quant-ph digest — 2026-04-29

Generated 2026-04-29 · 118 entries scored · 25 relevant

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

Source

arXiv listing: https://arxiv.org/list/quant-ph/new (95 new + 23 cross = 118 entries; announce cycle for Tuesday, 28 April 2026)

Coverage: all 118 entries scored. 25 relevant (score ≥ 1); 93 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) — 5 papers

A Spectral Gap Informed Parameter Schedule for QAOA

A challenge with the Quantum Approximate Optimisation Algorithm (QAOA), and variational algorithms in general, is finding good variational parameters, a task which in itself can be NP-hard. Recent work has sought to de-variationalise QAOA by picking well-informed guesses for the variational parameters. The Linear Ramp QAOA (LR-QAOA) achieves this by using parameter schedules inspired by the quantum adiabatic algorithm. We go a step further and use spectral gap information from an adiabatic Hamiltonian, with the QAOA mixer Hamiltonian as our initial Hamiltonian, to make smooth ramps which we call Spectral Gap Informed Ramps (SGIR-QAOA). SGIR-QAOA schedules perform slow evolution where the spectral gap of the adiabatic Hamiltonian is small. We show that SGIR-QAOA has performance improvements over LR-QAOA on Grover's problem at constant depth and that SGIR-QAOA requires shorter depths to achieve the same optimal solution probability. We then show that these performance benefits extend to a problem with potential practical applications — the Maximum Independent Set (MIS) problem. Finally, we demonstrate the scalability of the SGIR-QAOA method using extrapolated spectral gap information for scales that the spectral gap cannot be exactly evaluated, and show that the advantage appears to persist under mild depolarising noise.

Exhaustive and feasible parametrisation with applications to the travelling salesperson problem

This paper introduces the concept of exhaustively parametrised, feasibility-respecting quantum circuits for constrained combinatorial optimisation problems. Such circuits can reach, given the right parameter values, every feasible solution with certainty — including the optimum — with a fixed number of parameters, while avoiding infeasible solutions altogether. This is in sharp contrast to conventional quantum alternating operator ansatz schemes, which are merely guaranteed to reach the optimum asymptotically. We introduce an abstract pipeline for constructing exhaustively parametrised, feasibility-respecting circuits from a transitive group action on a problem's feasible set. Our constructions rely on the simple combination of the group action with group representation and the novel notion of generating sequences: group elements in fixed order, possibly with repetitions, that generate the entire group.

Improvement of performance of Grover's algorithm on three generations of Heron family IBM QPUs without and with topological dynamical decoupling

We investigate the performance of Grover's algorithm on three different generations of IBM Heron QPUs. On Heron family of IBM QPUs the success probabilities for three, four and five qubits without dynamical decoupling is better than results reported for previous generations of QPUs. The success probability as function of number of iterations of Grover operator is considered. A study of the improvement of results of Grover's algorithm for five qubit case with the help of topological dynamical decoupling is considered. For a six qubit case on Heron r3 QPU a clear result for finding the sought-after bitstring is reported for theoretically suboptimal number of iterations of Grover operator with the help of dynamical decoupling.

Constrained Quantum Optimization meets Model Reduction

Quantum optimization algorithms promise advantages for difficult problems but are costly to simulate and analyze on classical machines. Recently, constrained quantum optimization has been investigated through the lens of Quantum Zeno dynamics, an approach which constrains the search to a subspace by means of quantum measurements. Exploiting that quantum measurements are projections, we propose a model reduction approach and show that simulations can be conducted in a lower-dimensional space. As possible applications, we demonstrate exponential state-space reduction of constrained quantum optimization in case of random 3-SAT and an agent coordination problem over graphs.

Optimization Using Locally-Quantum Decoders

It was pointed out in [JSW+25] that widely-studied optimization problems such as D-regular max-k-XORSAT can be reduced to decoding of LDPC codes, using quantum algorithms related to Regev's reduction. LDPC codes have very good decoders, such as Belief Propagation (BP), and this therefore makes D-regular max-k-XORSAT an enticing target for this class of quantum algorithms. However, BP was found insufficient to achieve quantum advantage. Here, we develop an intrinsically quantum decoding technique, which decodes classical LDPC codes subject to coherent superpositions of bit flip errors. For average-case instances of D-regular max-k-XORSAT drawn from Gallager's ensemble, this quantum decoder strongly outperforms classical belief propagation at many values of k and D. For some (k,D) the approximate optima achievable using this decoder surpass both Prange's algorithm and simulated annealing. However, we stop short of achieving quantum advantage because we identify an enhancement to Prange's algorithm that recovers a precise tie.

Moderately relevant (score 5–7) — 7 papers

Accelerating quantum Gibbs sampling without quantum walks

Szegedy's quantum walk gives a generic quadratic speedup for reversible classical Markov chains, but extending this mechanism to quantum Gibbs sampling has remained challenging beyond special cases. We present a walk-free quantum algorithm for preparing purified Gibbs states with a quadratic improvement in spectral-gap dependence for a broad class of quantum Gibbs samplers that satisfy exact Kubo-Martin-Schwinger detailed balance. Our main structural result is an explicit factorization of the corresponding parent Hamiltonian into noncommutative first-order operators. This turns purified Gibbs-state preparation into a singular-value filtering problem and enables a quantum singular value transformation algorithm with quadratically improved gap dependence under standard coherent-access assumptions.

Experimental high-dimensional multi-qubit Bell non-locality on a superconducting quantum processor

Combining recent advances in superconducting quantum hardware, we explore quantum correlations in a previously inaccessible regime by observing simultaneously high-dimensional and many-body Bell non-locality. We report a high-confidence Bell violation in the correlations between two d=64-dimensional systems encoded in twelve qubits. For system sizes up to d=32, the strength of the observed nonlocal correlations exceeds the quantum upper bound for d=2 systems, providing direct evidence of high-dimensional nonlocality. Furthermore, we demonstrate that the observed violation is genuinely collective: all qubits contribute to the nonlocal correlations, while most pairwise correlations across the bipartition remain Bell-local.

AutoQResearch: LLM-Guided Closed-Loop Policy Search for Adaptive Variational Quantum Optimization

Configuring variational quantum algorithms for combinatorial optimization remains a difficult, expert-driven process requiring coordinated choices over solver family, ansatz, objective, and optimizer. We present AutoQResearch, an LLM-guided closed-loop experimentation framework that casts this task as sequential policy search over a curated design space. Instead of a single static configuration, the framework searches for adaptive solver-control policies that condition future decisions on diagnostics such as feasibility, optimality gap, and convergence stagnation.

Practical lower bounds for hybrid quantum interior point methods in linear programming

Quantum interior point methods (QIPMs) promise polynomial speed-ups over classical solvers for linear programming by outsourcing the solution of Newton linear systems to quantum linear solvers (QLSAs). However, asymptotic speed-ups do not necessarily translate to practical advantages on realistic problem instances. In this work, I evaluate whether practical advantage of a standard hybrid QIPM pipeline can already be excluded relative to the classical open-source solver HiGHS on a broad and diverse collection of LP instances spanning eight problem families.

Non-unitary extension of Grover's search algorithm

We have developed a non-unitary extension of Grover's search algorithm by changing the hidden geometry of Hilbert space carried by diffusion operator. Our algorithm finds the solution for search problem by performing a unique bigger rotation rather than small rotations in order polynomial times in the size N of search space. We analyze the complexity of implementing the non-unitary operation and we observed that the price paid by performing this rotation is due the normalization. In Kraus operator approach we need O(N) repetition of the algorithm to have a chance of measuring a solution in a post-selection, this is no better than the classical solution. However, the quantum singular value transform in addition with block encoding and Chebyshev polynomial approximation, we got complexity O(log N).

Calibrating the Role of Entanglement in Variational Quantum Algorithms from a Geometric Perspective

Calibrating the role of entanglement in quantum algorithms is a crucial task in the development of quantum computing. Most existing studies have primarily focused on how the static properties of entanglement-such as its magnitude and phase-affect key performance metrics. In this work, we instead explore the relationship between the dynamical behaviors of entanglement and the execution of variational quantum algorithms from a geometric perspective. We find that, in contrast to conventional Hamiltonian dynamics where the evolution process is dominated by the dynamical phase, quantum state evolution in quantum algorithms is primarily governed by the geometric phase with the trajectory determined by the parameter-dependent Hilbert space geometry.

Explore Simpler Eigenmarking: Quantum Entailment Model Checking

Targeting entailment model checking, a recent study has pioneered an idea of Eigenmarking search, an improvement over Grover search using extra qubits. The extra qubits condition the quantum state evolution such that the answer states (if exist) are always in the minority. The minority criteria is essential to Grover probability-amplitude amplification and consequently the effectiveness of Grover search.

Tangential (score 1–4) — 13 papers

Summary table

ScorearXiv IDShort titleOverlapsarXiv
92604.24580Spectral Gap Informed Parameter Schedule for QAOAY1, Y2, Y3link
92604.24297Exhaustive feasible parametrisation, TSPY2, Y4link
82604.23228Grover on three Heron QPUs with topological DDY4, Y6link
82604.23317Constrained Quantum Optimization meets Model ReductionY2, Y3link
82604.24633Optimization Using Locally-Quantum DecodersY4, Y5link
72604.22996Accelerating quantum Gibbs sampling without quantum walksY5link
72604.24740High-dimensional multi-qubit Bell non-locality on superconducting QPUY6link
62604.24283AutoQResearch (LLM-guided VQO policy search)Y1, Y3link
62604.24362Practical lower bounds for hybrid QIPM in LPY4link
62604.23382Non-unitary extension of Grover's searchY4link
52604.23555Calibrating Entanglement in VQA (geometric)Y1, Y3link
52604.23531Eigenmarking: Quantum Entailment Model CheckingY4link
32604.24475Improving ZNE via Physically Bounded ModelsY3link
32604.24397Few-Shot Cross-Device Quantum Noise ModelingY3, Y6link
32604.22859Bell Inequalities from Polyhedral SamplingY6link
32604.23898Contextuality from the Projector Overlap MatrixY6link
32604.24735How Quantum Contextuality disappears in Classical LimitY6link
22604.23700Quantum Circuit Cutting: Complexity and OptimizationY3link
22604.23777Architecture-aware Unitary SynthesisY3link
22604.24467Adaptive Tensor Network Sampling for QOCY1, Y3link
22604.24551GSC-QEMit (telemetry-driven QEM)Y3link
22604.24422Noise-aware circuit cutting under non-uniform noiseY3link
22604.24727Operating a contextual Stern-Gerlach apparatusY6link
22604.24760Contracting Tensor Networks with Generalized BPY4link
22604.23304Intrinsic Pointer Basis and Irreversible ClassicalityY6link