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We propose observable bounds for Gaussian illumination to maximize the signal-to-noise ratio, which minimizes the discrimination error between the presence and absence of a low-reflectivity target using Gaussian states. The observable…

We find and investigate the optimal scheme of quantum distributed Gaussian sensing for estimation of the average of independent phase shifts. We show that the ultimate sensitivity is achievable by using an entangled symmetric Gaussian…

Quantum Physics · Physics 2020-04-14 Changhun Oh , Changhyoup Lee , Seok Hyung Lie , Hyunseok Jeong

We study nonclassical correlations beyond entanglement in a family of two-mode non-Gaussian states which represent the continuous-variable counterpart of two-qubit Werner states. We evaluate quantum discord and other quantumness measures…

Quantum Physics · Physics 2015-06-03 Richard Tatham , Ladislav Mišta , Gerardo Adesso , Natalia Korolkova

When estimating an unknown phase rotation of a continuous-variable system with homodyne detection, the optimal probe state strongly depends on the value of the estimated parameter. In this article, we identify the optimal pure single-mode…

Quantum Physics · Physics 2025-05-28 Ricard Ravell Rodríguez , Simon Morelli

We present a novel approach to the separability problem for Gaussian quantum states of bosonic continuous variable systems. We derive a simplified necessary and sufficient separability criterion for arbitrary Gaussian states of $m$ vs $n$…

Quantum Physics · Physics 2018-02-22 Ludovico Lami , Alessio Serafini , Gerardo Adesso

The effective description of a bosonic quantum system identifies the minimum finite dimension required to capture its essential dynamics. This effective dimension plays an important role in the complexity of classical and quantum algorithms…

Quantum Physics · Physics 2026-04-22 Varun Upreti , Nicolás Quesada , Ulysse Chabaud

We consider the classic question of state tomography: given copies of an unknown quantum state $\rho\in\mathbb{C}^{d\times d}$, output $\widehat{\rho}$ which is close to $\rho$ in some sense, e.g. trace distance or fidelity. When one is…

Quantum Physics · Physics 2023-05-31 Sitan Chen , Brice Huang , Jerry Li , Allen Liu , Mark Sellke

Quantum phase estimation based on Gaussian states plays a crucial role in many application fields. In this paper, we study the precision bound for the scheme using two-mode squeezed Gaussian states. The quantum Fisher information is…

Quantum Physics · Physics 2024-11-27 Jian-Dong Zhang , Chuang Li , Lili Hou , Shuai Wang

We address the estimation of the loss parameter of a bosonic channel probed by arbitrary signals. Unlike the optimal Gaussian probes, which can attain the ultimate bound on precision asymptotically either for very small or very large…

Quantum Physics · Physics 2009-04-23 G. Adesso , F. Dell'Anno , S. De Siena , F. Illuminati , L. A. M. Souza

In the paper of F.A. Mele, A.A. Mele, L. Bittel, J. Eisert, V. Giovannetti, L. Lami, L. Leone, S.F.E. Oliviero, ArXiv:2405.01431, estimates for the trace-norm distance between two quantum Gaussian states in terms of the mean vectors and…

Quantum Physics · Physics 2025-09-01 A. S. Holevo

Gaussian states, operations, and measurements are central building blocks for continuous-variable quantum information processing which paves the way for abundant applications, especially including network-based quantum computation and…

Quantum Physics · Physics 2021-07-06 Mengzhen Zhang

Full reconstruction of quantum states from measurement samples is often a prohibitively complex task, both in terms of the experimental setup and the scaling of the sample size with the system. This motivates the relatively easier task of…

Quantum Physics · Physics 2025-08-04 Clara Wassner , Jack Davis , Sacha Cerf , Ulysse Chabaud , Francesco Arzani

Quantum non-Gaussianity is a key resource for quantum advantage in continuous-variable systems. We introduce a general framework to quantify non-Gaussianity based on correlation generation: two copies of a state become correlated at a…

Quantum Physics · Physics 2025-08-28 Oliver Hahn , Ryuji Takagi

We establish several upper bounds on the energy-constrained quantum and private capacities of all single-mode phase-insensitive bosonic Gaussian channels. The first upper bound, which we call the "data-processing bound," is the simplest and…

Quantum Physics · Physics 2018-06-18 Kunal Sharma , Mark M. Wilde , Sushovit Adhikari , Masahiro Takeoka

Multimode Gaussian states are a versatile resource for quantum information technologies and have been realized across a wide range of physical platforms. Recent progress in the large-scale generation of such states provides a key ingredient…

Quantum Physics · Physics 2026-04-14 Chan Roh , Geunhee Gwak , Young-Do Yoon , Young-Sik Ra

We present a sample- and time-efficient algorithm to learn any bosonic Fock state acted upon by an arbitrary Gaussian unitary. As a special case, this algorithm efficiently learns states produced in Fock state BosonSampling, thus resolving…

Gaussian states have played on important role in the physics of continuous-variable quantum systems. They are appealing for the experimental ease with which they can be produced, and for their compact and elegant mathematical description.…

Quantum Physics · Physics 2021-10-04 Mattia Walschaers

Free-fermionic states, also known as fermionic Gaussian states, represent an important class of quantum states ubiquitous in physics. They are uniquely and efficiently described by their correlation matrix. However, in practical…

Quantum Physics · Physics 2025-10-10 Lennart Bittel , Antonio Anna Mele , Jens Eisert , Lorenzo Leone

We study the problem of learning nonparametric distributions in a finite mixture, and establish tight bounds on the sample complexity for learning the component distributions in such models. Namely, we are given i.i.d. samples from a pdf…

Machine Learning · Computer Science 2023-07-06 Bryon Aragam , Wai Ming Tai

We provide sample complexity upper bounds for agnostically learning multivariate Gaussians under the constraint of approximate differential privacy. These are the first finite sample upper bounds for general Gaussians which do not impose…

Machine Learning · Statistics 2020-10-21 Ishaq Aden-Ali , Hassan Ashtiani , Gautam Kamath