arXiv subjects

Batia Friedman-Shaw

Publications and source records attributed to Batia Friedman-Shaw.

4 recordsLinked to original sources

arXiv2026

Dark Energy Bubble as Dynamical Dark Energy: Properties and CMB Constraints

Recent DESI results are in tension with the constant dark energy density predicted by the $\Lambda$CDM model. If dark energy is associated with the vacuum energy of a scalar field in a metastable state, it will undergo a first-order phase transition through the nucleation of bubbles containing a reduced dark energy density. In this paper, we explore the consequences of this model, where dark energy density varies in both space and time. We model a single bubble spacetime using the Israel junction conditions and derive each of the usual distance measures in this inhomogeneous cosmology. We find that the model predictions of Alcock-Paczynski distortion have features that align strikingly well with the DESI measurements if the dark energy phase transition occurred at roughly a redshift of 1.4 and if the bubble of lower dark energy density has roughly 10$\%$ less dark energy density than the outer cosmology. Despite this feature, we find that the dark energy bubble is heavily constrained by the CMB which excludes the region of parameter space that reproduces the DESI BAO measurements. Still, the peculiar features in the distance measurements of the dark energy bubble cosmology serve as a useful toy model to motivate and inform future work in the currently poorly explored area of spatially varying dynamical dark energy.

astro-ph.CO↗

arXiv2025

Holographic scattering and non-minimal RT surfaces

In the AdS/CFT correspondence, the causal structure of the bulk AdS spacetime is tied to entanglement in the dual CFT. This relationship is captured by the connected wedge theorem, which states that a bulk scattering process implies the existence of $O(1/G_N)$ entanglement between associated boundary subregions. In this paper, we study the connected wedge theorem in two asymptotically AdS$_{2+1}$ spacetimes: the conical defect and BTZ black hole geometries. In these settings, we find that bulk scattering processes require not just large entanglement, but also additional restrictions related to candidate RT surfaces which are non-minimal. We argue these extra relationships imply a certain CFT entanglement structure involving internal degrees of freedom. Because bulk scattering relies on sub-AdS scale physics, this supports the idea that sub-AdS scale locality emerges from internal degrees of freedom. While the new restriction that we identify on non-minimal surfaces is stronger than the initial statement of the connected wedge theorem, we find that it is necessary but still not sufficient to imply bulk scattering in mixed states.

hep-th↗

arXiv2025

Doppler bias: impact of peculiar velocities on color selection and the large scale structure of galaxy surveys

Lightcone selection effects on cosmic observables must be precisely accounted for in the next generation of surveys, including the Dark Energy Spectroscopic Instrument (DESI) survey. This will allow us to correctly model the data and extract subtle shifts from general-relativistic effects. We examine the effects of peculiar velocities on color selection in spectroscopic galaxy surveys, with a focus on their implications for the galaxy clustering dipole $P_1(k)$. Using DESI Emission Line Galaxy (ELG) targets, we show that peculiar velocities can shift spectral emission features into or out of filter bands, modifying galaxy colors and thereby changing galaxy selection. This phenomenon mimics the effect of evolution bias, and we refer to it as the Doppler bias, $b_D$. The Doppler bias is of comparable size to the evolution bias at $0.8 < z < 1$, where it is largest. This enhances the ELG-LRG (Luminous Red Galaxy) cross-correlation dipole by 25-50%. This could be detectable at the $\sim$6$σ$ level for the full DESI survey. Additionally, we found that our $b_D$ estimate is impacted by the incompleteness of the parent ELG sample. Therefore, this work highlights the essential need for careful consideration of spectral-dependent biases caused by peculiar velocities during the selection phase of galaxy surveys, to enable unbiased analyses.

astro-ph.CO↗

arXiv2021

The Physics of Machine Learning: An Intuitive Introduction for the Physical Scientist

This article is intended for physical scientists who wish to gain deeper insights into machine learning algorithms which we present via the domain they know best, physics. We begin with a review of two energy-based machine learning algorithms, Hopfield networks and Boltzmann machines, and their connection to the Ising model. This serves as a foundation to understand the phenomenon of learning more generally. Equipped with this intuition we then delve into additional, more "practical," machine learning architectures including feedforward neural networks, convolutional neural networks, and autoencoders. We also provide code that explicitly demonstrates training a neural network with gradient descent.

cond-mat.dis-nn↗