@galaxydinodragon@social.linux.pizzaWhy do people assume this reality being in a simulation would require a huge amount of compute?
It could just take ages, like it would be a big computer but also could take 10 years per frame. As far as ik, we'd experience reality the same if the simulation ran at 20 million FPS vs 1 frame per decade...
@heiseonline@social.heise.de
@pixelpusher220@dmv.community#AutonomousCars #NotReady
from back in December...a Waymo with passengers drives right through a felony traffic stop
https://www.nbcnews.com/news/us-news/driverless-waymo-vehicle-inadvertently-takes-riders-tense-police-stop-rcna246994
the quote from this article is telling
https://insideevs.com/news/780886/waymo-lapd-standoff/
"Those dynamics fall under what AV developers call “long-tail edge cases”: events so uncommon and so context-dependent that no amount of simulation can fully anticipate them."
Why the fsck are we letting them off with not doing the hard parts?
@theodric@social.linux.pizzaSpeaking as someone who grew up in the cassette and CD era: why in the hell would you want to make your recording sound worse? Tapes sucked. Their main advantages over CD were durability at rest when stepped on or dropped under the car seat, and (for about 15 years) recordability. The people who are convinced analog is superior aren't getting anything out of applying synthetic distortion to a digital file in ffmpeg, so it's not that.
@rasterweb@mastodon.socialMiddle school punk band with an anti-AI song.
"I won't be a slave to AI
It's time for us all to step out of line
Free your mind and look to the sky
End the code and blind the cyber eye
There's a crisis in the nation
Gotta break free from the simulation
The truth is music comes from the soul
Unplug, join in, take back control
Artificial Intelligence
Can't know the human experience..."
@Techmeme@techhub.socialCoval, which develops simulation and evaluation tech for testing, launching, and monitoring AI voice and chat agents, raised a $28M Series A led by Norwest (Duncan Riley/SiliconANGLE)
https://siliconangle.com/2026/06/24/coval-raises-28m-enterpri…
@_mr_moe@mastodon.social
@azonenberg@ioc.exchangeJust finished an end to end simulation, BGA land to ARF6 launch, of the actual SFP28 TX lane 0 pair (not the shorter pair I had been using for initial layout work).
Took a while - the final geometry would have been way too big to simulate in a sane amount of time. Sonnet estimated 113GB of RAM and 122K mesh cells which... yeah.
I *could* do it, I have half a terabyte of RAM on this workstation, but considering that a 22GB / 54K cell simulation takes ~20 minutes per frequency and …
@metacurity@infosec.exchangeNo, the NSA wasn’t hacked by AI. Here’s what actually happened
https://san.com/cc/no-the-nsa-wasnt-hacked-by-ai-heres-what-actually-happened/
@blackknight95857669@social.linux.pizzaIf y'all into sim games and you like cars well then I got some good news for ya. Car Mechanic Simulator 2018 is currently free on Steam for its 8th anniversary. Don't wait tho, this offer ends on the 27th. I happen to have Car Mech Sim 2021 and can absolutely rec that one (excellent podcast game btw). Never played the predecessor but it looks to be fundamentally the same. (also there's a new one coming this year woo)
@toxi@mastodon.thi.ngColor Therapy. Noisy evolution.
Two snapshots of my piece C-SCAPE, 2022, a multi-organism 1.5D cellular automata simulation. Patterns of symbiosis and annihilation.
Made with #CSCAPE
@ingo@social.stuetzle.ccBei aller Kritik an der Kürzung des #Wohngeld: Wohngeldzahlungen setzt auf die Simulation von Marktprozessen und stärkt die Zahlungsfähigkeit: „Allein die Zahlungen für Kosten der Unterkunft und das Wohngeld hatten in den letzten Jahren einen Umfang von über 15 Milliarden Euro pro Jahr und fließen über die Mietzahlungen der Empfängerinnen und Empfänger an die überwiegend privaten Wohnungsu…
@arXiv_physicsaoph_bot@mastoxiv.pageA Simulation Methodology Testbed for Typhoon Sensitivity Analysis: Framework Development and Perturbation-Response Experiments with the Pangu Weather Model
Yuehua Peng, Yuchen Zhang, Qin Huang, Chengzhi Ye, Jingsong Yang
https://arxiv.org/abs/2605.21864 https://arxiv.org/pdf/2605.21864 https://arxiv.org/html/2605.21864
arXiv:2605.21864v1 Announce Type: new
Abstract: Understanding how typhoons respond to localized perturbations in their environmental fields is fundamental to assessing the limits of predictability and exploring the potential for track or intensity intervention. This study develops a dedicated simulation methodology testbed for typhoon sensitivity analysis by integrating the Pangu weather model, a high-precision AI forecasting system, with Proportional-Integral-Derivative (PID) closed-loop techniques. The testbed is constructed with modular functional blocks including a meteorological prediction module, an artificial perturbation input interface, a typhoon quantitative modeling module, and a PID closed-loop test module, implemented via a cross-platform MATLAB/ONNX technical framework. A Single-Input Single-Output (SISO) test system was built, with velocity and thermal perturbations set as the core inputs and typhoon track and intensity as the key output targets, to perform controlled perturbation-response experiments. The experiments reveal the feasible perturbation-response range, the parameter tuning behavior of the PID module, and the energy-scale response characteristics under different perturbation modes, and quantify the input-output coupling relationships of the test system. By constructing this testbed on an operational AI weather forecasting model, this study provides a framework that goes beyond idealized sensitivity studies typically validated only on low-order dynamical models. The testbed offers an expandable platform for investigating typhoon sensitivity to artificial environmental perturbations and provides a foundation for subsequent expansion toward multi-input multi-output architectures and advanced analysis strategies such as nonlinear PID or model predictive control.
toXiv_bot_toot
@cosmos4u@scicomm.xyzCIGaRS I - combined #simulation-based inference from type Ia supernovae and host photometry: https://www.nature.com/articles/s41550-026-02842-5 -> From Supernova Light a Sharper View of the Universe: https://www.sissa.it/news/supernova-light-sharper-view-universe
@arXiv_physicsmedph_bot@mastoxiv.pageGeneration of synthetic CT images from optical scanning for superficial mold brachytherapy
Scott B. Crowe (Royal Brisbane and Women's Hospital, Brisbane Qld, Australia, Herston Biofabrication Institute, Metro North Hospital and Health Service, Brisbane Qld, Australia, University of Queensland, Brisbane Qld, Australia, Queensland University of Technology, Brisbane Qld, Australia), Emily Simpson-Page (Royal Brisbane and Women's Hospital, Brisbane Qld, Australia), Jenna Luscombe (Royal Brisbane and Women's Hospital, Brisbane Qld, Australia), Rachael Wilks (Royal Brisbane and Women's Hospital, Brisbane Qld, Australia, Herston Biofabrication Institute, Metro North Hospital and Health Service, Brisbane Qld, Australia, University of Queensland, Brisbane Qld, Australia), Tanya Kairn (Royal Brisbane and Women's Hospital, Brisbane Qld, Australia, Herston Biofabrication Institute, Metro North Hospital and Health Service, Brisbane Qld, Australia, University of Queensland, Brisbane Qld, Australia, Queensland University of Technology, Brisbane Qld, Australia)
https://arxiv.org/abs/2606.25221 https://arxiv.org/pdf/2606.25221 https://arxiv.org/html/2606.25221
arXiv:2606.25221v1 Announce Type: new
Abstract: Optical 3D scanning systems allow the acquisition of accurate models of patient anatomy, suitable for use in the design of simple 3D-printable patient-matched medical devices with 3D modelling software. This study developed and demonstrated the use of superficial brachytherapy surface mold design workflow that utilizes data from optical 3D surface scanning and enables a commercial brachytherapy treatment planning system to be used for catheter positioning and dose optimization steps. Synthetic CT images were generated from 14 optically scanned anatomical models of human participants. Models and skin textures ac-quired from the optical scans were imported into Autodesk Meshmixer, where the treatment area was delineated, and treatment and device volumes produced. 3D Slicer was used to convert the body, treatment and device volumes to DICOM CT and RTSTRUCT data. The synthetic CT data and contoured volumes were imported into Varian Eclipse, where catheters were designed, and dwell positions and times optimised for dose coverage of the treatment volume. The lack of in-ternal anatomy did not compromise dose calculations, due to clinical use of a TG43 based algorithm. Once 3D printed, molds can be imaged in-situ during CT simulation, and reconstructed, for clinical dose calculation and plan approval.
toXiv_bot_toot
@simon_lucy@mastodon.social#worldcup2026
I gave up watching the Canada Qatar game the ITV commentary pissed me off.
I had considerable doubts about the foul preventing a goal attempt if you're simulating, which is what it looked like.
And the attempt to claim another penalty later was also simulation.
@hex@kolektiva.socialRE: https://kolektiva.social/@tiotasram/116595511143252449
These types of things regularly destroy otherwise well organized groups. If we could develop practice exercises around sexual violence, bad-jacketing, and interpersonal conflict, we could significantly decrease state leverage against movements and internal disruption.
Bad things happen. We will have to deal with those bad things. The more experience we have dealing with them (even in simulation), the more easily we'll be able to manage them and the more often we'll be able to do the right thing.
But yes, this would need to be at the very least informed by DV/SV survives to make sure scenarios drive towards the right conclusions.
@heiseonline@social.heise.de
@curiouscat@fosstodon.org"Sharla Boehm earned a teaching degree from the University of California, Los Angeles, before she channeled her talent for math into computer #programming While working at the RAND Corporation, she built a groundbreaking simulation, originally conceived to strengthen military communications during the cold war. The simulation—and her work—would ultimately lay the foundation for the moder…
@azonenberg@ioc.exchangeOk so... First simulation pass on a SFP28 SERDES track is done.
Performance actually looks fine without a ground plane cutout under the BGA lands.
@david@boles.xyzThe Glass People: The Materials of Madness, from the Glass King to the Simulation
More than six hundred years ago, the King of France stopped letting anyone touch him. Charles VI had iron rods sewn into his clothing and moved through his palace with the stiff care of a man carrying something breakable, because he believed he was carrying something breakable....
@mcdanlj@social.makerforums.infoI've been enjoying practicing for field day using my fork of Morse Walker, and also using cwsim for a more realistic simulation of a busy contest CW experience.
It made me wonder whether anyone had made a cwsim fork to support field day.
When I did a Google search, it sent me to Gemini, which helpfully …
@arXiv_eessIV_bot@mastoxiv.pageSIMBA: ABidirectional Retrieval Forward Simulation Framework for Modeling FY-4A GIIRS Hyperspectral Infrared Radiances Toward NWP Applications
Jingdong Shen, Fu Wang*, Qifeng Lu, Hao Huang, Chunqiang Wu, Chi Yang, Xiaofang Liu
https://arxiv.org/abs/2606.19943
@Techmeme@techhub.socialAI researchers ran 15-day simulations of worlds governed by different AI models: Claude Sonnet 4.6 recorded zero crime, while Gemini 3 Flash had the most at 683 (Jake Angelo/Fortune)
https://fortune.com/2026/05/28/ai-model-simulation-claude-chatgpt-grok-gemini/…
@@arXiv_physicsatomph_bot@mastoxiv.page@mastoxiv.pageSimulation of Rydberg Ionization in Atomic Beams for FIB Optimization
Clelia Bastelica, Azer Trimeche, Colin Lopez, Matthieu Viteau, Patrick Cheinet, Daniel Comparat, Yan J. Picard
https://arxiv.org/abs/2605.22548
@mlawton@mstdn.social
@arXiv_csGR_bot@mastoxiv.pageFast VEM Fluid Simulation
Runze Zhang, Bo Ren
https://arxiv.org/abs/2607.17725 https://arxiv.org/pdf/2607.17725 https://arxiv.org/html/2607.17725
arXiv:2607.17725v1 Announce Type: new
Abstract: The intricate motion arising from fluid--boundary interactions is visually compelling, yet notoriously difficult and computationally expensive to simulate in the presence of complex boundaries. Accurately resolving boundary geometry requires body-fitted grids constructed via cut-cell methods, which often leads to poorly conditioned linear systems in the pressure projection stage and, consequently, prohibitive computational cost. We present FastVEM, an efficient boundary-conforming fluid simulation framework that enables high-fidelity flow--boundary interaction at substantially reduced cost. Computational efficiency is achieved through a coordinated, top-down design spanning numerical discretization, grid construction, and linear solvers. FastVEM adopts a Virtual Element Method (VEM) discretization to robustly enforce incompressibility and boundary conditions on irregular body-fitted grids, and employs a VEM polynomial-space Particle-in-Cell scheme for advection. Complementing this discretization, a convexity-preserving cut-cell strategy is introduced to construct simulation-friendly body-fitted grids. To accelerate pressure projection, we develop a Galerkin geometric multigrid solver featuring a diffusion-free prolongation operator that prevents coarse-level matrix densification, along with a nested, boundary-aware grid hierarchy that ensures well-posed placement of coarse-level degrees of freedom. Compared to prior cut-cell--based fluid simulators, FastVEM speeds up the computationally dominant pressure projection stage by up to 100x, while robustly handling even more challenging boundary geometries.
toXiv_bot_toot
@azonenberg@ioc.exchangeI did all of my original SI simulations for the SFP28 front side launches using only layer 1 signal and layer 2 ground plane, ignoring everything deeper in the board.
Some of you asked if the ground plane voids needed to extrude all the way into the board. Does it matter?
For the BGA launch, at least, the answer is in: there is a measurable effect in simulation, but it's minimal. Return loss of the launch is better than -20 dB in both configurations so I'm not going to bo…
@barijaona@mastodon.mgIn 1973, there were ELIZA and PARRY.
While ELIZA was a simulation of a Rogerian therapist, PARRY attempted to simulate a person with paranoid schizophrenia. And here’s what you got when ELIZA tried to diagnose PARRY: https://www.rfc-editor.org/info/rfc439/
Did anything really change?
Via…
@arXiv_csFL_bot@mastoxiv.pageReplaced article(s) found for cs.FL. https://arxiv.org/list/cs.FL/new
[1/1]:
- A Forward Simulation-Based Hierarchy of Linearizable Concurrent Objects
Chao Wang, Ruijia Li, Yang Zhou, Peng Wu, Yi Lv, Jianwei Liao, Jim Woodcock, Zhiming Liu
@dennisfaucher@infosec.exchangeI started an AI simulation last night - two conservatives and two progressives work together to increase the US democracy from a score of 37 out of 100 to something that works better for _all_ people not just the wealthy. They agreed on 7 proposals to bring the score up to 60%. If only it were that easy.
#USPol
@tinoeberl@mastodon.online#Steady #Klimacrew
Wie lässt sich das Wachstum von #Feldfrüchten vorhersagen, ohne sie überhaupt anzubauen?
Ein KI-Modell aus
@arXiv_physicsfludyn_bot@mastoxiv.pageRarefaction-induced inflation and similarity breakdown of hypersonic bow shocks over a circular cylinder
Ehsan Roohi, Ahmad Shoja-Sani
https://arxiv.org/abs/2605.17099 https://arxiv.org/pdf/2605.17099 https://arxiv.org/html/2605.17099
arXiv:2605.17099v1 Announce Type: new
Abstract: Rarefied hypersonic bow shocks over blunt bodies inflate as the Knudsen number increases, but it remains unclear whether this inflation is a simple shift and broadening of one common shock layer or a multi-scale change of the macroscopic and internal-energy fields. We address this question using direct simulation Monte Carlo (DSMC) data for Mach-10 flow over a circular cylinder in argon and nitrogen over \(Kn_\infty \approx 0.01\)--\(1\), together with a Mach-number sweep at \(Kn_\infty=0.01\). At low rarefaction, a ray-based density-gradient ridge gives a reproducible bow-shock location and agrees with an independent schlieren-based shock-wave-detection method. As \(Kn_\infty\) increases, this ridge is replaced by a broad kinetic compression layer, so the high-Knudsen cases are analysed using profile-based standoff and thickness metrics rather than by imposing a visual shock line. The Knudsen- and Mach-number sweeps separate two mechanisms. At fixed \(M_\infty\), the continuum normal-shock density ratio provides a useful low-rarefaction reference compression scale, whereas the measured standoff growth is governed primarily by the kinetic mean free path; the effective density thickness shows an intermediate minimum before increasing in the diffuse regime. At fixed low \(Kn_\infty\), changing \(M_\infty\) mainly changes compression strength and curvature, preserving a coherent attached-layer structure. Density-registered profiles and shock-attached proper orthogonal decomposition (POD) show that, within the present maximum-density-gradient registration, density becomes nearly rank one, whereas Mach number and thermal variables retain independent modal content. Rarefied bow-shock inflation is therefore a coupled compression--relaxation process, not a single-scale rescaling of a continuum-like shock.
toXiv_bot_toot
@arXiv_physicsaoph_bot@mastoxiv.pageA Simulation Methodology Testbed for Typhoon Sensitivity Analysis: Framework Development and Perturbation-Response Experiments with the Pangu Weather Model
Yuehua Peng, Yuchen Zhang, Qin Huang, Chengzhi Ye, Jingsong Yang
https://arxiv.org/abs/2605.21864
@azonenberg@ioc.exchangeContinuing to tweak the 25G diff pairs.
Here I replace a single large meander with a couple of smaller ones and adjust trace width slightly to reduce the mismatch at each meander.
The end result is replacing a single large reflection with a slightly wider but much lower one that should present less of an issue.
(The dip at T=100 is at the BGA ball itself and I'll be tweaking the cutout there slightly as well)
@metacurity@infosec.exchangeNato narrowly beats Russia-style enemy in cyber attack simulation
https://www.ft.com/content/cda17cca-a651-41c5-9ac7-75dcde998c66
@arXiv_physicsmedph_bot@mastoxiv.pageOpenPINT: Open-source Planning for Isoeffective Nuclear Treatments in BNCT research
Ian Postuma, Sara J. Gonz\'alez, Setareh Fatemi, Cristina Pezzi, Carolina Ruzzon, Oreste Nicrosini, Valerio Vercesi, Silva Bortolussi
https://arxiv.org/abs/2606.21476 https://arxiv.org/pdf/2606.21476 https://arxiv.org/html/2606.21476
arXiv:2606.21476v1 Announce Type: new
Abstract: Objective: Present OpenPINT (Open-source Planning for Isoeffective Nuclear Treatments), an open-source treatment planning system for nuclear therapies that integrates Monte Carlo dose calculations with modular dosimetric and radiobiological models for photon-isoeffective dose evaluation.
Approach: We describe the software architecture, implementation choices, and data flow from segmented geometry and source configuration to NIfTI dose outputs. We define BNCT-relevant dosimetric metrics and evaluate the workflow with reproducible analytic and voxelized cylindrical-phantom benchmarks, supplemented by a geometric patient-positioning example.
Main results: The module provides a reproducible and scriptable path for generating MCNP-ready inputs, extracting component-wise BNCT dose maps, and computing analysis-ready outputs for quality checks and decision support. Fine-resolution voxelized configurations reproduced the 1 mm analytic reference within 0.13% for the brain-limited irradiation-time endpoint, whereas the full voxelized sweep exposed deviations up to 4.42% in coarse 8--10 mm configurations. Patient-wide gamma pass rates were at least 99.60% for the evaluated mesh/interpolation cases, while low-dose DVH-tail quantities remained sensitive to boundary discretization.
Significance: This first paper isolates and validates the simulation-preparation and dosimetric-analysis core of an open-source BNCT treatment-planning platform. It establishes a foundation for subsequent work on optimization, biological weighting, and clinical workflow integration.
toXiv_bot_toot
@cosmos4u@scicomm.xyz @mlawton@mstdn.social
@arXiv_physicsgeoph_bot@mastoxiv.pageJoint elastic full waveform inversion of multi-component geophone and distributed acoustic sensing data
Hoang Anh Nguyen, Ali Tura
https://arxiv.org/abs/2607.01649 https://arxiv.org/pdf/2607.01649 https://arxiv.org/html/2607.01649
arXiv:2607.01649v1 Announce Type: new
Abstract: Joint full waveform inversion (FWI) of distributed acoustic sensing (DAS) and ocean-bottom node (OBN) data typically requires converting measured strain to particle velocity, introducing numerical noise and spectral distortion. To eliminate this, we present an elastic multi-parameter FWI framework using a velocity-stress-strain (VSS) formulation that directly models pressure, particle velocity, and gauge-length-averaged DAS strain from a single forward simulation. Data residuals are injected additively into a single backward simulation, making computational cost independent of the active sensor subsets. We benchmark individual and combined datasets on cross-talk and elastic Marmousi models. Our results show that joint inversion recovers elastic parameters more accurately than single deployments when the sensors offer complementary information. Specifically, pairing two-component geophones with a deviated borehole DAS cable yields the most accurate parameter recovery and mitigates inter-parameter cross-talk by providing a distinct physical observable and complementary depth aperture. We release our implementation as xFWI, an open-source, Devito-based Python package for scalable, multi-deployment inversions.
toXiv_bot_toot
@Techmeme@techhub.socialMistral launches Robostral Navigate, a hardware-agnostic robotics navigation model trained via simulation that utilizes a single camera and language prompts (Benoit Berthelot/Bloomberg)
https://www.bloomberg.com/news/articles/20
@Life_is@no-pony.farmWenn wir in einer Simulation leben würden, wäre die längst abgeschaltet worden.
@life_is@no-pony.farmWenn wir in einer Simulation leben würden, wäre die längst abgeschaltet worden.
@arXiv_nlincd_bot@mastoxiv.pageReplaced article(s) found for nlin.CD. https://arxiv.org/list/nlin.CD/new
[1/1]:
- Geometric encoding of turbulence for end-to-end quantum simulation
Zhaoyuan Meng, Xiao-Ming Zhang, Xiao Yuan, Yue Yang
@arXiv_csIT_bot@mastoxiv.pageJoint Movable Antenna Positioning and RIS Partitioning for Sum-Rate Maximization
Mohammed Saif
https://arxiv.org/abs/2606.11519 https://arxiv.org/pdf/2606.11519 https://arxiv.org/html/2606.11519
arXiv:2606.11519v1 Announce Type: new
Abstract: This paper investigates the utility of the movable antenna (MA) and reconfigurable intelligent surface (RIS) framework for downlink wireless communications. In the considered scenario, a base station (BS) is equipped with two sub-arrays of MAs transmits signals to the users via the RIS. By jointly exploiting the antenna-positioning flexibility of MAs and the RIS element selection capability, the proposed joint MA-RIS framework introduces additional design degrees of freedom to enhance desired signals and mitigate inter-user interference, thereby maximizing the network sum-rate. To this end, we formulate a joint optimization problem involving MA positioning, sub-array beamforming, and RIS element selection, subject to the minimum antenna separation and transmit power constraints. The resulting problem is highly non-convex and challenging to solve directly. To address this issue, an alternating optimization framework is developed that decomposes the problem into three tractable subproblems. Specifically, zero-forcing beamforming is employed for transmit beamformer design, a low-complexity one-dimensional search is derived for RIS element selection, and the MA positioning problem is solved using block coordinate descent (BCD) and convex optimization techniques implemented via CVX. Simulation results demonstrate that the proposed joint MA-RIS framework significantly improves the achievable sum-rate compared with conventional fixed MAs and benchmark schemes with random configurations.
toXiv_bot_toot
@arXiv_quantph_bot@mastoxiv.pageReplaced article(s) found for quant-ph. https://arxiv.org/list/quant-ph/new
[1/5]:
- Tight Bounds for Quantum Phase Estimation and Related Problems
Nikhil S. Mande, Ronald de Wolf
https://arxiv.org/abs/2305.04908 https://mastoxiv.page/@arXiv_quantph_bot/110337460439591382
- Quantum thermodynamics of the Caldeira-Leggett model with non-equilibrium Gaussian reservoirs
Vasco Cavina, Massimiliano Esposito
https://arxiv.org/abs/2405.00215 https://mastoxiv.page/@arXiv_quantph_bot/112370293649586776
- A quantum implementation of high-order power method for estimating geometric entanglement of pure...
Andrii Semenov, Niall Murphy, Simone Patscheider, Alessandra Bernardi, Elena Blokhina
https://arxiv.org/abs/2405.19134 https://mastoxiv.page/@arXiv_quantph_bot/112528797708787049
- Unifying framework for quantum simulation algorithms for time-dependent Hamiltonian dynamics
Yu Cao, Shi Jin, Nana Liu
https://arxiv.org/abs/2411.03180 https://mastoxiv.page/@arXiv_quantph_bot/113435338816776896
- Mixed-State Topological Order under Coherent Noise
Seunghun Lee, Eun-Gook Moon
https://arxiv.org/abs/2411.03441 https://mastoxiv.page/@arXiv_quantph_bot/113440883864687961
- Quest for quantum advantage: Monte Carlo wave-function simulations of the Coherent Ising Machine
Manushan Thenabadu, Run Yan Teh, Jia Wang, Simon Kiesewetter, Margaret D Reid, Peter D Drummond
https://arxiv.org/abs/2501.02681 https://mastoxiv.page/@arXiv_quantph_bot/113786139350946567
- Honest-binding quantum bit commitment from separable operations
Ziad Chaoui, Anna Pappa, Matteo Rosati
https://arxiv.org/abs/2501.07351 https://mastoxiv.page/@arXiv_quantph_bot/113825499573295523
- Expressivity of Quantum Reservoir Computers
Sch\"utte, G\"otting, M\"untinga, List, Brunner, Gies
https://arxiv.org/abs/2501.15528 https://mastoxiv.page/@arXiv_quantph_bot/113904787967762788
- Additivity and chain rules for quantum entropies via multi-index Schatten norms
Omar Fawzi, Jan Kochanowski, Cambyse Rouz\'e, Thomas Van Himbeeck
https://arxiv.org/abs/2502.01611 https://mastoxiv.page/@arXiv_quantph_bot/113944408733032864
- On the Addressability Problem on CSS Codes
J\'er\^ome Guyot, Samuel Jaques
https://arxiv.org/abs/2502.13889 https://mastoxiv.page/@arXiv_quantph_bot/114035128180919513
- Robust Mixed-State Cluster States and Spurious Topological Entanglement Negativity
Seunghun Lee, Eun-Gook Moon
https://arxiv.org/abs/2504.16165 https://mastoxiv.page/@arXiv_quantph_bot/114391788348136547
toXiv_bot_toot
@tinoeberl@mastodon.onlineDie monatliche #Energieerzeugung meiner #Kernfusionskollektoranlage im Vergleich zu Prognosedaten aus einer Simulation.
Gesamtleistung: 480 Wp
Ausrichtung: West
Anstellwinkel: 58 Grad
👉 So berechnest Du die Jahresertragsprognose:
@BBC6MusicBot@mastodonapp.uk🇺🇦 #NowPlaying on #BBC6Music's #LaurenLaverne
Big Thief:
🎵 Simulation Swarm
#BigThief
https://bigthief.bandcamp.com/track/simulation-swarm
https://open.spotify.com/track/2FwDApgXk91kXvqy2oB7dz
@azonenberg@ioc.exchangeAfter a bunch of iterating and simulation and getting pulled away for other things, I'm finally happy with the backside-fed ARF6 connector launch on the LATENTRED switch engine board.
Simulated return loss of the simple naive version (vias in pads, no ground cutouts or optimization) was around -10 dB return loss starting at 15 GHz and rising to -8.8 at 30 and -6 at 35.
Adding a cutout to the first ground layer improved this significantly, better than -15 dB to 33.8 GHz.
@arXiv_physicscompph_bot@mastoxiv.pageReconstructing Unobservable Temperature Fields via Simulation-Aided Intelligent Sensing
Monika Stipsitz, H\`elios Sanchis-Alepuz, Jacob Reynvaan, Silvester Sabathiel
https://arxiv.org/abs/2606.04582
@arXiv_csGR_bot@mastoxiv.pageEVOLVE: Efficient Learned Volume Compression with Variable-Rate Encoding on a Cross-Domain Database
Kaiyuan Tang, Maizhe Yang, Chaoli Wang
https://arxiv.org/abs/2607.18187 https://arxiv.org/pdf/2607.18187 https://arxiv.org/html/2607.18187
arXiv:2607.18187v1 Announce Type: new
Abstract: Large-scale scientific simulations generate volumetric data at rates that far outpace advances in storage and network bandwidth, making effective lossy compression increasingly critical. However, conventional compressors often struggle to preserve fine structural details at high compression ratios (CRs), and implicit neural representations (INRs) require costly per-volume optimization and produce models with fixed CRs. To respond, we present EVOLVE, an autoencoder (AE)-based volume-compression framework that targets high CRs for offline compression, with three key contributions. First, we construct a large-scale cross-domain database of 6,376 volumes from 21 scientific simulations, curated via perceptual hashing to ensure diversity, enabling the optimized model to extract features that generalize across volumes within the covered scientific simulation domains. Second, we reexamine the design space of AE-based compressors and incorporate several macro- and micro-designs into a vanilla AE to develop EVOLVE, which substantially improves the expressive power and compression capability. Third, we develop a learnable gain mechanism with a three-stage training strategy to enable variable-rate encoding, allowing a single model to support continuous CR adjustment at inference time. Experiments on multiple unseen scientific simulation datasets demonstrate that EVOLVE achieves substantially higher CRs than conventional compressors at comparable reconstruction quality, while delivering compression speeds that are orders of magnitude faster than INR-based methods, highlighting its promise as a strong alternative for compressing scientific data. The code, model weights, and results are available on our project page at https://evolve-vis.github.io.
toXiv_bot_toot
@arXiv_csGT_bot@mastoxiv.pageExploring cooperation mechanisms via reinforcement learning in network common-pool resource games
Yihang Qin, Lin Wang
https://arxiv.org/abs/2606.05867 https://arxiv.org/pdf/2606.05867 https://arxiv.org/html/2606.05867
arXiv:2606.05867v1 Announce Type: new
Abstract: Sustaining cooperation in resource-constrained populations requires allocation mechanisms that balance individual incentives, resource sustainability, and distributional fairness. This paper proposes a network common-pool resource game in which individuals are embedded in complex networks, participate in multiple overlapping local resource pools, and face endogenous resource constraints during strategy evolution. Within this framework, we first examine two representative allocation mechanisms, equal allocation and proportional allocation. The results show that equal allocation produces fair but inefficient outcomes by weakening contribution incentives, whereas proportional allocation can temporarily promote cooperation but amplifies accumulated advantages and leads to severe inequality. To overcome these limitations, we develop a graph neural network-based reinforcement learning framework in which a learned social planner allocates local pool resources without directly controlling individual strategies. Simulation results under four representative network topologies show that the learned planner sustains higher cooperation levels and average accumulated resources, and reduces inequality compared with the baselines. Furthermore, we interpret the learned policy and distill it into two simpler mechanisms: a resource-dependent mixture mechanism for regular networks and a degree-conditioned mixture mechanism for heterogeneous networks. These mechanisms reveal that effective allocation should adapt to both local resource states and structural positions, providing an interpretable route from reinforcement learning policy search to mechanism design in networked resource-sharing systems.
toXiv_bot_toot
@arXiv_astrophGA_bot@mastoxiv.pageReplaced article(s) found for astro-ph.GA. https://arxiv.org/list/astro-ph.GA/new
[2/3]:
- Hunting Wandering 3<z<8 Black Holes: Spatial Offsets in Ionization Ratio and Continuum Emission
Urvi Thakurdesai, et al.
https://arxiv.org/abs/2606.30715 https://mastoxiv.page/@arXiv_astrophGA_bot/116843669196485332
- Spectral Energy Distributions of Globular Clusters in VV191a
Ashton Cardona, et al.
https://arxiv.org/abs/2607.10352 https://mastoxiv.page/@arXiv_astrophGA_bot/116917375134409194
- The different methods to calculate cluster membership probabilities
Tahereh Ramezani, Prapti Mondal, Katerina Neumannova, Ernst Paunzen, Johana Supikova, Gabriel Szasz
https://arxiv.org/abs/2607.13711 https://mastoxiv.page/@arXiv_astrophGA_bot/116928584338673264
- On the current status of tidal tails of Galactic open clusters
Tahereh Ramezani, Prapti Mondal, Katerina Neumannova, Ernst Paunzen, Johana Supikova, Gabriel Szasz
https://arxiv.org/abs/2607.13747 https://mastoxiv.page/@arXiv_astrophGA_bot/116928607930493156
- The Stripped-Star Ultraviolet Magellanic Cloud Survey (SUMS): The UV Photometric Catalog and Stri...
Bethany Ludwig, Maria R. Drout, Ylva Gotberg, Dustin Lang, Alexander Laroche
https://arxiv.org/abs/2505.18632 https://mastoxiv.page/@arXiv_astrophSR_bot/114578704405418342
- Observable signature of magnetic tidal coupling in hierarchical triple systems
Marta Cocco, Gianluca Grignani, Troels Harmark, Marta Orselli, Davide Panella, Daniele Pica
https://arxiv.org/abs/2510.24897 https://mastoxiv.page/@arXiv_grqc_bot/115462391818777276
- Periodic Gravitational Lensing with Oscillating Boson Stars
Xing-Yu Yang, Tan Chen, Rong-Gen Cai
https://arxiv.org/abs/2511.19606 https://mastoxiv.page/@arXiv_grqc_bot/115615137595636545
- Search for Dark Matter Annihilation and Decay with H$\alpha$ Line Emission
Rebecca K. Leane
https://arxiv.org/abs/2512.09019 https://mastoxiv.page/@arXiv_hepph_bot/115700041751825685
- Reanalyzing DESI DR1: 5. Cosmological Constraints with Simulation-Based Priors
Anton Chudaykin, Mikhail M. Ivanov, Oliver H. E. Philcox
https://arxiv.org/abs/2602.18554 https://mastoxiv.page/@arXiv_astrophCO_bot/116124504277603946
- Can wormholes have vanishing Love numbers?
Shauvik Biswas
https://arxiv.org/abs/2605.03025 https://mastoxiv.page/@arXiv_grqc_bot/116526586864139338
toXiv_bot_toot
@galaxydinodragon@social.linux.pizzaCan any satellite imagery nerds help me out here?
Basically, I have a custom index made in QGIS from various sentinel 2 bands to try map fuel availability for grass fires. On this index, high values are "better" fuel ig is how you would phrase.
What I want to do is randomly elect "hot points" which would be the start point of a grass fire, I then have a spread simulation function to run based on distances of pixels from the hot spot as well as various other t…
@azonenberg@ioc.exchangeWhich one of these BGA fanouts is better?
Both are the same nominal trace/space, both are skew matched by the time you get to the vertical "home run" area heading towards the connector.
But TDR of the first one wasn't that great. Let's see if the second one is any better when the simulation finishes...
@tinoeberl@mastodon.onlineDie monatliche #Energieerzeugung meiner #Kernfusionskollektoranlage im Vergleich zu Prognosedaten aus einer Simulation.
Gesamtleistung: 480 Wp
Ausrichtung: West
Anstellwinkel: 58 Grad
👉 So berechnest Du die Jahresertragsprognose:
@Techmeme@techhub.socialA look at Eka, which trains its robotic claw on a "vision-force-action model" incorporating realistic joints, motors, and physics principles into its simulation (Will Knight/Wired)
https://www.wired.com/story/when-robots-have-their-chatgpt-…
@@arXiv_physicsatomph_bot@mastoxiv.page@mastoxiv.pageCrosslisted article(s) found for physics.atom-ph. https://arxiv.org/list/physics.atom-ph/new
[1/1]:
- Many-Body Physics with Rydberg Atoms: Quantum Simulation and Non-equilibrium Dynamics
Zhengyang Bai, Cheng Chen, Fan Yang, Weibin Li
@cosmos4u@scicomm.xyzA more technical update about the start of the #LSST with the #RubinObservatory in spite of non-perfect performance: https://community.lsst.org/t/the-lsst-has-started/12201 -> "a brief summary of what has prompted us to draw the early operations optimization phase to a close and get the survey started. [...] Pre-LSST observations show that the as-built Simonyi Telescope can already deliver an arcsecond sky survey, and there is a technical pathway to make the ~10% improvement in delivered image quality needed to approximately match the baseline survey simulation and deliver a sub-arcsecond LSST, as required. [...] The Board also noted that the time was right: all eight LSST Science Collaborations sent written support for starting the LSST while continuing to improve performance in parallel."
@arXiv_csIT_bot@mastoxiv.pageSegment-Wise Soft Robotics Inspired Flexible Antenna Arrays: Design and Optimization
Shuaishuai Han, Konstantinos Ntougias, Elio Faddoul, Ioannis Krikidis
https://arxiv.org/abs/2606.11771 https://arxiv.org/pdf/2606.11771 https://arxiv.org/html/2606.11771
arXiv:2606.11771v1 Announce Type: new
Abstract: In this paper, we propose a segment-wise soft robotic antenna (SRA) system, where each soft robotic arm referred to as a tentacle, comprises multiple independently controllable segments with bending, elongation-retraction, and sweeping motions. By adjusting segment motion parameters, the positions of surface-mounted antennas are reconfigured, distinguishing it from conventional reconfigurable antenna (RA) systems. Based on this model, we propose two antenna deployment schemes: the segmented end-antenna configuration (SEAC), where fixed antennas are mounted at the segment ends and reconfigured via segment motions; and the hybrid end-and-intermediate antenna configuration (HEIAC), where RAs are further integrated as intra-segment antennas. In HEIAC, soft-robot segment deformation provides large-scale spatial reconfiguration, while RAs enable fine-grained adjustment. For SEAC, we formulate a sum-rate maximization problem accounting for inter-segment connectivity and the nonlinear mapping from segment deformation parameters to antenna coordinates, and develop a penalty dual decomposition-projected gradient ascent (PDD-PGA) algorithm. For HEIAC, we jointly optimize segment deformation, intra-segment antenna positions, and antenna activation using a block coordinate descent (BCD)-PDD-PGA algorithm with greedy backward antenna selection. Simulation results demonstrate that the proposed schemes substantially outperform fixed-position antenna arrays and conventional RA baselines. In particular, SEAC and HEIAC achieve 37.9% and 32.1% sum-rate gains over conventional 3D reconfigurable arrays, respectively, while SEAC provides up to a 49.3% gain in compact array deployments.
toXiv_bot_toot
@tinoeberl@mastodon.onlineDie monatliche #Energieerzeugung meiner #Kernfusionskollektoranlage im Vergleich zu Prognosedaten aus einer Simulation.
Gesamtleistung: 480 Wp
Ausrichtung: West
Anstellwinkel: 58 Grad
👉 So berechnest Du die Jahresertragsprognose:
@arXiv_csGR_bot@mastoxiv.pageReplaced article(s) found for cs.GR. https://arxiv.org/list/cs.GR/new
[1/1]:
- ClothTransformer: Unified Latent-Space Transformers for Scalable Cloth Simulation
Yu Zhang, Yidi Shao, Wenqi Ouyang, Yushi Lan, Zhexin Liang, Chengrui Wu, Xudong Xu, Xingang Pan
https://arxiv.org/abs/2605.27852 https://mastoxiv.page/@arXiv_csGR_bot/116651047586260795
toXiv_bot_toot
@arXiv_csGR_bot@mastoxiv.pageFast Wave-optics Rendering of Multiplane Images for 3D Holographic Displays
Brian Chao, Dario Seyb, Nathan Matsuda, Oliver Cossairt, Yang Zhou, Douglas Lanman, Gordon Wetzstein, Grace Kuo, Changwon Jang
https://arxiv.org/abs/2607.19731 https://arxiv.org/pdf/2607.19731 https://arxiv.org/html/2607.19731
arXiv:2607.19731v1 Announce Type: new
Abstract: Recent advances in neural rendering have unlocked unprecedented capabilities in 3D reconstruction and novel view synthesis, giving rise to applications such as virtual fly-throughs of a 3D scene reconstructed from a set of sparse, casually captured images. However, these renderings are viewed on a computer screen or conventional VR headsets as 2D images, greatly limiting the perceptual realism and immersiveness of such experiences. The rapid development in novel 3D scene representations calls for dedicated rendering algorithms that convert these readily-available 3D contents into formats that are compatible with emerging 3D display technologies, such as holographic displays. In this paper, we propose a wave-optics rendering pipeline that works with multiplane images (MPIs) for efficient and high-quality hologram synthesis. Our MPI-based computer-generated holography algorithm greatly outperforms state-of-the-art primitive-based CGH algorithms in terms of runtime, achieving speedups up to 250,000x while achieving comparable image quality, and significantly outperforms conventional layer-based CGH algorithms in terms of image quality. We validate our method extensively on a wide variety of 3D scene datasets both in simulation and through experimentally captured results, showing exceptional 3D focal stack and 4D light field reconstruction performance without sacrificing efficiency.
toXiv_bot_toot
@arXiv_physicsmedph_bot@mastoxiv.pageTheoretical derivation of blood velocity from TOF-MRA based artery centerline
Abrar Faiyaz
https://arxiv.org/abs/2607.16498 https://arxiv.org/pdf/2607.16498 https://arxiv.org/html/2607.16498
arXiv:2607.16498v1 Announce Type: new
Abstract: Time-of-flight magnetic resonance angiography (TOF-MRA) is widely used for structural vascular imaging, but extracting functional hemodynamics like blood velocity typically requires supplementary phase-contrast scans. This study proposes a novel, physics-informed computational framework to extract variable fluid velocity directly from standard TOF-MRA signal profiles. We analytically expand the Bloch equations into Bloch-McConnell flow equations, establishing a mathematical relationship between the spatial decay of longitudinal magnetization and fluid velocity. To validate this derivation and overcome the limitations of constant-velocity assumptions, a MATLAB simulation framework was developed to model fluid flow in two variable-geometry flowing tube cases i.e continuous tapering and focal stenosis -under synthetic scanner noise. A global inverse optimization approach utilizing Dual-Tikhonov regularization was deployed to stably invert the ill-posed transit time integral, actively penalizing high-frequency numerical ringing while preserving structural curve stiffness. The computational sim-ulations successfully recovered ground-truth point-wise velocities, accurately tracking gradual hemodynamic accelerations and sharp stenotic jets. This theoretical framework provides a robust mathematical proof-of-concept that quantitative, localized functional hemodynamic metrics can be extracted from standard structural MRA imaging, estab-lishing a foundation for advanced flow quantification without requiring additional scan time.
toXiv_bot_toot
@hex@kolektiva.socialEvery now and then someone brings up #EffectiveAltruism, #TESCREAL, #RokosBasilisk, #Rationalism, or some other #Musk related nonsense. I ridicule it, or laugh, and move on. The whole evil god of Roko's Basilisk is so silly it doesn't feel worth writing about. But people started a whole cult over it and killed a bunch of people.
Since then I've been meaning to actually spend time tearing it down. So I think it's time to go kill a god. Fortunately it involves making fun of Elon Musk specifically and all the #AI-pilled #TechBros more generally, so that's nice I guess.
Also, I make the argument that we're all in a simulation that only exists to torture Elon Musk.
#NoAI #Singularity #longtermism #Yudkowsky #Zizians
