Tootfinder

🇺🇦 #NowPlaying on KEXP's #AstralPlane
Pixies:
🎵 Monkey Gone to Heaven
#Pixies
https://situationsmke.bandcamp.com/track/pixies-monkey-gone-to-heaven
https://open.spotify.com/track/6BT7qiDY4A5tOyklohjQuW

Is a race or a lottery a good way to allocate subsidies, or are there better alternatives?
Yesterday, a new round of subsidies for electric heavy-duty vehicles opened in the Netherlands – and was immediately oversubscribed, just like the previous rounds.
https://www.rvo.nl/subsidies-financiering/

Nonperturbative Semiclassical Spin Dynamics for Ordered Quantum Magnets
Hao Zhang, Tianyue Huang, Allen O. Scheie, Mengze Zhu, Tao Xie, N. Murai, S. Ohira-Kawamura, Andrey Zheludev, Andreas M. L\"auchli, Cristian D. Batista
https://arxiv.org/abs/2508.21142

Nonperturbative Semiclassical Spin Dynamics for Ordered Quantum Magnets
In ordered quantum magnets where interactions between elementary excitations dominate over their kinetic energy, perturbative approaches often fail, making non-perturbative methods essential to capture spectral features such as bound states and the redistribution of weight within excitation continua. Although an increasing number of experiments report anomalous spin excitation continua in such systems, their microscopic interpretation remains an open challenge. Here, we investigate the spin dyn…

DC-VideoGen: Efficient Video Generation with Deep Compression Video Autoencoder
Junyu Chen, Wenkun He, Yuchao Gu, Yuyang Zhao, Jincheng Yu, Junsong Chen, Dongyun Zou, Yujun Lin, Zhekai Zhang, Muyang Li, Haocheng Xi, Ligeng Zhu, Enze Xie, Song Han, Han Cai
https://arxiv.org/abs/2509.25182

DC-VideoGen: Efficient Video Generation with Deep Compression Video Autoencoder
We introduce DC-VideoGen, a post-training acceleration framework for efficient video generation. DC-VideoGen can be applied to any pre-trained video diffusion model, improving efficiency by adapting it to a deep compression latent space with lightweight fine-tuning. The framework builds on two key innovations: (i) a Deep Compression Video Autoencoder with a novel chunk-causal temporal design that achieves 32x/64x spatial and 4x temporal compression while preserving reconstruction quality and ge…

Photonics-Aware Planning-Guided Automated Electrical Routing for Large-Scale Active Photonic Integrated Circuits
Hongjian Zhou, Haoyu Yang, Nicholas Gangi, Bowen Liu, Meng Zhang, Haoxing Ren, Xu Wang, Rena Huang, Jiaqi Gu
https://arxiv.org/abs/2509.23764

Photonics-Aware Planning-Guided Automated Electrical Routing for Large-Scale Active Photonic Integrated Circuits
The rising demand for AI training and inference, as well as scientific computing, combined with stringent latency and energy budgets, is driving the adoption of integrated photonics for computing, sensing, and communications. As active photonic integrated circuits (PICs) scale in device count and functional heterogeneity, physical implementation by manual scripting and ad-hoc edits is no longer tenable. This creates an immediate need for an electronic-photonic design automation (EPDA) stack in …

Excited-CAFQA: A classical simulation bootstrap for the variational estimation of molecular excited states
Bikrant Bhattacharyya, Gokul Ravi
https://arxiv.org/abs/2509.20588 htt…

Excited-CAFQA: A classical simulation bootstrap for the variational estimation of molecular excited states
Variational Quantum Algorithms (VQAs) are iterative algorithms suited to implementation on current-era quantum devices. VQAs employ classical optimization to minimize cost functions evaluated on quantum circuits. However, the extent to which VQAs manage noise is often insufficient for quantum chemistry applications. One method of improving VQAs is through accurate ansatz initialization. The CAFQA (Clifford Ansatz For Quantum Accuracy) protocol runs a discrete search through a classically simula…

Den Preis für "Kleines Budget" beim digAMus Award erhält der Podcast "Mummies & Magic - Altägypten in der Popkultur".
❓️Was hat es mit den Legenden um das alte Ägypten WIRKLICH auf sich?
❗️Hört es Euch selbst an!
Herzlichen Glückwunsch an die begeisterten, begeisternden und überraschten GewinnerInnen!
#digAMus

Democracy-in-Silico: Institutional Design as Alignment in AI-Governed Polities
Trisanth Srinivasan, Santosh Patapati
https://arxiv.org/abs/2508.19562 https://

Democracy-in-Silico: Institutional Design as Alignment in AI-Governed Polities
This paper introduces Democracy-in-Silico, an agent-based simulation where societies of advanced AI agents, imbued with complex psychological personas, govern themselves under different institutional frameworks. We explore what it means to be human in an age of AI by tasking Large Language Models (LLMs) to embody agents with traumatic memories, hidden agendas, and psychological triggers. These agents engage in deliberation, legislation, and elections under various stressors, such as budget cris…

States face massive new costs under Trump budget cuts
States are scrambling to prepare for an unprecedented shift of costs and responsibilities under Trump’s sweeping tax and spending plan,
which will force them to make difficult decisions about cuts to state programs to offset the new financial burdens.

Unlike the federal government, states must balance their budgets each year.
That means deep cuts and changes to Medicaid and the Supplemental Nutrition Assistance …

States face massive new costs under Trump budget cuts
Governors are already making budgetary decisions in anticipation of added costs and responsibilities they will have to take on.

SciReasoner: Laying the Scientific Reasoning Ground Across Disciplines
Yizhou Wang, Chen Tang, Han Deng, Jiabei Xiao, Jiaqi Liu, Jianyu Wu, Jun Yao, Pengze Li, Encheng Su, Lintao Wang, Guohang Zhuang, Yuchen Ren, Ben Fei, Ming Hu, Xin Chen, Dongzhan Zhou, Junjun He, Xiangyu Yue, Zhenfei Yin, Jiamin Wu, Qihao Zheng, Yuhao Zhou, Huihui Xu, Chenglong Ma, Yan Lu, Wenlong Zhang, Chunfeng Song, Philip Torr, Shixiang Tang, Xinzhu Ma, Wanli Ouyang, Lei Bai

SciReasoner: Laying the Scientific Reasoning Ground Across Disciplines
We present a scientific reasoning foundation model that aligns natural language with heterogeneous scientific representations. The model is pretrained on a 206B-token corpus spanning scientific text, pure sequences, and sequence-text pairs, then aligned via SFT on 40M instructions, annealed cold-start bootstrapping to elicit long-form chain-of-thought, and reinforcement learning with task-specific reward shaping, which instills deliberate scientific reasoning. It supports four capability famili…