Prof. Peter Schweitzer, Department of Physics, University of Connecticut

Internal Structure of Hadrons

Hadrons are composed particles and exhibit a rich internal structure which is probed experimentally in high energy experiments and described in the theory of Quantum Chromodynamics. Recent advances in the theory of hadron structure with focus on gravitational form factors are discussed.

Dr. Eric Koch, Harvard Smithsonian Center for Astrophysics

Revealing the multi-phase neutral interstellar medium’s role in the star formation lifecycle: a sharpened view of nearby galaxies from LGLBS and PHANGS-JWST

The neutral interstellar medium (ISM) fuels the star formation lifecycle, yet we still lack vital constraints on the formation and destruction of molecular clouds because of challenges in observing the cold neutral ISM phases with high resolution and sensitivity. With dedicated surveys, the combination of VLA, ALMA, and JWST can now make significant advances in the coming years. In this talk, I will present multiple observational approaches that are making progress in this area: detailed 21-cm HI VLA mapping across the Local Group from the Local Group L-band Survey (lglbs.org), resolved molecular cloud studies with ALMA and JWST in M33 and PAH imaging from PHANGS-JWST as a highly sensitive resolved view of the total neutral gas tracer (phangs.org). These surveys bridge Galactic with extragalactic star formation studies and provide new constraints to guide the next generation of numerical simulations.

The Physics Department ice cream social

will take place on Friday, September 27th at 1:30 in Gant South 117.

All are welcome!

Prof. Simone Colombo, Department of Physics, University of Connecticut

Observing our Universe with Quantum Sensors

In this seminar, we will introduce the application of atomic, molecular, and optical (known as AMO) physics to the field of quantum metrology. We will show how atoms are used as probes of our universe and how to harness quantum effects to enhance their sensing capabilities.

We will then focus on a specific type of atomic sensor and one of our research interests: optical atomic clocks. Building upon recent results, we will illustrate how optical clocks’ performances can be pushed beyond current limitations and how they can be/are deployed to get a better glimpse of the inner workings of our universes. In this framework, we will highlight the research activities that we are currently pursuing in our lab. Crucially, we will attempt to give a perspective on the life of an AMO physicist.

Prof. Nikolay Prokofiev, UMass Amherst

Bi-polaron superconductivity in the low density limit

It has been assumed for decades that high values of Tc from the electron-phonon coupling are impossible. At weak-to-intermediate coupling strength this result follows from the Migdal-Eliashberg theory, while at strong coupling, when bipolarons form, the transition temperatures are low because of the exponential effective mass enhancement. However, the latter conclusion was based on numerical solutions of the Holstein model. I will discuss a different model with coupling based on the displacement modulated hopping of electrons and argue that much larger values of the bipolaron Tc can be achieved in this setup. Non-locality of the problem gives rise to small-size, yet relatively light bipolarons, which can be studied by an exact sign-problem-free quantum Monte Carlo approach even in the presence of strong Hubbard and Coulomb potentials. We find that Tc in this model generically and significantly exceeds typical upper bounds based on Migdal-Eliashberg theory or superfluidity of Holstein bipolarons, and, thus, offers a route towards the design of high-Tc superconductors via functional material engineering. Finally, there are indications for even better prospects in systems with non-linear electron-phonon coupling.

Jake Lewitt, Cortex Fusion, New York, NY

Nuclear fusion in molecules using lasers

Cortex Fusion Systems, Inc. uses shaped ultrafast laser pulses to catalyze fusion reactions in molecules. Our work comprises (1) designing transiently confining effective one-electron potentials in field-dressed molecules, (2) performing quantum chemistry calculations to validate the enhancement of nuclear tunneling by laser-modified electron screening dynamics, and (3) testing pulse shapes in the laser lab by coupling ultrafast spectroscopy techniques with nuclear radiation detection and spectrometry. In this regard, “quantum-controlled fusion” is a coherent, under-the-barrier process that does not require plasma ignition. Our goal is to repurpose the modern suite of commercial femtosecond laser amplifiers and pulse-shaping techniques to achieve compact and scalable fusion generators using quantum control.

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.

Monica Vidaurri, Stanford University and NASA Goddard

Ethics and Aliens: the need for an ethical approach to space science

The progress of space science and exploration has seemingly inevitably fallen to private companies, to the concern of private citizens and scientists, who are directly impacted by private actions in space. Additionally, academia has reached a critical limit in terms of unchecked features that promote elitism and exclusionism, including increasingly competitive admissions to programs and fellowships, scarcity in jobs, prevalent sexual harassment, and others. As individuals, it is difficult to imagine what a truly ethical framework for our work looks like, let alone how we alone can influence laws and policy to change the actions of individuals with seemingly unlimited wealth and resources. This talk will introduce 3 main facets of what ethics means with respect to space science and exploration, including introducing space science as a historically oppressive institution, and how we can begin to move past this as individuals, labs, departments, and institutions. The norms we allow and ignore ultimately shape these broader laws, policies, and workplace culture. As a result, our science cannot be detached from the social and political framework it exists in, and the custom of early and regular collaboration with ethicists and planetary protection specialists (and other social scientists) is critical for not only mission safety, but mission and science integrity, as well as the well-being of those contributing to the mission and who gets to be included in such work. Creating a safe, responsible, and ethical space for peaceful purposes cannot wait for the international space community to create these practices de jure, but must be started at the individual level and regarded as custom for integration into international law, de facto, and require an uncomfortable self-assessment in the true goals of space science, as well as the ways that the academic structure has failed certain groups of students. By creating a new framework that prioritizes ethics, only then can we responsibly go into the unknown.