Papers

We demonstrate an injection-locked 399 nm laser system with up to 1 W output power and a locked power fraction of 0.57. The system consists of a high power, multimode diode laser that is seeded by 5 mW from a single-mode external cavity diode laser. The locked high-power laser inherits the frequency agility and linewidth of the seed laser with 3.9 kHz broadening. With active stabilization, the injection lock can be maintained for more than a day. We verify the utility of this system for atomic physics by performing spectroscopy of an ytterbium atomic beam.

Silicon photonic components based on freely propagating beams in 220 nm thick Si slab waveguides are described and characterized. Examples include optical relays, waveguide crossings, couplers, and resonators with wavelength independent Q factors. The unconfined beams are manipulated using reflecting mirrors etched into the Si layer, which operate in the total internal reflection (TIR) regime. This approach eliminates the back-scattering and waveguide loss arising from sidewall roughness in single mode waveguides, reduces sensitivity to small dimensional variations, and reduces light induced self-heating. Although the detailed behavior of TIR at curved waveguide side wall mirror is too complex to capture by simple models, the experimental results are found to be in qualitative agreement with simple analytical calculations based on Gaussian beam theory and effective index approximations.

The classical Fourier analysis of a time signal, in the discrete sense, provides the frequency content of signal under the assumption of periodicity. Although the original signal can be exactly recovered using an inverse transform, the time dependence of the spectrum remains inaccessible. There exist various time-frequency analysis techniques, such as the short time fast Fourier transform and wavelets, but those are fundamentally limited in achieving high resolution in both the time and frequency domains concurrently. For spatiotemporal flowfields, the frequency based modal decompositions generally provide spatial modes with a temporal counterpart that evolves at a constant frequency. However, an accurate time-local spectral contribution and its variation over time are highly desired to better understand the intermittent/extreme events, for instance, in turbulent flowfields. To this end, this paper presents a spectral mode decomposition that yields spectral-space and spectral-time modes, where the latter along with the associated spectral energies provide a spectrogram that is at the resolution of flowfields. The spectral modes get both the frequency and energy ranks. The numerical examples demonstrate the use of technique not only in spacetime-frequency analysis but also in reduced-order modeling and denoising applications.

STEM (Science, Technology, Engineering, and Mathematics) outreach programs in Canada, especially those oriented towards youth, play a critical role in supporting the nation's future workforce, innovation capacity, and equity across social groups in STEM fields. They constitute a large, multi-layered ecosystem connecting universities, national laboratories, non profit organizations, and grassroots community groups. Despite the growing importance of these programs, and the frequency that they undergo self-evaluation, little systematic information exists on best practices or common approaches to evaluating the effectiveness of STEM outreach initiatives. To address this gap, we integrated literature review with email inquiries about self evaluation tools sent to Canadian STEM outreach programs funded by NSERC (Natural Sciences and Engineering Research Council of Canada) PromoScience grants. We contacted 200 programs and heard back from about 100 of them, for a response rate of 50%. Of those respondents, 68 shared information about a formal self-evaluation tool appropriate for general STEM outreach. The results led us to develop a toolbox of self-evaluation methods, master question banks and starting-point templates for student/participant and teacher/chaperone surveys, and a synthesized list of recommendations for evaluation process, design, and implementation. Our approach provides a broad treatment of how to do STEM outreach evaluation, supplementing the relevant literature, where large-N studies and Canadian studies are relatively rare. We acknowledge that some of the most effective practices in STEM outreach evaluation require resources or capacity (e.g. longitudinal approaches), which may be limited for many outreach practitioners, but others seem to have a high ratio of benefit to cost (e.g. adding qualitative questions to an otherwise quantitative survey).

Maxwell equations mathematically allow both retarded and advanced solutions, also their convex combinations. While Wheeler-Feynman absorber theory assumed their symmetric contributions (1/2-1/2), e.g. inspiraling show Asymmetry of Radiation instead, and currently there dominates unquestioned assumption of 1-0 only retarded. As it should depend on the boundary conditions, like absorber/emitter imbalance - which is essential but not necessarily perfect, we propose to finally verify this assumption experimentally, trying to distinguish it from e.g. 0.99-0.01 contributions. Experimental estimation of such Asymmetry of Radiation is currently difficult for EM waves due to receiver-emitter asymmetry. However, e.g. LIGO just measures lengths, which are invariant to T/CPT symmetry, making available gravitational wave observations appropriate for such estimation, and there are already observed suggestions for advanced waves. For example gravitational observations of e.g. neutron star merger, with required but clearly missing (retarded) EM counterpart, would leave possibility of being advanced wave. Also there are observed events happening too early according to current knowledge e.g. mergers of black holes in the Mass Gap, or insufficient number of retarded sources e.g. for "vibrations of the Universe" observed by Pulsar Timing Arrays.

The formulation of quantum field theory in Minkowski spacetime, which emerges from the unification of special relativity and quantum mechanics, is based on treating time as a parameter, assuming a fixed arrow of time, and requiring that field operators commute for spacelike distances. This procedure is questioned here in the context of quantum field theory in curved spacetime (QFTCS). In 1935, Einstein and Rosen (ER), in their seminal paper (Einstein and Rosen 1935 Phys. Rev. 48 73-77), proposed that "a particle in the physical Universe has to be described by mathematical bridges connecting two sheets of spacetime" which involved two arrows of time. Recently proposed direct-sum quantum theory reconciles this ER's vision by introducing geometric superselection sectors associated with the regions of spacetime related by discrete transformations. We further establish that the quantum effects at gravitational horizons involve the physics of quantum inverted harmonic oscillators that have phase space horizons. This new understanding of the ER bridges is not related to classical wormholes, it addresses the original ER puzzle and promises a unitary description of QFTCS, along with observer complementarity. Furthermore, we present compelling evidence for our new understanding of ER bridges in the form of large-scale parity asymmetric features in the cosmic microwave background, which is statistically 650 times stronger than the standard scale-invariant power spectrum from the typical understanding of inflationary quantum fluctuations when compared with the posterior probabilities associated with the model given the data. We finally discuss the implications of this new understanding in combining gravity and quantum mechanics.

Atomic cells made by anodically bonding silicon and borosilicate glasses are widely used in atomic devices. One inherent problem in these cells is that the silicon material blocks beams with wavelengths shorter than 1000 nm, which limits available optical accesses when alkali metal atoms are involved. In this work, we investigate the possibility of the silicon carbide material as an alternative of silicon materials in fabricating anodically bonded cells. We demonstrate that the optical, thermal and mechanical properties of silicon carbide help to improve the performance of atomic devices in certain applications.

To compute approximate solutions for combinatorial optimization problems, we describe variational methods based on the product state (PS) and matrix product state (MPS) ansätze. We perform variational energy minimization with respect to a quantum annealing Hamiltonian and utilize randomness by embedding the approaches in the metaheuristic iterated local search (ILS). The resulting quantum-inspired ILS algorithms are benchmarked on maximum cut problems of up to 50000 variables. We show that they can outperform traditional (M)PS methods, classical ILS, the quantum approximate optimization algorithm and other variational quantum-inspired solvers.

Divalent atoms have emerged as powerful alternatives to alkalis in ultracold atom platforms, offering unique advantages arising from their two-electron structure. Among these species, ytterbium (Yb) is especially promising, yet its anionic properties and its Rydberg spectrum remain comparatively unexplored. In this work, we perform a first and comprehensive experimental and theoretical investigation of ultralong-range Rydberg molecules (ULRMs) of $^{174}$Yb in $6sns\,^1S_0$ Rydberg states across nearly two decades in principal quantum number $n$ and three orders of magnitude in molecular binding energy. Using the Coulomb Green's function formalism, we compute Born-Oppenheimer molecular potentials describing the Rydberg atom in the presence of a ground-state perturber and achieve quantitative agreement with high-resolution molecular spectra. This enables the extraction of low-energy electron-Yb scattering phase shifts, including the zero-energy $s$-wave scattering length and the positions of two spin-orbit split $p$-wave shape resonances. Our results provide strong evidence that the Yb$^{-}$ anion exists only as a metastable resonance.% We additionally show the sensitivity of ULRM spectra to the atomic quantum defects, using this to determine the quantum defect of the $6s23f\, ^1F_3$ state. Together, these findings establish Yb ULRMs as a powerful probe of electron-Yb interactions and lay essential groundwork for future Rydberg experiments with divalent atoms.

RNA function is tied to secondary structure, operating through dynamic and heterogeneous structural ensembles. While current analysis tools typically output single static structures or averaged contact maps, chemical probing methods like DMS capture nucleotide-resolution signals representing the full structural ensemble, which remain difficult to interpret structurally. To address this, we present MERGE-RNA, a framework that describes and outputs RNA as a structural ensemble. By modeling the physics of the experimental pipeline, MERGE-RNA learns a small set of transferable and interpretable parameters, enabling the integration of measurements across different molecules, probe concentrations, and replicates in a single optimization to improve robustness. Our model employs a maximum-entropy principle to predict thermodynamic populations, with the minimal adjustments necessary to align the ensemble with experimental data. We validate MERGE-RNA on diverse RNAs, showing that it achieves structural accuracy surpassing standard pseudo-free-energy methods and yields ensembles better recapitulating measured DMS reactivity. Applied to the V. vulnificus adenine riboswitch, MERGE-RNA recovers the NMR-resolved conformations and their ligand-induced rearrangement, with population shifts matching the NMR-derived K_d. In a designed RNA construct for which we report new DMS data, MERGE-RNA deconvolves mixed states to reveal transient intermediate populations involved in strand displacement, dynamics invisible to methods based on enumerating a small number of structures.

Photonic convolutional accelerators have emerged as low-energy alternatives to power-demanding digital convolutional neural networks, though they often face limitations in scalability. In this work, we introduce a convolutional photonic accelerator that employs programmable kernels manifesting as trainable waveforms in the frequency domain to enable low-energy, high-throughput scalable image classification. The proposed scheme inherently provides dimensionality reduction and feature extraction directly in the optical domain. Numerical results targeting the Fashion-MNIST show that by using only 16 optical nodes, the system's classification accuracy tops at 90.1% when typical backpropagation is used. Moreover, by adapting the training technique to the forward-forward approach, a marginal drop of 1% is recorded compared to the backpropagation scenario, thus showcasing the compatibility of the overall architecture with a hardware-friendly training approach. Finally, we experimentally implement the trained kernels using a programmable waveshaper. Despite the difference between the simulated and experimentally generated transfer functions of the programmable kernels, the classification accuracy based on the experimentally obtained kernels exhibits a marginal 0.2% reduction, proving the validity of the idea and its high robustness to variations of the frequency-applied complex weights.

We outline the design and characterization of a laser pulse shaper, which creates an “ultraslow optical centrifuge” - a linearly polarized field whose polarization vector rotates with arbitrarily low angular acceleration. By directly recording this rotation in time with nonlinear cross-correlation, we demonstrate the tunability of such centrifuge (both in terms of its initial and its final rotational frequencies) in the range of accelerations which are three orders of magnitude lower than those available with a conventional centrifuge design. We showcase the functionality of the ultraslow centrifuge by spinning CS$_2$ molecules in a molecular jet. Utilizing the extremely low angular acceleration to control molecular rotation inside viscous media is a promising application for this unique optical tool.

Precision spectroscopy of atomic hydrogen is an important way to test bound-state quantum electrodynamics (QED), one of the building blocks of the Standard Model. In its simplest form, such a test consists of the comparison of a measured transition frequency with its QED prediction, which can be calculated with very high precision for the hydrogen atom. However, these calculations require some input in the form of physical constants, such as the Rydberg constant $R_\infty$ and the proton charge radius $r_\mathrm{p}$, both of which are currently determined to a large degree by hydrogen spectroscopy itself. Therefore, the frequency of at least three different transitions needs to be measured in order to test QED. Equivalently, a comparison of the values of $R_\infty$ and $r_\mathrm{p}$ determined from measurements of different transitions constitutes a test of QED. To this end, laser spectroscopy of optical 2S-$n$P transitions has been performed in this work. As these transitions are one-photon transitions, they are affected by a different set of systematic effects than the two-photon transitions on which most other spectroscopic measurements of hydrogen are based. In order to contribute to the test of QED, their transition frequencies must be determined with a relative uncertainty on the order of one part in $10^{12}$, corresponding to approximately 1 kHz in absolute terms. This is in turn approximately a factor of 10000 smaller than the relatively broad natural linewidth of the 2S-$n$P transitions, and a successful measurement requires both a very large experimental signal-to-noise ratio and a detailed theoretical understanding of the line shape of the observed resonance. The 2S-$n$P transitions were probed on a cryogenic beam of hydrogen atoms, which were optically excited to the metastable 2S level. The atomic beam was crossed at right angles with counter-propagating spectroscopy laser beams, which further excited the atoms to the $n$P level. The fluorescence from the subsequent rapid spontaneous decay served as experimental signal. The excitation with two counter-propagating beams led to two Doppler shifts of equal magnitude, but opposite sign, which thus canceled each other out. A velocity-resolved detection was used to determine any residual Doppler shifts, which could be excluded within the measurement uncertainty for both of the measurements discussed below. In a first experiment, the 2S-4P transition was probed. Quantum interference of neighboring atomic resonances produced subtle distortions of the line shape, which were found to be significant because of the very large resolution relative to the linewidth. The line shifts caused by the distortions were directly observed and could be removed by use of a line shape model based on perturbative calculations. With this, the transition frequency was determined with a relative uncertainty of 4 parts in $10^{12}$. In combination with the very precisely measured 1S-2S transition frequency, this allowed the, at the time, most precise determination of $R_\infty$ and $r_\mathrm{p}$ from atomic hydrogen. Moreover, good agreement was found with the much more precise value of $r_\mathrm{p}$ extracted from spectroscopy of muonic hydrogen, which had been in significant disagreement with previous data from (electronic) hydrogen, causing concern about the validity of QED. This result has since been confirmed by other experiments. The 2S-4P measurement is treated in the appendix of this thesis. The 2S-4P measurement, despite its large signal-to-noise ratio, was limited by counting statistics. To improve precision, a transition with a narrower linewidth and an improved experimental signal was necessary. Hence, the study of the 2S-6P transition, which offers a three times smaller natural linewidth, was begun. The atomic beam apparatus was upgraded, resulting in a corresponding decrease of the experimentally observed linewidth, and a close to an order of magnitude larger flux of atoms in the low-velocity tail of the atomic beam. Together with a detector redesign, this led to an up to 16 times larger signal than for the 2S-4P measurement, opening the path to increased precision. The Doppler-shift suppression was also rebuilt to support such precision, including a fiber collimator developed for this purpose, which provides high-quality spectroscopy beams at the new transition wavelength of 410 nm. This enabled a measurement of the 2S-6P transition frequency with a statistical uncertainty of 430 Hz, five times lower than for the 2S-4P measurement and corresponding to a suppression of the Doppler shift by six orders of magnitude. At this level of precision, the light force shift from the diffraction of atoms at the light grating formed by the counter-propagating spectroscopy beams becomes significant. This light force shift was directly observed for the first time for the 2S-$n$P transitions and found to be well-described by a model derived for this purpose. The size of all other systematic effects, except the very precisely known recoil shift, is estimated to be below 500 Hz each. The blind data analysis is ongoing at the time of writing and thus no transition frequencies can yet be given. However, a preliminary analysis suggests a five-fold improvement in the determination of $R_\infty$ and $r_\mathrm{p}$ as compared to the 2S-4P measurement, and a two-fold improvement over the currently most precise determination from atomic hydrogen. This places the uncertainty of the determined value of $r_\mathrm{p}$ within a factor of five of that of the muonic value. The 2S-6P measurement is treated in the main text of this thesis.

Optical pin beams (OPBs) represent a novel class of structured light fields engineered for resilient, long-distance propagation. Their exceptional stability and strong resistance to atmospheric turbulence make them a compelling alternative to conventional Gaussian and other structured beams for free-space optical systems. This review provides a comprehensive overview of the physical principles, generation strategies, experimental realizations, and emerging applications of OPBs. By precise spatial modulation of the optical wave vectors, OPBs achieve highly collimated, self-reconstructing propagation with distinctive pin-like features that confer remarkable robustness and self-healing capability. We further discuss several OPB derivatives–including vortex, inverted, and vortex-inverted OPBs–which expand the functional landscape by enabling flexible control over amplitude, phase, polarization, and orbital angular momentum. Experimentally, OPBs have demonstrated outstanding performance across diverse platforms, ranging from free-space and underwater optical communications to optical trapping and super-resolution imaging. With their unique combination of propagation stability, light-field tunability, and environmental adaptability, OPBs hold strong promise for next-generation optical communication, precision sensing, and advanced imaging technologies. This review summarizes recent research progresses in OPBs and highlights key opportunities and prospects for advancing their scientific discoveries and practical applications.

In many developmental systems, cells differentiate into a tissue by reading out morphogen concentration fields, a process fundamentally limited by noise. How much can the precision of this process be improved by nonlocal information, e.g., via cell-cell communication? Using a Bayes-optimal framework, we show that positional inference depends crucially on morphogen spatial correlations and on the “structural prior” that encodes the geometry of the cellular lattice performing the readout. We derive upper bounds on positional information gain due to nonlocal readout and identify signal processing algorithms that approximate optimal positional inference, as well as simple chemical reaction schemes which implement such algorithms. Our theory suggests that correlational information can be exploited to significantly enhance developmental precision.

Laser flash melting and revitrification experiments have recently improved the time resolution of cryo-electron microscopy (cryo-EM) to the microsecond timescale, making it fast enough to observe many of the protein motions that are associated with function. The technique has also opened up a new dimension for cryo-EM sample preparation, making it possible to deposit compounds onto a cryo-EM sample while it is frozen, so that upon flash melting, the embedded particles experience an altered environment. For example, we have recently shown that depositing ultrathin silicon dioxide membranes onto a cryo-EM sample causes particles to detach from the interface upon flash melting, removing preferred particle orientation. These experiments also point towards a new strategy for initiating protein dynamics in time resolved experiments by depositing reagents, which will then mix with the sample upon flash melting. Here, we describe an apparatus for physical vapor deposition of compounds onto cryo-EM samples, detailing its design and operation. As a demonstration, we determine that the minimum thickness of silicon dioxide sealing membranes in a laser flash melting experiment is just over two monolayers. We propose that our design can form the basis for an integrated platform for microsecond time-resolved cryo-EM experiments.

Gallium alloys are promising materials in biomedical engineering, electronics, and wireless communications, thanks to their good conductivity, non toxicity and their ability to sustain large deformations. They can be transported in capillaries using purely electric means by continuous electrowetting (CEW). Current models of CEW-driven flows do not address the transient response to fast changes in the excitation, crucial in many applications. Here, we present a theory that describes the CEW-driven oscillatory motion of a drop of Eutectic Gallium-Indium alloy inside a capillary. We consider inertia, viscosity and the transient response of the electrical circuit consisting of the drop plus the electrolyte where it is immersed. The theory describes fairly well the experimental drop velocity and explains the existence of an optimal frequency that maximizes the velocity.

Acoustic metamaterials enhance traditional material properties through microstructure engineering, providing new opportunities to shape sound fields in applications ranging from biomedical imaging, clinical therapy to non-destructive testing. However, at the MHz frequency ranges, only a few metamaterial architectures exist. They are often highly attenuating or difficult to manufacture, and generally provide limited 3D control over sound propagation. Here, we introduce a MHz-frequency ultrasonic metamaterial based on laser-engraved glass. By structuring meta-voxels with different engraving patterns, we define a fully-3D, anisotropic metamaterial exhibiting local variations in the sound speed of up to 20% compared to unstructured glass, and losses 100x lower than in comparable 3D printed metamaterials. We use this metamaterial to define a library of standard elements that can be modularly combined to create and shape complex-patterned ultrasonic fields. Our experiments are supported by a theoretical model, which provides additional insights into the microstructural origin of the metamaterial behavior and opens the door to designing tailored ultrasound fields and responses.

We demonstrate a dual optical frequency comb concept that down-converts arbitrary narrowband D-band (110-170 GHz) signals to baseband without any filter or optical/RF frequency tuning, using low frequency RF components.

Controlled assembly of active-passive colloidal mixtures offers a route to reconfigurable microscale machines, but their self-assembly pathways remain poorly understood. We study the directed assembly of metallo-dielectric Janus particles (JPs) and passive polystyrene (PS) beads using optoelectrically reconfigurable AC-field patterning, which allows precise control over particle composition and binding sequence. Through experiments, analytical modeling, and simulations, we show that dipolar interactions drive robust JP-JP and JP-PS dimer formation with frequency-dependent stability. At intermediate and high frequencies, JP-PS binding is strongly attractive, whereas at low frequencies it becomes effectively repulsive due to electrical double-layer screening and electrohydrodynamic flows at the metallic hemisphere. In multi-particle systems, PS beads act as cooperative hubs that hierarchically recruit JPs, yielding higher-order hybrid structures. We identify structural isomers - for example, 3JP + 1PS clusters can form chain-like or triangular configurations depending on assembly sequence. Simulations confirm both as equilibrium states, with the triangular isomer slightly more stable. Similar polymorphism appears in larger clusters (4JPs). Overall, we establish a framework for controlled active-passive colloidal assembly, showing how frequency-tunable interactions and structural polymorphism enable the design of reconfigurable colloidal machines for applications in microrobotics, targeted delivery, and adaptive materials.

Global warming is often framed in broad planetary numbers such as the 1.5C and 2C warming thresholds, creating the false impression that individual corporations efforts to reduce emissions are meaningless in the absence of collective action. This perspective causes companies to reduce ambition towards voluntarily cutting emissions, as they believe their pollution has negligible impacts on its own. Reframing the issue to focus on the life-saving potential of independent corporate actions empowers companies to act and holds them accountable for inaction. Here, we show the results from an innovative climate-health modeling technique which calculates the avoided deaths from sustainability efforts for 3,084 companies spanning a range of sizes and sectors. From the reported emissions and planned emissions reductions, we create scenarios for 2020-2049 with and without companies pledged emissions cuts and calculate the resulting warming from 2020-2100 using a climate emulator. We then use temperatures from these scenarios to calculate the deaths resulting from warming by using mortality damage functions. We find that more than 92% of these companies stand to save at least one life by following through with emissions reduction plans. Additionally, if all 3,084 companies follow through with their emissions reduction plans, over 4.4 million temperature-related deaths can be avoided.

Accurately calibrating the center-of-mass (CoM) offset between the spacecraft (SC) and the inertial sensor test mass (TM) is crucial for space-based gravitational-wave (GW) antennas, such as LISA and Taiji. Current calibration methods require additional spacecraft maneuvers that disrupt science data continuity and inter-satellite links, compromising the coherence of gravitational wave signals. Here, we present a maneuver-free calibration scheme that directly estimates the CoM offset vector using only standard science-mode measurements from inertial sensors, interferometers, and differential wavefront sensors. By embedding the CoM offset induced coupling acceleration as an extended state in a model-based adaptive Kalman filter, we achieve estimation accuracy of 0.01-1.5 mm across all axes with a maximum error below 1%. This approach enables continuous, high-precision calibration during nominal observation runs, ensuring continuous and coherent gravitational wave data collection while maintaining the required precision, and also facilitating advanced DFACS functions such as performance evaluations and fault diagnosis. For LISA-like missions, where data continuity is paramount for detecting faint gravitational wave signals, this method will enhance scientific output and reliability.

3D image display is essential for next-generation volumetric imaging; however, dense depth multiplexing for 3D image projection remains challenging because diffraction-induced cross-talk rapidly increases as the axial image planes get closer. Here, we introduce a 3D display system comprising a digital encoder and a diffractive optical decoder, which simultaneously projects different images onto multiple target axial planes with high axial resolution. By leveraging multi-layer diffractive wavefront decoding and deep learning-based end-to-end optimization, the system achieves high-fidelity depth-resolved 3D image projection in a snapshot, enabling axial plane separations on the order of a wavelength. The digital encoder leverages a Fourier encoder network to capture multi-scale spatial and frequency-domain features from input images, integrates axial position encoding, and generates a unified phase representation that simultaneously encodes all images to be axially projected in a single snapshot through a jointly-optimized diffractive decoder. We characterized the impact of diffractive decoder depth, output diffraction efficiency, spatial light modulator resolution, and axial encoding density, revealing trade-offs that govern axial separation and 3D image projection quality. We further demonstrated the capability to display volumetric images containing 28 axial slices, as well as the ability to dynamically reconfigure the axial locations of the image planes, performed on demand. Finally, we experimentally validated the presented approach, demonstrating close agreement between the measured results and the target images. These results establish the diffractive 3D display system as a compact and scalable framework for depth-resolved snapshot 3D image projection, with potential applications in holographic displays, AR/VR interfaces, and volumetric optical computing.

Using the Monte Carlo ray tracing package McStas, we illustrate the possibilities of creating virtual experiments of the neutron spectrometer BIFROST at the European Spallation Source, ESS. With this model, we are able to benchmark BIFROST with respect to expected intensity, $Q$- and energy-resolution. The simulations reproduce the expected resolution behavior and quantify effects that are difficult to capture analytically, including a wavelength-dependent edge enhancement arising from a combination of the long-pulsed source and the pulse-shaping chopper. Furthermore, we present an antiferromagnetic (AF) spin wave simulation, which we use to create realistic datasets at different instrument operation settings. Our virtual experiments focus on realistic dispersive dynamics and illustrate how the virtual experiment approach reveal resolution effects, not easily calculable via analytical models. This demonstrates the crucial role of numerical simulations in the planning of challenging experiments.

Surfaces and structures capable of multiple stable configurations have attracted growing interest for on-demand shape morphing. In this work, we consider an elastic compliant plate coupled to a two-dimensional foundation comprising an array of bistable elements, a system that can form and retain complex continuous morphologies without sustained actuation via creation of stable domain walls separating regions in different stable states. These domain walls exhibit three distinct behaviors: expansion, shrinking, and metastable pinning. These arise from two limits of foundation discreteness. In the continuum limit, where bistable units are strongly coupled, domain walls undergo global phase transitions analogous to first-order phase transitions. In the anti-continuum limit, discreteness introduces Peierls-Nabarro-type energy modulations that lead to metastable pinning. To quantify these behaviors and the transition between the two limits, we develop a reduced-order model that captures the total potential energy of configurations with domain walls and validate it using finite element analysis (FEA). For axisymmetric domain walls, the model yields phase diagrams identifying the regimes of expansion, shrinking, and pinning as functions of bistable-potential asymmetry, relative foundation discreteness, and domain-wall size. We then extend the analysis to non-axisymmetric geometries and establish local geometric criteria that predict the stability of convex and concave polygonal domain walls, confirmed by simulations. Together, these results clarify how discreteness enables stability through energy-landscape modulation, provide predictive design rules for multistable reconfigurable surfaces, and offer insights into domain-wall stability more generally in elastically coupled multistable metamaterials.

In this work, we propose a hybrid quantum-inspired heuristic for automatically tuning the Lorenz-96 model – a simple proxy to describe atmospheric dynamics, yet exhibiting chaotic behavior. Building on the history matching framework by Lguensat et al. (2023), we fully automate the tuning process with a new convergence criterion and propose replacing classical Gaussian process emulators with quantum counterparts. We benchmark three quantum kernel architectures, distinguished by their quantum feature map circuits. A dimensionality argument implies, in principle, an increased expressivity of the quantum kernels over their classical competitors. For each kernel type, we perform an extensive hyperparameter optimization of our tuning algorithm. We confirm the validity of a quantum-inspired approach based on statevector simulation by numerically demonstrating the superiority of two studied quantum kernels over the canonical classical RBF kernel. Finally, we discuss the pathway towards real quantum hardware, mainly driven by a transition to shot-based simulations and evaluating quantum kernels via randomized measurements, which can mitigate the effect of gate errors. The very low qubit requirements and moderate circuit depths, together with a minimal number of trainable circuit parameters, make our method particularly NISQ-friendly.

I present a general laser modulation control algorithm. I implement the LIDAR Frequency Modulated Continuous Wave (FMCW) scheme as a special case of study. My proposal applies to any arbitrary modulation pattern and is based on an iterative algorithm that infers the laser transfer function in order to perform on-the-fly deconvolution. I present an experimental proof-of-principle using an external-cavity diode laser, the accuracy of which I analyse by comparing the obtained frequency response with a targeted modulation pattern. In addition to the FMCW scheme, I am also testing square wave modulations, which are more demanding in terms of bandwidth.

First-principles based crystal structure prediction (CSP) methods have revealed an essential tool for the discovery of new materials. However, in solids close to displacive phase transitions, which are common in ferroelectrics, thermoelectrics, charge-density wave systems, or superconducting hydrides, the ionic contribution to the free energy and lattice anharmonicity become essential, limiting the capacity of CSP techniques to determine the thermodynamical stability of competing phases. While variational methods like the stochastic self-consistent harmonic approximation (SSCHA) accurately account for anharmonic lattice dynamics ab initio, their high computational cost makes them impractical for CSP. Machine-learning interatomic potentials offer accelerated sampling of the energy landscape compared to purely first-principles approaches, but their reliance on extensive training data and limited generalization restricts practical applications. Here, we propose an iterative learning framework combining evolutionary algorithms, atomic foundation models, and SSCHA to enable CSP with anharmonic lattice dynamics. Foundation models enable robust relaxations of random structures, drastically reducing required training data. Applied to the highly anharmonic H$_3$S system, our framework achieves good agreement with the benchmarks based on density functional theory, accurately predicting phase stability and vibrational properties from 50 to 200 GPa. Importantly, we find that the statistical averaging in the SSCHA reduces the error in the free energy evaluation, avoiding the need for extremely high accuracy of machine-learning potentials. This approach bridges the gap between data efficiency and predictive power, establishing a practical pathway for CSP with anharmonic lattice dynamics.

In both research and industrial settings, it is often necessary to expand the input/output channels of measurement instruments using relay-based multiplexer boards. In research activities in particular, the need for a highly flexible and easily configurable solution frequently leads to the development of customized systems. To address this challenge, we developed a system optimized for automated direct current (DC) measurements. The result is based on a 4x4 switching platform that simplifies measurement procedures that require instrument routing. The platform is based on a custom-designed circuit board controlled by a microcontroller. We selected bistable relays to guarantee contact stability after switching. We finally developed a system architecture that allows for straightforward expansion and scalability by connecting multiple platforms. We share both the hardware design source files and the firmware source code on GitHub with the open-source community. This work presents the design and development of the proposed system, followed by the performance evaluation. Finally, we present a test of our designed system applied to a specific case study: the DC analysis of complex resistive networks through multi-point resistance measurements using only a single voltmeter and current source.

For most of its history, cosmology was a qualitatively constrained discourse on the universe, shaped by limited observational access and the absence of global dynamical laws. This situation has changed decisively in recent decades. Modern cosmology is now driven by an unprecedented flow of high-precision data from a wide range of independent probes, including the cosmic microwave background, large-scale structure, supernovae, baryon acoustic oscillations, gravitational lensing, cosmic chronometers, redshift-space distortions, gravitational-wave standard sirens, and emerging 21-cm observations, among others. This observational wealth is matched by a concrete theoretical and mathematical framework, based on general relativity, which provides the dynamical equations governing the evolution of spacetime and matter at cosmic scales. Combined with explicit background and perturbative equations, this framework enables quantitative, predictive, and falsifiable descriptions of cosmic evolution. Thus, cosmology operates today as a nomological natural science of the observable universe, characterized by general laws, predictive power, and systematic empirical testing. We argue that this epistemic transformation motivates a corresponding conceptual shift, directly analogous to the historical transition from astrology to astronomy. In this sense, the transition from cosmology to cosmonomy should begin to be discussed among cosmologists, or, more precisely, among cosmonomers.