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Particle symmetries
Theory of fundamental particle symmetries derived from basic properties of space-time using principles of quantum mechanics and special relativity
Symmetry between particle and antiparticle populations in the universe.
Microscopic model of symmetry between particle and antiparticle populations in expanding universe
Quantum solver for single-impurity Anderson models with particle-hole symmetry
Quantum embedding methods, such as dynamical mean-field theory (DMFT), provide a powerful framework for investigating strongly correlated materials. A central computational bottleneck in DMFT is in solving the Anderson impurity model (AIM), whose exact solution is classically intractable for large bath sizes. In this work, we benchmark a quantum-classical hybrid solver tailored for particle-hole symmetric AIMs, using the variational quantum eigensolver to prepare the ground state of the model with shallow quantum circuits. The solver uses shallow quantum ansätze and one set of variational parameters to prepare the ground state and its particle and hole excitations, enabling the construction of the impurity Green’s function through a continued-fraction expansion. We evaluate the performance of this approach across a few bath sizes and interaction strengths under noisy, shot-limited conditions. We compare three optimization routines (COBYLA, Adam, and L-BFGS-B) in terms of convergence and fidelity, assess the benefits of estimating a quantum-computed moment correction to the variational energies, and benchmark the approach by comparing the density of states computed from the impurity Green’s function against that obtained using a classical pipeline. Our results demonstrate the feasibility of Green’s function construction on near-term devices and establish practical benchmarks for quantum impurity solvers embedded within self-consistent DMFT loops.
Question of combining internal symmetries and lorentz group
Combining internal symmetries with Lorentz group - relativistic spin dependent symmetry, particle multiplets, and mathematical structure of symmetry algebras
Crystallography of decahedral and icosahedral particles. II - High symmetry orientations
Based on the exact crystal structure of decahedral and icosahedral particles, high energy electron diffraction patterns and image profiles have been derived for various high symmetry orientations of the particles with respect to the incident beam. These results form a basis for the identification of small metal particle structures with advanced methods of transmission electron microscopy.
Nonlinear dynamics in dusty plasmas subjected to photo-discharging
Experimental research into the control of particle charge in dusty plasmas conducted at Auburn University indicates that photocurrents generated by exposing dust to intense, near-ultraviolet light can provide a reliable and novel method of independently controlling dust charge without radically altering the background plasma; the experiment also showed that some particles may respond differently to this photo-discharge, with some exhibiting highly periodic responses to the discharge and others exhibiting chaotic behaviour. Since the dust particles in the experiment were a polydisperse sample of different sizes and shapes, particle geometry may play a role in explaining this difference. Simulations of particle discharge and dynamics are used in an attempt to reproduce experimental results and investigate a possible correlation between particle symmetry and dynamic periodicity.
Dissipative ground state preparation in ab initio electronic structure theory
Dissipative engineering is a powerful tool for quantum state preparation, and has drawn significant attention in quantum algorithms and quantum many-body physics in recent years. In this work, we introduce a novel approach using the Lindblad dynamics to efficiently prepare the ground state for general ab initio electronic structure problems on quantum computers, without variational parameters. These problems often involve Hamiltonians that lack geometric locality or sparsity structures, which we address by proposing two generic types of jump operators for the Lindblad dynamics. Type-I jump operators break the particle number symmetry and should be simulated in the Fock space. Type-II jump operators preserves the particle number symmetry and can be simulated more efficiently in the full configuration interaction space. For both types of jump operators, we prove that in a simplified Hartree-Fock framework, the spectral gap of our Lindbladian is lower bounded by a universal constant. For physical observables such as energy and reduced density matrices, the convergence rate of our Lindblad dynamics with Type-I jump operators remains universal, while the convergence rate with Type-II jump operators only depends on coarse grained information such as the number of orbitals and the number of electrons. To validate our approach, we employ a Monte Carlo trajectory-based algorithm for simulating the Lindblad dynamics for full ab initio Hamiltonians, demonstrating its effectiveness on molecular systems amenable to exact wavefunction treatment.
Investigating solutions to the strong CP problem (Final Technical Report)
The weak interaction violates a symmetry between particles and anti-particles that is called a CP symmetry. This violation is expected to induce CP violation in the strong interaction by a large amount. However, observations show that the CP violation in the strong interaction is smaller than expected by more than ten orders of magnitude. This discrepancy is called the strong CP problem, and solving it has been one of the motivations for constructing a theory beyond the Standard Model (SM). In this research program, the PI investigated possible signals of solutions to the strong CP problem. The signals were predicted for a variety of experiments and observations. These predictions bridge different subfields of particle physics, cosmology, and astrophysics that are otherwise disconnected. As a byproduct, the PI also applied the techniques developed in this study to theories with axion-like particles to reveal signals of axion-like particles.
Normal scalar nonet K sub 1 goes to 2 pi decay and K sub 1 -K sub 2 mass difference.
Normal scalar nonet, K1 meson-2 pion decay, K1-K2 mass difference and S-wave pi-pion scattering
Physics-tailored machine learning reveals unexpected physics in dusty plasmas
Dusty plasma is a mixture of ions, electrons, and macroscopic charged particles that is commonly found in space and planetary environments. The particles interact through Coulomb forces mediated by the surrounding plasma, and as a result, the effective forces between particles can be nonconservative and nonreciprocal. Machine learning (ML) models are a promising route to learn these complex forces, yet their structure should match the underlying physical constraints to provide useful insight. Here, we demonstrate and experimentally validate an ML approach that incorporates physical intuition to infer force laws in a laboratory dusty plasma. Trained on 3D particle trajectories, the model accounts for inherent symmetries, nonidentical particles, and learns the effective nonreciprocal forces between particles with exquisite accuracy (R 2 > 0.99). We validate the model by inferring particle masses in two independent yet consistent ways. The model’s accuracy enables precise measurements of particle charge and screening length, identifying large deviations from common theoretical assumptions. Our ability to identify unknown physics from experimental data demonstrates how ML-powered approaches can guide new routes of scientific discovery in many-body systems. Furthermore, we anticipate our ML approach to be a starting point for inferring laws from dynamics in a wide range of many-body systems, from colloids to living organisms.
Excitons in fractionally filled moiré superlattices
Long-range Coulomb forces give rise to correlated insulating states when charge particles populate a moiré superlattice at certain fractional filling factors. Such behavior is characterized by a broken translation symmetry wherein particles spontaneously form a Wigner crystal. Here, focusing on the experimental findings of Xu et al. [Nature (London) 587, 214 (2020)], we present a theory that captures the correlated insulating state of a fractionally filled moiré superlattice through the energy shift and change in oscillator strength of the exciton absorption resonance. The theory shows that the experimental findings can only be supported if the electrons reside in a charge-ordered state (i.e., electrons are not randomly distributed among the sites of the moiré superlattice). Furthermore, we explain why the energy shifts of exciton resonances are qualitatively different in cases where the superlattice is nearly empty compared with a superlattice whose sites are doubly occupied.
Saturn's rings - Structure, dynamics, and particle properties
The current state of knowledge of Saturn's rings is reviewed. A brief historical introduction is given, followed by a discussion of the radial profile of the rings, ring dynamics, features without azimuthal symmetry, ring particle size distribution, and the physical properties of ring particles. The direction for future analysis and observation is considered.
Towards AI-assisted neutrino flavor theory design
Particle physics theories, such as those which explain neutrino flavor mixing, arise from a vast landscape of model-building possibilities. A model’s construction typically relies on the intuition of theorists. It also requires considerable effort to identify appropriate symmetry groups, assign field representations, and extract predictions for comparison with experimental data. We develop Autonomous Model Builder (AMBer), a framework in which a reinforcement learning agent interacts with a streamlined physics software pipeline to search these spaces efficiently. AMBer selects symmetry groups, particle content, and group representation assignments to construct models while minimizing the number of free parameters introduced. We validate our approach in well-studied regions of theory space and extend the exploration to a previously unexamined symmetry group. While demonstrated in the context of neutrino flavor theories, this approach of reinforcement learning with physics software feedback may be extended to other theoretical model-building problems in the future.
Determining Magnetic Field Directions and Omni-directional Fluxes of Particles from STPSat-6 ZPS Plasma Measurements
This report summarizes our recent data derivation efforts on STPSat-6 ZPS plasma measurements, presenting final outcomes. We begin by outlining the methodology developed to determine local magnetic field directions from measured directional intensities of ~20 keV ions, leveraging symmetry in particles’ pitch-angle distributions, and the determined field directions over a storm period are shown with errors analyzed through comparison with NOAA GOES measurements. Next, we further assess the validity of the method and quantify its overall high performance while acknowledging certain caveats. Finally, given local magnetic field directions and ZPS data, we explain how omni-directional fluxes of particles can be derived from ZPS measurements with limited directional coverage, and estimate the related errors under several theoretical scenarios. The methods developed in this study can be applied for processing and augmenting ZPS data for the next, and the insights gained here can also inform instrument design in the future.
Classifying photonic topology using the spectral localizer and numerical K -theory
Recently, the spectral localizer framework has emerged as an efficient approach for classifying topology in photonic systems featuring local nonlinearities and radiative environments. In nonlinear systems, this framework provides rigorous definitions for concepts such as topological solitons and topological dynamics, where a system’s occupation induces a local change in its topology due to nonlinearity. For systems embedded in radiative environments that do not possess a shared bulk spectral gap, this framework enables the identification of local topology and shows that local topological protection is preserved despite the lack of a common gap. However, as the spectral localizer framework is rooted in the mathematics of C*-algebras, and not vector bundles, understanding and using this framework requires developing intuition for a somewhat different set of underlying concepts than those that appear in traditional approaches for classifying material topology. In this tutorial, we introduce the spectral localizer framework from a ground-up perspective and provide physically motivated arguments for understanding its local topological markers and associated local measure of topological protection. In doing so, we provide numerous examples of the framework’s application to a variety of topological classes, including crystalline and higher-order topology. We then show how Maxwell’s equations can be reformulated to be compatible with the spectral localizer framework, including the possibility of radiative boundary conditions. To aid in this introduction, we also provide a physics-oriented introduction to multi-operator pseudospectral methods and numerical K-theory, two mathematical concepts that form the foundation for the spectral localizer framework. Finally, we provide some mathematically oriented comments on the C*-algebraic origins of this framework, including a discussion of real C*-algebras and graded C*-algebras that are necessary for incorporating physical symmetries. Looking forward, we hope that this tutorial will serve as an approachable starting point for learning the foundations of the spectral localizer framework.
Structural and compositional complexities of hierarchical self-assembly: A hypergraph approach
Programmable self-assembly enables the construction of complex molecular, supramolecular, and crystalline architectures from well-designed building blocks. In this work, we introduce a hypergraph-based formalism, Blocks & Bonds (B&B), which generalizes classical chemical graph theory by incorporating directed and multicolored interactions, internal symmetries, and hierarchical organization. Within this framework, we develop the Structure Code (SC), a compact and versatile language for describing self-assembled architectures. We define a Kolmogorov-style structural complexity as the total information content of SC, obtained through its tokenization and Shannon information assignment. Complementing this encoding-based measure, we introduce a much simpler quantity, the compositional complexity, which depends only on the number and cumulative usage of block and bond types in the construction set. A central result of this work is a strong empirical correlation between the token-based structural complexity and the compositional complexity across all examined systems. Owing to this agreement, the compositional complexity emerges as the most practical and broadly applicable measure: it is easy to compute, requires no explicit encoding, and yet closely tracks the actual information content of structurally diverse architectures. Applications to molecular systems (ethylene glycol and glucose), DNA-origami lattices, and crystalline assemblies show that B&B hypergraphs provide a unified, scalable, and information-efficient representation of structural organization, naturally capturing symmetry, modularity, and stereochemistry. This framework establishes a quantitative foundation for complexity-aware classification and inverse design of programmable matter.
Two-mode bosonic quoctit for high energy physics
In this work, we study a two-mode bosonic encoding of a quoctit inside a non-Abelian group-structured constellation of coherent states. This work is motivated by the importance of non-Abelian symmetry in particle physics and the desire to have transversal non-Abelian logical gates. We use the previously developed 2 T constellation of states used to encode a so-called 2 T qutrit. The fidelity of the 2 T quoctit is benchmarked against other bosonic qudits for different noise models and find it compare favorably when power constraints are considered. This paves the way for the construction of higher-dimensional qudits (e.g., a quicosotetrit with 2 T group structure) in bosonic systems with practical applications in quantum simulations of particle physics.