quant-ph digest — 2026-05-29

Generated 2026-06-01 · 103 entries scored · 23 relevant

Scored against Yuan's research programme (Y1–Y6):

Source

arXiv listing: https://arxiv.org/list/quant-ph/new (85 new + 18 cross = 103 entries from the Friday 29 May 2026 announce cycle)

Coverage: all 103 entries scored. 23 relevant (score ≥ 1); 80 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) — 2 papers

Evaluating Parameter Transfer in FALQON Across Graph Families

We evaluate FALQON parameter transfer for Max-Cut, transferring sequences from small donors ($n \in \{8,10,12\}$) to 14-node recipients. Using 3-regular and Erdős-Rényi families, we show that transfer success is dictated by the recipient graph, not the donor. Transfer excels for dense recipients -- achieving high approximation ratios regardless of the donor -- but remains challenging in sparse cross-family cases. Crucially, performance is highly resilient to donor size, with 8-node donors matching larger instances. Thus, cheap small graphs can provide robust parameters for larger targets, significantly reducing the measurement overhead of the feedback loop.

Non-Abelian Mixer for QAOA on Hybrid Oscillator-Qubit Quantum Processors

The realization of universal control in hybrid oscillator-qubit quantum processors enables the systematic design and implementation of quantum algorithms. However, the algorithmic development for such platforms remains at an early stage. While the Quantum Approximate Optimization Algorithm (QAOA) has been extensively studied in both continuous-variable (CV) and discrete-variable (DV) quantum systems, its development in the hybrid CV-DV setting remains limited. In this paper, we propose a hardware-native non-Abelian mixer for QAOA on hybrid CV-DV quantum processors and develop a corresponding hybrid ansatz for the Max-Cut problem. We evaluate the proposed ansatz on unweighted Erdős-Rényi grap…

Moderately relevant (score 5–7) — 8 papers

Quantitative semidefinite certificates for ground-state energies of Pauli Hamiltonians

The $k$-local Hamiltonian problem is a central model for quantum many-body systems and Hamiltonian complexity. Semidefinite programming and noncommutative sum-of-squares hierarchies provide systematic certificates for ground-state energies, but existing finite-convergence results give no quantitative guarantee on the accuracy of the low hierarchy levels accessible in computation. We prove explicit finite-level convergence rates for these hierarchies in the Pauli setting. For $k$-local Hamiltonians whose Pauli expansion contains only even-weight terms, we show that both the NPA-type lower-bound hierarchy and the upper-bound hierarchy on the spectral minimum have error at most $C(k)\xi^{n,4}_{…

Quantum optimization beyond QUBO for industrial logistics and scheduling

The increasing complexity of industrial scheduling and transport routing problems motivates the study of alternative optimization formulations and computational paradigms. In this work, we study how higher-order unconstrained binary optimization (HUBO) formulations of such problems map onto quantum optimization workflows in both noisy and fault-tolerant regimes. We consider three representative logistics and manufacturing use cases and formulate each as a HUBO problem. This captures process intricacies, such as highly correlated assembly-line scheduling rules, which are difficult to express faithfully with the standard quadratic (QUBO) form, while at the same time reducing the number of bina…

Hybrid Gaussian-exponential zero-noise extrapolation for periodic circuits

Zero-noise extrapolation provides a practical means of suppressing gate errors in current noisy intermediate-scale quantum hardware. The accuracy of the zero-noise estimate depends sensitively on the fidelity of the assumed noise model to the actual error scaling. This work introduces a hybrid Gaussian-exponential extrapolation scheme tailored for quantum circuits with periodic structure, which are ubiquitous in quantum algorithms. Under Pauli diagonal errors, by constructing and analyzing an approximate Markov process for the transfer of Pauli operators, we prove a central limit theorem: the noise amplification factor weakly approaches a log-normal distribution, which motivates augmenting t…

Exponentially Fast Solution State Preparation for the Heat Equation and its use for Option Pricing

In this work, we present the methods necessary to price an important set of derivatives on a quantum device while offering an advantage over existing classical methods. The methods developed here, in conjunction with ~\cite{GumaroS2026}, also provide an exponential advantage in requirement of qubits when pricing some option contracts with path-dependent payoff compared to state-of-the-art quantum Monte Carlo methods.

Elfs, transducers and quantum walks

Electric flow sampling (elfs) is a new tool in the quantum walk toolbox and a useful primitive for solving search, sampling and optimization problems on graphs. We refine this tool by showing that there exists a zero-error transducer for implementing elfs. More broadly, we establish a zero-error transducer for reflecting about the intersection of two subspaces, yielding an errorfree transducer version of the effective gap lemma. Building on this result, we obtain improved quantum walk algorithms for estimating effective resistances and span program witness sizes with an optimal error scaling, and for sampling from the random walk arrival distribution, via the composition of many elfs. Using …

Alternative adiabatic quantum dynamics with algorithmic applications

In adiabatic quantum computing the aim is to track an eigenstate as the Hamiltonian changes. In the usual setup this is achieved using the natural time-dependent Hamiltonian evolution of the system and the main technical tool is the adiabatic theorem. We propose several alternative processes that achieve the same goal, but can easily be implemented on a gate-based quantum computer without the overhead of simulating time-dependent Hamiltonian evolution. We give a general framework for deriving `adiabatic' theorems for these processes. As an application, we give various algorithms for solving the Quantum Linear Systems Problem (QLSP) with optimal scaling in the condition number. One of these a…

Overcoming the Matrix-Product-State Encoding Barrier via DMRG-Guided Probabilistic Imaginary-Time Evolution

Ground-state preparation is a fundamental task in quantum simulation, because the overlap of the prepared state with the true ground state significantly affects the overall cost of subsequent quantum algorithms. We propose a three-stage framework in which a matrix product state (MPS) of an $N$-site system obtained by the density-matrix renormalization group (DMRG) is loaded onto an $N$-qubit quantum register through an optimization-free matrix product disentangler (MPD) encoding circuit, and the residual error is then reduced by probabilistic imaginary-time evolution (PITE). We demonstrate that the central-bond Schmidt rank of intermediate states during MPS encoding grows logistically with t…

High-Fidelity ROI CT Reconstruction with Limited Quantum Resources via Hybrid Classical-Quantum Refinement

Quantum optimization for computed tomography (CT) reconstruction is constrained by the number of binary variables required for image representation, making direct whole-image quantum reconstruction difficult for large or structurally complex objects. We propose a hybrid region-of-interest (ROI) refinement framework in which a coarse global image is first reconstructed by quantum tomographic reconstruction (QTR) and quantum compressed sensing tomographic reconstruction (QCSTR), filtered backprojection (FBP), or simultaneous algebraic reconstruction technique (SART), and quantum optimization is then applied only to the selected ROI through a residual projection-image formulation. This strategy…

Tangential (score 1–4) — 13 papers

Summary table

ScorearXiv IDShort titleOverlapsarXiv
92605.29917Evaluating Parameter Transfer in FALQON Across Graph FamiliesY1, Y3link
82605.30234Non-Abelian Mixer for QAOA on Hybrid Oscillator-Qubit Quantum ProcessorsY2, Y6link
72605.29959Quantitative semidefinite certificates for ground-state energies of Pauli HamiltoniansY5link
62605.29242Hybrid Gaussian-exponential zero-noise extrapolation for periodic circuitsY3, Y4, Y6link
62605.30252Quantum optimization beyond QUBO for industrial logistics and schedulingY2, Y3, Y4link
52605.28950Exponentially Fast Solution State Preparation for the Heat Equation and its use for Opt…Y3link
52605.29472High-Fidelity ROI CT Reconstruction with Limited Quantum Resources via Hybrid Classical…Y3link
52605.30013Elfs, transducers and quantum walksY4link
52605.30110Alternative adiabatic quantum dynamics with algorithmic applicationsY1, Y3link
52605.30141Overcoming the Matrix-Product-State Encoding Barrier via DMRG-Guided Probabilistic Imag…Y3link
42605.28986Comparing Classical Simulation and Sample-Based Learning of Quantum Systems: Learning t…link
42605.29723Treewidth-Aware Gate Cut Selection for Reducing Transpilation Overhead on Superconducti…link
42605.29872Claim against Measurement: Statistical Artefacts in Quantum Error Mitigation Benchmarkslink
42605.29944Quadratic Sums-of-Powers for Fixed-Parameter Tractable Quantum-Circuit Simulationlink
42605.30026On the question of noise as a resource in quantum computinglink
32605.29181A Variational Quantum Algorithm for Nonlinear Finite Element Analysis of Hyperelastic M…link
32605.29521Ground-state estimation of the Heisenberg model on frustrated lattices with Sample-base…link
32605.29589Bell's theorem: why probability factorisation failslink
22605.29514Non-Clifford Crosstalk Noise in Surface Codes Using Hybrid Stabilizer-Tensor Network Me…link
22605.29775Incompleteness is necessary for activation of nonlocality without entanglementlink
22605.30067Quantum Mechanics: Problems and Paradoxeslink
22605.30217Programmable Dissipation via Partial Quantum Error Correctionlink
22605.30238Indefinite Causal Order Reverses the Real-Complex Hierarchylink