Matches in SemOpenAlex for { <https://semopenalex.org/work/W3027922144> ?p ?o ?g. }
Showing items 1 to 97 of
97
with 100 items per page.
- W3027922144 abstract "We present an approach for a deep-learning compiler of quantum circuits, designed to reduce the output noise of circuits run on a specific device. We train a convolutional neural network on experimental data from a quantum device to learn a hardware-specific noise model. A compiler then uses the trained network as a noise predictor and inserts sequences of gates in circuits so as to minimize expected noise. We tested this approach on the IBM 5-qubit devices and observed a reduction in output noise of 12.3% (95% CI [11.5%, 13.0%]) compared to the circuits obtained by the Qiskit compiler. Moreover, the trained noise model is hardware-specific: applying a noise model trained on one device to another device yields a noise reduction of only 5.2% (95% CI [4.9%, 5.6%]). These results suggest that device-specific compilers using machine learning may yield higher fidelity operations and provide insights for the design of noise models." @default.
- W3027922144 created "2020-05-29" @default.
- W3027922144 creator A5003116157 @default.
- W3027922144 creator A5034927946 @default.
- W3027922144 date "2020-05-21" @default.
- W3027922144 modified "2023-09-27" @default.
- W3027922144 title "A deep learning model for noise prediction on near-term quantum devices" @default.
- W3027922144 cites W1877184193 @default.
- W3027922144 cites W1983727080 @default.
- W3027922144 cites W2003132673 @default.
- W3027922144 cites W2040175558 @default.
- W3027922144 cites W2079216847 @default.
- W3027922144 cites W2268604949 @default.
- W3027922144 cites W3024350329 @default.
- W3027922144 cites W3037347557 @default.
- W3027922144 cites W3099175659 @default.
- W3027922144 cites W3209612530 @default.
- W3027922144 cites W63585698 @default.
- W3027922144 cites W792163153 @default.
- W3027922144 cites W3105080542 @default.
- W3027922144 hasPublicationYear "2020" @default.
- W3027922144 type Work @default.
- W3027922144 sameAs 3027922144 @default.
- W3027922144 citedByCount "2" @default.
- W3027922144 countsByYear W30279221442021 @default.
- W3027922144 crossrefType "posted-content" @default.
- W3027922144 hasAuthorship W3027922144A5003116157 @default.
- W3027922144 hasAuthorship W3027922144A5034927946 @default.
- W3027922144 hasConcept C108583219 @default.
- W3027922144 hasConcept C111335779 @default.
- W3027922144 hasConcept C113775141 @default.
- W3027922144 hasConcept C115961682 @default.
- W3027922144 hasConcept C119599485 @default.
- W3027922144 hasConcept C121332964 @default.
- W3027922144 hasConcept C127413603 @default.
- W3027922144 hasConcept C134146338 @default.
- W3027922144 hasConcept C154945302 @default.
- W3027922144 hasConcept C163294075 @default.
- W3027922144 hasConcept C169590947 @default.
- W3027922144 hasConcept C199360897 @default.
- W3027922144 hasConcept C2524010 @default.
- W3027922144 hasConcept C33923547 @default.
- W3027922144 hasConcept C41008148 @default.
- W3027922144 hasConcept C50644808 @default.
- W3027922144 hasConcept C58053490 @default.
- W3027922144 hasConcept C62520636 @default.
- W3027922144 hasConcept C81363708 @default.
- W3027922144 hasConcept C84114770 @default.
- W3027922144 hasConcept C99498987 @default.
- W3027922144 hasConceptScore W3027922144C108583219 @default.
- W3027922144 hasConceptScore W3027922144C111335779 @default.
- W3027922144 hasConceptScore W3027922144C113775141 @default.
- W3027922144 hasConceptScore W3027922144C115961682 @default.
- W3027922144 hasConceptScore W3027922144C119599485 @default.
- W3027922144 hasConceptScore W3027922144C121332964 @default.
- W3027922144 hasConceptScore W3027922144C127413603 @default.
- W3027922144 hasConceptScore W3027922144C134146338 @default.
- W3027922144 hasConceptScore W3027922144C154945302 @default.
- W3027922144 hasConceptScore W3027922144C163294075 @default.
- W3027922144 hasConceptScore W3027922144C169590947 @default.
- W3027922144 hasConceptScore W3027922144C199360897 @default.
- W3027922144 hasConceptScore W3027922144C2524010 @default.
- W3027922144 hasConceptScore W3027922144C33923547 @default.
- W3027922144 hasConceptScore W3027922144C41008148 @default.
- W3027922144 hasConceptScore W3027922144C50644808 @default.
- W3027922144 hasConceptScore W3027922144C58053490 @default.
- W3027922144 hasConceptScore W3027922144C62520636 @default.
- W3027922144 hasConceptScore W3027922144C81363708 @default.
- W3027922144 hasConceptScore W3027922144C84114770 @default.
- W3027922144 hasConceptScore W3027922144C99498987 @default.
- W3027922144 hasLocation W30279221441 @default.
- W3027922144 hasOpenAccess W3027922144 @default.
- W3027922144 hasPrimaryLocation W30279221441 @default.
- W3027922144 hasRelatedWork W1568345435 @default.
- W3027922144 hasRelatedWork W1973256592 @default.
- W3027922144 hasRelatedWork W2161685427 @default.
- W3027922144 hasRelatedWork W2171493164 @default.
- W3027922144 hasRelatedWork W2257937122 @default.
- W3027922144 hasRelatedWork W2562526363 @default.
- W3027922144 hasRelatedWork W2755255888 @default.
- W3027922144 hasRelatedWork W2781738013 @default.
- W3027922144 hasRelatedWork W2889126882 @default.
- W3027922144 hasRelatedWork W2923370183 @default.
- W3027922144 hasRelatedWork W2941673255 @default.
- W3027922144 hasRelatedWork W2945191606 @default.
- W3027922144 hasRelatedWork W2980100927 @default.
- W3027922144 hasRelatedWork W3024350329 @default.
- W3027922144 hasRelatedWork W3028156913 @default.
- W3027922144 hasRelatedWork W3098154398 @default.
- W3027922144 hasRelatedWork W3098581063 @default.
- W3027922144 hasRelatedWork W3101479050 @default.
- W3027922144 hasRelatedWork W3103872322 @default.
- W3027922144 hasRelatedWork W3116822337 @default.
- W3027922144 isParatext "false" @default.
- W3027922144 isRetracted "false" @default.
- W3027922144 magId "3027922144" @default.
- W3027922144 workType "article" @default.