Evidence map›Paper›PMID 38786810›Full record

ArticleNanomaterials (Basel, Switzerland)2024

Optimisation Challenge for a Superconducting Adiabatic Neural Network That Implements XOR and OR Boolean Functions.

Dmitrii S Pashin, Marina V Bastrakova, Dmitrii A Rybin, Igor I Soloviev, Nikolay V Klenov, Andrey E Schegolev

Abstract read
In one paragraph

Article in Nanomaterials (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Dmitrii S PashinFaculty of Physics, Lobachevsky State University of Nizhni Novgorod, 603022 Nizhny Novgorod, Russia.ORCID 0000-0002-7326-562X
Marina V BastrakovaFaculty of Physics, Lobachevsky State University of Nizhni Novgorod, 603022 Nizhny Novgorod, Russia.ORCID 0000-0002-6597-563X
Dmitrii A RybinFaculty of Physics, Lobachevsky State University of Nizhni Novgorod, 603022 Nizhny Novgorod, Russia.ORCID 0000-0002-4406-4677
Igor I SolovievRussian Quantum Centre, 143025 Moscow, Russia.ORCID 0000-0001-9735-2720
Nikolay V KlenovNational University of Science and Technology MISIS, 119049 Moscow, Russia.ORCID 0000-0001-6265-3670
Andrey E SchegolevSkobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State University, 119991 Moscow, Russia.ORCID 0000-0002-5381-3297

Funding

Foundation for the Advancement of Theoretical Physics 272 and Mathematics "BASIS" 22-1-3-16-1Rosatom in the framework of the Roadmap for Quantum computing 868-1.3-15/15-2021Russian Science Foundation 22-72-10075Strategic Academic Leadership Program "Priority-2030" of NITU "MISIS K2-2022- 029
6 · The paper itself

Abstract

In this article, we consider designs of simple analog artificial neural networks based on adiabatic Josephson cells with a sigmoid activation function. A new approach based on the gradient descent method is developed to adjust the circuit parameters, allowing efficient signal transmission between the network layers. The proposed solution is demonstrated on the example of a system that implements XOR and OR logical operations.

Indexed as

hardware implementation of neural networksnonlinear dynamicsoptimisation procedurequantum parametronsuperconducting quantum interferometer

Identifiers

PMID38786810
PMCPMC11124324

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.