Tootfinder

Closing objectivity loophole in Bell tests on a public quantum computer
Adam Bednorz, Josep Batle, Tomasz Bia{\l}ecki, Jaros{\l}aw K. Korbicz
https://arxiv.org/abs/2506.08940

Closing objectivity loophole in Bell tests on a public quantum computer
We have constructed and run a Bell test of local realism focusing on the objectivity criterion. The objectivity means that the outcomes are confirmed macroscopically by a few observers at each of party. The IBM Quantum devices turn out to be sufficiently accurate to pass such an extended Bell-type test, although at the price of communication loopholes and residual but statistically significant signaling. The test serves also as the benchmark of entanglement spread across larger sets of qubits.

Jacobi-accelerated FFT-based solver for smooth high-contrast data
Martin Ladeck\'y, Ivana Pultarov\'a, Fran\c{c}ois Bignonnet, Indre J\"odicke, Jan Zeman, Lars Pastewka
https://arxiv.org/abs/2508.02613

Jacobi-accelerated FFT-based solver for smooth high-contrast data
The computational efficiency and rapid convergence of fast Fourier transform (FFT)-based solvers render them a powerful numerical tool for periodic cell problems in multiscale modeling. On regular grids, they tend to outperform traditional numerical methods. However, we show that their convergence slows down significantly when applied to microstructures with smooth, highly-contrasted coefficients. To address this loss of performance, we introduce a Green-Jacobi preconditioner, an enhanced succe…

Asymptotic Behavior of a Buoyant Jet Regime inside a Carbon-dioxide Ejector
Sreetam Bhaduri, Ivan C. Christov, Eckhard A. Groll, Davide Ziviani
https://arxiv.org/abs/2507.01992

Asymptotic Behavior of a Buoyant Jet Regime inside a Carbon-dioxide Ejector
Ejectors are used in various engineering systems, including steam and vapor compression cycles. Optimizing the performance of ejectors requires understanding and analysis of multiphase and turbulent flow structures associated with their internal flow fields. This approach yields higher fidelity but at a high computational cost. Lower-fidelity one-dimensional (1D) models offer lower computational costs; however, 1D models are often empirical and provide limited understanding of the internal flow…

Quantum chemistry with provable convergence via randomized sample-based quantum diagonalization
Samuele Piccinelli, Alberto Baiardi, Max Rossmannek, Almudena Carrera Vazquez, Francesco Tacchino, Stefano Mensa, Edoardo Altamura, Ali Alavi, Mario Motta, Javier Robledo-Moreno, William Kirby, Kunal Sharma, Antonio Mezzacapo, Ivano Tavernelli
https://

Quantum chemistry with provable convergence via randomized sample-based quantum diagonalization
Sample-based quantum diagonalization (SQD) is a recently proposed algorithm to approximate the ground-state wave function of many-body quantum systems on near-term and early-fault-tolerant quantum devices. In SQD, the quantum computer acts as a sampling engine that generates the subspace in which the Hamiltonian is classically diagonalized. A recently proposed SQD variant, Sample-based Krylov Quantum Diagonalization (SKQD), uses quantum Krylov states as circuits from which samples are collected…

Breaking a 5-Bit Elliptic Curve Key using a 133-Qubit Quantum Computer
Steve Tippeconnic
https://arxiv.org/abs/2507.10592 https://arx…

Breaking a 5-Bit Elliptic Curve Key using a 133-Qubit Quantum Computer
This experiment breaks a 5-bit elliptic curve cryptographic key using a Shor-style quantum attack. Executed on IBM's 133-qubit ibm_torino with Qiskit Runtime 2.0, a 15-qubit circuit, comprised of 10 logical qubits and 5 ancilla, interferes over an order-32 elliptic curve subgroup to extract the secret scalar k from the public key relation Q = kP, without ever encoding k directly into the oracle. From 16,384 shots, the quantum interference reveals a diagonal ridge in the 32 x 32 QFT outcome spac…

Predicting Post-Surgical Complications with Quantum Neural Networks: A Clinical Study on Anastomotic Leak
Vojt\v{e}ch Nov\'ak, Ivan Zelinka, Lenka P\v{r}ibylov\'a, Lubom\'ir Mart\'inek, Vladim\'ir Ben\v{c}urik
https://arxiv.org/abs/2506.01708

Predicting Post-Surgical Complications with Quantum Neural Networks: A Clinical Study on Anastomotic Leak
Quantum computing represents a transformative leap in computational power, with the potential to revolutionize various fields, including healthcare. In this study, we explore the application of quantum machine learning in medical diagnostics, specifically focusing on the prediction of anastomotic leak, a severe post-surgical complication. By comparing quantum neural networks implemented with different ansatz functions to classical classification approaches-including logistic regression, support…

Taming Diffusion Transformer for Real-Time Mobile Video Generation
Yushu Wu, Yanyu Li, Anil Kag, Ivan Skorokhodov, Willi Menapace, Ke Ma, Arpit Sahni, Ju Hu, Aliaksandr Siarohin, Dhritiman Sagar, Yanzhi Wang, Sergey Tulyakov
https://arxiv.org/abs/2507.13343

Taming Diffusion Transformer for Real-Time Mobile Video Generation
Diffusion Transformers (DiT) have shown strong performance in video generation tasks, but their high computational cost makes them impractical for resource-constrained devices like smartphones, and real-time generation is even more challenging. In this work, we propose a series of novel optimizations to significantly accelerate video generation and enable real-time performance on mobile platforms. First, we employ a highly compressed variational autoencoder (VAE) to reduce the dimensionality of…

Three-dimensional SPH modeling of brittle fracture under hydrodynamic loading
Vishabjeet Singh, Chong Peng, Md Rushdie Ibne Islam
https://arxiv.org/abs/2507.10553

Three-dimensional SPH modeling of brittle fracture under hydrodynamic loading
A three-dimensional SPH computational framework is presented for modeling fluid-structure interactions with structural deformation and failure. We combine weakly compressible SPH with a pseudo-spring-based SPH solver to capture the fluid flow and deformable structures. A unified modeling approach captures the solid boundaries and fluid-structure interfaces without penalty-based contact force. The $δ$-SPH technique improves the pressure calculations in the fluid phase, while structural damage i…

Resource-Efficient Simulations of Particle Scattering on a Digital Quantum Computer
Yahui Chai, Joe Gibbs, Vincent R. Pascuzzi, Zo\"e Holmes, Stefan K\"uhn, Francesco Tacchino, Ivano Tavernelli
https://arxiv.org/abs/2507.17832

Resource-Efficient Simulations of Particle Scattering on a Digital Quantum Computer
We develop and demonstrate methods for simulating the scattering of particle wave packets in the interacting Thirring model on digital quantum computers, with hardware implementations on up to 80 qubits. We identify low-entanglement time slices of the scattering dynamics and exploit their efficient representation by tensor networks. Circuit compression based on matrix product state techniques yields on average a reduction by a factor of 3.2 in circuit depth compared to conventional approaches, …

Taylors hypothesis and its impact on flux measurements in a forest clearcut
Subharthi Chowdhuri, Ivan Mammarella, Olli Peltola
https://arxiv.org/abs/2507.12069

Taylors hypothesis and its impact on flux measurements in a forest clearcut
Taylors hypothesis is the backbone to convert observations done over time to spatial information of the flow while carrying out turbulence measurements on a micrometeorological tower. To address its validity over a highly heterogeneous forest clearcut surface, we utilize an extensive Distributed Temperature Sensing (DTS) and Eddy Covariance (EC) datasets. The DTS measured space-time correlation curves of temperature fluctuations are used to compute the bulk convective speeds of temperature stru…