quantum state tomography
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Author(s):  
Violeta Nikolaeva Ivanova-Rohling ◽  
Guido Burkard ◽  
Niklas Rohling

Abstract We present a framework that formulates the quest for the most efficient quantum state tomography measurement set as an optimization problem which can be solved numerically, where the optimization goal is the maximization of the information gain. This approach can be applied to a broad spectrum of relevant setups including measurements restricted to a subsystem. To illustrate the power of this method we present results for the six-dimensional Hilbert space constituted by a qubit-qutrit system, which could be realized e.g. by the N-14 nuclear spin-1 and two electronic spin states of a nitrogen-vacancy center in diamond. Measurements of the qubit subsystem are expressed by projectors of rank three, i.e., projectors on half-dimensional subspaces. For systems consisting only of qubits, it was shown analytically that a set of projectors on half-dimensional subspaces can be arranged in an informationally optimal fashion for quantum state tomography, thus forming so-called mutually unbiased subspaces. Our method goes beyond qubits-only systems and we find that in dimension six such a set of mutually-unbiased subspaces can be approximated with a deviation irrelevant for practical applications.


2021 ◽  
pp. 104999
Author(s):  
Xuanmin Zhu ◽  
Yuanchun Deng ◽  
Runping Gao ◽  
Qun Wei ◽  
Lixia Liu ◽  
...  

2021 ◽  
Vol 20 (10) ◽  
Author(s):  
Syed Muhammad Kazim ◽  
Ahmad Farooq ◽  
Junaid ur Rehman ◽  
Hyundong Shin

2021 ◽  
Vol 127 (14) ◽  
Author(s):  
Shahnawaz Ahmed ◽  
Carlos Sánchez Muñoz ◽  
Franco Nori ◽  
Anton Frisk Kockum

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Ming Zhang ◽  
Shuqiao Zhang ◽  
Yanwei Xiong ◽  
Hankai Zhang ◽  
Anatoly A. Ischenko ◽  
...  

AbstractUltrafast electron diffraction and time-resolved serial crystallography are the basis of the ongoing revolution in capturing at the atomic level of detail the structural dynamics of molecules. However, most experiments capture only the probability density of the nuclear wavepackets to determine the time-dependent molecular structures, while the full quantum state has not been accessed. Here, we introduce a framework for the preparation and ultrafast coherent diffraction from rotational wave packets of molecules, and we establish a new variant of quantum state tomography for ultrafast electron diffraction to characterize the molecular quantum states. The ability to reconstruct the density matrix, which encodes the amplitude and phase of the wavepacket, for molecules of arbitrary degrees of freedom, will enable the reconstruction of a quantum molecular movie from experimental x-ray or electron diffraction data.


2021 ◽  
Author(s):  
Hsuan-Hao Lu ◽  
Karthik Myilswamy ◽  
Ryan Bennink ◽  
Suparna Seshadri ◽  
Mohammed Alshaykh ◽  
...  

Abstract Owing in large part to the advent of integrated biphoton frequency combs (BFCs), recent years have witnessed increased attention to quantum information processing in the frequency domain for its inherent high dimensionality and entanglement compatible with fiber-optic networks. Quantum state tomography (QST) of such states, however, has required complex and precise engineering of active frequency mixing operations, which are difficult to scale. To address these limitations, we propose a novel solution that employs a pulse shaper and electro-optic phase modulator (EOM) to perform random operations instead of mixing in a prescribed manner. Incorporating state-of-the-art Bayesian statistical method, we successfully verify the entanglement and reconstruct the full density matrix of BFCs generated from an on-chip Si3N4 microring resonator (MRR) in up to an 8×8-dimensional two-qudit Hilbert space, the highest dimension to date for frequency bins. Overall, our method furnishes an experimentally powerful approach for frequency-bin tomography with readily implementable operations.


2021 ◽  
Vol 127 (2) ◽  
Author(s):  
Chang-Jiang Huang ◽  
Guo-Yong Xiang ◽  
Yu Guo ◽  
Kang-Da Wu ◽  
Bi-Heng Liu ◽  
...  

Author(s):  
Libor Motka ◽  
Martin Paur ◽  
Jaroslav Rehacek ◽  
Zdenek Hradil ◽  
Luis L Sánchez-Soto

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