Wigner quasi-probability distribution for symmetric multi-quDit systems and their generalized heat kernel
- URL: http://arxiv.org/abs/2507.14866v1
- Date: Sun, 20 Jul 2025 08:26:28 GMT
- Title: Wigner quasi-probability distribution for symmetric multi-quDit systems and their generalized heat kernel
- Authors: Manuel Calixto, Julio Guerrero,
- Abstract summary: We analyze the phase-space structure of Schr"odinger $U(D)$-spin cat states.<n>We compute the generalized heat kernel relating two quasi-probability distributions $mathcalF(s)_rho$ and $mathcalF(s')_rho$.
- Score: 0.0
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: For a symmetric $N$-quDit system described by a density matrix $\rho$, we construct a one-parameter $s$ family $\mathcal{F}^{(s)}_\rho$ of quasi-probability distributions through generalized Fano multipole operators and Stratonovich-Weyl kernels. The corresponding phase space is the complex projective ${C}P^{D-1}=U(D)/U(D-1)\times U(1)$, related to fully symmetric irreducible representations of the unitary group $U(D)$. For the particular cases $D=2$ (qubits) and $D=3$ (qutrits), we analyze the phase-space structure of Schr\"odinger $U(D)$-spin cat (parity adapted coherent) states and we provide plots of the corresponding Wigner $\mathcal{F}^{(0)}_\rho$ function. We examine the connection between non-classical behavior and the negativity of the Wigner function. We also compute the generalized heat kernel relating two quasi-probability distributions $\mathcal{F}^{(s)}_\rho$ and $\mathcal{F}^{(s')}_\rho$, with $t=(s'-s)/2$ playing the role of ``time'', together with their twisted Moyal product in terms of a trikernel. In the thermodynamic limit $N\to\infty$, we recover the usual Gaussian smoothing for $s'>s$. A diagramatic interpretation of the phase-space construction in terms of Young tableaux is also provided.
Related papers
- Leading and beyond leading-order spectral form factor in chaotic quantum many-body systems across all Dyson symmetry classes [8.105213101498085]
We show the emergence of random matrix theory (RMT) spectral correlations in the chaotic phase of generic periodically kicked interacting many-body systems.<n>We analytically calculating spectral form factor (SFF), $K(t)$, up to two leading orders in time, $t$.<n>Our derivation only assumes random phase approximation to enable ensemble average.
arXiv Detail & Related papers (2025-02-06T15:37:18Z) - 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) - Random-Matrix Model for Thermalization [0.0]
Isolated quantum system said to thermalize if $rm Tr (A rho(t)) to rm Tr (A rho_rm eq)$ for time.
$rho_rm eq(infty)$ is the time-independent density matrix.
arXiv Detail & Related papers (2022-11-22T10:43:29Z) - Near-optimal fitting of ellipsoids to random points [68.12685213894112]
A basic problem of fitting an ellipsoid to random points has connections to low-rank matrix decompositions, independent component analysis, and principal component analysis.
We resolve this conjecture up to logarithmic factors by constructing a fitting ellipsoid for some $n = Omega(, d2/mathrmpolylog(d),)$.
Our proof demonstrates feasibility of the least squares construction of Saunderson et al. using a convenient decomposition of a certain non-standard random matrix.
arXiv Detail & Related papers (2022-08-19T18:00:34Z) - Classical shadows of fermions with particle number symmetry [0.0]
We provide an estimator for any $k$-RDM with $mathcalO(k2eta)$ classical complexity.
Our method, in the worst-case of half-filling, still provides a factor of $4k$ advantage in sample complexity.
arXiv Detail & Related papers (2022-08-18T17:11:12Z) - Learning a Single Neuron with Adversarial Label Noise via Gradient
Descent [50.659479930171585]
We study a function of the form $mathbfxmapstosigma(mathbfwcdotmathbfx)$ for monotone activations.
The goal of the learner is to output a hypothesis vector $mathbfw$ that $F(mathbbw)=C, epsilon$ with high probability.
arXiv Detail & Related papers (2022-06-17T17:55:43Z) - Markovian Repeated Interaction Quantum Systems [0.0]
We study a class of dynamical semigroups $(mathbbLn)_ninmathbbN$ that emerge, by a Feynman--Kac type formalism, from a random quantum dynamical system.
As a physical application, we consider the case where the $mathcalL_omega$'s are the reduced dynamical maps describing the repeated interactions of a system with thermal probes.
arXiv Detail & Related papers (2022-02-10T20:52:40Z) - 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) - Spectral properties of sample covariance matrices arising from random
matrices with independent non identically distributed columns [50.053491972003656]
It was previously shown that the functionals $texttr(AR(z))$, for $R(z) = (frac1nXXT- zI_p)-1$ and $Ain mathcal M_p$ deterministic, have a standard deviation of order $O(|A|_* / sqrt n)$.
Here, we show that $|mathbb E[R(z)] - tilde R(z)|_F
arXiv Detail & Related papers (2021-09-06T14:21:43Z) - Kernel Thinning [26.25415159542831]
kernel thinning is a new procedure for compressing a distribution $mathbbP$ more effectively than i.i.d. sampling or standard thinning.
We derive explicit non-asymptotic maximum mean discrepancy bounds for Gaussian, Mat'ern, and B-spline kernels.
arXiv Detail & Related papers (2021-05-12T17:56:42Z) - Stochastic behavior of outcome of Schur-Weyl duality measurement [45.41082277680607]
We focus on the measurement defined by the decomposition based on Schur-Weyl duality on $n$ qubits.
We derive various types of distribution including a kind of central limit when $n$ goes to infinity.
arXiv Detail & Related papers (2021-04-26T15:03:08Z) - Linear Time Sinkhorn Divergences using Positive Features [51.50788603386766]
Solving optimal transport with an entropic regularization requires computing a $ntimes n$ kernel matrix that is repeatedly applied to a vector.
We propose to use instead ground costs of the form $c(x,y)=-logdotpvarphi(x)varphi(y)$ where $varphi$ is a map from the ground space onto the positive orthant $RRr_+$, with $rll n$.
arXiv Detail & Related papers (2020-06-12T10:21:40Z)
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.