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cs.DS updates on arXiv.org

PAC Learning with Bandit Feedback: Sharp Sample Complexity in the Realizable Setting Algorithms with Polynomially-Improved Approximation Factors for the $2 \rightarrow q$ Norm, and Applications A computational phase transition for learning-to-sample from Ising models Covering vertices by sequential stars Fermi-Dirac machines as quantizations of neurons A Comprehensive Evaluation of Vertex Elimination Algorithms for Algorithmic Differentiation A Tight Bound on Localization of Electrical Flows Optimal Dimension-Free Sampling for Regularized Classification Reducing the Randomness in Partition Oracles for Bounded Degree Minor-Free Graphs Beyond the Half-Approximation: Fair and Efficient Online Class Matching Efficient Uniform Sampling of Surjections via their Profiles Tractable Maximization of Budgeted Phylogenetic Diversity on Networks Utilizing Node Scanwidth Fairness in Aggregation: Optimal Top-$k$ and Improved Full Ranking Learning-Augmented Online Scheduling with Parsimonious Preemption Entropy Equivalence Testing Lumberjack: Better Differentially Private Random Forests through Heavy Hitter Detection in Trees The Secretary Problem with a Stochastic Precursor Polynomial-Time Robust Multiclass Linear Classification under Gaussian Marginals Efficient Banzhaf-Based Data Valuation for $k$-Nearest Neighbors Classification Block-Sphere Vector Quantization An Approximation Algorithm for Graph Label Selection Iterative Chow Filtering for Learning with Distribution Shift Complexity of Non-Log-Concave Sampling in Fisher Information Stochastic Matching via Local Sparsification Finite Sample Bounds for Learning with Score Matching What is Learnable in Valiant's Theory of the Learnable? Provable Quantization with Randomized Hadamard Transform Min-Max Optimization Requires Exponentially Many Queries Fast and Compact Graph Cuts for the Boykov-Kolmogorov Algorithm A proximal gradient algorithm for composite log-concave sampling
Coherent Rollout Oracles for Finite-Horizon Sequential De...
Nishant Shukla · 2026-04-28 · via cs.DS updates on arXiv.org

Coherent quantum rollout for sequential decision problems requires a unitary simulator: randomness must live in explicit quantum registers, and basis-state selectors must be mapped to actions reversibly. With branch-dependent valid actions, this mapping is totalized coherent rank-select over an entangled $N$-bit validity mask: return the position of the $r$-th valid bit, or a sentinel if $r$ is out of range. We give the first reversible-circuit complexity analysis of this primitive. For selector width $w = \lceil \log_2(N+1) \rceil$, rank-select admits an $O(Nw)$-gate low-ancilla bounded-span scan, proved gate-optimal in its model, and an $O(N\log w)$-gate low-ancilla blocked construction when long-range gates are available; across all bounded-fan-in layouts, the unconditional gate lower bound is $Ω(N)$. Composing rank-select with reversible transition and predicate-evaluation circuits gives an explicit polynomial-size coherent rollout oracle for finite-horizon planning problems satisfying these primitive assumptions. The resulting oracle satisfies the access model of the best-arm pipeline of Wang et al., yielding $\widetilde{O}(\sqrt{k}/\varepsilon)$ coherent oracle calls against the standard classical $Ω(k/\varepsilon^2)$ arm-pull lower bound. We give a bounded-influence lifting theorem that extends this lower-bound construction from a base configuration to an exponential family of configurations. We instantiate the construction on SIR epidemic intervention, with a stochastic placement-game sanity check, and machine-check the main results in Lean 4. Code and proofs: https://github.com/BinRoot/b01t/tree/main/demos/rollout.