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Quantum state tomography is an essential tool for the characterization and verification of quantum states. However, as it cannot be directly applied to systems with more than a few qubits, efficient tomography of larger states on mid-sized…

Quantum Physics · Physics 2023-02-01 Yotam Y. Lifshitz , Eyal Bairey , Eli Arbel , Gadi Aleksandrowicz , Haggai Landa , Itai Arad

Efficiently characterising quantum systems, verifying operations of quantum devices and validating underpinning physical models, are central challenges for the development of quantum technologies and for our continued understanding of…

Quantum state tomography is an elementary tool to fully characterize an unknown quantum state. As the quantum hardware scales up in size, the standard quantum state tomography becomes increasingly challenging due to its exponentially…

Quantum Physics · Physics 2022-12-12 Lu Zhong , Chu Guo , Xiaoting Wang

To obtain a complete description of a quantum system, one usually employs standard quantum state tomography, which however requires exponential number of measurements to perform and hence is impractical when the system's size grows large.…

Quantum Physics · Physics 2020-01-17 Tao Xin , Xinfang Nie , Xiangyu Kong , Jingwei Wen , Dawei Lu , Jun Li

Quantum process characterization is a fundamental task in quantum information processing, yet conventional methods, such as quantum process tomography, require prohibitive resources and lack scalability. Here, we introduce an efficient…

Quantum Physics · Physics 2025-04-11 Yusen Wu , Yukun Zhang , Chuan Wang , Xiao Yuan

Complete characterization of states and processes that occur within quantum devices is crucial for understanding and testing their potential to outperform classical technologies for communications and computing. However, solving this task…

Quantum Physics · Physics 2020-05-07 E. S. Tiunov , V. V. Tiunova , A. E. Ulanov , A. I. Lvovsky , A. K. Fedorov

The characterization of Hamiltonians and other components of open quantum dynamical systems plays a crucial role in quantum computing and other applications. Scientific machine learning techniques have been applied to this problem in a…

Quantum Physics · Physics 2026-04-07 Peter Sentz , Stanley Nicholson , Yujin Cho , Sohail Reddy , Brendan Keith , Stefanie Günther

To analyze quantum many-body Hamiltonians, recently, machine learning techniques have been shown to be quite useful and powerful. However, the applicability of such machine learning solvers is still limited. Here, we propose schemes that…

Strongly Correlated Electrons · Physics 2020-04-17 Yusuke Nomura

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 introduce a method of quantum tomography for a continuous variable system in position and momentum space. We consider a single two-level probe interacting with a quantum harmonic oscillator by means of a class of Hamiltonians, linear in…

Quantum Physics · Physics 2015-03-19 J. Casanova , C. E. Lopez , J. J. Garcia-Ripoll , C. F. Roos , E. Solano

Determining the Hamiltonian of a quantum system is essential for understanding its dynamics and validating its behavior. Hamiltonian learning provides a data-driven approach to reconstruct the generator of the dynamics from measurements on…

In this work, we consider a fundamental task in quantum many-body physics - finding and learning ground states of quantum Hamiltonians and their properties. Recent works have studied the task of predicting the ground state expectation value…

Quantum Physics · Physics 2025-01-16 Štěpán Šmíd , Roberto Bondesan

The experimental realization of increasingly complex quantum states underscores the pressing need for new methods of state learning and verification. In one such framework, quantum state tomography, the aim is to learn the full quantum…

Quantum Physics · Physics 2025-01-30 Antonio Anna Mele , Yaroslav Herasymenko

Learning the Hamiltonian governing a quantum system is a central task in quantum metrology, sensing, and device characterization. Existing Heisenberg-limited Hamiltonian learning protocols either require multi-qubit operations that are…

Quantum Physics · Physics 2026-01-16 Shrigyan Brahmachari , Shuchen Zhu , Iman Marvian , Yu Tong

We introduce a generalizable framework for learning to identify effective Hamiltonians directly from experimental data in solid-state quantum systems. Our approach is based on a physics-informed neural network architecture that embeds…

Mesoscale and Nanoscale Physics · Physics 2026-03-04 Jarosław Pawłowski , Mateusz Krawczyk

In this work, quantum transformers are designed and analysed in detail by extending the state-of-the-art classical transformer neural network architectures known to be very performant in natural language processing and image analysis.…

This paper summarizes several recent developments in the area of estimation and robust control of quantum systems and outlines several directions for future research. Quantum state tomography via linear regression estimation and adaptive…

Systems and Control · Computer Science 2018-06-11 Daoyi Dong , Yuanlong Wang

Recently, tremendous progress has been made in the field of quantum science and technologies: different platforms for quantum simulation as well as quantum computing, ranging from superconducting qubits to neutral atoms, are starting to…

Quantum state tomography, a process that reconstructs a quantum state from measurements on an ensemble of identically prepared copies, plays a crucial role in benchmarking quantum devices. However, brute-force approaches to quantum state…

Quantum information technologies provide promising applications in communication and computation, while machine learning has become a powerful technique for extracting meaningful structures in 'big data'. A crossover between quantum…

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