arXiv subjects

Israel Klich

Publications and source records attributed to Israel Klich.

At least 19 recordsLinked to original sources

arXiv2026

Thermalization packets and optimal ice cubes

Relaxation toward equilibrium is usually accelerated by modifying the environment or by cooling a system further from equilibrium. Here we introduce a distinct strategy: thermalization packets, auxiliary systems prepared in advance and later coupled to a target system to accelerate its relaxation toward a prescribed thermal state. Thus, thermalization packets trade preparation effort for reduced waiting time. When the objective is cooling, we colloquially refer to such packets as ice cubes. Unlike ordinary coolants, thermalization packets are characterized not only by their temperature or heat capacity, but also by their microscopic preparation. We define perfect and optimal packets by their ability to suppress the slowest relaxation mode of the coupled dynamics: perfect packets eliminate it entirely, while optimal packets minimize its amplitude. We show that, under generic conditions, perfect packets exist among thermal preparations near equilibrium. Surprisingly, for asymptotic relaxation, the optimum among thermal preparations is generally not the coldest packet: cooling the packet beyond the slow-mode-cancelling optimum restores a nonzero slow mode and can therefore slow relaxation, yielding a packet analog of the Mpemba effect. We demonstrate the concept in exactly solvable Metropolis dynamics, a minimal two-qubit model, and a boundary-coupled interacting Ising-spin system. We also extend the framework to packets optimized for finite readout times. Finally, we show that the perfect-packet contour can connect the trivial bath-equilibrium point to a nontrivial strong Mpemba or strong inverse-Mpemba point.

cond-mat.stat-mech↗

arXiv2026

On Factorizing Aggregate Counting Distributions into Independent Latent Processes

Given only the probability distribution of an aggregate counting variable, what independent latent counting processes are compatible with the observation? Equivalently, when does a probability-generating function admit a factorization into normalized polynomials with nonnegative coefficients? We develop a mathematical theory of such positive factorizations. We introduce the positive factorization poset, whose elements are all positive factorizations ordered by refinement, and define the factorization entropy, measuring the maximal latent Shannon entropy compatible with the observed distribution. We prove a sharp entropy inequality, characterize the equality case by injectivity of the latent addition map, show that entropy optimization may be restricted to maximal atomizations, and exhibit examples where distinct maximal atomizations have different entropy. We further establish support-based obstructions to positive factorization, characterize the real-rooted and Hurwitz-stable sectors, prove a local stability theorem for coprime factorizations, determine exactly the factorable regions in degrees two and three, obtain an exact quartic Hurwitz volume, and investigate the geometry of the factorable region inside the probability simplex through exact calculations and Monte Carlo experiments. These results identify the positive factorization poset as a natural algebraic object associated with probability-generating functions and provide a framework for studying latent independent structure in aggregate counting statistics.

math-ph↗

arXiv2026

Perturbative Contrastive Physical Learning

Responses to perturbations are key to understanding physical systems. The ability to contrast such responses by comparing how a system reacts under slightly different conditions provides a mechanism for learning. Here, we introduce Perturbative Contrastive Physical Learning (PCPL), a general framework in which learning emerges from measurable contrasts between physical states produced by controlled changes to inputs, boundary conditions, parameters, or interpreter functions. PCPL unifies and extends prior approaches: Equilibrium Propagation is rooted in contrasts between free and nudged equilibria in energy-based systems, while Frequency Propagation corresponds to contrasts extracted from sinusoidally driven, frequency-demodulated responses. We show that contrast-driven updates can reflect either local sensitivities or global inverse-problem structure, yet do not require centralized gradient computation. Instead, effective learning geometry emerges implicitly from the system's own physical response, allowing learning behavior to arise without an external processor or explicit backpropagation. We demonstrate PCPL in two platforms: (i) spring networks that update bond stiffness using measured displacements and forces, and (ii) continuous-variable photonic circuits trained via x quadrature measurements and finite-difference estimates of the Jacobian. Both platforms successfully learn classification tasks. We further show that a continuous-variable photonic circuit can be trained to implement analog multiplication, illustrating a step toward more autonomous physical learning systems.

cs.LG↗

arXiv2026

Laser interferometry as a robust neuromorphic platform for machine learning

We present a method for implementing an optical neural network using only linear optical resources, namely field displacement and interferometry applied to coherent states of light. The nonlinearity required for learning in a neural network is realized via an encoding of the input into phase shifts allowing for far more straightforward experimental implementation compared to previous proposals for, and demonstrations of, $\textit{in situ}$ inference. Beyond $\textit{in situ}$ inference, the method enables $\textit{in situ}$ training by utilizing established techniques like parameter shift methods or physical backpropagation to extract gradients directly from measurements of the linear optical circuit. We also investigate the effect of photon losses and find the model to be very resilient to these.

physics.optics↗

arXiv2025

From Quantum Annealing to Alloy Discovery: Towards Accelerated Design of High-Entropy Alloys

Data scarcity remains a central challenge in materials discovery, where finding meaningful descriptors and tuning models for generalization is critical but inherently a discrete optimization problem prone to multiple local minima confounding the true optimal state. Classical methods often get trapped in these minima, while quantum annealing can escape them via quantum fluctuations, including tunneling, that overcome narrow energy barriers. We present a quantum-assisted machine-learning (QaML) framework that employs quantum annealing to address these combinatorial optimization challenges through feature selection, support-vector training formulated in QUBO form for classification and regression, and a new QUBO-based neural-network pruning formulation. Recursive batching enables quantum annealing to handle large feature spaces beyond current qubit limits, while quantum-pruned networks exhibit superior generalization over classical methods, suggesting that quantum annealing preferentially samples flatter, more stable regions of the loss landscape. Applied to high-entropy alloys (HEAs), a data-limited but compositionally complex testbed, the framework integrates models for fracture-strain classification and yield-strength regression under physics-based constraints. The framework identified and experimentally validated Al8Cr38Fe50Mn2Ti2 (at.%), a single-phase BCC alloy exhibiting a 0.2 % yield strength of 568 MPa, greater than 40 % compressive strain without fracture, and a critical current density in reducing acid nearly an order of magnitude lower than 304 stainless steel. These results establish QA as a practical route to overcome classical optimization limits and accelerate materials discovery.

cond-mat.mtrl-sci↗

arXiv2025

Quantum-Annealing Enhanced Machine Learning for Interpretable Phase Classification of High-Entropy Alloys

High entropy alloys (HEAs) offer unprecedented compositional flexibility for designing advanced materials, yet predicting their crystallographic phases remains a key bottleneck due to limited data and complex phase formation behavior. Here, we present a quantum-enhanced machine learning framework that leverages quantum annealing to enhance phase classification in HEAs. Our pipeline integrates Quantum Boosting (QBoost) for interpretable feature selection and classification, with Quantum Support Vector Machines (QSVM) that use quantum-enhanced kernels to capture nonlinear relationships between physical descriptors. By reformulating both models as Quadratic Unconstrained Binary Optimization (QUBO) problems, we exploit the efficient sampling capabilities of quantum annealers to achieve rapid training and robust generalization, demonstrating notable runtime reductions relative to classical baselines in our setup. We target six key phases: FCC, BCC, Sigma, Laves, Heusler, and AlXY B2, and benchmark model performance using both cross-validation and a rigorously curated test set of prior experimentally synthesized HEAs. The results confirm strong alignment between predicted and measured phases. Our findings demonstrate that quantum-enhanced classifiers match or exceed classical models in accuracy and offer insights grounded in interpretable physical descriptors. This work constitutes an important step toward practical quantum acceleration in materials discovery pipelines.

cond-mat.mtrl-sci↗

arXiv2024

SWAP and Transpose by displacements, Stabilizer Renyi entropies for continuous variables and qudits and other applications

In this note, I highlight a useful formula for the SWAP operator as an average of anti-correlated Heisenberg-Weyl displacements, valid for arbitrary-dimensional quantum systems. As an application I show how the relation can be used to quickly prove normalization identities for the Weyl function, and apply the result to Weyl magic and Wigner magic as the generalization of the recently suggested Renyi Stabilizer entropy to q-dits and CV.

quant-ph↗

arXiv2024

Random walk with horizontal and cyclic currents

We construct a minimal two-chain random walk model and study the information that fluctuations of the flux and higher cumulants can reveal about the model: its structure, parameters, and whether it operates under nonequilibrium conditions. The two coupled chains allow for both horizontal and cyclic transport. We capture these processes by deriving the cumulant generating function of the system, which characterizes both horizontal and cyclic transport in the long time limit. First, we show that either the horizontal or the cyclic currents, along with their higher-order cumulants, can be used to unravel the intrinsic structure and parameters of the model. Second, we investigate the "zero current" situation, in which the {\it horizontal} current vanishes. We find that fluctuations of the horizontal current reveal the nonequilibrium condition at intermediate bias, while the cyclic current remains nonzero throughout. We also show that in nonequilibrium scenarios close to the zero {\it horizontal} current limit, the entropy production rate is more tightly lower-bounded by the relative noise of the {\it cyclic} current, and vice versa. Finally, simulations of transport before the steady state sets in allow for the extraction of the interchain hopping rate. Our study, illustrating the information concealed in fluctuations, could see applications in chemical networks, cellular processes, and charge and energy transport materials.

cond-mat.stat-mech↗

arXiv2023

Confinement and Kink Entanglement Asymmetry on a Quantum Ising Chain

In this work, we explore the interplay of confinement, string breaking and entanglement asymmetry on a 1D quantum Ising chain. We consider the evolution of an initial domain wall and show that, surprisingly, while the introduction of confinement through a longitudinal field typically suppresses entanglement, it can also serve to increase it beyond a bound set for free particles. Our model can be tuned to conserve the number of domain walls, which gives an opportunity to explore entanglement asymmetry associated with link variables. We study two approaches to deal with the non-locality of the link variables, either directly or following a Kramers-Wannier transformation that maps bond variables (kinks) to site variables (spins). We develop a numerical procedure for computing the asymmetry using tensor network methods and use it to demonstrate the different types of entanglement and entanglement asymmetry.

quant-ph↗

arXiv2023

Entanglement asymmetry and quantum Mpemba effect in the XY spin chain

Entanglement asymmetry is a quantity recently introduced to measure how much a symmetry is broken in a part of an extended quantum system. It has been employed to analyze the non-equilibrium dynamics of a broken symmetry after a global quantum quench with a Hamiltonian that preserves it. In this work, we carry out a comprehensive analysis of the entanglement asymmetry at equilibrium taking the ground state of the XY spin chain, which breaks the $U(1)$ particle number symmetry, and provide a physical interpretation of it in terms of superconducting Cooper pairs. We also consider quenches from this ground state to the XX spin chain, which preserves the broken $U(1)$ symmetry. In this case, the entanglement asymmetry reveals that the more the symmetry is initially broken, the faster it may be restored in a subsystem, a surprising and counter-intuitive phenomenon that is a type of a quantum Mpemba effect. We obtain a quasi-particle picture for the entanglement asymmetry in terms of Cooper pairs, from which we derive the microscopic conditions to observe the quantum Mpemba effect in this system, giving further support to the criteria recently proposed for arbitrary integrable quantum systems. In addition, we find that the power law governing symmetry restoration depends discontinuously on whether the initial state is critical or not, leading to new forms of strong and weak Mpemba effects.

cond-mat.stat-mech↗

arXiv2023

Measurement Induced Chirality II: Diffusion and Disorder

Repeated quantum measurements can generate effective new non-equilibrium dynamics in matter. Here we combine such a measurement driven system with disorder. In particular, we investigate the diffusive behavior in the system and the effect of various types of disorder on the measurement induced chiral transport protocol [1]. We begin by characterizing the diffusive behavior produced by the measurements themselves in a clean system. We then examine the edge flow of particles per measurement cycle for three different types of disorder: site dilution, lattice distortion, and disorder in onsite chemical potential. In the quantum Zeno limit, the effective descriptions for the disordered measurement system with lattice distortions and random onsite potential can be modelled as a classical stochastic model, and the overall effect of increasing these disorders induces a crossover from perfect flow to zero transport. On the other hand if vacancies are present in the lattice the flow of particles per measurement cycle undergoes a percolation phase transition from unity to zero with percolation threshold $p_c \approx 0.26$, with critical exponent $\nu \approx 1.35$. We also present numerical results away from Zeno limit and note that the overall effect of moving away from the Zeno effect is to reduce particle flow per cycle when the measurement frequency in our protocol is reduced.

cond-mat.dis-nn↗

arXiv2022

Fragmentation and Novel Prethermal Dynamical Phases in Disordered, Strongly-Interacting Floquet Systems

We explore how disorder and interactions conspire in lattice models with sequentially activated hopping to produce novel k-body (or many-body) localized phases. Specifically, we show that when disorder is added to the set of interacting floquet models considered in [Wampler and Klich arXiv:2209.09180], regions in parameter space near the special points where classical-like dynamics emerge are stabilized prethermally (or via many-body localization in some cases) producing new families of interesting phases. We also find that this disordered system exhibits novel phases in regions of parameter space away from the special, Diophantine points. Furthermore, the regions in parameter space where Hilbert space fragmentation occurs in the clean system (leading to Krylov subspaces exhibiting frozen dynamics, cellular automation, and subspaces exhibiting signs of ergodic behavior) may also be stabilized by the addition of disorder. This leads to the emergence of exotic dynamics within the Krylov subspace.

cond-mat.stat-mech↗

arXiv2022

Coupled Fredkin and Motzkin chains from quantum six- and nineteen-vertex models

We generalize the area-law violating models of Fredkin and Motzkin spin chains into two dimensions by building quantum six- and nineteen-vertex models with correlated interactions. The Hamiltonian is frustration free, and its projectors generate ergodic dynamics within the subspace of height configuration that are non negative. The ground state is a volume- and color-weighted superposition of classical bi-color vertex configurations with non-negative heights in the bulk and zero height on the boundary. The entanglement entropy between subsystems has a phase transition as the $q$-deformation parameter is tuned, which is shown to be robust in the presence of an external field acting on the color degree of freedom. The ground state undergoes a quantum phase transition between area- and volume-law entanglement phases with a critical point where entanglement entropy scales as a function $L\log L$ of the linear system size $L$. Intermediate power law scalings between $L\log L$ and $L^2$ can be achieved with an inhomogeneous deformation parameter that approaches 1 at different rates in the thermodynamic limit. For the $q>1$ phase, we construct a variational wave function that establishes an upper bound on the spectral gap that scales as $q^{-L^3/8}$.

quant-ph↗

arXiv2022

Quantum lozenge tiling and entanglement phase transition

While volume violation of area law has been exhibited in several quantum spin chains, the construction of a corresponding ground state in higher dimensions, entangled in more than one direction, has been an open problem. Here we construct a 2D frustration-free Hamiltonian with maximal violation of the area law. We do so by building a quantum model of random surfaces with color degree of freedom that can be viewed as a collection of colored Dyck paths. The Hamiltonian may be viewed as a 2D generalization of the Fredkin spin chain. It relates all the colored random surface configurations subject to a Dirichlet boundary condition and hard wall constraint from below to one another, and the ground state is therefore a superposition of all such classical states and non-degenerate. Its entanglement entropy between subsystems undergoes a quantum phase transition as the deformation parameter is tuned. The area- and volume-law phases are similar to the one-dimensional model, while the critical point scales with the linear size of the system $L$ as $L\log L$. Further it is conjectured that similar models with entanglement phase transitions can be built in higher dimensions with even softer area law violations at the critical point.

quant-ph↗

arXiv2022

Arrested Development and Fragmentation in Strongly-Interacting Floquet Systems

We explore how interactions can facilitate classical like dynamics in models with sequentially activated hopping. Specifically, we add local and short range interaction terms to the Hamiltonian, and ask for conditions ensuring the evolution acts as a permutation on initial local number Fock states. We show that at certain values of hopping and interactions, determined by a set of Diophantine equations, such evolution can be realized. When only a subset of the Diophantine equations is satisfied the Hilbert space can be fragmented into frozen states, states obeying cellular automata like evolution and subspaces where evolution mixes Fock states and is associated with eigenstates exhibiting high entanglement entropy and level repulsion.

quant-ph↗

arXiv2021

Stirring by Staring: Measurement Induced Chirality

In quantum mechanics, the observer necessarily plays an active role in the dynamics of the system, making it difficult to probe a system without disturbing it. Here, we leverage this apparent difficulty as a tool for driving an initially trivial system into a chiral phase. In particular, we show that by utilizing a pattern of repeated occupation measurements we can produce chiral edge transport of fermions hopping on a Lieb lattice. The procedure is similar in spirit to the use of periodic driving to induce chiral edge transport in Floquet topological insulators, while also exhibiting novel phenomena due to the non-unitary nature of the quantum measurements. We study in detail the dependence of the procedure on measurement frequency, showing that in the Zeno limit the system can be described by a classical stochastic dynamics, yielding protected transport. As the frequency of measurements is reduced, the charge flow is reduced and vanishes when no measurements are done.

quant-ph↗

arXiv2021

Freezing of a disorder induced quantum spin liquid

$\rm{Sr_2CuTe_{0.5}W_{0.5}O_6}$ is a square-lattice magnet with super-exchange between S=1/2 $\rm{Cu^{2+}}$ spins mediated by randomly distributed Te and W ions. Here, using sub-K temperature and 20 $\rm{\mu}$eV energy resolution neutron scattering experiments we show that this system transits from a gapless disorder-induced quantum spin liquid to a new quantum state below $\rm{T_f}$ = 1.7(1) K, exhibiting a weak frozen moment of /S ~ 0.1 and low energy dynamic susceptibility,${\chi}''({\hbar\omega})$ linear in energy which is surprising for such a weak freezing in this highly fluctuating quantum regime.

cond-mat.mtrl-sci↗

arXiv2020

Quantum wakes in lattice fermions

The wake following a vessel in water is a signature interference effect of moving bodies, and, as described by Lord Kelvin, is contained within a constant universal angle. However, wakes may accompany different kinds of moving disturbances in other situations and even in lattice systems. Here, we investigate the effect of moving disturbances on a Fermi lattice gas of ultracold atoms and analyze the novel types of wake patterns that may occur. We show how at half-filling, the wake angles are dominated by the ratio of the hopping energy to the velocity of the disturbance and on the angle of motion relative to the lattice direction. Moreover, we study the difference between wakes left behind a moving particle detector versus that of a moving potential or a moving particle extractor. We show that these scenarios exhibit dramatically different behavior at half-filling, with the "measurement wake" following an idealized detector vanishing, though the motion of the detector does still leaves a trace through a "fluctuation wake." Finally, we discuss the experimental requirements to observe our predictions in ultracold fermionic atoms in optical lattices.

cond-mat.quant-gas↗