On August 27, 2024, scholars, trustees, and friends of UConn gathered at the University of Connecticut School of Law to honor members of the university community elected to the National Academies of Sciences, Engineering, and Medicine. Established by an Act of Congress in 1863, the National Academy of Sciences was followed by the National Academy […]
Dear Friends of UConn Physics, Last year, I wrote to you as a new Interim Head of Physics and only barely a month into my appointment. During the past year, we conducted a search for a permanent head and I was selected. For this, I am very grateful for the trust and support I received […]
Every year, the American Physical Society (APS) sponsors CU*IP – Conference for Undergraduate Women and Gender Minorities in Physics – at several locations around the country. This year, led by Prof. Nora Berrah, UConn Physics applied to host this national conference in Storrs and our proposal was accepted for January 24-26, 2025! The purpose of […]
Lawrence “Larry” Kappers, passed away on Friday, August 2, 2024. Professor Lawrence (Larry) Kappers (aka “Kap”) retired in 2009, having joined the UConn Physics Department in 1973. After receiving his Ph.D. from the University of Missouri-Columbia and completing postdoctoral appointments at the University of Minnesota and Oklahoma State University, he developed an active research program […]
The UConn STARs group visited Hartford Public High School (HPHS) to teach physics for a total of eight class periods from May 6th-9th, 2024. UConn brought 16 undergraduate students from the STARs program to HPHS for our annual outreach program, during which we interacted with about 100 high school students. We collaborated with physics teacher […]
Prof. Cara Battersby, Department of Physics, University of Connecticut
The Milky Way Laboratory
Galaxy centers are the hubs of activity that drive galaxy evolution, from supermassive black holes to feedback from dense stellar clusters. While the bulk of our Milky Way Galaxy is a prime example of present epoch “normal” star formation, our galaxy’s center has gas properties that are more reminiscent of star formation during its cosmic peak. In our research group, the Milky Way Laboratory, we capitalize on both the “normal” and “extreme” star formation in our own cosmic backyard in order to resolve the interplay of physical processes in detail. In this talk, I will discuss efforts to measure how stars gain their mass and how the star formation process may vary across the Galaxy. In our galaxy’s central molecular zone, the process of star formation is complicated by constant gas inflow, high levels of turbulence, and more. I will present both simulations and observations toward this region that aim to understand the role of the gas inflow, the 3-D geometry of the region, properties of the gas, and incipient star formation.
Unveiling the Physics of Galaxy Formation and its Large-Scale Effects at Cosmic Dawn
Cosmic Dawn, loosely defined here to be the first billion years of cosmic time, is an ever-intriguing era that witnessed the formation of the first generations of galaxies. Toward the end of it there was also the last major phase transition of our Universe, the epoch of reionization (EoR), which is believed to be driven by the hydrogen-ionizing background emerged from the early galaxies formed. In this talk, I will explain how Cosmic Dawn becomes a real exciting epoch for unveiling the physics of galaxy formation thanks to the James Webb Space Telescope (JWST), as well as several forthcoming facilities such as SPHEREx, Roman Space Telescope, Square Kilometer Array, and LiteBIRD focusing on the large-scale effects. I will discuss the theoretical landscape galaxy formation at Cosmic Dawn informed by new JWST observations, with a particular focus on the phenomenon of bursty star formation. I will introduce methods and ideas to shed light on different aspects of early galaxy formation, including the star formation history, stellar feedback, outflows, and the ionizing output, using both individual galaxies and their effects on the large-scale structure and cosmic background radiations. With a few case studies, I will demonstrate how to harness the power of the aforementioned facilities and their synergies for these purposes.
Everyone is welcome to attend (undergraduate and graduate students, staff, and faculty at the physics department). This big event is part of our efforts to foster a welcoming work environment and solidify our physics community.
Prof. Mingda Li, Nuclear Science and Engineering, MIT
Exploring Potential Roles of Machine Learning in Quantum Materials Research
In recent years, machine learning has achieved great success in chemistry and materials science, but quantum materials face unique challenges. These include the scarcity of data (volume challenge), high dimensionality and computational costs (complexity challenge), elusive experimental signatures (experimental challenge), and unreliable ground truth (validation challenge).
In this Physics Colloquium, we present our recent efforts to support the study of quantum materials with machine learning. For scenarios with high data volumes, such as density-functional-theory (DFT) level studies with weak correlation, machine learning can predict lower-dimensional properties. We introduce a convolutional neural network classifier predicting band topology class based on X-ray absorption (XAS) signals [1]. This approach can also be applied to experimental data, demonstrated by an autoencoder-based protocol to study the magnetic proximity effect with polarized neutron reflectometry, improving fitting resolution [2].
For lower data volumes due to higher computational costs, incorporating symmetry into neural networks can reduce data volume needs. Using the O(3) Euclidean neural network, we predict phonon density-of-states [3], dielectric functions [4], and quantum weight [5] directly from crystal structures. Machine learning without data can also be performed by using differential equations as constraints [5].
For high output dimensions and low input data volumes, such as phonon dispersion relations, we introduce additional approaches like virtual nodes in a graph neural network [6], showing improved efficiency compared to machine-learning potential without losing accuracy.
To address unreliable ground truth, we use machine learning to distinguish Majorana zero modes in scanning tunneling spectroscopy for topological quantum computation [7]. For cases like quantum spin liquids, where experimental signatures are unclear and computational costs are high, we generate materials with potential geometrical frustration. Our latest work, SCIGEN, produces eight million materials belonging to Archimedean lattices, with over 50% passing DFT stability checks after pre-screening [8].
Despite progress, applying machine learning to quantum materials is still in its infancy. We reflect on the out-of-distribution problem, aiming to generate genuine surprises and new features rather than merely recognizing patterns. Additionally, we must address accuracy limitations in many machine learning approaches, especially with complex quantum systems and phase diagram studies.
Prof. Carlos Trallero, Department of Physics, University of Connecticut
Quantum times
The uncertainty principle for a free electron provides one of the most fundamental time scales known as the Coulomb time scale, that ranges from 3 to 8 zeptoseconds (10-21s). I will discuss about experimental developments in our lab with this temporal resolution and it’s application to fundamental measurements as well as applied research.
We discuss the anharmonic oscillator in quantum mechanics using exact WKB methods in a ‘t Hooft-like double scaling limit where classical behavior is expected to dominate. We compute the tunneling action in this double scaling limit, and compare it to the transition amplitude from the vacuum to a highly excited state. Our results, exact in the semiclassical limit, show that the two expressions coincide, apart from an irreducible and surprising instanton contribution. The semiclassical limit of the anharmonic oscillator betrays its quantum origin as a rule showing that the quantum theory is intrinsically gapped from classical behavior. Besides an example of a resurgent connection between perturbative and nonperturbative physics, this may provide a way to study transition amplitudes from tunnelling actions, and vice versa.
Graduate student Debadarshini Mishra, Department of Physics, University of Connecticut
Photo-Induced Ultrafast Dynamics in Molecules
Imaging electronic and molecular dynamics at ultrafast timescales is crucial for understanding the mechanisms of chemical reactions, which are of fundamental importance in fields ranging from materials science to biochemistry. Furthermore, gaining insights into these processes at the atomic and molecular levels can enable precise control over reaction dynamics, leading to significant technological advancements through the development of efficient catalysts, innovative materials, and targeted drugs. In this dissertation talk, I will present my work on imaging time-resolved dynamics in molecular systems, using various light sources and ultrafast spectroscopy techniques. First, I will discuss a method for the direct visualization of neutral fragments in roaming reactions, which involve an unconventional dissociation process, using coincident Coulomb explosion imaging. Next, I will explore ultrafast electron diffraction as a different yet complementary imaging technique to identify the competing non-radiative relaxation pathways for a UV-excited molecule. Finally, I will briefly discuss our recent work on relaxation and fragmentation dynamics in large molecules, particularly C60, and isomerization and excited-state dynamics in small molecules.
Astrophysical observations give overwhelming evidence for the existence of dark matter. Several theoretical particles have been proposed as dark matter candidates, including weakly interacting massive particles (WIMPs), axions, and, more recently, their much lighter counterparts. However, there has yet to be a definitive detection of dark matter. For years, one group, the DAMA collaboration, has asserted that they observe a dark matter-induced annual modulation signal in their NaI(Tl)-based detectors. Their observations are inconsistent with those from other direct detection dark matter experiments under most assumptions of dark matter. In this talk, I will describe how I came to work on this topic and the debate’s current status, the worldwide experimental effort to test this extraordinary claim, and our progress toward resolving the current stalemate in the field.
Note: The pre-colloquium reception will be 3-4pm in the Gant Light Court
Graduate student Mitchell Bredice, Department of Physics, University of Connecticut
Kinetics, Nucleation, and Relaxation Dynamics of Ion-Seeded Nanoparticles
The recent interest in studying the adsorption and emission spectra of the hazy atmospheres of exoplanets stimulates the interest in clusters, small aggregates of atoms or molecules. The nucleation and dynamics of nanoparticles in the Earth’s atmosphere and their impact on the global climate and environment is another important area of research stimulating investigations of nucleation processes. However, how these small aggregates form is not wholly understood. Traditionally, nucleation of clusters or other phases is described through Classical Nucleation Theory. Although this theory has many discrepancies in describing the nucleation of submicron particles. In this work, we have performed molecular dynamics simulations of the nucleation of ion-seeded nanoparticles, specifically ArnH+ clusters, to investigate the microscopic mechanisms of nucleation from a gas or liquid phase. From these simulations, we have studied the stages of the nonequilibrium and equilibrium growth of ArnH+ clusters and analyzed the size distribution and internal energy relaxation of nascent clusters during different stages of their growth. The fundamental impact of the internal energy relaxation on the nonequilibrium nucleation of small ArnH+ clusters has been demonstrated. This analysis has generally been avoided in previous investigations due to assumptions of the equilibrium nature of the nucleation process. The results of our simulations showed that nanoparticles are formed in highly excited states, thus the cluster growth and relaxation are concurrent processes, and that relaxation of the cluster internal energy can delay cluster growth processes. To further investigate the internal energy relaxation, an ensemble of molecular dynamics simulations was performed for the detailed analysis of the average time evolution of kinetic, potential, and total energies of small ArnH+ clusters, and their kinetic energy relaxation. The results of the performed simulations have been explained through the use of a collisional Boltzmann equation describing the energy relaxation processes. Lastly, the general relationship between nonequilibrium growth and internal energy relaxation is discussed.