quant-ph digest — 2026-05-14
Scored against Yuan's research programme (Y1–Y6):
- Y1 — arXiv:2502.09704 — iterative warm-started QAOA
- Y2 — arXiv:2304.06915 — quasi-binary portfolio QAOA
- Y3 — arXiv:2410.16265 — QAOA DGMVP portfolio (QST 2026)
- Y4 — arXiv:2603.14744 — Grover + ADMM cardinality-constrained BO
- Y5 — arXiv:2510.08292 — GW speed-ups via Gibbs states + Pauli sparsity
- Y6 — arXiv:2510.11213 — PBR test on IBM Heron2
Source
arXiv listing: https://arxiv.org/list/quant-ph/new (61 new + 12 cross = 73 entries, announce cycle Wed 13 May 2026)
Coverage: all 73 entries scored. 9 relevant (score ≥ 1); 64 SKIP (score 0, omitted).
Scoring rubric
0–10 on method/scope/conclusion overlap — max wins. HIGH 8–10 · MED 5–7 · LOW 1–4 · SKIP 0.
Highly relevant (score 8–10) — 1 paper
Benchmarking and Resource Analysis for Augmented-Lagrangian Quantum Hamiltonian Descent
- Authors: Zeguan Wu, Mingze Li, Muqing Zheng, Meng Wang, Junyu Liu, Samuel Stein, Ang Li, Yousu Chen, Chenxu Liu
- arXiv: 2605.12066
- Category: new submission — Quantum Physics (quant-ph)
- Score: 8/10 (HIGH)
- Overlaps with: Y4 (method — ADMM/ALM-style classical-quantum hybrid for constrained nonconvex optimization), Y2/Y3 (scope — constrained nonconvex/iterative-refinement portfolio-style optimization), Y3 (conclusion — NISQ resource estimates rule out near-term advantage; FT regime required)
- Why it matters: This is the QHD-side counterpart to Yuan's Grover+ADMM (Y4) and QAOA-portfolio (Y2/Y3) work: same hybrid architecture, same iterative-refinement philosophy at fixed qubit cost, same FT-vs-NISQ resource verdict on a real engineering problem (ACOPF, $\sim 530$ variables). It is a directly comparable end-to-end study from a non-overlapping group and a strong citation candidate for any future Yuan paper on constrained quantum optimization.
Quantum Hamiltonian Descent (QHD) is a continuous optimization algorithm based on simulating a time-dependent quantum Hamiltonian whose potential energy encodes the objective function and whose kinetic energy promotes exploration through quantum interference and tunneling. While QHD is formulated for unconstrained optimization, many real-world optimization problems are constrained and highly nonconvex. In this paper, we benchmark AL-QHD, a hybrid framework that embeds QHD within the Augmented Lagrangian Method (ALM), thereby solving a sequence of unconstrained subproblems while using ALM to enforce constraints. We evaluate AL-QHD on standard nonconvex test functions and use iterative refinement to improve solution accuracy at fixed per-run qubit cost. We also perform a gate-based resource analysis on ACOPF-derived power-system subproblems constructed from power-network data to estimate the quantum-computer scale required for practical applications. Resource estimates on Texas7k-derived ACOPF instances show steep hard-gate scaling, reaching ~4.46×107 entangling gates in a NISQ-oriented model and ~9.42×108 T gates in a fault-tolerant model at ~5.3×102 active variables.
Moderately relevant (score 5–7) — 3 papers
Digital Annealer-Assisted Accuracy-First Quantum Circuit Transpilation with Integrated QUBO Mapping and Routing
- Authors: (see arXiv listing)
- arXiv: 2605.11500
- Category: new submission — Quantum Physics (quant-ph)
- Score: 5/10 (MED)
- Overlaps with: Y2/Y3 (method — QUBO formulation as solved by classical/annealing primitives), scope (NISQ-era circuit fidelity, gate-count minimisation as a downstream cost driver in Y3-style noise analyses)
- Why it matters: Frames qubit mapping/routing for NISQ transpilation as a QUBO and solves it on a Digital Annealer, achieving 13.7% (avg, up to 57.4%) CNOT reduction over Qiskit's highest opt level. The QUBO structure is the same family Yuan attacks with QAOA — relevant as a baseline of what classical annealers can do on the QUBOs produced by these workflows, and it tightens the pipeline that determines effective fidelity in Y3-style noise studies.
In the Noisy Intermediate-Scale Quantum (NISQ) era, limited qubit counts and high gate error rates directly constrain circuit fidelity, making the minimization of CNOT gate counts crucial. While conventional compilers prioritize heuristic efficiency, there is a compelling need for “accuracy-first” transpilation that prioritizes gate reduction over compilation latency. We propose a framework leveraging the Digital Annealer (DA) via two complementary strategies: (1) Hybrid, which uses DA-driven global initial mapping combined with high-speed heuristic routing by Qiskit, and (2) Full DA, which solves mapping and routing as separate DA-assisted QUBO subproblems within an iterative workflow. Benchmarks demonstrate that our Hybrid approach achieves an average CNOT reduction of 13.7% (up to 57.4%) compared to Qiskit's highest optimization level, with the largest gains on structured circuits.
Runtime Calibration as State-Trajectory Feedback Control in Quantum-Classical Workflows
- Authors: (see arXiv listing)
- arXiv: 2605.11860
- Category: new submission — Quantum Physics (quant-ph); Hardware Architecture (cs.AR); Emerging Technologies (cs.ET)
- Score: 5/10 (MED)
- Overlaps with: Y3 (scope — NISQ superconducting variational workloads, gate/readout fidelity drift on hour timescales, exactly the regime where Yuan's thermal-relaxation analysis applies); Y1/Y2 (variational/iterative scheduling)
- Why it matters: Treats runtime calibration as a feedback-control problem under fixed wall-clock budget; finds tight-loop calibration (4 µs) and local-ms calibration both open positive-gain regions for variational workloads, while cloud-like (25 ms) is uncompetitive. This directly addresses the Y3 finding that thermal/relaxation noise dominates QAOA performance at NISQ; their result quantifies how calibration scheduling could partially recover quality in Yuan's setting.
In superconducting devices running variational workloads, gate and readout fidelities drift on hour timescales, while existing runtime schedulers treat backend quality as static. The temporal dimension of calibration remains unresolved. We formulate runtime calibration as a state-trajectory feedback-control problem under a fixed wall-clock budget, and investigate whether spending time on calibration now can improve the future optimization trajectory. ... Using a finite-horizon rollout controller, we compare feedback calibration against a strengthened family of open-loop baselines across three latency regimes: cloud-like (25 ms), local-millisecond (1 ms), and tight-loop (4 µs). The results show a clear ordering: cloud-like feedback is generally uncompetitive, while local-ms and tight-loop regimes open a positive-gain region.
QAP-Router: Tackling Qubit Routing as Dynamic Quadratic Assignment with Reinforcement Learning
- Authors: (see arXiv listing)
- arXiv: 2605.12365
- Category: new submission — Quantum Physics (quant-ph); Artificial Intelligence (cs.AI)
- Score: 5/10 (MED)
- Overlaps with: Y2/Y4 (method — QAP is a quadratic-assignment problem, structurally a generalisation of QUBO; cardinality/permutation-constrained), scope (combinatorial optimization as an NP-hard problem solved by quantum-adjacent ML)
- Why it matters: Models qubit routing as a Quadratic Assignment Problem (QAP) with a flow matrix and a distance matrix — structurally close to the QUBOs and constrained binary problems Yuan attacks with QAOA (Y2) and Grover+ADMM (Y4). The solution-aware Transformer encoding the flow×distance interaction is a useful contrast to QAOA's parameterised quantum approach to similar combinatorial structure.
Qubit routing is a fundamental problem in quantum compilation, known to be NP-hard. ... We introduce QAP-Router, framing qubit routing based on a dynamic Quadratic Assignment Problem (QAP) formulation. By modeling logical interactions, or quantum gates, as flow matrices and hardware topology as a distance matrix, our approach captures the interaction-distance coupling in a unified objective, which defines the reward in the reinforcement learning environment. ... Extensive experiments on 1,831 real-world quantum circuits show that our method substantially reduces the CNOT gate count of routed circuits by 15.7%, 30.4% and 12.1%, respectively, relative to existing industry compilers.
Tangential (score 1–4) — 5 papers
- 2605.11016 · score 3/10 · Counting anticommuting Pauli pairs in linear time — classical $O(m)$ subroutine for processing large Pauli-string lists in bounded-locality regime; useful primitive for Y5-style Pauli-sparse Gibbs-state algorithms.
- 2605.11228 · score 3/10 · Quantum Algorithm for Identifying Hidden Graphs: Spectral Theory and Numerical Evidence — quantum-walk + Hadamard-test algorithm with conjectured exponential speedup for graph identification; combinatorial-quantum-speedup theme adjacent to Y4.
- 2605.11879 · score 3/10 · Pre-Asymptotic Trainability in Photonic Variational Circuits under Postselection — barren-plateau / variational trainability analysis (photonic-specific); same trainability landscape that gates Y1/Y2/Y3 QAOA optimisation.
- 2605.12502 · score 3/10 · Scalable Measurement-Based Quantum Simulation Patterns for Benchmarking — QPatLib measurement-pattern library for MBQC; the MBQC paradigm is the substrate of Y1's measurement-based warm-starting.
- 2605.11488 · score 2/10 · Breaking the scalability barrier via a vertical tunable coupler in 3D integrated transmon system — 3D-integrated transmon hardware; the NISQ superconducting platform that hosts Y3-style QAOA experiments and Y6 PBR tests.
Summary table
| Score | arXiv ID | Short title | Overlaps | arXiv |
|---|---|---|---|---|
| 8 | 2605.12066 | Augmented-Lagrangian Quantum Hamiltonian Descent | Y4 method, Y2/Y3 scope, Y3 conclusion | link |
| 5 | 2605.11500 | Digital Annealer QUBO transpilation | Y2/Y3 method+scope | link |
| 5 | 2605.11860 | Runtime Calibration as feedback control | Y3 scope; Y1/Y2 variational | link |
| 5 | 2605.12365 | QAP-Router (RL qubit routing) | Y2/Y4 method (QAP/QUBO) | link |
| 3 | 2605.11016 | Anticommuting Pauli pair counting | Y5 (Pauli sparsity) | link |
| 3 | 2605.11228 | Quantum algo for hidden graphs | Y4 (combinatorial speedup) | link |
| 3 | 2605.11879 | Photonic variational trainability | Y1/Y2/Y3 (variational) | link |
| 3 | 2605.12502 | MBQC simulation patterns library | Y1 (measurement-based) | link |
| 2 | 2605.11488 | 3D vertical tunable coupler transmons | Y3/Y6 (NISQ SC scope) | link |