Tootfinder

Quantum Transport Protected by Acceleration From Nonadiabaticity and Dissipation
Arnab Chakrabarti, Biswarup Ash, Igor Mazets, Xi Chen, Gershon Kurizki
https://arxiv.org/abs/2506.21462

Quantum Transport Protected by Acceleration From Nonadiabaticity and Dissipation
We put forth a hitherto unexplored control strategy that enables high-fidelity fast transport of an unstable quantum wavepacket even in the presence of bath-induced dissipation. The wavepacket, which is confined within any shallow (anharmonic) potential trap is steered in acceleration, so as to maximize the transfer fidelity. This strategy can generally optimize any non-Markovian bath-dressed continuous-variable system dynamics. It can simultaneously cope with wavepacket leakage via non-adiabat…

Sennheiser generated €492.3 million in sales in 2024, despite “volatile market conditions”
#MusicTech #MusicBiz

Sennheiser generated €492.3 million in sales in 2024, despite “volatile market conditions”
The Sennheiser Group generated sales of €492.3 million across the 2024 financial year, despite facing “turbulent times” across the economic landscape. 

Surrogate normal-forms for the numerical bifurcation and stability analysis of navier-stokes flows via machine learning
Alessandro Della Pia, Dimitrios G. Patsatzis, Gianluigi Rozza, Lucia Russo, Constantinos Siettos
https://arxiv.org/abs/2506.21275

Surrogate normal-forms for the numerical bifurcation and stability analysis of navier-stokes flows via machine learning
Inspired by the Equation-Free multiscale modeling approach, we demonstrate how the embed-learn-lift framework enables the construction of surrogate normal-forms, namely minimal-dimensional reduced-order models (ROMs), from high-fidelity Navier-Stokes simulations. These surrogate models are then used for efficient and accurate bifurcation and stability analysis. The framework proceeds in four steps. First, manifold learning reveals the intrinsic latent dimension of the high-dimensional spatio-te…

Autonomous Cyber Resilience via a Co-Evolutionary Arms Race within a Fortified Digital Twin Sandbox
Malikussaid, Sutiyo
https://arxiv.org/abs/2506.20102 h…

Autonomous Cyber Resilience via a Co-Evolutionary Arms Race within a Fortified Digital Twin Sandbox
The convergence of IT and OT has created hyper-connected ICS, exposing critical infrastructure to a new class of adaptive, intelligent adversaries that render static defenses obsolete. Existing security paradigms often fail to address a foundational "Trinity of Trust," comprising the fidelity of the system model, the integrity of synchronizing data, and the resilience of the analytical engine against sophisticated evasion. This paper introduces the ARC framework, a method for achieving analytic…

Decoherence and fidelity enhancement during shuttling of entangled spin qubits
Yu-Ning Zhang, Aleksandr S. Mokeev, Viatcheslav V. Dobrovitski
https://arxiv.org/abs/2506.19671

Decoherence and fidelity enhancement during shuttling of entangled spin qubits
Shuttling of spin qubits between different locations is a key element in many prospective semiconductor systems for quantum information processing, but the shuttled qubits should be protected from decoherence created by time- and space-dependent noises. Since the paths of different spin qubits are interrelated, the noises acting on the shuttled spins exhibit complex and unusual correlations. We appraise the role of these correlations using the concept of trajectories on random sheets, and demon…

ThinkSound: Chain-of-Thought Reasoning in Multimodal Large Language Models for Audio Generation and Editing
Huadai Liu, Jialei Wang, Kaicheng Luo, Wen Wang, Qian Chen, Zhou Zhao, Wei Xue
https://arxiv.org/abs/2506.21448

ThinkSound: Chain-of-Thought Reasoning in Multimodal Large Language Models for Audio Generation and Editing
While end-to-end video-to-audio generation has greatly improved, producing high-fidelity audio that authentically captures the nuances of visual content remains challenging. Like professionals in the creative industries, such generation requires sophisticated reasoning about items such as visual dynamics, acoustic environments, and temporal relationships. We present \textbf{ThinkSound}, a novel framework that leverages Chain-of-Thought (CoT) reasoning to enable stepwise, interactive audio gener…

ECLEIRS: Exact conservation law embedded identification of reduced states for parameterized partial differential equations from sparse and noisy data
Aviral Prakash, Ben S. Southworth, Marc L. Klasky
https://arxiv.org/abs/2506.18855

ECLEIRS: Exact conservation law embedded identification of reduced states for parameterized partial differential equations from sparse and noisy data
Multi-query applications such as parameter estimation, uncertainty quantification and design optimization for parameterized PDE systems are expensive due to the high computational cost of high-fidelity simulations. Reduced/Latent state dynamics approaches for parameterized PDEs offer a viable method where high-fidelity data and machine learning techniques are used to reduce the system's dimensionality and estimate the dynamics of low-dimensional reduced states. These reduced state dynamics appr…

Experimental demonstration of high-fidelity logical magic states from code switching
Lucas Daguerre, Robin Blume-Kohout, Natalie C. Brown, David Hayes, Isaac H. Kim
https://arxiv.org/abs/2506.14169

Experimental demonstration of high-fidelity logical magic states from code switching
Preparation of high-fidelity logical magic states has remained as a necessary but daunting step towards building a large-scale fault-tolerant quantum computer. One approach is to fault-tolerantly prepare a magic state in one code and then switch to another, a method known as code switching. We experimentally demonstrate this protocol on an ion-trap quantum processor, yielding a logical magic state encoded in an error-correcting code with state-of-the-art logical fidelity. Our experiment is base…

A Neural-Operator Surrogate for Platelet Deformation Across Capillary Numbers
Marco Laudato
https://arxiv.org/abs/2506.20341 https://…

A Neural-Operator Surrogate for Platelet Deformation Across Capillary Numbers
Reliable multiscale models of thrombosis require platelet-scale fidelity at organ-scale cost, a gap that scientific machine learning has the potential to narrow. We train a DeepONet surrogate on platelet dynamics generated with LAMMPS for platelets spanning ten elastic moduli and capillary numbers (0.07 - 0.77). The network takes in input the wall shear stress, bond stiffness, time, and initial particle coordinates and returns the full three-dimensional deformation of the membrane. Mean-squared…

Fidelity of entanglement and quantum entropies: unveiling their relationship in quantum states and channels
Komal Kumar, Bivas Mallick, Tapaswini Patro, Nirman Ganguly
https://arxiv.org/abs/2506.11506

Fidelity of entanglement and quantum entropies: unveiling their relationship in quantum states and channels
Entanglement serves as a fundamental resource for various quantum information processing tasks. Fidelity of entanglement (which measures the proximity to a maximally entangled state) and various quantum entropies are key indicators for certifying entanglement in a quantum state. Quantum states with high fidelity are particularly useful for numerous information-theoretic applications. Similarly, states possessing negative conditional entropy provide significant advantages in several quantum info…