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We consider the classical shadows task for pure states in the setting of both joint and independent measurements. The task is to measure few copies of an unknown pure state $\rho$ in order to learn a classical description which suffices to…

Quantum Physics · Physics 2024-06-19 Daniel Grier , Hakop Pashayan , Luke Schaeffer

Quantum metrology plays a fundamental role in many scientific areas. However, the complexity of engineering entangled probes and the external noise raise technological barriers for realizing the expected precision of the to-be-estimated…

Quantum Physics · Physics 2021-01-21 Xiaodong Yang , Xi Chen , Jun Li , Xinhua Peng , Raymond Laflamme

The method of classical shadows heralds unprecedented opportunities for quantum estimation with limited measurements [H.-Y. Huang, R. Kueng, and J. Preskill, Nat. Phys. 16, 1050 (2020)]. Yet its relationship to established quantum…

Quantum Physics · Physics 2021-07-19 Joseph M. Lukens , Kody J. H. Law , Ryan S. Bennink

The most elementary prepare-and-measure scenarios have no independent measurement inputs. No inputs mean that quantum advantages require two indispensable ingredients: shared entanglement and measurements that can be adapted to the…

Quantum Physics · Physics 2026-04-01 Elna Svegborn , Armin Tavakoli

Quantum entanglement offers powerful opportunities for enhancing measurement sensitivity beyond classical limits, with optical atomic clocks serving as a leading platform for such advances. This chapter introduces the principles of…

Quantum Physics · Physics 2025-12-04 Raphael Kaubruegger , Adam M. Kaufman

Quantum entanglement is an essential feature of many-body systems that impacts both quantum information processing and fundamental physics. The growth of entanglement is a major challenge for classical simulation methods. In this work, we…

Quantum Physics · Physics 2025-07-15 Qi Zhao , You Zhou , Andrew M. Childs

Quantum informatic quantities such as entanglement entropy are useful in detecting quantum phase transitions. Recently, a new entanglement measure called pseudo-entropy was proposed which is a generalization of the more well-known…

High Energy Physics - Theory · Physics 2025-09-23 Song He , Pak Hang Chris Lau , Long Zhao

We address the problem of implementing bottleneck layers from classical pre-trained neural networks on a quantum computer, with the goal of exploring intrinsically quantum ansatz for representing large linear layers within hybrid…

Quantum Physics · Physics 2026-04-09 Borja Aizpurua , Sukhbinder Singh , Román Orús

One interpretation of how the classical world emerges from an underlying quantum reality involves the build-up of certain robust entanglements between particles due to scattering events [Science Vol.301 p.1081]. This is an appealing view…

Quantum Physics · Physics 2013-04-26 P. A. Knott , J. Sindt , J. A. Dunningham

We present a scheme to efficiently simulate, with a classical computer, the dynamics of multipartite quantum systems on which the amount of entanglement (or of correlations in the case of mixed-state dynamics) is conveniently restricted.…

Quantum Physics · Physics 2016-09-08 Guifre Vidal

In this paper, we investigate how to reduce the number of measurement configurations needed for sufficiently precise entanglement quantification. Instead of analytical formulae, we employ artificial neural networks to predict the amount of…

Quantum Physics · Physics 2022-07-20 Jan Roik , Karol Bartkiewicz , Antonín Černoch , Karel Lemr

The laws of quantum physics endow superior performance and security for information processing: quantum sensing harnesses nonclassical resources to enable measurement precision unmatched by classical sensing, whereas quantum cryptography…

Classical shadows (CS) has recently emerged as an important framework to efficiently predict properties of an unknown quantum state. A common strategy in CS protocols is to parametrize the basis in which one measures the state by a random…

Shadow tomography is a framework for constructing succinct descriptions of quantum states using randomized measurement bases, called classical shadows, with powerful methods to bound the estimators used. We recast existing experimental…

Quantum Machine Learning (QML) has emerged as a promising framework for exploring how quantum dynamics may enhance data processing tasks. Here we investigate Quantum Extreme Learning Machines (QELMs), a quantum analogue of classical Extreme…

Quantum Physics · Physics 2026-04-27 A. De Lorenzis , M. P. Casado , N. Lo Gullo , T. Lux , F. Plastina , A. Riera

Randomized measurement protocols, including classical shadows, entanglement tomography, and randomized benchmarking are powerful techniques to estimate observables, perform state tomography, or extract the entanglement properties of quantum…

Quantum Physics · Physics 2024-04-03 Jacob Bringewatt , Jonathan Kunjummen , Niklas Mueller

Quantum dynamics is of fundamental interest and has implications in quantum information processing. The four-point out-of-time-ordered correlator (OTOC) is traditionally used to quantify quantum information scrambling under many-body…

Quantum Physics · Physics 2021-12-06 Roy J. Garcia , You Zhou , Arthur Jaffe

We propose an ordered set of experimentally accessible conditions for detecting entanglement in mixed states. The $k$-th condition involves comparing moments of the partially transposed density operator up to order $k$. Remarkably, the…

The quantum entanglement enables the precision measurement and frequency metrology beyond the standard quantum limit that is imposed by the quantum projection noise and photon shot noise. Here we propose employing the entangled atoms in the…

Quantum Physics · Physics 2023-05-10 Deshui Yu , Jingbiao Chen , Shougang Zhang

We introduce a technique to estimate error-mitigated expectation values on noisy quantum computers. Our technique performs shadow tomography on a logical state to produce a memory-efficient classical reconstruction of the noisy density…

Quantum Physics · Physics 2022-03-15 Hong-Ye Hu , Ryan LaRose , Yi-Zhuang You , Eleanor Rieffel , Zhihui Wang
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