Witness expansion: A unified framework for analytical and measurable mixed-state resource detection
- URL: http://arxiv.org/abs/2606.27105v1
- Date: Thu, 25 Jun 2026 14:43:38 GMT
- Title: Witness expansion: A unified framework for analytical and measurable mixed-state resource detection
- Abstract summary: We propose a unified framework for constructing nonlinear criteria for detecting quantum resources associated with a well-defined free unitaries.<n>We show how several well-known resource quantities naturally emerge from our framework, including the $l$ norm of coherence, partial-transpose moments for entanglement, stabilizer entropy for nonstabilizerness (quantum magic) and fermionic antiflatness for fermionic non-Gaussianity.
- Score: 12.64780702558456
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Quantum information science aims to harness different kinds of quantum resources to accomplish specific information-processing tasks. These resources also play an increasingly important role in addressing fundamental questions concerning quantum phases and dynamics. Therefore, developing powerful and practical methods for identifying and detecting quantum resources is of great significance, with applications ranging from benchmarking quantum devices to understanding the fundamental structure of quantum theory. In this work, we propose witness expansion, a unified framework for constructing nonlinear criteria for detecting quantum resources that are associated with a well-defined group of free unitaries. These criteria apply to both pure and mixed quantum states and are based on polynomial functions of the target state, which can be estimated experimentally using multiple copies of the state and evaluated analytically in certain physical models. We show how several well-known resource-detection quantities naturally emerge from our framework, including the $l_2$ norm of coherence, partial-transpose moments for entanglement, stabilizer entropy for nonstabilizerness (quantum magic), and fermionic antiflatness for fermionic non-Gaussianity. Beyond recovering these existing structures, our framework also yields new criteria for detecting qubit and qudit magic states, substantially enhancing witness-based detection capabilities. In addition, it gives, to the best of our knowledge, the first analytical criterion for detecting mixed-state fermionic non-Gaussianity with respect to the convex hull of pure fermionic Gaussian states that remains nontrivial for arbitrary numbers of qubits, demonstrating the broad applicability and conceptual unifying power of the framework.
Related papers
- Quantum Hypergraph States: A Review [0.0]
We provide a compact overview of the formal structure, entanglement characteristics, and operational relevance of hypergraph states in quantum information theory.<n>A central focus is placed on their entanglement properties, including the classification under local unitary (LU)<n>Additional attention is given to the role of hypergraph states in error correction, and as a computational resource in measurement-based quantum computation.
arXiv Detail & Related papers (2026-03-11T16:02:39Z) - Hysteretic squashed entanglement in many-body quantum systems [42.085941481155295]
Entanglement in many-body quantum systems is distributed across spatial regions.<n>We propose hysteretic entanglement $T_sq$, a conditional entanglement that measures the genuine quantum correlations between two subregions.<n>We show that $T_sq$ can detect genuine quantum correlations across both adjacent and long-range subsystems.
arXiv Detail & Related papers (2026-03-10T17:00:49Z) - Digitized Counterdiabatic Quantum Feature Extraction [35.670314643295036]
We introduce a Hamiltonian-based quantum feature extraction method that generates complex features via the dynamics of $k$-local many-body spins Hamiltonians.<n>We assess the approach on high-dimensional, real-world datasets, including molecular toxicity classification and image recognition.<n>The results suggest that combining quantum and classical feature extraction can provide consistent improvements across diverse machine learning tasks.
arXiv Detail & Related papers (2025-10-15T17:59:35Z) - Towards Quantum Enhanced Adversarial Robustness with Rydberg Reservoir Learning [45.92935470813908]
Quantum computing reservoir (QRC) leverages the high-dimensional, nonlinear dynamics inherent in quantum many-body systems.<n>Recent studies indicate that perturbation quantums based on variational circuits remain susceptible to adversarials.<n>We investigate the first systematic evaluation of adversarial robustness in a QR based learning model.
arXiv Detail & Related papers (2025-10-15T12:17:23Z) - Resources for bosonic metrology: quantum-enhanced precision from a superselection rule perspective [0.0]
We present a unified framework for quantum metrology that encompasses all known precision-enhancing regimes.<n>We show how it encompasses both the discrete and the continuous limits of quantum optics.<n>We also develop strategies to optimize precision using arbitrary multimode entangled probe states.
arXiv Detail & Related papers (2025-07-17T15:54:34Z) - Fermionic Magic Resources of Quantum Many-Body Systems [0.0]
We develop a framework for quantifying fermionic magic resources, also referred to as fermionic non-Gaussianity.<n>FAF is an efficiently computable and experimentally accessible measure of non-Gaussianity.<n>We show that FAF detects phase transitions, reveals universal features of critical points, and uncovers special solvable points in many-body systems.
arXiv Detail & Related papers (2025-05-30T18:00:01Z) - Nuclear responses with neural-network quantum states [37.902436796793616]
We introduce a variational Monte Carlo framework that combines neural-network quantum states with the Lorentz integral transform technique.<n>We focus on the photoabsorption cross section of light nuclei, where benchmarks against numerically exact techniques are available.
arXiv Detail & Related papers (2025-04-28T18:57:21Z) - Extracting randomness from magic quantum states [3.9000096678531606]
We show that when a subsystem of a quantum state is measured, the resultant unmeasured part of the system can exhibit a high degree of randomness.<n>Our findings suggest an approach to quantifying correlations within magic quantum states beyond the conventional paradigm of entanglement.
arXiv Detail & Related papers (2024-02-15T18:33:21Z) - Quantifying High-Order Interdependencies in Entangled Quantum States [43.70611649100949]
We introduce the Q-information: an information-theoretic measure capable of distinguishing quantum states dominated by synergy or redundancy.
We show that quantum systems need at least four variables to exhibit high-order properties.
Overall, the Q-information sheds light on novel aspects of the internal organisation of quantum systems and their time evolution.
arXiv Detail & Related papers (2023-10-05T17:00:13Z) - Enhanced Entanglement in the Measurement-Altered Quantum Ising Chain [43.80709028066351]
Local quantum measurements do not simply disentangle degrees of freedom, but may actually strengthen the entanglement in the system.<n>This paper explores how a finite density of local measurement modifies a given state's entanglement structure.
arXiv Detail & Related papers (2023-10-04T09:51:00Z) - Quantification of Entanglement and Coherence with Purity Detection [16.01598003770752]
Entanglement and coherence are fundamental properties of quantum systems, promising to power near future quantum technologies.
Here, we demonstrate quantitative bounds to operationally useful entanglement and coherence.
Our research offers an efficient means of verifying large-scale quantum information processing.
arXiv Detail & Related papers (2023-08-14T11:03:40Z) - Quantum data learning for quantum simulations in high-energy physics [55.41644538483948]
We explore the applicability of quantum-data learning to practical problems in high-energy physics.
We make use of ansatz based on quantum convolutional neural networks and numerically show that it is capable of recognizing quantum phases of ground states.
The observation of non-trivial learning properties demonstrated in these benchmarks will motivate further exploration of the quantum-data learning architecture in high-energy physics.
arXiv Detail & Related papers (2023-06-29T18:00:01Z) - Preparing random states and benchmarking with many-body quantum chaos [48.044162981804526]
We show how to predict and experimentally observe the emergence of random state ensembles naturally under time-independent Hamiltonian dynamics.
The observed random ensembles emerge from projective measurements and are intimately linked to universal correlations built up between subsystems of a larger quantum system.
Our work has implications for understanding randomness in quantum dynamics, and enables applications of this concept in a wider context.
arXiv Detail & Related papers (2021-03-05T08:32:43Z)
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.