quant-ph digest — 2026-05-02

Generated 2026-05-02 · 80 entries scored · 19 relevant

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

Source

arXiv listing: https://arxiv.org/list/quant-ph/new (65 new + 15 cross = 80 entries; announce cycle Friday, 1 May 2026)
Coverage: all 80 entries scored. 19 relevant (score ≥ 1); 61 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) — 6 papers

Explicit Quantum Search Algorithm for the Densest k-Subgraph Problem

This paper addresses the problem of finding the densest $k$-vertex subgraph in an arbitrary graph. This problem is NP-hard and has important applications in social network analysis, fraud detection, recommendation systems, and bioinformatics. We propose two quantum approaches to solve this problem: reduction to Quadratic Unconstrained Binary Optimization (QUBO) and using Grover's quantum search algorithm. For the latter approach, we present an explicit gate-based oracle circuit utilizing Dicke states and Quantum Fourier Transform for edge counting. Numerical simulations demonstrate a quadratic speedup over classical Brute-force search.

Efficient mapping of multi-constraint satisfaction problems to Rydberg platforms

We present a hardware-native gadget framework for solving constraint satisfaction problems on Rydberg quantum computing architectures. Our approach introduces a compact $xor_1$ gadget that enforces exactly-one constraints, ubiquitous in combinatorial optimization, directly through geometric embedding and blockade interactions. A key advantage of the $xor_1$ gadget is its fixed, problem-size-independent detuning requirements: enforcing constraints through blockade interactions eliminates the need for large penalty terms, thereby substantially reducing the detuning range compared to Quadratic Unconstrained Binary Optimization (QUBO) formulations and improving experimental feasibility. By tailo…

Formulating Subgroup Discovery as a Quantum Optimization Problem for Network Security

While current network intrusion detection systems achieve satisfactory accuracy, they often lack explainability. Subgroup Discovery (SD) addresses this by building interpretable rules that characterize feature interactions associated with attack traffic. With large datasets, classical heuristic beam search methods struggle with exponentially scaling search spaces and can prune critical multi-feature interactions. This paper introduces a quantum-enhanced pipeline for SD applied to network intrusion detection using NSL-KDD, formulating SD as quantum optimization for the first time. By encoding feature selection as a Quadratic Unconstrained Binary Optimization (QUBO) and solving it via the Quan…

Q3SAT-GPT: A Generative Model for Discovering Quantum Circuits for the 3-SAT Problem

This work introduces Q3SAT-GPT, a generative model for discovering quantum circuits for the Max-E3-SAT problem. Our method learns from high-performing QAOA-style ansätze to directly generate candidate circuits. To create high-quality supervision, we also introduce Mosaic Adaptive QAOA (MosaicADAPT-QAOA), an adaptive strategy for constructing low-depth QAOA circuits by selecting subsets of mixer operators in each step, rather than inserting operators sequentially. The resulting circuits serve as training data for the generative model, allowing it to learn effective circuit design patterns while eliminating the need for costly variational optimization at inference time. Experiments show that o…

Finite Imaginary-Time Evolution for Polynomial Unconstrained Binary Optimization

Imaginary-time evolution is a standard primitive for ground-state preparation but is nonunitary, precluding direct quantum implementation. We develop Finite Imaginary-Time Evolution (FinITE), a finite-beta construction for diagonal Pauli-Z cost Hamiltonians arising from polynomial unconstrained binary optimization (PUBO) instances, including QUBO and HUBO cases. FinITE uses the linear-combination-of-unitaries (LCU) framework to implement a scaled imaginary-time propagator. The commuting Pauli-Z structure makes termwise block-encodings compose without product-formula error, and higher-order Pauli-Z terms are handled directly without quadratization. The structure yields an exact finite-beta id…

Towards High Performance Quantum Computing (HPQ): Parallelisation of the Hamiltonian Auto Decomposition Optimisation Framework (HADOF)

Practical applicability of quantum optimisation on near term devices is constrained by limited qubit counts and hardware noise, which restricts the scalability of quantum optimisation algorithms for combinatorial problems. The simulation of large quantum circuits is also difficult and constrained by memory requirement. The Hamiltonian Auto Decomposition Optimisation Framework (HADOF) addresses this by decomposing large QUBOs into smaller subproblems that can be solved iteratively on quantum or classical backends. This allows the scalability of quantum QUBO algorithms beyond device limits, as well as their simulation on classical devices. In this research, we extend the evaluation of HADOF by…

Moderately relevant (score 5–7) — 3 papers

Demonstration of Exponential Quantum Speedup with Constant-Depth Compiled Circuits for Simon's Problem

We demonstrate exponential quantum speedup for a restricted-Hamming-weight version of Simon's problem on present-day superconducting quantum processors by introducing a hardware-aware compilation strategy that compiles the quantum part of each Simon query circuit to constant depth. The resulting compiled circuits have $O(1)$ depth and linear connectivity, map directly onto common device layouts, and avoid additional routing and SWAP overhead. Implemented on IBM's $156$-qubit Boston and $120$-qubit Miami processors, the resulting circuits achieve sufficiently high fidelity to exhibit algorithmic quantum speedup without error suppression. Using the number-of-queries-to-solution metric, we obse…

Permutation Invariant Optimization Problems in Quantum Information Theory: A Framework for Channel Fidelity and Beyond

Exploiting permutation invariance to reduce the exponential scaling of semidefinite programs in quantum information has emerged as a powerful computational technique. In this work, we develop a systematic framework for using this reduction via Schur-Weyl duality for optimization problems, and establish methods that allow one to work fully inside the permutation invariant subspace while performing operations such as (partially) applying channels and taking (partial) traces, or computing expressions like the quantum relative entropy. We then apply our techniques to the problem of computing efficient lower bounds on the channel fidelity over $n$ parallel uses of a quantum channel. The algorithm…

Congestion-free routing on quantum chips

Limited connectivity makes nonlocal quantum gates expensive on near-neighbor hardware, where compilation typically relies on SWAP transport, inheriting both depth overhead and path congestion. We present a swap-free routing framework in which higher levels of a qudit act as orthogonal spectral buses that transport control information without moving the computational state. We show that exact congestion relief in nearest-neighbor architectures requires local Hilbert-space expansion. In this model, a nonlocal operation over a path of length $L$ requires $2L+1$ logical routing primitives, compared to the $3L$ baseline. Overlapping routes remain distinguishable through bus labels encoded in the …

Tangential (score 1–4) — 10 papers

Summary table

ScorearXiv IDShort titleOverlapsarXiv
92604.27782Explicit Quantum Search Algorithm for the Densest k-Subgraph ProblemY4link
82604.27030Efficient mapping of multi-constraint satisfaction problems to Rydberg platformsY2, Y4link
82604.27153Formulating Subgroup Discovery as a Quantum Optimization Problem for Network Sec…Y2, Y3, Y4link
82604.27324Q3SAT-GPT: A Generative Model for Discovering Quantum Circuits for the 3-SAT Pro…Y1, Y2link
82604.27482Finite Imaginary-Time Evolution for Polynomial Unconstrained Binary OptimizationY1, Y2, Y3link
82604.27836Towards High Performance Quantum Computing (HPQ): Parallelisation of the Hamilto…Y2, Y3, Y4link
72604.27457Demonstration of Exponential Quantum Speedup with Constant-Depth Compiled Circui…Y6link
62604.27040Permutation Invariant Optimization Problems in Quantum Information Theory: A Fra…Y5link
52604.27015Congestion-free routing on quantum chipsY3link
22604.27042Onset of superactivation of quantum capacityY5link
22604.27125Derivation of the Born Rule and Operational Quantum Formalism in the Accessibili…Y6link
22604.27339Fixed-PVM Born Rule Uniqueness from Fisher Non-Expansion and Operational Calibra…Y6link
22604.27648Effective Noise Mitigation via Quantum Circuit Learning in Quantum Simulation of…Y3link
22604.27886Unentangled stoquastic Merlin-Arthur proof systems: the power of unentanglement …Y5link
12604.27171Structure-Aware Transformers for Learning Near-Optimal Trotter Orderings with Sy…Y3link
12604.27838Heisenberg-limited Hamiltonian learning without short-time controlY6link
12604.28009Learning quantum disentanglement scheduling from reduced states via modular hybr…Y3link
12604.28121Quantum Lattice Boltzmann Solutions for Transport under 3D Spatially Varying Adv…Y3, Y6link
12604.28160Reorganizing Quantum Measurement Records Improves Time-Series PredictionY3link