Tootfinder

SpiceMixer - Netlist-Level Circuit Evolution
Stefan Uhlich, Andrea Bonetti, Arun Venkitaraman, Chia-Yu Hsieh, Mustafa Emre G\"ursoy, Ryoga Matsuo, Lorenzo Servadei
https://arxiv.org/abs/2506.01497

SpiceMixer - Netlist-Level Circuit Evolution
This paper introduces SpiceMixer, a genetic algorithm developed to synthesize novel analog circuits by evolving SPICE netlists. Unlike conventional methods, SpiceMixer operates directly on netlist lines, enabling compatibility with any component or subcircuit type and supporting general-purpose genetic operations. By using a normalized netlist format, the algorithm enhances the effectiveness of its genetic operators: crossover, mutation, and pruning. We show that SpiceMixer achieves superior pe…

🇺🇦 #NowPlaying on KEXP's #Early
Sufjan Stevens:
🎵 Chicago
#SufjanStevens
https://stephenshero.bandcamp.com/track/sufjan-stevens-chicago-remix
https://open.spotify.com/track/1yupbrI7ROhigIHpQBevPh

At the risk of repeating myself repeatedly: Peace Orchestra, Who Am I. #sound
https://www.youtube.com/watch?v=SG5BVxImD8o

Asteroseismology of the G8 subgiant beta Aquilae with SONG-Tenerife, SONG-Australia and TESS
Hans Kjeldsen, Timothy R. Bedding, Yaguang Li, Frank Grundahl, Mads Fredslund Andersen, Duncan J. Wright, Jack Soutter, Robert Wittenmyer, Claudia Reyes, Dennis Stello, Courtney Crawford, Yixiao Zhou, Mathieu Clerte, Pere L. Palle, Sergio Simon-Diaz, Joergen Christensen-Dalsgaard, Rasmus Handberg, Hasse Hansen, Paul Heeren, Jens Jessen-Hansen, Mikkel Lund, Mia S. Lundkvist, Karsten Brogaard, Re…

Asteroseismology of the G8 subgiant beta Aquilae with SONG-Tenerife, SONG-Australia and TESS
We present radial velocities of the G8 subgiant star beta Aql obtained in 2022 and 2023 using SONG-Tenerife and SONG-Australia. We also analysed a sector of TESS photometry that overlapped with the 2022 SONG data. We processed the time series to assign weights and to remove bad data points. The power spectrum clearly shows solar-like oscillations centred at 430 muHz. The TESS data show the oscillations at lower signal-to-noise because photometric measurements are much more affected by the granu…

Spegion: Implicit and Non-Lexical Regions with Sized Allocations
Jack Hughes, Michael Vollmer, Mark Batty
https://arxiv.org/abs/2506.02182 https://

Spegion: Implicit and Non-Lexical Regions with Sized Allocations
Region based memory management is a powerful tool designed with the goal of ensuring memory safety statically. The region calculus of Tofte and Talpin is a well known example of a region based system, which uses regions to manage memory in a stack-like fashion. However, the region calculus is lexically scoped and requires explicit annotation of memory regions, which can be cumbersome for the programmer. Other systems have addressed non-lexical regions, but these approaches typically require the…

🇺🇦 Auf radioeins läuft...
Sophia Kennedy:
🎵 Hot Match
#NowPlaying #SophiaKennedy
https://sophiakennedy.bandcamp.com/track/hot-match
https://open.spotify.com/track/1QBwezIfN3BP7CF1vN7wCk

Improved belief propagation is sufficient for real-time decoding of quantum memory
Tristan M\"uller, Thomas Alexander, Michael E. Beverland, Markus B\"uhler, Blake R. Johnson, Thilo Maurer, Drew Vandeth
https://arxiv.org/abs/2506.01779

Improved belief propagation is sufficient for real-time decoding of quantum memory
We introduce a new heuristic decoder, Relay-BP, targeting real-time quantum circuit decoding for large-scale quantum computers. Relay-BP achieves high accuracy across circuit-noise decoding problems: significantly outperforming BP+OSD+CS-10 for bivariate-bicycle codes and comparable to min-weight-matching for surface codes. As a lightweight message-passing decoder, Relay-BP is inherently parallel, enabling rapid low-footprint decoding with FPGA or ASIC real-time implementations, similar to stan…

Minimal Neuron Circuits -- Part I: Resonators
Amr Nabil, T. Nandha Kumar, Haider Abbas F. Almurib
https://arxiv.org/abs/2506.02341 https://

Minimal Neuron Circuits -- Part I: Resonators
Spiking Neural Networks have earned increased recognition in recent years owing to their biological plausibility and event-driven computation. Spiking neurons are the fundamental building components of Spiking Neural Networks. Those neurons act as computational units that determine the decision to fire an action potential. This work presents a methodology to implement biologically plausible yet scalable spiking neurons in hardware. We show that it is more efficient to design neurons that mimic …

The Promise of Spiking Neural Networks for Ubiquitous Computing: A Survey and New Perspectives
Hemanth Sabbella, Archit Mukherjee, Thivya Kandappu, Sounak Dey, Arpan Pal, Archan Misra, Dong Ma
https://arxiv.org/abs/2506.01737

The Promise of Spiking Neural Networks for Ubiquitous Computing: A Survey and New Perspectives
Spiking neural networks (SNNs) have emerged as a class of bio -inspired networks that leverage sparse, event- driven signaling to achieve low-power computation while inherently modeling temporal dynamics. Such characteristics align closely with the demands of ubiquitous computing systems, which often operate on resource- constrained devices while continuously monitoring and processing time - series sensor data. Despite their unique and promising features, SNNs have received limited attention an…

Spatio-Temporal Decoupled Learning for Spiking Neural Networks
Chenxiang Ma, Xinyi Chen, Kay Chen Tan, Jibin Wu
https://arxiv.org/abs/2506.01117 https://…

Spatio-Temporal Decoupled Learning for Spiking Neural Networks
Spiking neural networks (SNNs) have gained significant attention for their potential to enable energy-efficient artificial intelligence. However, effective and efficient training of SNNs remains an unresolved challenge. While backpropagation through time (BPTT) achieves high accuracy, it incurs substantial memory overhead. In contrast, biologically plausible local learning methods are more memory-efficient but struggle to match the accuracy of BPTT. To bridge this gap, we propose spatio-tempora…