Demo Data from EDBT 2026 / reviewers in the wild / expert
Pavithran Iyer
dblp:167/0469
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2015
—ORCID · unresolved
Domains — the database's venue-derived domains; a paper can count in several
Theory of computation · 1 · 1 first-author
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.
| Theoretical computer science
1 paper |
Quantum computing and quantum information · 54% Coding theory · 29% Computational complexity · 18% |
Topics — the 7 heaviest of 7, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Computational complexity › counting complexity
#p-completeness |
0.2 | 1 | 2015 | Hardness of Decoding Quantum Stabilizer Codes · IEEE Trans. Inf. Theory 2015 |
Coding theory › error-correcting codes › decoding › decoding problems
decoding complexity |
0.2 | 1 | 2015 | Hardness of Decoding Quantum Stabilizer Codes · IEEE Trans. Inf. Theory 2015 |
Quantum computing and quantum information › quantum error correction
quantum code decoding |
0.2 | 1 | 2015 | Hardness of Decoding Quantum Stabilizer Codes · IEEE Trans. Inf. Theory 2015 |
Quantum computing and quantum information
quantum error correction |
0.2 | 1 | 2015 | Hardness of Decoding Quantum Stabilizer Codes · IEEE Trans. Inf. Theory 2015 |
Quantum computing and quantum information › quantum error correction
stabilizer codes |
0.2 | 1 | 2015 | Hardness of Decoding Quantum Stabilizer Codes · IEEE Trans. Inf. Theory 2015 |
Coding theory › error-correcting codes › block codes
linear code |
0.1 | 1 | 2015 | Hardness of Decoding Quantum Stabilizer Codes · IEEE Trans. Inf. Theory 2015 |
Coding theory › error-correcting codes › decoding › decoding algorithms
optimal decoding |
0.1 | 1 | 2015 | Hardness of Decoding Quantum Stabilizer Codes · IEEE Trans. Inf. Theory 2015 |
Methods — techniques the papers use, named apart from their topics
syndrome decoding · 0.2degeneracy analysis · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2015 | Hardness of Decoding Quantum Stabilizer CodesabstractIn this paper, we address the computational hardness of optimally decoding a quantum stabilizer code. Much like classical linear codes, errors are detected by measuring certain check operators which yield an error syndrome, and the decoding problem consists of determining the most likely recovery given the syndrome. The corresponding classical problem is known to be NP-complete, and are appropriate a similar decoding problem for quantum codes is also known to be NP-complete. However, this decoding strategy is not optimal in the quantum setting as it does not consider error degeneracy, which causes distinct errors to have the same effect on the code. Here, we show that optimal decoding of stabilizer codes (previously known to be NP-hard) is in fact computationally much harder than optimal decoding of classical linear codes, it is #P-complete. Pavithran Iyer, David Poulin |
IEEE Trans. Inf. Theory | 1 |