Papers

Deep learning models have proven enormously successful at using multiple layers of representation to learn relevant features of structured data. Encoding physical symmetries into these models can improve performance on difficult tasks, and recent work has motivated the principle of parameter symmetry breaking and restoration as a unifying mechanism underlying their hierarchical learning dynamics. We evaluate the role of parameter symmetry and network expressivity in the generalisation behaviour of neural networks when learning a real-space renormalisation group (RG) transformation, using the central limit theorem (CLT) as a test case map. We consider simple multilayer perceptrons (MLPs) and graph neural networks (GNNs), and vary weight symmetries and activation functions across architectures. Our results reveal a competition between symmetry constraints and expressivity, with overly complex or overconstrained models generalising poorly. We analytically demonstrate this poor generalisation behaviour for certain constrained MLP architectures by recasting the CLT as a cumulant recursion relation and making use of an established framework to propagate cumulants through MLPs. We also empirically validate an extension of this framework from MLPs to GNNs, elucidating the internal information processing performed by these more complex models. These findings offer new insight into the learning dynamics of symmetric networks and their limitations in modelling structured physical transformations.

We experimentally study a scallop-like swimmer with reciprocally flapping wings in a nearly frictionless, cohesive granular medium consisting of hydrogel spheres. Significant locomotion is found when the swimmer's flapping frequency matches the inverse relaxation time of the material. Remarkably, the swimmer moves in the opposite direction compared to its motion in a cohesion-free granular material of hard plastic spheres. At higher or lower frequencies, we observe no motion of the swimmer, apart from a short initial transient phase. X-ray radiograms reveal that the wing motions create low-density zones, which in turn give rise to a hysteresis in drag and propulsion forces. This time-dependent effect, combined with the swimmer's inertia, accounts for locomotion at intermediate frequencies.

Kinetic constraints in quantum many-body systems strongly restrict the accessible Hilbert space, giving rise to highly nontrivial dynamical behavior. In recent years, such systems have attracted growing interest as they provide insight into mechanisms of thermalization and into regimes where thermalization fails. In this work, we study a family of rule-based kinetically constrained models, including the celebrated Quantum Game of Life, from the perspective of quantum complexity, with a focus on entanglement, nonstabilizerness, and quantum chaos. Using spectral diagnostics such as level statistics and spectral form factors, we show that these models exhibit robust chaotic behavior while simultaneously supporting both strong and weak Hilbert-space fragmentation and quantum many-body scar states. Our results reveal that the nature of Hilbert-space fragmentation can be tuned qualitatively from strong to weak fragmentation and ultimately to its absence, within a single family of models through simple variations of the underlying kinetic rules. To further elucidate the structure of these fragmented subspaces, we characterize them through their ability to generate quantum resources. In particular, we show that resource-generation capacity does not necessarily correlate with the dimensionality of a fragmented sector, and that entanglement structure and the ability to generate nonstabilizerness provide effective diagnostics for distinguishing dynamically disconnected sectors, including those supporting nonthermal scarred dynamics. Our work thus places kinetically constrained models within a broader and more general framework, not limited to Rydberg blockade based constraints only, and demonstrates that simple variations in underlying rules can lead to qualitatively distinct static and dynamical regimes including chaotic, fragmented, and scarred phases.

Two classes of Phase Change Materials (PCMs) have emerged as the best candidates for applications requiring the fast reading and writing of data: GeTe-Sb$_{2}$Te$_{3}$ pseudobinary alloys (group 1) and doped Sb-Te compounds near the eutectic composition Sb$_{70}$Te$_{30}$ (group 2). Both material classes undergo reversible switching between a low-resistance opaque crystalline phase and a high-resistance but less absorbing amorphous phase through heating, electrical, or optical pulses, achieving (sub-)nanosecond switching speeds. While group 1 compounds are employed in current generation devices and relatively well studied, model systems in group 2 compounds have been found to crystallize more rapidly and thus offer the perspective of improved devices. Despite their superior crystallization speed (SET process), to this point there have been no ultrafast experimental studies on crystallized PCMs of group 2 for the RESET process. Here we perform ultrafast electron diffraction and femtosecond resolved sum frequency non-linear spectroscopy on Peierls distorted Sb$_{2}$Te crystallized thin films (PCM of group 2) following femtosecond optical pulse irradiation. We observe a pump-induced structural change on two distinct timescales: responses with characteristic timescales of $\approx$ 300 fs and 2~ps. We quantified the experimental result by a coherent displacement and the Debye-Waller effect. In particular, the $\approx$ 300 fs UED signal results from the ultrafast release of the Peierls distortion through non-thermal coherent Sb displacement, while the 2~ps response reflects electron-lattice equilibrium. These results reveal the ultrafast non-thermal structural dynamics of Sb$_{2}$Te and suggest energy-efficient switching of group 2 PCMs should be possible on femtosecond time scales.

We introduce a space-time Floquet operator for crystals whose spatial and temporal translations are intertwined. Unlike the conventional Floquet operator, which describes evolution over a full time period, the space-time Floquet operator evolves the system over a fraction of the period paired with a spatial shift that generates the primitive space-time unit cell. Its eigenmode spectrum defines a space-time band structure that unfolds conventional Floquet bands to reveal the consequences of the intertwined crystal symmetry in reciprocal frequency-wavevector space. We relate the topology of these space-time bands to quantized transport phenomena, such as Bloch oscillations and adiabatic charge transport, and uncover an intrinsically fractional charge pump enabled by the primitive space-time cycle. Numerical simulations quantitatively support these predictions with small deviations controlled by the speed of the modulation. We also demonstrate how nonreciprocal parametric resonances are naturally anticipated and accurately predicted by our framework. Our approach applies broadly to both classical and quantum systems with space-time symmetry, including non-Hermitian crystals.

We report the discovery of a ternary compound, Eu$_{0.8}$Pt$_6$Al$_{16.4}$. We determine its chemical and structural characteristics based on energy-dispersive X-ray spectroscopy as well as both powder and single-crystal X-ray diffraction, demonstrating that it crystallizes in a hexagonal structure type EuPt$_6$Al$_{17}$ with no reported structural analog. The electronic and magnetic properties are characterized by temperature- and field-dependent magnetization, and temperature-dependent resistance measurements, revealing that the Eu$^{2+}$ magnetic moments order antiferromagnetically below 2.8 K.

High-quality ultrafast light sources are critical for developing advanced time- and angle-resolved photoemission spectroscopy (TrARPES). While the application of high harmonic generation (HHG) light sources in TrARPES has increased significantly over the past decade, the optimization of the HHG probe beam size and selective control of the light polarization, which are important for TrARPES measurements, have been rarely explored. In this work, we report the implementation of high-quality HHG probe source with an optimum beam size down to 57 $\mu$m $\times$ 90 $\mu$m and selective light polarization control, together with mid-infrared (MIR) pumping source for TrARPES measurements using a 10 kHz amplifier laser. The selective polarization control of the HHG probe source allows to enhance bands with different orbital contributions or symmetries, as demonstrated by experimental data measured on a few representative transition metal dichalcogenide materials (TMDCs) as well as topological insulator Bi$_2$Se$_3$. Furthermore, by combining the HHG probe source with MIR pumping at 2 $\mu$m wavelength, TrARPES on a bilayer graphene shows a time resolution of 140 fs, allowing to distinguish two different relaxation processes in graphene. Such high-quality HHG probe source together with the MIR pumping expands the capability of TrARPES in revealing the ultrafast dynamics and light-induced emerging phenomena in quantum materials.

We examine how an anomalous Josephson current influences odd-frequency superconducting correlations in two Josephson junction geometries. The first consists of two ferromagnetic layers between conventional $s$-wave superconductors, with magnetizations along the $x$- and $y$-axes, forming a bilayer junction. The second contains three ferromagnetic layers between two $s$-wave superconductors, with magnetizations along the $x$-, $y$-, and $z$-axes, forming a trilayer junction. Both systems are analyzed in the short and long junction limits. In the bilayer case, where no anomalous Josephson current is present, odd-frequency equal-spin triplet correlations develop pronounced peaks at finite magnetizations in the short junction limit for both tunneling and transparent interfaces. The odd-frequency mixed-spin triplet correlations also exhibit peaks at finite magnetizations for tunneling interfaces, whereas for transparent interfaces they display both peaks and zeros. In the trilayer case, where an anomalous Josephson current exists, similar peaks in both equal- and mixed-spin odd-frequency triplet correlations occur at finite magnetizations for tunneling and transparent interfaces. The spatial profiles of these correlations remain largely unaffected by the anomalous current. The Josephson diode efficiency is finite and reaches its maximum at magnetizations corresponding to the peaks of the anomalous current. Overall, our results show that the anomalous Josephson current has only a marginal influence on odd-frequency spin-triplet pairing. This indicates that the emergence of odd-frequency correlations and the Josephson diode effect are largely independent phenomena, contrary to earlier conjectures. Analysis of the long junction limit leads to the same qualitative conclusions for both configurations.

This study investigates two critical aspects of the gas sensing mechanism in metal oxide sensors: (1) the conditions that maximize chemisorbed oxygen concentration as a function of temperature and oxygen partial pressure, and (2) which surface oxygen species (chemisorbed or lattice-bound) are primarily responsible for interaction with carbon monoxide (CO). SnO2 thin films, deposited at temperatures as low as 60 C and exhibiting mixed amorphous-crystalline phases with open, tortuous porosity, were evaluated for CO sensing at 200 C. Comprehensive characterization using EIS, MS, XPS, TEM, and sensor tests revealed a strong correlation between high sensing performance and the structural/electronic features of the defect rich low-temperature-deposited SnO2. Electrochemical impedance spectroscopy (EIS) was employed to identify the optimal sensing temperature. Mass spectroscopy (MS) used to analyze the exhaust gases after sensing reactions. The films exhibited oxygen under-stoichiometry and high concentrations of chemisorbed oxygen species. In situ XPS under 1 mbar (10000 ppm) O2 and CO exposures showed that chemisorbed oxygen, not lattice oxygen, was actively involved in CO oxidation, as further confirmed by CO2 detection via Mass spectroscopy (MS). Quantitative analysis revealed dynamic surface chemical status alternations, emphasizing the pivotal role of chemisorbed oxygen in the sensing mechanism at 200 C.

Thermal decomposition of metastable fcc-(Ti,Al)Nx limits the lifetime of coated components. While energetic decomposition aspects can be modelled reliably, the inherent variability of chemical environment-dependent diffusion activation energies remains systematically unexplored. Here, we predict an activation energy range (envelope) for mass transport in varying chemical environments, reflecting the vacancy concentration range fcc-(Ti0.5Al0.5)1-xNx with x = 0.47, 0.5, 0.53. The stoichiometric compound shows maximum thermal stability, consistent with experimental data. Metal vacancies decrease the average migration energy, while metal and nitrogen vacancies reduce barriers via lattice strain relaxation, enhancing mobility. The strong chemical environment dependence challenges conclusions from single-point activation energy data.

Shear thickening suspensions of non-Brownian polydisperse particles are simulated in 2D using a discrete element method based algorithm (LF-DEM) at high packing fractions ($\phi$) and large non-dimensional stresses ($\sigma$). Rigidity analysis of the stress induced particle clusters is carried out using pebble game algorithm for polydisperse suspensions and compared with the statistically equivalent bidisperse systems. A critical value of the packing fraction, $\phi_c$, close to the shear jamming transition, $\phi_J^{\mu}$, ($\phi_c<\phi_J^{\mu}$) is obtained where rigid particle clusters begin to grow sharply. The growth is found to be characterized by a critical transition of an order parameter ($f_\text{rig}$), defined by the fraction of particles in rigid clusters which scales as, $f_\text{rig}\sim (\phi-\phi_c)^{\beta}$ for $\phi>\phi_c$, and by the susceptibility scaling, $\chi_\text{rig}\sim|\phi-\phi_c |^{-\gamma}$, with exponents having values consistent with the critical exponents in 2D percolation transition. The variations of $f_\text{rig}$ and $\chi_\text{rig}$ in polydisperse suspensions are found to be identical to that of the statistically equivalent bidisperse suspensions. Finite size scaling analysis shows a divergence of correlation length near $\phi_{c_\infty}$ following critical exponent $\nu\approx 1.33$, in agreement with the 2D percolation theory. Furthermore, $\phi_c$ and $\phi_J^{\mu}$ are found to vary non-monotonically with polydispersity index and depend on the particle stiffness.

One among the most intriguing results coming from the application of statistical mechanics to the study of brain is the understanding that it, as a dynamical system, is inherently out of equilibrium. In the realm of non-equilibrium statistical mechanics and stochastic processes the standard observable computed to discriminate whether a system is at equilibrium or not is the entropy produced along the dynamics. For this reason we present here a detailed calculation of the entropy production in the Amari model, a coarse-grained model of the brain neural network, consisting in an integro-differential equation for the neural activity field, when stochasticity is added to the original dynamics. Since the way to add stochasticity is always to some extent arbitrary, i.e., in particular for coarse-grained models, there is no general prescription to do it, we precisely investigate the interplay between the noise properties and the original model features, discussing in which cases the stationary state is of thermal equilibrium and which cases is out of equilibrium, providing explicit and simple formulas. We also show how, following for the derivation the particular case considered, how the entropy production rate is related to the variation in time of the Shannon entropy of the system.

Understanding the emergence of complex correlations in strongly interacting systems remains a fundamental challenge in quantum many-body physics. One fruitful approach is to develop solvable toy models that encapsulate universal properties shared by realistic systems. In this work, we introduce the Brownian SYK-Hubbard model, which combines the all-to-all random interactions of the Sachdev-Ye-Kitaev (SYK) model with on-site Hubbard-type interactions. This hybrid construction enables the study of the interplay between nonlocal random dynamics and local correlation effects: (1) As the interaction strength increases, the single-particle spectrum exhibits a transition from a single peak to a two-peak structure, signaling the onset of Mottness. (2) The spectral form factor undergoes a sequence of dynamical transitions as the evolution time increases before reaching the plateau in the long-time limit under strong Hubbard interactions. (3) The out-of-time-order correlator is computed by summing a series of modified ladder diagrams, which determines the quantum Lyapunov exponent and reveals a violation of the bound on branching time. Our results establish a new analytically tractable platform for exploring the effects of Hubbard interactions in chaotic many-body systems.

Two-dimensional(2D) multiferroic materials hold significant promise for advancing the miniaturization and integration of nanodevices. In this study, we demonstrate that 2D bilayer ScI2, which exhibits ferromagnetic(FM) ordering within each layer, enables the tuning of interlayer magnetic coupling, ferroelectricity, and valley polarization through interlayer sliding and rotation. Our first-principles calculations show that the AA stacking configuration induces antiferromagnetic (AFM) interlayer coupling, while a 180 rotation of one layer (resulting in the antialigned AA stacking) leads to FM interlayer coupling. Moreover, the interlayer magnetic coupling can be switched between AFM and FM by translating the stacking configuration: FM in the aligned AB and BA configurations, and AFM in the antialigned AB and BA configurations. This switching behavior is driven by variations in superexchange interactions due to orbital hopping between layers. Notably, the aligned stacking exhibits ferroelectricity upon sliding, which is induced by interlayer orbital hybridization and the resulting asymmetric charge redistribution, with maximal ferroelectric behavior occurring at the AB and BA stacking configurations. Additionally, for the AB and BA stackings, spontaneous valley polarization emerges from the manipulation of the spin orientation toward the out-of-plane direction. This valley polarization arises due to inversion symmetry breaking, either through ferroelectricity (in the AB and BA stackings) or AFM interlayer coupling , in combination with spin-orbit coupling. These results highlight the intricate interplay between magnetism, ferroelectricity, and valley polarization in bilayer ScI2, with each property being tunable via stacking configuration.

In density functional theory, the SCAN (Strongly Constrained and Appropriately Normed) and r2SCAN functionals significantly improve over generalized gradient approximation functionals such as PBE (Perdew-Burke-Ernzerhof) in predicting electronic, magnetic, and structural properties across various materials, including transition-metal compounds. However, there remain puzzling cases where SCAN and r2SCAN underperform, such as in calculating the band structure of graphene, the magnetic moment of Fe, the potential energy curve of the Cr2 molecule, and the bond length of VO2. This research identifies a common characteristic among these challenging materials: non-compact covalent bonding through s-s, p-p, or d-d electron hybridization. While SCAN and r2SCAN excel at capturing electron localization at local atomic sites, they struggle to accurately describe electron localization in non-compact covalent bonds, resulting in a biased improvement. To address this issue, we propose the r2SCAN+V approach as a practical modification that improves accuracy across all the tested materials. The parameter V is 4 eV for metallic Fe, but substantially lower for the other cases. Our findings provide valuable insights for the future development of advanced functionals.

High-resolution absorption and laser spectroscopy are used to determine electronic energy levels for Ho$^{3+}$ ions in K$_2$YF$_5$ microparticles. A total of 72 crystal-field energy levels, distributed among 8 multiplets, are assigned. This optical data is used for crystal-field modelling of the electronic structure of Ho$^{3+}$ in K$_2$YF$_5$. Partially-resolved hyperfine splittings are accurately reproduced by the model. The temperature dependence of the fluorescent lifetime of the $^5$F$_5$ multiplet is measured and the temperature dependence of the non-radiative relaxation is modelled by a five-phonon process. Preliminary measurements of infra-red to visible upconversion in microparticles co-doped with Ho$^{3+}$ and Yb$^{3+}$ is reported.

Artificial transmission lines built with lumped-element inductors and capacitors form the backbone of broadband, nearly quantum-limited traveling-wave parametric amplifiers (TWPAs). When tailoring these transmission lines for parametric processes, nonlinear elements are added, typically nonlinear inductances in superconducting circuits, and energy and momentum conservation between interacting tones must be enforced through careful design of the ATL dispersion relation. However, a unified theoretical framework describing achievable dispersion relations is lacking. Here, I develop such a framework, borrowing from periodic structure theory and passive network synthesis. These complementary approaches divide the design space: periodic loading synthesis employs spatial modulation of frequency-independent components, while filter synthesis employs frequency-dependent responses in spatially-uniform components. The framework reveals fundamental constraints and enables the discovery of novel TWPA architectures. In particular, I design a kinetic inductance TWPA with a novel phase-matching architecture, and a backward-pumped Josephson TWPA exploiting an ambidextrous i.e., right-left-handed transmission line.

Laser-induced cavitation in liquids originates from optical breakdown processes that depend sensitively on both laser-plasma dynamics and the chemical microenvironment of the solvent. Herein, we experimentally decouple the effects of ionic strength and ion specificity on cavitation inception in aqueous electrolytes spanning neutral, acidic, and alkaline regimes. Using focused nanosecond laser pulses, we show that increasing ionic strength universally lowers the cavitation threshold by enhancing charge screening and seed-electron availability. However, under constant ionic strength, strongly asymmetric behavior emerges: acidic (hydrogen chloride, HCl) solutions inhibit cavitation, whereas alkaline (sodium hydroxide, NaOH) solutions enhance it. This asymmetry arises from hydrated-electron kinetics that depends on the ion specificity. In acidic solutions, hydronium ions act as diffusion-limited scavengers of hydrated electrons, quenching their lifetime and inhibiting avalanche ionization. In contrast, hydroxide ions reduce hydronium availability and extend electron survival, promoting more efficient plasma formation. Despite large discrepancies in breakdown thresholds, electrical conductivity remains nearly constant, demonstrating that microscopic electron chemistry, rather than bulk charge transport, governs cavitation onset. These results establish a mechanism connection between electrolyte chemistry and optical breakdown, showing that ion-specific reaction dynamics fundamentally control laser-induced cavitation in aqueous environments.

The standard Axelrod model of cultural dissemination, based on discrete cultural traits, exhibits a non-equilibrium phase transition but is inherently limited by its inability to continuously probe the critical behavior. We address this limitation by introducing a generalized Axelrod model utilizing continuous cultural traits confined to the interval $[0,1]$, and a similarity threshold, $d$, that serves as a continuous control parameter representing cultural tolerance. This framework allows for a robust analysis of the model's critical properties and its dynamics under cultural drift (copying noise). For the perfect copying scenario, we precisely locate the critical threshold $d_c$, which separates the disordered (fragmented) and ordered (polarized) phases. Through Finite-Size Scaling, we find that the mean domain density vanishes continuously at $d_c$ with the exponent $\beta = 1/3$. Simultaneously, the largest domain fraction displays a surprising discontinuous jump at $d_c$. We find that the finite size effects in the critical region are governed by the exponent $\nu=2$ for both the continuous and discontinuous transitions. Under imperfect copying, persistent noise introduces a powerful selective pressure on the trait space, leading to the emergence of two symmetry-related attractors at the trait values $d$ and $1-d$. However, these noise-induced attractors prove fragile in the thermodynamic limit, becoming unstable at large lattice sizes, which directly accounts for the observed failure of the dynamics to freeze under sustained cultural drift. This suggests that in large, continuously evolving societies, true cultural convergence is highly unlikely, leading instead to sustained fragmentation and nonstationary dynamics where cultural domains never fully stabilize.

We study fermionic and bosonic systems coupled to a real or synthetic static gauge field that is quantized, so the field itself is a quantum degree of freedom and can exist in coherent superposition. A natural example is electrons on a quantum ring encircling a quantized magnetic flux (QMF) generated by a superconducting current. We show that coupling to a common QMF gives rise to an emergent interaction between particles with no classical analog, as it is topological and nonlocal (independent of interparticle distance). Moreover, the interaction persists even when the particles lie in a nominally field-free region, with the vector potential mediating the interaction. We analyze several one- and two-dimensional model systems, encompassing both real and synthetic gauge fields. These systems exhibit unusual behavior, including strong nonlinearities, non-integer Chern numbers, and quantum phase transitions. Furthermore, synthetic gauge fields offer high tunability and can reach field strengths that are difficult to realize with real magnetic fields, enabling engineered nonlinearities and interaction profiles.

Altermagnets feature antiparallel spin sublattices with $d$-, $g$-, or $i$-wave spin order, yielding nonrelativistic spin splitting without net magnetization. We show that embedding a two-dimensional $d$-wave altermagnet in a driven optical cavity induces a finite, tunable magnetization. Coherent photon driving couples selectively to electronic sublattices, and the resulting altermagnets' symmetry-broken spin texture yields a pronounced steady-state spin imbalance – coherent magnetization – absent in conventional antiferromagnets for the same lattice configuration. A mean-field Lindblad analysis reveals the dominance of quadratic over linear couplings. In the strong-coupling regime, distinct polariton signatures emerge in the steady state of induced magnetization. This work demonstrates cavity control of altermagnets for spintronic applications.

A binary system of particles that move in opposite directions under an applied field can exhibit disordered states as well as laned states where the particles organize into oppositely moving high-mobility lanes to reduce collisions. Previous studies of laning transitions generally focused on particles with purely repulsive interactions. Here, we examine laning transitions for oppositely moving pattern-forming systems of particles with competing attractive and repulsive interactions, which in equilibrium form crystal, stripe, and bubble states. In addition to multiple types of laned states, we find jammed crystals, stripes, and bubbles, and generally observe a much richer variety of phases compared to the purely repulsive system. In the stripe forming regime, the system can dynamically reorder into oppositely moving stripes that are aligned in the direction of the drive. The bubble phase can produce strongly polarized jammed states of elongated bubbles where particles in the individual bubbles segregate to opposite sides of the bubbles. We also find disordered states, segregated laned bubble states where the bubbles pass each other in lanes, and segregated bubbles that move through one another. In the compact bubble regime, we obtain a plastic bubble state in which the oppositely driven particles remain trapped in the bubbles but the bubbles move past each other at a slow velocity due to a net imbalance in the bubble population. At higher drives, individual particles begin to jump from bubble to bubble. We show that the different phases and the transitions between them produce signatures in the velocity-force and differential mobility curves. We demonstrate that the critical force for escaping from the jammed state is nonmonotonic, with stripes exhibiting the lowest unjamming force.

Small polarons remain a significant bottleneck in the realization of efficient devices using transition metal oxides. Routes to engineer small polaron coupling to electronic states and lattice modes to control carrier localization remain unclear. Here, we measure the formation of small polarons in CuFeO$_{2}$ using transient extreme ultraviolet reflection spectroscopy and compare it to theoretical predictions in realistically parameterized Holstein models, demonstrating that polaron localization depends on its coupling to the high-frequency versus low-frequency components of the phonon bath. We measure that small polaron formation occurs on a comparable ~100 fs timescale to other Fe(III) compounds. After formation, a dynamic delocalization of the small polaron occurs through a coherent lattice expansion between Fe-O layers and charge-sharing with surrounding Fe(IV) states. Our simulations of polaron formation dynamics reveal that two major factors dictate polaron formation timescales: phonon density and reorganization energy distributions between acoustic and optical modes, matching experimental findings. Our work provides a detailed, real-time observation of how electronic-structural coupling in a polaron-host material can be leveraged to suppress polaronic effects for various applications.

We study the noisy dynamics of periodically driven, discrete-step quantum walks in a one-dimensional photonic lattice. We find that in the bulk, temporal noise that is constant within a Floquet period leads to decoherence-free momentum subspaces, whereas fully random noise destroys coherence in a few time steps. When considering topological edge states, we observe decoherence no matter the type of temporal noise. To explain these results, we derive a non-perturbative master equation to describe the system's dynamics. We experimentally confirm our findings in a time multiplexed photonic lattice implemented in a double-fiber ring setup subject to laser pulse input states, in which we engineer different types of temporal noise.

Optical Bloch equations and rate equations serve as powerful tools to model light-matter interactions from textbook-like two-level atoms to the complex internal dynamics of molecules. A particular challenge in this context is posed by molecular laser cooling, where many dozens or hundreds of levels need to be taken into account for a comprehensive modeling. Here, we present MoleCool, a numerically efficient Python toolbox to implement and solve the corresponding differential equation systems. We illustrate both the capabilities of the toolbox and some of the intricacies of molecular laser cooling by educational examples, which range from simple Rabi oscillations to spontaneous and coherent cooling schemes for various currently studied or considered molecular species. This includes, in particular, a comprehensive modeling of laser cooling dynamics with full hyperfine structure resolution in radioactive radium monofluoride (RaF), as well as studies of other complex species such as barium monofluoride (BaF) and ytterbium monohydroxide (YbOH).

A key question in benchmarking generative crystal reconstruction models is how the amount and type of crystallographic information provided to a generative model affects its ability to reconstruct atomic structures. Yet such comparisons often overlook the fact that models receive unequal information about the target during reconstruction, thereby confounding architectural conclusions. We present AtomBench, an extensible, model-agnostic framework for comparing generative models on a well-defined crystal reconstruction task (rather than de novo generation), which we here apply to conventional superconductors. We train and evaluate four models, AtomGPT, CDVAE, FlowMM, and MatterGen, on the JARVIS Supercon-3D and Alexandria DS-A/B datasets, grouping them by the information each accesses at inference. Reconstruction fidelity is measured by the Kullback-Leibler divergence (KLD) and mean absolute error (MAE) of lattice parameters and the root-mean-squared displacement (RMSD) of atomic coordinates. We further introduce the continuous corrected RMSD (ccRMSD), a continuous measure of local geometric fidelity defined for every structure in the test set. MatterGen achieves the best atomic-coordinate reconstruction, followed by AtomGPT, while CDVAE reconstructs lattices most accurately, and FlowMM is the least accurate but fastest overall. We find that conditioning on critical temperature T$_c$ does not consistently improve fidelity. We also release AtomBench as an open-source Python package that reproduces all reported reconstruction metrics, figures, and tables from one or more benchmark files and supports direct submission to the JARVIS-Leaderboard. Any inverse model emitting crystal reconstructions can be benchmarked with atombench, and we encourage community use. https://github.com/atomgptlab/atombench

Driven-dissipative systems provide a natural setting for the emergence of exceptional points – i.e. non-Hermitian degeneracies where eigenmodes coalesce. These points are important for applications such as sensing, where enhanced sensitivity is required, and exhibit interesting and useful phenomena that can be controlled with experimentally accessible parameters. In this regard a four-port, three-mode, cavity-magnonics platform is demonstrated in which two microwave excitations can be precisely phase shifted and/or attenuated relative to one another. Destructive interference between the hybridised cavity-magnon modes is shown to give rise to antimodes (antiresonances) in the transmission spectrum, enabling coherent perfect extinction of the outgoing signals at selected ports. This interference can be used to actively tune the position and properties of exceptional points, without the fine tuning conventionally required to obtain exceptional points. Such controllable, interference-based engineering of exceptional points provides a practical and flexible pathway toward next-generation, high-sensitivity sensing devices operating at microwave frequencies.

Considering ultracold spin-imbalanced Fermi-Fermi mixtures with different spin up and down masses, the absorbed power, subject to an external perturbation with low frequency, has been calculated. The system is composed of spin-up quasiparticles and spin-down quasiholes. The average chemical potential and energy gap have also been numerically calculated via applying different fixed interaction strengths and masses, and then by solving coupled differential equations characterized by Hartree-Fock potential for the spin species, as well as that of the phase separation (PS), leading to imbalance chemical potential. The dependence of the imbalance and average chemical potential in PS regime, to the polarization of the normal component, mass ratios, and interaction strengths are analyzed. Examining density of states (DOS), and by applying the Fermi golden rule at finite temperatures, the absorbed power has accordingly been calculated as a function of temperature, interaction strength, and mass ratio. Finally, the behavior of absorbed power versus frequency has been investigated.

Density functional theory has demonstrated remarkable predictive power in calculating magnetic properties at zero temperature. At finite temperatures, thermally excited phonons may affect magnetism. Efficient ab-initio methods to calculate the temperature dependence of magnetic exchange interactions are still lacking despite the importance of room temperature magnetism for applications. Exchange is controlled by an interplay between metal-ligand hybridization, Hubbard repulsion, band gap, interatomic distances and bond angles, all of which change with temperature. Here we present a method to calculate the exchange interactions at finite temperatures from first principles using only two supercell calculations and quantify these mechanisms. Changes in bond angles and the band gap are identified as a primary factors. In NiO with 180-degree bonds exchange decreases with temperature, while in Cr$_2$O$_3$ with the bond angles away from 180 degrees the exchange increases by 10% at room temperature.

Encapsulating low-dimensional magnetic materials within carbon nanotubes (CNTs) offers a compelling route to stabilize unconventional magnetic states and engineer quantum functionalities at the limit of miniaturization. In this work, we systematically investigate the structural, electronic, and magnetic properties of one-dimensional (1D) CrSBr chains encapsulated within CNTs using density functional theory (DFT) and spin dynamics simulations. We demonstrate the structural stability of CrSBr@CNT, where confinement and charge transfer cooperate to stabilize ferromagnetism in the 1D limit, which persists up to 50 K. These findings position CrSBr@CNT as a model platform for realizing 1D magnetism and establish CNT encapsulation as a powerful strategy for exploring emergent quantum spin phenomena and engineering nanoscale spintronic devices.