Papers

Understanding real-time flux-tube dynamics in more than one spatial dimension is key to unlocking the non-perturbative physics of confinement, and is now actively pursued by quantum computing and simulation experiments. However, describing such dynamics has proven to be extremely challenging with both experiments and state-of-the-art numerical simulations limited to small volumes and short timescales. Here we investigate flux tube statics and real-time evolution in a genuine two-dimensional $\mathbb{Z}_2$ Higgs gauge theory at system sizes and timescales order of magnitude beyond present experiments and numerics. The key enabling element is the recently introduced Clifford-augmented matrix product states (CAMPS) framework, which we demonstrate to parametrically reduce the entanglement that must be represented in the matrix product state; both in the pure-gauge limit and in the presence of dynamical matter. We benchmark this capability through stringent tests of effective string theory, including universal spectral features and flux tube roughening properties in presence of matter. We then introduce a string-pull protocol that selectively excites transverse modes and reconstructs their finite-size spectrum in real time. In the rough regime, the response is collective, and our simulations show that this is also well captured by universal effective string theory predictions. Strong confinement instead produces long-lived, lattice-locked local dynamics persisting to times $tJ \gtrsim 100$. These results provide ab initio evidence that effective string theory captures nonequilibrium string dynamics and reveal a hitherto unexplored long-lived prethermal regime of strongly confined flux tubes, providing a novel angle on how confinement dictates dynamics in more than one spatial dimension.

Continuous quantum phase transitions in interacting many-body systems exhibit universal phenomena that are largely independent of microscopic details. An organizing principle distilled from canonical examples such as the magnetic transition in Ising models is that the low-energy physics of transitions between gapped phases is governed by scale-invariant quantum field theories with gapless degrees of freedom at isolated points in momentum space. In this paper, we show that this principle can fail in a radical way: an entire gapless Fermi surface can emerge at a quantum critical point separating two fully gapped insulators. These exotic phase transitions are dubbed metallogenic quantum critical points (MGQCP). We construct a controlled family of effective field theories for MGQCPs between distinct fractional Chern insulators and propose a periodically modulated quantum Hall bilayer as a minimal microscopic setting. The critical theory exhibits an unusual mixture of physical signatures: while transport and compressibility follow scaling laws compatible with a conformal field theory, the electron spectral function develops a power-law non-analyticity at the Fermi momentum, characteristic of non-Fermi-liquid metals. We discuss how the concept of MGQCP may shed new light on critical phenomena in moire materials with tunable Chern bands. More generally, our results point to a broader class of quantum critical phenomena in which extended manifolds of gapless excitations emerge in momentum space despite being absent in both neighboring phases.

The physics of information scrambling in quantum many-body systems is intimately related to thermalisation and emergence of chaos. However, its standard characterisation through bipartite entanglement or operator growth remains inherently coarse-grained, obscuring the spatiotemporal anatomy of how quantum information flows between different regions of the system and across various length scales. In this work, we develop a theory for the dynamics of local information in local random unitary circuits which resolves the fine-grained microscopic structures of local information flow in such systems. Using the framework of information lattice which systematises the information content at each length scale within each subsystem, we identify a distribution of length scales at which information resides and obtain the dynamics of the distribution. For Haar-random circuits with infinite local Hilbert-space dimensions, we map this dynamics onto an exact classical stochastic process which reveals that this distribution is described by a Tracy-Widom form which moves ballistically in time ($ \propto t$) toward larger scales, accompanied by a $\sim t^{1/3}$ broadening. We also find the same qualitative behaviour for random Clifford circuits acting on qubits. The similar scaling behaviour in two rather different settings hints strongly towards the universality of our results. In the case of Clifford circuits, we develop a phenomenological Markov process for the dynamics of the stabiliser generators in a specific gauge which confirms the Tracy-Widom distribution and the $t^{1/3}$ scaling of the fluctuations. Ultimately, our results establish the universal properties of the dynamics of local quantum information in a length scale-resolved fashion and provide a possible route towards bridging exact microscopic theories for information dynamics with emergent hydrodynamic descriptions of information flow.

We investigate bottleneck formation in turbulence using the Voigt-regularised SABRA model and DNS of the corresponding Voigt-Navier-Stokes (NSV) equations. The Voigt regularisation introduces a scale-dependent slowdown of nonlinear interactions without enhancing dissipation, providing a natural setting to study the interplay between nonlinear transfer and thermalised behaviour. We find three distinct spectral regimes: an inertial range at $k<k_I$, an intermediate equilibrium-like range associated with partial thermalisation for $k_I<k<k_{II}$, and a high-$k$ thermal regime for $k>k_{II}$, where the Voigt contribution dominates the conserved invariant. The crossover to the high-$k$ regime occurs at $k_{II}\sim 1/\alpha$, while $k_I$ marks the onset of thermalised behaviour. Equal and multi-time statistics reveal a progressive suppression of intermittency and a tendency towards Gaussianity at small scales, together with a transition from dynamic multiscaling in the turbulent regime to simple scaling in the equilibrium ranges. The shell model resolves these three regimes over a broad range of scales, while DNS of the corresponding NSV equations reproduces the same qualitative trends, including bottleneck formation, delayed cascade completion, reduced intermittency, and a tendency towards Gaussianity at small scales. We find that bottleneck formation might be associated with scale-dependent dynamical slowdown and incipient thermalisation, rather than being purely dissipative in origin. We provide strong evidence that, in the regime where the regularization parameter $\alpha$ is much smaller than the dissipation length scale, the Voigt model reproduces the same inertial-range turbulent regime and turbulence statistics as the Navier-Stokes (NS) equations. This provides evidence that the Voigt model constitutes an excellent practical approximation to the NS equations for small $\alpha$.

The interplay between coherent unitary evolution and environment-induced dissipation can give rise to a wide range of non-equilibrium dynamics in open quantum systems, ranging from interesting transport phenomena to dynamical phase transitions. However, accessing such long-time dynamics remains challenging for the existing methods developed for the simulation of many-body open quantum systems. We address this problem by developing a quantum generating function (QGF) formalism for open many-body systems for both ensemble-averaged dynamics governed by a Markovian quantum master equation and trajectory-resolved dynamics described by the quantum trajectory formalism, including quantum jumps, and quantum state diffusion. Our approach computes the dynamics of higher-order moments and fluctuation statistics without explicitly evolving the quantum state, thereby providing an efficient and scalable approach for investigating many-body open quantum systems. We demonstrate the versatility of the formalism by applying it to both the integrable open XXZ chain and the nonintegrable open next-nearest-neighbor XXZ spin chain, where it uncovers distinct initial state dependent long-time transport regimes. Our work establishes quantum generating functions as an efficient and scalable framework for investigating long-time dynamics in open quantum many-body systems.

Stochastic resetting can localize diffusion and generate nonequilibrium steady states, but the conditions under which spatially dependent resetting produces localization remain unclear. Here, we establish a general classification for diffusion under adaptive resetting, where the resetting rate $r(x)$ depends on position. For rates with the asymptotic scaling $r(x)\sim |x|^\lambda$, we identify a sharp threshold at $\lambda=-2$. For $\lambda>-2$, the steady state is localized and exhibits stretched-exponential tails, whereas for $\lambda<-2$, resetting is asymptotically too weak to localize the particle. Precisely at the marginal scaling $r(x)\sim |x|^{-2}$, a qualitatively new regime emerges: the steady state develops power-law tails with a temperature-dependent exponent and exhibits a finite-temperature delocalization transition. Thus, inverse-square resetting plays the role of the logarithmic potential in equilibrium, establishing a nonequilibrium counterpart of the temperature-driven delocalization seen there.

Active XY models and active surfaces are two paradigmatic nonequilibrium systems with distinct microscopic origins. We show that the hydrodynamic theories for a quenched-disordered nonreciprocal random bond two-dimensional XY model and an inversion-symmetric active surface tangentially advected by quenched velocities are identical. This theory predicts sub-logarithmic phase order in the XY model and sub- or super-logarithmic positional order in the surface for short-range disorder with nonuniversal exponents, which vary continuously with the degree of transversality of the disorder variance. We argue that the nonreciprocal random bond XY model can disorder through vortex proliferation.

Fast and reliable qubit reset is essential for the efficient operation of quantum processors. Among the proposed strategies, Mpemba-effect-based protocols offer a simple route to accelerated relaxation, but provide limited insight into the optimality of the full reset dynamics. Geometric approaches, by contrast, quantify optimality but do not generally suggest practical acceleration protocols. Here, we bridge these perspectives through a geometric analysis of entanglement-assisted qubit reset. We show that entangling operations can redistribute local coherences across a multi-qubit register, allowing the reduced state of each qubit to follow a geodesic path towards the ground state. Remarkably, this locally optimal behaviour can emerge even when the collective evolution becomes suboptimal in the full state space. We illustrate this interplay for different families of initial multi-qubit states. Our results provide a geometric perspective on Mpemba-inspired reset acceleration and clarify when extending two-qubit protocols to larger registers provides a further advantage in the reset process.

In Brownian yet non-Gaussian diffusion (BnGD) the mean squared displacement grows linearly in time. However, the displacement statistics do not follow a normal distribution throughout. Typically, they are non-Gaussian at intermediate times, before they cross over to Gaussian in the long-time regime. We demonstrate that nonlinear friction under correctly applied stochastic equilibrium conditions provides an explanation of this phenomenon also for homogeneous environments.

We show a finite-time Otto-like quantum thermodynamic cycle that preserves the adiabatic population structure of a time-dependent harmonic oscillator in the non-quasi-static regime. In the conventional energy representation, finite-rate driving induces non-adiabatic population redistribution and leaves residual excitations after the Hamiltonian has returned to its initial value. We show that this difficulty can be avoided by formulating the dynamics in the Lewis-Riesenfeld invariant representation, without modifying the physical Hamiltonian through auxiliary counterdiabatic driving. For a parametric Mathieu protocol, quantum inertia produces a mismatch between the spatial width of the working mode and its transient dressed energy scale. We propose an experimental implementation of this scheme in a trapped-ion Paul trap using stimulated Raman interactions, with independent control of the laser detuning and beam intersection angle. This provides a finite-time implementation in which the invariant population structure is preserved while the physical trap frequency evolves non-quasi-statically. Our results establish a clear distinction between adiabatic operation and quasi-static driving, providing a route toward finite-time quantum thermal cycles that retain the adiabatic energy structure without requiring the quasi-static limit.

We study the emptiness formation probability (EFP) in the ground state of the repulsive one-dimensional Lieb-Liniger Bose gas. For a macroscopic empty interval of length $2R$, its leading asymptotic behavior is described by a rate function $f(\gamma_0)$, defined by $-\log P(R)\sim(\rho_0R)^2f(\gamma_0)$, where $\rho_0$ is the mean density and $\gamma_0$ is the dimensionless interaction strength. We propose a parameter-free integral equation for $f(\gamma_0)$. Starting from the exact dual-field Fredholm-determinant representation of the EFP, we show how the conjectured kernel arises formally and identify the uniform asymptotic statement that remains to be proven for a rigorous derivation. The conjecture reproduces the Tonks-Girardeau and weak-coupling limits, as well as the first correction obtained independently in both limits. It also agrees at the few-percent level with numerical minimization of the Lieb-Liniger hydrodynamic action over more than four orders of magnitude in coupling. The numerical calculation yields the corresponding emptiness instantons and their astroid-like vacuum regions.

Non-equilibrium steady states (NESSs) generally lack thermodynamic occupation laws because finite stationary circulation and a globally exact rate-ratio field cannot coexist for the same Markov generator. Here we construct a sector-separated geometry that overcomes this incompatibility without arresting dissipation. Entropy-production exposure-and-separation excludes the entropy-producing state~$0$ from the conditional occupation manifold while retaining it in the dissipative full graph; physical returns $i\to0\to0^\ast$ become effectively Markovian in the strong-bias/rapid-reset (SR) limit. For a thermodynamically complete conditional manifold, autonomous redistribution (AR) eliminates residual futile circulation, making the rate-ratio one-form exact. Thermodynamic calibration gives $X_i=\beta(\Delta\mu- \mathcal F_i^{\mathrm{cost}})$ and $p_i=e^{X_i}/Z_\mathcal{C}$, with $Z_\mathcal{C}=1+\sum_i e^{X_i}$. Full-graph probabilities factorize exactly as $P_\alpha=(1-P_0)p_\alpha$. In the SR limit, the kinetic factor tends to unity while $p_\alpha\to e^{X_\alpha}/Z_\mathcal C$, yielding $P_\alpha\to p_\alpha$ while finite dissipation persists. Near AR, integrability is lost linearly in residual cycle current whereas dissipation begins quadratically. In the binary zero-cycle-rank limit, occupation redistributes autonomously under maintained $\Delta\mu$ bias, yielding the inverted Fermi–Dirac law, which is applied to thermal smearing in quantum-dot lasers. The framework provides constructive acquisition conditions and failure diagnostics for thermodynamic occupation laws in dissipative NESSs.

Dark matter halos, which host galaxies and galaxy clusters, have peculiar velocities far from thermal equilibrium. Characterizing the nonlinear and non-Gaussian features of this velocity distribution improves our understanding of the gravitational evolution of the cosmic web and supports related cosmological applications. We endeavor to establish a connection between the peculiar velocity distribution of halos and nonequilibrium statistical mechanics, with the objective of obtaining a model that is both concise and accurate for practical applications. We extracted halo samples from large N-body simulations and performed maximum-likelihood fits to the peculiar velocity distributions using a two-parameter Tsallis model, derived from non-extensive statistical mechanics. On the theoretical side, we reformulated the halo distribution in the superstatistics framework by means of a generalized Gram-Charlier expansion based on the gamma distribution. For halo peculiar velocities below 1000 km/s, the Tsallis model achieves 5 percent accuracy over z=0-2, with performance improving toward lower redshifts. Our results show that the halo velocity distribution becomes increasingly non-Gaussian and departs further from equilibrium over time. The best-fit parameters depend only weakly on mass, though low-mass halos exhibit slightly stronger non-Gaussianity. The two parameters, especially the velocity dispersion, offer promising probes of cosmological parameters. Theoretically, we find that in general the halo peculiar velocity distribution function is expressible as a superposition of a series of Tsallis distribution functions, while simulation results demonstrate that the zeroth-order approximation, namely a single Tsallis function, already achieves sufficient accuracy.

A looped transformer performs inference by iterating a weight-tied map, making its computation a dynamical process whose cost is set by the resulting inference dynamics. Here we show that networks with identical architecture and objective, trained to identical accuracy, nevertheless realize distinct dynamical phases depending strongly on initialization, and that the bifurcation defining each phase determines how test-time compute scales. The phases are distinguished by their bifurcation mechanisms, including a saddle-node fold and a Neimark-Sacker-type transition to bounded nonstationary motion. In the fold phase, a one-dimensional normal-form reduction predicts both the relaxation-time and spectral-gap amplitudes from local derivatives of the trained map, yielding the parameter-free relation $\tau(\varepsilon)[1-\lambda_{\max}(-\varepsilon)]\to\pi$. Composed with a regular distribution of problem difficulty, the same critical slowing down produces the workload-level tail $P(\tau>N)\sim N^{-2}$. In the Neimark–Sacker phase, the fold scaling law disappears rather than merely changing its prefactor. Thus, test-time compute is not determined by architecture alone. It is governed by the dynamical phase of the solution found by training.

We investigate random recursive simplicial complexes growing by adding, at each step, a vertex together with a simplex formed by joining the new vertex with a randomly chosen existing simplex. We also add all faces of the new simplex to ensure that the resulting object remains a simplicial complex. If the choice of an existing simplex is uniform among simplices of dimension $<m$, the number $S_d$ of simplices of any admissible dimension $d\leq m$ is an asymptotically self-averaging random variable. This feature allows us to determine the asymptotic growth law of the average of $S_d$ when the number of vertices diverges. We also probe the degree distribution, examine the probabilities of various extreme outcomes, and analyze the characteristics of the first vertex.

In swollen elastomers, elasticity can arrest macroscopic demixing between the polymer network and the solvent, producing stable domains of finite size. While previous theories have focused on isotropically swollen elastomers, anisotropy strongly influences the phase behavior of many related systems, such as gels and crosslinked polymer blends. Building on the approach developed in Part I of this two-part paper, we investigate the effects of two experimentally induced sources of anisotropy: uniaxial swelling and stiffness gradients. We show that uniaxial swelling can lead to the formation of stable lamellar microphases and modify phase behavior, while stiffness gradients can cause spatial variations in the characteristic microphase size.

Complex hypergraphs (chygraphs) contain graphs, hypergraphs, multiplex and interacting networks as special cases, and the percolation threshold of all of them follows from one symbolic calculation: the spectrum of a tensor $A$ built from four matrices of first moments. That calculation stops at the threshold. Here I show that $A$ is the Jacobian, at its trivial fixed point, of a non-linear self-consistency map whose non-trivial fixed point is the giant component fraction, so threshold and order parameter are two orders of one object on one index set. Carrying the expansion one order further gives the critical amplitude $B$ in $S=B\Lambda+O(\Lambda^2)$ in closed form, and exposes a hierarchy: first moments fix the threshold, second moments the amplitude, and only the generating functions themselves the order parameter away from it. Dropping the assumption that a complex's participation in different layers is independent generalises the tensor again, replacing unconditional first moments by inclusion-biased second moments: distributions with identical marginals have different thresholds and different order parameters. Six constructions from the literature are then solved by substitution, among them AND- against OR-logic hypergraph percolation, which share a chygraph and differ in one generating function, and SIR epidemics with two levels of mixing, whose household reproduction number falls out of the tensor. A reported failure of mean-field theory on strongly clustered graphs is shown to be a failure of applying it to the wrong object: mapped onto the treelike backbone rather than the clustered graph, the same calculation reproduces the exact threshold, order parameter and critical exponents. Everything is implemented in one class, in which a chygraph is specified once by its generating functions and then returns all three, and validated against Monte Carlo simulation.

In this work, we investigate the extent to which fluctuation–response relations emerge from coarse-grained stochastic dynamics alone, and which aspects instead depend on additional information about the system. To address this question, we study the rotating stochastic Landau model, an exactly solvable system describing an overdamped charged Brownian particle in a constant magnetic field, coupled dissipatively to a rotating environment, whose steady state supports circulating probability currents. Using the Martin–Siggia–Rose path integral, we show that there is an emergent $\mathbb{Z}_2$ symmetry transformation that implements the time-reversed dynamics and changes the action by a boundary term. Comparison with the Crooks fluctuation theorem identifies this term with the entropy associated with transitions between steady-state configurations. After coupling the theory to external sources, the same symmetry yields Ward identities relating fluctuations and response. These identities follow entirely from the coarse-grained stochastic theory and do not fix the noise strength. Finally, upon imposing the Einstein relation, we show that they coincide with the high-temperature fluctuation–dissipation relations implied by the rotating Kubo–Martin–Schwinger condition for a microscopic Gibbs ensemble.

The Traveling Salesman Problem (TSP) asks for the shortest route to visit a set of cities exactly once. It combines a simple local rule - each city must be visited once - with a hard, global constraint- all cities must be traversed within a single cycle. We cast the problem within a probabilistic, information-theoretic framework. The coexistence of local and global constraints is precisely what makes the problem difficult to address in this framework: the local rule can be enforced through vertex-level constraints, whereas the global constraint cannot be captured by independent edge probabilities. We show that this obstacle can be overcome by defining a maximum-entropy probability distribution over graphs, in which edge costs and degree constraints generate an assignment-like ensemble, and a global term, describing the hard constraint, tilts this ensemble toward Hamiltonian cycles. To make the construction tractable, we derive a mean-field approximation in terms of edge occupancies and implement a differentiable cycle penalty that suppresses sub-tours. This leads to a self-consistent numerical procedure whose output is not only a candidate tour but also a probability matrix encoding competing edges and degenerate solutions. We test the method on synthetic ensembles and on TSPLIB instances. The algorithm converges to connected tours in polynomial time, matching the best-known solution in the majority of instances and remaining within a small relative gap otherwise. Beyond its competitive performance, the proposed framework offers a general approach for handling hard constraints while reducing hard combinatorial optimization problems to simpler ones.

We study an assembly of $N$ scalar fields coupled via a quenched random interaction, equivalent to a spin glass whose spins are promoted to $d$-dimensional fields. When $N$ is large, the random coupling matrix produces a family of Gaussian universality classes whose critical exponents are determined by the behavior of the eigenvalue density near the spectral edge. For a Wigner matrix, the correlation length diverges at criticality but the susceptibility remains finite, and one-loop replica analysis supports an upper critical dimension of unity. In an exactly solvable spherical variant, the heat capacity jumps at the transition in $d>1$, and correlations remain pinned to their critical form throughout the glass phase, giving generic scale invariance despite the absence of a Goldstone mode.

Quantum anomalies strongly constrain the possible behavior of many-body systems. A prime example is the Lieb-Schultz-Mattis (LSM) theorem, which relates UV symmetry and filling constraints to IR features of the energy spectrum and ground-state structure. Here, we ask how LSM constraints shape dynamical signatures and temporal correlations in open quantum systems. Using a spacetime duality, we show that the Liouvillian of a $d$-dimensional repeated quantum channel with a mixed anomaly between strong $S$ and weak $G$ symmetry can be mapped to a $(d{+}1)$-dimensional mixed-state symmetry-protected topological (mSPT) phase. Under this correspondence, the initial and steady states of the channel are identified with boundary states of the higher-dimensional mSPT in the presence of bulk projection. We further introduce the twisted Renyi-$N$ correlator (TRNC) as a probe of temporal correlations in the channel and demonstrate that it is dual to the mSPT strange correlator, providing a direct bulk-boundary route to diagnose long-range temporal order implied by the LSM anomaly. Finally, we identify the Liouvillian singular spectrum, rather than the Liouvillian spectrum itself, as a more fundamental diagnostic of quantum anomalies, and show that it is dual to the operator entanglement spectrum of the mSPT.

Counting processes provide a fundamental description of stochastic events ranging from photon detection to clock ticks. A central question is how accurately such events can be timed when only finite memory resources are available. Here, we investigate this problem within a general framework of finite-dimensional classical and quantum counting processes. We derive a rigorous finite-memory variance bound obeyed by every classical $d$-state counting process, which is tight and saturated by a discrete Erlang-type ladder process. Through numerical optimization, we identify quantum counting processes that violate this classical bound, achieving smaller first-tick fluctuations than any classical process with the same memory size and mean tick time. For the qubit case, we further derive an analytical large-mean bound within a single-Kraus no-tick family, showing that the quantum advantage persists asymptotically within this class. The optimized quantum processes exhibit coherent conditioned dynamics and approach a continuous-time quantum-jump description as the mean increases. Our results establish a finite-memory quantum advantage in temporal precision and connect discrete-time counting processes with continuous-time quantum timekeeping.

We show that the $d+0$-dimensional Yang-Lee theory describing classical Ising spins in an imaginary magnetic field can be realized, without post-selection, within a $(d-1)+1$ open quantum system whose dynamics consist of local unitaries and engineered dissipation. Competition between the coherent unitary and dissipative dynamics drives a transition wherein the time-dependence of a particular class of linear observables changes from damped oscillatory "underdamped" to purely exponential "overdamped" decay. Our construction relies on an extensive number of weak-symmetries of the Lindbladian fixed by the choice of observable but is otherwise exact. Consequently, we show that the dynamics are described by the non-Hermitian generator of the Yang-Lee transfer matrix, leading to an effective Yang-Lee theory defined on the spacetime history of the open system. By locally modifying the dynamics, we directly measure spin correlation functions of the Yang-Lee theory as well as a related "Loschmidt Echo" correlator which we detail. We explicitly show that the required dissipation channels can be obtained through local $2$-qubit gates and discuss potential realization on near-term quantum simulator devices. Finally, we generalize our construction to embed arbitrary non-Hermitian Hamiltonians within an open quantum system under Lindbladian time-evolution without post-selection, drawing connections between unconditional open quantum dynamics, exceptional point physics, and non-unitary statistical mechanics.

While band topology is usually associated with the deterministic dynamics of a system, we show that it can instead reside in its fluctuations. Using a reciprocal lattice driven by nonequilibrium chiral active noise, we find that the displacement spectrum—which quantifies displacement fluctuations—admits bands with nonzero Chern numbers despite a Chern-trivial deterministic mechanics. A two-band valley theory captures the emergence of this topology through a Dirac mass inversion, a Haldane-type mechanism, or a quadratic band touching, depending on the relevant transition. Through the bulk–boundary correspondence, we find boundary-localized fluctuation modes that are distinct from the usual propagating mechanical edge states.

We investigate the statistics of the time-integrated current in an infinite one-dimensional gas of independent active Ornstein–Uhlenbeck particles, as a model system for studying an active generalisation of the corresponding passive (diffusive) phenomenology. Unlike the latter, where current fluctuations exhibit universal sub-diffusive scaling, active systems display diffusive, super-diffusive, and sub-diffusive regimes over different time scales. We fully characterise the distribution of current in terms of large-deviation asymptotics, showing that all of these scaling regimes are described by a single scaled cumulant generating function. Moreover, the statistics retain a dependence on the initial condition even at large times, revealing a persistent memory of the initial state. We further obtain the joint large-deviation statistics of currents measured at two distinct times, characterising temporal correlations. Our analytical predictions are verified using rare-event importance sampling, which resolves probabilities as small as $10^{-1000}$.

We study the localization of a quantum particle in a one-dimensional disordered system with long-range hopping amplitudes $t(r)\propto r^{-a}$. In contrast to the standard one-dimensional Anderson model ($a\to\infty$), in which all states are localized and the localization length is minimal at the band edge, the long-range model with $1<a<3/2$ exhibits a disorder-driven transition at the band edge, while high-energy states remain localized at arbitrary disorder strength. We investigate this transition for the ground state in momentum space. In the weak-disorder regime, we derive perturbative expressions for the characteristic functions and moments of the momentum-space wave function, as well as for its fractal dimensions. Our results demonstrate that the ground state exhibits $\it semilocalization$ rather than conventional localization, thereby extending the class of models displaying the unusual $\it semifractality$ of wave functions.

We develop an exactly solvable chemo–thermal extension of the three-state Metropolis Brownian heat engine. The particle moves through the periodic energy sequence $0\to E\to 2E\to0$, performs mechanical work against a load $f$ on every forward step, interacts with two cold links and one hot link, and consumes one fuel molecule of free-energy drop $\muu$ on the hot transition. Local detailed balance gives an exact cycle affinity \begin{equation*} \mathcal A=E\left(\Tc^{-1}-\Th^{-1}\right)+\muu/\Th-f\left(2/\Tc+1/\Th\right), \end{equation*} and the full stationary probabilities and current are obtained without linear-response, weak-driving, or high-barrier approximations. Several results follow. First, the exact stall force is \begin{equation*} \fs=\frac{E(\Th-\Tc)+\Tc\muu}{2\Th+\Tc}. \end{equation*} Second, there is a temperature-neutral chemical compensation point $\muu_*=3E/2$ at which $\fs=E/2$ for every $\Th>\Tc$ and the hot and cold heats both vanish at reversible stall. Third, in both Metropolis branches the stationary current is a strictly increasing function of $\muu$ at fixed mechanical parameters, but approac

Equations of state accurately describe hard-sphere thermodynamics but are generally considered to fail under nanoscale confinement. We show that this failure is geometric rather than thermodynamic: a closed-form, parameter-free mapping from apparent to effective packing fraction restores the accuracy of the Carnahan-Starling equation of state and, with it, the entire analytical thermodynamic framework, including free energies, wall pressures, chemical potentials, and the large-cavity surface response. Applied to overlapping anchored hard-sphere droplets, a geometry inherent to biomolecular force generation, it yields unmixing free energies and full distance-dependent force profiles in quantitative agreement with simulations from the dilute regime to above the bulk freezing transition.

The simple exclusion process (SEP) is a paradigmatic model for nonequilibrium transport, yet its rich dynamics over an exponentially large configuration space remain notoriously intractable. Here, we leverage variational autoregressive networks to characterize the nonequilibrium dynamics of the symmetric (SSEP), asymmetric (ASEP), and totally asymmetric (TASEP) cases in one to three dimensions at any time. We validate the approach against established finite-time 1D and long-time 2D results for the SSEP, and further provide new results on dynamical activity, density fields and nonequilibrium phase transitions for 2D and 3D cases. In 2D, we give a directional-density criterion connecting the bulk-density organization to the 1D TASEP phase diagram, and reveal how boundary and bulk rates separately control the activity and susceptibility. In 3D, we provide the first finite-time characterization of the SSEP active-inactive phase transition, and uncover scaling relations over time. Across dimensions, the critical field follows a trend $s_c\sim L^{-2}$, suggesting tuning strategies by the characteristic diffusive length scale. Overall, this work establishes a unified neural-network framework for characterizing nonequilibrium dynamics of representative transport systems.

Hypergraphs describe higher-order interactions that involve more than a pair of nodes. A characteristic feature of hypergraphs is that their robustness can be strongly affected by the different roles of the nodes. Indeed, some nodes might be essential for a hyperedge's function, while others might not be. The loss of a single essential node completely destroys the hyperedge it belongs to, while the loss of a non-essential node has a buffering effect, inducing the hyperedge to simply reduce its size. In order to capture this phenomenology, we formulate a comprehensive theoretical framework for $(k,n)$-core percolation models on hypergraphs, where each node of a hyperedge is an anchor with probability $\theta$, and a hyperedge fails if an anchor node fails. Hypergraph $(k,n)$-core percolation problems can be classified as first-neighbor and second-neighbor problems, indicating that in the pruning process the connectivity is ensured only by the state of the first neighbors or the second neighbors, respectively. We derive self-consistency equations for first-neighbor and second-neighbor (node- and hyperedge-based) pruning processes, and obtain the size of the giant $(k,n)$-core. We obtain the phase diagram, including continuous and discontinuous transitions, and confirm our theory on random hypergraphs using numerical simulations. The results show how the heterogeneity of the nodes' functional roles and the extended range of the interactions affect the robustness of higher-order networks.