Papers

This work introduces a spectral transfer formalism for nonlinear synchronisation dynamics to resolve how internal dynamical activity redistributes across network scales, moving beyond traditional global observables like the Kuramoto order parameter. By projecting Kuramoto phase dynamics onto the eigenbasis of the graph Laplacian, we construct a time-dependent transfer matrix and derive novel network metrics, including the spectral flux, which quantifies directional redistribution between structural dynamical scales rather than physical transport across nodes. Numerical simulations on modular and hierarchical networks reveal highly structured, intermittent spectral transfer episodes characterised by forward and inverse spectral cascades, directional reversals, and complex interaction geometries. Crucially, we demonstrate a clear separation between macroscopic coherence and microscopic spectral interactions, showing that highly organised, fluctuating internal redistribution dynamics persist even beneath nearly stationary and featureless global synchronisation states. This framework extends conventional synchronisation analysis and establishes a multiscale approach for interpreting network dynamics as an evolving process of spectral reorganisation.

We examine the interchangeability between two duplex systems with opinion dynamics: one characterized by different dynamics parameters $a_1$ and $a_2$ on each layer and full node overlap, and the second with the same parameter $a_1$ on both layers but only partial node overlap $r$. We introduce a general framework for identifying the critical line between the ordered and disordered phases, thereby translating one system into another. The description is supported by several examples of opinion dynamics models and a rigorous measure of the distance between the stationary solutions of the rate equations in both settings. Our results show that even large values of $r$ are sufficient to obtain very good correspondence between the two settings.

Although integrability does not universally require a continuous one-site symmetry, we rigorously prove that every jointly analytic, regular Yang-Baxter deformation of the qutrit exchange interaction necessarily retains a nontrivial, analytically varying one-site charge. Breaking this local symmetry imposes a fundamental physical constraint on approximate conservation, governed by the optimal uniform bound $\delta^3 \le C\varepsilon$ that explicitly relates the minimal one-site symmetry defect $\delta$ to the local current-conservation residual $\varepsilon$. While breaking all one-site charges strictly forbids an exact integrable completion, an optimally compensated nearest-neighbor interaction saturates this cubic limit and anomalously extends the guaranteed infinite-temperature energy-current correlation window to order $|\lambda|^{-3}$ in the perturbation strength $\lambda$. Furthermore, we reveal a fundamental resonance obstruction for intrinsic conversion perturbations that strictly prevents any exact first-order repair of a broken one-site charge on any finite ring. Nevertheless, we demonstrate that the complete eight-dimensional charge memory matrix remains thermodynamically protected and approaches the identity for timescales $t=o(|\lambda|^{-3/2})$, a robust feature of the full infinite-temperature dynamics when the thermodynamic limit is taken before weak coupling.

Fermionic Gaussian states are the workhorse reference states for qubit-based quantum simulation of fermionic systems, yet existing certification protocols either proceed via fidelity estimation, leading to suboptimal sample complexity in the target precision $\epsilon$, only apply to Haar-typical states, or require adaptive measurements on a large fraction of qubits. We give an adaptive protocol that certifies any $d$-mode pure fermionic Gaussian state using $O(d^2\epsilon^{-1})$ copies, single-qubit measurements with only one qubit measured adaptively per copy, and $O(d^3)$ classical processing time per copy. The $\epsilon^{-1}$ dependence is optimal for the certification problem, even among strategies using entangled measurements. The sample complexity is controlled by the spectral gap of a $d\leftrightarrow d-2$ down-up walk—a Markov chain studied in the theory of high-dimensional expanders, equivalent to a two-site Glauber dynamics in statistical physics—relating certification efficiency to relaxation time to equilibrium. The worst-case bound is tight for this protocol and is attained by physically relevant states, including ground states of the fully dimerized Su-Schrieffer-Heeger (SSH) chain and BCS pair states. In contrast, numerics up to $d=14$ suggest that $O(d \epsilon^{-1})$ copies suffice to certify Haar-typical Gaussian states, a factor of $d$ improvement over the worst-case bound. Finally, because the bound depends only on the target's computational-basis distribution, the protocol extends to efficiently phase-dressed states—states obtained by injecting an efficiently computable diagonal phase to Gaussian states—with the same sample complexity. The class includes a continuous family of four-mode non-Gaussian magic states for matchgate computation.

We study the high-dimensional recovery of a signal vector $\mathbf{x}$ in the presence of sparse Wishart-like noise. We define an $N \times N$ matrix $A = J+(\theta/N)\mathbf{xx}^{\top}$, where $\mathbf{xx}^{\top}$ is the rank-one deformation of the random noise matrix $J$. We consider a Wishart-like matrix $J={X}^{\top} X$, where $X$ is a sparse $M \times N$ random matrix with entries $X_{ij} = c_{ij}W_{ij}$, with $c_{ij}$ regulating the density of non-zero elements, and $W_{ij}$ the bond weights. Using the replica method, we compute analytically the top eigenpair statistics of $A$, and their dependence on the signal strength $\theta$, the rectangularity ratio $\alpha=\sqrt{M/N}$, and the average connectivity of the noise. The spectral observables are expressed in terms of a system of Recursive Distributional Equations, which are efficiently solved via a Population Dynamics algorithm. They allow us to compute the average largest eigenvalue $\langle\lambda_1\rangle_{A}$, the average top eigenvector component density, and the average overlap between the top eigenvector of $A$ and $\mathbf{x}$. We identify a critical threshold $\theta_{\mathrm{crit}}$–depending on the average connectivity of the noise–that marks a BBP-like phase transition: below this value, $\langle\lambda_1\rangle_{A}$ is unaffected by the signal, and the overlap vanishes. Thus, the signal is not recoverable from the top eigenvector of $A$. For $\theta>\theta_{\mathrm{crit}}$, the signal-related outlier eigenvalue becomes $\langle\lambda_1\rangle_{A}$ and the overlap is nonzero, allowing for recovery of the signal. The results are in excellent agreement with numerical diagonalisation. We show that in the dense limit, the recovery threshold and eigen-statistics converge to the results predicted by the classical BBP transition for additive rank-one deformations of dense Wishart matrices.

We investigate nonequilibrium phase transitions and thermodynamic properties of driven Potts models coupled to two thermal reservoirs at different temperatures. The interplay with the multi-state structure of the Potts model leads to distinct phase-transition scenarios. The proposed driving scheme breaks the symmetry between the Potts states and gives rise to multiple transitions within the ordered phases, where the phases are characterized by different numbers of stable fixed points. This number can vary from $q$ fixed points to $1$ fixed point, corresponding to $q-1$ distinct transitions. The driving scheme strongly affects the thermodynamic operation regimes, allowing the system to operate as a heat engine. We demonstrate that these phenomena persist for both a mean-field (MF) model and a two-dimensional model, confirming the robustness of the results with respect to dimensionality. For the MF case, we also develop a phenomenological description in the strongly ordered regime that yields analytical expressions for the power, heat currents, and efficiency. Our results show how multi-state collective interactions, nonequilibrium driving, and thermal bias jointly generate a rich phase structure and the emergence of a collective heat engine.

Returning to a familiar location can help a searcher find its target—but how should the target move to avoid being found? We address this question for a resetting Brownian searcher and a mobile target fluctuating around a home location. Keeping the target's typical exploration range fixed, we find that the mean capture time is maximized at an intermediate correlation time: rapid motion promotes encounters, whereas slow motion leaves the target effectively stationary. Between these extremes, persistent excursions away from the searcher's reset point can substantially delay capture. Analytical limiting results explain this optimum, while numerical solutions reveal an approximately linear relation between the maximal mean capture time and the optimal correlation time across many decades. These findings identify temporal correlations as a resource for evasion, allowing a target to prolong survival by changing how it moves rather than where it roams.

The Generalized Langevin Equation (GLE) is an integro-differential equation of motion for a general observable of a many-body system and is rigorously derived using the projection operator formalism. In the standard derivation, a stationary canonical phase space distribution is used for the projection. Here, we derive a novel class of GLEs using a non-stationary projection distribution that constrains the initial ensemble to a hypersurface in phase space on which the observable has a fixed value $A_0$. As a result, all GLE parameters, and in particular the memory friction kernel, depend on $A_0$ and can be extracted from short simulations that do not sample the entire phase space. Applying this non-stationary GLE to protein folding trajectories, we find for villin and an $\alpha$-helical poly-alanine segment that the total friction is higher in the folded state. These results demonstrate that observable-dependent friction effects are non-negligible and can be accounted for using non-stationary GLEs derived by constrained projection schemes.

In a recent paper arxiv.org/abs/2609.21031, we have introduced the concept of a relational background field as a new approach to the renormalization group (RG) for discrete quantum gravity models, focusing on random matrix models. The proposed method offers the dual advantage of preserving the model's gauge symmetry (typically $U(N)$ or $O(N)$), whose breaking in conventional approaches has remained an open problem, and providing a more satisfactory treatment of the continuum or infrared (IR) limit. In this limit, the theory is described by a non-local field theory in dimension $D = 2k + 3$, where $k$ denotes the number of cuts in the effective spectrum as dictated by random matrix theory. This pedagogical paper reviews this construction for real random vector models in zero dimensions, with $O(N)$ as the symmetry group. Following the general strategy of background-field-type formulations, we show, using the BBP (Baik-Ben Arrous-P'ech'e) phase transition, that a partial Hubbard–Stratonovich decomposition of the quartic interaction, involving a matrix-valued intermediate field, allows a preferred notion of scale to emerge. This scale, in turn, defines an RG flow, whose perturbative structure is analyzed. Our calculation demonstrates the existence of an asymptotic Wilson–Fisher-type fixed point, whose sole relevant critical exponent is in qualitative agreement with the double-scaling critical exponent of these models.

We develop a multiscale entropy framework based on the wavelet conditional renormalization group that decomposes the total Shannon entropy into contributions from different spatial scales. Generative modeling enables accurate estimation of these entropies from configurations or snapshots, even in nonequilibrium systems whose underlying probability distributions are unknown. Applications to the equilibrium $\varphi^4$ model and nonequilibrium active Model B+ show that multiscale entropies reveal criticality and spatial organization obscured in the total entropy. These entropies serve as scale-dependent order parameters for characterizing phase transitions and pattern formation.

Universal information extracted from a critical quantum state depends on how the state is probed. Spatial entanglement, participation statistics, and stabilizer Rényi entropy correspond to different replica geometries and need not isolate the same boundary data. We show that the complete distribution of Pauli magnitudes in critical Ising chains carries an exact geometric fingerprint of boundary termination, distinguishing lattice realizations that flow to the same infrared boundary fixed point. This structure is organized by discrete Selberg ensembles associated with the classical root systems $A$, $B$, $C$, and $D$: three open chains sharing the free–free Ising boundary condition retain distinct $B_L$, $C_L$, and $D_L$ trigonometric wall geometries. The standard symmetry-breaking representatives instead produce rectangular, pinned, and character-inserted $C$ ensembles. Their four boundary moments contain exactly two independent multiplicative combinations invariant under local endpoint normalizations. One of these reduces exactly at finite rank to a moment of the fundamental symplectic character and provides a lattice target for a defect–measurement-boundary junction amplitude. A conditional Gaussian-character law predicts its values throughout the unlocked phase, while exact-arithmetic finite-rank results at the $\alpha=4$ transition depart sharply from the Gaussian continuation. These results show that the full Pauli spectrum resolves boundary information invisible to the infrared boundary fixed point alone and provide concrete targets for replicated boundary conformal field theory.

The fate of average symmetry-protected topological (ASPT) states based on the one-dimensional cluster state is investigated by using the Choi mapping, namely, the doubled Hilbert-space formalism. By introducing two effective spins, $\tau$ and $\eta$, on each doubled rung, we obtain a transparent representation of the ASPT parent Hamiltonian and systematically identify the conserved stabilizers and the corresponding orders. We further study symmetry-preserving operations that deform the ASPT by combining qualitative effective-Hamiltonian and systematic parent-Hamiltonian analyses with numerical matrix-product-state filtering calculations. We find that although the ASPT remains robust over a broad range of decoherence strengths, strong-to-weak spontaneous symmetry breaking (SWSSB) becomes exact in the maximal-decoherence limit. In addition, we consider symmetry preserving no-click postselection, which removes the exact conservation law supporting the Rényi-2 string order of the ASPT and drives the system toward weak-symmetry spontaneous symmetry breaking (WSSB). Again, the ASPT remains robust over a broad range of postselection strengths, with WSSB becoming pronounced only near the projective limit and exact at the limit itself.

Local quantum interactions generate dynamics in an exponentially large Hilbert space, yet locality and entanglement restrict the information that can spread and accumulate. Bounds on propagation and entanglement growth, together with tensor networks, exploit these restrictions to discard information unnecessary for describing the evolution. This leads to a sharper question: how much information must any low-rank representation retain? Here we determine these limits, up to logarithmic factors, for short-range interactions. For time-independent evolution, the optimal rank obeys $\log D=\widetilde O(t+\sqrt{\log(1/\epsilon)})$, with matching lower bounds fixing the accuracy exponent $1/2$; for arbitrary driving, matching fixed-time bounds instead give $2/3$. Correspondingly, the corresponding dynamical entanglement spectra exhibit distinct small-$\alpha$ Rényi laws, $\alpha^{-1}$ and $\alpha^{-2}$. In one dimension, the static limit is constructively attained by an explicit MPO algorithm, with an analogous extension to Liouvillian dynamics. Together, these results determine the irreducible information required to represent local quantum evolution and uncover distinct entanglement structures in static and driven dynamics.

First passage processes in active systems combine stochastic transport with self-propulsion and orientational persistence, making motion along and against an external bias sensitive to the internal active dynamics. For passive biased diffusion, opposite exits can have different splitting probabilities while their conditional first passage time distributions remain identical. We study how this relation changes for an active Brownian particle driven by a constant external force between two absorbing boundaries. Self-propulsion breaks the equality of the uphill and downhill first passage time distributions and modifies the splitting probabilities. Nevertheless, the two directional path ensembles remain exactly related by spatial reflection, which pairs downhill and uphill first passage paths of the same duration while preserving their orientational history. The log-ratio of the probabilities of a path and its reflected partner defines a path-dependent asymmetry functional and provides an exact reweighting between the two ensembles. In the symmetric half-weighted representation, the uphill and downhill first passage time distributions coincide for arbitrary orientational persistence. The same path relation also allows rare uphill statistics to be reconstructed from the more frequently sampled downhill trajectories. Numerical simulations confirm the weighted equality across the explored bias and persistence regimes, while perturbative and asymptotic analyses clarify how orientational persistence produces the directional asymmetry of the unweighted statistics. The exact relation between the two directional path ensembles suggests that similar symmetry-based reconstruction protocols may be found in other nonequilibrium first-passage problems.

The stochastic block model is a paradigmatic model of networks with community structure. Yet percolation in the model has been studied primarily in cases with a fixed block structure, even though in real networks, the community structure may evolve as the network grows. Here we study percolation in sequences of stochastic block models in which the numbers and sizes of communities, as well as the intra- and intercommunity connection probabilities may all change with the network size. We analyze five such sequences using two methods: linearized self-consistent equations for the locally tree-like models and a branching process at the community scale for the models with nonvanishing clustering. We find that the critical average degree is not generally equal to $1$, even in locally tree-like sequences, because the transition depends on how connections are distributed across the evolving community structure. We also show that the community-scale branching process accurately predicts the transition when intercommunity connections are sufficiently sparse, even in the presence of nonvanishing clustering, while a geometric stochastic block model sequence demonstrates the limitations of this method when correlations between intercommunity connections cannot be neglected. These results extend percolation studies in the stochastic block model to more realistic scenarios with evolving community structure, and may provide new methods to derive the upper and lower bounds for the percolation threshold in geometric long-range percolation.

Biochemical systems such as protein complexes often occupy configuration spaces whose dimensionality grows with the number of molecular components. Although usually viewed as an obstacle to coherent dynamics, here we show that high dimensionality can enhance topologically protected oscillations. In the topological regime, a stochastic system with a $D$-dimensional configuration space develops a steady-state current confined to a one-dimensional edge cycle. The intervening boundary faces between the $D$-dimensional bulk and the one-dimensional cycle form an interdimensional funnel, sequentially pushing the system towards lower dimensional faces, down to the one-dimensional cycle. As a consequence, increasing $D$ enhances the funnel, leading to improved one-dimensional localization and oscillatory coherence. A quantized biorthogonal Zak phase identifies the transition to the topological regime, which additionally exhibits a highly structured non-Hermitian skin effect. In contrast with previous realizations of topological states in stochastic systems, the phenomena we uncover have no counterpart in quantum condensed matter or active matter systems.

A conventional interaction-driven Weyl density wave is a complex scalar and supports vortex lines, but no topologically stable point defects. We show that two Weyl flavors do not merely duplicate this order. Starting from the matrix-valued internode coherence, a local flavor-symmetric repulsion selects a traceless adjoint condensate within the density-wave sector, while the fermionic ground-state energy locks its complex components into the collinear form $\mathbf{\Delta}=\Phi_0\mathbf{n} e^{i\theta}$. The resulting order-parameter manifold, $(S^2\times S^1)/\mathbb Z_2$, supports both unit hedgehogs and half-quantum Alice strings of the same electronic mass that gaps the Weyl fermions. An elementary hedgehog binds a single normalizable zero mode whose empty and occupied sectors carry charges $-e/2$ and $+e/2$ at neutrality. An elementary Alice string carries a single chiral electronic mode despite its $\pi$ phase winding, and transporting a hedgehog around it reverses the hedgehog winding, $N\rightarrow-N$. Flavor therefore converts spontaneous translation breaking into a route to point-defect fractionalization and intertwines the point- and line-defect sectors of an interaction-generated electronic mass.

A simple symmetric random walk on a one-dimensional lattice is guaranteed to reach any target site, yet its mean first-passage time diverges. Here, we show that stochastic fluctuations in the jump rate can fundamentally alter this classic result. We find a phase transition in the mean first-passage time: sufficiently broad rate fluctuations render it finite, whereas weaker fluctuations leave it infinite. Our results demonstrate that temporal fluctuations in the jump rate—and hence in the diffusivity—can overcome spatial wandering and regularize otherwise divergent first-passage times.

The quantum circuit complexity of an evolving many-body quantum system is believed to exhibit a sustained growth, maintained for timescales much longer than the onset of thermalization. Most previous works have focused on models which violate energy conservation, such as random unitary circuits. Here we study generic, local time-independent Hamiltonian dynamics. We unconditionally prove that for generic local Hamiltonians and typical initial product states at high effective temperature, the robust quantum circuit complexity must grow over a very long period of time, attaining an exponentially large value at late times. Our approach relies on two structural properties that we prove rigorously: (i) generic local Hamiltonians satisfy generalized spectral no-resonance conditions of arbitrary order, and (ii) typical high-temperature product states are effectively supported in exponentially many energy eigenstates. These properties have been widely assumed without proof in prior works. As corollaries of this result, we show the late-time state displays robust volume-law entanglement that is irremovable by polynomial-size circuits, and we establish a no fast-forwarding result for generic local Hamiltonians. We also lower bound the complexity of preparing sufficiently large subsystems with local quantum channels, in contrast with sufficiently small thermalizing regions which we show retain low complexity at late times.

We present exact analytical solutions to the nonlinear relativistic Boltzmann equation for homogeneous, isotropic massless multi-component systems with non-isotropic scattering cross sections. For a two-component system, we identify three distinct classes of exact solutions, each corresponding to specific constraints among initial energy densities, particle number densities, and scattering cross sections. These solutions comprise the equilibrium state and two novel classes: a hybrid structure featuring a non-equilibrium Maxwell-Juttner distribution coupled with a nontrivial distribution; the former is unprecedented in kinetic theory, while the latter refers to nontrivial dynamics shared by both species, which is novel in the relativistic context.

Network diffusion is a well-known model for studying how a quantity in a network propagates to reach a steady state, where its value becomes uniformly distributed across all nodes. Previous studies of network diffusion have mainly focused on the second-smallest eigenvalue of the network Laplacian to determine the timescale associated with the slowest decaying mode. However, this study investigates the eigenspectrum of the network Laplacian in terms of its statistical properties. This method is useful for studying the statistical properties of network diffusion without calculating all eigenvalues, which can be useful for large networks. Additionally, this study introduces a condition under which the system is less diffusive and investigates how changes in the network structure influence the overall diffusion dynamics.

Receptor-mediated endocytosis requires a particle to approach the cell membrane to within a few nanometers before ligand–receptor binding can occur. Existing continuum models often start from an already established contact and do not explicitly describe how crowding particles on the extracellular side influence the distribution of the particle near the membrane. We examine entropic depletion forces as one possible nonspecific contribution to this initial approach. For ideal depletants, the Asakura–Oosawa excluded-volume construction gives an exact depletion potential for the planar geometry before contact. The potential and force vanish continuously at the onset of excluded-volume overlap. This interaction provides a possible contribution to membrane proximity before specific binding, while its extension to curved wrapping geometries requires additional approximation. Within a reduced continuum model, we combine depletion attraction, ligand–receptor binding, membrane deformation, and cytoskeletal viscoelastic dissipation. The viscoelastic contact is formulated through a hereditary integral and a standard linear solid. The kinetic model gives a conditional minimum ligand density for complete engulfment, a finite particle-size window, and a stiffness-dependent upper limit. When the stationary radius lies inside the domain of finite positive wrapping times, the estimated wrapping time has a minimum at a radius that decreases with increasing binding energy density. At fixed viscosity and other independent parameters, the same time approximation predicts slower wrapping as cell stiffness increases. The two positive roots defining the size window merge at a limiting parameter value, which characterizes closure of the admissible size interval. Depletion attraction is interpreted as one possible contribution to particle-membrane association

We study the leading probe-flavour contribution to equal-time spatial entanglement entropy in a homogeneous 3+1-dimensional strongly coupled conductor at finite temperature and charge density, realised holographically by the D3-D7 system and driven by a constant DC electric field. We compare slab-shaped subregions that are extended in two spatial directions and have finite width parallel or transverse to the field. The difference between the corresponding entropy corrections isolates a homogeneous, spatially traceless response and exhibits a density-driven sign reversal. Over the investigated parameter range, the crossover density increases with the electric-field magnitude and decreases with the strip width. Mutual information shows the same qualitative reversal and provides an ultraviolet-finite check. We trace the effect to a radial sign competition in the full Dirac-Born-Infeld stress anisotropy. The reversal is a smooth response crossover rather than a thermodynamic phase transition.

The dynamics of gauge theories is of fundamental interest, with low-dimensional systems displaying a rich phenomenology beyond the rapid thermalization typical of QCD and non-Abelian theories. In particular, recent quantum simulation experiments have reported robust and unexpected signatures of slow relaxation in generic regimes and at large volumes in one-dimensional U(1) lattice gauge theories (LGTs), whose origin remains poorly understood. Here, we present a framework that provides a unified perspective on such slow dynamics and establishes a new route for exploring subdiffusive fractonic hydrodynamics in Rydberg experiments. The backbone of our theory is an exact analytical mapping from U(1) LGTs with a topological $\theta$ angle to non-local kinetically constrained fermionic models with an emergent linear Stark potential. In the absence of the $\theta$ term, this framework interprets the non-thermal dynamics reported in recent experiments as prethermal behavior arising from proximity to an integrable free-fermion model. For non-zero $\theta$, the emergent Stark potential instead explains the freezing dynamics observed in other recent experiments. We argue that this correspondence could also lead to subdiffusive transport due to emergent conservation laws. We predict that these phenomena arise in a much broader class of models, and support this prediction with numerical simulations and proposals for future experiments.

Driven-dissipative many-body quantum systems can be exploited in quantum enhanced sensing protocols. Here, non-classical correlations may allow one to reach a measurement precision that surpasses the standard quantum limit. The relevant figure of merit for assessing such quantum advantage is the quantum Fisher information (QFI). In a many-body setting its computation is challenging as it requires knowledge of the full system-environment state. Here we make use of a field-theoretical approach, which is particularly well suited for systems with many degrees of freedom. In particular, we exploit that the QFI can be linked to a Keldysh path-integral. This route leads to a semiclassical expression of the QFI, which is obtained through a controlled expansion in the so-called quantum fields. We benchmark the framework on three systems of increasing complexity: the driven-dissipative harmonic oscillator, the boundary time crystal - which becomes semiclassical at large system sizes - and a two-dimensional array of collectively emitting atoms. We assess in which parameter regimes the semiclassical description holds and gives access to system sizes beyond the reach of exact methods.

Strong-to-weak spontaneous symmetry breaking (SWSSB) can occur in a maximally mixed charge sector even when ordinary charged correlations vanish. We study this order when a charge sector splits into dynamically disconnected fragments. In a one-dimensional $t$-$J_z$ chain with species-resolved dephasing, each fragment is labeled by a conserved spin word. A charged transfer between separated finite intervals preserves that word only if the intervening spins satisfy a periodicity constraint. In the full-state two-point sense, we use this constraint to prove the absence of long-range fidelity and Rényi-1 order in typical fixed-composition fragments, uniformly over all norm-bounded charged operators in any prescribed finite interval. A fragment with primitive spin-word period $k$ supports a $k$-particle channel with exact long-distance value $\nu^k(1-\nu)^k/k^2$, and no charged operator on fewer than $k$ sites can carry this order. A transverse exchange connects the fragments while preserving the global charges and restores the full-sector steady state at finite size. The conserved spin word therefore selects the local channels that can support mixed-state order.

Entanglement embezzlement asks how much entanglement can be borrowed from a many-body state by local operations and classical communication while returning that state with a small error. We uncover a conservation-law mechanism that redistributes the dominant probability mass of the Schmidt spectrum in the logarithmic Schmidt-rank coordinate and thereby controls this operational resource. For typical random pure states at fixed U(1) charge, we prove a finite-error conversion law: away from half filling, the charge bias converts $O(\sqrt L)$ charge fluctuations into $O(\sqrt L)$ borrowable entanglement, whereas particle–hole symmetry at half filling removes this contribution entirely. We then show how the resource develops dynamically in charge-conserving random circuits. Combining hydrodynamic analysis with large-scale replica tensor-network calculations, we find that diffusion broadens the operationally relevant distribution in the logarithmic Schmidt-rank coordinate on the scale $t^{1/4}$ and increases the amount of entanglement that can be borrowed. Charge transport therefore continues to reorganize the entanglement spectrum and activate embezzlement after the leading volume-law entropy has saturated.

We study the thermal equilibrium of a classical system of identical point charges moving between two walls with parallel surfaces at a distance $d$, charged symmetrically with position-dependent surface charge densities. Specifically, we study the effect of surface charge modulation on the effective force (pressure) between the walls in the Poisson-Boltzmann limit. Based on Monte Carlo simulations at high temperatures, it is predicted that surface charge modulation reduces the pressure between the walls compared to uniformly charged wall surfaces with the same average surface charge density. We restrict ourselves to surface charge modulations in only one direction and, using a general solution of the two-dimensional Liouville equation, we construct exact solutions for the electrostatic potential. The surface charge density on the walls is generated inversely from this potential, which means that our exact results apply to a limited set of models with a specific variation of the surface charge density with distance $d$. Explicit analytical results show that surface charge modulation can both increase (small distances $d$) and decrease (large $d$) the pressure between the walls.

The debate over pairwise and higher-order models is often framed as a contest of expressive power. This framing is misleading. A graph with arbitrary multivariate node functions can reproduce the node-level dynamics of many hypergraph models, but the hypergraph's grouping information does not thereby disappear: it may simply move from the structure to the rule. We separate four notions frequently conflated here: structural representation, functional representability, statistical identifiability, and mechanistic adequacy. We then prove that interaction order, the number of variables that must act jointly in some term of any additive decomposition of a node's update, is the same in every exact representation: no change of structural language can lower it. As a description-length problem, at the unrestricted algorithmic level a fixed compiler redistributes information between structure and rule at constant overhead, so expressiveness alone cannot privilege either language. Preferences arise only relative to explicit model classes, code families, and data. This yields an operational minimum-description-length criterion combining structural cost, conditional rule cost, and imperfect fit. Within it, for $M$ disjoint groups of size $k$, the clique projection's edge list is asymptotically $k-1$ times longer than the hyperedge list it replaces: the projection encodes the same grouping at higher cost. Examples from diffusion, Boolean dynamics, ecology, and ambiguous projections give graph-preferred, hypergraph-preferred, and unresolved cases; for bipartite and multilayer lifts, cost, fit, and identifiability tie, and the choice turns on which entities are posited as primitive. The position is symmetric: higher-order structure should not be inferred from phenomenology alone, nor does a graph's ability to emulate a system make it the most parsimonious or adequate description.

We study the equilibrium statistical mechanics of one-dimensional classical Machian fractons: particles whose dynamics conserves a global dipole moment and whose Hamiltonian couples momentum differences through a position-dependent pair-inertia kernel. Compactly supported interaction kernels have a divergence in the Gibbs partition function, and have been shown to break ergodicity and symmetry by forming non-equilibrium steady states with particle clusters, evading the Hohenberg-Mermin-Wagner-Coleman theorem. In this paper, we consider kernels with non-compact support and study their ergodic properties. For exponentially decaying kernels, graph-Laplacian and matrix-tree bounds provide an extensive free energy suggesting that a putative statistical mechanical description is valid. Similarly, uniform non-local kernels have a super-extensive free energy and require a Kac rescaling. A generalized Hohenberg–Mermin–Wagner–Coleman argument, supported by finite-size scaling, implies symmetry-breaking density order parameter vanishes at all wave vectors melting the long-range translation-breaking density order of compact kernels. To study the resulting equilibrium ensemble, we construct a nonreversible event-chain Monte Carlo (ECMC) algorithm that samples the coupled position-momentum phase space while preserving the dipole moment and total momentum. The ECMC sampling is shown to quantitatively match long time-averaged quantites in Hamiltonian dynamics. The equilibrium liquid exhibits preferred short-range clustering and strongly non-Gaussian single-particle momentum tails associated with the correlated nature of positions and momenta. This paper provides a detailed investigation into the equilibrium liquid properties of the non-compact regime, whilst the companion paper investigates the mechanisms that relax the liquid.