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Newton-Okounkov bodies and toric degenerations arxiv.org/abs/2407.14515

Newton-Okounkov bodies and toric degenerations

In recent times, a wide variety of combinatorics has been introduced in order to solve problems from algebraic geometry. Newton-Okounkov bodies and tropical geometry are two such combinatorial theories. As shown by Kaveh and Manon, there is a certain correspondence between these two. Building on this correspondence, and exploiting the link of both theories to toric degenerations, Harada and Escobar obtained their wall-crossing result for prime cones. This result states that moving between two adjacent prime maximal cones in a tropical variety corresponds to a mutation between the associated Newton-Okounkov bodies of these cones. In this thesis, we provide a method for applying the wall-crossing result to non-prime cones. Our approach uses a procedure developed by Bossinger, Lamboglia, Mincheva and Mohammadi in order to compute an embedding which changes a tropical variety in such a way that a non-prime cone becomes prime. Assuming that adjacent cones stay adjacent, the wall-crossing result can then be applied in this new embedding. Building on computations by Clarke, Mohammadi and Zaffalon, we show that for Gr(3,6), this approach works. We compute the new embedding and its tropicalization in this case, and study the relation between cones in the new embedding and the original embedding.

arxiv.org

A Random Matrix Model for a Family of Cusp Forms arxiv.org/abs/2407.14526

A Random Matrix Model for a Family of Cusp Forms

The Katz-Sarnak philosophy states that statistics of zeros of $L$-function families near the central point as the conductors tend to infinity agree with those of eigenvalues of random matrix ensembles as the matrix size tends to infinity. While numerous results support this conjecture, S. J. Miller observed that for finite conductors, very different behavior can occur for zeros near the central point in elliptic curve $L$-function families. This led to the creation of the excised model of Dueñez, Huynh, Keating, Miller, and Snaith, whose predictions for quadratic twists of a given elliptic curve are well fit by the data. The key ingredients are relating the discretization of central values of the $L$-functions to excising matrices based on the value of the characteristic polynomials at 1 and using lower order terms (in statistics such as the one-level density and pair-correlation) to adjust the matrix size. We extended this model for a family of twists of an $L$-function associated to a given holomorphic cuspidal newform of odd prime level and arbitrary weight. We derive the corresponding "effective" matrix size for a given form by computing the one-level density and pair-correlation statistics for a chosen family of twists, and we show there is no repulsion for forms with weight greater than 2 and principal nebentype. We experimentally verify the accuracy of the model, and as expected, our model recovers the elliptic curve model.

arxiv.org

Convexity and concavity of a class of functions related to the elliptic functions arxiv.org/abs/2407.14547

Convexity and concavity of a class of functions related to the elliptic functions

We investigate the convexity property on $(0,1)$ of the function $$f_a(x)=\frac{{\cal K}{(\sqrt x)}}{a-(1/2)\log(1-x)}.$$ We show that $f_a$ is strictly convex on $(0,1)$ if and only if $a\geq a_c$ and $1/f_a$ is strictly convex on $(0,1)$ if and only if $a\leq\log 4$, where $a_c$ is some critical value. The second main result of the paper is to study the log-convexity and log-concavity of the function $$h_p(x)=(1-x)^p{\cal K}(\sqrt x).$$ We prove that $h_p$ is strictly log-concave on $(0,1)$ if and only if $p\geq 7/32$ and strictly log-convex if and only if $p\leq 0$. This solves some problems posed by Yang and Tian and complete their result and a result of Alzer and Richards that $f_a$ is strictly concave on $(0,1)$ if and only if $a=4/3$ and $1/f_a$ is strictly concave on $(0,1)$ if and only if $a\geq 8/5$. As applications of the convexity and concavity, we establish among other inequalities, that for $a\geq a_c$ and all $r\in(0,1)$ $$\frac{2π\sqrtπ}{(2a+\log 2)Γ(3/4)^2}\leq \frac{{\cal K}(\sqrt r)}{a-\frac12\log (r)}+\frac{{\cal K}(\sqrt{1-r})}{a-\frac12\log (1-r)}<1+\fracπ{2a},$$ and for $p\geq 3(2+\sqrt 2)/8$ and all $r\in(0,1)$ $$\sqrt{(r-r^2)^p{\cal K}(\sqrt{1-r}){\cal K}(\sqrt r)}< \frac{π\sqrtπ}{2^{p+1}Γ(3/4)^2}<\frac{r^p{\cal K}(\sqrt{1-r})+(1-r)^p{\cal K}(\sqrt r)}{2}.$$

arxiv.org

On the Distributions of Product and Quotient of two Independent $\hat{I}$-function variates arxiv.org/abs/2407.14554

On the Distributions of Product and Quotient of two Independent $\hat{I}$-function variates

The study of probability distributions for random variables and their algebraic combinations has been a central focus driving the advancement of probability and statistics. Since the 1920s, the challenge of calculating the probability distributions of sums, differences, products, and quotients of independent random variables have drawn the attention of numerous statisticians and mathematicians who studied the algebraic properties and relationships of random variables. Statistical distributions are highly helpful in data science and machine learning, as they provide a range of possible values for the variables, aiding in the development of a deeper understanding of the underlying problem. In this paper, we have presented a new probability distribution based on the $\hat{I}$-function. Also, we have discussed the applications of the $\hat{I}$ function, particularly in deriving the distributions of product and the quotient involving two independent $\hat{I}$ function variates. Additionally, it has been shown that both the product and quotient of two independent $\hat{I}$-function variates also follow the $\hat{I}$-function distribution. Furthermore, the new distribution, known as the $\hat{I}$-function distribution, includes several well-known classical distributions such as the gamma, beta, exponential, normal H-function, and G-function distributions, among others, as special cases. Therefore, the $\hat{I}$-function distribution can be considered a characterization or generalization of the above-mentioned distributions.

arxiv.org

Existence and Uniqueness of Permutation-Invariant Optimizers for Parisi Formula arxiv.org/abs/2407.13846

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