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Quantum state tomography, aimed at deriving a classical description of an unknown state from measurement data, is a fundamental task in quantum physics. In this work, we analyse the ultimate achievable performance of tomography of…

We introduce an approach for performing quantum state reconstruction on systems of $n$ qubits using a machine-learning-based reconstruction system trained exclusively on $m$ qubits, where $m\geq n$. This approach removes the necessity of…

Quantum process tomography is an experimental technique to fully characterize an unknown quantum process. Standard quantum process tomography suffers from exponentially scaling of the number of measurements with the increasing system size.…

Quantum Physics · Physics 2022-08-02 Shichuan Xue , Yong Liu , Yang Wang , Pingyu Zhu , Chu Guo , Junjie Wu

Computing the ground state of interacting quantum matter is a long-standing challenge, especially for complex two-dimensional systems. Recent developments have highlighted the potential of neural quantum states to solve the quantum…

Disordered Systems and Neural Networks · Physics 2025-07-03 Ao Chen , Markus Heyl

A central task in medical imaging is the reconstruction of an image or function from data collected by medical devices (e.g., CT, MRI, and PET scanners). We provide quantum algorithms for image reconstruction with exponential speedup over…

Quantum Physics · Physics 2020-04-27 Bobak Toussi Kiani , Agnes Villanyi , Seth Lloyd

We present a new procedure for quantum state reconstruction based on weak continuous measurement of an ensemble average. By applying controlled evolution to the initial state new information is continually mapped onto the measured…

Quantum Physics · Physics 2009-11-10 Andrew Silberfarb , Poul S. Jessen , Ivan H. Deutsch

Accurate control of quantum states is crucial for quantum computing and other quantum technologies. In the basic scenario, the task is to steer a quantum system towards a target state through a sequence of control operations. Determining…

Quantum Physics · Physics 2024-06-14 Yan Zhu , Tailong Xiao , Guihua Zeng , Giulio Chiribella , Ya-Dong Wu

In the area of network performance and discovery, network tomography focuses on reconstructing network properties using only end-to-end measurements at the application layer. One challenging problem in network tomography is reconstructing…

Distributed, Parallel, and Cluster Computing · Computer Science 2012-05-08 Kiril Dichev , Fergal Reid , Alexey Lastovetsky

The article introduces efficient quantum state tomography schemes for qutrits and entangled qubits subject to pure decoherence. We implement the dynamic state reconstruction method for open systems sent through phase-damping channels which…

Quantum Physics · Physics 2020-11-03 Artur Czerwinski

Extracting information from quantum devices has long been a crucial problem in the field of quantum mechanics. By performing elaborate measurements, quantum state tomography, an important and fundamental tool in quantum science and…

Quantum Physics · Physics 2022-06-24 Yu Wang , Keren Li

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…

We propose an efficient quantum state tomography method inspired by compressed sensing and threshold quantum state tomography that can drastically reduce the number of measurement settings to reconstruct the density matrix of an $N$-qudit…

Quantum Physics · Physics 2025-04-01 Giovanni Garberoglio , Maurizio Dapor , Diego Maragnano , Marco Liscidini , Daniele Binosi

We introduce the concept of quantum field tomography, the efficient and reliable reconstruction of unknown quantum fields based on data of correlation functions. At the basis of the analysis is the concept of continuous matrix product…

Quantum Physics · Physics 2015-06-22 A. Steffens , C. A. Riofrío , R. Hübener , J. Eisert

The success of modern deep learning hinges on the ability to train neural networks at scale. Through clever reuse of intermediate information, backpropagation facilitates training through gradient computation at a total cost roughly…

Quantum state reconstruction using Neural Quantum States has been proposed as a viable tool to reduce quantum shot complexity in practical applications, and its advantage over competing techniques has been shown in numerical experiments…

Quantum Physics · Physics 2024-05-29 Haimeng Zhao , Giuseppe Carleo , Filippo Vicentini

The challenge posed by the many-body problem in quantum physics originates from the difficulty of describing the non-trivial correlations encoded in the exponential complexity of the many-body wave function. Here we demonstrate that…

Disordered Systems and Neural Networks · Physics 2017-02-13 Giuseppe Carleo , Matthias Troyer

Magnetic resonance image reconstruction starting from undersampled k-space data requires the recovery of many potential nonlinear features, which is very difficult for algorithms to recover these features. In recent years, the development…

Image and Video Processing · Electrical Eng. & Systems 2024-10-15 Shuo Zhou , Yihang Zhou , Congcong Liu , Yanjie Zhu , Hairong Zheng , Dong Liang , Haifeng Wang

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

The novel experimental realization of three-level optical quantum systems is presented. We use the polarization state of biphotons to generate a specific sequence of states that are used in the extended version of BB84 protocol. We…

Quantum Physics · Physics 2009-11-10 Yu. Bogdanov , M. Chekhova , S. Kulik , G. Maslennikov , C. H. Oh , M. K. Tey , A. Zhukov

Quantum tomography is a process of quantum state reconstruction using data from multiple measurements. An essential goal for a quantum tomography algorithm is to find measurements that will maximize the useful information about an unknown…

Quantum Physics · Physics 2020-08-05 A. D. Moiseevskiy , G. I. Struchalin , S. S. Straupe , S. P. Kulik
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