Kunal Sharma | Toward Quantum Advantage for Ground State Problems | QDC 2025

Item: Kunal Sharma | Toward Quantum Advantage for Ground State Problems | QDC 2025
Rating: 4
Author: PostSingularity Institute

by Kunal Sharma

Formal & Physical Sciences Computing & Cybersecurity UYComputer science UYXNatural computing

🎙 Kunal Sharma 👥 203K 📅 November 26, 2025 ⏱ 15 min 👁 1K 📄 expert opinion 🧭 2026-08-16

Available in: English (current) Français

Keywords

SKQDquantum diagonalizationground statenoise mitigationDMRG

Summary

Kunal Sharma presents IBM’s Sample-based Krylov Quantum Diagonalization (SKQD) algorithm for approximating ground state energies on current noisy quantum hardware. He outlines three criteria for quantum advantage: shallow circuits, noise resilience, and provable guarantees. SKQD uses time evolution circuits to generate bitstrings, which are processed on HPC with configuration recovery and subspace diagonalization. The algorithm provides convergence guarantees under assumptions of good initial state, constant gap, and ground state sparsity. Experiments on IBM Heron processors achieved state-of-the-art accuracy on impurity models up to 85 qubits and 5,000 two-qubit gates, matching DMRG results. The talk also mentions related algorithms (SQD, SQDrift) and the Quantum Advantage Tracker for community verification.

108 words

Critical Evaluation

Value of the Information & Strength of the Argument

The talk provides valuable insights into a practical quantum algorithm for near-term devices, emphasizing rigorous guarantees and experimental validation. The argumentation is solid, systematically addressing each criterion for quantum advantage. The speaker clearly explains the algorithm’s steps and justifies design choices, though some technical details are condensed.

56 words

Title / Content Match

The title accurately reflects the content, focusing on quantum advantage for ground state problems.

Quality & Reliability

8/10

Talk by IBM researcher presenting peer-reviewed algorithm (SKQD) with provable guarantees, backed by experimental results on IBM Heron processors up to 85 qubits. Claims are specific and reproducible via provided tools, though not all details are fully elaborated in the talk.

Key Moments

Markers derived by PSI from the transcript: the creator did not define chapters.

Cited Sources

SKQD paper (with ORNL) — Introduced SKQD algorithm with provable guarantees.
Quantum Advantage Tracker — Platform to verify and test quantum advantage claims.

Concurring Sources

IBM Quantum — IBM's quantum computing initiative, context for the talk.

Contribution & Novelties

The talk presents SKQD, a novel algorithm that combines shallow circuits, noise resilience, and provable guarantees, achieving state-of-the-art accuracy on 85-qubit impurity models. This is a significant step toward quantum advantage in ground state problems.

Pour aller plus loin :

Quantum Phase Estimation — Foundational algorithm for ground state energy with deep circuits.
DMRG — Classical state-of-the-art method for 1D systems, used as benchmark.
Variational Quantum Eigensolver — Heuristic near-term algorithm with measurement overhead issues.

75 words

Radar Profile

The radar profile shows high scores across all dimensions, indicating a well-rounded and reliable presentation with strong technical depth and credibility.

Reliability 8/10