quant-ph digest — 2026-04-30
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 (70 new + 20 cross = 90 entries)
Coverage: all 90 entries scored. 20 relevant (score ≥ 1); 70 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) — 7 papers
Query-Efficient Quantum Approximate Optimization via Graph-Conditioned Trust Regions
- Authors: Molena Huynh
- arXiv: 2604.24803
- Category: cross submission — Machine Learning (cs.LG) ; Quantum Physics (quant-ph)
- Score: 9/10 (HIGH)
- Overlaps with: Y1, Y3
- Why it matters: Graph-conditioned trust regions for QAOA where a GNN predicts a Gaussian over angles to seed local optimisation — same warm-start + parameter-optimisation lineage as Y1/Y3.
In low-depth implementations of the Quantum Approximate Optimization Algorithm (QAOA), the dominant cost is often the number of objective evaluations rather than circuit depth. We introduce a graph-conditioned trust-region method for reducing this query cost. A graph neural network predicts a Gaussian distribution N(mu, Sigma) over QAOA angles. The mean initializes a local optimizer, the covariance defines an ellipsoidal trust region that constrains the search, and the predicted uncertainty determines an instance-dependent evaluation budget. Thus the learned distribution defines a search policy rather than only an initial parameter estimate. Under explicit assumptions on local smoothness, cu…
Experimental Workflows for Combinatorial Optimization: Towards Quantum Advantage
- Authors: Prashanti Priya Angara, Luis F. Rivera, Ulrike Stege, Hausi Müller, Ibrahim Shehzad
- arXiv: 2604.25162
- Category: new submission — Quantum Physics (quant-ph)
- Score: 9/10 (HIGH)
- Overlaps with: Y2, Y3, Y4
- Why it matters: End-to-end hybrid quantum-classical workflows for combinatorial optimisation explicitly aimed at quantum-advantage demonstration; direct conclusion overlap with Y3 and scope overlap with Y2/Y4.
Demonstrating quantum advantage for combinatorial optimization requires more than standalone algorithmic results; it calls for end-to-end case studies that integrate problem modelling, quantum execution, and classical refinement into practical workflows. This paper presents a sandbox platform for experimenting with hybrid quantum-classical workflows in graph optimization, enabling the systematic study of end-to-end optimization pipelines. Using our platform, we investigate three classically intractable and mutually reducible graph problems -- Minimum Vertex Cover, Maximum Independent Set, and Maximum Clique -- by transforming them into an unconstrained problem and solving the resulting insta…
Graph-Conditioned Meta-Optimizer for QAOA Parameter Generation on Multiple Problem Classes
- Authors: Kien X. Nguyen, Ilya Safro
- arXiv: 2604.25275
- Category: new submission — Quantum Physics (quant-ph)
- Score: 9/10 (HIGH)
- Overlaps with: Y1, Y3
- Why it matters: Meta-optimiser that learns QAOA parameter generation across problem classes — directly extends Y1's warm-starting and Y3's layerwise/parameter-optimisation lines.
We study parameter transferability for the Quantum Approximate Optimization Algorithm (QAOA) across multiple combinatorial optimization problem classes from a parameter generation perspective. Specifically, a meta-optimizer is trained on one problem class and deployed on another during test time. Prior work employs a Long Short-Term Memory network to emulate QAOA optimization trajectories, but the learned dynamics usually collapse to near-identical paths, limiting cross-problem transfer efficiency. In this paper, we present a problem-aware graph-conditioned meta-optimizer for QAOA that learns to generate parameter trajectories over a fixed horizon, providing strong initializations with only…
A SWAP-free Framework for QAOA
- Authors: Thiago Assis, Pedro Baptista, Laila Lopes, Diego Ferreira, Gabriel Coutinho
- arXiv: 2604.25058
- Category: new submission — Quantum Physics (quant-ph) ; Combinatorics (math.CO)
- Score: 8/10 (HIGH)
- Overlaps with: Y1, Y3
- Why it matters: SWAP-free QAOA: modifies cost Hamiltonian to map natively to hardware topology — same QAOA-on-NISQ axis as Y1/Y3.
The performance of the Quantum Approximate Optimization Algorithm (QAOA) on noisy intermediate-scale quantum (NISQ) devices is strongly limited by sparse qubit connectivity. When interactions required by QAOA Hamiltonians are not aligned to the hardware topology, transpilation introduces SWAP gates, increasing circuit depth and noise. We propose a SWAP-free QAOA framework based on modifying the cost Hamiltonian so that it can be implemented natively on the hardware. We formulate this as a mixed-integer semidefinite program (MISDP) that selects a hardware-compatible approximation of the original cost matrix and optimizes the allocation of logical variables to physical qubits. We prove that th…
Quantum Optimization Methods for the Generalized Traveling Salesman Problem
- Authors: Maximilian Zorn, Melinda Braun, Michael Ertl, Tommy Kiss, Sara Juarez Oropeza, Claudia Linnhoff-Popien, Jonas Stein
- arXiv: 2604.25531
- Category: new submission — Quantum Physics (quant-ph) ; Emerging Technologies (cs.ET)
- Score: 8/10 (HIGH)
- Overlaps with: Y2, Y3
- Why it matters: QUBO + constrained QAOA with X-type hard mixer for the Generalised TSP — exactly Y2's hard-mixer-for-feasibility approach in a new constrained domain.
This paper studies quantum optimization baselines for the Generalized Traveling Salesman Problem (GTSP), a clustered routing problem that naturally models variant selection and sequencing problems under discrete alternatives. We propose a novel GTSP QUBO formulation focused on maintaining feasible solutions for quantum annealing, as well as a hardware-executable gate-based pipeline utilizing the Quantum Approximate Optimization Algorithm (QAOA). We implement a constrained QAOA variant using an XY-mixer, which preserves the stepwise Hamming weight in the ideal circuit model, while feasibility with respect to the full GTSP constraints is tracked explicitly during post-processing. We compare th…
Quantum annealing inspired algorithms for the NISQ Era
- Authors: Rijul Sachdeva, Vrinda Mehta, Manpreet Singh Jattana, Kristel Michielsen, Fengping Jin
- arXiv: 2604.25573
- Category: new submission — Quantum Physics (quant-ph)
- Score: 8/10 (HIGH)
- Overlaps with: Y1, Y3
- Why it matters: Approximate quantum annealing as a NISQ ansatz; resulting parameters used as initialisation — overlaps both Y1's warm-start and Y3's parameter scans / layerwise optimisation.
We study algorithms inspired by quantum annealing that are suited for the NISQ era. First, we analyze approximate quantum annealing (AQA), which employs a discretized annealing ansatz in which the time step and the number of layers are allowed to deviate from a faithful implementation of quantum annealing. Parameter scans identify regimes that reproduce annealing-like behavior with reduced resources, making them more suitable for NISQ devices. The resulting parameters can then be used as an effective warm start for the quantum approximate optimization algorithm (QAOA), improving its performance compared to random initializations. We also introduce evolving Hamiltonian quantum optimization (E…
Beyond Single Trajectories: Optimal Control and Jordan-Lie Algebra in Hybrid Quantum Walks for Combinatorial Optimization
- Authors: Tianen Chen, Yun Shang
- arXiv: 2604.25760
- Category: new submission — Quantum Physics (quant-ph)
- Score: 8/10 (HIGH)
- Overlaps with: Y1, Y2, Y3
- Why it matters: Hybrid quantum-walk ansatz that coherently superposes multiple driver paths inside each QAOA layer with optimal-control parameter design — direct method overlap with Y1/Y2/Y3.
The Quantum Approximate Optimization Algorithm (QAOA) follows a single, fixed evolution path, overlooking the potential computational advantage of coherently superposing multiple trajectories. Here we overcome this limitation with a hybrid quantum walk (HQW) ansatz that super poses multiple Hamiltonian-driven paths coherently within each circuit layer via a dynamical coin operator. QAOA emerges as a special case of this framework with a static Pauli-X coin. Using Pontryagin's minimum principle, we derive the optimal form of the coin operator, demonstrating that it generally differs from a constant gate. A dynamical Lie algebra analysis reveals that HQW generates a strictly larger Jordan-Lie…
Moderately relevant (score 5–7) — 5 papers
Ground-state energies of Ising models calculated using the samples from a quantum computer that simulates short-time evolution
- Authors: John P. T. Stenger, C. Stephen Hellberg, Daniel Gunlycke
- arXiv: 2604.25715
- Category: new submission — Quantum Physics (quant-ph)
- Score: 7/10 (MEDIUM)
- Overlaps with: Y1, Y3
- Why it matters: CVQE for Ising ground states on heavy-hex up to 63 qubits with explicit error/qubit-budget analysis — same scope as Y3's noise-regime crossover analysis for QAOA on QUBO/Ising problems.
We find the ground-state energy of the Ising model using the Cascaded Variational Quantum Eigensolver (CVQE) algorithm with the Guided-Sampling Ansatz (GSA) using up to 63 qubits on a quantum computer. We study a heavy-hex lattice to match the qubit architecture, allowing us to perform calculations in the quantum utility regime. We study both a homogeneous and random-coupling model. We locate the boundary of acceptable quantum errors as a function of the number of qubits and coupling strength. An entropic analysis is performed giving insights into the quantum computing performance. A subspace analysis is performed that suggests that the Ising model is especially suited for near-term quantum…
Sector-dominant graph-local drivers for path-window barrier Hamiltonians on the Boolean hypercube
- Authors: Takiko Sasaki, Tetsuji Tokihiro
- arXiv: 2604.25494
- Category: new submission — Quantum Physics (quant-ph) ; Mathematical Physics (math-ph)
- Score: 6/10 (MEDIUM)
- Overlaps with: Y1, Y2
- Why it matters: Custom graph-local adiabatic drivers using monotone Gray-code sector coordinates — adjacent to Y2's hard-mixer construction and Y1's iterative QAOA-style state preparation.
We study finite-size adiabatic state preparation on Boolean hypercubes using graph-local drivers built from sector/path coordinates related to monotone Gray-code representatives. The construction is not presented as a new all-$n$ Gray-code existence theorem; rather, it provides finite representatives, explicitly checked through the cases used in the numerical experiments, for testing problem-dependent graph-local drivers. For ordinary diagonal-cost transverse-field annealing, the ordering does not yield a robust advantage, and we include this negative result as a baseline. For non-diagonal target Hamiltonians whose geometry is expressed in the same sector/path coordinates, hybrid drivers com…
Simultaneous Fragment Docking for Geometrically Linkable Pose Pairs
- Authors: Jiyun Lee, You Kyoung Chung, Joonsuk Huh
- arXiv: 2604.24773
- Category: cross submission — Biomolecules (q-bio.BM) ; Quantum Physics (quant-ph)
- Score: 5/10 (MEDIUM)
- Overlaps with: Y2, Y4
- Why it matters: QUBO formulation for paired fragment docking with explicit constraint terms and quantum-annealing readout — adjacent to Y2's portfolio-QUBO encoding and Y4's cardinality-constrained binary optimisation.
Computational molecular design requires binding arrangements that are not only energetically favorable but also chemically realizable. However, computational methods remain limited in directly recovering fragment pose pairs that can later be connected into a single molecule. To address this problem, we formulated the simultaneous placement of two fragments as a quadratic unconstrained binary optimization problem, Q-SFD, and introduced an explicit inter-fragment distance term to favor reconstruction-feasible arrangements. Relative to the formulation without this term, Q-SFD approximately doubled top-1 recovery of reconstruction-feasible pairs, and the top-5 solutions contained at least one fe…
Ember: An Extensible Benchmark Suite for Quantum Annealing Embedding Algorithms
- Authors: Zachary Macaskill-Smith, Unmol Sharma, Melissa Warner, Kálmán Varga, David A. B. Hyde
- arXiv: 2604.25433
- Category: new submission — Quantum Physics (quant-ph)
- Score: 5/10 (MEDIUM)
- Overlaps with: Y3
- Why it matters: Standardised benchmark suite for quantum-annealing minor-embedding algorithms with reproducible metrics — supplies the comparison infrastructure that Y3-style end-to-end optimisation studies have been missing.
Minor embedding is a required compilation step for quantum annealing, mapping logical problem graphs onto sparse hardware topologies. Despite its central role in determining solution quality, no standardized benchmark exists for comparing embedding algorithms: prior studies use incompatible graph libraries, inconsistent metrics, and non-reproducible experimental setups, making cross-algorithm comparisons unreliable. We present Ember (Embedding Minor Benchmark for Evaluative Reproducibility), an open-source benchmarking framework addressing this gap. Ember provides a standardized algorithm interface with seeded, reproducible execution infrastructure; a diverse graph library of 24,016 instance…
One Coordinate at a Time: Convergence Guarantees for Rotosolve in Variational Quantum Algorithms
- Authors: Sayantan Pramanik, M Girish Chandra
- arXiv: 2604.25613
- Category: new submission — Quantum Physics (quant-ph)
- Score: 5/10 (MEDIUM)
- Overlaps with: Y1, Y3
- Why it matters: First proven convergence guarantee for Rotosolve coordinate descent on parametrised circuits — relevant to Y1/Y3's layerwise optimisation, where Rotosolve-family methods are common baselines.
In this paper, we resolve an open question in the field of optimization algorithms for training parametrized quantum circuits: Does the popular Rotosolve algorithm converge? Until now, interpolation-based coordinate descent methods such as Rotosolve have mostly been treated as heuristics, lacking any formal convergence guarantees. We rigorously analyze Rotosolve, and show that it converges to $\varepsilon$-stationary points if the optimization landscape is non-convex and smooth; and to $\varepsilon$-suboptimal points if the objective function additionally obeys the Polyak-Lojasiewicz (PL) condition. Further, we derive explicit worst-case rates of convergence in the finite quantum measurement…
Tangential (score 1–4) — 8 papers
- 2604.25503 · score 4/10 · Quantum-Accelerated Gowers $U_2$ Norm for Bent Boolean Functions — Hybrid quantum-classical GA where the quantum circuit evaluates Gowers U_2 norm as fitness for binary functions — method-adjacent to Y4's hybrid Grover/ADMM workflow for binary optimisation.
- 2604.24962 · score 3/10 · Use case study: benchmarking quantum breadth-first search for maximum flow problems — Benchmarks quantum BFS as a substitute for classical BFS in max-flow Dinic-style algorithms — Grover-style speedup on a structured combinatorial subroutine, adjacent to Y4.
- 2604.24973 · score 3/10 · Approximate Sparse State Preparation with the Grover-Rudolph Algorithm — Improvements to the Grover-Rudolph sparse-state preparation algorithm — Grover-family subroutine, tangential to Y4.
- 2604.25148 · score 3/10 · Extending UNIQuE: Quantum Simulation Speedup for the HHL Algorithm — Classical emulator for HHL — same dequantisation/classical-emulation flavour as Y5's quantum-inspired SDP solver.
- 2604.25333 · score 3/10 · Sign Embedding Quantum Algorithms for Matrix Equations and Matrix Functions — Sign-embedding quantum algorithms for matrix equations and matrix functions — block-encoded linear-algebra primitive in the same family Y5 builds on for SDP relaxations.
- 2604.25631 · score 3/10 · Local tensor-train surrogates for quantum learning models — Local tensor-train classical surrogates for trained QML models with provable accuracy — same dequantisation theme as Y5's classical solution of structured quantum problems.
- 2604.25863 · score 3/10 · MCMit: Mid-Circuit Measurement Error Mitigation — Holistic mid-circuit-measurement error-mitigation pipeline for superconducting hardware — relevant to Y3's noise-regime analysis and Y6's superconducting-hardware experiments.
- 2604.25901 · score 3/10 · Testing a continuous-variable Bell-like inequality with a hybrid-encoded system — Continuous-variable Bell-like inequality test on a hybrid-encoded photonic system — foundations test in the same family as Y6's PBR no-go test.
Summary table
| Score | arXiv ID | Short title | Overlaps | arXiv |
|---|---|---|---|---|
| 9 | 2604.24803 | Query-Efficient Quantum Approximate Optimization via Graph-Conditioned Trust Reg… | Y1, Y3 | link |
| 9 | 2604.25162 | Experimental Workflows for Combinatorial Optimization: Towards Quantum Advantage | Y2, Y3, Y4 | link |
| 9 | 2604.25275 | Graph-Conditioned Meta-Optimizer for QAOA Parameter Generation on Multiple Probl… | Y1, Y3 | link |
| 8 | 2604.25058 | A SWAP-free Framework for QAOA | Y1, Y3 | link |
| 8 | 2604.25531 | Quantum Optimization Methods for the Generalized Traveling Salesman Problem | Y2, Y3 | link |
| 8 | 2604.25573 | Quantum annealing inspired algorithms for the NISQ Era | Y1, Y3 | link |
| 8 | 2604.25760 | Beyond Single Trajectories: Optimal Control and Jordan-Lie Algebra in Hybrid Qua… | Y1, Y2, Y3 | link |
| 7 | 2604.25715 | Ground-state energies of Ising models calculated using the samples from a quantu… | Y1, Y3 | link |
| 6 | 2604.25494 | Sector-dominant graph-local drivers for path-window barrier Hamiltonians on the… | Y1, Y2 | link |
| 5 | 2604.24773 | Simultaneous Fragment Docking for Geometrically Linkable Pose Pairs | Y2, Y4 | link |
| 5 | 2604.25433 | Ember: An Extensible Benchmark Suite for Quantum Annealing Embedding Algorithms | Y3 | link |
| 5 | 2604.25613 | One Coordinate at a Time: Convergence Guarantees for Rotosolve in Variational Qu… | Y1, Y3 | link |
| 4 | 2604.25503 | Quantum-Accelerated Gowers $U_2$ Norm for Bent Boolean Functions | Y4 | link |
| 3 | 2604.24962 | Use case study: benchmarking quantum breadth-first search for maximum flow probl… | Y4 | link |
| 3 | 2604.24973 | Approximate Sparse State Preparation with the Grover-Rudolph Algorithm | Y4 | link |
| 3 | 2604.25148 | Extending UNIQuE: Quantum Simulation Speedup for the HHL Algorithm | Y5 | link |
| 3 | 2604.25333 | Sign Embedding Quantum Algorithms for Matrix Equations and Matrix Functions | Y5 | link |
| 3 | 2604.25631 | Local tensor-train surrogates for quantum learning models | Y5 | link |
| 3 | 2604.25863 | MCMit: Mid-Circuit Measurement Error Mitigation | Y3, Y6 | link |
| 3 | 2604.25901 | Testing a continuous-variable Bell-like inequality with a hybrid-encoded system | Y6 | link |