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The Quantum Wasserstein Distance of Order 1
We propose a generalization of the Wasserstein distance of order 1 to the quantum states of n qudits. The proposal recovers the Hamming distance for the vectors of the canonical basis, and more generally the classical Wasserstein distance for quantum states diagonal in the canonical basis. The pro...
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Published in: | IEEE transactions on information theory 2021-10, Vol.67 (10), p.6627-6643 |
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creator | De Palma, Giacomo Marvian, Milad Trevisan, Dario Lloyd, Seth |
description | We propose a generalization of the Wasserstein distance of order 1 to the quantum states of n qudits. The proposal recovers the Hamming distance for the vectors of the canonical basis, and more generally the classical Wasserstein distance for quantum states diagonal in the canonical basis. The proposed distance is invariant with respect to permutations of the qudits and unitary operations acting on one qudit and is additive with respect to the tensor product. Our main result is a continuity bound for the von Neumann entropy with respect to the proposed distance, which significantly strengthens the best continuity bound with respect to the trace distance. We also propose a generalization of the Lipschitz constant to quantum observables. The notion of quantum Lipschitz constant allows us to compute the proposed distance with a semidefinite program. We prove a quantum version of Marton's transportation inequality and a quantum Gaussian concentration inequality for the spectrum of quantum Lipschitz observables. Moreover, we derive bounds on the contraction coefficients of shallow quantum circuits and of the tensor product of one-qudit quantum channels with respect to the proposed distance. We discuss other possible applications in quantum machine learning, quantum Shannon theory, and quantum many-body systems. |
doi_str_mv | 10.1109/TIT.2021.3076442 |
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The proposal recovers the Hamming distance for the vectors of the canonical basis, and more generally the classical Wasserstein distance for quantum states diagonal in the canonical basis. The proposed distance is invariant with respect to permutations of the qudits and unitary operations acting on one qudit and is additive with respect to the tensor product. Our main result is a continuity bound for the von Neumann entropy with respect to the proposed distance, which significantly strengthens the best continuity bound with respect to the trace distance. We also propose a generalization of the Lipschitz constant to quantum observables. The notion of quantum Lipschitz constant allows us to compute the proposed distance with a semidefinite program. We prove a quantum version of Marton's transportation inequality and a quantum Gaussian concentration inequality for the spectrum of quantum Lipschitz observables. Moreover, we derive bounds on the contraction coefficients of shallow quantum circuits and of the tensor product of one-qudit quantum channels with respect to the proposed distance. We discuss other possible applications in quantum machine learning, quantum Shannon theory, and quantum many-body systems.</description><identifier>ISSN: 0018-9448</identifier><identifier>EISSN: 1557-9654</identifier><identifier>DOI: 10.1109/TIT.2021.3076442</identifier><identifier>CODEN: IETTAW</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>concentration inequalities ; Continuity ; Entropy ; Hamming distance ; Lipschitz constant ; Machine learning ; Mathematical analysis ; Permutations ; Probability distribution ; Quantum mechanics ; Quantum optimal mass transport ; Quantum state ; qudits ; Tensors ; Training ; von Neumann entropy ; Wasserstein distance</subject><ispartof>IEEE transactions on information theory, 2021-10, Vol.67 (10), p.6627-6643</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2021</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c446t-26a43ca12479e39bf9ef14058fe238ebcb797a35908d71706b9c1e6662694b543</citedby><cites>FETCH-LOGICAL-c446t-26a43ca12479e39bf9ef14058fe238ebcb797a35908d71706b9c1e6662694b543</cites><orcidid>0000-0002-5064-8695</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/9420734$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,776,780,27903,27904,54774</link.rule.ids></links><search><creatorcontrib>De Palma, Giacomo</creatorcontrib><creatorcontrib>Marvian, Milad</creatorcontrib><creatorcontrib>Trevisan, Dario</creatorcontrib><creatorcontrib>Lloyd, Seth</creatorcontrib><title>The Quantum Wasserstein Distance of Order 1</title><title>IEEE transactions on information theory</title><addtitle>TIT</addtitle><description>We propose a generalization of the Wasserstein distance of order 1 to the quantum states of <inline-formula> <tex-math notation="LaTeX">n </tex-math></inline-formula> qudits. The proposal recovers the Hamming distance for the vectors of the canonical basis, and more generally the classical Wasserstein distance for quantum states diagonal in the canonical basis. The proposed distance is invariant with respect to permutations of the qudits and unitary operations acting on one qudit and is additive with respect to the tensor product. Our main result is a continuity bound for the von Neumann entropy with respect to the proposed distance, which significantly strengthens the best continuity bound with respect to the trace distance. We also propose a generalization of the Lipschitz constant to quantum observables. The notion of quantum Lipschitz constant allows us to compute the proposed distance with a semidefinite program. We prove a quantum version of Marton's transportation inequality and a quantum Gaussian concentration inequality for the spectrum of quantum Lipschitz observables. Moreover, we derive bounds on the contraction coefficients of shallow quantum circuits and of the tensor product of one-qudit quantum channels with respect to the proposed distance. We discuss other possible applications in quantum machine learning, quantum Shannon theory, and quantum many-body systems.</description><subject>concentration inequalities</subject><subject>Continuity</subject><subject>Entropy</subject><subject>Hamming distance</subject><subject>Lipschitz constant</subject><subject>Machine learning</subject><subject>Mathematical analysis</subject><subject>Permutations</subject><subject>Probability distribution</subject><subject>Quantum mechanics</subject><subject>Quantum optimal mass transport</subject><subject>Quantum state</subject><subject>qudits</subject><subject>Tensors</subject><subject>Training</subject><subject>von Neumann entropy</subject><subject>Wasserstein distance</subject><issn>0018-9448</issn><issn>1557-9654</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><recordid>eNo9kEFLw0AQRhdRsFbvgpeAR0nc2Z3dzR6lVi0UihDxuGzSCabYpO4mB_-9KSmehoH3fcM8xm6BZwDcPharIhNcQCa50YjijM1AKZNarfCczTiHPLWI-SW7inE3rqhAzNhD8UXJ--Dbftgnnz5GCrGnpk2em9j7tqKkq5NN2FJI4Jpd1P470s1pztnHy7JYvKXrzetq8bROK0Tdp0J7lJUHgcaStGVtqQbkKq9JyJzKqjTWeKksz7cGDNelrYC01kJbLBXKObufeg-h-xko9m7XDaEdTzqhjNAaxxdHik9UFboYA9XuEJq9D78OuDsqcaMSd1TiTkrGyN0UaYjoH7couJEo_wBWnVnM</recordid><startdate>20211001</startdate><enddate>20211001</enddate><creator>De Palma, Giacomo</creator><creator>Marvian, Milad</creator><creator>Trevisan, Dario</creator><creator>Lloyd, Seth</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><orcidid>https://orcid.org/0000-0002-5064-8695</orcidid></search><sort><creationdate>20211001</creationdate><title>The Quantum Wasserstein Distance of Order 1</title><author>De Palma, Giacomo ; Marvian, Milad ; Trevisan, Dario ; Lloyd, Seth</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c446t-26a43ca12479e39bf9ef14058fe238ebcb797a35908d71706b9c1e6662694b543</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>concentration inequalities</topic><topic>Continuity</topic><topic>Entropy</topic><topic>Hamming distance</topic><topic>Lipschitz constant</topic><topic>Machine learning</topic><topic>Mathematical analysis</topic><topic>Permutations</topic><topic>Probability distribution</topic><topic>Quantum mechanics</topic><topic>Quantum optimal mass transport</topic><topic>Quantum state</topic><topic>qudits</topic><topic>Tensors</topic><topic>Training</topic><topic>von Neumann entropy</topic><topic>Wasserstein distance</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>De Palma, Giacomo</creatorcontrib><creatorcontrib>Marvian, Milad</creatorcontrib><creatorcontrib>Trevisan, Dario</creatorcontrib><creatorcontrib>Lloyd, Seth</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE/IET Electronic Library (IEL)</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts – Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>IEEE transactions on information theory</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>De Palma, Giacomo</au><au>Marvian, Milad</au><au>Trevisan, Dario</au><au>Lloyd, Seth</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>The Quantum Wasserstein Distance of Order 1</atitle><jtitle>IEEE transactions on information theory</jtitle><stitle>TIT</stitle><date>2021-10-01</date><risdate>2021</risdate><volume>67</volume><issue>10</issue><spage>6627</spage><epage>6643</epage><pages>6627-6643</pages><issn>0018-9448</issn><eissn>1557-9654</eissn><coden>IETTAW</coden><abstract>We propose a generalization of the Wasserstein distance of order 1 to the quantum states of <inline-formula> <tex-math notation="LaTeX">n </tex-math></inline-formula> qudits. The proposal recovers the Hamming distance for the vectors of the canonical basis, and more generally the classical Wasserstein distance for quantum states diagonal in the canonical basis. The proposed distance is invariant with respect to permutations of the qudits and unitary operations acting on one qudit and is additive with respect to the tensor product. Our main result is a continuity bound for the von Neumann entropy with respect to the proposed distance, which significantly strengthens the best continuity bound with respect to the trace distance. We also propose a generalization of the Lipschitz constant to quantum observables. The notion of quantum Lipschitz constant allows us to compute the proposed distance with a semidefinite program. We prove a quantum version of Marton's transportation inequality and a quantum Gaussian concentration inequality for the spectrum of quantum Lipschitz observables. Moreover, we derive bounds on the contraction coefficients of shallow quantum circuits and of the tensor product of one-qudit quantum channels with respect to the proposed distance. We discuss other possible applications in quantum machine learning, quantum Shannon theory, and quantum many-body systems.</abstract><cop>New York</cop><pub>IEEE</pub><doi>10.1109/TIT.2021.3076442</doi><tpages>17</tpages><orcidid>https://orcid.org/0000-0002-5064-8695</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | concentration inequalities Continuity Entropy Hamming distance Lipschitz constant Machine learning Mathematical analysis Permutations Probability distribution Quantum mechanics Quantum optimal mass transport Quantum state qudits Tensors Training von Neumann entropy Wasserstein distance |
title | The Quantum Wasserstein Distance of Order 1 |
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