Tzu-Wei Lin | Search arXiv

arXiv2026

Tailored coupled cluster method with sample-based quantum diagonalization: Application to titanium-based metallocene catalytic reactions for 1-hexene production

Sample-based quantum diagonalization (SQD) is a hybrid quantum-classical method for electronic-structure calculations. We applied SQD to a titanium-based metallocene catalyst system for 1-hexene production, where free-energy differences must be predicted within 1 kcal/mol to accurately determine product selectivity. However, currently accessible active spaces on quantum computers are limited in size, leaving significant dynamical correlation effects outside the active space. To address this challenge, we combined SQD with Tailored Coupled Cluster (TCC) theory. In this SQD-TCC framework, static correlation is treated by SQD, while dynamical correlation is incorporated through CCSD and its perturbative triples extension, TCC(T). We calculated the relative energies of two transition states governing 1-hexene selectivity. While SQD alone did not yield converged relative energies within practically accessible active spaces, SQD-TCC and SQD-TCC(T) provided reasonably converged results. Importantly, the relative energy obtained from SQD-TCC(T) differed by more than 1 kcal/mol from the corresponding CCSD(T) result, demonstrating the significance of static correlation in this system and its impact on predicted selectivity. Although TCC(T) calculations based on CASCI are feasible for small active spaces, the present system requires substantially larger active spaces that are beyond the reach of CASCI. By using SQD, we were able to access active spaces impractical for classical CASCI calculations. These results demonstrate that both static and dynamical electron correlation are essential for a reliable description of this chemistry and highlight the importance of incorporating dynamical correlation into quantum-computing approaches targeting chemically accurate simulations.

physics.chem-ph↗

arXiv2026

Matrix Representations of Finite Fields

Finite fields are important algebraic structures that have a wide range of applications in fields such as coding theory and cryptography. But the standard construction of finite field extensions through polynomial quotients is computationally opaque, especially when we want to identify a degree-$2$ extension of $F_8$ and a degree-$3$ extension of $F_4$. In this short note, we present a coherent family of representations by matrices $ρ_q^n\colon F_{q^n} \to F_q^{n\times n}$ for all prime powers $q$ and all degrees $n \ge 1$. These maps are chosen so that concatenating $ρ_{q^n}^m$ and $ρ_q^n$ recovers $ρ_q^{nm}$ up to row and column permutations. As a consequence, the images of $ρ_2^6$ can be partitioned into four $3 \times 3$ blocks or nine $2 \times 2$ blocks to visualize the subfield chains $F_{64} / F_8 / F_2$ and $F_{64} / F_4 / F_2$ at the same time. A variant $\varrho$ is also discussed, wherein the Frobenius automorphism is represented by a cyclic shift of rows and columns. From an educational point of view, these rhos give explicit and self-contained mental models of finite fields; subfields, trace, norm, minimal polynomial, and Frobenius all become visible through matrix algebra accessible to most students. From a theoretical point of view, the construction exhibits structural implications of Conway polynomials and the normal basis theorem.

math.HO↗