Dr. Maxim Pospelov, University of Minnesota

Dark Matter snooker

Despite enormous experimental investment in searches of particle dark matter, certain well-motivated corners of parameter space remain to be elusive “blind spots” for direct detection. In my talk I will address two of such exceptions: light particles that simply do not have enough kinetic energy to detect, and strongly-interacting particles that quickly thermalize and also become sub-threshold for direct detection. I show that both blind spots can be probed through double collisions of Dark matter – first with some energetic Standard model particles (solar electrons, cosmic rays, particles in a beam, neutrons in nuclear reactors etc) that bring DM to energies above thresholds followed by the scattering inside a detector. This way, I derive novel constraints on light dark matter, as well as strongly-interacting dark matter models, using existing dark matter and neutrino experiments. 

Prof. Dr. Ralf S. Klessen, Universität Heidelberg

The First Stars: Formation, Properties, and Impact

The first generation of stars, often called Population III (or Pop III), form from metal-free primordial gas at redshifts z ~ 30 and below. They dominate the cosmic star formation history until z ~ 20-15, at which point the formation of metal-enriched Pop II stars takes over. I review current theoretical models for the formation, properties and impact of Pop III stars, and discuss observational constraints. I argue that primordial gas is highly susceptible to fragmentation and Pop III stars form as members of small clusters with a logarithmically flat mass function. Feedback from massive Pop III stars plays a central role in regulating subsequent star formation, but major uncertainties remain regarding its immediate impact. Direct observations of Pop III stars in the early Universe remain extremely challenging, whereas stellar archeological surveys allow us to constrain both the low-mass and the high-mass ends of the Pop III mass distribution. Observations suggest that most massive Pop III stars end their lives as core-collapse supernovae rather than as pair-instability supernovae. I also speculate about the formation of supermassive stars, which under very specific circumstances can get as massive as several 100.000 solar masses and can become the seeds of the supermassive black holes observed in the high-redshift universe.

Dr. Jesus Perez Rios, Department of Physics and Astronomy, Stony Brook University

The three-body problem in chemical physics

The three-body problem, such as three bodies interacting through gravity, is paramount in fundamental and mathematical physics. It is well-known that it has no closed solution, and the dynamics is chaotic. The equivalent problem in chemical physics is a termolecular reaction (or third-order reaction) in which three bodies (chemicals) collide, yielding a bound state between two bodies while the third one gets the excess kinetic energy. Termolecular reactions are essential to many chemical and physical systems, from ultracold atoms, determining the system’s stability, to plasma physics, explaining the recombination dynamics. In this talk, we will present our methodology for treating termolecular reactions and its application to several intriguing scenarios: cold chemistry, atmospheric physics, and geochemistry. Within cold chemistry, we will present the current understanding of ion-atom-atom recombination reactions essential to understanding the stability of cold ions in ion-atom hybrid traps. On the atmospheric physics front, we will present our results on the ozone formation reaction, one of the most relevant reactions in atmospheric physics. Regarding geochemistry, we will discuss our latest results on the sulfur cycle reactions essential to understanding the great oxygenation event, that moment in the history of our planet when the living organism transitioned from anaerobic to aerobic. Finally, we will present some of our efforts toward the theoretical understanding of cluster physics, solvation chemistry, and nucleation dynamics.

Prof. Ronald Garcia Ruiz, MIT

Radioactive Molecules are Dying to Reveal New Physics

Rapid progress in the experimental control and interrogation of molecules is enabling new opportunities for investigating the fundamental laws of our universe. In particular, molecules containing heavy, octupole-deformed nuclei, such as radium, offer enhanced sensitivity for measuring yet-to-be-discovered parity and time-reversal violating nuclear properties. In this colloquium, I will present recent highlights and perspectives from laser spectroscopy experiments on these species, as well as discuss the relevance of these experiments in addressing open problems in nuclear and particle physics.

Dr. Dima Kharzeev, Stony Brook University and Brookhaven National Laboratory

When Physics meets Quantum information

The interplay between physics and quantum information drives profound advancements in our understanding of nature, reshaping fundamental concepts and enabling groundbreaking technologies. In this colloquium, we will explore how quantum information and physics intersect, influencing and transforming each other.

I will discuss the role of entanglement in quantum matter (both in and out of equilibrium), quantum computation as a powerful tool for simulating complex physical systems, and the impact of information-theoretic principles on nuclear, high-energy, and condensed matter physics. By bridging the gap between these fields, we unlock new avenues for discovery and pave the way for technological breakthroughs.

Prof. Victor S. Batista, Department of Chemistry, Yale University and Yale Quantum Institute

Simulating Dynamics on Bosonic Quantum Devices

Bosonic quantum devices offer a novel approach to realize quantum computations, where the quantum two-level system (qubit) is replaced with the quantum (an)harmonic oscillator (qumode) as the fundamental building block of the quantum simulator. The simulation of chemical structure and dynamics can then be achieved by representing or mapping the system Hamiltonians in terms of bosonic operators. In this talk, we review recent progress and future potential of using bosonic quantum devices for addressing a wide range of challenging chemical problems, including the calculation of molecular vibronic spectra, the simulation of adiabatic and nonadiabatic chemical dynamics, quantum machine learning applications for characterization of molecular systems, molecular docking of molecular graph theory problems, and the calculations of electronic structure

Dr. Taran Driver, PULSE institute and SLAC National Accelerator Laboratory and Linac Coherent Light Source

Probing Correlated Multi-Electron Dynamics on the Attosecond Timescale

The interaction of light with matter is a fundamental process for probing and engineering the quantum properties of a molecule or material. This interaction is mediated by electrons, and understanding the many-body dynamics of electronic systems in the first moments following light-driven excitation is a frontier challenge. The characteristic timescale for this electron motion is set by the splitting of the relevant energy levels, which results in motion on the attosecond (10-18 s) timescale. It is now possible to generate pulses of light lasting on the order of one hundred attoseconds, both on the tabletop in the laboratory and at large free-electron laser facilities. I will present recent work using attosecond x-ray pulses to probe the ultrafast dynamics of multi-electron systems. We measured the photoemission delay in the core-level ionization of a molecule. This is the delay between the arrival of a photon and the emission of an electron in photoionization, which was long considered an instantaneous process. In fact, this delay reveals strong modulations due to electron correlation. We also time-resolved the response of an aromatic molecule, para-aminophenol, to impulsive photoionization. By accessing the dynamics within the first femtosecond following the removal of an electron, we observed the interplay between the sub-femtosecond decay of shake-up states and coherent charge density oscillation on the few-femtosecond timescale. I will also touch on future directions which will harness these new methods to develop ultrafast probes of electron motion and exotic light-engineered states in quantum materials.

Prof. Lina Necib, Department of Physics, MIT

Mapping out the Dark Matter in the Milky Way

In this talk, I will explore the interfacing of simulations, observations, and machine learning techniques to construct a detailed map of Dark Matter in the Milky Way, focusing on the Galactic Center/Halo and dwarf galaxies. For the Galactic Halo, I will present a recent work that reveals a decline in the stellar circular velocity, inducing tensions with established estimates of the Milky Way’s mass and Dark Matter content. I will discuss how the underestimated systematic errors in such a common methodology necessitates a revised approach that combines theory, observations, and machine learning. In dwarf galaxies, I will present a novel Graph Neural Network methodology that facilitates the accurate extraction of Dark Matter density profiles, validated against realistic simulations. I will conclude with a discussion on the future trajectory of astroparticle physics, emphasizing the need for the integration of astrophysical probes with experimental Dark Matter research, potentially leading to a better understanding of the nature of Dark Matter.

Prof. Philip Mannheim, University of Connecticut

The Accelerating Universe

I will describe some of the background that led to the award of the Nobel prize to Dr. Adam Riess, who will be our 2024 Katzenstein speaker on November 15.

Prof. Matthew Guthrie, University of Connecticut;

A New Era for Connecticut’s Oldest Planetarium: Historic Roots to Modern Revival

The UConn Planetarium, built in 1954, has long been a central resource for astronomy education and outreach at the University of Connecticut. In this talk, I will present an overview of the planetarium’s historical roots at UConn, its significance in the community, and the extensive renovations we have completed to bring this important facility back to life. After years of disuse, the planetarium has been fully upgraded with modern technology and will officially reopen on November 1st, immediately following this colloquium.

Our efforts to restore the planetarium are guided by the legacy of Dr. Cynthia Peterson, UConn’s first woman physics faculty member and a pioneer in science education. The planetarium now officially bears her name as the Cynthia Wyeth Peterson Memorial Planetarium, in honor of her decades of dedication to astronomy outreach. Following my presentation, Nora Berrah and Celeste Peterson will speak about Dr. Peterson’s life and achievements - how her contributions to UConn and the wider scientific community continue to resonate today.

Prof. Philip Kim, Harvard University

Searching for Anyon in Quantum Materials

The search for anyons, quasiparticles with fractional charge and exotic exchange statistics, has inspired decades of condensed matter research. Moreover, it has been predicted that exchange braiding of these particles, especially non-abelian anyons, can produce topologically protected logic operations that can serve as building blocks for fault-tolerant quantum computing. In this talk, I will discuss the progress of research on two quantum materials platforms to realize these exotic particles. In the first example, we will discuss anyons arising in fractional quantum Hall (FQH) effects, using quantum Hall interferometers for direct observation of the anyon braiding phase around a confined cavity. In the second example, we will discuss our recent experimental efforts to realize non-abelian anyons in proximitized topological insulator surfaces by controlled manipulation of magnetic vortices containing non-abelian anyons.

Prof. Jun Ye, University of Colorado and JILA

Title and abstract TBA

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.

[1] “Machine learning spectral indicators of topology,” Advanced Materials 34, 202204113 (2022).

[2] “Elucidating proximity magnetism through polarized neutron reflectometry and machine learning,” Applied Physics Review 9, 011421 (2022).

[3] “Direct prediction of phonon density of states with Euclidean neural networks,” Advanced Science 8, 2004214 (2021).

[4] “Ensemble-Embedding Graph Neural Network for Direct Prediction of Optical Spectra from Crystal Structure,” arXiv:2406.16654.

[5] “Panoramic mapping of phonon transport from ultrafast electron diffraction and machine learning,” Advanced Materials 35, 2206997 (2023).

[6] “Virtual Node Graph Neural Network for Full Phonon Prediction,” Nature Computational Science 4, 522 (2024).

[7] “Machine Learning Detection of Majorana Zero Modes from Zero Bias Peak Measurements,” Matter 7, 2507 (2024).

[8] “Structural Constraint Integration in Generative Model for Discovery of Quantum Material Candidates,” arXiv:2407.04557.

Prof.. Reina Maruyama,Yale University

What is dark matter?

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

Prof. Cassandra Paul (San Jose State University)

Title and abstract (TBD)

Contact: Prof. Erin Scanlon

Remote talk (details forthcoming)