Interparticle interactions with multiple length scales play a pivotal role in the formation and stability of quasicrystals. Choosing a minimal set of length scales to stabilize a given quasicrystal is a challenging problem. To address this challenge, we propose a symmetry-preserving screening method (SPSM) to design a Landau theory with a minimal number of length scales—referred to as the minimal Landau theory—that includes only the essential length scales necessary to stabilize quasicrystals. Based on a generalized multiple-length-scale Landau theory, SPSM first evaluates various spectral configurations of candidate structures under a hard constraint. It then identifies the configuration with the lowest free energy. Using this optimal configuration, SPSM calculates phase diagrams to explore the thermodynamic stability of desired quasicrystals. SPSM can design a minimal Landau theory capable of stabilizing the desired quasicrystals by incrementally increasing the number of length scales. Our application of SPSM has not only confirmed known behaviors in 10- and 12-fold quasicrystals but also led to a significant prediction that quasicrystals with 8-, 14-, 16-, and 18-fold symmetry could be stable within three-length-scale Landau models.

An intriguing phenomenon in nonequilibrium quantum thermodynamics is the asymmetry of thermal processes. Relaxation to thermal equilibrium is the most important dissipative process, being a key concept for the design of heat engines and refrigerators, contributing to the study of foundational questions of thermodynamics, and being relevant for quantum computing through the process of algorithmic cooling. Despite their importance, the dynamics of these processes are far from being understood. We show that the free relaxation to thermal equilibrium follows intrinsically different paths depending on whether it involves the temperature of the system to increase or to decrease. Our theory is exemplified using the recently developed thermal kinematics based on information geometry theory, utilizing three prototypical examples: a two-level system, the quantum harmonic oscillator, and a trapped quantum Brownian particle, in all cases showing faster heating than cooling under the appropriate conditions. A general understanding is obtained based on the spectral decomposition of the Liouvillian and the spectral gap of reciprocal processes.

It has been shown that dipolar Bose-Einstein condensates that are tightly trapped along the polarization direction can feature a rich phase diagram. In this paper we show that finite temperature can assist in accessing parts of the phase diagram that otherwise appear hard to realize due to excessively large densities and number of atoms being required. These include honeycomb and stripe phases both unconfined and with a finite extent. To map out a phase-diagram, we employ both variational analysis and full numerical calculations solving the finite-temperature extended Gross-Pitaevskii equation (TeGPE). Furthermore, we exhibit real-time evolution simulations leading to such states. We account for the effect of thermal fluctuations by means of Bogoliubov theory, employing the local density approximation. We find that finite temperatures can lead to a significant decrease in the necessary particle number and density that might ultimately pave a route for future experimental realizations.

Numerical methods based on matrix product states (MPSs) are currently the de facto standard for calculating the ground-state properties of (quasi-)one-dimensional quantum many-body systems. While the properties of the low-lying excitations in such systems are often studied in this MPS framework through dynamics by means of time-evolution simulations, we can also look at their statics by directly calculating eigenstates corresponding to these excitations. The so-called MPS excitation ansatz is a powerful method for finding such eigenstates with a single-particle character in the thermodynamic limit. Although this excitation ansatz has been used quite extensively, a general method for calculating expectation values for these states is lacking in the literature: We aim to fill this gap by presenting a recursive algorithm to calculate arbitrary observables expressed as matrix product operators. This method concisely encapsulates existing methods for—as well as extensions to—the excitation ansatz, such as excitations with a larger spatial support and multiparticle excitations, and is robust enough to handle further innovations. We demonstrate the versatility of our method by studying the low-lying excitations in the spin-1 Heisenberg chain and the one-dimensional Hubbard model, looking at how the excitations converge in the former, while in the latter, we present a refined method of targeting single-particle excitations inside a continuum by minimizing the energy variance rather than the energy itself. We hope that this technique will foster further advancements with the excitation ansatz.

Acoustic levitation in air provides a containerless, gravity-free platform for investigating driven many-particle systems with nonconservative interactions and underdamped dynamics. In prior work the interactions among levitated particles were limited to attractive forces from scattered sound and repulsion from hydrodynamic microstreaming. We report on experiments in which contact cohesion provides a third type of interaction. When particle size and separation are both much smaller than the sound wavelength, this interplay of three interactions results in forces that are attractive over several particle diameters, become repulsive at close approach, and are again attractive at contact. In the presence of sound-induced athermal fluctuations that generate particle collisions, the interplay of these three forces enables the formation of particle chains with anisotropic interactions that depend on chain size and shape due to multibody effects. With the control of the kinetic pathways and the strength of the contact cohesion, different patterns can be assembled, from triangular lattices to labyrinthine patterns of chains to lacelike networks of interconnected rings. These results shed light on the multibody character of acoustic interactions and can be utilized to direct the self-assembly of particles.

Relating macroscopic observables to microscopic interactions is a central challenge in the study of complex systems. While current approaches often focus on pairwise interactions, a complete understanding requires going beyond these to capture the full range of possible interactions. We present a unified mathematical formalism, based on the Möbius inversion theorem, that reveals how different decompositions of a system into parts lead to different, but equally valid, microscopic theories. By providing an exact bridge between microscopic and macroscopic descriptions, this framework demonstrates that many existing notions of interaction, from epistasis in genetics and many-body couplings in physics, to synergy in game theory and artificial intelligence, naturally and uniquely arise from particular choices of system decomposition, or mereology. By revealing the common mathematical structure underlying seemingly disparate phenomena, our paper highlights how the choice of decomposition fundamentally determines the nature of the resulting interactions. We discuss how this unifying perspective can facilitate the transfer of insights across domains, guide the selection of appropriate system decompositions, and enable the search for new notions of interaction. To illustrate the latter in practice, we decompose the Kullback-Leibler divergence, and show that our method correctly identifies which variables are responsible for the divergence. In addition, we use Rota's Galois connection theorem to describe coarse grainings of mereologies, and efficiently derive the renormalized couplings of a 1D Ising model. Our results suggest that the Möbius inversion theorem provides a powerful and practical lens for understanding the emergence of complex behavior from the interplay of microscopic parts, with applications across a wide range of disciplines.

The response of many-body quantum systems to an optical pulse can be extremely challenging to model. Here we explore the use of neural networks, both traditional and generative, to learn and thus simulate the response of such a system from data. The quantum system can be viewed as performing a complex mapping from an input time series (the optical pulse) to an output time-series (the systems response), which is often also an optical pulse. Using both the transverse and nonintegrable Ising models as examples, we show that not only can temporal convolutional networks capture the input/output mapping generated by the system but can also be used to characterize the complexity of the mapping. This measure of complexity is provided by the size of the smallest latent space that is able to accurately model the mapping. We further find that a generative model, in particular a variational autoencoder, significantly outperforms traditional autoencoders at learning the complex response of many-body quantum systems. For the example that generated the most complex mapping, the variational autoencoder produces outputs that have less than 10% error for more than 90% of inputs across our test data.

Förster resonance energy transfer (FRET) is a quantum mechanical process governing the nonradiative energy transfer between coupled electric dipoles. Its strong distance dependence makes it a widely used as a “molecular ruler” in biology, chemistry, and physics. In single-molecule FRET (smFRET) experiments employing time-resolved confocal microscopy, deviations from the theoretical Förster relationship between FRET efficiency and donor fluorescence lifetime—termed dynamic shifts—provide insight into underlying molecular conformational dynamics. A key challenge in interpreting these shifts is disentangling contributions from the intrinsic motion of the fluorescent dyes from those of the biomolecular system under study. We present a novel theoretical framework based on Langevin dynamics to model the stochastic translational and rotational motion of dye linkers, incorporating first-principles physics and chemical constraints consistent with molecular dynamics simulations. Our results demonstrate that the dominant factor influencing dynamic shifts in smFRET is the relative orientational fluctuations of the dyes' electric dipole moments, rather than their accessible spatial volumes. These findings refine the theoretical foundations of FRET and provide the most precise estimates of FRET efficiency to date, enhancing its utility as a molecular-scale probe of dynamic processes.

Jamming systems, including colloids, emulsions, foams, and biological tissues, undergo significant deformation during processes like material scraping or wound self-healing. To adequately spread a foam or cream over a surface, external force must be applied to artificially scrape it. Notably, the transition from slip to scraping when foam is manipulated using a rigid plate remains poorly understood. Systematic observations of the internal foam structure during scraping were conducted, and the scraping length was qualitatively analyzed by varying the scraping velocity. Our study reveals that the transition from slip to scraping is driven by the sequential propagation of bubble rearrangements. Furthermore, the scraping length diverges towards the transition point, with a critical exponent of approximately 0.61. These findings align with directional percolation theory, underscoring the robustness of the theoretical framework. This study offers a comprehensive understanding of the macroscopic kinetics and rheological behaviors in jamming systems, with implications for applications in materials science, food processing, and biological systems.

Over the past decades, the development of optical parametric amplification (OPA) -based systems has demonstrated excellent performance characteristics in terms of pulse duration, energy, peak power, and repetition rate. However, the studies on OPA typically rely on specific experimental conditions or numerical parameters, limiting the comprehensive understanding of the overall process. In this work, by introducing a new quantum perspective by incorporating non-Hermitian theory into the optical parametric process, we demonstrate the global behaviors of the non-Hermitian optical parametric system in the parametric space, and we categorize such behaviors into four distinct quadrants, depending on whether the anti-parity-time (anti-PT) symmetry is broken and the amplification is present. We observe exceptional surfaces separating the anti-PT exact phase and anti-PT broken phase in the anti-PT symmetric OPAs, and a unique behavior of gain/loss-sgn (phase mismatch) locking indicating the gain phase transition of eigenmodes in the anti-PT symmetry-broken OPAs. In the vicinity around the exceptional points, we observe significant amplification jumps, which are beneficial for experimental observation. Our study demonstrates that lossful OPAs with unique non-Hermitian characteristics provide promising routes for definitely advancing the novel design of ultrabroadband and high efficiency.

Oxygen-deficient titanium dioxide (${\mathrm{TiO}}_{2-x}$) is a very attractive material for several applications ranging from photocatalysis to resistive switching. Oxygen vacancies turn insulating anatase titanium dioxide into a polaronic conductor, while creating a defect-state band below the ultraviolet semiconducting gap. Here we employ a combination of broadband infrared (IR) reflectivity and THz-pump/IR-probe measurements to investigate the relationship between localized defect states and delocalized conducting polaronic states. We show that the THz pump allows to convert deeply localized electrons into metastable polarons with a lifetime in the ns range. These long-lived metastable states may find application in novel optoelectronic applications exploiting the interplay of dc resistivity, with terahertz and infrared signals.

Deep neural networks (DNNs) share important similarities with structural glasses. Both have many degrees of freedom and their dynamics are governed by a high-dimensional, nonconvex landscape representing either the loss or energy, respectively. Furthermore, both experience gradient descent dynamics subject to noise. In this work we investigate, by performing quantitative measurements on realistic networks trained on the MNIST and CIFAR-10 data sets, the extent to which this qualitative similarity gives rise to glasslike dynamics in neural networks. We demonstrate the existence of a topology trivialization transition as well as the previously studied under-to-overparametrized transition analogous to jamming. By training DNNs with overdamped Langevin dynamics in the resulting disordered phases, we do not observe diverging relaxation times at nonzero temperature nor do we observe any caging effects, in contrast to glass phenomenology. However, the weight overlap function follows a power law in time, with exponent $\approx -0.5$, in agreement with the mode-coupling theory of structural glasses. In addition, the DNN dynamics obey a form of time-temperature superposition. Finally, dynamic heterogeneity and aging are observed at low temperatures. These results highlight important and surprising points of both difference and agreement between the behavior of DNNs and structural glasses.

Layered van der Waals tellurides reveal topologically nontrivial properties that give rise to unconventional magneto-transport phenomena. Additionally, their semimetallic character with high mobility makes them promising candidates for large magneto-thermoelectric effects. Remarkable studies on the very large and unconventional Nernst effect in ${\mathrm{WTe}}_2$ have been reported, raising questions about whether this property is shared across the entire family of van der Waals tellurides. In this study, systematic measurements of the Nernst effect in telluride van der Waals Weyl semimetals are presented. Large linear Nernst coefficients in ${\mathrm{WTe}}_2$ and ${\mathrm{MoTe}}_2$ are identified, and moderate Nernst coefficients with nonlinear behavior in magnetic fields are observed in ${\mathrm{W}}_{0.65}{\mathrm{Mo}}_{0.35}{\mathrm{Te}}_2, {\mathrm{TaIrTe}}_4$, and ${\mathrm{TaRhTe}}_4$. Within this sample set, a correlation between the dominant linear-in-magnetic-field component of the Nernst coefficient and mobility is established, aligning with the established Nernst scaling framework, although with a different scaling factor compared with existing literature. This enhancement might be caused by the shared favorable electronic band structure of this family of materials. Conversely, the nonlinear component of the Nernst effect in a magnetic field could not be correlated with mobility. This nonlinear term is almost absent in the binary compounds, suggesting a multiband origin and strong compensation between electron-like and hole-like carriers. This comprehensive study highlights the potential of van der Waals tellurides for thermoelectric conversion.

We study a binary metric-free Vicsek model involving two species of self-propelled particles aligning with their Voronoi neighbors, focusing on a weakly nonreciprocal regime, where species $A$ aligns with both $A$ and $B$, but species $B$ does not align with either. Using agent-based simulations, we find that even with a small fraction of $B$ particles, the phase behavior of the system can be changed qualitatively, which becomes reentrant as a function of noise strength: traveling bands arise not only near the flocking transition, but also in the low-noise regime, separated in the phase diagram by a homogeneous polar liquid regime. We find that the ordered bands in the low-noise regime travel through an ordered background, in contrast to their metric counterparts. We develop a coarse-grained field theory, which can account for the reentrant phase behavior qualitatively, provided the higher-order angular modes are taken into consideration.