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From the 1 of 5 linked papers with an AI index.

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5 papers

quant-ph2026

Classical Tensor Network and Quantum Fourier Transform Approaches for Large-Scale Carr-Madan Option Pricing

Sascha Hauck, Ivica Turkalj

The paper reformulates the Carr‑Madan Fourier option‑pricing method using tensor‑network techniques, specifically a Superfast Fourier Transform (a compressed Tensor‑Train version o…

cond-mat.mtrl-sci2026

Performance Benchmarking of Tensor Trains for accelerated Quantum-Inspired Homogenization on TPU, GPU and CPU architectures

Sascha H. Hauck, Matthias Kabel, Nicolas R. Gauger

Recent advances in high-resolution CT-imaging technology are creating a new class of ultra-high resolved microstructural datasets that challenge the limits of traditional homogeniz…

q-bio.MN2026

Epigenetic feedback reshapes dynamical landscapes in gene regulatory networks

Sascha H. Hauck, Sandip Saha, Narsis A. Kiani +1

Understanding how gene regulatory networks (GRNs) give rise to stable and dynamic cellular states remains a central challenge in theoretical biology, particularly when slow epigene…

quant-ph2026

Enhanced shortcuts to adiabaticity for coherent atom transport in a family of two-dimensional dynamical optical lattices

Sascha H. Hauck, Vladimir M. Stojanovic

In view of the compelling need for coherent atom transport as a prerequisite for a variety of emerging quantum technologies, we investigate such transport on the example of an adju…

cond-mat.mtrl-sci2025

SFFT-Based Homogenization: Using Tensor Trains to Enhance FFT-Based Homogenization

Sascha H. Hauck, Matthias Kabel, Mazen Ali +1

Homogenization is a fundamental technique for estimating the macroscopic properties of materials with microscale heterogeneity. Among Homogenization methods, the FFT-based Homogeni…