Detecting bipartite entanglement with PnCP maps and non-negative polynomials
- URL: http://arxiv.org/abs/2605.30426v1
- Date: Thu, 28 May 2026 18:00:06 GMT
- Title: Detecting bipartite entanglement with PnCP maps and non-negative polynomials
- Abstract summary: We show how to generate PnCP maps based on the construction of certain positive non-Sum-of-Squares.<n>We numerically investigate their entanglement power, demonstrating notably that they are capable of detecting entangled states.
- Score: 0.7036032466145112
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Positive non-Completely Positive (PnCP) maps are an essential tool to detect entanglement since their characterization is a dual aspect of the separability problem. A recent algorithm proposed by Kelp et al. explains how to generate PnCP maps based on the construction of certain positive non-Sum-of-Squares polynomials. We implement this algorithm in a numerically robust way and propose a working version on GitHub. We theoretically demonstrate that the maps produced by the algorithm are indecomposable, localized on the boundary of the positive cone and show that they are inequivalent with most other known PnCP maps. We numerically investigate their entanglement power, demonstrating notably that they are capable of detecting PPT entangled states that most criteria fail to detect.
Related papers
- Generating Non-Decomposable Maps with Differentiable Semidefinite Programming [0.6157382820537719]
We introduce an optimization framework for generating positive non-decomposable maps under flexible structural constraints.<n>We show that the same approach can be adapted to explore open questions in quantum information theory.
arXiv Detail & Related papers (2026-05-14T10:01:29Z) - Positive maps and extendibility hierarchies from copositive matrices [4.914288166307964]
This work introduces and systematically studies a new convex cone of PCOP (pairwise copositive)<n>We establish that this cone is dual to the cone of PCP (pairwise completely positive) and, critically, provides a complete characterization for the positivity of the broad class of covariant maps.
arXiv Detail & Related papers (2025-09-18T17:54:09Z) - Revisiting Atomic Patterns for Elliptic Curve Scalar Multiplication Revealing Inherent Vulnerability to Simple SCA [0.0]
kP operation is the basic operation in all Elliptic Curve based cryptographic protocols.<n>In this work, we investigated the resistance of a kP algorithm implemented in hardware using Longa's atomic patterns.
arXiv Detail & Related papers (2024-12-04T11:13:04Z) - Linearized Wasserstein dimensionality reduction with approximation
guarantees [65.16758672591365]
LOT Wassmap is a computationally feasible algorithm to uncover low-dimensional structures in the Wasserstein space.
We show that LOT Wassmap attains correct embeddings and that the quality improves with increased sample size.
We also show how LOT Wassmap significantly reduces the computational cost when compared to algorithms that depend on pairwise distance computations.
arXiv Detail & Related papers (2023-02-14T22:12:16Z) - Efficient Graph Field Integrators Meet Point Clouds [59.27295475120132]
We present two new classes of algorithms for efficient field integration on graphs encoding point clouds.
The first class, SeparatorFactorization(SF), leverages the bounded genus of point cloud mesh graphs, while the second class, RFDiffusion(RFD), uses popular epsilon-nearest-neighbor graph representations for point clouds.
arXiv Detail & Related papers (2023-02-02T08:33:36Z) - Linear maps as sufficient criteria for entanglement depth and
compatibility in many-body systems [0.0]
We extend results presented in [Phys. Rev A 93, 042335], where sufficient separability criteria for bipartite systems were derived.
We derive criteria to detect arbitrary $(N-n)$-entanglement depth tailored to states in close vicinity of the completely depolarized state.
We also provide separability (or $1$- entanglement depth) conditions in the symmetric sector, including for diagonal states.
arXiv Detail & Related papers (2022-11-05T10:42:24Z) - Reinforcement Learning from Partial Observation: Linear Function Approximation with Provable Sample Efficiency [111.83670279016599]
We study reinforcement learning for partially observed decision processes (POMDPs) with infinite observation and state spaces.
We make the first attempt at partial observability and function approximation for a class of POMDPs with a linear structure.
arXiv Detail & Related papers (2022-04-20T21:15:38Z) - Near-optimal estimation of smooth transport maps with kernel
sums-of-squares [81.02564078640275]
Under smoothness conditions, the squared Wasserstein distance between two distributions could be efficiently computed with appealing statistical error upper bounds.
The object of interest for applications such as generative modeling is the underlying optimal transport map.
We propose the first tractable algorithm for which the statistical $L2$ error on the maps nearly matches the existing minimax lower-bounds for smooth map estimation.
arXiv Detail & Related papers (2021-12-03T13:45:36Z) - Probabilistic Generating Circuits [50.98473654244851]
We propose probabilistic generating circuits (PGCs) for their efficient representation.
PGCs are not just a theoretical framework that unifies vastly different existing models, but also show huge potential in modeling realistic data.
We exhibit a simple class of PGCs that are not trivially subsumed by simple combinations of PCs and DPPs, and obtain competitive performance on a suite of density estimation benchmarks.
arXiv Detail & Related papers (2021-02-19T07:06:53Z) - Generating and detecting bound entanglement in two-qutrits using a
family of indecomposable positive maps [0.0]
We propose an indecomposable positive map for two-qutrit systems.
A corresponding witness operator is constructed and shown to be weakly optimal.
We find a new entangled state which is not detectable by certain other well-known entanglement detection criteria.
arXiv Detail & Related papers (2020-08-29T12:52:27Z) - Decomposable Pauli diagonal maps and Tensor Squares of Qubit Maps [91.3755431537592]
We show that any positive product of a qubit map with itself is decomposable.
We characterize the cone of decomposable ququart Pauli diagonal maps.
arXiv Detail & Related papers (2020-06-25T16:39:32Z) - Determinantal Point Processes in Randomized Numerical Linear Algebra [80.27102478796613]
Numerical Linear Algebra (RandNLA) uses randomness to develop improved algorithms for matrix problems that arise in scientific computing, data science, machine learning, etc.
Recent work has uncovered deep and fruitful connections between DPPs and RandNLA which lead to new guarantees and improved algorithms.
arXiv Detail & Related papers (2020-05-07T00:39:52Z)
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.