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Shiqi Cao

Publications and source records attributed to Shiqi Cao.

4 recordsLinked to original sources

Wilf Equivalence for Length-Three Patterns and Flat POPs, and a Conjecture of Qiu and Remmel

It is well known that, for each classical pattern $τ$ of length 3, the number of $τ$-avoiding permutations of length $n$ is the $n$th Catalan number, and numerous bijections between different length-three avoidance classes have been constructed and studied. In this paper, we refine this classical problem by studying Wilf equivalence among permutations that simultaneously avoid a classical pattern of length three and a flat partially ordered pattern. Partially ordered patterns (POPs) provide a flexible framework for encoding families of classical permutation patterns. For $\ell\geq 3$ and $1\leq x\leq\ell$, let $P_{\ell,x}$ be the length-$\ell$ POP in which the entry at position $x$ is required to be smaller than all the other entries, while no relations are imposed among the remaining entries. Such POPs are called flat POPs. We classify the Wilf equivalences among all pairs $(τ,P_{\ell,x})$, where $τ$ is a classical pattern of length three. For every $\ell\geq4$, the resulting $6\ell$ pairs form exactly $2\ell-1$ Wilf equivalence classes, while the exceptional case $\ell=3$ gives four classes. Our proofs combine the derivation of explicit formulas and recurrence relations with the construction of bijections. Moreover, we introduce novel prime-divisor arguments to distinguish the remaining candidate classes, reducing the problem to showing that a certain Diophantine equation has no solutions for $\ell\ge 3{,}274$, where the bound $3{,}274$ is not claimed to be sharp. Finally, by extending our work on POPs, we resolve a conjecture of Qiu and Remmel concerning the distribution of quadrant marked mesh patterns on 132-avoiding permutations and correct an error in their paper that is crucial to the proof.

math.CO

Counting permutations avoiding two flat partially ordered patterns

Partially ordered patterns (POPs) play an important role in the study of permutation patterns, providing a convenient framework for describing large families of classical patterns. The problem of enumerating permutations that avoid POPs has therefore attracted considerable attention in the literature. In particular, Gao and Kitaev resolved many counting problems for POP-avoiding permutations of lengths 4 and 5, linking the enumeration to a wide range of other combinatorial objects. Motivated by their work, we initiate the study of permutations that simultaneously avoid two POPs belonging to the class of flat POPs. We establish a connection between permutations avoiding such POPs and the $k$-Fibonacci numbers. Moreover, we provide a bijection between permutations avoiding these POPs and certain restricted permutations, which allows us to use the method developed by Baltić to derive the generating function for permutations avoiding these POPs. Finally, we obtain enumerative results for separable permutations avoiding these two POPs, of lengths up to 5, with respect to six statistics, thereby extending the results of Gao et al. on the avoidance of a single flat POP in separable permutations. Notably, when both patterns are of length 5, the respective generating function is a rational function, with the sum in the numerator (resp., denominator) containing 293 (resp., 17) monomials.

math.CO

Dowling's polynomial conjecture for independent sets of matroids

The celebrated Mason's conjecture states that the sequence of independent set numbers of any matroid is log-concave, and even ultra log-concave. The strong form of Mason's conjecture was independently solved by Anari, Liu, Oveis Gharan and Vinzant, and by Brändén and Huh. The weak form of Mason's conjecture was also generalized to a polynomial version by Dowling in 1980 by considering certain polynomial analogue of independent set numbers. In this paper we completely solve Dowling's polynomial conjecture by using the theory of Lorentzian polynomials.

math.CO

ResPanDiff: Diffusion Model for Pansharpening by Inferring Residual Inference

The implementation of diffusion-based pansharpening task is predominantly constrained by its slow inference speed, which results from numerous sampling steps. Despite the existing techniques aiming to accelerate sampling, they often compromise performance when fusing multi-source images. To ease this limitation, we introduce a novel and efficient diffusion model named Diffusion Model for Pansharpening by Inferring Residual Inference (ResPanDiff), which significantly reduces the number of diffusion steps without sacrificing the performance to tackle pansharpening task. In ResPanDiff, we innovatively propose a Markov chain that transits from noisy residuals to the residuals between the LRMS and HRMS images, thereby reducing the number of sampling steps and enhancing performance. Additionally, we design the latent space to help model extract more features at the encoding stage, Shallow Cond-Injection~(SC-I) to help model fetch cond-injected hidden features with higher dimensions, and loss functions to give a better guidance for the residual generation task. enabling the model to achieve superior performance in residual generation. Furthermore, experimental evaluations on pansharpening datasets demonstrate that the proposed method achieves superior outcomes compared to recent state-of-the-art~(SOTA) techniques, requiring only 15 sampling steps, which reduces over $90\%$ step compared with the benchmark diffusion models. Our experiments also include thorough discussions and ablation studies to underscore the effectiveness of our approach.

cs.CV