English
Related papers

Related papers: Identifiability of Autonomous and Controlled Open …

200 papers

The study of the physical properties of open quantum systems is at the heart of many present investigations which aim to describe their dynamical evolution, on theoretical ground and through physical realizations. Here we develop a…

Quantum Physics · Physics 2021-11-23 Tarek Khalil , Jean Richert

Entanglement is a fundamental feature of quantum mechanics, playing a crucial role in quantum information processing. However, classifying entangled states, particularly in the mixed-state regime, remains a challenging problem, especially…

We consider quantum state tomography with measurement procedures of the following type: First, we subject the quantum state we aim to identify to a know time evolution for a desired period of time. Afterwards we perform a measurement with a…

Quantum Physics · Physics 2017-01-24 Michael Kech

The problem of discriminating the state of a quantum system among a number of hypothetical states is usually addressed under the assumption that one has perfect knowledge of the possible states of the system. In this thesis, I analyze the…

Quantum Physics · Physics 2014-07-18 Gael Sentís

In this article we derive a useful expectation identity using the language of quantum statistical mechanics, where density matrices represent the state of knowledge about the system. This identity allows to establish relations between…

Quantum Physics · Physics 2024-10-29 Boris Maulén , Sergio Davis , Daniel Pons

We use open quantum system techniques to construct one-parameter semigroups of positive maps and apply them to study the entanglement properties of a class of 16-dimensional density matrices, representing states of a 4x4 bipartite system.

Quantum Physics · Physics 2007-05-23 Fabio Benatti , Roberto Floreanini , Marco Piani

Ordinary differential equations (ODEs) are widely used to model dynamical behavior of systems. It is important to perform identifiability analysis prior to estimating unknown parameters in ODEs (a.k.a. inverse problem), because if a system…

Optimization and Control · Mathematics 2021-03-11 Xing Qiu , Tao Xu , Babak Soltanalizadeh , Hulin Wu

The knowledge of the density matrix of a quantum state plays a fundamental role in several fields ranging from quantum information processing to experiments on foundations of quantum mechanics and quantum optics. Recently, a method has been…

Quantum Physics · Physics 2010-12-07 G. Brida , M. Genovese , M. Gramegna , A. Meda , F. Piacentini , P. Traina , E. Predazzi , S. Olivares , M. G. A. Paris

Tailoring many-body interactions among a proper quantum system endows it with computing ability by means of static quantum computation in the sense that some of the physical degrees of freedom can be used to store binary information and the…

Quantum Physics · Physics 2008-02-03 Haiqing Wei , Xin Xue

Quantum state tomography (QST) is the process of reconstructing the state of a quantum system (mathematically described as a density matrix) through a series of different measurements, which can be solved by learning a parameterized…

Quantum Physics · Physics 2025-03-31 Hailan Ma , Zhenhong Sun , Daoyi Dong , Chunlin Chen , Herschel Rabitz

Rapid improvement in quantum hardware has opened the door to complex problems, but the precise characterization of quantum systems itself remains a challenge. To address this obstacle, novel tomography schemes have been developed that…

Quantum Physics · Physics 2022-07-08 Abigail McClain Gomez , Susanne F. Yelin , Khadijeh Najafi

We study joint measurability of quantum observables in open systems governed by a master equation of Lindblad form. We briefly review the historical perspective of open systems and conceptual aspects of quantum measurements, focusing…

Quantum Physics · Physics 2023-09-13 Jukka Kiukas , Pekka Lahti , Juha-Pekka Pellonpää

Controllable, coherent many-body systems can provide insights into the fundamental properties of quantum matter, enable the realization of new quantum phases and could ultimately lead to computational systems that outperform existing…

We realize the probabilistic cloning and identifying linear independent quantum states of multi-particles system, given prior probability, with universal quantum logic gates using the method of unitary representation. Our result is…

Quantum Physics · Physics 2007-05-23 Chuan-Wei Zhang , Chuan-Feng Li , Guang-Can Guo

Identifying Hamiltonian of a quantum system is of vital importance for quantum information processing. In this Letter, we realized and benchmarked a quantum Hamiltonian identification algorithm recently proposed [Phys. Rev. Lett.…

Quantum Physics · Physics 2014-10-16 Shi-yao Hou , Hang Li , Gui-Lu Long

Identifiability concerns finding which unknown parameters of a model can be quantified from given input-output data. Many linear ODE models, used in systems biology and pharmacokinetics, are unidentifiable, which means that parameters can…

Algebraic Geometry · Mathematics 2013-12-12 Nicolette Meshkat , Seth Sullivant

Symbolic recovery of differential equations is the ambitious attempt at automating the derivation of governing equations with the use of machine learning techniques. In contrast to classical methods which assume the structure of the…

Machine Learning · Computer Science 2024-10-10 Philipp Scholl , Aras Bacho , Holger Boche , Gitta Kutyniok

Recent works have shown that generic local Hamiltonians can be efficiently inferred from local measurements performed on their eigenstates or thermal states. Realistic quantum systems are often affected by dissipation and decoherence due to…

Quantum Physics · Physics 2020-03-25 Eyal Bairey , Chu Guo , Dario Poletti , Netanel H. Lindner , Itai Arad

We consider closed quantum many-body systems subject to stochastic resetting. This means that their unitary time evolution is interrupted by resets at randomly selected times. When a reset takes place the system is reinitialized to a state…

Statistical Mechanics · Physics 2021-12-15 Gabriele Perfetto , Federico Carollo , Matteo Magoni , Igor Lesanovsky

System identification is a common tool for estimating (linear) plant models as a basis for model-based predictive control and optimization. The current challenges in process industry, however, ask for data-driven modelling techniques that…

Systems and Control · Computer Science 2018-02-06 Paul M. J. Van den Hof , Arne G. Dankers , Harm H. M. Weerts