Efficient multi‐qubit quantum data compression

Fan, Chen-Rui; Lü, Bo; Feng, Xue-Ting; Gao, Wei-Chao; Wang, Chuan

doi:10.1002/que2.67

Cited by 12 publications

(3 citation statements)

References 28 publications

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“…In addition, quantum processors (such as the IBM QE 5-qubit [ 82 ]) can be used to realize the quantum simulation in this work.…”

Section: Experimental Proposalsmentioning

confidence: 99%

Quantum Simulation of Pseudo-Hermitian-φ-Symmetric Two-Level Systems

Zheng

2022

Entropy

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Non-Hermitian (NH) quantum theory has been attracting increased research interest due to its featured properties, novel phenomena, and links to open and dissipative systems. Typical NH systems include PT-symmetric systems, pseudo-Hermitian systems, and their anti-symmetric counterparts. In this work, we generalize the pseudo-Hermitian systems to their complex counterparts, which we call pseudo-Hermitian-φ-symmetric systems. This complex extension adds an extra degree of freedom to the original symmetry. On the one hand, it enlarges the non-Hermitian class relevant to pseudo-Hermiticity. On the other hand, the conventional pseudo-Hermitian systems can be understood better as a subgroup of this wider class. The well-defined inner product and pseudo-inner product are still valid. Since quantum simulation provides a strong method to investigate NH systems, we mainly investigate how to simulate this novel system in a Hermitian system using the linear combination of unitaries in the scheme of duality quantum computing. We illustrate in detail how to simulate a general P-pseudo-Hermitian-φ-symmetric two-level system. Duality quantum algorithms have been recently successfully applied to similar types of simulations, so we look forward to the implementation of available quantum devices.

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“…In addition, quantum processors (such as the IBM QE 5-qubit [ 82 ]) can be used to realize the quantum simulation in this work.…”

Section: Experimental Proposalsmentioning

confidence: 99%

Quantum Simulation of Pseudo-Hermitian-φ-Symmetric Two-Level Systems

Zheng

2022

Entropy

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“…In this paper we join this effort and implement quantum compression algorithm introduced in 44 and further developed in 45 – 50 . This algorithm is used to compress n identical copies of an arbitrary pure qubit state into roughly qubits.…”

Section: Introductionmentioning

confidence: 99%

Implementation of quantum compression on IBM quantum computers

Pivoluska

Plesch

2022

Sci Rep

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Advances in development of quantum computing processors brought ample opportunities to test the performance of various quantum algorithms with practical implementations. In this paper we report on implementations of quantum compression algorithm that can efficiently compress unknown quantum information. We restricted ourselves to compression of three pure qubits into two qubits, as the complexity of even such a simple implementation is barely within the reach of today’s quantum processors. We implemented the algorithm on IBM quantum processors with two different topological layouts—a fully connected triangle processor and a partially connected line processor. It turns out that the incomplete connectivity of the line processor affects the performance only minimally. On the other hand, it turns out that the transpilation, i.e. compilation of the circuit into gates physically available to the quantum processor, crucially influences the result. We also have seen that the compression followed by immediate decompression is, even for such a simple case, on the edge or even beyond the capabilities of currently available quantum processors.

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“…In this paper we join this effort and implement quantum compression algorithm introduced in 28 and further developed in [29][30][31][32][33][34] . This algorithm is used to compress n identical copies of an arbitrary pure qubit state into roughly log(n) qubits.…”

Section: Introductionmentioning

confidence: 99%

Implementation of quantum compression on IBM quantum computers

Pivoluska¹,

Plesch²

2022

Preprint

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Advances in development of quantum computing processors brought ample opportunities to test the performance of various quantum algorithms with practical implementations. In this paper we report on implementations of quantum compression algorithm that can efficiently compress unknown quantum information. We restricted ourselves to compression of three pure qubits into two qubits, as the complexity of even such a simple implementation is barely within the reach of today's quantum processors. We implemented the algorithm on IBM quantum processors with two different topological layouts-a fully connected triangle processor and a partially connected line processor. It turns out that the incomplete connectivity of the line processor affects the performance only minimally. On the other hand, it turns out that the transpilation, i.e. compilation of the circuit into gates physically available to the quantum processor, crucially influences the result. We also have seen that the compression followed by immediate decompression is, even for such a simple case, on the edge or even beyond the capabilities of currently available quantum processors.

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Efficient multi‐qubit quantum data compression

Cited by 12 publications

References 28 publications

Quantum Simulation of Pseudo-Hermitian-φ-Symmetric Two-Level Systems

Quantum Simulation of Pseudo-Hermitian-φ-Symmetric Two-Level Systems

Implementation of quantum compression on IBM quantum computers

Implementation of quantum compression on IBM quantum computers

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