Noise-Assisted Quantum Autoencoder

Quantum autoencoder is an efficient variational quantum algorithm for quantum data compression. However, previous quantum autoencoders fail to compress and recover high-rank mixed states. In this work, we discuss the fundamental properties and limitations of the standard quantum autoencoder model in...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:arXiv.org
Hlavní autoři: Cao, Chenfeng, Wang, Xin
Médium: Paper
Jazyk:angličtina
Vydáno: Ithaca Cornell University Library, arXiv.org 24.04.2021
Témata:
ISSN:2331-8422
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Abstract Quantum autoencoder is an efficient variational quantum algorithm for quantum data compression. However, previous quantum autoencoders fail to compress and recover high-rank mixed states. In this work, we discuss the fundamental properties and limitations of the standard quantum autoencoder model in more depth, and provide an information-theoretic solution to its recovering fidelity. Based on this understanding, we present a noise-assisted quantum autoencoder algorithm to go beyond the limitations, our model can achieve high recovering fidelity for general input states. Appropriate noise channels are used to make the input mixedness and output mixedness consistent, the noise setup is determined by measurement results of the trash system. Compared with the original quantum autoencoder model, the measurement information is fully used in our algorithm. In addition to the circuit model, we design a (noise-assisted) adiabatic model of quantum autoencoder that can be implemented on quantum annealers. We verified the validity of our methods through compressing the thermal states of transverse field Ising model and Werner states. For pure state ensemble compression, we also introduce a projected quantum autoencoder algorithm.
AbstractList Quantum autoencoder is an efficient variational quantum algorithm for quantum data compression. However, previous quantum autoencoders fail to compress and recover high-rank mixed states. In this work, we discuss the fundamental properties and limitations of the standard quantum autoencoder model in more depth, and provide an information-theoretic solution to its recovering fidelity. Based on this understanding, we present a noise-assisted quantum autoencoder algorithm to go beyond the limitations, our model can achieve high recovering fidelity for general input states. Appropriate noise channels are used to make the input mixedness and output mixedness consistent, the noise setup is determined by measurement results of the trash system. Compared with the original quantum autoencoder model, the measurement information is fully used in our algorithm. In addition to the circuit model, we design a (noise-assisted) adiabatic model of quantum autoencoder that can be implemented on quantum annealers. We verified the validity of our methods through compressing the thermal states of transverse field Ising model and Werner states. For pure state ensemble compression, we also introduce a projected quantum autoencoder algorithm.
Author Cao, Chenfeng
Wang, Xin
Author_xml – sequence: 1
  givenname: Chenfeng
  surname: Cao
  fullname: Cao, Chenfeng
– sequence: 2
  givenname: Xin
  surname: Wang
  fullname: Wang, Xin
BookMark eNotjs1KAzEURoMoWGsfwF3Rdcabv0myHIpWoShC9yWd3AtTNNHJRHx8B3R1Nh_nO1fsPOWEjN0IaLQzBu7D-DN8NxKEbMApJc7YQs7gTkt5yValnABAtlYaoxbs9iUPBXlXylAmjOu3GtJUP9ZdnTKmPkccr9kFhfeCq38u2f7xYb954rvX7fOm2_FgZMuj7pUlE31AAC0soLXee3TRmKODcFTUY0-SYlAYyYh-XhKRJ4chWq2W7O5P-znmr4plOpxyHdP8eJDagoE5uFW_toVDCA
ContentType Paper
Copyright 2021. This work is published under http://arxiv.org/licenses/nonexclusive-distrib/1.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Copyright_xml – notice: 2021. This work is published under http://arxiv.org/licenses/nonexclusive-distrib/1.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
DBID 8FE
8FG
ABJCF
ABUWG
AFKRA
AZQEC
BENPR
BGLVJ
CCPQU
DWQXO
HCIFZ
L6V
M7S
PHGZM
PHGZT
PIMPY
PKEHL
PQEST
PQGLB
PQQKQ
PQUKI
PRINS
PTHSS
DOI 10.48550/arxiv.2012.08331
DatabaseName ProQuest SciTech Collection
ProQuest Technology Collection
ProQuest MSED
ProQuest Central (Alumni)
ProQuest Central UK/Ireland
ProQuest Central Essentials
ProQuest Central
Technology Collection
ProQuest One Community College
ProQuest Central Korea
SciTech Premium Collection
ProQuest Engineering Collection
Engineering Database
ProQuest Central Premium
ProQuest One Academic (New)
proquest-Publicly Available Content Database
ProQuest One Academic Middle East (New)
ProQuest One Academic Eastern Edition (DO NOT USE)
ProQuest One Applied & Life Sciences
ProQuest One Academic (retired)
ProQuest One Academic UKI Edition
ProQuest Central China
Engineering Collection
DatabaseTitle Publicly Available Content Database
Engineering Database
Technology Collection
ProQuest One Academic Middle East (New)
ProQuest Central Essentials
ProQuest One Academic Eastern Edition
ProQuest Central (Alumni Edition)
SciTech Premium Collection
ProQuest One Community College
ProQuest Technology Collection
ProQuest SciTech Collection
ProQuest Central China
ProQuest Central
ProQuest One Applied & Life Sciences
ProQuest Engineering Collection
ProQuest One Academic UKI Edition
ProQuest Central Korea
Materials Science & Engineering Collection
ProQuest Central (New)
ProQuest One Academic
ProQuest One Academic (New)
Engineering Collection
DatabaseTitleList Publicly Available Content Database
Database_xml – sequence: 1
  dbid: PIMPY
  name: Publicly Available Content Database
  url: http://search.proquest.com/publiccontent
  sourceTypes: Aggregation Database
DeliveryMethod fulltext_linktorsrc
Discipline Physics
EISSN 2331-8422
Genre Working Paper/Pre-Print
GroupedDBID 8FE
8FG
ABJCF
ABUWG
AFKRA
ALMA_UNASSIGNED_HOLDINGS
AZQEC
BENPR
BGLVJ
CCPQU
DWQXO
FRJ
HCIFZ
L6V
M7S
M~E
PHGZM
PHGZT
PIMPY
PKEHL
PQEST
PQGLB
PQQKQ
PQUKI
PRINS
PTHSS
ID FETCH-LOGICAL-a526-d4c37f5d9ae004170e77999e8d55b80ab3fcecf2fda3edf51c9aefff9f8ead743
IEDL.DBID BENPR
IngestDate Mon Jun 30 09:24:22 EDT 2025
IsDoiOpenAccess true
IsOpenAccess true
IsPeerReviewed false
IsScholarly false
Language English
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-a526-d4c37f5d9ae004170e77999e8d55b80ab3fcecf2fda3edf51c9aefff9f8ead743
Notes SourceType-Working Papers-1
ObjectType-Working Paper/Pre-Print-1
content type line 50
OpenAccessLink https://www.proquest.com/docview/2470502556?pq-origsite=%requestingapplication%
PQID 2470502556
PQPubID 2050157
ParticipantIDs proquest_journals_2470502556
PublicationCentury 2000
PublicationDate 20210424
PublicationDateYYYYMMDD 2021-04-24
PublicationDate_xml – month: 04
  year: 2021
  text: 20210424
  day: 24
PublicationDecade 2020
PublicationPlace Ithaca
PublicationPlace_xml – name: Ithaca
PublicationTitle arXiv.org
PublicationYear 2021
Publisher Cornell University Library, arXiv.org
Publisher_xml – name: Cornell University Library, arXiv.org
SSID ssj0002672553
Score 1.7559526
SecondaryResourceType preprint
Snippet Quantum autoencoder is an efficient variational quantum algorithm for quantum data compression. However, previous quantum autoencoders fail to compress and...
SourceID proquest
SourceType Aggregation Database
SubjectTerms Accuracy
Algorithms
Circuit design
Data compression
Information theory
Ising model
Noise
Title Noise-Assisted Quantum Autoencoder
URI https://www.proquest.com/docview/2470502556
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
link http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV09T8MwELWgBYmJb_FRqgqxmgbHjuMJAWoFEkQBOpSpcu2z1IGmJE3Fz-ecpsDEwhglluKzfX53fn5HyEXItTW4yigIjE04YJyirBCUIzyFK7DSLS8KP8okiYdDldYJt6KmVa58YuWobWZ8jrzLuAxEJZh1PfugvmqUP12tS2isk6ZXKuMN0rztJenLd5aFRRKbhMvjzEq8q6vzz8nCc7rYJcKPurjcbydc7Sz97f_-0w5ppnoG-S5Zg-ke2awYnabYJ-dJNimAovn9QNrOc4k2LN87N-U88-KVFvIDMuj3Bnf3tC6IQLVgEbXchNIJqzR4mSwZgJSI7yBG447jQI9DZ8A45qwOwTpxZfBL55xyMc4XhAqHpDHNpnBEOo5FiBMQncQYlQodKNy1lQyUjoyIIx0ek9aqx6N6Uhejn-6e_P36lGwxT_0IOGW8RRrzvIQzsmEW80mRt-sxanua5Ss-pQ9P6dsX1tSeNA
linkProvider ProQuest
linkToHtml http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMw1V1LTwIxEJ4gavTkOz5QN0aPlaW73e4ejDEqgfAIJhzwREofCQdZ3AXUH-V_dLos6skbB89tmun06_SbdjoDcOn5QkncZUQz9E18jX5KpBgjPtJTXdGKm_lH4SZvt8NeL-oU4HPxF8aGVS5sYmaoVSztHXmZ-txlWcKs2_ErsVWj7OvqooTGHBYN_fGGLlt6U3_A9b2itPrYva-RvKoAEYwGRPnS44apSGiba4q7mnMkSTpECQehKwaekVoaapTwtDKsIrGnMSYyISodz1scdgVWfcR6WITVTr3Vef6-1KEBRwm9-etpliusLJL34cyGkNFrZDt5LbvfNj87yKpb_0wF2zh1MdbJDhT0aBfWs3hVme7BRTseppoguCxMlfM0RYRMX5y76SS2qTmVTvahuwypDqA4ikf6EBxDA2RByL1C9LmZcCPkJBF3IxFIFgbCO4LSQsH9fMum_R_tHv_dfA4btW6r2W_W240T2KQ2yMX1CfVLUJwkU30Ka3I2GabJWQ4PB_pLXo0vFWH8ZA
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Noise-Assisted+Quantum+Autoencoder&rft.jtitle=arXiv.org&rft.au=Cao%2C+Chenfeng&rft.au=Wang%2C+Xin&rft.date=2021-04-24&rft.pub=Cornell+University+Library%2C+arXiv.org&rft.eissn=2331-8422&rft_id=info:doi/10.48550%2Farxiv.2012.08331