Related papers: Detecting $k$-nonstretchability via a class of informationally complete symmetric measurements

Related papers

$\mathbb{R}^{2k}$ is Theoretically Large Enough for Embedding-based Top-$k$ Retrieval [99.8640829555514]
This paper studies the minimal dimension required to embed subset memberships ($m$ elements and $mchoose k$ subsets of at most $k$ elements) into vector spaces, denoted as Minimal Embeddable Dimension (MED)<n>The tight bounds of MED are derived theoretically and supported empirically for various notions of "distances" or "similarities," including the $ell$ metric, inner product and cosine similarity.
arXiv Detail & Related papers (2026-01-28T18:45:43Z)
$k$-Entanglement Measure for Multipartite Systems without Convex-Roof Extensions and its Evaluation [12.462680093105286]
Multipartite entanglement underpins quantum technologies but its study is limited by the lack of universal measures.<n>We introduce the first emphtrue $k$-entanglement measure, $E_w(k,n)$, which satisfies all axioms.<n>A universal algorithm evaluates arbitrary finite-dimensional states, with open-source software covering all partitions of four-qubit systems.
arXiv Detail & Related papers (2025-12-14T07:51:23Z)
Shallow IQP circuit and graph generation [37.067444579637076]
We introduce shallow instantaneous quantum-time circuits as generative graph models.<n>We study bipartite and ErdHos-R'enyi distributions through simulations and large-scale experiments.
arXiv Detail & Related papers (2025-11-07T14:28:56Z)
Enabling Pareto-Stationarity Exploration in Multi-Objective Reinforcement Learning: A Multi-Objective Weighted-Chebyshev Actor-Critic Approach [23.834874532235382]
We propose a weighted-ulineMulineActor-critic (MOCHA) algorithm for multi-objective reinforcement learning (MORL)<n>By carefully choosing learning rates, the sample complexity for each exploration can be given $tildemathcalO(epsilon-2)$.<n>The performance of MOCHA algorithm significantly outperforms other baseline MORL approaches.
arXiv Detail & Related papers (2025-07-29T00:11:59Z)
Detecting $k$-nonseparability and $k$-partite Entanglement with Generalized Skew Information and Mutually Unbiased Measurements [0.0]
Multipartite quantum entanglement is fundamental to the advancement of quantum science and technology.<n>We propose sufficient criteria for detecting $k$-nonseparability and $k$-partite entanglement.
arXiv Detail & Related papers (2025-05-20T01:46:47Z)
An Efficient Quantum Classifier Based on Hamiltonian Representations [50.467930253994155]
Quantum machine learning (QML) is a discipline that seeks to transfer the advantages of quantum computing to data-driven tasks.<n>We propose an efficient approach that circumvents the costs associated with data encoding by mapping inputs to a finite set of Pauli strings.<n>We evaluate our approach on text and image classification tasks, against well-established classical and quantum models.
arXiv Detail & Related papers (2025-04-13T11:49:53Z)
Entanglement-Assisted Coding for Arbitrary Linear Computations Over a Quantum MAC [34.32444379837011]
We study a linear computation problem over a quantum multiple access channel (LC-QMAC)<n>We propose an achievable scheme for LC-QMAC based on the stabilizer formalism and the ideas from entanglement-assisted quantum error-correcting codes (EAQECC)
arXiv Detail & Related papers (2025-01-27T18:35:33Z)
Sample-Efficient Quantum State Tomography for Structured Quantum States in One Dimension [25.333797381352973]
Many physical quantum states often exhibit certain low-dimensional structures that enable the development of efficient QST.<n>We show that the number of state copies to guarantee bounded recovery error of an MPO state with a constrained least-squares estimator depends on the probability distribution of the MPO.<n>We prove that only a number of state copies proportional to the number of independent parameters in the MPO is sufficient for a guaranteed recovery of any state represented by an MPO.
arXiv Detail & Related papers (2024-10-03T15:26:26Z)
Classical Bandit Algorithms for Entanglement Detection in Parameterized Qubit States [3.5502600490147196]
Entanglement is a key resource for a wide range of tasks in quantum information and computing. This paper highlights the potential for employing classical machine learning techniques for quantum entanglement detection.
arXiv Detail & Related papers (2024-06-28T08:26:47Z)
Geometry of degenerate quantum states, configurations of $m$-planes and invariants on complex Grassmannians [55.2480439325792]
We show how to reduce the geometry of degenerate states to the non-abelian connection $A$. We find independent invariants associated with each triple of subspaces. Some of them generalize the Berry-Pancharatnam phase, and some do not have analogues for 1-dimensional subspaces.
arXiv Detail & Related papers (2024-04-04T06:39:28Z)
Towards large-scale quantum optimization solvers with few qubits [59.63282173947468]
We introduce a variational quantum solver for optimizations over $m=mathcalO(nk)$ binary variables using only $n$ qubits, with tunable $k>1$. We analytically prove that the specific qubit-efficient encoding brings in a super-polynomial mitigation of barren plateaus as a built-in feature.
arXiv Detail & Related papers (2024-01-17T18:59:38Z)
Toward a classification of PT-symmetric quantum systems: From dissipative dynamics to topology and wormholes [0.0]
A symmetry classification of non-Hermitian systems leads to 38 universality classes. Under certain conditions, PT-symmetric systems are grouped into 24 universality classes. Different sectors of the PT-symmetric Hamiltonian may have different symmetries.
arXiv Detail & Related papers (2023-11-27T10:07:19Z)
Multipartite entanglement detection via generalized Wigner-Yanase skew information [7.222232547612572]
The detection of multipartite entanglement in multipartite quantum systems is a fundamental and key issue in quantum information theory. We develop two different approaches in form of inequalities to construct entanglement criteria, which are expressed in terms of the Wigner-Yanase skew information. Our results reveal some $k$-nonseparability and $k$-partite entanglement that remain undetected by other methods.
arXiv Detail & Related papers (2023-09-20T03:30:15Z)
Quantum Resources Required to Block-Encode a Matrix of Classical Data [56.508135743727934]
We provide circuit-level implementations and resource estimates for several methods of block-encoding a dense $Ntimes N$ matrix of classical data to precision $epsilon$. We examine resource tradeoffs between the different approaches and explore implementations of two separate models of quantum random access memory (QRAM) Our results go beyond simple query complexity and provide a clear picture into the resource costs when large amounts of classical data are assumed to be accessible to quantum algorithms.
arXiv Detail & Related papers (2022-06-07T18:00:01Z)
Detection of $k$-partite entanglement and $k$-nonseparability of multipartite quantum states [1.5125686694430571]
Identifying the $k$-partite entanglement and $k$-nonseparability of general $N$-partite quantum states are fundamental issues in quantum information theory. We present some simple and powerful $k$-partite entanglement and $k$-nonseparability criteria that works very well.
arXiv Detail & Related papers (2020-12-05T09:47:31Z)
Towards Assessment of Randomized Smoothing Mechanisms for Certifying Adversarial Robustness [50.96431444396752]
We argue that the main difficulty is how to assess the appropriateness of each randomized mechanism. We first conclude that the Gaussian mechanism is indeed an appropriate option to certify $ell$-norm. Surprisingly, we show that the Gaussian mechanism is also an appropriate option for certifying $ell_infty$-norm, instead of the Exponential mechanism.
arXiv Detail & Related papers (2020-05-15T03:54:53Z)

This list is automatically generated from the titles and abstracts of the papers in this site.