graph state
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2021 ◽  
Author(s):  
Jia-Min Xu ◽  
Qing Zhou ◽  
Yu-Xiang Yang ◽  
Zi-Mo Cheng ◽  
Xin-Yu Xu ◽  
...  
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2021 ◽  
Author(s):  
Ying Yang ◽  
Huaixin Cao

Abstract With the rapid development of machine learning, artificial neural networks provide a powerful tool to represent or approximate many-body quantum states. It was proved that every graph state can be generated by a neural network. In this paper, we aim to introduce digraph states and explore their neural network representations (NNRs). Based on some discussions about digraph states and neural network quantum states (NNQSs), we construct explicitly the NNR for any digraph state, implying every digraph state is an NNQS. The obtained results will provide a theoretical foundation for solving the quantum many-body problem with machine learning method whenever the wave-function is known as an unknown digraph state or it can be approximated by digraph states.


2021 ◽  
Author(s):  
Wenbo Xie ◽  
Wenhan Dai ◽  
Don Towsley

2021 ◽  
Vol 15 ◽  
Author(s):  
Xin Chen ◽  
Yuanjie Zheng ◽  
Changxu Dong ◽  
Sutao Song

In terms of seizure prediction, how to fully mine relational data information among multiple channels of epileptic EEG? This is a scientific research subject worthy of further exploration. Recently, we propose a multi-dimensional enhanced seizure prediction framework, which mainly includes information reconstruction space, graph state encoder, and space-time predictor. It takes multi-channel spatial relationship as breakthrough point. At the same time, it reconstructs data unit from frequency band level, updates graph coding representation, and explores space-time relationship. Through experiments on CHB-MIT dataset, sensitivity of the model reaches 98.61%, which proves effectiveness of the proposed model.


2021 ◽  
Vol 104 (1) ◽  
Author(s):  
Pengcheng Liao ◽  
David L. Feder

2021 ◽  
Author(s):  
P. Renault ◽  
J. Nokkala ◽  
N. Treps ◽  
J. Piilo ◽  
V. Parigi
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2020 ◽  
Vol 102 (6) ◽  
Author(s):  
Priya J. Nadkarni ◽  
Ankur Raina ◽  
Shayan Srinivasa Garani

Quantum ◽  
2020 ◽  
Vol 4 ◽  
pp. 348
Author(s):  
Axel Dahlberg ◽  
Jonas Helsen ◽  
Stephanie Wehner

Critical to the construction of large scale quantum networks, i.e. a quantum internet, is the development of fast algorithms for managing entanglement present in the network. One fundamental building block for a quantum internet is the distribution of Bell pairs between distant nodes in the network. Here we focus on the problem of transforming multipartite entangled states into the tensor product of bipartite Bell pairs between specific nodes using only a certain class of local operations and classical communication. In particular we study the problem of deciding whether a given graph state, and in general a stabilizer state, can be transformed into a set of Bell pairs on specific vertices using only single-qubit Clifford operations, single-qubit Pauli measurements and classical communication. We prove that this problem is NP-Complete.


Quantum ◽  
2020 ◽  
Vol 4 ◽  
pp. 305
Author(s):  
Jeremy C. Adcock ◽  
Sam Morley-Short ◽  
Axel Dahlberg ◽  
Joshua W. Silverstone

Graph states, and the entanglement they posses, are central to modern quantum computing and communications architectures. Local complementation – the graph operation that links all local-Clifford equivalent graph states – allows us to classify all stabiliser states by their entanglement. Here, we study the structure of the orbits generated by local complementation, mapping them up to 9 qubits and revealing a rich hidden structure. We provide programs to compute these orbits, along with our data for each of the 587 orbits up to 9 qubits and a means to visualise them. We find direct links between the connectivity of certain orbits with the entanglement properties of their component graph states. Furthermore, we observe the correlations between graph-theoretical orbit properties, such as diameter and colourability, with Schmidt measure and preparation complexity and suggest potential applications. It is well known that graph theory and quantum entanglement have strong interplay – our exploration deepens this relationship, providing new tools with which to probe the nature of entanglement.


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