Electron field emission is a complicated phenomenon which is sensitive not only to the particular material under illumination but also to the specific crystalline orientation of the surface. Summarizing the ability for a crystal to emit in a particular direction would be of great use when searching for good field emitters. In this paper we propose a material normal energy distribution which describes the ability of the bound electrons to tunnel under an intense electric field.

A solid object's geometry, density, and elastic moduli completely determine its spectrum of normal modes. Solving the inverse problem - determining a material's elastic moduli given a set of resonance frequencies and sample geometry - relies on the ability to compute resonance spectra accurately and efficiently. Established methods for calculating these spectra are either fast but limited to simple geometries, or are applicable to arbitrarily shaped samples at the cost of being prohibitively slow.

Gaining recognition from peers has been shown to improve student persistence and career intentions in physics. It is important, therefore, to understand how students develop perceptions of their peers. Prior research suggests that interactions are one possible mechanism for peer recognition: interacting with others allows students to demonstrate their physics skills and knowledge and acquire recognition as a physicist. To probe this explanation directly, we use methods from social network analysis to compare students' self-reported interactions to their recognition of strong peers.

Researchers have pinpointed recognition from others as one of the most important dimensions of students' science and engineering identity. Studies, however, have found gender biases in students' recognition of their peers, with inconsistent patterns across introductory science and engineering courses. Toward finding the source of this variation, we examine whether a gender bias exists in students' nominations of strong peers across three different remote, introductory physics courses with varying student populations (varying demographics, majors, and course levels).

While insects such as Drosophila are flying, aerodynamic instabilities require that they make millisecond time scale adjustments to their wing motion to stay aloft and on course. These stabilization reflexes can be modeled as a proportional-integral (PI) controller; however, it is unclear how such control might be instantiated in insects at the level of muscles and neurons.

We explore matrix product state approximations to wave functions which have spontaneously broken symmetries or are critical. We are motivated by the fact that symmetries, and their associated conservation laws, lead to block-sparse matrix product states. Numerical calculations which take advantage of these symmetries run faster and require less memory. However, in symmetry-broken and critical phases the block-sparse ansatz yields less accurate energies. We characterize the role of conservation laws in matrix product states and determine when it is beneficial to make use of them.

Engaging in interactions with peers is important for student learning. Many studies have quantified patterns of student interactions in in-person physics courses using social network analysis, finding different network structures between instructional contexts (lecture and laboratory) and styles (active and traditional). Such studies also find inconsistent results as to whether and how student-level variables (e.g., grades and demographics) relate to the formation of interaction networks.