quant-ph digest — 2026-04-25

Generated 2026-04-25 · 69 entries scored · 11 relevant

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

Source

arXiv listing: https://arxiv.org/list/quant-ph/new (58 new + 11 cross = 69 entries, announce cycle Friday 2026-04-24)

Coverage: all 69 entries scored. 11 relevant (score ≥ 1); 58 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

Qubit-efficient and gate-efficient encodings of graph partitioning problems for quantum optimization

We introduce a qubit- and gate-efficient higher-order unconstrained binary optimization (HUBO) encoding for graph partitioning problems requiring label-count minimization. This widely applicable class of problems includes minimum graph coloring, minimum k-cut, and community detection. To the best of our knowledge, this is the first work to address the optimization versions of these problems in a quantum setting, rather than only their decision counterparts. Our construction encodes each k-valued vertex variable using ⌈log₂ k⌉ bits and employs a novel lexicographic penalty system that implicitly minimizes partition count without requiring dedicated indicator variables. [truncated]

Partial oracles quantum algorithm framework — Part I: Analysis of in-place operations

The partial oracles framework is a quantum search algorithm that has the potential to exceed the quadratic speedup of Grover's algorithm, up to a theoretical maximum of an exponential speedup. Until now, however, the framework has lacked an explicit method for constructing the operator that represents the search iteration. In this paper, we provide the missing construction, for the special case of an oracle function definable using only in-place operations (that is, where the calculated result of the oracle function can be read just from the qubits in the search index). The restriction to in-place operations means that the current work does not yet exhibit quantum advantage. [truncated]

Moderately relevant (score 5–7) — 3 papers

A rigorous quasipolynomial-time classical algorithm for SYK thermal expectations

Estimating local observables in Gibbs states is a central problem in quantum simulation. While this task is BQP-complete at asymptotically low temperatures, the possibility of quantum advantage at constant temperature remains open. The Sachdev-Ye-Kitaev (SYK) model is a natural candidate: at any constant temperature, its Gibbs states have polynomial quantum circuit complexity and are not described by Gaussian states. […] Despite this, we give a rigorous proof of a quasipolynomial-time classical algorithm that estimates SYK local thermal expectations at sufficiently high constant temperature. Our result introduces a new Wick-pair cluster expansion that we expect to be broadly useful for disordered quantum many-body systems.

Efficient Classical Simulation of Heuristic Peaked Quantum Circuits

Peaked quantum circuits, whose output distribution is sharply concentrated on a single bitstring, have emerged as a promising candidate for verifiable quantum advantage. Recent work by Gharibyan et al. arXiv:2510.25838 claimed heuristic quantum advantage using peaked circuits executed on Quantinuum's 56-qubit H2 processor. […] We show that these circuits can be efficiently simulated classically. We describe a method that efficiently performs a full tensor network contraction, allowing near-exact sampling and extraction of the peaked bitstring. The method exploits the mirrored structure of the circuit and iteratively cancels both halves into a Matrix Product Operator (MPO), and avoids the obfuscated permutation by greedily reducing the MPO bond dimension.

On the importance of hyperparameters in initializing parameterized quantum circuits

There has been intensive research on increasing the utility and performance of Parameterized Quantum Circuits (PQCs) in the past couple of years. […] In this paper, we focus on the problem of finding performant initial parameters for a given PQC. Different from previous research that focuses on finding the right distribution, we focus on finding the hyperparameters for any given distribution. To that end we introduce an evolutionary-search based algorithm that finds optimal hyperparameter given a PQC and quantum task. Our empirical results indicate that our algorithm consistently leads to selection of performant initial parameters tuned specifically to the ansatz and the quantum task leading to faster convergence and performance. More importantly, our algorithm does not negatively affect the barren plateau phenomenon.

Tangential (score 1–4) — 6 papers

Summary table

ScorearXiv IDShort titleOverlapsarXiv
92604.21123Qubit/gate-efficient HUBO encoding for graph partitioningY2, Y4link
82604.21788Partial oracles framework (Part I, in-place)Y4link
72604.21089Quasipolynomial classical alg for SYK Gibbs expectationsY5link
62604.21908Classical simulation of peaked quantum circuitsY5link
52604.21266Hyperparameters for PQC initializationY1, Y3link
42604.21863Replay-buffer RL for noise-robust circuit optimizationY1, Y3link
32604.20961VQE ansatz expressivity for TFIMY1, Y3link
32604.21458HEOM calibration loop for SC qubitsY3link
32604.21705Testing spontaneous collapse modelsY6link
32604.21919Tensor-network belief propagation with provable boundsY5link
22604.21630KMS/GNS spectral gap of quantum Markov semigroupsY5link