quant-ph digest — 2026-05-20

Generated 2026-05-20T01:42:37Z · 126 entries scored · 15 relevant

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

Source

arXiv listing: https://arxiv.org/list/quant-ph/new (100 new + 26 cross = 126 entries)
Coverage: all 126 entries scored. 15 relevant (score ≥ 1); 111 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) — 4 papers

A Penalty-Free Pipeline for Direct Quantum-Annealer Portfolio Optimization

Direct quantum-annealer portfolio optimization is commonly formulated as a penalty-encoded QUBO and submitted to D-Wave hardware. We show that this standard formulation fails on current devices and identify the structural reason: the cardinality penalty contributes a dense rank-one term proportional to the all-ones matrix that makes the logical interaction graph complete regardless of the covariance structure. On Pegasus and Zephyr, chain-break fractions reach 83 percent at N equal to 24 and 92 percent at N equal to 49, producing no feasible samples. Attempting to fix this through topology-aware sparsification reveals a second problem: any sparsifier that removes off-diagonal entries also…

Where the Quantum Lives in D-Wave Hybrid Portfolio Optimization

We audit how much of D-Wave's hybrid quantum-classical portfolio-optimization service is actually quantum. On cardinality-constrained mean-variance-turnover instances spanning N equal to 10 to 640 with a Gurobi MIQP optimality anchor, the constraint-native LeapHybridCQM service matches Gurobi's proven optimum on all 54 instances where Gurobi proves optimality, but the mean QPU access time is only 0.034 seconds out of a 5-second wall-clock budget, roughly 0.7 percent of the run. The remaining roughly 99 percent is the service's classical decomposition, sub-problem assembly, and feasibility-aware reassembly, so the reported D-Wave hybrid win on this problem class is a constraint-native…

Truncated-Binary Encoding: Spectral Degree Reduction of Combinatorial Optimization Problems for Quantum Hardware

Exact-binary encoding compiles a discrete cost function network (CFN) into a higher-order unconstrained binary optimization (HUBO) problem whose maximum monomial degree grows with the cardinalities of the underlying CFN variables. Given that quantum optimization hardware generally favours quadratic unconstrained binary optimization or low-degree HUBO Hamiltonians, high-cardinality CFNs therefore incur substantial overhead in the form of circuit depth, or ancilla qubits when degree-reduction techniques are employed. To ameliorate these issues, we propose \textit{truncated-binary encoding} (TBE): a modification of exact-binary encoding in which Ising-basis monomials exceeding a chosen cutoff…

Quantum Model for CVRPTW

This paper proposes a quantum algorithm for the capacitated vehicle routing problem with time windows (CVRPTW) based on Grover Search framework. This problem is often faced by Postal services in the context of package delivery or other time-sensitive operations. We provide an implementation on gate based quantum computer of a model inspired by classical route first, cluster second technique. The quantum paradigm allows to overcome suboptimality inherent property of this decomposition. In the current NISQ (Noisy Intermediate-Scale Quantum) era, the most important limitation is the number of available qubits which makes time windows and capacity constraints hard to tackle. We introduce a…

Moderately relevant (score 5–7) — 7 papers

Scaling Quantum Optimization for Unit Commitment via Pauli Correlation Encoding

Unit commitment is an important optimization problem in power system operations, classified as NP-hard. This paper presents a hybrid quantum-classical method for the unit commitment problem with time-dependent constraints, where decisions must be made about which generators to turn on/off and how much power they should produce over a planning horizon. We use a hybrid quantum-classical optimization procedure to determine the on/off schedules of the generating units and the corresponding power dispatch that satisfies operational constraints such as load balance, generator limits, ramping, and reserve requirements. We frame the optimization loop as a leader-follower structure, where the…

From Constraint to Code: DQI-Kit -- A Software Framework for Decoded Quantum Interferometry

Trying to solve hard optimisation problems with quantum techniques requires transformations of domain objectives and constraints into formats compatible with a chosen quantum algorithm. This often introduces inefficiencies and overheads that limit or even endanger potential quantum advantage for current and future approaches. To understand and mitigate these inefficiencies, software toolchains are essential for implementing transformations, analysing overheads and eventually selecting optimal transformation paths. Decoded Quantum Interferometry (DQI) is a novel approach that achieves apparent quantum advantage for certain algebraic optimisation problems. It natively operates on Max-LINSAT,…

Efficient Hamiltonian Engineering for Adiabatic MIS Algorithms

We present a hybrid adiabatic algorithm for maximum independent set (MIS) using Rydberg atom arrays. We engineer local controls that preferentially excite atoms with few neighbors, which represent graph nodes with small degrees. Numerical simulations show that the designed pulses accelerate convergence to the MIS state and suppress population in trap states. We obtain higher success probabilities than traditional global controls and a $25\%$ reduction in fidelity decay rate as problem hardness increases.

Schedule-dependent basin occupation in a programmable quantum annealer

On a mixed-frustration 12-qubit Ising instance (seed 14029) run on two D-Wave generations, Advantage2 Zephyr and Advantage_system6.4 Pegasus, the late-time subsystem autocorrelation under cycled reverse annealing sits strictly between two equilibrium reference processes at the device-calibrated effective temperature: localized parallel tempering, and delocalized equilibrated path-integral simulated quantum annealing at a fixed Advantage2 pause-point transverse-field scale. The bracket holds on all three tested schedules and at both hardware calibrations. We obtain this result through two ingredients: a cycled reverse-anneal protocol (reinitialize_state=False, 50 cycles per submission) used…

An Entropy-Governed Speedup for Quantum Algorithms on Local Hamiltonians

Low-energy estimation and state preparation for general $k$-local Hamiltonians are fundamental challenges in quantum complexity theory. For constant relative accuracy, Buhrman et al. (PRL 2025) recently broke the natural Grover bound $O(2^{n/2})$, where $n$ denotes the number of qubits, for both problems. In this paper, for any sufficiently small parameter $d\ge 0$, we present an even faster quantum algorithm that outputs a quantum state with energy bounded by the minimum energy over all depth-$d$ states (i.e., states obtained by applying a depth-$d$ circuit to the all-zero state), together with an estimate of this energy. For the class of Hamiltonians with depth-$d$ ground states, our…

Structural $f$-divergence: Tight universal bounds for cost function moments and gradients in parameterized quantum circuits

The barren plateau phenomenon, in which cost-function gradients of variational quantum algorithms vanish exponentially, remains a central obstacle for near-term quantum computing. Existing analyses typically depend on t-design or Haar-random assumptions and bound quantities at the level of unitary distributions, offering limited insight for designing probability measures on the parameter space of parameterized quantum circuits. In this paper, we introduce the structural $f$-divergence, a symmetric $f$-divergence-based measure between probability distributions on the parameter space. We establish analytically trade-off inequalities that bound the discrepancies in the expected gradient…

The QuaST Decision Tree: Achieving Automation With Data-Based Recommendations

Quantum computers are increasingly powerful. Software tools for the development of quantum-enhanced algorithms are maturing. However, the software stack still lacks the connection to applications that would enable hybrid algorithms combining classical and quantum computing steps. End users need to be assisted in choosing the best combination of preprocessing, postprocessing, classical and quantum algorithms options. The application-facing software stack is therefore required to cover problem modeling, encoding, algorithm selection and hyperparameter tuning. A variety of tools exist for specific recommendations. The QuaST Decision Tree reflects the complexity in combining individual…

Tangential (score 1–4) — 4 papers

Summary table

ScorearXiv IDShort titleOverlapsarXiv
102605.17628A Penalty-Free Pipeline for Direct Quantum-Annealer Portfolio OptimizationY2 (method: no-penalty), Y3 (scope: cardinality portfolio), Y4 (scope: cardinality BO)link
92605.17623Where the Quantum Lives in D-Wave Hybrid Portfolio OptimizationY3 (scope: portfolio benchmark), Y4 (scope: cardinality-constrained), Y2 (method: constraint-native)link
92605.17143Truncated-Binary Encoding: Spectral Degree Reduction of Combinatorial Optimization Prob…Y2 (method: encoding for QAOA), Y1 (method: warm-start basin analysis)link
82605.18393Quantum Model for CVRPTWY4 (method: Grover Adaptive Search on structured feasible space)link
72605.17145Scaling Quantum Optimization for Unit Commitment via Pauli Correlation EncodingY2 (method: qubit-efficient encoding of binary decision variables)link
62605.16955From Constraint to Code: DQI-Kit -- A Software Framework for Decoded Quantum Interferom…Y2 (method: encoding transformations for constrained optimization)link
62605.16944Efficient Hamiltonian Engineering for Adiabatic MIS AlgorithmsY3 (scope: NISQ combinatorial optimization on hardware)link
62605.17604Schedule-dependent basin occupation in a programmable quantum annealerY3 (scope: annealing-based combinatorial optimization, noise-regime benchmarking)link
62605.18241An Entropy-Governed Speedup for Quantum Algorithms on Local HamiltoniansY4 (method: Grover-bound improvement for structured Hamiltonians)link
52605.18051Structural $f$-divergence: Tight universal bounds for cost function moments and gradien…Y1 / Y3 (method: variational-circuit optimization landscape)link
52605.18539The QuaST Decision Tree: Achieving Automation With Data-Based RecommendationsY1–Y4 (method: hybrid quantum-classical solver software stack)link
42605.18112Linear-optical test of quantum contextuality with sequential measurementsY6 (foundations: nonclassicality test on hardware, adjacent)link
32605.18243One pure steered state implies Einstein-Podolsky-Rosen steeringY6 (foundations: EPR steering, adjacent)link
22605.18291Quantum randomness beyond projective measurementsY6 (foundations: measurement randomness)link
22605.16500Robust generalized quantum Stein's lemmaY5 (loose: SDP / relative-entropy continuity tools)link