Evidence map›Paper›PMID 35546151›Full record

ArticleScientific reports2022

Quantum pixel representations and compression for N-dimensional images.

Mercy G Amankwah, Daan Camps, E Wes Bethel, Roel Van Beeumen, Talita Perciano

Erratum issuedAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Mercy G Amankwah *Lawrence Berkeley National Laboratory, Computing Sciences Area, Berkeley, CA, 94720, USA.
Daan Camps *Lawrence Berkeley National Laboratory, Computing Sciences Area, Berkeley, CA, 94720, USA.
E Wes BethelLawrence Berkeley National Laboratory, Computing Sciences Area, Berkeley, CA, 94720, USA.
Roel Van BeeumenLawrence Berkeley National Laboratory, Computing Sciences Area, Berkeley, CA, 94720, USA.
Talita PercianoLawrence Berkeley National Laboratory, Computing Sciences Area, Berkeley, CA, 94720, USA. tperciano@lbl.gov.

Funding

U.S. Department of Energy DE-AC02-05CH11231
6 · The paper itself

Abstract

We introduce a novel and uniform framework for quantum pixel representations that overarches many of the most popular representations proposed in the recent literature, such as (I)FRQI, (I)NEQR, MCRQI, and (I)NCQI. The proposed QPIXL framework results in more efficient circuit implementations and significantly reduces the gate complexity for all considered quantum pixel representations. Our method scales linearly in the number of pixels and does not use ancilla qubits. Furthermore, the circuits only consist of [Formula: see text] gates and [Formula: see text] gates making them practical in the NISQ era. Additionally, we propose a circuit and image compression algorithm that is shown to be highly effective, being able to reduce the necessary gates to prepare an FRQI state for example scientific images by up to 90% without sacrificing image quality. Our algorithms are made publicly available as part of QPIXL++, a Quantum Image Pixel Library.

Identifiers

PMID35546151
PMCPMC9095730

What OpenQuestion holds

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Registered trials

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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.