Materials science, superconductivity, mesoscale physics, and quantum materials
Autoregressive generative models -- including Transformers, recurrent neural networks, classical Kalman filters, state space models, and Mamba -- all generate sequences by sampling each output from a deterministic summary of the past, producing genuinely non-Markovian observed processes. We develop a general theoretical framework based on stochastic thermodynamics for this class of architectures and introduce the entropy production, which can be efficiently estimated from sampled trajectories without exponential sampling cost despite the non-Markovian nature of the observed dynamics. As a proof-of-concept experiment for a large language model (LLM), we evaluate the token-level and sentence-level entropy production for a pre-trained Transformer-based model, GPT-2. We also demonstrate the framework in the linear Gaussian case, where the model reduces to the Kalman innovation representation and the entropy production admits an analytical expression. We further show that the entropy production decomposes exactly into non-negative per-step contributions in terms of retrospective inference, and each of those terms further splits into information-theoretically meaningful terms: a compression loss and a model mismatch. Our results establish a bridge between stochastic thermodynamics and modern generative models, and provide a starting point for quantifying irreversibility in a broad class of highly non-Markovian processes such as LLMs.
The Boltzmann-Loschmidt dispute of 1876 questioned the possibility of a statistical irreversible description by time reversible classical equations of motion of atoms. Here we show analytically and numerically that the quantum chaos diffusion of cold atoms, or ions, in a harmonic trap and pulsed optical lattice can be inverted back in time with up to 100\% efficiency. This is in sharp contrast to classical evolution where exponentially small errors break time reversibility. We argue that the existing experimental skills allow highlighting the Boltzmann-Loschmidt dispute from a quantum perspective.
2604.04778We present QCommute, a software tool implemented in C++ for symbolic computation of nested commutators between a Hamiltonian and local observables in quantum many-body spin-1/2 systems on one-, two-, and three-dimensional hypercubic lattices. The computation is performed algebraically directly in the thermodynamic limit, and the Hamiltonian parameters are kept symbolic. Importantly, this way the entire parameter space is covered in a single run. The implementation supports extensive parallelization to achieve high computational performance. QCommute enables the investigation of quantum dynamics in strongly correlated regimes that are inaccessible to perturbative approaches, either through direct Taylor expansion in time or via advanced techniques such as the recursion method.
Stochastic resetting has emerged as a powerful mechanism for driving systems into nonequilibrium stationary states with tunable properties. While most existing studies focus on global resetting, where all degrees of freedom are simultaneously reset, recent work has shown that resetting only a subset of degrees of freedom (subsystem resetting) can qualitatively alter collective behavior in interacting many-body systems. In this work, we develop a general theoretical framework for analysing subsystem resetting in Kuramoto-type coupled-oscillator systems. Building on a continued-fraction approach, we derive self-consistent equations for the stationary-state order parameter of the non-reset subsystem, applicable to both noisy and noiseless dynamics and to models with arbitrary interaction harmonics. Using this framework, we systematically investigate how the stationary state and phase transitions depend on the resetting rate, the size of the reset subsystem, and the reset configuration. We show that subsystem resetting can shift or even suppress synchronization transitions, and can give rise to nontrivial features such as re-entrant behavior and restructuring of phase boundaries. In specific cases, including the noiseless Kuramoto model with a Lorentzian frequency distribution, our results recover known analytical predictions and extend them to more general settings. These results establish subsystem resetting as a versatile control protocol for engineering collective dynamics in nonequilibrium interacting systems.
Two-dimensional (2D) ferromagnetic materials with high Curie temperature ($T_{\rm c}$) and large magnetic anisotropy energy (MAE) are critical for nanoscale spintronics but remain rare. We propose, via first-principles calculations, that adsorbing alkali atoms ($A$ = Li, Na, K, Rb, Cs) onto a tetragonal CoSe monolayer transforms it into a series of stable 2D ferromagnetic metals, $A$CoSe, with an in-plane easy axis. Notably, LiCoSe is a half-metal. These functionalized monolayers exhibit dramatically enhanced ferromagnetism compared to the pristine layer, with $T_{\rm c}$ > 300 K and MAE > 800 $μ$eV/Co. The coupled alkali atoms amplify the local magnetic moment of Co ions, reinforce ferromagnetic Ruderman-Kittel-Kasuya-Yosida (RKKY) and superexchange couplings, and concurrently weaken the direct antiferromagnetic exchange between Co ions. Furthermore, tensile strain can further elevate the MAE (via band shifting) and increase $T_{c}$ (by strengthening the nearest-neighbor exchange $J_1$). Among them, NaCoSe exhibits the highest MAE and excellent strain-modulated $T_{c}$, rendering it the most promising candidate material. Our results establish alkali-metal decoration as an effective strategy for realizing 2D ferromagnets with high $T_{\rm c}$ and large MAE in tetragonal lattices.
Heat engines that convert thermal energy into work are a cornerstone of classical thermodynamics and remain an active area of contemporary research. Notable examples include microscopic heat engines, trade-off relations between power and efficiency, and the attainability of Carnot efficiency at finite power. We propose a cyclic heat engine based on the Ising model, in which the thermodynamic cycle involves variations of both temperature and magnetic field. We analyze the one-dimensional and mean-field Ising models, which allow for simple analytical results and provide new insight into the role of interactions in cyclic heat engines. In particular, we show that interactions can enhance both power and efficiency. Moreover, a system that does not operate as an engine in the absence of interactions can become an engine upon tuning the interaction strength. The mean-field model enables us to investigate the relevance of the phase transition for the performance of this Ising heat engine. Owing to the emergence of spontaneous magnetization, the mean-field model can still operate as an engine even when one of the magnetic fields is set to zero. Remarkably, when the work is maximized, we find that the optimal parameters are numerically consistent with this regime, in which one magnetic field vanishes and the cycle explores the phase transition. We also consider an alternative cycle for the mean-field model, obtained by varying the interaction strength while keeping both temperatures below the critical temperature and setting the magnetic field to zero throughout the cycle. The power and efficiency of this cycle are analyzed as well. Finally, while our analytical results are valid for the limit of large period we use numerical simulations for finite periods and show that the power decreases monotonically with the period.
This work presents a comprehensive benchmark and validation of a recently proposed method called Effective Bethe Ansatz (EBA). It is a variational method that deforms the exact Bethe wavefunctions of one-dimensional spin chains at integrable points to approximate non-integrable systems. We apply this method to the non-integrable regime of the spin-1 bilinear-biquadratic chain. By performing EBA method starting from the two integrable endpoints, the Takhtajan-Babujian point and the Lai-Sutherland point, we systematically evaluate the accuracy of the EBA for the ground state and first excited state. Our validation is based on a direct comparison with exact diagonalization, assessing energy, fidelity, and entanglement entropy. The results confirm that the EBA provides a physically accurate description near integrability, with fidelity decreasing controllably as the perturbation increases. The method successfully captures key finite-size effects, such as level crossings, manifested as sharp drops in fidelity, and provides a probe to potential phase transitions. This study establishes the EBA as a reliable and efficient semi-analytical tool, clarifying its scope and limitations for studying low-energy physics in non-integrable quantum spin chains.
We propose an effective Bethe ansatz for solving quantum many-body systems near an integrable point. Our approach retains the functional form of the Bethe wave function while renormalizing the Bethe roots to account for integrability-breaking interactions. These effective roots are determined by minimizing physically motivated cost functions. The resulting off-shell Bethe states serve as approximate eigenstates of the non-integrable models. We assess the quality of the approximation using various physical observables, including the energy eigenvalue, state fidelity, and bipartite entanglement entropy. Our tests show that for models with weak integrability-breaking, the effective Bethe ansatz provides a high-quality approximation to the exact eigenstates over a wide range of deformation parameters. In contrast, for models with strong integrability-breaking interactions, the efficacy of the effective Bethe ansatz degrades relatively quickly as the deformation parameter increases. The efficacy of the method thus offers a useful probe for characterizing the strength of integrability breaking. Within its regime of accuracy, it also provides a new representation of the eigenstates of nearly integrable models, enabling one to exploit the algebraic structure inherited from integrability.
Microscopic heat engines operate in regimes where thermodynamic quantities fluctuate strongly, making stochastic effects an essential aspect of their performance. However, existing geometric formulations of finite-time thermodynamics primarily characterize average dissipation and do not systematically capture its fluctuations. Here, we develop a unified geometric framework that consistently describes both the mean dissipated availability and its fluctuations. In the linear-response regime, we show that these quantities are governed by metric tensors constructed from equilibrium correlation functions, providing a common geometric structure for dissipation and its fluctuations. This framework yields geometric bounds on both the mean and variance of the dissipated availability, and thereby on the efficiency and its fluctuations. The formalism applies broadly to stochastic systems, including Markov jump processes and overdamped and underdamped Brownian dynamics, establishing a unified geometric description across microscopic heat engines.
We study the large deviations of the time-integrated current for a self-propelled particle moving within a confined environment. The dynamics is modeled as a semi-Markovian process, where the transitions between a \textit{normal running phase} (Phase $0$) and a \textit{wall-attached phase} (Phase $1$) are governed by time-dependent reset probabilities. We study two different examples: In the first case, the particle undergoes a biased random walk in Phase $0$, while it intermittently resets and interacts with the container boundaries, remaining stationary in Phase $1$. In this scenario, the reset probabilities for transitions between the two phases follow an ``aging'' logic. In the second case, the particle alternates between two active phases: a Markovian Phase $0$ characterized by memoryless, downstream-biased motion, and a semi-Markovian Phase $1$ with a reversed, upstream bias representing boundary-attached navigation. Here, we assume a time-independent survival probability in Phase $0$ and a time-dependent one in Phase $1$. By analyzing the Scaled Cumulant Generating Function (SCGF) in the long-time limit, we derive the conditions for Dynamical Phase Transition (DPT)s in the fluctuations of the particle velocity. We demonstrate that, depending on the aging strength, the system exhibits either discontinuous (first-order) or continuous (second-order) DPTs. Analytical predictions are validated via computer simulations.
Yttrium iron garnet (Y3Fe5O12) is a prototypical ferrimagnetic insulator widely used in spin-wave and magnonic devices owing to its extremely low magnetic damping and long magnon propagation length, and recent experiments suggest that lattice vibrations can influence magnetic properties, motivating a microscopic understanding of how phonons modify exchange interactions. In this work, phonon-driven tuning of exchange interactions in Y3Fe5O12 is investigated from a mode-resolved perspective based on first-principles calculations. We focus on how optical phonons modify the dominant superexchange pathways and how lattice distortions affect the Fe-O-Fe bond geometry that governs the exchange interaction. To this end, phonon modes are computed from density functional theory, and the exchange interactions are evaluated from a Wannier-based tight-binding model and mapped onto a spin Hamiltonian, while displaced structures along individual infrared-active modes are used to quantify their impact on the magnetic interactions.
We study nonreciprocal current response in noncentrosymmetric crystals under time-reversal symmetry. We show that the nonreciprocal current appears in a dissipative system through interband processes. The nonreciprocal current is inversely proportional to the lifetime $τ$ and has a close relationship to the geometric quantity called the shift vector. The current mechanism is suitable for minigap systems where the energy gap and relaxation strength are comparable. We present a numerical simulation of the nonreciprocal current in the one-dimensional Rice--Mele model.
In this work, we investigate the collective electrostatic effects of one-dimensional (1D) Janus MoSTe nanotubes and their impacts on the band alignment of nanotube heterostructures. Using first-principles calculations based on Density Functional Theory, we find that the Janus nanotube generates a large and uniform electrostatic potential of over 1.3 V within the nanotube pores, which is accumulative for double wall nanotubes. We develop an analytical model to provide a quantitative understanding of the electrostatic potential and its dependence on the quadrupole moment and nanotube radius. For double wall MoSTe nanotube, we find a substantial band edge shift of about 1.0 eV for the inner tube originated from the electrostatic effects, leading to a type-II band alignment. These results demonstrate that the electrostatic effects of 1D nanotubes can be used to tune the electronic properties and band alignment of 1D nanotube heterostructures for optoelectronic and catalytic applications.
We develop a self-contained theoretical framework that classifies the topological phases and critical phenomena of classical pyrochlore magnets with arbitrary spin $S$, subject to competing exchange and single-ion anisotropies. In the small-$w$ regime, where the single-ion term favors low spin amplitudes, exact dualities reveal a dichotomy: integer spins exhibit a continuous 3D $XY$ deconfinement transition, whereas half-integer spins remain in a $U(1)$ Coulomb liquid without any transition. In the large-$w$ regime, where the local spin amplitudes are maximized ($|S^z| = S$), the macroscopic flux is quantized to multiples of $2S$. By mapping the defect structure to topological loop gases, we prove that the compatibility between the physical ice rule and the emergent $\mathbb{Z}_{2S}$ flux conservation holds if and only if $S \le 3/2$. For $S=3/2$, this maps the system to the 3-state Potts model, whose symmetry-allowed cubic invariant drives a first-order transition. For $S \ge 2$, monopole contamination breaks the discrete clock mapping. Using an exact decomposition of the partition function, we show that the hierarchical string fusion cascade exponentially suppresses the discrete perturbations, which act as a dangerously irrelevant operator at the 3D $XY$ fixed point, protecting 3D $XY$ criticality. Finally, incorporating thermal monopoles, we show that they act as a symmetry-breaking effective magnetic field that severs defect strings. Consequently, the continuous transitions are rounded into crossovers, whereas the first-order $S=3/2$ transition is predicted to survive at finite temperatures, terminating at a critical endpoint. Classical Monte Carlo simulations for $S$ up to $7/2$ corroborate these analytical predictions.
We predict ultrafast switching in a chiral anti-ferromagnet that occurs at femtosecond times, nearly 5 orders of magnitude faster than the torque induced nanosecond switching previously observed. The physical mechanism, quite different from that which drives slow switching, involves the creation of massive effective magnetic fields by ultrafast spin current injection. Identifying these fields as key to femtosecond rotation, we establish simple practical rules for their maximisation with wide applicability to all magnetised materials. Employing state-of-the-art time-dependent density-functional theory and using the example of chiral magnet, Mn$_3$Sn, we induce ultrafast rotation enough to drive the switching of magnetic order between the six possible non-collinear ground states. We further demonstrate the possibility of undoing this switching by subsequent injection of oppositely polarized spin current. Our findings place chiral anti-ferromagnets as a materials platform for femtosecond Néel-vector switching, opening a route towards the manipulation of magnetic matter at ultrafast times.
Continual learning in artificial neural networks is fundamentally limited by the stability--plasticity dilemma: systems that retain prior knowledge tend to resist acquiring new knowledge, and vice versa. Existing approaches, most notably elastic weight consolidation~(EWC), address this empirically without a physical account of why plasticity eventually collapses as tasks accumulate. Separately, the distinction between sudden insight and gradual skill acquisition through repetitive practice has lacked a unified theoretical description. Here, we show that both problems admit a common resolution within non-equilibrium statistical physics. We model the state of a learning system as a particle evolving under Langevin dynamics on a double-well energy landscape, with the noise amplitude governed by a time-dependent effective temperature $T(t)$. The probability density obeys a Fokker--Planck equation, and transitions between metastable states are governed by the Kramers escape rate $k = (ω_0ω_b/2π)\,e^{-ΔE/T}$. We make two contributions. First, we identify the EWC penalty term as an energy barrier whose height grows linearly with the number of accumulated tasks, yielding an exponential collapse of the transition rate predicted analytically and confirmed numerically. Second, we show that insight and repetitive learning correspond to two qualitatively distinct temperature protocols within the same Fokker--Planck equation: insight events produce transient spikes in $T(t)$ that drive rapid barrier crossing, whereas repetitive practice operates at a modestly elevated but fixed temperature, achieving transitions through sustained stochastic diffusion. These results establish a physically grounded framework for understanding plasticity and its failure in continual learning systems, and suggest principled design criteria for adaptive noise schedules in artificial intelligence.
A two dimensional ferromagnetic XY model with its bound vortex-antivortex dominated quasi long range ordered phase at low temperatures is a long standing as well as well studied problem of interest in the field of condensed matter. We conduct a detailed Monte Carlo study of such model with rather unexplored extensions where additional anisotropic exchange coupling and Dzyaloshinskii-Moriya interactions (DMI) together affect the Kosterlitz-Thoulass (KT) transition in presence/absence of symmetry breaking fields. Without DMI, the exchange term promotes collinear (ferromagnetic) order, whereas the DMI term induces spin cantings. By tuning anisotropy upto Ising limit, we document energy, specific-heat, magnetizations as well as helicity modulus and vortex densities for different tempeatures and DMI strength. We also compute the 2nd moment of correlation lengths in order to probe the spatial correlation of the spins. Furthermore, the effect of U(1) symmetry breaking 4-fold and 8-fold symmetric h4 and h8 fields are explored which shows how the double-peaked specific heat profiles changes in presence of DMI. Overall, our findings append many important updates in the low temperature phases of a topological XY ferromagnet when additional DMI and isotropy-breaking exchange and/or field terms are considered and thus providing a practical blueprint for suitably engineering topological spin systems.
Recently, studies have explored the statistics of matrix elements of local operators in the Lieb-Liniger model. It was found that the probability distribution function for off-diagonal matrix elements $\langle \boldsymbolμ|\mathcal{O}|\boldsymbolλ \rangle$ within the same macro-state is well described by the Fréchet distributions. This represents a significant development for the Eigenstate Thermalization Hypothesis (ETH). In this paper, we investigate a similar phenomenon in another solvable model: the disorder-free Sachdev-Ye-Kitaev (SYK) model. The Hamiltonian of this model consists of 4-body interactions of Majorana fermions. Unlike the conventional SYK model, the coupling strengths in this model are fixed to a constant, earning it the name ``disorder-free.'' We evaluate the matrix elements of operators constructed from products of $n$ Majorana fermions: $\mathcal{O} = χ_{a_1}χ_{a_2}\ldots χ_{a_n}$. For a general choice of indices and $n \geq 4$, we find that the statistics of the off-diagonal matrix elements are well-fitted by a generalized inverse Gaussian distribution rather than Fréchet distributions.
Understanding the realization of thermal equilibrium through the thermalization process in a many-body system is a fundamental and complex scientific question, bridging thermodynamics and classical dynamics and connecting to a host of physical phenomena, such as mechanical instabilities in a thermal environment. In this work, based on the harmonic lattice model, we investigate the thermalization process in both velocity and coordinate spaces, by examining microscopic dynamics on the atomic level. We show the distinct relaxation rates of the transverse and longitudinal components of the velocity, reveal the power law governing the nonlinear proliferation of dominant frequencies, and observe the concurrent rapid proliferations of frequencies and topological defects. We also show that the lattice system's persistent out-of-plane deformations exhibit two-stage fluctuation behaviors, characterized by distinct power laws of fractional exponents and associated with the broken up-down symmetry. This work demonstrates the rich dynamics underlying the thermalization process, and advances our understanding on the dynamical adaptations of many-body systems to external disturbances.
Classical thermal transport theories that preserve rotational symmetry, predict strong anharmonic scattering of out-of-plane lattice vibrational modes called flexural phonons in flat suspended graphene sheets. Such strong scattering processes cause a breakdown of the phonon quasiparticle picture, which remains valid only when several cycles of lattice vibrations occur before the mode decays. Here we show that the renormalization of elastic bending rigidity ($D$), caused by the coupling between the in-plane and the out-of-plane thermal lattice fluctuations, restores phonon quasiparticles in suspended graphene. Importantly, this $D$-renormalization weakens the momentum-dissipating Umklapp phonon scattering processes, resulting in improved thermal conductivity and amplified phonon hydrodynamics in suspended graphene. Our results unveil a previously-unrecognized connection between the macroscopic elasticity and the microscopic flexural phonon scattering in two-dimensional (2D) materials that does not occur in three-dimensional bulk crystals, thereby motivating a re-examination of the classical theories and opening up new avenues to engineer the thermal as well as the phonon-limited electronic transport and relaxation in two- and lower-dimensional materials.