Tootfinder

An elementary derivation of 3-cycles for a quadratic map
Arpad Benyi, Ioan Casu
https://arxiv.org/abs/2510.12558 https://arxiv.org/pdf/2510.12558

An elementary derivation of 3-cycles for a quadratic map
We present an elementary derivation of the period-three cycles for the real quadratic map $x\mapsto x^2+c$, a fundamental model in one-dimensional discrete dynamics. Using symmetric polynomials, we obtain a complete algebraic characterization of 3-cycles and determine explicit conditions for their existence and stability, without reliance on computer algebra. Through conjugacy with the logistic map, we recover the classical threshold values of the logistic parameter corresponding to the emergen…

Adjoint ferromagnets
Joaqu\'in L\'opez-Su\'arez, Alexios P. Polychronakos, Konstantinos Sfetsos
https://arxiv.org/abs/2510.11776 https://arxiv.…

Adjoint ferromagnets
We derive the phase structure and thermodynamics of ferromagnets consisting of elementary magnets carrying the adjoint representation of $SU(N)$ and coupled through two-body quadratic interactions. Such systems have a continuous $SU(N)$ symmetry as well as a discrete conjugation symmetry. We uncover a rich spectrum of phases and transitions, involving a paramagnetic and two distinct ferromagnetic phases that can coexist as stable and metastable states in different combinations over a range of t…

Mit dem neuen #Solarthermiepark Au setzt #Tübingen ein starkes Zeichen für die #Wärmewende.
Auf 23.200 Quadratmetern erzeugt die Anlage jährlich rund 6 Millionen kWh

Sonne ab sofort Partnerin der Tübinger Wärmewende: Stadtwerke weihen Solarthermie-Park Au ein
Drittgrößte Anlage Deutschlands auf 23.000 Quadratmetern | Die Stadtwerke Tübingen (swt) haben jetzt eine der denkbar energiegeladensten Partnerinnen an ihrer Seite: Die Sonne. Sie sorgt ab sofort jährlich für sechs Millionen Kilowattstunden klimafreundliche Fernwärme. Die erzeugte Wärme kann viele Haushalte versorgen, die an das Fernwärmenetz angeschlossen sind. Die erste Solarthermie-Freiflächenanlage der swt ist gleichzeitig ein wichtiger Baustein für die Fernwärmetransformat…

A Martingale Kernel Two-Sample Test
Anirban Chatterjee, Aaditya Ramdas
https://arxiv.org/abs/2510.11853 https://arxiv.org/pdf/2510.11853

A Martingale Kernel Two-Sample Test
The Maximum Mean Discrepancy (MMD) is a widely used multivariate distance metric for two-sample testing. The standard MMD test statistic has an intractable null distribution typically requiring costly resampling or permutation approaches for calibration. In this work we leverage a martingale interpretation of the estimated squared MMD to propose martingale MMD (mMMD), a quadratic-time statistic which has a limiting standard Gaussian distribution under the null. Moreover we show that the test is…

On the Speed-up of Wave-like Dark Matter Searches with Entangled Qubits
Arushi Bodas, Sohitri Ghosh, Roni Harnik
https://arxiv.org/abs/2510.11795 https://a…

On the Speed-up of Wave-like Dark Matter Searches with Entangled Qubits
Qubit-based sensing platforms offer promising new directions for wave-like dark matter searches. Recent proposals demonstrate that entangled qubits can achieve quadratic scaling of the signal in the number of qubits. In this work we expand on these proposals to analyze the bandwidth and scan rate performance of entangled qubit protocols across different error regimes. We find that the phase-based readout of entangled protocols preserves the search bandwidth independent of qubit number, in contr…

Replaced article(s) found for cs.AI. https://arxiv.org/list/cs.AI/new
[3/9]:
- Kernel-Free Universum Quadratic Surface Twin Support Vector Machines for Imbalanced Data
Hossein Moosaei, Milan Hlad\'ik, Ahmad Mousavi, Zheming Gao, Haojie Fu

Monte Carlo quasi-interpolation of spherical data
Zhengjie Sun, Mengyuan Lv, Xingping Sun
https://arxiv.org/abs/2510.12027 https://arxiv.org/pdf/2510.12027…

Monte Carlo quasi-interpolation of spherical data
We establish a deterministic and stochastic spherical quasi-interpolation framework featuring scaled zonal kernels derived from radial basis functions on the ambient Euclidean space. The method incorporates both quasi-Monte Carlo and Monte Carlo quadrature rules to construct easily computable quasi-interpolants, which provide efficient approximation to Sobolev-space functions for both clean and noisy data. To enhance the approximation power and robustness of our quasi-interpolants, we develop a…

A Class of Functionals on the Sequence Space $s$ Satisfying the Palais-Smale Condition
Kaveh Eftekharinasab
https://arxiv.org/abs/2510.10146 https://arxiv.…

A Class of Functionals on the Sequence Space $s$ Satisfying the Palais-Smale Condition
We introduce a class of functionals on the space of rapidly decreasing sequences $s$, called $\mathcal{F}_s$-functionals, defined as decomposable sums of quadratic and convex terms with quadratic growth. We prove that such functionals satisfy the Palais-Smale condition and admit a unique global minimum. Furthermore, we show that the Palais-Smale condition is preserved under linear homeomorphisms. This allows us to construct corresponding functionals satisfying the Palais-Smale condition on Fré…

from my link log —
Two workers are quadratically better than one: modelling a queue with PRISM.
https://www.hillelwayne.com/post/queueing-prism/
saved 2020-11-02

FragmentRetro: A Quadratic Retrosynthetic Method Based on Fragmentation Algorithms
Yu Shee, Anthony M. Smaldone, Anton Morgunov, Gregory W. Kyro, Victor S. Batista
https://arxiv.org/abs/2509.15409

FragmentRetro: A Quadratic Retrosynthetic Method Based on Fragmentation Algorithms
Retrosynthesis, the process of deconstructing a target molecule into simpler precursors, is crucial for computer-aided synthesis planning (CASP). Widely adopted tree-search methods often suffer from exponential computational complexity. In this work, we introduce FragmentRetro, a novel retrosynthetic method that leverages fragmentation algorithms, specifically BRICS and r-BRICS, combined with stock-aware exploration and pattern fingerprint screening to achieve quadratic complexity. FragmentRetr…