Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Log inSign up
Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Blog
Job Board
Q3AS

© 2026 Aqora Quantum S.A.S.

TermsPrivacyLegal Notice

arXiv:1410.3941 · Physical Review Letters

Quantum Data Compression of a Qubit Ensemble

Lee A. Rozema, Dylan H. Mahler, Alex Hayat, Peter S. Turner, Aephraim M. Steinberg

Published Oct 17, 2014• 58 citations
arXivHTMLPDF

Abstract

Data compression is a ubiquitous aspect of modern information technology, and the advent of quantum information raises the question of what types of compression are feasible for quantum data, where it is especially relevant given the extreme difficulty involved in creating reliable quantum memories. We present a protocol in which an ensemble of quantum bits (qubits) can in principle be perfectly compressed into exponentially fewer qubits. We then experimentally implement our algorithm, compressing three photonic qubits into two. This protocol sheds light on the subtle differences between quantum and classical information. Furthermore, since data compression stores all of the available information about the quantum state in fewer physical qubits, it could allow for a vast reduction in the amount of quantum memory required to store a quantum ensemble, making even today's limited quantum memories far more powerful than previously recognized.

DOI
10.1103/physrevlett.113.160504

Related papers

Experimental demonstration of quantum data compression

Lee A. Rozema, Dylan H. Mahler, Alex Hayat +2 more

We present experimental results implementing the Quantum Schur-Weyl Transform QSWT for three qubits, allowing us to compress three quantum bits into two. In our implementation the three qubits are encoded in two photons. The first photon encodes a path and a polarization qubit, while the second photon encodes a single polarization qubit. We use the QSWT to map all of the information from the 3 qubits onto the path and polarization qubits encoded in the first photon, allowing us to discard the second photon. We characterize our compression by performing measurements on the remaining two qubits and show that they obey the statistics of a three qubit system. We expect our technique to become extremely useful in the near future, for all quantum information architectures, as few qubit quantum memories become available.

Conference on Lasers and Electro-Optics Europe & European Quantum Electronics Conference (CLEO/Europe-EQEC)•May 1, 2013•0 citations

Efficient multi‐qubit quantum data compression

Chen‐Rui Fan, Bo Lü, Xue‐Ting Feng +2 more

Quantum data compression is of great significance to both quantum computation and quantum communication due to the limited resources for quantum storage. Here in this study, we present an efficient multi-qubit quantum data compression protocol in which N identically prepared qubits can be perfectly compressed into qubits. Moreover, the feasible implementation of the quantum data compression is also designed based on the IBM Quantum Experience. The experiment reveals efficient information compression performance using the current scheme. We believe this method might be useful in quantum information which one could make the encoding of information on the qubits more efficiently, and also reducing the resources consumption for quantum storage.

Quantum Engineering•May 5, 2021•15 citations

Title: Non-Euclidean Data Compression via Quantum Iteration

Jincheng Zhang

This paper explores the potential of quantum data compression through a novel algorithm predicated on the principles of quantum superposition and entanglement. Traditional data compression techniques rely on sequential processing, inherently limiting efficiency. We propose a quantum-based approach that leverages these principles to achieve exponential compression of data, exploiting inherent parallelism within quantum systems. The core mechanism involves quantum algorithms designed to systematically explore the data space, identifying and exploiting redundancies and correlations that classical algorithms struggle to detect. The resulting compression method offers a fundamentally different paradigm, potentially surpassing the capabilities of existing techniques in terms of compression ratios and computational speed. This research investigates the feasibility of implementing this quantum algorithm and analyzes its potential impact on various data types. The ultimate goal is to demonstrate a practical application of quantum data compression and explore its implications for future data storage and transmission.

•Sep 6, 2026•0 citations

Quantum Entanglement-Based Data Compression & Transmission

Jincheng Zhang

This paper investigates the potential of quantum entanglement for data compression and transmission, aiming to surpass the limitations of classical methods. We propose a novel entanglement protocol that utilizes instantaneous correlations to represent data bits, incorporating quantum error correction to enhance reliability. The core mechanism focuses on encoding information via entangled particle states, suggesting a pathway for transmitting data across significant distances with enhanced efficiency and security. This work explores the theoretical foundations, algorithm design, and preliminary experimental results demonstrating the feasibility of this approach. The potential implications for data security and efficient information transfer are significant, representing a potential paradigm shift in data storage and communication technologies.

•Sep 6, 2026•0 citations

Quantum Data Compression Based on Quantum Demixing

Jincheng Zhang

This paper explores a novel approach to classical data compression leveraging the principles of quantum demixing and measurement. The core idea is to transform classical data into a quantum state representation and subsequently exploit quantum demixing to effectively eliminate unwanted quantum correlations. This process allows for the selective extraction of information, ultimately leading to a compressed representation. We present a theoretical framework outlining this methodology, focusing on the mathematical underpinnings of the transformation, demixing, and measurement stages. The proposed method offers a potential pathway to achieve high compression ratios by exploiting the unique properties of quantum systems. We demonstrate, through theoretical analysis, the feasibility and potential advantages of this technique compared to conventional classical compression methods. The key elements involve mapping classical data to a quantum state, employing a demixing protocol to reduce redundancy, and finally, measuring the quantum state to recover the compressed information. This work lays the groundwork for future research into practical implementations of quantum data compression. ---

•Sep 2, 2026•0 citations

Compressing Quantum Fisher Information

Rui Jie Tang, Jeremy Guenza Marcus, Noah Lupu-Gladstein +5 more

We show that the quantum Fisher information about any phase parameter encoded in a family of pure quantum states can be faithfully compressed into a single qubit, accompanied by a logarithmic amount of classical bits. When the phase is encoded into many identical copies of a qubit state on the equator of the Bloch sphere, we show that the compression can be implemented sequentially, by iteratively compressing pairs of qubits into a single qubit. We experimentally demonstrate this building block in a photonic setup, developing two alternative compression strategies, based on Type-I fusion gate and a postselected implementation of the CNOT gate.

quant-pharXiv:2602.09358•Feb 11, 2026•0 citations
Data compression is a ubiquitous aspect of modern information technology, and the advent of quantum information raises the question of what types of compression are feasible for quantum data, where it is especially relevant given the extreme difficulty involved in creating reliable quantum memories. We present a protocol in which an ensemble of quantum bits (qubits) can in principle be perfectly compressed into exponentially fewer qubits. We then experimentally implement our algorithm, compressing three photonic qubits into two. This protocol sheds light on the subtle differences between quantum and classical information. Furthermore, since data compression stores all of the available information about the quantum state in fewer physical qubits, it could allow for a vast reduction in the amount of quantum memory required to store a quantum ensemble, making even today's limited quantum memories far more powerful than previously recognized.
We present experimental results implementing the Quantum Schur-Weyl Transform QSWT for three qubits, allowing us to compress three quantum bits into two. In our implementation the three qubits are encoded in two photons. The first photon encodes a path and a polarization qubit, while the second photon encodes a single polarization qubit. We use the QSWT to map all of the information from the 3 qubits onto the path and polarization qubits encoded in the first photon, allowing us to discard the second photon. We characterize our compression by performing measurements on the remaining two qubits and show that they obey the statistics of a three qubit system. We expect our technique to become extremely useful in the near future, for all quantum information architectures, as few qubit quantum memories become available.
Quantum data compression is of great significance to both quantum computation and quantum communication due to the limited resources for quantum storage. Here in this study, we present an efficient multi-qubit quantum data compression protocol in which N identically prepared qubits can be perfectly compressed into qubits. Moreover, the feasible implementation of the quantum data compression is also designed based on the IBM Quantum Experience. The experiment reveals efficient information compression performance using the current scheme. We believe this method might be useful in quantum information which one could make the encoding of information on the qubits more efficiently, and also reducing the resources consumption for quantum storage.
This paper explores the potential of quantum data compression through a novel algorithm predicated on the principles of quantum superposition and entanglement. Traditional data compression techniques rely on sequential processing, inherently limiting efficiency. We propose a quantum-based approach that leverages these principles to achieve exponential compression of data, exploiting inherent parallelism within quantum systems. The core mechanism involves quantum algorithms designed to systematically explore the data space, identifying and exploiting redundancies and correlations that classical algorithms struggle to detect. The resulting compression method offers a fundamentally different paradigm, potentially surpassing the capabilities of existing techniques in terms of compression ratios and computational speed. This research investigates the feasibility of implementing this quantum algorithm and analyzes its potential impact on various data types. The ultimate goal is to demonstrate a practical application of quantum data compression and explore its implications for future data storage and transmission.
This paper investigates the potential of quantum entanglement for data compression and transmission, aiming to surpass the limitations of classical methods. We propose a novel entanglement protocol that utilizes instantaneous correlations to represent data bits, incorporating quantum error correction to enhance reliability. The core mechanism focuses on encoding information via entangled particle states, suggesting a pathway for transmitting data across significant distances with enhanced efficiency and security. This work explores the theoretical foundations, algorithm design, and preliminary experimental results demonstrating the feasibility of this approach. The potential implications for data security and efficient information transfer are significant, representing a potential paradigm shift in data storage and communication technologies.
This paper explores a novel approach to classical data compression leveraging the principles of quantum demixing and measurement. The core idea is to transform classical data into a quantum state representation and subsequently exploit quantum demixing to effectively eliminate unwanted quantum correlations. This process allows for the selective extraction of information, ultimately leading to a compressed representation. We present a theoretical framework outlining this methodology, focusing on the mathematical underpinnings of the transformation, demixing, and measurement stages. The proposed method offers a potential pathway to achieve high compression ratios by exploiting the unique properties of quantum systems. We demonstrate, through theoretical analysis, the feasibility and potential advantages of this technique compared to conventional classical compression methods. The key elements involve mapping classical data to a quantum state, employing a demixing protocol to reduce redundancy, and finally, measuring the quantum state to recover the compressed information. This work lays the groundwork for future research into practical implementations of quantum data compression. ---
We show that the quantum Fisher information about any phase parameter encoded in a family of pure quantum states can be faithfully compressed into a single qubit, accompanied by a logarithmic amount of classical bits. When the phase is encoded into many identical copies of a qubit state on the equator of the Bloch sphere, we show that the compression can be implemented sequentially, by iteratively compressing pairs of qubits into a single qubit. We experimentally demonstrate this building block in a photonic setup, developing two alternative compression strategies, based on Type-I fusion gate and a postselected implementation of the CNOT gate.