Lorentz Center

McGibbon et al., (2025). SOAP: A Python Package for Calculating the Properties of Galaxies and Halos Formed in Cosmological Simulations. Journal of Open Source Software, 10(111), 8252, https://doi.org/10.21105/joss.08252

One of the main challenges in the study of time-varying networks is the interplay of memory effects with structural heterogeneity. In particular, different nodes and dyads can have very different statistical properties in terms of both link formation and link persistence, leading to a superposition of typical timescales, suboptimal parametrizations, and substantial estimation biases. Here we develop an unbiased maximum-entropy framework to study empirical network trajectories by controlling for the observed structural heterogeneity and local link persistence simultaneously. An exact mapping to a heterogeneous version of the one-dimensional Ising model leads to an analytic solution that rigorously disentangles the hidden variables that jointly determine both static and temporal properties. Additionally, model selection via likelihood maximization identifies the most parsimonious structural level (either global, node specific, or dyadic) accounting for memory effects. As we illustrate on real-world social networks, this method enables an improved estimation of dyadic transition probabilities, relaxation times, and structural breaks between dynamical regimes. In the resulting picture, the graph follows a generalized configuration model with given degrees and given time-persisting degrees, undergoing transitions between empirically identifiable stationary regimes. Published by the American Physical Society 2024

Temporal networks present a unique challenge regarding the community discovery task. The inherent dynamism of these systems requires an intricate understanding of memory effects and structural heterogeneity, which are often key drivers of network evolution. This study focuses on Markovian temporal networks and addresses these challenges with an innovative community detection method that introduces a modularity function. We specifically demonstrate how our approach enhances the detectability threshold, thereby improving the effectiveness of community detection in such a dynamic setting. We show that by associating memory directly with nodes' memberships and including it into the modularity expression, we can enhance the detectability threshold compared to scenarios where memory is ignored, thus extending the conditions under which communities can be accurately identified. We validate our approach through extensive numerical simulations, confirming its efficacy in a controlled environment. Additionally, by applying our method to real-world data, we not only demonstrate its practicality and robustness but also reveal its capacity to indirectly tackle additional challenges, such as determining the optimal time window for aggregating data in dynamic graphs. Published by the American Physical Society 2024

We have calculated an entropy or information measure of previously reported experimentally determined temporal dominance of sensations (TDS) data of texture attributes for two sets of emulsion filled gels throughout the mastication cycle. The samples were emulsion filled gels and two-layered emulsion filled gels. We find that the entropy measure follows an average curve, which is different for each set. The specifics of the entropy curve may serve as a fingerprint for the perception of a specific food sample.

A statistical theory is presented of the magnesium ion interacting with lysozyme under conditions where the latter is positively charged. Temporarily assuming magnesium is not noncovalently bound to the protein, I solve the nonlinear Poisson–Boltzmann equation accurately and uniformly in a perturbative fashion. The resulting expression for the effective charge, which is larger than nominal owing to overshooting, is subtle and cannot be asymptotically expanded at high ionic strengths that are practical. An adhesive potential taken from earlier work together with the assumption of possibly bound magnesium is then fitted to be in accord with measurements of the second virial coefficient by Tessier et al. The resulting numbers of bound magnesium ions as a function of MgBr_2 concentration are entirely reasonable compared with densitometry measurements.

We extend the cosmological bootstrap to correlators involving massless particles with spin.In de Sitter space, these correlators are constrained both by symmetries and by locality.In particular, the de Sitter isometries become conformal symmetries on the future boundary of the spacetime, which are reflected in a set of Ward identities that the boundary correlators must satisfy.We solve these Ward identities by acting with weight-shifting operators on scalar seed solutions.Using this weight-shifting approach, we derive three-and four-point correlators of massless spin-1 and spin-2 fields with conformally coupled scalars.Four-point functions arising from tree-level exchange are singular in particular kinematic configurations, and the coefficients of these singularities satisfy certain factorization properties.We show that in many cases these factorization limits fix the structure of the correlators uniquely, without having to solve the conformal Ward identities.The additional constraint of locality for massless spinning particles manifests itself as current conservation on the boundary.We find that the four-point functions only satisfy current conservation if the s, t, and u-channels are related to each other, leading to nontrivial constraints on the couplings between the conserved currents and other operators in the theory.For spin-1 currents this implies charge conservation, while for spin-2 currents we recover the equivalence principle from a purely boundary perspective.For multiple spin-1 fields, we recover the structure of Yang-Mills theory.Finally, we apply our methods to slow-roll inflation and derive a few phenomenologically relevant scalar-tensor three-point functions.

Mott insulators form because of strong electron repulsions, being at the heart of strongly correlated electron physics. Conventionally these are understood as classical "traffic jams" of electrons described by a short-ranged entangled product ground state. Exploiting the holographic duality, which maps the physics of densely entangled matter onto gravitational black hole physics, we show how Mott-insulators can be constructed departing from entangled non-Fermi liquid metallic states, such as the strange metals found in cuprate superconductors. These "entangled Mott insulators" have traits in common with the "classical" Mott insulators, such as the formation of Mott gap in the optical conductivity, super-exchange-like interactions, and form "stripes" when doped. They also exhibit new properties: the ordering wave vectors are detached from the number of electrons in the unit cell, and the DC resistivity diverges algebraically instead of exponentially as function of temperature. These results may shed light on the mysterious ordering phenomena observed in underdoped cuprates.

We start with a short introduction of the role that constraints and Lagrange multiplers play in variational calculus. After recalling briefly the properties of the nonlinear sigma model, we show how the Hamilton–Jacobi method can be applied to find its solutions. We discuss the importance of the Hamiltonian constraint in the standard cosmological model, and finally, apply the Hamilton–Jacobi method to the solution of coupled gravitational and sigma-field equations.