@Techmeme@techhub.socialOpenAI confirms it will follow President Trump's EO that asks AI companies to allow the US government to assess their models' capabilities before release (Michael Considine/CNBC)
https://www.cnbc.com/2026/06/05/openai-trump-ai-model-review-order.html
@memeorandum@universeodon.comA Conservative Role Model for Ending the Fertility Crisis (Anemona Hartocollis/New York Times)
https://www.nytimes.com/2026/07/08/us/politics/emma-waters-restorative-reproduction.html
http://www.memeorandum.com/260708/p125#a260708p125
@arXiv_hepth_bot@mastoxiv.pageIntegrable models of inflation beyond slow-roll
M. Bianchi, G. Dibitetto, J. F. Morales, V. Zevola
https://arxiv.org/abs/2608.06071 https://arxiv.org/pdf/2608.06071 https://arxiv.org/html/2608.06071
arXiv:2608.06071v1 Announce Type: new
Abstract: We propose a novel analytic approach to the study of multi-component FLRW cosmologies and their perturbations. The dynamics is triggered by a single scalar field with a scalar potential codifying the energy density and pressure of the multi-component fluid. This description unifies standard Big Bang cosmologies, models of inflation and dark energy under a unique framework. The key to integrability is to express the scalar potential in terms of the Hubble function $H(\phi)$ that plays the role of a fake superpotential, turning the dynamics into a first order problem, that may be analytically solved in a suitable time coordinate. In this framework, we propose integrable inflationary models with similar properties to the ones analysed in the literature and compatible with observations. Finally, we study scalar and tensor cosmological perturbations in each model by integrating Mukhanov-Sasaki equations via numerical and (semi-)analytic techniques. This allow us to compute the power spectrum, the spectral indices and the tensor-to-scalar ratio beyond the slow-roll approximation and compare our general results {against} the currently available observations and the theoretical predictions based on the slow-roll approximation.
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@arXiv_mathDS_bot@mastoxiv.pagePattern formation: reactivity is not necessary for chemotaxis--driven instabilities
Angela Monti
https://arxiv.org/abs/2608.03685 https://arxiv.org/pdf/2608.03685 https://arxiv.org/html/2608.03685
arXiv:2608.03685v1 Announce Type: new
Abstract: A classical result by Neubert, Caswell and Murray states that reactivity of a spatially homogeneous equilibrium is a necessary condition for diffusion-driven (Turing) instability. In this work, we investigate whether the same conclusion remains valid in the presence of chemotaxis. We consider a general reaction--diffusion system coupled with a chemotactic flux and establish necessary conditions for asymptotic instability. We show that the classical requirement of reactivity can be relaxed when the chemotactic contribution is sufficiently strong. In particular, while reactivity remains necessary for Turing instability, it is not a necessary condition for chemotaxis-driven instability. From a computational viewpoint, we extend the matrix-oriented formulation developed for reaction--diffusion systems to the more general class of reaction--diffusion--chemotaxis models. The chemotactic transport term is discretized in a form compatible with the matrix-oriented approximation of the diffusion operator, yielding an efficient numerical framework for the simulation of chemotaxis-driven pattern formation. A geometric interpretation of the instability region is presented, highlighting the distinct roles played by diffusion and chemotaxis. The theoretical and numerical developments are illustrated through two representative examples: a chemotaxis-extended Schnakenberg model, showing how chemotaxis modifies classical Turing patterns, and a predator--prey model, demonstrating that chemotaxis alone can induce pattern formation in the absence of both reactivity and diffusion-driven instability. These results reveal a fundamental difference between diffusion-driven and chemotaxis-driven mechanisms of spatial self-organization and provide new theoretical and computational insights into the role of non-symmetric transport processes in biological pattern formation.
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@arXiv_physicsgeoph_bot@mastoxiv.pageHow effective normal stress oscillations advance failure in fault gouge: frequency dependence, non-failure window, and the role of dilation
Pritom Sarma, Einat Aharonov, Renaud Toussaint, Stanislav Parez
https://arxiv.org/abs/2607.01448 https://arxiv.org/pdf/2607.01448 https://arxiv.org/html/2607.01448
arXiv:2607.01448v1 Announce Type: new
Abstract: Cyclic pore-pressure or normal stress variations arise both in relation to natural earthquakes and in engineered subsurface systems, yet their effect on fault stability remains poorly constrained at the grain scale. Here we numerically model, using a coupled Discrete Element--fluid dynamics model, the response of a sheared, fluid-saturated or dry, gouge-filled fault to effective normal stress oscillations over a wide frequency range (0.5-10000 Hz). The effective normal stress is oscillated either by cycling the pore-pressure or by directly cycling the normal stress, while keeping the stress state below the Mohr-Coulomb threshold measured in continuous loading. Despite this sub-critical loading, we observe failure across most frequencies, with a non-monotonic frequency dependence. A distinct non-failure window emerges at intermediate frequencies (30-200 Hz), bounded by failure at both lower and higher frequencies; the system exhibits four regimes from cyclic failure-and-arrest to continuous sliding. Pore-pressure and normal stress oscillations produce the same regime structure, confirming that they act as equivalent forcings via Terzaghi's principle, with fluid coupling adding only a delay due to dilatant hardening. Sub-critical failure arises from dilation-induced strength deterioration via two mechanisms: (i) low-frequency cycles allow sufficient time for shear-driven ratcheting dilation, while (ii) high-frequency cycles induce dynamic dilation (acoustic fluidization) via amplified seepage forces, stress gradients and inertial forces. The intermediate non-failure window represents the gap between these mechanisms. These results identify frequency as a controlling parameter for failure in granular materials, with implications for dynamic earthquake triggering and cyclic injection protocols.
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@arXiv_physicsfludyn_bot@mastoxiv.pageA discrete Boltzmann model with state-dependent power-law relaxation time for nonequilibrium transport in compressible flows
Demei Li, Zhongyi He, Huilin Lai, Yanbiao Gan, Hailong Liu, Pengfei Lin
https://arxiv.org/abs/2605.18216 https://arxiv.org/pdf/2605.18216 https://arxiv.org/html/2605.18216
arXiv:2605.18216v1 Announce Type: new
Abstract: Thermodynamic nonequilibrium effects play a central role in momentum and energy transport in compressible flows. In conventional BGK kinetic models, the relaxation time $\tau$ is taken as a constant, which neglects the dependence of the relaxation process on local macroscopic states. To overcome this limitation, we develop a discrete Boltzmann model with a density- and temperature-dependent power-law relaxation time, termed DTRT-DBM, in which $\tau=\tau_0(\rho/\rho_0)^a(T/T_0)^b$. This formulation extends the discrete Boltzmann framework to flows with spatially varying nonequilibrium intensity. The model is validated by the Sod shock tube and by analytical solutions for viscous stress and heat flux, demonstrating accurate recovery of both macroscopic wave structures and nonequilibrium quantities across shock waves, rarefaction waves, and contact discontinuities. On this basis, phase diagrams of viscous stress and heat flux are constructed to examine how these quantities depend on the power-law exponents $a$ and $b$. The extrema of these quantities depend exponentially on the model parameters and exhibit regime-dependent behaviour. The roles of $a$ and $b$ are not symmetric: the nonequilibrium response is more sensitive to $a$ when density gradients dominate, but more sensitive to $b$ when temperature gradients dominate. Within the parameter range and flow configurations examined here, higher-order viscous stress increases the growth rate of the total viscous-stress extremum, whereas higher-order heat flux reduces the growth rate of the total heat-flux extremum. These results show that the proposed model can capture different higher-order nonequilibrium responses in compressible flows and provides a framework for the modelling and analysis of multiscale nonequilibrium processes.
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@arXiv_qbioNC_bot@mastoxiv.pageAnalysis of inter-spike interval statistics in neuronal networks with depolarizing and hyperpolarizing threshold potentials
Oliver Gambrell, Abhyudai Singh
https://arxiv.org/abs/2607.18428 https://arxiv.org/pdf/2607.18428 https://arxiv.org/html/2607.18428
arXiv:2607.18428v1 Announce Type: new
Abstract: Neuronal communication is mediated in part by changes in neuronal firing rates. The time interval between successive neuronal firings is referred to as the inter-spike interval (ISI), and quantifying its statistics is important for understanding neuronal communication. This paper studies the ISI statistics of a postsynaptic neuron receiving independent excitatory and inhibitory presynaptic action potentials (EI circuit). This circuit is modeled as a classical integrate-and-fire neuron, and the ISI statistics are investigated for both fixed and adaptive threshold potentials. First, a depolarizing adaptive threshold model is studied, where the threshold potential increases with the postsynaptic membrane potential. Our analysis shows that the ISI noise, quantified as the coefficient of variation, is larger in the adaptive threshold model compared to the fixed threshold model for the same mean ISI. Additionally, simulations reveal that the ISI noise can be either hypo- or hyper-exponential (defined as ISI noise smaller or larger than one, respectively) depending on the frequencies of excitatory and inhibitory inputs. Next, a hyperpolarizing adaptive threshold potential is studied, where the threshold decreases as the membrane potential hyperpolarizes. Interestingly, this model shows that the postsynaptic neuron can generate action potentials (APs) when driven solely by inhibitory inputs. Furthermore, mean and noise signatures are characterized across model parameters for both excitatory and inhibitory inputs. In summary, this work provides a systematic stochastic analysis of adaptive threshold models for AP generation to understand their role in interneuronal information processing.
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