Open House Poster Presentation Abstracts

Hanlin Tang, Graduate Student

h.tang@yale.edu

Quantum transducers that convert microwave photons into optical photons are important components of quantum networks. High efficiency quantum transducers require transduction medium have strong optical and microwave light coupling, as well as low noise operating environment. Yb3+: YVO4 emerges as competitive candidate for transduction application. Previous research on bulk Yb3+: YVO4 shows that the current limit on the transduction efficiency is the re-absorption of the outgoing optical signal by the host crystal [1]. The re-absorption effect can be reduced by controlling the thickness of the host crystal. The optimal thickness of YVO4 is ∼ 1μm by theoretical calculation, which cannot be achieved in bulk crystals. An alternative approach is to grow YVO4 thin films as the host.
In this talk, we will discuss the methods growing YVO4 thin films on YVO4 substrates and sapphire substrates using Molecular Beam Epitaxy. The surface quality has been significantly improved in homoepitaxial thin films compared to bare substrates. For heteroepitaxial growth on sapphire substrates. We discovered interface strain-controlled Zircon-Scheelite phase transition of YVO4 thin films by introducing a buffer oxide layer. To study the domain structures of YVO4 thin films grown on sapphire substrates, we also did plane-view 4D STEM and obtained the 2D mapping of the domain distribution, which is consistent with what we observed in AFM and RHEED.

Ryan Everly, Graduate Student

ryan.everly@yale.edu

Quasicrystals are aperiodic but still have long-range order; they possess crystallographically forbidden rotational symmetry but not translational symmetry. Electronic band structure and topology, which provide insight into material properties of periodic crystals, are still not well-understood for quasicrystals because standard theoretical methods used to study band structure rely on translational symmetry. Quantum simulation of a quasicrystalline lattice will open a window into quasicrystal band structure and topology that is largely inaccessible to theory. This poster details the design of an ultra-cold lithium experiment with a 10-fold rotation symmetric optical lattice: a quasicrystal quantum simulator. This proof-of-concept experiment will pave the way to follow-up experiments with Bose condensates and degenerate Fermi gases in dynamical quasicrystal lattices, such as the mapping of intriguing features in quasicrystalline band structures that have deep connections to the properties of quasicrystalline topological quantum materials.

Siddharth Mukherjee, Graduate Student

siddharth.mukherjee@yale.edu

Cavity quantum electrodynamics (cQED) systems can leverage strong coupling between atoms and photons to generate strong all-to-all interactions between atoms. These all-to-all interactions have already demonstrated many use cases, with applications including analog simulation of BCS superconductor spin dynamics [1] and generation of strong entanglement between atomic ensembles [2]. Building on this further, multimode cQED is an appealing prospect, as being able to control the number of cavity modes participating in atom-light interactions adds the ability to engineer more complex coupling than the all-to-all interactions seen in single mode cavities. Previous experiments have already used multimode cavities to induce phonon-like effects for ultracold atoms within optical lattices [3], as well as explore unique spin glass phases for ultracold bosons [4]. <\p>

In our poster, we will describe our plans for a cQED analog quantum simulator, which will consist of a high-finesse multimode cavity placed within an ultracold atom apparatus capable of creating degenerate quantum gasses of 6Li. We will highlight our future plans for the fermionic multimode cQED experiments this cavity will be used for. In particular, we will discuss our plans for the analog quantum simulation of holographic models such as the Sachdev-Ye-Kitaev (SYK) model, which will leverage the degeneracy of our cavity modes, a randomly disordered optical potential, and strong atom-light interactions between fermions to generate quantum chaotic dynamics and fast quantum information scrambling [5,6].

• [1]: Young, D. J. et al. Observing dynamical phases of BCS superconductors in a cavity QED simulator. Nature 625, 679–684 (2024).
• [2]: Cooper, E. S., Kunkel, P., Periwal, A. & Schleier-Smith, M. Graph states of atomic ensembles engineered by photon-mediated entanglement. Nat. Phys. 20, 770–775 (2024).
• [3]: Guo, Y. et. al. An optical lattice with sound. Nature 599, 211-215 (2021).
• [4]: Marsh, B.P. et al. A multimode cavity QED Ising spin glass. Phys. Rev. Lett. 135, 160403 (2025).
• [5]: Uhrich, P. et al. A cavity quantum electrodynamics implementation of the Sachdev–Ye–Kitaev model. arxiv: 2303.11343 (2023).
• [6]: Solis, D. P. et al. From single-particle to many-body chaos in Yukawa–SYK: Theory and a cavity-QED proposal. arxiv: 2511.04762 (2026).

Ryan Hamilton, Graduate Student

ryan.hamilton@yale.edu

The Yale Relativistic Heavy Ion Group (RHIG) studies extreme conditions of nuclear matter and properties of Quantum Chromodynamics (QCD), the theoretical description of strong nuclear forces, by analyzing data from the Large Hadron Collider (LHC) and Relativistic Heavy Ion Collider (RHIC). We primarily study jets (very high energy scatterings produced in collisions at RHIC and LHC) and how they interact with the hot, dense medium produced in these collisions, though some members also study other properties of produced particles like strangeness. We look forward to chatting with you!

Eric Regis, Graduate Student

eric.regis@yale.edu

A Brief Tour of Physics-Inspired Sampling
Many of the most important sampling algorithms in computational statistics have roots in physics. In this poster, we survey several foundational physics-inspired sampling methods, tracing their origins and unifying principles.

Throughout, we highlight the common threads linking these methods: their basis in statistical physics, their dynamical perspective, and their use of stochastic processes to explore probability distributions.

Harsh Vashistha, Postdoctoral Associate

harash.vashhistha@yale.edu

Animals benefit from quickly and reliably detecting approaching visual objects. Studies in many animals have identified neurons and circuits dedicated to detecting objects that grow in size over time, a hallmark of visual approach. However, approaching objects generate cues beyond expansion alone, and the roles of these alternative cues in approach detection remain largely unknown. Here, we show that Drosophila, like humans, can distinguish approach from retreat in a purely temporally modulated luminance stimulus devoid of any spatial motion, including expansion or contraction. In flies, targeted genetic silencing and two-photon calcium imaging revealed that two loom-sensitive visual projection neurons, LPLC1 and LPLC2, mediate turning and freezing responses both to classical looming and to pure luminance-based approach stimuli, establishing them as general approach sensors. We establish a framework predicting the natural temporal order of luminance and expansion cues during object approach. Consistent with this, we demonstrate that LPLC1 and LPLC2 neurons integrate these cues synergistically, boosting responses only when the cues are aligned in the natural order. Taken together, our results link a luminance-defined approach percept in humans to a concrete circuit computation in flies, and reveal how motion and luminance signals converge to support reliable approach detection.

Superfluid Optomechanics in Fiber Fabry–Pérot and Whispering-Gallery-Mode Cavities toward Heralded Phonon Entanglement

Yijun Zhang, Graduate Student

yijun.zhang@yale.edu

Quantum optomechanics provides a route to quantum control of sound through photon–phonon interactions, including heralded single-phonon processes via sideband photons and single-photon detection. Our primary platform is based on superfluid helium–filled fiber Fabry–Pérot cavities (FPFCs), where optical and acoustic modes share the same boundary conditions and phase matching selects coupling to an acoustic mode at half the optical wavelength. We have demonstrated near-ground-state cooling and single-photon sideband counting in individual FPFCs. Extending this architecture to multiple cavities tuned into optical and acoustic indistinguishability should enable indistinguishable scattering and heralded generation of collective phonon states, including W states.

A current limitation of FPFCs is phonon coherence, which remains restricted to ～ 50~ µs by acoustic leakage at the fiber–helium interface. To address this, we are developing superfluid helium–filled whispering-gallery-mode (WGM) resonators, whose circulating geometry improves acoustic confinement while maintaining strong optomechanical coupling. We have a microshell device and are transitioning to smaller microbottle resonators. Simulations predict phonon lifetimes of approaching 1 s, with g_0 ～ 580 Hz, C ～ 0.15, and acoustic frequencies around 300 MHz. Together, FPFCs and WGM resonators provide a path toward heralded phonon entanglement and long-lived phononic quantum memories.

Scanning Mutual Inductance Microscope for Superconducting and Magnetic Material Investigations

Aria Wang, Undergraduate Student

aria.wang@yale.edu

The performance of superconductors and nanomagnets are often contingent on deliberately nano-patterned structures or inadvertent sub-micron-scale inhomogeneities. Current technology, such as scanning SQUID, is optimized to probe magnetization and susceptibilities at cryogenic temperatures. To obtain spatially-resolved ac magnetic susceptibility, especially in the study of room temperature 2D magnetism and combinatorially synthesized high-Tc superconductors, we propose a scanning mutual inductance microscope (SMIM) that utilizes the nano-positioning mechanism from scanning tunneling microscopy and susceptometry mechanism from two-coil mutual inductance. In this work, we demonstrate with finite element simulation that placing a high magnetic permeability tip at the core of a mutual inductance solenoid can focus kHz-level magnetic field down to sub-micron scales. We discuss the tip design principle, sample measurement geometry, resolution function, and specifically how to obtain the superfluid density for thin film superconductors from such a setup. Finally, experimental demonstrations and limitations will be discussed.

Rohit Raut, graduate student

rohit.raut@yale.edu

The Deep Underground Neutrino Experiment (DUNE) is a global collaboration of over 1,000 researchers aiming to study the properties of neutrinos and search for phenomena beyond the Standard Model (BSM). DUNE will employ liquid argon time projection chambers (LArTPCs) containing 70 ktons of LAr, 40 ktons of which are active, located more than a kilometer underground at the Sanford Underground Research Facility. The high-resolution imaging capabilities of LArTPCs, combined with the large detector volume and underground location, allow DUNE to investigate both neutrino behavior and rare processes by significantly reducing cosmogenic backgrounds.
This poster highlights Yale’s contributions to DUNE, spanning detector development, involvement in the ProtoDUNE prototype program, and Far Detector physics studies including atmospheric neutrinos and rare process searches such as proton decay. ProtoDUNE also provides opportunities to search for new particles produced in beam dump like conditions, including Neutrinos and Heavy Neutral Leptons (HNLs), where Yale is working on trigger study to identify these rare BSM signatures. These efforts reflect Yale’s role in both hardware development and physics analysis as the experiment moves toward construction and operation in the coming years.

This poster highlights some of the ongoing research in the group.

_{Jose Betancourt, Graduate Student}

_{jose.betancourtvalencia@yale.edu}

In order to perform chemotaxis, microscopic organisms use diverse navigation strategies. For example, E. coli perform run-and-tumble motion, while V. cholerae do run-reverse-flick, while some larger organisms implement continuous steering. These qualitatively distinct strategies are implemented by differing mechanical structures, and in different environments, and it is possible that they reflect different mechanical constraints or evolutionary happenstance. Here, we consider a simpler possibility – that given a limited information budget, qualitatively different strategies might be optimal. Under our information theoretic constraint an organism that can measure the direction of the gradient should always perform continuous steering, becoming more accurate as their information rate increases. By contrast, an organism able only to measure the time derivative of concentration should instead alternate straight running with reversals when information is sparse. But as the amount of sensory information available increases, the optimal strategy undergoes a series of transitions to incorporate progressively smaller flicks. These strategies remain discrete for all information rates. Our results could help explain qualitative features of the diverse strategies used by organisms to chemotax.

Ellis Eisenberg, Undergraduate Student

ellis.eisenberg@yale.edu

Gravitational waves are the latest predictions from Einstein’s theory of General Relativity to be detected. In 2023, NANOGrav found evidence for a low-frequency gravitational wave background (GWB). The findings suggest that this background arises from the superposition of gravitational wave signals from merging supermassive black hole binaries. Confirmation for this detection is found by detecting the Hellings and Downs curve – the relation between the angular separation of pulsars and pulsar signal arrival time asynchronism. By deriving an expanded version of the Hellings-Downs curve, we hope to account for anisotropy to greatly improve sky localization for continuous wave searches.

Qinyuan Zheng, Graduate Student

qinyuan.zheng@yale.edu

With periods much longer than the duration of current pulsar timing surveys, gravitational waves in the picohertz (pHz) regime are not detectable in the typical analysis framework for pulsar timing data. However, signatures of these low-frequency signals persist in the slow variation of pulsar timing parameters. In this work, we present the results of the first Bayesian search for continuous pHz gravitational waves using the drift of two sensitive pulsar timing parameters—time derivative of pulsar binary orbital period $\dot{P}_b$ and second order time derivative of pulsar spin period $\ddot{P}$. We apply our new technique to a dataset with more than double the number of pulsars as previous searches in this frequency band, achieving an order-of-magnitude sensitivity improvement. No continuous wave signal is detected in current data; however, we show that future observations by the Square Kilometre Array will provide significantly improved sensitivity and the opportunity to observe continuous pHz signals, including the early stages of supermassive black hole mergers. We explore the detection prospects for this signal by extending existing population models into the pHz regime, finding that future observations will probe phenomenologically-interesting parameter space. Our new Bayesian technique and leading sensitivity in this frequency domain paves the way for new discoveries in both black hole astrophysics and the search for new physics in the early universe.

Scanning Targeted Searches for Gravitational Waves from Supermassive Black Hole Binaries

Forrest Hutchison, Graduate Student

forest.hutchison@yale.edu
 

Pulsar timing arrays (PTAs) are galaxy-scale detectors of nanohertz gravitational waves. In recent years, they have found evidence for a stochastic gravitational wave background (GWB), but the detection of continuous gravitational waves (CWs) from a single source remains elusive.

We search for CWs from 113 active galactic nuclei (AGN) that potentially host supermassive black hole binaries. By incorporating information from electromagnetic observations of these AGN, we achieve a median factor of 2.2 improvement in strain and chirp mass upper limits over all-sky searches at the same frequencies. While a GWB-only model is preferred for most targets, we present two interesting outliers as opportunities to develop a robust protocol for future detections.

The NANOGrav 15 yr Dataset: A Study of Chromatic Gaussian Process Noise Models in Six Pulsars

Bjorn Larsen, Graduate Student

bjorn.larsen@yale.edu

Pulsar timing arrays (PTAs) are designed to detect low-frequency gravitational waves (GWs). GWs induce achromatic signals in PTA data, meaning that the timing delays do not depend on radio frequency. However, pulse arrival times are also affected by radio-frequency-dependent “chromatic” noise from propagation effects such as dispersion measure (DM) and scattering delay variations. Furthermore, the characterization of GW signals may be influenced by the choice of chromatic noise model for each pulsar. To better understand this effect, we assess if and how different chromatic noise models affect the achromatic noise properties in each pulsar. The models we compare include existing DM models used by the North American Nanohertz Observatory for Gravitational waves (NANOGrav) and noise models used for the European PTA Data Release 2 (EPTA DR2). We perform this comparison using a subsample of six pulsars from the NANOGrav 15 yr data set, selecting the same six pulsars as from the EPTA DR2 six-pulsar data set. We find that the choice of chromatic noise model noticeably affects the achromatic noise properties of several pulsars. This is most dramatic for PSR J1713+0747, where the amplitude of its achromatic red noise reduces substantially, below the level of current GW measurements. We also compare each pulsar’s noise properties with those inferred from the EPTA DR2, using the same models. From the discrepancies, we identify areas where the noise models could be improved. These results highlight the potential for custom chromatic noise models to improve PTA sensitivity to GWs.

Joaquin Fernandez Odell, Graduate Student

joaquin.fernandezodell@yale.edu

Levitated particles have emerged as a promising tool for quantum sensing. The MAcroscopic Superpositions Towards witnessing the Quantum nature of Gravity (MAST-QG) experiment aims to observe the gravitationally mediated quantum entanglement of two levitated microdiamonds with embedded NV centers. Electromagnetic interactions provide the dominant background in this experiment generating unwanted entanglement. We have built a magneto-gravitational trap capable of optically sensing and optically and electrically controlling the particle’s motion. We are also capable of controlling the particle’s charge at the single electron level, allowing for characterization of the particle’s multipole moments. Characterization of the microdiamonds will inform materials research and the choice of background suppression protocols for MAST-QG. Our experiment also serves as a possible platform for other tests of fundamental physics requiring small electromagnetic backgrounds such as the search for millicharged particles and matter neutrality.

Alan Tsidilkovski, Graduate Student

alan.tsidilkovski@yale.edu

We present an overview of recent experimental work at Yale using homogeneous Fermi gases, including the realization of strongly driven Fermi polarons via radio-frequency excitation, the observation of sound propagation with tunable interactions, and measurements of loss dynamics induced by near-resonant light across the BEC–BCS crossover. We also investigate the recombination dynamics and energetics of a three-component Fermi gas, highlighting the versatility of uniform ultracold gases as a platform for probing equilibrium and nonequilibrium many-body physics with unprecedented control.

Naomi Brandt, Graduate Student

naomi.brandt@yale.edu

An important goal of computational studies of protein-protein interfaces (PPIs) is to predict the binding site between two monomers that form a heterodimer. The simplest version of this problem is to rigidly re-dock the bound forms of the monomers, which involves generating computational models of the heterodimer and then scoring them to determine the most native-like models. PPI scoring functions have been assessed previously using rank- and classification-based metrics; however, these methods are sensitive to the number and quality of models in the scoring function training set. We assess the accuracy of seven physical, statistical, or deep-learning-based PPI scoring functions by comparing their scores of computational models of PPIs to a measure of structural similarity to the x-ray crystal structure (i.e. the DockQ score) for a non-redundant set of heterodimers from the Protein Data Bank. For each heterodimer, we generate re-docked models uniformly sampled over DockQ and calculate the Spearman correlation between the PPI scores and DockQ. For some targets, the scores and DockQ are highly correlated; however, for many targets, there are weak correlations. Several physical features explain the difference between difficult- and easy-to-score targets. Strong correlations exist between the score and DockQ for targets with highly intertwined monomers and many interface contacts. We also develop a new score based on only two physical features that matches the performance of current PPI scoring functions. In addition, we address the more general problem of flexible-body docking by generating and docking intermediate monomer conformations between their bound and unbound forms. We score the docked models and find that the Spearman correlations between the PPI scores and DockQ decrease strongly as the monomers are deformed from their bound conformations. These results emphasize that PPI docking predictions can be improved by focusing on correlations between the PPI score and DockQ and incorporating more discriminating physical features into PPI scoring functions.

Armita Nourmohammad, Faculty

armita.nourmohammad@gmail.com

The PhABLE group for Physics of Adaptation, Learning, and Evolution in Biology [acronym sbj. to permutation invariance] is part of the Yale Center for Systems and Engineering Immunology (CSEI), the Yale QBio institute, and the departments of Immunobiology, Biomedical engineering, and Physics at Yale. We study how biological systems learn and adapt to their environments, and over longer time scales, how they evolve functional molecular programs and machinery. Our research bridges physics, mathematics, and computer science to uncover the principles underlying biological function, with a special focus on the immune system. By moving beyond description toward predictive understanding, we aim to develop frameworks that guide the rational design of control strategies for next-generation immune engineering.

This poster highlights some of the ongoing research in the group.