Papers

We show that the low-energy theory of a $d$-wave altermagnet is characterized by anisotropic Dirac cones with spin-split band structures based on a recently proposed tight-binding model. In this system, spin-selective perfect elliptic dichroism emerges, enabling exclusive excitation of either up-spin or down-spin electrons by tuning the ellipticity of the incident light. We further derive a formula for the third-order photocurrent generated under simultaneous application of elliptically polarized light and a static electric field, expressed in terms of the quantum metric and Berry curvature. Using this formula, we demonstrate that only an up-spin polarized current is induced. This third-order response constitutes the leading photocurrent, as second-order processes such as injection and shift currents are forbidden by the inversion symmetry inherent to altermagnets. They lead to the prediction that, in insulating $d$-wave altermagnets, a spin-polarized third-order photocurrent arises as the leading electric response when elliptically polarized light and a static electric field are applied simultaneously. These findings provide a foundation for future developments in photoinduced spintronics based on altermagnets.

Machine learning force fields enable high-accuracy modeling of solid-state electrolytes (SSEs). This perspective evaluates dataset size, reference quality, and model architectures. We show that rigid SSE frameworks favor efficient learning, prioritizing data quality over quantity. Crucially, force RMSE does not reliably predict transport performance. By analyzing locality and benchmarking frameworks, we provide practical guidelines to accelerate the development of next-generation solid-state batteries.

Fractal electronic spectra arising from the competition between lattice periodicity and magnetic flux are a fundamental hallmark of two-dimensional quantum systems. While the spectral properties of Hofstadter butterflies are well documented, their thermodynamic response has remained remarkably unexplored. We present an original characterization of the electronic entropy $S_{e}$, and specific heat $C_{e}$, at half-filling, for square, honeycomb, and triangular lattices under a magnetic field. We demonstrate that these observables exhibit fast and slow magneto-thermo oscillations and pronounced magnetocaloric effects. We identify striking self-similarity in $S_e$ and $C_e$, tracing heart-shaped specific heat and tunnel-like entropy contours that repeat at specific lattice-dependent magnetic fluxes. Entropy minima at low temperatures play a remarkable role, acting as fingerprints for the butterfly spines, resolving the underlying fractal spectra. These findings may establish thermal measurements as high-resolution spectroscopic probes, providing a robust framework for recognizing fractal signatures through thermodynamics in diverse nanostructures.

We propose that scaling dimensions of d=3 conformal field theories can be studied on a system of qubits with near term quantum simulation platforms. Our proposal chooses couplings of quantum many-body problems on a polyhedral lattice at which the conformal state-operator correspondence can be observed most accurately in the spectrum. We validate our protocol on the Ising model where we extract the scaling dimensions of a number of scaling operators with a few percent accuracy from the spectrum of a system of just 20 qubits. The procedure makes only minor assumptions beyond general conformal invariance – it may hence be applied widely. Requirements and challenges to realize this proposal on quantum computers are discussed. Our results demonstrate that for current or near term qubit platforms, three dimensional conformal field theories present a unique opportunity – a forefront problem that is difficult on classical computers but may be solved through quantum simulation.

Monolayer semiconductors hold great potential for nanoscale electronics, optoelectronics, and photonics. Excitons dominate their optical properties. As their electric fields extend outside the monolayer, they are sensitive to their surroundings. Thus, disorder can cause exciton instability, which is detrimental to device performance and critical for scalability and reproducibility. Here, we adapt a super-resolution fluorescence fluctuation microscopy technique to image localized exciton fluctuations in monolayer semiconductors, allowing us to identify unstable spots in an otherwise continuous monolayer with constant fluorescence. These spots correspond to interfacial disorder measured by atomic force microscopy. We examine how different material interfaces influence the fluctuations by comparing several substrates and provide additional insight into the disorder behind the fluctuations using hyperspectral imaging. We also assess the reduction of disorder upon thermal annealing, evidenced by a decrease in fluctuations. Our results show that fluorescence fluctuation imaging can detect disorder features similar to those of atomic force microscopy and hyperspectral imaging, while being faster and easier to implement. Therefore, it is a promising method for evaluating the quality of monolayer semiconductors, particularly when integrated with nanostructures and heterostructures found in nano-optoelectronic devices.

Understanding whether retrieval in dense associative memories survives thermal noise is essential for bridging zero-temperature capacity proofs with the finite-temperature conditions of practical inference and biological computation. We use Monte Carlo simulations to map the retrieval phase boundary of two continuous dense associative memories (DAMs) on the $N$-sphere with an exponential number of stored patterns $M = e^{\alpha N}$: a log-sum-exp (LSE) kernel and a log-sum-ReLU (LSR) kernel. Both kernels share the zero-temperature critical load $\alpha_c(0)=0.5$, but their finite-temperature behavior differs markedly. The LSE kernel sustains retrieval at arbitrarily high temperatures for sufficiently low load, whereas the LSR kernel exhibits a finite support threshold below which retrieval is perfect at any temperature; for typical sharpness values this threshold approaches $\alpha_c$, making retrieval nearly perfect across the entire load range. We also compare the measured equilibrium alignment with analytical Boltzmann predictions within the retrieval basin.

We study transient nonequilibrium dynamics in Fisher-regularized Wasserstein gradient flows and identify a sign-changing cross-dissipation mechanism generated by the coupling between transport dissipation and Fisher-information geometry. Using the Ornstein–Uhlenbeck Fokker–Planck system as an analytically tractable setting, we derive an exact reduced variance dynamics on the Gaussian manifold, \[ \dot{u}=2(1-u)+\frac{\varepsilon}{u}, \] where \(u(t)=\sigma^2(t)\) is the variance and \(\varepsilon>0\) is the Fisher regularization strength. The reduced dynamics reveal distinct transient regimes induced by the interaction between transport relaxation and information-geometric curvature. The associated cross-dissipation term changes sign at the critical scale \(\sigma=1\), separating cooperative acceleration for localized states with \(\sigma<1\) from transient interference at larger variance scales. In the subcritical regime, Fisher curvature accelerates the descent of the baseline free energy; beyond the critical transition, it partially opposes the Ornstein–Uhlenbeck pullback and generates transient overshoot toward a displaced Fisher-regularized equilibrium. We also establish a bounded transient-acceleration-window result, showing that the cooperative acceleration phase has finite duration with an upper bound depending only on the Fisher regularization strength. Finite-difference simulations support the analytical predictions and suggest that qualitatively similar sign-transition behavior may persist beyond Gaussian closure for non-Gaussian initial conditions, including bimodal and Laplace distributions. Overall, the results provide a transient dynamical perspective on Fisher-regularized dissipative systems and show how information-geometric curvature can reorganize intermediate-time Wasserstein relaxation while preserving the globally dissipative structure of the flow.

Thermomechanical Controlled Processing (TMCP) is widely used to control the microstructure and properties of linepipe or high strength low alloy steels (HSLA). These steels are often joined by welding and used in demanding environments such as the Arctic. In these materials, the thermal path the steel experiences is critical for understanding microstructural evolution during processing. A key step is the solid-state phase transformation during cooling from the high-temperature austenite to the room-temperature microstructure which significantly influences the final mechanical properties. We used 3D electron backscatter diffraction (EBSD) to explore the relationship between the austenite phase and the room temperature microstructure. A significant result for the present work is the collection, and analysis, of data from a large volume (150 x 150 x 100 um3, with a (200 nm)3 voxel size) which enables analysis of a complete prior austenite grain. This grain is twinned, allowing us to analyse the variants at the twin boundary in this grain, which offers new insights into the mechanisms of the transformation to the low temperature phase by highlighting the significant of the twin boundaries on the variants present. This suggests opportunities to engineer novel microstructures by controlling the high-temperature grain boundary character.

Active stresses in biological cells and tissues drive many developmental processes. However, increasing experimental evidence suggests that additional mechanical interactions with surrounding material can play a crucial role in guiding these processes. We introduce a minimal model of this scenario and investigate how pattern formation in an active material can be controlled by an inhomogeneous environment. Specifically, we consider an active fluid in which a chemical species regulates local active stresses and is redistributed by the resulting flows. We show that active stress patterns within such a fluid exhibit frictiotaxis and systematically characterize how inhomogeneous external friction affects mechanochemical pattern formation instabilities. We find that hydrodynamic screening plays a crucial role in mediating the cross-talk between friction patterns and active fluid self-organization and identify a mechanochemical frustration mechanism that gives rise to pattern oscillations caused by inhomogeneous friction.

We study the self-assembly of colloidal microgel particles at a quasi-two-dimensional air-water interface of a drying droplet. Using bright-field microscopy, we demonstrate that increasing particle elasticity drives interfacial organization from repulsion-stabilized crystallization to attraction-dominated gelation, via diverse metastable structures including clusters, voids and anisotropic aggregates. Molecular dynamics simulations using an effective potential that captures the interplay between hydrophobic, capillary, steric and dipolar interactions, reproduce the overall phenomenology of the observed colloidal morphogenesis. Our findings establish particle elasticity as a key parameter governing non-equilibrium structural organization of colloids at an interface.

The microstructural mechanisms governing the plastic work partitioning in twinning-induced plasticity (TWIP) steels remain insufficiently understood, particularly under strain localization. This study provides a crystallographic-scale interpretation of the fraction of plastic work stored during deformation of 310S TWIP steel exhibiting complex deformation mechanisms. Electron backscatter diffraction (EBSD) was used to characterize local crystallographic orientation and microtexture during uniaxial tensile deformation using two complementary approaches: tracking the same surface region at successive strain levels and analyzing regions corresponding to known local plastic strain. Deformation was initially dominated by dislocation slip, whereas twinning activity increased significantly beyond an equivalent plastic strain of approximately 0.3. Progressive deformation produced pronounced lattice rotations and a dual-fiber texture comprising dominant 111 parallel to rolling direction (RD) and secondary 100 parallel to RD components. Correlation of the EBSD observations with previously quantified evolution of the energy storage rate reveals that intensified twinning and texture redistribution in strain-localized regions are accompanied by a pronounced decrease in the fraction of plastic work stored in the material. Twin-matrix refinement and progressive lattice rotation promote non-uniform strain distribution and create favorable conditions for shear-band-mediated deformation, contributing to a reduction of the energy storage rate toward zero or negative values at advanced stages of localization.

Interband pairing in multiband superconductors is often neglected because of its higher energetic cost compared with intraband pairing. We show that, in multiband systems, a Zeeman magnetic field can stabilize interband pairing through the near degeneracy of spin-split branches from different bands, even within a minimal on-site attractive interaction. Using hexagonal tight-binding models with locally broken inversion symmetry, we find a Zeeman-driven transition between a conventional intraband s-wave state and an interband-dominated superconducting Mixing state. The resulting quasiparticle spectrum is intrinsically gapless, leading to anomalous thermodynamic behavior, including a T-linear specific heat at low temperatures, reflecting a finite zero-energy density of states.

Density functional theory augmented with a Hubbard correction (DFT+U) is widely used to treat localized electronic states, but its predictions are often sensitive to the choice of the local projection space defining the correlated subspace. This sensitivity poses a practical challenge for computational reproducibility, particularly when projection parameters vary across codes, basis sets, or materials. In this work, we systematically investigate how the effective on-site Coulomb interaction $U_{\mathrm{eff}}$, determined ab initio using constrained density functional theory, depends on the size of the local projection space in all-electron APW+lo calculations. Using rutile and anatase TiO$_2$ and $\beta$-MnO$_2$ as representative test cases, we show that applying a single fixed $U_{\mathrm{eff}}$ across different projection choices introduces artificial projection-driven errors in total energies, including spurious magnetic ordering transitions and unphysical sensitivity of phase stability. These artifacts are eliminated when $U_{\mathrm{eff}}$ is determined in an internally consistent manner for each projection space, yielding projection-consistent DFT+U predictions for lattice parameters, phase energetics, and magnetic ground states. By analyzing total-energy trends alongside the spatial characteristics of the localized $d$ orbitals, we demonstrate that the systematic reduction of $U_{\mathrm{eff}}$ with increasing projection size originates from orbital relaxation and enhanced electronic screening associated with orbital spatial extension. These results provide a physically motivated framework for controlling projection-space artifacts in DFT+U calculations and for obtaining energetically robust predictions across diverse correlated materials and computational setups.

Trust is one of the cornerstones of human society. One of the evolutionary pressure mechanisms that may have led to its emergence is the presence of incentives for trustworthy behavior. However, this type of reward has received relatively little attention in the context of spatial trust games, which are often used to build models in evolutionary game theory. To fill this gap, we introduce an inter-role reward mechanism in the spatial trust game, so that an investing trustor can choose to pay an extra cost to reward a trustworthy trustee. With extensive numerical simulations, we find that this type of reward does not always promote trust. Rather, while moderate rewards break the dominance of mistrust, thereby favoring investment, excessive rewards eventually stimulate a nonreturn strategy, ultimately suppressing the evolution of trust. Additionally, lower reward costs do not necessarily promote trust. Instead, more costly, but not excessive, rewards enhance the advantage of the original investment, consolidating the clusters of rewarders and improving trust. Our model thus provides evidence about the counterintuitive nature of the relationship between trust and rewards in a complex society.

The application of molecular dynamics (MD) simulations to quasistatic loading is severely limited by the large separation between atomic vibration timescales and experimentally relevant deformation rates. In this work we employ the Practical Time Averaging (PTA) framework to overcome this limitation and enable atomistic simulations of crystalline solids under quasistatic loading conditions. PTA exploits the intrinsic separation of timescales by defining slow variables as time-averaged observables of the fast atomistic dynamics and their evolution on the slow loading timescale, thereby avoiding explicit integration of the fast dynamics. Using this approach, we simulate uniaxial deformation, in both tension and compression, of 4 to 20 nm cubic specimens of face centered cubic aluminum nanocrystals at applied strain rates approaching quasistatic conditions. We define slow variables as the averaged kinetic energy, potential energy, and normal stress in the loading direction, and track their evolution on the slow timescale. The stress-strain curves show yielding close to the theoretical stress for homogeneous nucleation, followed by successive load drops and rises caused by dislocation nucleation, motion, and exit from free surfaces. The "smaller is harder" effect is evident from the stress-strain response and from the variation of yield stress with sample size. Serrations in the response are more pronounced for smaller samples. The effects of applied strain rate and initial temperature are also studied. The method also captures the evolution of intricate dislocation microstructures on the slow timescale by tracking time-averaged atomic positions. The PTA framework enables simulations at strain rates several orders of magnitude lower than those accessible to conventional MD, demonstrating significant speedup in computational time while retaining full atomistic resolution.

High-quality InAs quantum wells grown on InP are a promising platform for topological quantum information processing due to their large g-factor, strong Rashba spin-orbit interaction, and their compatibility with in-situ-deposited superconductors. In this work, we investigate InAs/InGaAs quantum wells grown on InP (001) wafers, focusing on how the layer structure and strain influence the electronic properties and surface morphology. By combining quantum transport measurements with atomic force microscopy, we show that the layer design predominantly affects the mobility anisotropy, which aligns well with the surface morphology. Surface characterization further reveals the mechanism of quantum well collapse when the layer thickness exceeds the strain limit. In addition, transport measurements demonstrate that quantum confinement has a clear impact on band nonparabolicity.

The Holstein model often serves as an archetype for electron-phonon interactions and polaron formation in solids. However, precise descriptions of the Holstein polaron are difficult when the phonon frequency is small and the electron-phonon coupling is strong, due to the presence of many phonons in the ground state. We present a semi-analytical approximation that consists of a variational ansatz with clouds of phonons surrounding the electron in the form of coherent states. This becomes particularly simple and exact in the Lang-Firsov limit. We determine the domain of validity away from this limit, and further explore the improvement achieved with a removal of the requirement that the phonon clouds form coherent states. Both approximations work extremely well for the ground-state energy at strong coupling, and both work surprisingly well also at weak coupling. For the effective mass, however, both approximations have difficulty, particularly in the crossover region. Moreover, the coherent-state ansatz retains an unphysical jump in the crossover region. Nonetheless, the coherent-state ansatz provides a simple and intuitive picture of the polaron ground-state wavefunction, and in addition predicts accurate values for the ground-state energy.

Spin defects in diamond are promising platforms for quantum sensing. The longest electron spin relaxation times ($T_1$) at room temperature for solid-state defects are observed in nitrogen vacancy centers in diamond, which can reach 6.67 ms, and substitutional nitrogen ("P1 centers") in diamond, which exhibit a $T_1$ of 2 ms. No other solid-state defect has exhibited millisecond-scale spin relaxation times at room temperature thus far. Here, we characterize the spin properties of the WAR5 defect in diamond with pulsed electron spin resonance. The observed $T_1$ is one of the longest for solid-state spin defects: 0.97(27) ms at room temperature and 14.38(19) min at 4 K. The observed coherence time ($T_2$) is 246(7) $\mu$s, which can be extended to 6.49(34) ms at 4 K with dynamical decoupling. Furthermore, we demonstrate optical spin polarization with a range of wavelengths from 405 nm to 500 nm and propose potential zero-phonon line candidates.

Uranium dioxide (UO2) is a prototypical nuclear fuel material, yet predicting its thermophysical properties across a wide temperature range remains challenging. One factor contributing to this difficulty is the complex magnetic ordering at low temperatures, where spin-orbit coupling produces strong coupling between spin and lattice degrees of freedom. Direct DFT simulations of magnetic phase transitions at finite temperatures are computationally prohibitive. Here, we develop a spin neural network potential (SpinNNP) that explicitly incorporates spin degrees of freedom together with spin-orbit coupling to describe the magnetic states of UO2.Reference datasets were generated using magnetic constrained DFT+U calculations with spin-orbit coupling, covering a wide range of non-collinear spin configurations. The SpinNNP accurately reproduces DFT energies, atomic forces, spin forces, and lattice constants. Machine learning molecular dynamics simulations with spin dynamics successfully capture the antiferromagnetic-paramagnetic transition. Although the predicted magnetic ground state differs from experiment due to known limitations of the underlying DFT description, the transition temperature obtained is of the correct order of magnitude compared with experiment. These results demonstrate that machine-learning potentials can enable large-scale spin-lattice simulations of actinide oxides and provide a practical route toward predictive modeling of complex magnetic materials.

In the context of hybrid superconductor-semiconductor systems, Josephson junctions based on two-dimensional materials, such as graphene, offer promising opportunities because of their scalability and gate-tunable electronic properties. In this work, we investigate the inductive coupling between a quantum LC resonator and a superconducting loop embedding a short, ballistic, planar Josephson junction, with the graphene-based case as a representative example. Within a mean-field formalism, we analyze how the properties of the global system depend on the light-matter interaction coupling, the Fermi level of the two-dimensional material, and temperature. Our findings reveal that the current-phase relation can show features indicative of spontaneous time-reversal symmetry breaking. Furthermore, starting from the mean-field theory, we determine the low-energy spectrum of collective hybridized light-matter excitations.

Collective motion in animals and cells often exhibits rapid reorientations and scale-free velocity correlations. This allows information to spread rapidly through the group, allowing an adequate collective response to environmental changes and threats such as predators. To explain this phenomenon, we introduce a simple, biologically plausible mechanism: a minority-triggered reorientation rule. When local order is high, agents sometimes follow a strongly deviating neighbor instead of the majority. This rule qualitatively changes the macroscopic system behavior compared to traditional flocking models, as it generates heavy-tailed cascades of reorientations over broad parameter ranges. Our mechanism preserves cohesion while markedly enhancing collective responsiveness because localized directional cues elicit amplified group-level reorientation. Our results provide a parsimonious, biologically interpretable route to critical-like fluctuations and high responsiveness during flocking.

Collective temporal organization in complex systems is commonly attributed to synchronization, resonance, or proximity to dynamical instabilities. Here we identify a distinct mechanism by which coherent, synchronization-like behavior can emerge in stochastic systems that are linearly stable and contain no intrinsic oscillators. The mechanism arises from non-normal pseudospectral amplification and leads to what we term pseudo-coherence: an intermittent form of collective organization characterized by transient phase alignment, broken time-reversal symmetry, positive entropy production, and drifting spectral peaks. Using a minimal overdamped stochastic model, we show that increasing non-normality drives a sharp pseudo-critical transition. Beyond a well-defined threshold, fluctuations concentrate along a dominant reaction mode, generating intermittent growth of Kuramoto-like order parameters and irreversible probability currents without eigenvalue crossings or Hopf bifurcations. Analytically, we demonstrate that pseudo-critical non-normal dynamics reshapes the imaginary pseudospectrum, amplifying slow fluctuations and producing coherent frequency bands under finite-time observation. These results identify pseudo-coherence as a new route to collective temporal organization in non-equilibrium systems, suggesting that apparent rhythms and synchronization in natural systems may arise from non-normal stochastic amplification rather than intrinsic oscillators.

Here we develop a formalism for reversible ionic aggregation kinetics in an example concentrated electrolyte, building on previous equilibrium work of McEldrew and co-workers, and thermoreversible polymers and patchy particle systems. This is achieved through solving a macroscopic rate equation of open/occupied association sites, shown to be a solution of the reversible Smoluchowski aggregation equation, which predicts how ionic associations in electrolytes change subject to a step-change in conditions. We test the derived equations against atomistic molecular dynamics simulations of a salt-in-ionic liquid, where good qualitative agreement is obtained, but quantitative differences are found. This highlights the multiple time scales that exist in concentrated electrolytes, with a fast timescale preceding a longer timescale. We hope this formalism opens new avenues in understanding the dynamics and non-equilibrium behaviour in electrolytes. For example, the formalism can be developed further to investigate the non-Newtonian behaviour of concentrated electrolytes, double layer charging, and the slow dynamics of these electrolytes in confinement.

We extend the statistical field-theoretical framework of rough surface contact mechanics to characterize the interfacial gap between an elastic half-space and a randomly rough surface incorporating exponential repulsion. Building upon a cumulant expansion to second-order, we derive an explicit analytical relation between the mean gap and the applied normal pressure. This result provides a closed-form expression for the drift and diffusion coefficients in a convection-diffusion equation governing the scale-dependent evolution of the gap distribution. Solving this equation with appropriate initial and boundary conditions yields the gap distribution under varying external pressures. Both the mean gap and the gap distribution are found to be in good agreement with Green's function molecular dynamics (GFMD) simulations. Our results demonstrate that the field-theoretical approach enables quantitative predictions not only for contact stresses but also for interfacial gap in rough surface contacts.

The localization transition in the Hermitian Aubry-André model is known to have a clear classical origin, with the critical point being exactly predictable from an analysis of classical phase-space trajectories. Motivated by this correspondence, we investigate whether a similar classical origin exists for localization transitions in non-Hermitian quasiperiodic Hamiltonians. Using semiclassical Husimi dynamics together with a detailed phase-space stability analysis, we show that localization transitions persist even in the semiclassical limit of such non-Hermitian models. However, in sharp contrast to the Hermitian Aubry-André case, the transition point inferred from classical phase-space analysis does not coincide with the quantum critical point. Instead, we find that the semiclassical transition depends sensitively on the choice of the irrational parameter defining the quasiperiodic potential, indicating the absence of a universal classical-quantum correspondence for the localization transition in the non-Hermitian setting. Nonetheless, we identify a suitable parameter regime in which the classical dynamics can faithfully mimic the quantum dynamics over a finite but appreciable time window.

Unlike conventional approaches where topological order is statically fixed post-synthesis, we demonstrate that a single external knob-strain-can independently modulate topological order and functional responses in the Tc-adsorbed penta-hexa silicene (Tc_PH-Si) monolayer, with both properties governed by a single microscopic mechanism: momentum-space orbital-selective engineering of Tc-dxz_Si-px hybridization. Combining first-principles calculations and tight-binding models, we show that biaxial strain drives a complete topological pathway: C=1 (0) to C=0 (-2) to C = -1 (-3 to -4) to C = 0 metallic state (-6). This is exemplified by two pivotal states: a topologically critical point yet functionally optimal state at -2 strain (C=0) hosting a direct bandgap (0.17 eV) and d11 = 8.34 pm_V, and a topologically nontrivial but equally optimal state at -4 strain (C = -1) with d11 = 11.01 pm_V-three times that of MoS2. Berry curvature analysis reveals that functionality arises from local orbital hybridization strength, while topology originates from its global phase distribution. This establishes a new paradigm for materials design, transforming static functional materials into dynamically tunable quantum platforms.

Quantum measurement is a dynamical process of an apparatus coupled to a test system. Ideal measurement of the $z$-component of a spin-$\frac{1}{2}$ ($s_z=\pm\frac{1}{2}$) has been modeled by the Curie-Weiss model for quantum measurement. Recently, the model was generalized to higher spin and the thermodynamics was solved. Here the dynamics is considered. To this end, the dynamics for spin-$\frac{1}{2}$ case are cast in general notation. The dynamics of the measurement of the $z$-component of a spin-1 ($s_z=0,\pm 1$) are solved in detail and evaluated numerically. Energy costs of the measurement, which are macroscopic, are evaluated. Generalization to higher spin is straightforward.

We study the dynamic equilibrium between trions and excitons in monolayers of transition metal dichalcogenides in the presence of resident charge carriers and continuous photogeneration of excitons. We show that heating of the system via Drude absorption of low-frequency radiation leads to bistability of the steady-state equilibrium. The first is a low-temperature state, in which almost all resident charge carriers are bound into trions. The second state occurs at high temperatures, where most trions are dissociated; in this regime, the heating is more efficient due to the higher Drude conductivity of unbound charge carriers compared to trions. Switching between these two states occurs on a timescale of tens to hundreds of picoseconds and is accompanied by a jump in various observables such as temperature, current, and the intensity of exciton or trion luminescence.

Conventional heat engines typically require two distinct thermal reservoirs, with their efficiency strictly bounded by the Carnot limit. We present a theoretical design for a phase-change heat engine that utilizes water as the working fluid undergoing state transitions within geometry-constrained flow paths. The proposed cycle operates under a micro-temperature difference (1–2\,$^\circ$C) and relies on liquid-only compression. The system harvests thermal energy via an ambient micro-temperature difference relative to the environment ($q_{\mathrm{in}} \approx 8.37\,\mathrm{kJ}/\mathrm{kg}$ at 24–26\,$^\circ$C). Expansion work is recovered from the enthalpy drop during flash evaporation. Comprehensive numerical analysis using NIST property data confirms that, in the reversible limit, the cycle yields positive net work while maintaining standard thermodynamic consistency. This study illustrates the theoretical potential for ambient energy harvesting via low-pressure phase change, although the extremely small work output per cycle suggests that hardware realization will require exceptional mechanical precision to overcome parasitic losses.

By means of path integral- Monte Carlo, we study the finite-temperature behavior of the extended Bose-Hubbard model with cavity-mediated long-range interactions at unit filling. At zero temperature, the system supports superfluid, Mott-insulating, supersolid, and charge-density-wave phases, with a strongly first-order transition between superfluid and charge density wave states characterized by a broad coexistence region. Focusing on this coexistence regime, we explore how the dominant order evolves with temperature. When the system is initialized in a superfluid state, the superfluid density is progressively suppressed upon heating, and a normal fluid is stabilized. Upon further increasing the temperature, a thermally assisted emergence of crystalline order occurs which eventually melts into the normal fluid. In contrast, simulations initialized in a charge-density-wave configuration display a smooth thermal melting of density order, with no reemergence of superfluid coherence. Overall, our results show that metastability persists at low temperatures, but ultimately disappears at higher temperatures, where thermally induced crystallization takes place.