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Nadezhda Voronova

dblp:342/2870 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2024
0009-0001-9167-9164ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Theory of computation · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer architecture, parallel and distributed computing, and storage systems
1 paper
Emerging computing paradigms · 100%
Theoretical computer science
1 paper
Algorithms and data structures · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Emerging computing paradigms › quantum computing
quantum algorithms
0.812024
Exponential Quantum Space Advantage for Approximating Maximum Directed Cut in the Streaming Model · STOC 2024
Emerging computing paradigms
quantum computing and quantum information
0.812024
Exponential Quantum Space Advantage for Approximating Maximum Directed Cut in the Streaming Model · STOC 2024
Algorithms and data structures › data streams › streaming algorithms
maximum directed cut
0.812024
Exponential Quantum Space Advantage for Approximating Maximum Directed Cut in the Streaming Model · STOC 2024
Algorithms and data structures › data streams
streaming algorithms
0.812024
Exponential Quantum Space Advantage for Approximating Maximum Directed Cut in the Streaming Model · STOC 2024

Methods — techniques the papers use, named apart from their topics

quantum algorithm · 1.5approximation algorithm · 1.5
YearPublicationVenuePosition
2024 Exponential Quantum Space Advantage for Approximating Maximum Directed Cut in the Streaming Model
abstract
While the search for quantum advantage typically focuses on speed­ups in execution time, quantum algorithms also offer the potential for advantage in space complexity. Previous work has shown such advantages for data stream problems, in which elements arrive and must be processed sequentially without random access, but these have been restricted to specially-constructed problems Le Gall, SPAA ‘06 or polynomial advantage Kallaugher, FOCS ‘21. We show an exponential quantum space advantage for the maximum directed cut problem. This is the first known exponential quantum space advantage for any natural streaming problem. This also constitutes the first unconditional exponential quantum resource advantage for approximating a discrete optimization problem in any setting.
John Kallaugher, Ojas Parekh, Nadezhda Voronova
STOC3