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)

TITLE:

Quantum acoustics and the physics of the strange metals

ABSTRACT:

Quantum acoustics is the analog of quantum optics, with phonons playing the role of photons. The classical fields (electromagnetic, acoustic) are reached by virtue of coherent states in both cases. Quantum acoustics leads to two time dependent, interacting wave fields, one lattice, one quantum. The electron diffuses at a Planckian rate, independent of electron-lattice coupling and temperature, and the calculated resistivity is linear in temperature. Mott-Ioffe-Regel and Drude peak mysteries are also resolved. A rather different carrier transport scenario emerges for the strange metals.

Dr. Nick Hutzler, California Institute of Technology

UConn Physics Colloquium

Title and abstract: TBD

Contact: Profs. Tom Blum and Dan McCarron

Dr. James Cryan, SLAC National Lab (UConn Physics Colloquium)

Ultrafast dynamics using X-ray attosecond pulses.

Contact: Prof. Nora Berrah

UConn Physics Colloquium: Dr. Andrew Held

High Power Commercial Laser Markets and Applications

Abstract: Ubiquitous and familiar applications for lasers include telecom data transmission, laser surgery (LASIK), information processing (DVD/Blue Ray), supermarket scanners, laser pointers and a multitude of laser sensing applications (LIDAR, range finders, facial recognition, etc.). Sophisticated laser technology is also well-recognized as a key, enabling research tool.

Perhaps less well known are the “unsung” commercial applications and markets for higher power lasers. Often out of public view, these laser applications drive diverse and massive commercial markets and are supported by extensive industry-based research and development investments. And are generating increasingly abundant STEM based career opportunities.

The presentation will highlight the laser technologies and applications used in materials processing to mark, engrave, cut, and join everything from shoe leather to sheet metal. Also covered are laser applications supporting the manufacturing of microelectronics-based consumer technology, enabling higher performing devices and ever larger displays. The laser technology and developments that support emerging Directed Energy military applications will be also be reviewed.

Bio:

Andrew Held has recently retired as Senior Vice President of Coherent’ s Aerospace and Defense business. Andrew has over 30 years’ experience in General Business Management, Research, Sales and Marketing of lasers and photonics into a broad range of markets and applications. He received his B.S. in Chemistry and Ph.D. in Laser Spectroscopy from the University of Pittsburgh and was an Alexander von Humboldt Research Fellow at the Technical University in Munich.

Dr. Josiah Sinclair, MIT

A new platform for quantum science: programmable arrays of single atoms inside an optical cavity.

Recently, programmable arrays of single atoms have emerged as a leading platform for quantum computing and simulation with experiments demonstrating control over hundreds of atoms [1]. Interfacing an atom array with a high-quality optical cavity promises even greater control and new capabilities. By coupling atoms to an optical cavity, we can more efficiently collect light from each atom improving detection. In addition, an optical cavity can be used to efficiently entangle many atoms in a single step relying on a novel technique called counterfactual carving [2]. I will describe our progress towards the goal of detecting and correcting errors on a register of Rubidium atoms selectively coupled to a large-waist optical cavity. Beyond detecting errors, applying corrections requires real-time feedback, and I will present a simple experiment demonstrating that fast feedback on microsecond timescales can already improve measurement fidelity. Finally, I will describe our accidental realization that we can use our cavity to directly observe collisions between pairs of trapped atoms in real time.

Dr. Jim Zickefoose and Dr. Gabriela Ilie, Senior Scientists, Physics Division, Mirion Technologies, Meriden CT

Mirion Technologies – Connecting Academia and Industry

Mirion Technologies is a world leader in the development and supply of nuclear instrumentation and supporting software. To accomplish its goals and objectives, Mirion has a diverse team of physicists holding various levels of degrees. In this seminar we will show our paths from graduate studies to joining Mirion, emphasizing how the skills we gained during our academic journeys have contributed or have been beneficial to our professional development in industry. Furthermore, we will highlight Mirion Technologies’ general areas of interest as well as revealing some interesting applications where we have partnered with academia.

Speakers’ bio:

Gabriela is the Product Line Manager for Specialty Detectors and a Senior Application Scientist at Mirion Technologies, focused on developing custom high-purity germanium (HPGe) detector solutions for challenging and unique applications. She joined Mirion in 2012 (formerly Canberra Industries) as a physicist and has worked on a variety of projects offering physics support and doing validation and testing for different products. Gabriela has a Ph.D. in Experimental Nuclear Physics from the University of Cologne, Germany. Before joining Mirion, Gabriela held a Postdoctoral Research position at Yale University where she helped maintain and use a large array of HPGe Clover detectors for nuclear physics measurements and experiments. In the last few years, she has played an active role in promoting new technologies that help customers select the best radiation detection and instrumentation for their applications.

Jim Zickefoose is a Sr. Scientist and R&D Physics Manager at Mirion Technologies in Meriden CT. In these roles he concentrates on driving new technology development across the various Mirion divisions and incorporating those technologies in new or existing products. He joined Mirion in 2010 directly after earning a PhD in physics from the University of Connecticut with a concentration in experimental nuclear astrophysics. During his PhD research Jim studied carbon fusion reactions at accelerator facilities in Caserta, Italy and Bochum, Germany. Prior to his time at UConn Jim earned an Honors Degree in physics from the University of Adelaide.

Note: coffee and cookies at 3:00 outside the lecture room.

Prof. Geoff Potvin, FIU

UConn physics departmental colloquium

Title and abstract: TBD

Dr. Ming Li

UConn Physics Colloquium

Title and abstract: TBD

Dr. Christopher Hayward, Center for Computational Astrophysics, Flatiron Institute

Solving the puzzle of galaxy formation

Understanding the physics of galaxy formation has been a central goal of astrophysics for decades, but we have yet to solve this complicated problem. I will describe what makes understanding galaxy formation so challenging. I will detail how theorists work to decipher this puzzle using numerical simulations, highlighting the key physical processes involved. I will then discuss the idea of ‘forward modeling’, i.e. predicting synthetic observables from hydrodynamical simulations in order to more directly confront theory and observation, and highlight some recent important results of such work.

Speaker’s biography and background

Prof. Roopali Kukreja, UC Davis

Imaging ultrafast and ultrasmall: Unraveling nanoscale electronic and magnetic behavior using time-resolved x-ray scattering

Ultrafast laser control of correlated materials has emerged as a fascinating avenue of manipulating magnetic and electronic behavior at femtosecond timescales. Ultrafast manipulation of these materials has also been envisioned as a new paradigm for next generation memory and data storage devices. Numerous studies have been performed to understand the mechanism underlying laser excitation. However, it has been recently recognized that spatial domain structure and nanoscale heterogeneities can play a critical role in dictating ultrafast behavior. In this talk, I will discuss methods and our recent results which capture material behavior at nanoscale lengthscales and femtosecond-nanosecond timescales. I will describe our recent experimental studies using emerging synchrotron techniques and free electron laser such as European XFEL and FERMI. In the first part of my talk, I will discuss our results on ultrafast magnetization dynamics where we uncovered a symmetry-dependent behavior of the ultrafast response. Labyrinth domain structure with no translation symmetry exhibit an ultrafast shift in their isotropic diffraction peak position that indicates their spatial rearrangement. On the other hand, anisotropic domains with translation symmetry do not exhibit any modification of their anisotropic diffraction peak position. In the second part of my talk, I will focus on x-ray imaging of correlated oxides and discuss spatially dependent ultrafast response observed in complex oxides such as rare-earth nickelates. These intriguing observation suggests preferential, texture-dependent paths not only for the transport of angular momentum, but also for structural rearrangements. These measurements provide us with a unique way to study and manipulate spin, charge and lattice degrees of freedom.

Speaker’s bio: Roopali Kukreja joined Materials Science and Engineering department at UC Davis as an Assistant Professor in Fall 2016. She received her B.S. in Metallurgical Engineering and Materials Science from the Indian Institute of Technology Bombay in 2008 and then her M.S. and Ph.D. degrees in Materials Science and Engineering from Stanford University in 2011 and 2014, respectively. Prior to her appointment at UC Davis, Kukreja worked as a postdoctoral researcher at the UC San Diego, with Profs. Oleg Shpyrko (Physics Department) and Eric Fullerton (Center for Magnetic Recording Research). Her research interests at UC Davis focuses on ultrafast dynamics in nanoscale magnetic and electronic materials, time resolved X-ray diffraction and imaging techniques, thin film deposition and device fabrication.

Prof. Abhay Pasupathy, Columbia University and Brookhaven National Laboratory

We understand that the phenomenon of superconductivity involves the formation of pairs of electrons that find a way to attract each other in a solid. We also know that in most known superconductors, pairs of electrons are formed between two electrons that have opposite momentum and spin. A magnet, on the other hand, is a material where there is a dominance of electrons of one spin with respect to the other. What happens if we put these two phenomena together in a single material? Such is the case in the curious compound EuRbFe4As4, which displays superconducting order at a temperature of 35 K, and displays magnetic order at a lower temperature of 16 K. In this compound, superconductivity lives in atomic planes of FeAs, while the magnetism lives in adjacent layers of Eu. Electrons can jump from from one layer to the other, coupling the superconducting and magnetic properties to each other. I will describe scanning tunneling microscopy measurements that probe the consequences of this coupling, including the formation of superconducting order that is modulated in space, as well as an unusual set of excitations that exist in the magnetic superconducting state.

Prof. Simone Colombo
University of Connecticut

Title: Quantum Metrology with Ultracold Atoms (and Optical Cavities)

Abstract:

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

I will then focus on a specific type of atomic sensor and one of my research interests: optical atomic clocks. State-of-the-art optical atomic clocks achieve mind-boggling stabilities and in many regimes are almost solely limited by quantum noise. Building upon recent results (mine and from other groups), I will illustrate how optical clocks’ performances can be pushed beyond current quantum noise limitations and how they can be/are deployed in the search for new physics and the testing of the fundaments of general relativity. Within this framework, I will finally overview the research activities I am developing at UConn.