Tootfinder

Towards universal property prediction in Cartesian space: TACE is all you need
Zemin Xu, Wenbo Xie, Daiqian Xie, P. Hu
https://arxiv.org/abs/2509.14961 https://

Towards universal property prediction in Cartesian space: TACE is all you need
Machine learning has revolutionized atomistic simulations and materials science, yet current approaches often depend on spherical-harmonic representations. Here we introduce the Tensor Atomic Cluster Expansion and Tensor Moment Potential, the first unified framework formulated entirely in Cartesian space for the systematic prediction of arbitrary structure-determined tensorial properties. TACE achieves this by decomposing atomic environments into a complete hierarchy of (irreducible) Cartesian …

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Bara för att det finns en studie så innebär inte det att resultatet är sant | Podcast https://tyngre.se/podcast/tyngre-traningssnack/bara-for-att-det-finns-en-studie-sa-innebar-inte-det-att-resultatet-ar-sant

Bara för att det finns en studie så innebär inte det att resultatet är sant | Podcast
Bara för att det finns en studie så innebär inte det att resultatet är sant

State-to-Hamiltonian conversion with a few copies
Kaito Wada, Jumpei Kato, Hiroyuki Harada, Naoki Yamamoto
https://arxiv.org/abs/2509.14791 https://arxiv.o…

State-to-Hamiltonian conversion with a few copies
Density matrix exponentiation (DME) is a general procedure that converts an unknown quantum state into the Hamiltonian evolution. This enables state-dependent operations and can reveal nontrivial properties of the state, among other applications, without full tomography. However, it has been proven that for any physical process, the DME requires $Θ(1/\varepsilon)$ state copies in error $\varepsilon$. In this work, we go beyond the lower bound and propose a procedure called the virtual DME that…

Tensor Products with Verma Module and Restriction to Parabolic Subalgebra
Antoine Merceron
https://arxiv.org/abs/2509.14220 https://arxiv.org/pdf/2509.1422…

Tensor Products with Verma Module and Restriction to Parabolic Subalgebra
Using the tensor identity, we obtain decomposition results for the tensor product of a generalized Verma module with a module $M$ in the category $\mathcal{O}^{\mathfrak{p}}$, based on the decomposition of the restriction of $M$ to the parabolic subalgebra $\mathfrak{p}$. We show that this restriction admits an essentially unique decomposition into indecomposable $\mathfrak{p}$-modules and identify two particular types of direct summands: finite-dimensional quotients and tilting submodules. Fin…

Overcoming Quantum Resistivity Scaling in Nanoscale Interconnects Using Delafossite PdCoO2
Seoung-Hun Kang, Youngjun Lee, Sangmoon Yoon, JongMok Ok, Mina Yoon, Ho Nyung Lee, Young-Kyun Kwon
https://arxiv.org/abs/2508.13573

Overcoming Quantum Resistivity Scaling in Nanoscale Interconnects Using Delafossite PdCoO2
Continued scaling into the sub 7 nm regime exacerbates quantum limited resistivity in Cu interconnects. We evaluated layered PdCoO2 and explicitly benchmarked it against Cu to identify mechanisms that maintain conductivity under confinement. Using a momentum resolved relaxation time formalism derived from the conductivity tensor, we link k and energy resolved velocities, life times, and mean free paths (MFPs) to thickness dependent resistivity for films and wires. PdCoO2 exhibits quasi 2D trans…

En riktigt dålig studie har fått en hel del rubriker de senaste dagarna där det påstås att sötningsmedel ska snabba på hjärnans åldrande.
Sötningsmedel snabbar inte på hjärnans åldrande | Podcast https://tyngre.se/podcast/halsoveckan-by-tyngre/…

Sötningsmedel snabbar inte på hjärnans åldrande | Podcast
Erik och Jacob granskar den uppmärksammade studien som påstår att sötningsmedel snabbar på hjärnans åldrande – och förklarar varför resultaten haltar rejält.

Quantum Noise Tomography with Physics-Informed Neural Networks
Antonin Sulc
https://arxiv.org/abs/2509.11911 https://arxiv.org/pdf/2509.11911

Quantum Noise Tomography with Physics-Informed Neural Networks
Characterizing the environmental interactions of quantum systems is a critical bottleneck in the development of robust quantum technologies. Traditional tomographic methods are often data-intensive and struggle with scalability. In this work, we introduce a novel framework for performing Lindblad tomography using Physics-Informed Neural Networks (PINNs). By embedding the Lindblad master equation directly into the neural network's loss function, our approach simultaneously learns the quantum sta…

Classical State Detection Using Quantum State Tomography
Kim Fook Lee, Prem Kumar
https://arxiv.org/abs/2509.11509 https://arxiv.org/pdf/2509.11509

Classical State Detection Using Quantum State Tomography
We present a model to detect a classical state mixed with an idler photon from a polarization-entangled pair. A weak coherent light with a well-defined polarization, matched in wavelength to the idler photon, is injected into the idler channel. Quantum state tomography is then performed on both the classically mixed idler photon and its entangled signal partner. The reconstructed state is modeled as a combination of an $X-$quantum state and a classical-quantum (CQ) state. In this framework, the…