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Generation of high fidelity photonic non-Gaussian states is a crucial ingredient for universal quantum computation using continous-variable platforms, yet it remains a challenge to do so efficiently. We present a general framework for a…

Quantum Physics · Physics 2019-11-06 Daiqin Su , Casey R. Myers , Krishna Kumar Sabapathy

This work addresses the problem of state estimation in multivariable dynamic systems with quantized outputs, a common scenario in applications involving low-resolution sensors or communication constraints. A novel method is proposed to…

Systems and Control · Electrical Eng. & Systems 2025-09-10 Angel L. Cedeño , Rodrigo A. González , Boris I. Godoy , Juan C. Agüero

To understand quantum optics experiments, we must perform calculations that consider the principal sources of noise, such as losses, spectral impurity and partial distinguishability. In both discrete and continuous variable systems, these…

Quantum Physics · Physics 2025-08-15 Jacob F. F. Bulmer , Javier Martínez-Cifuentes , Bryn A. Bell , Nicolás Quesada

Pulsed homodyne quantum tomography usually requires a high detection efficiency limiting its applicability in quantum optics. Here, it is shown that the presence of low detection efficiency ($<50\%$) does not prevent the tomographic…

Photonic Quantum Computers provides several benefits over the discrete qubit-based paradigm of quantum computing. By using the power of continuous-variable computing we build an anomaly detection model to use on searches for New Physics.…

High Energy Physics - Phenomenology · Physics 2021-12-01 Andrew Blance , Michael Spannowsky

A three level atom in $\Lambda$ configuration is reduced to an effective two level system, under appropriate conditions, and its $\mathcal{PT}$ symmetric properties are investigated. This effective qubit system when subjected to a…

Quantum Physics · Physics 2022-06-10 Javid Naikoo , Subhashish Banerjee , Anirban Pathak

We present a quantifier of non-classical correlations for bipartite, multi-mode Gaussian states. It is derived from the Discriminating Strength measure, introduced for finite dimensional systems in A. Farace et al., New. J. Phys. 16, 073010…

Quantum Physics · Physics 2015-11-03 Luca Rigovacca , Alessandro Farace , Antonella De Pasquale , Vittorio Giovannetti

Sequential Bayesian Filtering aims to estimate the current state distribution of a Hidden Markov Model, given the past observations. The problem is well-known to be intractable for most application domains, except in notable cases such as…

Machine Learning · Statistics 2024-02-16 Théophile Cantelobre , Carlo Ciliberto , Benjamin Guedj , Alessandro Rudi

The effective quantum field theory description of gravity, despite its non-renormalizability, allows for predictions beyond classical general relativity. As we enter the age of gravitational wave astronomy, an important and timely question…

General Relativity and Quantum Cosmology · Physics 2022-12-21 Thiago Guerreiro , Francesco Coradeschi , Antonia Micol Frassino , Jennifer Rittenhouse West , Enrico Junior Schioppa

Although squeezed states are nonclassical states, so far, their nonclassicality could not be demonstrated by negative quasiprobabilities. In this work we derive pattern functions for the direct experimental determination of so-called…

Quantum Physics · Physics 2011-09-12 T. Kiesel , W. Vogel , B. Hage , R. Schnabel

A state of a quantum systems can be regarded as {\it classical} ({\it quantum}) with respect to measurements of a set of canonical observables iff there exists (does not exist) a well defined, positive phase space distribution, the so…

Quantum Physics · Physics 2009-11-10 J. Korbicz , J. I. Cirac , J. Wehr , M. Lewenstein

Time-continuous non-anticipating quantum processes of nondemolition measurements are introduced as the dynamical realizations of the causal quasi-measurements, which are described in this paper by the adapted operator-valued probability…

Quantum Physics · Physics 2007-05-23 V. P. Belavkin

Cubic phase states provide the essential non-Gaussian resource for continuous-variable quantum computing. We show that they also offer significant potential for quantum metrology, surpassing the phase-sensing sensitivity of all Gaussian…

Quantum Physics · Physics 2025-12-04 Jiajie Guo , Shuheng Liu , Boxuan Jing , Qiongyi He , Manuel Gessner

We address the quantification of non-Gaussianity of states and operations in continuous-variable systems and its use in quantum information. We start by illustrating in details the properties and the relationships of two recently proposed…

Quantum Physics · Physics 2013-01-16 Marco G. Genoni , Matteo G. A. Paris

The tantalizing promise of quantum computational speedup in solving certain problems has been strongly supported by recent experimental evidence from a high-fidelity 53-qubit superconducting processor1 and Gaussian boson sampling (GBS) with…

Estimation of a dynamical system's latent state subject to sensor noise and model inaccuracies remains a critical yet difficult problem in robotics. While Kalman filters provide the optimal solution in the least squared sense for linear and…

Robotics · Computer Science 2022-02-10 Fahira Afzal Maken , Fabio Ramos , Lionel Ott

Advanced quantum technologies rely on non-Gaussian states of light, essential for universal quantum computation, fault-tolerant error correction, and quantum sensing. Their practical realization, however, faces hurdles: simulating large…

We address the joint estimation of changes in the position and linear momentum of a quantum particle or, equivalently, changes in the complex field of a bosonic mode. Although these changes are generated by non-commuting operators, we show…

Gaussian bipartite states are basic tools for the realization of quantum information protocols with continuous variables. Their complete characterization is obtained by the reconstruction of the corresponding covariance matrix. Here we…

Quantum Physics · Physics 2016-04-27 D. Buono , G. Nocerino , V. D'Auria , A. Porzio , S. Olivares , M. G. A. Paris

We consider the problem of sequential estimation of the unknowns of state-space and deep state-space models that include estimation of functions and latent processes of the models. The proposed approach relies on Gaussian and deep Gaussian…

Machine Learning · Computer Science 2024-03-26 Yuhao Liu , Marzieh Ajirak , Petar Djuric