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Andreu Ballus Santacana

Publications and source records attributed to Andreu Ballus Santacana.

6 recordsLinked to original sources

Proof-Carrying Analytic Approximation: Local-to-Global Evidence Transport at Encoding Cost

Under quasi-uniform refinement, bounded local-encoding hypotheses, and local $W^{r,2}$ approximation of order $r\ge 2$ in a rational piecewise-polynomial presentation of $W^{1,2}(0,1)$, carrying the complete proof genealogy up to the level required by an accuracy $\varepsilon$ costs the same asymptotic bit order as the finest-level conventional coefficient encoding. If $B_n=Θ(M_nβ_n)$ denotes that level-$n$ encoding size, our compiler transports supplied local approximation and overlap witnesses through exact partition-of-unity synthesis and geometric refinement to a represented limit with total certificate size $O(B_{m(\varepsilon)})$, where $m(\varepsilon)=O(\log(1/\varepsilon)/(r-1))$. The construction makes no oracle query to an independently supplied semantic target name ($Q_{\rm target}=0$). When $β_n=O(n+1)$, this becomes $O(\varepsilon^{-1/(r-1)}(1+\log(1/\varepsilon)))$. The surrounding framework is intentionally separated from this resource theorem. Every real computable Banach presentation admits a uniformly computable linear isometric embedding into standard computable $C([0,1])$, with computable inverse on its represented range. Complete metric evidence with rational strict slack collapses extensionally to the represented analytic metric once effective names are available, while chosen evidence transformations retain construction history and resource information. For the Lipschitz grammar used here, qualitative evidence-local lifting is canonical; the nontrivial question is therefore which evidence is retained and at what cost.

math.FA↗

The Syncytial Mesh Model: A Mesoscale Control-Field Framework for Scale-Dependent Coherence in the Brain

The Syncytial Mesh Model introduces a three-layered framework for large-scale brain dynamics integrating local neural circuitry, macrostructural connectivity, and a slow mesoscale control-field substrate associated with astrocytic syncytial organization. Rather than directly generating electrophysiological activity, the proposed syncytial layer modulates neuronal excitability, coherence structure, and metastable coordination across spatial scales. The framework is formulated as a phenomenological effective theory combining neural-mass dynamics, connectome-scale coupling, and continuous-field interactions. Within this architecture, the model provides a candidate explanation for large-scale traveling-wave organization, low-frequency coherence structure, and distributed plasticity phenomena that are not straightforwardly reducible to direct local synaptic connectivity alone. Numerical simulations of the effective field dynamics generate stable traveling-wave propagation, smooth phase-gradient organization, and low-frequency modal structure qualitatively resembling experimentally reported infra-slow and delta/theta coordination patterns. An analytic mesoscale coherence model further illustrates how scale-dependent synchronization probabilities may emerge from slow-field modulation and damping dynamics without requiring globally phase-locked neuronal oscillations.

q-bio.NC↗

The Dimension-Shift Category and Its Mellin-Gamma Representation

We define a thin category $\mathrm{Dim}^+$ of dimension shifts and a category $\mathrm{RadMeas}$ of positive Radon measures with Radon--Nikodym density morphisms. We classify scaling-covariant functors $\mathrm{Dim}^+\to\mathrm{RadMeas}$ whose morphisms are given by homogeneous densities. Gaussian normalization selects a unique functor with values $ dμ_x(u)=\frac{π^{x/2}}{Γ(x/2)}u^{x/2-1}\,du. $ Its morphism component yields the radial-integration transport $ R(x,r)=\frac{π^rΓ(x/2)}{Γ(x/2+r)}, $ while the unit-interval observable recovers the Euclidean ball-volume formula $ V(x)=\frac{π^{x/2}}{Γ(x/2+1)}. $ The two transports differ by the multiplicative coboundary of $β(x)=x$, identified with the categorical dimension of the standard object in Deligne's interpolation category $\mathrm{Rep}(O_t)$.

math.RT↗

Radial Integration in Continuous Dimension: A Mellin-Gamma Classification of Euclidean Ball Volume

We classify positive linear functionals on $C_c(\mathbb{R}_{>0})$ satisfying scaling covariance of degree $x/2$ and Gaussian normalization to $π^{x/2}$. We prove that the unique such functionals are represented by the Mellin--Gamma measures \[ dμ_x(u) = \frac{π^{x/2}}{Γ(x/2)}\, u^{x/2 - 1}\, du, \quad x > 0. \] The result is a rigidity statement: the Mellin--Gamma structure is forced by the axioms, without assuming analytic continuation, special functions, or a priori formulas. The proof reduces the scaling condition, via a logarithmic change of variables, to translation invariance on $\mathbb{R}$, where Haar measure uniqueness determines the measure up to normalization, which is fixed by the Gaussian integral. As a consequence, the Euclidean ball volume formula \[ V(x) = \frac{π^{x/2}}{Γ(x/2 + 1)} \] is recovered as the mass of the unit interval. We further analyze the induced dimension-shift structure, identifying two multiplicative cocycles whose ratio is a coboundary given by the dimension function $x$, and give an independent characterization via a shifted Bohr--Mollerup theorem.

math.CA↗

From Copying to Corelations via Ancestry Partitions

We study the free PROP $\mathrm{Syn}(δ)$ on a single binary generator $δ:1\to 2$. The ancestry functor $Π:\mathrm{Syn}(δ)\to \mathrm{FinCorel}$, defined by connected components of the underlying undirected string diagram, has image the sub-PROP $\mathrm{FinCorel}^{\circ}$ of finite corelations whose equivalence classes contain exactly one input and at least one output. The induced quotient [ \mathrm{AncQ}:=\mathrm{Syn}(δ)/\ker(Π) ] is equivalent as a PROP to $\mathrm{Cocom}$, the PROP for non-counital cocommutative comonoids. We then locate this primitive construction inside the standard cospan/corelation framework: $\mathrm{Cospan}(\mathcal B)$ realizes pushout-style gluing as a free hypergraph category; $\mathrm{Cospan}(\mathrm{FinSet})$ collapses under jointly epic corestriction to $\mathrm{FinCorel}$, the PROP for extraspecial commutative Frobenius monoids; and the Yoneda envelope [ \mathcal W=\mathrm{Fun}(\mathrm{FinCorel}^{op},\mathrm{Spc}) ] is a presheaf $\infty$-topos carrying the standard subobject, modality, and monotone fixed-point apparatus. The PROP-level identification $\mathrm{AncQ}\simeq \mathrm{Cocom}$ is the only result claimed as new; the remaining material is organizational and reduces explicitly to cited classical results.

math.CT↗

An Incremental Framework for Topological Dialogue Semantics: Efficient Reasoning in Discrete Spaces

We present a tractable, incremental framework for topological dialogue semantics based on finite, discrete semantic spaces. Building on the intuition that utterances correspond to open sets and their combinatorial relations form a simplicial complex (the dialogue nerve), we give a rigorous foundation, a provably correct incremental algorithm for nerve updates, and a reference implementation in the Wolfram Language. The framework supports negative nerve computation (inconsistency tracking), consequence extraction, and a transparent, set-theoretic ranking of entailments. We clarify which combinatorial properties hold in the discrete case, provide motivating examples, and outline limitations and prospects for richer logical and categorical extensions.

cs.LO↗