quant-ph digest — 2026-05-11

Generated 2026-05-11 · 77 entries scored · 12 relevant

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

Source

arXiv listing: https://arxiv.org/list/quant-ph/new (59 new + 18 cross = 77 entries)

Coverage: all 77 entries scored. 12 relevant (score ≥ 1); 65 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) — 3 papers

Quantum Search without Global Diffusion

Authors: John Burke, Ciaran McGoldrick (Trinity College Dublin)

arXiv: 2604.15435

Category: new submission — Quantum Physics (quant-ph); Data Structures and Algorithms (cs.DS)

Score: 8/10 (HIGH)

Overlaps with: Y4 (Grover / amplitude-amplification method); secondary tie to Y1 via amplitude-overlap construction.

Why it matters: Proves that Grover's quadratic speedup survives without a global diffusion operator when the prepared and target states factorise across a partition — opening a route to dramatically shallower diffusion circuits in cardinality-constrained Grover loops like Y4's algorithm, with quantifiable depth-vs-oracle-overhead trade-offs.

Quantum search is among the most important algorithms in quantum computing. At its core is quantum amplitude amplification, a technique that achieves a quadratic speedup over classical search by combining two global reflections: the oracle, which marks the target, and the diffusion operator, which reflects about the initial state. We show that this speedup can be preserved when the oracle is the only global operator, with all other operations acting locally on non-overlapping partitions of the search register. We present a recursive construction that, when the initial and target states both decompose as tensor products over these chosen partitions, admits an exact closed-form solution for the algorithm's dynamics. This is enabled by an intriguing degeneracy in the principal angles between successive reflections, which collapse to just two distinct values governed by a single recursively defined angle.

Asymptotic optimality of Grover–Radhakrishnan–Korepin algorithm

Authors: Kun Zhang, Kang-Yuan Chen, Xiao-Hui Wang, Vladimir Korepin (Northwest University, Stony Brook)

arXiv: 2604.15886

Category: new submission — Quantum Physics (quant-ph)

Score: 8/10 (HIGH)

Overlaps with: Y4 (Grover variant / optimal-control proof of query-count optimality).

Why it matters: Closes a long-standing structural conjecture for partial-search Grover algorithms — proves the global–local–global ordering is asymptotically query-optimal via Pontryagin maximum principle. The same control-theoretic machinery is the right framework for arguing tightness of Y4's Grover stage and for a potential depth-optimality follow-up.

Grover's algorithm is a cornerstone of quantum algorithms and is strictly optimal in oracle-query complexity. While the full search problem admits no further improvement, one may trade accuracy for speed in the partial search problem, where the task is to identify only the block containing the target item. The best known quantum algorithm for the partial search problem is the Grover-Radhakrishnan-Korepin (GRK) algorithm, whose optimality has long been conjectured but not proved. In this work, we prove the optimality of GRK in the large-block limit. We formulate partial search as a time-optimal control problem and apply the Pontryagin maximum principle to derive the switching-function dynamics, establish the bang-bang structure of regular extremals, and exclude non-optimal switching patterns. As a result, we show that the optimal regular extremal has the global-local-global form, which yields a control-theoretic proof of the asymptotic optimality of the GRK algorithm in oracle-query complexity.

Overcoming the Lamb Shift in System-Bath Models via KMS Detailed Balance: High-Accuracy Thermalization with Time-Bounded Interactions

Authors: Hongrui Chen, Zhiyan Ding, Ruizhe Zhang

arXiv: 2604.15616

Category: new submission — Quantum Physics (quant-ph)

Score: 8/10 (HIGH)

Overlaps with: Y5 (quantum Gibbs state preparation — supplies an early-FT-friendly Gibbs primitive complementing Y5's Pauli-sparse SDP framework).

Why it matters: First end-to-end Õ(1/ε) cost for system-bath Gibbs preparation at constant interaction time T, with single-qubit baths and no block-encoded jump operators — exactly the early-FT-friendly Gibbs primitive Y5's Pauli-sparse Goemans–Williamson speed-up programme needs at the implementation level.

We investigate quantum thermal state preparation algorithms based on system-bath interactions and uncover a surprising phenomenon in the weak-coupling regime. We rigorously prove that, if the system-bath interaction is engineered so that the transition part of the approximate Lindbladian generator satisfies the KMS detailed balance condition, then the unique fixed point of the dynamics can be made arbitrarily close to the Gibbs state in the weak-coupling limit, regardless of the structure of the Lamb shift term. Importantly, this remains true even when the approximate Lindbladian differs substantially from the ideal Davies generator and the Lamb shift term does not commute with the thermal state.

Moderately relevant (score 5–7) — 3 papers

Quantum computation at the edge of chaos

Authors: Tomohiro Hashizume, Zhengjun Wang, Frank Schlawin, Dieter Jaksch

arXiv: 2604.15441

Category: new submission — Quantum Physics (quant-ph)

Score: 5/10 (MED)

Overlaps with: Y1, Y3 (VQA trainability / barren-plateau / cost-function-shape — same family of issues that constrain QAOA depth-scaling).

Why it matters: Proposes topological-entanglement-entropy regularisation as a cost-function shape principle to address barren plateaus in VQAs, including QAOA-style variational ansatzes. Adjacent to Y1/Y3's parameter-optimisation pathways and worth tracking if Y1/Y3's next iteration targets trainability under noise.

A key challenge in classical machine learning is to mitigate overparameterization by selecting sparse solutions. We translate this concept to the quantum domain, introducing quantum sparsity as a principle based on minimizing quantum information shared across multiple parties. This allows us to address fundamental issues in quantum data processing and convergence issues such as the barren plateau problem in Variational Quantum Algorithm (VQA). We propose a practical implementation of this principle using the topological Entanglement Entropy (TEE) as a cost function regularizer.

Observable-Guided Generator Selection for Improving Trainability in Quantum Machine Learning

Authors: Hiroshi Ohno

arXiv: 2604.15693

Category: new submission — Quantum Physics (quant-ph)

Score: 5/10 (MED)

Overlaps with: Y1, Y2, Y3 (parameterised-unitary / Pauli-generator design — directly maps to QAOA mixer / cost-Hamiltonian generator selection).

Why it matters: Formulates Pauli-string generator selection for parameterised circuits as a binary optimisation problem favouring mutually anti-commuting generators. The framing — picking generators to maintain first-order gradient sensitivity while suppressing second-order interference — is directly applicable to QAOA-mixer design and could complement Y2's hard-constraint-preserving mixer construction.

To study generator design for parameterized unitaries in quantum machine learning (QML), we propose an observable-guided generator selection algorithm for n-qubit Pauli-string generator pools. The proposed method selects generators based on two criteria: maintaining large first-order sensitivity in the gradients and suppressing second-order interference in the Hessian matrix. Under a restricted setting with Pauli-string observables and candidate generators, the selection problem can be formulated as a binary optimization problem that favors mutually anti-commuting generators.

Quantum-Inspired Simulation of 2D Turbulent Rayleigh-Bénard Convection

Authors: Nis-Luca van Hülst, Mario Guillaume Cecile, Hai-Yen Van, Tomohiro Hashizume, Eugene de Villiers, Dieter Jaksch

arXiv: 2604.16179

Category: cross submission — Fluid Dynamics (physics.flu-dyn); Computational Physics; Quantum Physics

Score: 5/10 (MED)

Overlaps with: Y5 (quantum-inspired classical algorithm; Matrix Product State compression — same dequantisation-style argument family).

Why it matters: Pushes MPS-based quantum-inspired classical simulation into a regime (buoyancy-driven turbulence at Ra=10¹⁰) where quantum-inspired tensor-network methods compete with state-of-the-art DNS. Reinforces Y5's broader thesis that structured classical algorithms can dequantise quantum primitives in high-dimensional settings.

Turbulent thermal convection governs heat transport in systems ranging from stellar interiors to industrial heat exchangers. […] We apply MPS to two-dimensional Rayleigh-Bénard convection with dynamical simulations up to Ra = 10¹⁰. An a priori decomposition of DNS snapshots up to Ra = 10¹¹ shows that the bond dimension χ required to represent the flow fields grows weakly with Rayleigh number.

Tangential (score 1–4) — 6 papers

Summary table

ScorearXiv IDShort titleOverlapsarXiv
82604.15435Quantum Search without Global DiffusionY4link
82604.15886Asymptotic optimality of GRK algorithmY4link
82604.15616Lamb-Shift / KMS detailed balance Gibbs preparationY5link
52604.15441Quantum computation at the edge of chaos (VQA sparsity)Y1, Y3link
52604.15693Observable-Guided Generator Selection (QML/QAOA)Y1, Y2, Y3link
52604.16179Quantum-Inspired MPS Rayleigh-BénardY5link
32604.15427TNBP cannot simulate Google quantum echoesY5link
32604.15920Local qubit invariants on IBM QuantumY6link
22604.15666Explainable quantum regressionY1–Y3link
22604.15895Digital predistortion for superconducting qubitsY6link
22604.16107Molecular quantum eraser (photoelectron holography)Y6link
22604.16144Gravitationally induced wave-function collapseY6link