Tootfinder

Eu estava lendo agora hš pouco sobre mitologia hindu na wikipedia. O assunto é fascinante, mas é muito confuso. Os deuses e entidades têm všrias manifestações, cada uma com diferentes formas e nomes (nomes esses ališs, bem esquisitos e difíceis de diferenciar). No fim, eu sempre saio dessas leituras com a impressão de estar entendendo menos do assunto do que antes da leitura kkkk.
Não adianta, pra mim tem que ser essas versões muito ocidentalizadas. Como as do William Buck.

RE: https://masto.pt/@tugatech/116624544854397332
O pior carro Š venda no mercado europeu agora quer transformar uma compra num aluguer.

🇺🇦 #NowPlaying on KEXP's #MiddayShow
Algernon Cadwallader:
🎵 You’ve Always Been Here
#AlgernonCadwallader
https://algernoncadwallader.bandcamp.com/track/youve-always-been-here
https://open.spotify.com/track/1AQRyY7PtSZlRBCOmNmdAA

Improved Approximation Guarantees for Groupwise Maximin Share Fairness
Georgios Amanatidis, Anna Korfiati, Evangelos Markakis, Christodoulos Santorinaios
https://arxiv.org/abs/2606.04731 https://arxiv.org/pdf/2606.04731 https://arxiv.org/html/2606.04731
arXiv:2606.04731v1 Announce Type: new
Abstract: We study the problem of fairly allocating a set of indivisible goods to a set of $n$ agents with additive valuation functions. We focus on the very demanding notion of \textit{groupwise maximin share fairness} (GMMS), which requires that each agent $i$ receives value comparable to their maximin share, where the latter is computed \textit{with respect to any subset of agents that contains $i$}. We show that it is possible to compute $(\phi-1)$-approximate GMMS allocations in polynomial time, where $\phi \approx 1.618$ is the golden ratio). This improves on the previously known guarantee of $4/7$ of Chaudhury et al. [SICOMP; 2021] and Amanatidis et al. [TCS; 2020]. We propose a simple algorithm that maintains the same main properties as the Draft-and-Eliminate algorithm of Amanatidis et al. [TCS, 2020] and we improve on the approximation guarantee analysis by carefully bounding the relevant value within any subinstance induced by the restriction of our allocation to a subset of agents. Our analysis is asymptotically tight for algorithms that share these properties and has the additional benefit of giving improved guarantees for restricted settings; in particular, when the agents agree on the top $n$ goods or when the number of agents is small. To illustrate the challenges of going beyond the guarantees of our algorithm, we also present a variant with an improved approximation of $(\sqrt{10}-1)/3 \approx 0.72$ for the case of three agents. To achieve this improvement we partially characterize the maximin share guarantees of short picking sequences for a small number of goods.
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Ališs, a seleção brasileira (de verde e amarelo) estš jogando melhor neste jogo de agora do que no jogo de mais cedo, hein? rs
#Copa2026 #CopaFifa2026 #CopaMundialFIFA

Era uma vez um blogue sobre literatura fantšstica relacionada com o Algarve que estava alojado nos blogues do Sapo.
O endereço era (e contunuarš a ser, durante algum tempo) https://fantasticoalgarve.blogs.sapo.pt/
Pois bem, agora estš no Wordpress, em

Vz-GAL Dusty Star-Forming Galaxies: Revisiting the CO-H2 Conversion Factor Tension
Prachi Prajapati, Axel Weiss, Dominik Riechers, Tom J. L. C. Bakx, Leindert A. Boogaard, Diana Ismail, Pierre Cox, Andrew J. Baker, Roberto Neri, Matthew Lehnert, Chentao Yang, Emilio Romano-Diaz, Hiddo S. B. Algera, Stefano Berta, Edoardo Borsato, Kirsty M. Butler, Asantha Cooray, Bethany Jones, Amelie Saintonge, Paul van der Werf
https://arxiv.org/abs/2607.18440 https://arxiv.org/pdf/2607.18440 https://arxiv.org/html/2607.18440
arXiv:2607.18440v1 Announce Type: new
Abstract: The CO luminosity-to-H$_2$ mass conversion factor ($\alpha_{CO}$) remains a debated uncertainty in determining molecular gas masses of high-redshift dusty star-forming galaxies (DSFGs). Dynamical mass constraints have often favored $\alpha_{CO}=0.8$~$M_{\odot}~{(K~km~{s}^{-1}~{pc}^{2})}^{-1}$, whereas dust- and radiative-transfer-based methods imply higher values. We revisit this ``tension" using the largest homogeneous sample of 21 unlensed $z\sim1-4$ DSFGs, with securely measured \coonezero luminosities from the VLA \vzgal survey and resolved ($\sim{0.1}^{\prime\prime}$) ALMA 1~mm dust continuum imaging. For 12 galaxies with robust modeling constraints, we derive molecular gas masses using dust spectral energy distribution modeling and the TUNER LVG framework, adopting a solar-metallicity gas-to-dust mass ratio of 100. Although not fully independent due to shared assumptions on dust properties, these approaches yield mutually consistent gas masses corresponding to $\alpha_{CO}\sim1.5-11.5$, with a median near the Galactic $\alpha_{CO}=4.3$. Isotropic virial dynamical masses agree with these gas masses when realistic molecular gas sizes are adopted, while our proposed ``mixed" (rotating, pressure-supported, thick-disk) estimator systematically underestimates dynamical masses, producing low $\alpha_{CO}$ limits. Using GN20 ($z=4.055$) as a case study, we show that resolved gas geometry and kinematics reconcile the discrepancy with LVG-derived $\alpha_{CO}$. Our results suggest that current data do not require $\alpha_{CO}=0.8$, and intermediate to near-Galactic values remain dynamically viable given uncertainties in gas geometry, dust properties, and gas-to-dust ratios. Further progress in calibrating $\alpha_{CO}$ in the early universe will require resolved molecular gas observations, physically motivated ISM modeling, and stringent constraints on dust properties.
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An iterative Ising decoder for quantum error correction codes
Yuanqi Liu, Weilei Zeng, Peixiang Li, Yantong Liu, Guangyao Huang, Yingwen Liu, Dongyang Wang, Junjie Wu, Lingling Lao
https://arxiv.org/abs/2606.12301 https://arxiv.org/pdf/2606.12301 https://arxiv.org/html/2606.12301
arXiv:2606.12301v1 Announce Type: new
Abstract: The Ising framework maps the decoding problem in quantum error correction onto ground-state optimization of a classical Hamiltonian, in which $X$-$Z$ error correlations enter as cross terms. Under phenomenological depolarizing noise, the exact joint formulation contains up to 8-body interactions for the toric code and 10-body for the $6.6.6$ color code. These high-order terms degrade solver convergence, inflate runtime, and raise the auxiliary spin overhead when embedding into native 2-body Ising hardware. In this work, we propose the iterative low-order decoding (ILOD) algorithm, which alternates between $X$- and $Z$-type sub-Hamiltonians, approximating cross-type correlations through Bayesian priors that reweight each type's couplings using the other type's inferred error configuration. This halves the maximum body count of interaction terms in the Hamiltonian, accelerating the solver, restoring convergence at larger code distances, and reducing the total spin count for 2-body embedding by a factor of $2.5$. For the toric code, ILOD attains a threshold of $4.73%$ versus $4.83%$ for the joint formulation, with the empirical runtime ratio scaling as $(0.81)^d$. For the $6.6.6$ color code, their thresholds agree within statistical uncertainty for small code distances, and ILOD remains convergent for larger distances where the joint formulation fails to converge despite a larger annealing budget.
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🇺🇦 #NowPlaying on BBCRadio3's #Radio3Breakfast
Antoine Reicha, Munich Radio Orchestra & Valentin Egel:
🎵 Symphony in D Major, AJR I:17: IV. Finale. Allegro vivace
#AntoineReicha #MunichRadioOrchestra #ValentinEgel