Fast quantum state discrimination with nonlinear PTP channels
- URL: http://arxiv.org/abs/2111.05977v2
- Date: Tue, 4 Jul 2023 20:59:13 GMT
- Title: Fast quantum state discrimination with nonlinear PTP channels
- Authors: Michael R. Geller
- Abstract summary: We investigate models of nonlinear quantum computation based on deterministic positive trace-preserving (PTP) channels and evolution equations.
PTP channels support Bloch ball torsion and other distortions studied previously, where it has been shown that such nonlinearity can be used to increase the separation between a pair of close qubit states.
We argue that this operation can be made robust to noise by using dissipation to induce a bifurcation to a novel phase where a pair of attracting fixed points create an intrinsically fault-tolerant nonlinear state discriminator.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: We investigate models of nonlinear quantum computation based on deterministic
positive trace-preserving (PTP) channels and evolution equations. The models
are defined in any finite Hilbert space, but the main results are for dimension
$N \! = \! 2$. For every normalizable linear or nonlinear positive map $\phi$
on bounded linear operators $X$, there is an associated normalized PTP channel
$ \phi(X) / {\rm tr}[\phi(X)]$. Normalized PTP channels include unitary mean
field theories, such as the Gross-Pitaevskii equation for interacting bosons,
as well as models of linear and nonlinear dissipation. They classify into 4
types, yielding 3 distinct forms of nonlinearity whose computational power we
explore. In the qubit case these channels support Bloch ball torsion and other
distortions studied previously, where it has been shown that such nonlinearity
can be used to increase the separation between a pair of close qubit states,
suggesting an exponential speedup for state discrimination. Building on this
idea, we argue that this operation can be made robust to noise by using
dissipation to induce a bifurcation to a novel phase where a pair of attracting
fixed points create an intrinsically fault-tolerant nonlinear state
discriminator.
Related papers
- Learning with Norm Constrained, Over-parameterized, Two-layer Neural Networks [54.177130905659155]
Recent studies show that a reproducing kernel Hilbert space (RKHS) is not a suitable space to model functions by neural networks.
In this paper, we study a suitable function space for over- parameterized two-layer neural networks with bounded norms.
arXiv Detail & Related papers (2024-04-29T15:04:07Z) - The Challenges of the Nonlinear Regime for Physics-Informed Neural Networks [0.0]
We show how the NTK perspective falls short in the nonlinear scenario.
We explore the convergence guarantees of such methods in both linear and nonlinear cases.
arXiv Detail & Related papers (2024-02-06T10:24:36Z) - Conformal duality of the nonlinear Schrödinger equation: Theory and applications to parameter estimation [0.09782246441301058]
We present the unified theory of the nonlinear Schr"odinger equation (NLSE)
All stationary solutions of the local one-dimensional cubic-quintic NLSE can be classified according to a single number called the cross-ratio.
Any two solutions with the same cross-ratio can be converted into one another using a conformal transformation.
arXiv Detail & Related papers (2023-06-30T15:03:51Z) - Dynamical chaos in nonlinear Schr\"odinger models with subquadratic
power nonlinearity [137.6408511310322]
We deal with a class of nonlinear Schr"odinger lattices with random potential and subquadratic power nonlinearity.
We show that the spreading process is subdiffusive and has complex microscopic organization.
The limit of quadratic power nonlinearity is also discussed and shown to result in a delocalization border.
arXiv Detail & Related papers (2023-01-20T16:45:36Z) - Nonlinear perturbation of a high-order exceptional point: skin discrete
breathers and the hierarchical power-law scaling [5.249388938927588]
We study the nonlinear perturbation of a high-order exceptional point (EP) of the order equal to the system site number $L$ in a Hatano-Nelson model.
We find a class of discrete breathers that aggregate to one boundary, here named as it skin discrete breathers (SDBs)
The nonlinear spectrum of these SDBs shows a hierarchical power-law scaling near the EP.
arXiv Detail & Related papers (2022-12-28T09:55:58Z) - Nonlinear and non-CP gates for Bloch vector amplification [0.0]
We discuss the complementary state-preparation protocol for qubits at the center of the Bloch ball, r=0, based on increasing or amplifying |r| to its desired value, then rotating.
Amplification can be achieved with a linear Markovian CPTP channel by placing the channel's fixed point away from r=0, making it nonunital, but the resulting gate suffers from a critical slowing down as that fixed point is approached.
Here we consider alternative designs based on linear and nonlinear Markovian PTP channels, which offer benefits relative to linear CPTP channels, namely fast Bloch vector amplification without deceleration.
arXiv Detail & Related papers (2022-08-03T01:46:24Z) - Matching Normalizing Flows and Probability Paths on Manifolds [57.95251557443005]
Continuous Normalizing Flows (CNFs) are generative models that transform a prior distribution to a model distribution by solving an ordinary differential equation (ODE)
We propose to train CNFs by minimizing probability path divergence (PPD), a novel family of divergences between the probability density path generated by the CNF and a target probability density path.
We show that CNFs learned by minimizing PPD achieve state-of-the-art results in likelihoods and sample quality on existing low-dimensional manifold benchmarks.
arXiv Detail & Related papers (2022-07-11T08:50:19Z) - Multipartite spatial entanglement generated by concurrent nonlinear
processes [91.3755431537592]
Continuous variables multipartite entanglement is a key resource for quantum technologies.
This work considers the multipartite entanglement generated in separated spatial modes of the same light beam by three different parametric sources.
arXiv Detail & Related papers (2021-11-09T17:15:13Z) - Designing Kerr Interactions for Quantum Information Processing via
Counterrotating Terms of Asymmetric Josephson-Junction Loops [68.8204255655161]
static cavity nonlinearities typically limit the performance of bosonic quantum error-correcting codes.
Treating the nonlinearity as a perturbation, we derive effective Hamiltonians using the Schrieffer-Wolff transformation.
Results show that a cubic interaction allows to increase the effective rates of both linear and nonlinear operations.
arXiv Detail & Related papers (2021-07-14T15:11:05Z) - Probabilistic Circuits for Variational Inference in Discrete Graphical
Models [101.28528515775842]
Inference in discrete graphical models with variational methods is difficult.
Many sampling-based methods have been proposed for estimating Evidence Lower Bound (ELBO)
We propose a new approach that leverages the tractability of probabilistic circuit models, such as Sum Product Networks (SPN)
We show that selective-SPNs are suitable as an expressive variational distribution, and prove that when the log-density of the target model is aweighted the corresponding ELBO can be computed analytically.
arXiv Detail & Related papers (2020-10-22T05:04:38Z)
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.