s ductility, causing liquation cracking. This study has revealed additional fundamental mechanisms governing the formation of highly non-equilibrium microstructures during DED-AM.

We present a numerical algorithm that enables a phase-space adaptive Eulerian Vlasov-Fokker-Planck (VFP) simulation of an inertial confinement fusion (ICF) capsule implosion. The approach relies on extending a recent mass, momentum, and energy conserving phase-space moving-mesh adaptivity strategy to spherical geometry. In configuration space, we employ a mesh motion partial differential equation (MMPDE) strategy while, in velocity space, the mesh is expanded/contracted and shifted with the plasma's evolving temperature and drift velocity. The mesh motion is dealt with by transforming the underlying VFP equations into a computational (logical) coordinate, with the resulting inertial terms carefully discretized to ensure conservation. To deal with the spatial and temporally varying dynamics in a spherically imploding system, we have developed a novel nonlinear stabilization strategy for MMPDE in the configuration space. The strategy relies on a nonlinear optimization procedure that optimizes between mesh quality and the volumetric rate change of the mesh to ensure both accuracy and stability of the solution. Implosions of ICF capsules are driven by several boundary conditions: 1) an elastic moving wall boundary; 2) a time-dependent Maxwellian Dirichlet boundary; and 3) a pressure-driven Lagrangian boundary. Of these, the pressure-driven Lagrangian boundary driver is new to our knowledge. The implementation of our strategy is verified through a set of test problems, including the Guderley and Van-Dyke implosion problems --the first-ever reported using a Vlasov-Fokker-Planck model.

CubeSats are miniature satellites used to carry experimental payloads into orbit, where it is often critical to precisely control their spatial orientation. One way to do this is through the use of magnetorquers, which can be integrated into PCBs. This technique saves considerable space and capital when compared with more common torque-rod magnetorquer systems. Here we derive a method of analyzing different PCB-integrated magnetorquer geometries, parametrizing them such that the moment and efficiency are maximized. Furthermore, by modulating the trace width, the trace number, and other electrical characteristics of the magnetorquer coil, this paper optimizes the generated magnetic moment. Both constant voltage and constant current sources are analyzed as inputs. These optimizations are then simulated in COMSOL for multiple geometries, and it is found that there exists an optimal geometry, given a specified power dissipation. Simulations verify the general trend and maxima of these derivations, barring small, consistent re-scaling in the magnitude of the coil resistance. It is also found that these PCB-magnetorquers provide a sufficient alternative to commercial coil magnetorquers - particularly in volume-restricted configurations. Optimizations for common PCB-implementable geometries on small satellites are tabulated in the Appendix.

Social gravity law widely exists in human travel, population migration, commodity trade, information communication, scientific collaboration and so on. Why is there such a simple law in many complex social systems is an interesting question. Although scientists from fields of statistical physics, complex systems, economics and transportation science have explained the social gravity law, a theoretical explanation including two dominant mechanisms, namely individual interaction and bounded rationality, is still lacking. Here we present a free utility model from the perspective of individual choice behavior to explain the social gravity law. The basic assumption is that bounded rational individuals interacting with each other will trade off the expected utility and information-processing cost to maximize their own utility. The previous explanations of the social gravity law including the maximum entropy model, the free cost model, the Logit model and the destination choice game model are all special cases under our model. Further, we extend the free utility model to the dummy network and real transportation network. This model not only helps us to better understand the underlying mechanisms of spatial interaction patterns in complex social systems, but also provides a new perspective for understanding the potential function in game theory and the user equilibrium model in transportation science.

Pancreas stereotactic body radiotherapy treatment planning requires planners to make sequential, time consuming interactions with the treatment planning system (TPS) to reach the optimal dose distribution. We seek to develop a reinforcement learning (RL)-based planning bot to systematically address complex tradeoffs and achieve high plan quality consistently and efficiently. The focus of pancreas SBRT planning is finding a balance between organs-at-risk sparing and planning target volume (PTV) coverage. Planners evaluate dose distributions and make planning adjustments to optimize PTV coverage while adhering to OAR dose constraints. We have formulated such interactions between the planner and the TPS into a finite-horizon RL model. First, planning status features are evaluated based on human planner experience and defined as planning states. Second, planning actions are defined to represent steps that planners would commonly implement to address different planning needs. Finally, we have derived a reward system based on an objective function guided by physician-assigned constraints. The planning bot trained itself with 48 plans augmented from 16 previously treated patients and generated plans for 24 cases in a separate validation set. All 24 bot-generated plans achieve similar PTV coverages compared to clinical plans while satisfying all clinical planning constraints. Moreover, the knowledge learned by the bot can be visualized and interpreted as consistent with human planning knowledge, and the knowledge maps learned in separate training sessions are consistent, indicating reproducibility of the learning process.

Recent epidemiological studies have hypothesized that the prevalence of cortical cataracts is closely related to ultraviolet radiation. However, the prevalence of nuclear cataracts is higher in elderly people in tropical areas than in temperate areas. The dominant factors inducing nuclear cataracts have been widely debated. In this study, the temperature increase in the lens due to exposure to ambient conditions was computationally quantified in subjects of 50-60 years of age in tropical and temperate areas, accounting for differences in thermoregulation. A thermoregulatory response model was extended to consider elderly people in tropical areas. The time course of lens temperature for different weather conditions in five cities in Asia was computed. The temperature was higher around the mid and posterior part of the lens, which coincides with the position of the nuclear cataract. The duration of higher temperatures in the lens varied, although the daily maximum temperatures were comparable. A strong correlation (adjusted R2 > 0.85) was observed between the prevalence of nuclear cataract and the computed cumulative thermal dose in the lens. We propose the use of a cumulative thermal dose to assess the prevalence of nuclear cataracts. Cumulative wet-bulb globe temperature, a new metric computed from weather data, would be useful for practical assessment in different cities.

An improved quantum trajectory Monte Carlo method involving the Stark shift of the initial state, Coulomb potential, and multielectron polarization-induced dipole potential is used to revisit the origin of the low-energy interference structure in the photoelectron momentum distribution of the xenon atom subjected to an intense laser field, and resolve the different contributions of these three effects. In addition to the well-studied radial finger-like interference structure, a ring-like interference structure induced by interference among electron wave packets emitted from multi-cycle time windows of the laser field is found in the low energy part of the photoelectron momentum spectrum. It is attributed to the combined effect of the Coulomb potential and Stark shift. Our finding provides new insight into the imaging of electron dynamics of atoms and molecules with intense laser fields.

Monolayer transition metal dichalcogenides, coupled to metal plasmonic nanocavities, have recently emerged as new platforms for strong light-matter interactions. These systems are expected to have nonlinear optical properties that will enable them to be used as entangled photon sources, compact wave-mixing devices, and other elements for classical and quantum photonic technologies. Here we report the first experimental investigation of the nonlinear properties of these strongly coupled systems, by observing second harmonic generation from a WSe2 monolayer strongly coupled to a single gold nanorod. The pump frequency dependence of the second harmonic signal displays a pronounced splitting that can be explained by a coupled oscillator model with second-order nonlinearities. Rigorous numerical simulations utilizing a nonperturbative nonlinear hydrodynamic model of conduction electrons support this interpretation and reproduce experimental results. Our study thus lays the groundwork for understanding the nonlinear properties of strongly coupled nanoscale systems.

In this work, we numerically study linear stability of multiple steady-state solutions to a type of steric Poisson--Nernst--Planck (PNP) equations with Dirichlet boundary conditions, which are applicable to ion channels. With numerically found multiple steady-state solutions, we obtain $S$-shaped current-voltage and current-concentration curves, showing hysteretic response of ion conductance to voltages and boundary concentrations with memory effects. Boundary value problems are proposed to locate bifurcation points and predict the local bifurcation diagram near bifurcation points on the $S$-shaped curves. Numerical approaches for linear stability analysis are developed to understand the stability of the steady-state solutions that are only numerically available. Finite difference schemes are proposed to solve a derived eigenvalue problem involving differential operators. The linear stability analysis reveals that the $S$-shaped curves have two linearly stable branches of different conductance levels and one linearly unstable intermediate branch, exhibiting classical bistable hysteresis. As predicted in the linear stability analysis, transition dynamics, from a steady-state solution on the unstable branch to a one on the stable branches, are led by perturbations associated to the mode of the dominant eigenvalue. Further numerical tests demonstrate that the finite difference schemes proposed in the linear stability analysis are second-order accurate. Numerical approaches developed in this work can be applied to study linear stability of a class of time-dependent problems around their steady-state solutions that are computed numerically.

Results obtained with a new very compact detector for imaging with a matrix of Leak Microstructures (LM)are reported. Spatial linearity and spatial resolution obtained by scanning as well as the detection of alpha particles with 100% efficiency, when compared with a silicon detector, are stressed. Preliminary results recently obtained in detecting single electrons emitted by heated filament (Ec < 1 eV) at 1-3 mbar of propane are reported.

Current research presents an innovative model of half-space plasmon excitations for electron gas of arbitrary degeneracy in an ambient jellium-like positive background . The linearized Schr\"{o}dinger-Poisson system is used to derive effective coupled pseudoforce and damped pseudoforce system of second-order differential equations from which the state functions such as the electron probability density and electrostatic potential energy are calculated and the appropriate half-space equilibrium plasmon excitation wave-functions are constructed. Current model of half-space finite temperature electron plasmon reveals many interesting features not present in previous studies. This model benefits a dual length scale character of quantum plasmon excitations taking into account the detailed electrostatic interactions between single electrons and their collective entity in an unmagnetized arbitrary degeneracy electron gas. The interaction of these length scales is remarked to lead to the formation of well defined miniature periodic density fringes in the gas which are modulated over the envelop density pattern and causes the presence of an electron halo in front of the physical jellium boundary of the system. A novel attractive Lennard-Jones-like potential energy forms in front of the boundary for parametric density-temperature region relevant to the strongly doped N-type semiconductors as well as metallic surfaces. The later effect may appropriately explain the Casimir-Polder-like forces between parallel metallic plates in vacuum.

In this paper we develop a new method to study the plasmon energy band structure in multispecies plasmas. Using this method, we investigate plasmon dispersion band structure of different plasma systems with arbitrary degenerate electron fluid. The linearized Schr\"{o}dinger-Poisson model is used to derive appropriate coupled pseudoforce system from which the energy dispersion structure is calculated. It is shown that the introduction of ion mobility, beyond the jellium (static ion) model with a wide plasmon energy band gap, can fundamentally modify the plasmon dispersion character leading to a new form of low-level energy band, due to the electron-ion band structure mixing. The effects ionic of charge state and chemical potential of the electron fluid on the plasmonic band structure indicate many new features and reveal the fundamental role played by ions in the phonon assisted plasmon excitations in the electron-ion plasma system. Moreover, our study reveals that ion charge screening has a significant impact on the plasmon excitations in ion containing plasmas. The energy band structure of pair plasmas confirm the unique role of ions on the plasmon excitations in many all plasma environments. Current research helps to better understand the underlying mechanisms of collective excitations in charged environment and the important role of heavy species on the elementary plasmon quasiparticles. The method developed in this research may also be extended for complex multispecies and magnetized quantum plasmas as well as to investigation the surface plasmon-polariton interactions in nanometallic structures.

Integrated optics is at the heart of a wide range of systems from remote sensing and communications to computing and quantum information processing. Demand for smaller and more energy efficient structures stimulates search for more advanced material platforms. Here, we propose a concept of an all van der Waals photonics, where we show that electronically bulk transition metal dichalcogenide (TMDC) semiconductors are well fitted for the design of key optical components for nanoscale and integrated photonics. Specifically, we demonstrate theoretically that owing to low optical loss and high refractive index across near-infrared and telecom frequency bands, components made of bulk TMDCs can potentially outperform counterparts made of conventional 3D semiconductors, such as Si and III/Vs. We discuss several key quantum and classical optical components and show that bulk TMDCs may pave the way to smaller footprint devices, more energy efficient electro-optical modulators, and stronger quantum light-materials interaction. Enhanced optical performance, ease of integration, and a wide selection of materials suggest that bulk TMDCs may complement and, potentially, replace existing integrated photonics systems.

Machine learning entails a broad range of techniques that have been widely used in Science and Engineering since decades. High-energy physics has also profited from the power of these tools for advanced analysis of colliders data. It is only up until recently that Machine Learning has started to be applied successfully in the domain of Accelerator Physics, which is testified by intense efforts deployed in this domain by several laboratories worldwide. This is also the case of CERN, where recently focused efforts have been devoted to the application of Machine Learning techniques to beam dynamics studies at the Large Hadron Collider (LHC). This implies a wide spectrum of applications from beam measurements and machine performance optimisation to analysis of numerical data from tracking simulations of non-linear beam dynamics. In this paper, the LHC-related applications that are currently pursued are presented and discussed in detail, paying also attention to future developments.

In this invited review in honor of 100 years since the Stern-Gerlach (SG) experiments, we describe a decade of SG interferometry on the atom chip. The SG effect has been a paradigm of quantum mechanics throughout the last century, but there has been surprisingly little evidence that the original scheme, with freely propagating atoms exposed to gradients from macroscopic magnets, is a fully coherent quantum process. Specifically, no full-loop SG interferometer (SGI) has been realized with the scheme as envisioned decades ago. Furthermore, several theoretical studies have explained why it is a formidable challenge. Here we provide a review of our SG experiments over the last decade. We describe several novel configurations such as that giving rise to the first SG spatial interference fringes, and the first full-loop SGI realization. These devices are based on highly accurate magnetic fields, originating from an atom chip, that ensure coherent operation within strict constraints described by previous theoretical analyses. Achieving this high level of control over magnetic gradients is expected to facilitate technological applications such as probing of surfaces and currents, as well as metrology. Fundamental applications include the probing of the foundations of quantum theory, gravity, and the interface of quantum mechanics and gravity. We end with an outlook describing possible future experiments.

The linear instability of a surfactant-laden two-layer falling film over an inclined slippery wall is analyzed under an influence of external shear which is imposed on the top surface of the flow. The free surface of the flow as well as the interface among the fluids are contaminated by insoluble surfactants. Dynamics of both the layers are governed by the Navier--Stokes equations, and the surfactant transport equation regulates the motion of the insoluble surfactants at the interface and free surface. Instability mechanisms are compared by imposing the external shear along and opposite to the flow direction. A coupled Orr--Sommerfeld system of equations for the considered problem is derived using the perturbation technique and normal mode analysis. The eigenmodes corresponding to the Orr--Sommerfeld eigenvalue problem are obtained by employing the spectral collocation method. The numerical results imply that the stronger external shear destabilizes the interface mode instability. However, a stabilizing impact of the external shear on the surface mode is noticed if the shear is imposed in the flow direction, which is in contrast to the role of imposed external shear on the surface mode for a surfactant laden single layer falling film. Moreover, the impression of shear mode on the primary instability is analyzed in the high Reynolds number regime with sufficiently low inclination angle. Under such configuration, dominance of the shear mode over the surface mode is observed due to the weaker impact of the gravitation force on the surface instability. The shear mode can also be stabilized by applying the external shear in the counter direction of the streamwise flow. Conclusively, the extra imposed shear on the stratified two-layer falling film plays an active role to control the attitude of the instabilities.

Moire lattices consist of two identical periodic structures overlaid with a relative rotation angle. Present even in everyday life, moire lattices have been also produced, e.g., with coupled graphene-hexagonal boron nitride monolayers, graphene-graphene layers, and layers on a silicon carbide surface.A fundamental question that remains unexplored is the evolution of waves in the potentials defined by the moire lattices. Here we experimentally create two-dimensional photonic moire lattices, which, unlike their material predecessors, have readily controllable parameters and symmetry allowing to explore transitions between structures with fundamentally different geometries: periodic, general aperiodic and quasi-crystal ones. Equipped with such realization, we observe localization of light in deterministic linear lattices. Such localization is based on at band physics, in contrast to previous schemes based on light difusion in optical quasicrystals,where disorder is required for the onset of Anderson localization. Using commensurable and incommensurable moire patterns, we report the first experimental demonstration of two-dimensional localization-delocalization-transition (LDT) of light. Moire lattices may feature almost arbitrary geometry that is consistent with the crystallographic symmetry groups of the sublattices, and therefore afford a powerful tool to control the properties of light patterns, to explore the physics of transitions between periodic and aperiodic phases, and two-dimensional wavepacket phenomena relevant to several areas of science.

We address topological currents in polariton condensates excited by uniform resonant pumps in finite honeycomb arrays of microcavity pillars with a hole in the center. Such currents arise under combined action of the spin-orbit coupling and the Zeeman splitting that break the time-reversal symmetry and open a topological gap in the spectrum of the structure. The most representative feature of this structure is the presence of two interfaces, inner and outer ones, where the directions of topological currents are opposite. Due to the finite size of the structure polariton-polariton interactions lead to the coupling of the edge states at the inner and outer interfaces, which depends on the size of the hollow region. Moreover, switching between currents can be realized by tuning the pump frequency. We illustrate that currents in this finite structure can be stable and study bistability effects arising due to the resonant character of the pump.

Recently, suction-based robotic systems with microscopic features or active suction components have been proposed to grip rough and irregular surfaces. However, sophisticated fabrication methods or complex control systems are required for such systems, and robust attachment to rough real-world surfaces still remains a grand challenge. Here, we propose a fully soft robotic gripper, where a flat elastic membrane is used to conform and contact parts or surfaces well, where an internal negative pressure exerted on the air-sealed membrane induces the suction-based gripping. 3D printing in combination with soft molding techniques enable the fabrication of the soft gripper. Robust attachment to complex 3D and rough surfaces is enabled by the surface-conformable soft flat membrane, which generates strong and robust suction at the contact interface. Such robust attachment to rough and irregular surfaces enables manipulation of a broad range of real-world objects, such as an egg, lime, and foiled package, without any physical damage. Compared to the conventional suction cup designs, the proposed suction gripper design shows a four-fold increase in gripping performance on rough surfaces. Furthermore, the structural and material simplicity of the proposed gripper architecture facilitates its system-level integration with other soft robotic peripherals, which can enable broader impact in diverse fields, such as digital manufacturing, robotic manipulation, and medical gripping applications.

We demonstrate three-dimensional (3D) field-free alignment of the prototypical non-rotation-symmetric molecule indole using elliptically polarized, shaped, off-resonant laser pulses. A truncated laser pulse is produced using a combination of extreme linear chirping and controlled phase and amplitude shaping using a spatial-light-modulator (SLM) based pulse shaper of a broadband laser pulse. The angular confinement is detected through velocity-map imaging of H$^+$ and C$^{2+}$ fragments resulting from strong-field ionization and Coulomb explosion of the aligned molecules by intense femtosecond laser pulses. The achieved three-dimensional alignment is characterized by comparing the result of ion-velocity-map measurements for different alignment directions and for different times during and after the alignment laser pulse to accurate computational results. The achieved strong three-dimensional field-free alignment of $\langle\cos^{2}\delta\rangle=0.89$ demonstrates the feasibility of both, strong three-dimensional alignment of generic complex molecules and its quantitative characterization.

Purpose: Patient movement affects image quality in oral and maxillofacial cone-beam CT imaging. While many efforts are made to minimize the possibility of motion during a scan, relatively little attention has been given to motion compensation after the acquisition. Methods: In a previous study, we proposed a retrospective motion compensation approach for helical head CT imaging, which iteratively estimates and compensates for rigid head motion. This study reports on an extension of the previous method to cone-beam CT imaging. To address the issue of the limited field-of-view, improvements were made to the original method. The proposed motion estimation/ motion compensation (ME/MC) method was evaluated with simulations, phantom and patient studies. Two experts in dentomaxillofacial radiology assessed the diagnostic importance of the achieved motion artifact suppression. Results: The quality of the reconstructed images was improved after motion compensation, and most of the image artifacts were eliminated. Quantitative analysis by comparison to a reference image (simulation and phantom) and by calculation of a sharpness metric agreed with the qualitative observation. Conclusions: The proposed method has the potential to be clinically applied.

We give a hypothesis on the mass spectrum of compact $N$-quark hadron states in a classical field picture, which indicates that there would be a mass dependence on about $N^4$. We call our model "bag-tube oscillation model", which can be seemed as a kind of combination of quark-bag model and flux-tube model. The large decay widths due to large masses might be the reason why the compact $N$-quark hadrons still disappear so far.

Dissipative solitons rely on the double balance between nonlinearity and dispersion as well as gain and loss have attracted a lot of attention in optics, since it gives rise to ultrashort pulses and broadband frequency combs with good stability and smooth spectral envelopes. Here we observe a novel dissipative solitons in microwave photonics that gives rise to wideband tunable frequency hopping microwave signals with fast frequency switching speed. The dissipative microwave photonic solitions are achieved through the double balance between nonlinear gain saturation and linear filtering as well as gain and loss in a microwave photonic resonant cavity. The generation of dissipative solitons with different pulse width, repletion rate and number of solitons per round-trip time are observed, together with the corresponding wideband tunable frequency hopping microwave signals. This work opens new avenues for signal generation, processing and control based on the principle of solitons in microwave photonics, and has great potential in many applications such as modern radars, electronic warfare systems, and telecommunications.

We obtain a class of anisotropic spherically symmetric relativistic solutions of compact objects in hydrostatic equilibrium in the $f(R,T) =R+2\chi T$ modified gravity, where $R$ is the Ricci scalar, $T$ is the trace of the energy momentum tensor and $\chi$ is a dimensionless coupling parameter. The matter Lagrangian is $L_{m}=- \frac{1}{3}(2p_{t}+p_{r})$, where $p_r$ and $p_t$ represents the radial and tangential pressures. Compact objects with dense nuclear matter is expected to be anisotropic. Stellar models are constructed for anisotropic neutron stars working in the modified Finch-Skea (FS) ansatz without preassuming an equation of state. The stellar models are investigate plotting physical quantities like energy density, anisotropy parameter, radial and tangential pressures in all particular cases. The stability of stellar models are checked using the causality conditions and adiabatic index. Using the observed mass of a compact star we obtain stellar models that predicts the radius of the star and EoS for matter inside the compact objects with different values of gravitational coupling constant $\chi$. It is also found that a more massive star can be accommodated with $\chi <0$. The stellar models obtained here obey the physical acceptability criteria which show consistency for a class of stable compact objects in modified $f(R, T)$ gravity.

In this article, we introduce higher derivative Lagrangians of this form $\alpha_1 A_{\mu}(x)\dot{x}^\mu$, $\alpha_2 G_{\mu}(x)\ddot{x}^\mu$, $\alpha_3 B_{\mu}(x)\dddot{x}^\mu$, $\alpha_4 K_{\mu}(x)\ddddot{x}^\mu$, $\cdots$, that generalize the electromagnetic interaction to higher order derivatives. We show that odd order Lagrangians describe interactions analog to electromagnetism while even order Lagrangians are similar to gravitational interaction. From this analogy, we formulate the concept of the generalized induction principle assuming the coupling between the higher fields $U_{(n),\mu}(x),\ n\geq1$ and the higher currents $j^{(n)\mu}=\rho(x)d^nx^{\mu}/ds^n$, where $\rho(x)$ is the spatial density of mass ($n$ even) or of electric charge ($n$ odd). In short, this article is an invitation to reflect on a generalization of the concept of force and of inertia. We discuss the implications of these paradigms more in depth in the last section of the paper.

This cosmological model is a study of modified f(Q, T) theory of gravity which was recently proposed by Xu et al. (Eur. Phys. J. C {\bf 79}, 708 (2019)). In this theory of gravity, the action contains an arbitrary function f(Q, T) where Q is non-metricity and T is the trace of energy-momentum tensor for matter fluid. In our research, we have taken the function f(Q, T) quadratic in $Q$ and linear in T as $f(Q,T)=\alpha Q+\beta Q^{2}+\gamma T$ where $\alpha$, $\beta$ and $\gamma$ are model parameters, motivated by $f(R,T)$ gravity. We have obtained the various cosmological parameters in Friedmann-Lemaitre-Robertson-walker (FLRW) Universe viz. Hubble parameter $H$, deceleration parameter $q$ etc. in terms of scale-factor as well as in terms of redshift $z$ by constraining energy-conservation law. For observational constraints on the model, we have obtained the best-fit values of model parameters using the available data sets like Hubble data sets H(z), Joint Light Curve Analysis (JLA) data sets and union $2.1$ compilation of SNe Ia data sets by applying $R^{2}$-test formula. We have calculated the present values of various observational parameters viz. $H_{0}$, $q_{0}$, $t_{0}$ and statefinder parameters (s,r), these values are very close to the standard cosmological models. Also, we have observed that the deceleration parameter $q(z)$ shows a signature-flipping (transition) point within the range of $0.622\leq z_{t}\leq1.27$ through which it changes its phase from decelerated to the accelerated expanding universe.

The coupling of a molecule and a cavity induces non-adiabaticity in the molecule which makes the description of its dynamics complicated. For polyatomic molecules, reduced-dimensional models and the use of the Born-Oppenheimer approximation (BOA) may remedy the situation. It is demonstrated that contrary to expectation, BOA may even fail in a one-dimensional model and generally expected to fail in two- or more-dimensional models due to the appearance of conical intersections induced by the cavity.

In this letter, we investigate a quite recent new class of spin one-half fermions, namely \emph{Ahluwalia class-7 spinors}, endowed with mass dimensionality $1$ rather than $3/2$, being candidates to describe dark matter. Such spinors, under the Dirac adjoint structure, belongs to the Lounesto's class-6, namely dipole spinors. Up to our knowledge, dipole spinor fields have Weyl spinor fields as their most known representative, nonetheless, here we explore the \emph{dark} counterpart of the dipole spinors, which represents eigenspinors of the chirality operator.

Mohs micrographic surgery (MMS) is a precise technique where layers of tissue are resected and examined with intraoperative histopathology to minimize the removal of normal tissue while completely excising the cancer. To achieve intraoperative pathology, the tissue is frozen, sectioned and stained over a 20- to 60-minute period, then analyzed by the MMS surgeon. Surgery is continued one layer at a time until no cancerous cells remain, meaning MMS can take several hours to complete. Ideally, it would be desirable to circumvent or augment frozen sectioning methods and directly visualize subcellular morphology on the unprocessed excised tissues. Employing photoacoustic remote sensing (PARS) microscopy, we present a non-contact label-free reflection-mode method of performing such visualizations in frozen sections of human skin. PARS leverages endogenous optical absorption contrast within cell nuclei to provide visualizations reminiscent of histochemical staining techniques. Here, we demonstrate the ability of PARS microscopy to provide large grossing scans (>1 cm^2, sufficient to visualize entire MMS sections) and regional scans with subcellular lateral resolution (400 +- 150 nm).

In this work, we study the dispersive coupling between optical quasi-bound-states in the continuum at telecom wavelengths and GHz-mechanical modes in high-index wavelength-sized disks. We show that such cavities can display values of the optomechanical coupling rate on par with optomechanical crystal cavities ($g_{0}/2\pi\backsimeq$ 800 kHz). Interestingly, optomechanical coupling of optical resonances with mechanical modes at frequencies well above 10 GHz seems attainable. We also show that mechanical leakage in the substrate can be extremely reduced by placing the disk over a thin silica pedestal. Our results suggest a new route for ultra compact optomechanical cavities which can potentially be arranged in massive arrays forming optomechanical metasurfaces.

Geminal wavefunctions have been employed to model strongly-correlated electrons. These wavefunctions represent products of weakly-correlated pairs of electrons and reasonable approximations are computable with polynomial cost. In particular, Richardson-Gaudin states have recently been employed as a variational ansatz. This contribution serves to explain the Richardson-Gaudin wavefunctions in the conventional language of quantum chemistry.

Most traffic state forecast algorithms when applied to urban road networks consider only the links in close proximity to the target location. However, for longer-term forecasts also the traffic state of more distant links or regions of the network are expected to provide valuable information for a data-driven algorithm. This paper studies these expectations of using a network clustering algorithm and one year of Floating Car (FCD) collected by a large fleet of vehicles. First, a clustering algorithm is applied to the data in order to extract congestion-prone regions in the Munich city network. The level of congestion inside these clusters is analyzed with the help of statistical tools. Clear spatio-temporal congestion patterns and correlations between the clustered regions are identified. These correlations are integrated into a K- Nearest Neighbors (KNN) travel time prediction algorithm. In a comparison with other approaches, this method achieves the best results. The statistical results and the performance of the KNN predictor indicate that the consideration of the network-wide traffic is a valuable feature for predictors and a promising way to develop more accurate algorithms in the future.

A high-fidelity simulation of the shock/transitional boundary layer interaction caused by a 15-degrees axisymmetrical compression ramp is performed at a freestream Mach number of 5 and a transitional Reynolds number. The inlet of the computational domain is perturbed with a white noise in order to excite convective instabilities. Coherent structures are extracted using Spectral Proper Orthogonal Decomposition (SPOD), which gives a mathematically optimal decomposition of spatio-temporally correlated structures within the flow. The mean flow is used to perform a resolvent analysis in order to study non-normal linear amplification mechanisms. The comparison between the resolvent analysis and the SPOD results provides insight on both the linear and non-linear mechanisms at play in the flow. To carry out the analysis, the flow is separated into three main regions of interest: the attached boundary layer, the mixing layer and the reattachment region. The observed transition process is dependent on the linear amplification of oblique modes in the boundary layer over a broad range of frequencies. These modes interact nonlinearly to create elongated streamwise structures which are then amplified by a linear mechanism in the rest of the domain until they break down in the reattachment region. The early nonlinear interaction is found to be essential for the transition process.

Turbulent fluid flows are ubiquitous in nature and technology, and are mathematically described by the incompressible Navier-Stokes equations (INSE). A hallmark of turbulence is spontaneous generation of intense whirls, resulting from amplification of the fluid rotation-rate (vorticity) by its deformation-rate (strain). This interaction, encoded in the non-linearity of INSE, is non-local, i.e., depends on the entire state of the flow, constituting a serious hindrance in turbulence theory and in establishing regularity of INSE. Here, we unveil a novel aspect of this interaction, by separating strain into local and non-local contributions utilizing the Biot-Savart integral of vorticity in a sphere of radius R. Analyzing highly-resolved numerical turbulent solutions to INSE, we find that when vorticity becomes very large, the local strain over small R surprisingly counteracts further amplification. This uncovered self-attenuation mechanism is further shown to be connected to local Beltramization of the flow, and could provide a direction in establishing the regularity of INSE.

Controlling infrasound signals is crucial to many processes ranging from predicting atmospheric events and seismic activities to sensing nuclear detonations. These waves can be manipulated through phononic crystals and acoustic metamaterials. However, at such ultra-low frequencies, the size (usually on the order of meters) and the mass (usually on the order of many kilograms) of these materials can hinder its potential applications in the infrasonic domain. Here, we utilize tunable lattices of repelling magnets to guide and sort infrasound waves into different channels based on their frequencies. We construct our lattices by confining meta-atoms (free-floating macroscopic disks with embedded magnets) within a magnetic boundary. By changing the confining boundary, we control the meta-atoms' spacing and therefore the intensity of their coupling potentials and wave propagation characteristics. As a demonstration of principle, we present the first experimental realization of an infrasound phonon demultiplexer (i.e., guiding ultra-low frequency waves into different channels based on their frequencies). The realized platform can be utilized to manipulate ultra-low frequency waves, within a relatively small volume, while utilizing negligible mass. In addition, the self-assembly nature of the meta-atoms can be key in creating re-programmable materials with exceptional nonlinear properties.

In the framework of full Maxwell equations, we systematically study the electromagnetic radiation, namely the transition radiation, when a swift electron perpendicularly crosses a monolayer graphene. Based on the plane wave expansion and the Sommerfeld integration, we demonstrate the spatial distribution of this free-electron radiation process in the frequency domain, which clearly shows the broadband excitation of both the photons and graphene plasmons. Moreover, the radiation spectra for the excited photons and graphene plasmons are analytically derived. We find that the excitation of photons and graphene plasmons favours different velocities of the swift electron. To be specific, a higher electron velocity can give rise to the excitation of photons with better directivity and higher intensity, while a lower electron velocity can enable the efficient excitation of graphene plasmons in a broader frequency range. Our work indicates that the interaction between swift charged particles and ultrathin 2D materials or metasurfaces is promising for the design of terahertz on-chip radiation sources.

Disease outbreaks force the governments to rapid decisions to deal with. However, the rapid stream of decision-making could be costly in terms of the democratic representativeness. The aim of the paper is to investigate the trade-off between pluralism of preferences and the time required to approach a decision. To this aim we develop and test a modified version of the Hegselmann and Krause (2002) model to capture these two characteristics of the decisional process in different institutional contexts. Using a twofold geometrical institutional setting, we simulate the impact of disease outbreaks to check whether countries exhibits idiosyncratic effects, depending on their institutional frameworks. Main findings show that the degree of pluralism in political decisions is not necessarily associated with worse performances in managing emergencies, provided that the political debate is mature enough.

From the moment the first COVID-19 vaccines are rolled out, there will need to be a large fraction of the global population ready in line. It is therefore crucial to start managing the growing global hesitancy to any such COVID-19 vaccine. The current approach of trying to convince the "no"s cannot work quickly enough, nor can the current policy of trying to find, remove and/or rebut all the individual pieces of COVID and vaccine misinformation. Instead, we show how this can be done in a simpler way by moving away from chasing misinformation content and focusing instead on managing the "yes--no--not-sure" hesitancy ecosystem.

Amplified spontaneous emission is a source of broadband noise that parasitically limits the achievable gain in laser amplifiers. While optical bandpass filtering elements can suppress these broadband noise contributions, such filters are typically designed around specific frequencies or require manual tuning, rendering them less compatible with tunable laser systems. Here, we introduce a nonlinear self-adaptive filter and demonstrate the suppression of amplified spontaneous emission surrounding the lasing mode of a tunable 780 nm external cavity diode laser, using the two-beam coupling interaction in photorefractive BaTiO$_3$. A peak suppression of $-$10 dB is observed $\pm$2.5 nm from the lasing mode, with an overall 50% filter power throughput. The dynamic photorefractive filter is automatically centered on the peak frequency due to the continuous writing and readout of the volume holographic grating and can thereby also automatically adapt to frequency tuning, drift, or mode hopping with an estimated auto-tuning rate of 100 GHz/s under typical conditions. Additionally, we present opportunities for enhancing filter suppression characteristics via the input intensity ratio and tuning the bandwidth via the coupling angle, toward versatile, self-adaptive optical filtering.

The second-harmonic generation process of a focused laser beam inside a nonlinear crystal is described by the Boyd-Kleinman theory. Calculating the actual conversion efficiency and upconverted power requires the solution of a double integral that is analytically intractable. We provide an expression that predicts the exact gain coefficient within an error margin of less than 2% over several orders of magnitude of the confocal parameter and as a function of the walk-off parameter. Our result allows for readily tuning the beam parameters to optimize the performance of the upconversion process and improve optical system designs.

With advent of quantum internet, it becomes crucial to find novel ways to connect distributed quantum testbeds and develop novel technologies and research that extend innovations in managing the qubit performance. Numerous emerging technologies are focused on quantum repeaters and specialized hardware to extend the quantum distance over special-purpose channels. However, there is little work that utilizes current network technology, invested in optic technologies, to merge with quantum technologies. In this paper we argue for an AI-enabled control that allows optimized and efficient conversion between qubit and photon energies, to enable optic and quantum devices to work together. Our approach integrates AI techniques, such as deep reinforcement learning algorithms, with physical quantum transducer to inform real-time conversion between the two wavelengths. Learning from simulated environment, the trained AI-enabled transducer will lead to optimal quantum transduction to maximize the qubit lifetime.

Modern surveys of gravitational microlensing events have progressed to detecting thousands per year. Surveys are capable of probing Galactic structure, stellar evolution, lens populations, black hole physics, and the nature of dark matter. One of the key avenues for doing this is studying the microlensing Einstein radius crossing time distribution ($t_E$). However, systematics in individual light curves as well as over-simplistic modeling can lead to biased results. To address this, we developed a model to simultaneously handle the microlensing parallax due to Earth's motion, systematic instrumental effects, and unlensed stellar variability with a Gaussian Process model. We used light curves for nearly 10,000 OGLE-III and IV Milky Way bulge microlensing events and fit each with our model. We also developed a forward model approach to infer the timescale distribution by forward modeling from the data rather than using point estimates from individual events. We find that modeling the variability in the baseline removes a source of significant bias in individual events, and previous analyses over-estimated the number of long timescale ($t_E>100$ days) events due to their over simplistic models ignoring parallax effects and stellar variability. We use our fits to identify hundreds of events that are likely black holes.

Classical dynamical density functional theory (DDFT) is one of the cornerstones of modern statistical mechanics. It is an extension of the highly successful method of classical density functional theory (DFT) to nonequilibrium systems. Originally developed for the treatment of simple and complex fluids, DDFT is now applied in fields as diverse as hydrodynamics, materials science, chemistry, biology, and plasma physics. In this review, we give a broad overview over classical DDFT. We explain its theoretical foundations and the ways in which it can be derived. The relations between the different forms of deterministic and stochastic DDFT as well as between DDFT and related theories, such as quantum-mechanical time-dependent DFT, mode coupling theory, and phase field crystal models, are clarified. Moreover, we discuss the wide spectrum of extensions of DDFT, which covers methods with additional order parameters (like extended DDFT), exact approaches (like power functional theory), and systems with more complex dynamics (like active matter). Finally, the large variety of applications, ranging from fluid mechanics and polymer physics to solidification, pattern formation, biophysics, and electrochemistry, is presented.

We demonstrate that electron electric dipole moment experiments with molecules in paramagnetic state are sensitive to $P,T$-violating nuclear forces and other $CP$-violating parameters in the hadronic sector. These experiments, in particular, measure the coupling constant $C_{SP}$ of the $CP$-odd contact semileptonic interaction. We establish relations between $C_{SP}$ and different $CP$-violating hadronic parameters including strength constants of the $CP$-odd nuclear potentials, $CP$-odd pion-nucleon interactions, quark-chromo EDM and QCD vacuum angle. These relations allow us to find limits on various $CP$-odd hadronic parameters.

The crystalline structure, magnetism, and magnetocaloric effect of a GdCrO$_3$ single crystal grown with the laser-diode-heated floating-zone technique have been studied. The GdCrO$_3$ single crystal crystallizes into an orthorhombic structure with the space group $Pmnb$ at room temperature. Upon cooling, under a magnetic field of 0.1 T, it undergoes a magnetic phase transition at $T_{\textrm{N-Cr}} =$ 169.28(2) K with Cr$^{3+}$ ions forming a canted antiferromagnetic (AFM) structure, accompanied by a weak ferromagnetism. Subsequently, a spin reorientation takes place at $T_{\textrm{SR}} =$ 5.18(2) K due to Gd$^{3+}$-Cr$^{3+}$ magnetic couplings. Finally, the long-range AFM order of Gd$^{3+}$ ions establishes at $T_{\textrm{N-Gd}} =$ 2.10(2) K. Taking into account the temperature-(in)dependent components of Cr$^{3+}$ moments, we obtained an ideal model in describing the paramagnetic behavior of Gd$^{3+}$ ions within 30--140 K. We observed a magnetic reversal (positive $\rightarrow$ negative $\rightarrow$ positive) at 50 Oe with a minimum centering around 162 K. In the studied temperature range of 1.8--300 K, there exists a strong competition between magnetic susceptibilities of Gd$^{3+}$ and Cr$^{3+}$ ions, leading to puzzling magnetic phenomena. We have built the magnetic-field-dependent phase diagrams of $T_{\textrm{N-Gd}}$, $T_{\textrm{SR}}$, and $T_{\textrm{N-Cr}}$, shedding light on the nature of the intriguing magnetism. Moreover, we calculated the magnetic entropy change and obtained a maximum value at 6 K and ${\Delta}{\mu}_0H$ = 14 T, i.e., --${\Delta}S_{\textrm{M}} \approx$ 57.5 J/kg.K. Among all RECrO$_3$ (RE = $4f^n$ rare earths, $n =$ 7--14) compounds, the single-crystal GdCrO$_3$ compound exhibits the highest magnetic entropy change, as well as an enhanced adiabatic temperature, casting a prominent magnetocaloric effect for potential application in magnetic refrigeration.

We present atomistic computations within an empirical pseudopotential framework for the electron $s$-shell ground state $g$-tensor of embedded InGaAs quantum dots (QDs). A large structural set consisting of geometry, size, molar fraction and strain variations is worked out. The tensor components are observed to show insignificant discrepancies even for the highly anisotropic shapes. The family of $g$-factor curves associated with these parameter combinations coalesce to a single universal one when plotted as a function of the gap energy, thus confirming a recent assertion using a completely different electronic structure. Moreover, our work extends its validity to alloy QDs with various shapes and finite confinement that allows for penetration to the host matrix as in actual samples. Our set of results for practically relevant InGaAs QDs can help to accomplish through structural control, $g$-near-zero, or other targeted $g$ values for spintronic or electron spin resonance-based direct quantum logic applications.

In this work, we simulated the physical vapor deposition (PVD) process of Cu atoms on the amorphous SiO$_2$ substrate. The resulting Cu thin layer exhibit amorphous structure. The Cu liquid quenching from 2000 K to 50 K was also simulated with different cooling rate to form the Cu metallic glass for comparison. The Cu glasses from the two different processes (PVD and quenching) revealed the same radial distribution function but different local structure from the Voronoi tessellation analysis. The PVD glass exhibit higher densities and lower potential energy compared with the melt-quenched counterpart, which corresponded to the properties of ultrastable glasses.

The physics of astrophysical jets can be divided into three regimes: (i) engine and launch (ii) propagation and collimation, (iii) dissipation and particle acceleration. Since astrophysical jets comprise a huge range of scales and phenomena, practicality dictates that most studies of jets intentionally or inadvertently focus on one of these regimes, and even therein, one body of work may be simply boundary condition for another. We first discuss long standing persistent mysteries that pertain the physics of each of these regimes, independent of the method used to study them. This discussion makes contact with frontiers of plasma astrophysics more generally. While observations theory, and simulations, and have long been the main tools of the trade, what about laboratory experiments? Jet related experiments have offered controlled studies of specific principles, physical processes, and benchmarks for numerical and theoretical calculations. We discuss what has been done to date on these fronts. Although experiments have indeed helped us to understand certain processes, proof of principle concepts, and benchmarked codes, they have yet to solved an astrophysical jet mystery on their own. A challenge is that experimental tools used for jet-related experiments so far, are typically not machines originally designed for that purpose, or designed with specific astrophysical mysteries in mind. This presents an opportunity for a different way of thinking about the development of future platforms: start with the astrophysical mystery and build an experiment to address it.

We consider near field topological singularities originated from magnetic dipolar mode oscillations in ferrite disk particles.

Numerical simulations support the possibility of long-time existence of vortex structures in the form of quantized filaments on arrays of coupled, weakly dissipative nonlinear oscillators within a three-dimensional domain, under a resonance external driving applied at the domain boundary. Qualitatively established are the ranges of parameters characterizing the system and the external signal, which are favorable for creating a modulation-stable quasi-uniform energy background, a crucial factor for realization of this phenomenon.

Hybrid nanoparticles allow exploiting the interplay of confinement, proximity between different materials and interfacial effects. However, to harness their properties an in-depth understanding of their (meta)stability and interfacial characteristics is crucial. This is especially the case of nanosystems based on functional oxides working under reducing conditions, which may severely impact their properties. In this work, the in-situ electron-induced selective reduction of Mn3O4 to MnO is studied in magnetic Fe3O4/Mn3O4 and Mn3O4/Fe3O4 core/shell nanoparticles by means of high-resolution scanning transmission electron microscopy combined with electron energy-loss spectroscopy. Such in-situ transformation allows mimicking the actual processes in operando environments. A multi-stage image analysis using geometric phase analysis combined with particle image velocity enables direct monitoring of the relationship between structure, chemical composition and strain relaxation during the Mn3O4 reduction. In the case of Fe3O4/Mn3O4 core/shell the transformation occurs smoothly without the formation of defects. However, for the inverse Mn3O4/Fe3O4 core/shell configuration the electron beam-induced transformation occurs in different stages that include redox reactions and void formation followed by strain field relaxation via formation of defects. This study highlights the relevance of understanding the local dynamics responsible for changes in the particle composition in order to control stability and, ultimately, macroscopic functionality.

Using explicit-water molecular dynamics (MD) simulations of a generic pocket-ligand model we investigate how chemical and shape anisotropy of small ligands influences the affinities, kinetic rates and pathways for their association to hydrophobic binding sites. In particular, we investigate aromatic compounds, all of similar molecular size, but distinct by various hydrophilic or hydrophobic residues. We demonstrate that the most hydrophobic sections are in general desolvated primarily upon binding to the cavity, suggesting that specific hydration of the different chemical units can steer the orientation pathways via a `hydrophobic torque'. Moreover, we find that ligands with bimodal orientation fluctuations have significantly increased kinetic barriers for binding compared to the kinetic barriers previously observed for spherical ligands due to translational fluctuations. We exemplify that these kinetic barriers, which are ligand specific, impact both binding and unbinding times for which we observe considerable differences between our studied ligands.

The Pencil Code is a highly modular physics-oriented simulation code that can be adapted to a wide range of applications. It is primarily designed to solve partial differential equations (PDEs) of compressible hydrodynamics and has lots of add-ons ranging from astrophysical magnetohydrodynamics (MHD) to meteorological cloud microphysics and engineering applications in combustion. Nevertheless, the framework is general and can also be applied to situations not related to hydrodynamics or even PDEs, for example when just the message passing interface or input/output strategies of the code are to be used. The code can also evolve Lagrangian (inertial and noninertial) particles, their coagulation and condensation, as well as their interaction with the fluid.

The role of the spatiotemporal degrees of freedom in the preparation and observation of squeezed photonic states, produced by parametric down-conversion, is investigated. The analysis is done with the aid of a functional approach under the semi-classical approximation and the thin-crystal approximation. It is found that the squeezed state loses its minimum uncertainty property as the efficiency of down-conversion is increased, in a way that depends on the conditions of the homodyne measurements with which the amount of squeezing is determined.

The present project aims to use machine learning, specifically neural networks (NN), to learn the trajectories of a set of coupled ordinary differential equations (ODEs) and decrease compute times for obtaining ODE solutions by using this surragate model. As an example system of proven biological significance, we use an ODE model of a gene regulatory circuit of cyanobacteria related to photosynthesis \cite{original_biology_Kehoe, Sundus_math_model}. Using data generated by a numeric solution to the exemplar system, we train several long-short-term memory neural networks. We stopping training when the networks achieve an accuracy of of 3\% on testing data resulting in networks able to predict values in the ODE time series ranging from 0.25 minutes to 6.25 minutes beyond input values. We observed computational speed ups ranging from 9.75 to 197 times when comparing prediction compute time with compute time for obtaining the numeric solution. Given the success of this proof of concept, we plan on continuing this project in the future and will attempt to realize the same computational speed-ups in the context of an agent-based modeling platfom.

Robust model-fitting to spectroscopic transitions is a requirement across many fields of science. The corrected Akaike and Bayesian information criteria (AICc and BIC) are most frequently used to select the optimal number of fitting parameters. In general, AICc modelling is thought to overfit (too many model parameters) and BIC underfits. For spectroscopic modelling, both AICc and BIC lack in two important respects: (a) no penalty distinction is made according to line strength such that parameters of weak lines close to the detection threshold are treated with equal importance as strong lines and (b) no account is taken of the way in which spectral lines impact on narrow data regions. In this paper we introduce a new information criterion that addresses these shortcomings, the "Spectral Information Criterion" (SpIC). Spectral simulations are used to compare performances. The main findings are (i) SpIC clearly outperforms AICc for high signal to noise data, (ii) SpIC and AICc work equally well for lower signal to noise data, although SpIC achieves this with fewer parameters, and (iii) BIC does not perform well (for this application) and should be avoided. The new method should be of broader applicability (beyond spectroscopy), wherever different model parameters influence separated small ranges within a larger dataset and/or have widely varying sensitivities.

General purpose quantum computers can, in principle, entangle a number of noisy physical qubits to realise composite qubits protected against errors. Architectures for measurement-based quantum computing intrinsically support error-protected qubits and are the most viable approach for constructing an all-photonic quantum computer. Here we propose and demonstrate an integrated silicon photonic architecture that both entangles multiple photons, and encodes multiple physical qubits on individual photons, to produce error-protected qubits. We realise reconfigurable graph states to compare several schemes with and without error-correction encodings and implement a range of quantum information processing tasks. We observe a success rate increase from 62.5% to 95.8% when running a phase estimation algorithm without and with error protection, respectively. Finally, we realise hypergraph states, which are a generalised class of resource states that offer protection against correlated errors. Our results show how quantum error-correction encodings can be implemented with resource-efficient photonic architectures to improve the performance of quantum algorithms.

We calculate the longitudinal structure function of the deuteron up through next-to-next-to-leading order in the framework of pionless effective field theory. We use these results to compute the two-photon polarizability contribution to Lamb shift in muonic deuterium, which can be utilized to extract the nuclear charge radius of the deuteron. We present analytical expressions order-by-order for the relevant transition matrix elements and the longitudinal structure function, and we give numerical results for the corresponding contributions to the Lamb shift. We also discuss the impact of relativistic and other higher-order effects. We find agreement with previous calculations and explain the accuracy of our calculation.

Recent miniaturization of electronics in very small, low-cost and low-power configurations suitable for use in spacecraft have inspired innovative small-scale satellite concepts, such as ChipSats, centimeter-scale satellites with a mass of a few grams. These extremely small spacecraft have the potential to usher in a new age of space science accessibility. Due to their low ballistic coefficient, ChipSats can potentially be used in a swarm constellation for extended surveys of planetary atmospheres, providing large amounts of data with high reliability and redundancy. We present a preliminary feasibility analysis of a ChipSat planetary atmospheric entry mission with the purpose of searching for traces of microscopic lifeforms in the atmosphere of Venus. Indeed, the lower cloud layer of the Venusian atmosphere could be a good target for searching for microbial lifeforms, due to the favourable atmospheric conditions and the presence of micron-sized sulfuric acid aerosols. A numerical model simulating the planetary entry of a spacecraft of specified geometry, applicable to any atmosphere for which sufficient atmospheric data are available, is implemented and verified. The results are used to create a high-level design of a ChipSat mission cruising in the Venusian atmosphere at altitudes favorable for the existence of life. The paper discusses the ChipSat mission concept and considerations about the spacecraft preliminary design at system level, including the selection of a potential payload.

Solar flares are a fundamental component of solar eruptive events (SEEs; along with solar energetic particles, SEPs, and coronal mass ejections, CMEs). Flares are the first component of the SEE to impact our atmosphere, which can set the stage for the arrival of the associated SEPs and CME. Magnetic reconnection drives SEEs by restructuring the solar coronal magnetic field, liberating a tremendous amount of energy which is partitioned into various physical manifestations: particle acceleration, mass and magnetic-field eruption, atmospheric heating, and the subsequent emission of radiation as solar flares. To explain and ultimately predict these geoeffective events, the heliophysics community requires a comprehensive understanding of the processes that transform and distribute stored magnetic energy into other forms, including the broadband radiative enhancement that characterises flares. This white paper, submitted to the Heliophysics 2050 Workshop, discusses the flare impulsive phase part of SEEs, setting out the questions that need addressing via a combination of theoretical, modelling, and observational research. In short, by 2050 we must determine the mechanisms of particle acceleration and propagation, and must push beyond the paradigm of energy transport via nonthermal electron beams, to also account for accelerated protons & ions and downward directed Alfven waves.

Deuterium (D) is one of the light elements created in the big bang. As the Galaxy evolves, the D/H abundance in the interstellar medium (ISM) decreases from its primordial value due to "astration". However, the observed gas-phase D/H abundances of some interstellar sightlines are substantially lower than the expected reduction by astration alone. The missing D could have been depleted onto polycyclic aromatic hydrocarbon (PAH) molecules which are ubiquitous and abundant in interstellar regions. To quantitatively explore the hypothesis of PAHs as a possible reservoir of interstellar D, we compute quantum-chemically the infrared vibrational spectra of mono-deuterated PAHs (and their cations) of various sizes. We find that, as expected, when H in PAHs is replaced by D, the C-H stretching and bending modes at 3.3, 8.6 and 11.3 $\mu$m respectively shift to longer wavelengths at $\sim$4.4, 11.4 and 15.4 $\mu$m by a factor of $\sim$$\sqrt{13/7}$, the difference in reduced mass between the C-H and C-D oscillators. We derive from the computed spectra the mean intrinsic strengths of the 3.3 $\mu$m C-H stretch and 4.4 $\mu$m C--D stretch to be $\langle A_{3.3} \rangle \sim 13.4$ km/mol and $\langle A_{4.4} \rangle \sim 7.4$ km/mol for neutral deuterated PAHs which would dominate the interstellar 3.3 and 4.4 $\mu$m emission. By comparing the computationally-derived mean ratio of $\langle A_{4.4}/A_{3.3} \rangle \sim 0.56$ for neutral PAHs with the mean ratio of the observed intensities of $\langle (I_{4.4}/I_{3.3})_{\rm obs} \rangle \sim 0.019$, we estimate the degree of deuteration (i.e., the fraction of peripheral atoms attached to C in the form of D) to be ~2.4\%, corresponding to a D-enrichment of a factor of ~1200 with respect to the interstellar D/H abundance.

An interesting inference drawn by some Covid-19 epidemiological models is that there exists a proportion of the population who are not susceptible to infection -- even at the start of the current pandemic. This paper introduces a model of the immune response to a virus. This is based upon the same sort of mean-field dynamics as used in epidemiology. However, in place of the location, clinical status, and other attributes of people in an epidemiological model, we consider the state of a virus, B and T-lymphocytes, and the antibodies they generate. Our aim is to formalise some key hypotheses as to the mechanism of resistance. We present a series of simple simulations illustrating changes to the dynamics of the immune response under these hypotheses. These include attenuated viral cell entry, pre-existing cross-reactive humoral (antibody-mediated) immunity, and enhanced T-cell dependent immunity. Finally, we illustrate the potential application of this sort of model by illustrating variational inversion (using simulated data) of this model to illustrate its use in testing hypotheses. In principle, this furnishes a fast and efficient immunological assay--based on sequential serology--that provides a (i) quantitative measure of latent immunological responses and (ii) a Bayes optimal classification of the different kinds of immunological response (c.f., glucose tolerance tests used to test for insulin resistance). This may be especially useful in assessing SARS-CoV-2 vaccines.