Evolution of the eigenvalues and eigenstates of the single-particle reduced density operator during two-particle scattering
- URL: http://arxiv.org/abs/2512.02239v1
- Date: Mon, 01 Dec 2025 22:07:24 GMT
- Title: Evolution of the eigenvalues and eigenstates of the single-particle reduced density operator during two-particle scattering
- Authors: Arsam Najafian, Mark Van Raamsdonk,
- Abstract summary: We present explicit results for the time-dependence of eigenvalues and eigenstates for simple scattering experiments in one and two dimensions.<n>This provides a time-resolved picture of the scattering process, showing in detail how an initial state described entirely in terms of continuous parameters evolves into a discrete set of possible outcomes.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: A particle initially in a pure state but interacting with some environment evolves into a discrete ensemble of pure states, the eigenstates of its reduced density operator, with ensemble probabilities given by the corresponding eigenvalues. In this work, we use numerics to present explicit results for the time-dependence of these eigenvalues and eigenstates for simple scattering experiments in one and two dimensions. This provides a time-resolved picture of the scattering process, showing in detail how an initial state described entirely in terms of continuous parameters evolves into a discrete set of possible outcomes, each with an associated probability and time-evolving wavefunction. We find that for scattering of Gaussian wavepackets in one dimension, the late time spectrum is dominated by two large eigenvalues nearly equal to the transmission and reflection probabilities associated with the central value of momentum. The corresponding eigenstates appear as single-peaked reflected or transmitted wavepackets. The remaining smaller eigenvalues, which increase to a maximum during scattering and then decrease to small values, correspond to reflected or transmitted wavepackets with multiple spatially separated parts. In this case and also for two-dimensional scattering, we find that successively smaller eigenvalues correspond to probability distributions with successively more peaks. These multi-peaked states correspond to outcomes of the scattering experiment where a particle initially in a single wavepacket ends up in a superposition of separated wavepackets after scattering.
Related papers
- Dimension-free error estimate for diffusion model and optimal scheduling [22.20348860913421]
Diffusion generative models have emerged as powerful tools for producing synthetic data from an empirically observed distribution.<n>Previous analyses have quantified the error between the generated and the true data distributions in terms of Wasserstein distance or Kullback-Leibler divergence.<n>In this work, we derive an explicit, dimension-free bound on the discrepancy between the generated and the true data distributions.
arXiv Detail & Related papers (2025-12-01T15:58:20Z) - Unraveling superradiance: Entanglement and mutual information in collective decay [0.0]
We study the collective decay of an initially inverted ensemble of two-level emitters in two distinct scenarios.<n>We investigate entanglement and classical correlations along individual quantum trajectories over time.<n>We provide a purely classical theory for the burst in squeezed superradiance, which is both intuitive and exact for a large number of emitters.
arXiv Detail & Related papers (2025-05-19T17:36:37Z) - Your Absorbing Discrete Diffusion Secretly Models the Conditional Distributions of Clean Data [55.54827581105283]
We show that the concrete score in absorbing diffusion can be expressed as conditional probabilities of clean data.<n>We propose a dedicated diffusion model without time-condition that characterizes the time-independent conditional probabilities.<n>Our models achieve SOTA performance among diffusion models on 5 zero-shot language modeling benchmarks.
arXiv Detail & Related papers (2024-06-06T04:22:11Z) - Arbitrary relaxation rate under non-Hermitian matrix iterations [0.0]
We study the exponential relaxation of observables propagated with a non-Hermitian transfer matrix.
We show that the decay rate can be an arbitrary value between the second largest eigenvalue and the largest value in the pseudospectrum.
arXiv Detail & Related papers (2023-12-22T11:18:35Z) - Potential scattering in $L^2$ space: (2) Rigorous scattering probability
of wave packets [0.0]
A breaking of an associativity is observed in scalar products with stationary scattering states in a majority of short-range potentials.
The results also demonstrate an interference term displaying unique behavior at an extreme forward direction.
arXiv Detail & Related papers (2023-05-26T14:23:50Z) - Upper Bounds on the Distillable Randomness of Bipartite Quantum States [15.208790082352351]
distillable randomness of a bipartite quantum state is an information-theoretic quantity.
We prove measures of classical correlations and prove a number of their properties.
We then further bound these measures from above by some that are efficiently computable by means of semi-definite programming.
arXiv Detail & Related papers (2022-12-18T12:06:25Z) - Optimal Second-Order Rates for Quantum Soft Covering and Privacy
Amplification [19.624719072006936]
We study quantum soft covering and privacy amplification against quantum side information.
For both tasks, we use trace distance to measure the closeness between the processed state and the ideal target state.
Our results extend to the moderate deviation regime, which are the optimal rates when the trace distances vanish at sub-exponential speed.
arXiv Detail & Related papers (2022-02-23T16:02:31Z) - Observation-dependent suppression and enhancement of two-photon
coincidences by tailored losses [68.8204255655161]
Hong-Ou-Mandel (HOM) effect can lead to a perfect suppression of two-particle coincidences between the output ports of a balanced beam splitter.
In this work, we demonstrate experimentally that the two-particle coincidence statistics of two bosons can instead be seamlessly tuned to substantial enhancement.
Our findings reveal a new approach to harnessing non-Hermitian settings for the manipulation of multi-particle quantum states.
arXiv Detail & Related papers (2021-05-12T06:47:35Z) - Compressive Privatization: Sparse Distribution Estimation under Locally
Differentially Privacy [18.43218511751587]
We show that as long as the target distribution is sparse or approximately sparse, the number of samples needed could be significantly reduced.
Our mechanism does privatization and dimensionality reduction simultaneously, and the sample complexity will only depend on the reduced dimensionality.
arXiv Detail & Related papers (2020-12-03T17:14:23Z) - Quantum dynamics on a lossy non-Hermitian lattice [12.373452169290541]
We investigate quantum dynamics of a quantum walker on a finite bipartite non-Hermitian lattice.
Quantum walker initially located on one of the non-leaky sites will finally disappear after a length of evolution time.
The intriguing behavior of the resultant decay probability distribution is intimately related to the existence and specific property of edge states.
arXiv Detail & Related papers (2020-11-15T03:51:13Z) - Absorption and analysis of unbound quantum particles -- one by one [0.0]
We present methods for calculating differential probabilities for unbound particles.
In addition to attenuating outgoing waves, this absorber is also used to probe them by projection onto single-particle scattering states.
We show how energy distributions of unbound particles may be determined on numerical domains considerably smaller than the actual extension of the system.
arXiv Detail & Related papers (2020-10-06T12:48:03Z) - Unbalanced Sobolev Descent [31.777218621726284]
We introduce Unbalanced Sobolev Descent (USD), a particle descent algorithm for transporting a high dimensional source distribution to a target distribution that does not necessarily have the same mass.
USD transports particles along flows of the witness function of the Sobolev-Fisher discrepancy (advection step) and reweighs the mass of particles with respect to this witness function (reaction step)
We show on synthetic examples that USD transports distributions with or without conservation of mass faster than previous particle descent algorithms.
arXiv Detail & Related papers (2020-09-29T16:43:38Z) - Learning interaction kernels in stochastic systems of interacting
particles from multiple trajectories [13.3638879601361]
We consider systems of interacting particles or agents, with dynamics determined by an interaction kernel.
We introduce a nonparametric inference approach to this inverse problem, based on a regularized maximum likelihood estimator.
We show that a coercivity condition enables us to control the condition number of this problem and prove the consistency of our estimator.
arXiv Detail & Related papers (2020-07-30T01:28:06Z)
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.