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Related papers: Dissipative Spectroscopy

200 papers

Spectroscopy underpins modern scientific discovery across diverse disciplines. While experimental spectroscopy probes material properties through scattering or radiation measurements, computational spectroscopy combines theoretical models…

We study the current noise spectrum of qubits under transport conditions in a dissipative bosonic environment. We combine (non-)Markovian master equations with correlation functions in Laplace-space to derive a noise formula for both weak…

Mesoscale and Nanoscale Physics · Physics 2009-11-10 R. Aguado , T. Brandes

Quantum metrology protocols exploiting ensembles of $N$ two-level systems and Ramsey-style measurements are ubiquitous. However, in many cases excess readout noise severely degrades the measurement sensitivity; in particular in sensors…

Quantum Physics · Physics 2022-12-06 Martin Koppenhöfer , Peter Groszkowski , Hoi-Kwan Lau , A. A. Clerk

Standard spectroscopic protocols model the dynamics of open quantum systems as a superposition of isolated, exponentially decaying eigenmodes. This paradigm fails fundamentally at Exceptional Points, where the eigenbasis collapses and the…

Quantum Physics · Physics 2025-12-29 Prasoon Saurabh

Spectral densities encode the relevant information characterising the system-environment interaction in an open-quantum system problem. Such information is key to determining the system's dynamics. In this work, we leverage the potential of…

Quantum Physics · Physics 2024-03-13 Jessica Barr , Giorgio Zicari , Alessandro Ferraro , Mauro Paternostro

Smoothed dissipative particle dynamics (SDPD) is a widely used particle-based method for modelling soft matter systems at mesoscopic and macroscopic scales, offering thermodynamic consistency and direct control over the fluid's transport…

Fluid Dynamics · Physics 2025-10-22 Marina Echeverria Ferrero , Nicolas Moreno , Marco Ellero

Quantum technologies offer a promising route to the efficient sampling and analysis of stochastic processes, with potential applications across the sciences. Such quantum advantages rely on the preparation of a quantum sample state of the…

Quantum Physics · Physics 2024-04-17 Chengran Yang , Marta Florido-Llin`as , Mile Gu , Thomas J. Elliott

Dynamic mode decomposition has emerged as a leading technique to identify spatiotemporal coherent structures from high-dimensional data, benefiting from a strong connection to nonlinear dynamical systems via the Koopman operator. In this…

Systems and Control · Computer Science 2017-12-01 Zhe Bai , Eurika Kaiser , Joshua L. Proctor , J. Nathan Kutz , Steven L. Brunton

Quantum dissipation arises from the unavoidable coupling between a quantum system and its surrounding environment, which is known as a major obstacle in the quantum processing of information. Apart from its existence, how to trace the…

Quantum Physics · Physics 2022-08-17 Li Chen , Yadong Wu

Dynamic mode decomposition (DMD) is a powerful and increasingly popular tool for performing spectral analysis of fluid flows. However, it requires data that satisfy the Nyquist-Shannon sampling criterion. In many fluid flow experiments,…

Fluid Dynamics · Physics 2014-09-17 Jonathan H. Tu , Clarence W. Rowley , J. Nathan Kutz , Jessica K. Shang

We introduce a new characteristics of chaoticity of classical and quantum dynamical systems by defining the notion of the dissipation time which enables us to test how the system responds to the noise and in particular to measure the speed…

Chaotic Dynamics · Physics 2007-05-23 Lech Wolowski

By considering a solvable driven-dissipative quantum model, we demonstrate that continuous second order phase transitions in dissipative systems may occur without an accompanying spontaneous symmetry breaking. As such, the underlying…

Quantum Physics · Physics 2018-10-24 Julia Hannukainen , Jonas Larson

Adaptive sampling results in dramatic improvements in the recovery of sparse signals in white Gaussian noise. A sequential adaptive sampling-and-refinement procedure called Distilled Sensing (DS) is proposed and analyzed. DS is a form of…

Statistics Theory · Mathematics 2010-05-31 Jarvis Haupt , Rui Castro , Robert Nowak

Correlations between different regions of a quantum many-body system can be quantified through measures based on entropies of (reduced) subsystem states. For closed systems, several analytical and numerical tools, e.g., hydrodynamic…

Statistical Mechanics · Physics 2022-12-26 Federico Carollo , Vincenzo Alba

We analyze the phase diagram of a quantum particle confined to a finite chain, subject to a dissipative environment described by an Ohmic spectral function. Analytical and numerical techniques are employed to explore both the perturbative…

Mesoscale and Nanoscale Physics · Physics 2009-11-13 J. Sabio , L. Borda , F. Guinea , F. Sols

Characterising optical quantum states is essential for the development of quantum technologies. While traditional approaches to perform full quantum state tomography are often experimentally demanding, neuromorphic architectures may provide…

We propose a continuous-variable quantum sensing scheme, in which a harmonic oscillator is employed as the probe to estimate the parameters in the spectral density of a quantum reservoir, within a non-Markovian dynamical framework. It is…

Quantum Physics · Physics 2022-06-02 Yi-Da Sha , Wei Wu

Distributed quantum sensing (DQS) leverages quantum resources to estimate an unknown global property of a networked quantum sensor beyond the classical limit. We propose and analyze an all-optical resource-efficient scheme for the…

Quantum Physics · Physics 2024-07-19 Rajveer Nehra , Changhun Oh , Liang Jiang , Alireza Marandi

We present the adiabatic theory of dissipative solitons (DS) of complex cubic-quintic nonlinear Ginzburg-Landau equation (CQGLE). Solutions in the closed analytical form in the spectral domain have the shape of Rayleigh-Jeans distribution…

Pattern Formation and Solitons · Physics 2024-06-12 Vladimir L. Kalashnikov , Alexander Rudenkov , Evgeni Sorokin , Irina Sorokina

Compressive Sensing (CS) is a new technique for the efficient acquisition of signals, images, and other data that have a sparse representation in some basis, frame, or dictionary. By sparse we mean that the N-dimensional basis…

Information Theory · Computer Science 2015-05-18 Chinmay Hegde , Richard G. Baraniuk