KPZ Superdiffusion of Local Correlators in Diffusive Random Quantum Circuits
- URL: http://arxiv.org/abs/2608.06459v1
- Date: Thu, 06 Aug 2026 18:00:02 GMT
- Title: KPZ Superdiffusion of Local Correlators in Diffusive Random Quantum Circuits
- Abstract summary: We find Kardar-Parisi-Zhang scaling in the wandering statistics of the normalized spatial distribution $p(x,t)propto |G(x,t)|2$.<n>In particular, its center $langle x(t)rangleequivsum_x x, p(x,t)$ wanders on a length-scale $mathcalO(t2/3)$, while sample-to-sample fluctuations of $-logsum_x |G(x,t)|2$ scale as
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: We study the single-particle Green's function $G(x,t)=\langle σ^-_x(0)σ^+_0(t)\rangle$ in one-dimensional particle-number-conserving random unitary circuits coupled to an external bath. For fixed spacetime disorder, we argue that $G(x,t)$ is governed, in both the strong- and weak-noise limits, by directed waves in a random medium. We find Kardar-Parisi-Zhang (KPZ) scaling in the wandering statistics of the normalized spatial distribution $p(x,t)\propto |G(x,t)|^2$ and in the associated free energy. In particular, its center $\langle x(t)\rangle\equiv\sum_x x\, p(x,t)$ wanders on a length-scale $\mathcal{O}(t^{2/3})$, while sample-to-sample fluctuations of $-\log\sum_x |G(x,t)|^2$ scale as $t^{1/3}$. At weak noise $γ\ll 1$, the crossover to the strong-disorder fixed point occurs at a parametrically long time $\mathcal{O}(γ^{-3/2})$. These predictions are confirmed numerically using tensor-network simulations of the noisy operator dynamics in individual circuits at moderate noise, and of a phase-annealed proxy retaining hopping disorder at weak noise.
Related papers
- OAM-Induced Lattice Rotation Reveals a Fractional Optimum in Fault-Tolerant GKP Quantum Sensing [0.0]
We establish that orbital-angular-momentum encoding and Gottesman-Kitaev-Preskill (GKP) lattice geometry are structurally coupled.<n>Using an end-to-end differentiable Strawberry Fields--TensorFlow circuit, we jointly optimise $ell$, the lattice aspect ratio $r$, and the finite-energy envelope $$ to maximise quantum Fisher information.
arXiv Detail & Related papers (2026-05-13T09:49:16Z) - The Wristband Gaussian Loss: Deterministic, Composable Latents via a Sphere-Interval Decomposition [1.0195618602298684]
Wristband Gaussian Loss is a deterministic batch loss for Gaussianizing point embeddings without sampling, KL terms, or iterative transport.<n>We compute this reflected- kernel objective in two ways: a nearest three-image pairwise truncation at $O(N2 d)$, and a spectral Neumann path joining angular and radial Mercer modes.<n>A 1D Wasserstein radial term and a moment penalty serve as finite-sample accelerators with the same optimum, and Monte-Carlo$ turns the components into a single standardized statistic.
arXiv Detail & Related papers (2026-05-09T07:25:37Z) - Quantum Brownian motion with non-Gaussian noises: Fluctuation-Dissipation Relation and nonlinear Langevin equation [0.0]
We consider the quantum Brownian motion (QBM) model with one oscillator as the system.<n>The influence action $S_IF$ is calculated using a perturbative expansion in $$.<n>The non-Gaussian noise kernel gives rise to non-zero three-point correlation function of the corresponding force.
arXiv Detail & Related papers (2026-02-11T02:03:26Z) - Privacy Loss of Noise Perturbation via Concentration Analysis of A Product Measure [9.081364242189691]
In this paper, we propose a novel scheme to generate $mathbfn$ by leveraging the fact that the noise is typically spherically symmetric.<n>Under the same $(,)$-DP guarantee, our mechanism yields a smaller expected noise magnitude than the classic Gaussian noise in high dimensions.
arXiv Detail & Related papers (2025-12-06T02:55:46Z) - Mesoscopic Fluctuations and Multifractality at and across Measurement-Induced Phase Transition [46.176861415532095]
We explore statistical fluctuations over the ensemble of quantum trajectories in a model of two-dimensional free fermions.<n>Our results exhibit a remarkable analogy to Anderson localization, with $G_AB$ corresponding to two-terminal conductance.<n>Our findings lay the groundwork for mesoscopic theory of monitored systems, paving the way for various extensions.
arXiv Detail & Related papers (2025-07-15T13:44:14Z) - Proving the Limited Scalability of Centralized Distributed Optimization via a New Lower Bound Construction [57.93371273485736]
We consider a centralized distributed learning setup where all workers jointly find an unbiased bound LDeltaepsilon2,$ better poly-logarithmically in $n$, even in the homogeneous (i.i.d.) case, where all workers access the same distribution.
arXiv Detail & Related papers (2025-06-30T13:27:39Z) - Dimension-free Private Mean Estimation for Anisotropic Distributions [55.86374912608193]
Previous private estimators on distributions over $mathRd suffer from a curse of dimensionality.
We present an algorithm whose sample complexity has improved dependence on dimension.
arXiv Detail & Related papers (2024-11-01T17:59:53Z) - A Unified Framework for Uniform Signal Recovery in Nonlinear Generative
Compressed Sensing [68.80803866919123]
Under nonlinear measurements, most prior results are non-uniform, i.e., they hold with high probability for a fixed $mathbfx*$ rather than for all $mathbfx*$ simultaneously.
Our framework accommodates GCS with 1-bit/uniformly quantized observations and single index models as canonical examples.
We also develop a concentration inequality that produces tighter bounds for product processes whose index sets have low metric entropy.
arXiv Detail & Related papers (2023-09-25T17:54:19Z) - Measurement-induced phase transition for free fermions above one dimension [46.176861415532095]
Theory of the measurement-induced entanglement phase transition for free-fermion models in $d>1$ dimensions is developed.
Critical point separates a gapless phase with $elld-1 ln ell$ scaling of the second cumulant of the particle number and of the entanglement entropy.
arXiv Detail & Related papers (2023-09-21T18:11:04Z) - Random quantum circuits transform local noise into global white noise [118.18170052022323]
We study the distribution over measurement outcomes of noisy random quantum circuits in the low-fidelity regime.
For local noise that is sufficiently weak and unital, correlations (measured by the linear cross-entropy benchmark) between the output distribution $p_textnoisy$ of a generic noisy circuit instance shrink exponentially.
If the noise is incoherent, the output distribution approaches the uniform distribution $p_textunif$ at precisely the same rate.
arXiv Detail & Related papers (2021-11-29T19:26:28Z) - Random matrices in service of ML footprint: ternary random features with
no performance loss [55.30329197651178]
We show that the eigenspectrum of $bf K$ is independent of the distribution of the i.i.d. entries of $bf w$.
We propose a novel random technique, called Ternary Random Feature (TRF)
The computation of the proposed random features requires no multiplication and a factor of $b$ less bits for storage compared to classical random features.
arXiv Detail & Related papers (2021-10-05T09:33:49Z) - Agnostic Learning of a Single Neuron with Gradient Descent [92.7662890047311]
We consider the problem of learning the best-fitting single neuron as measured by the expected square loss.
For the ReLU activation, our population risk guarantee is $O(mathsfOPT1/2)+epsilon$.
For the ReLU activation, our population risk guarantee is $O(mathsfOPT1/2)+epsilon$.
arXiv Detail & Related papers (2020-05-29T07:20:35Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.