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At least 739 records · Page 41

Twisting the Hubbard model into the momentum-mixing Hatsugai–Kohmoto model

The Hubbard model is a standard theoretical tool for studying materials with strong electron–electron interactions, such as cuprate superconductors. Unfortunately, interaction-driven phenomena, such as a transition into the strongly correlated Mott insulator phase, are difficult to treat with established theoretical techniques. However, the exactly solvable Hatsugai–Kohmoto model displays similar Mott physics. In this work we show how the Hatsugai–Kohmoto model can be deformed continuously into the Hubbard model. The trick is to systematically reintroduce all the momentum mixing that the original Hatsugai–Kohmoto model omits. This can be accomplished by grouping n momenta into a cell and hybridizing them, resulting in the momentum-mixing Hatsugai–Kohmoto model. We recover the Bethe ansatz ground-state energy of the one-dimensional Hubbard model to within 1% from only ten mixed momenta. Overall, the convergence scales as 1/n2 as opposed to the inverse linear behaviour of standard finite-cluster techniques. Our results for a square lattice reproduce all the known features from state-of-the-art simulations also with only a few mixed momenta. Consequently, we believe that the momentum-mixing Hatsugai–Kohmoto model offers an alternative tool for strongly correlated quantum matter.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Machine learning inversion of interatomic force constants from single-crystal inelastic neutron scattering

Atomic vibrations govern many macroscopic properties of materials, but experiments to comprehensively probe them remain challenging. Inelastic neutron scattering (INS) is a powerful technique to map phonon dispersions in crystals, especially when leveraging modern time-of-flight (ToF) spectrometers with large detectors. However, efficiently and robustly extracting interatomic force constants (FCs) parameterizing phonon dynamics from experimental spectra remains a bottleneck due to the complexity and high dimensionality of ToF INS datasets. Here, we present a machine learning approach for the direct inversion of FCs from single-crystal INS measurements. The framework leverages synthetic training data generated using universal machine-learned force fields and an efficient physics-based forward model. We benchmark two neural architectures–one emphasizing structured latent representation learning and the other direct, supervised spectral regression–across simulated datasets for two materials under idealized and noisy conditions. The latent-representation model is subsequently applied to experimental single-crystal INS data on germanium. The model is shown to reproduce FCs derived from both first-principles simulations and from iterative optimization, and furthermore achieves reliable inference even from sparse, single-orientation measurements representing short data acquisitions. Analysis of the learned latent space reveals semantically continuous and physically interpretable encodings that support strong cross-domain generalization. By bridging theoretical and experimental domains, we establish a path toward rapid inversion of experimental spectra and data-driven interpretation of temperature-dependent lattice dynamics.

42 ENGINEERING↗

Quadratic pseudospectrum for identifying localized states

Here we examine the utility of the quadratic pseudospectrum for understanding and detecting states that are somewhat localized in position and energy, in particular, in the context of condensed matter physics. Specifically, the quadratic pseudospectrum represents a method for approaching systems with incompatible observables {A j |1 ≤ j ≤ d} as it minimizes collectively the errors $\parallel$A j v - λ j v$\parallel$ while defining a joint approximate spectrum of incompatible observables. Moreover, we derive an important estimate relating the Clifford and quadratic pseudospectra. Finally, we prove that the quadratic pseudospectrum is local and derive the bounds on the errors that are incurred by truncating the system in the vicinity of where the pseudospectrum is being calculated.

97 MATHEMATICS AND COMPUTING↗

Quantum Monte Carlo studies of a trimer scaling function with microscopic two- and three-body interactions

Here, we present an energy scaling function to predict, in a specific range, the energy of bosonic trimers with large scattering lengths and finite range interactions, which is validated by quantum Monte Carlo calculations using microscopic Hamiltonians with two- and three-body potentials. The proposed scaling function depends on the scattering length, effective range, and a reference energy, which we chose as the trimer energy at unitarity. We obtained the scaling function as a limit cycle from the solution of the renormalized zero-range model with effective range corrections. We proposed a simple parametrization of the energy scaling function. Besides the intrinsic interest in theoretical and experimental investigations, this scaling function allows one to probe Efimov physics with only the trimer ground states, which may open opportunities to identify Efimov trimers whenever access to excited states is limited.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Disentangling quantum matter with measurements

Measurements destroy entanglement. Building on ideas used to study ‘quantum disentangled liquids,’ we explore the use of this effect to characterize states of matter. In this work, we focus on systems with multiple components, such as charge and spin in a Hubbard model or local moments and conduction electrons in a Kondo lattice model. In such systems, measurements of (a subset of) one of the components can leave behind a quantum state of the other that is easy to understand, for example in terms of scaling of entanglement entropy of subregions. We bound the outcome of this protocol, for any choice of measurement, in terms of more standard information-theoretic quantities. We apply this quantum disentangling protocol to several problems of physical interest, including gapless topological phases, heavy fermions, and scar states in the Hubbard model.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Crossover behavior in the magnetoresistance of thin flakes of the topological material ZrTe 5

ZrTe 5 is a layered material that exhibits intricate topological effects. Intensive theoretically and experimental efforts have been devoted to try to understand the physics in this materials. In this paper the temperature dependent magneto-transport properties of ZrTe 5 thin flakes are investigated. A characteristic temperature T* is observed in the temperature dependence of three different types of magnetoresistance simultaneously, which are the saturated Hall anomaly, the chiral anomaly and the longitudinal magnetoresistance. Furthermore, the value of T* decreases monotonically from 200K to 160K with increasing thickness of the ZrTe 5 thin flakes from 42nm to 89nm. Temperature induced topological phase transitions are attributed to the cause of such anomaly in the three types of magnetoresistance at T*. Overall, our findings provide a multi-parameter indicator for the emergence of topological phase transition in ZrTe 5 and could be extended to the study of other topological materials. The temperature dependence of the three types of magnetoresistance also shed light on the role of anomalous Hall Effect in the transport properties of ZrTe 5 .

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Screening two-dimensional materials with topological flat bands

The topological flat band (TFB) has been proposed theoretically in various lattice models, to exhibit a rich spectrum of intriguing physical behaviors. However, the experimental demonstration of flat band (FB) properties has been severely hindered by the lack of materials realization. In this study, by screening materials from a first-principles materials database, we identify a group of two-dimensional materials with TFBs near the Fermi level, covering some simple line-graph and generalized line-graph FB lattice models. These include the kagome sublattice of O in Ti O 2 yielding a spin-unpolarized TFB, and that of V in ferromagnetic V 3 F 8 yielding a spin-polarized TFB. The monolayer Nb 3 Te Cl 7 and its counterparts from element substitution are found to be breathing-kagome-lattice crystals. The family of monolayer II I 2 V I 3 compounds exhibit a TFB representing the coloring-triangle lattice model. Re F 3 , Mn F 3 , and Mn Br 3 are all predicted to be diatomic-kagome-lattice crystals, with TFB transitions induced by atomic substitution. Finally, Hg F 2 , Cd F 2 , and Zn F 2 are discovered to host dual TFBs in the diamond-octagon lattice. Our findings pave the way to further experimental exploration of eluding FB materials and properties.

36 MATERIALS SCIENCE↗

Characterizing the Stability of NISQ Devices

In this study, we focus on the question of stability of NISQ devices. The parameters that define the device stability profile are motivated by the work of DiVincenzo in [9] where the requirements for physical implementation of quantum computing are discussed. We develop the metrics and theoretical framework to quantify the DiVincenzo requirements and study the stability of those key metrics. The basis of our assessment is histogram similarity (in time and space). For identical experiments, devices which produce reproducible histograms in time, and similar histograms in space, are considered more reliable. To investigate such reliability concerns robustly, we propose a moment-based distance (MBD) metric. We illustrate our methodology using data collected from IBM's Yorktown device. Two types of assessments are discussed: spatial stability and temporal stability.

Dasgupta, Samudra↗

Stability Considerations for Virtual Capacitor Control in Constant Power DC Loads

In a DC grid, constant power loads (CPLs) necessitate a large bus capacitor to prevent negative impedance instability. Some of the capacitance can be realized virtually through CPL control to reduce the bus capacitor size. Here, this paper analytically studies system stability with virtual capacitor control. We demonstrate that the effectiveness of virtual capacitor control is highly sensitive to the implementation of the derivative action required to emulate the capacitor. For the first time, we theoretically demonstrate that a virtual capacitor can stabilize the system without any physical bus capacitor, provided that a set of analytically derived conditions are met. However, this stabilization is not achievable in practice due to the influence of non-idealities. In an example system requiring a $14$ mF capacitor to stably support the CPL, we show that stability can be achieved through virtual capacitor control, using only a 2 mF physical capacitor to account for the switching ripple non-idealities. Hardware-in-the-loop tests verify the analysis.

24 POWER TRANSMISSION AND DISTRIBUTION↗

$J/\psi $-p scattering length from the total and differential photoproduction cross sections

The J/ψ-p scattering length, αJ/ψp, can be extracted from the J/ψ photoproduction cross section near threshold using the Vector Meson Dominance (VMD) model to relate the reaction γp→J/ψp to J/ψp→J/ψp. Such estimates based on experimental data result in values for |αJ/ψp|, which are much lower than most of the theoretical predictions. In this work, we study the relations between the different results, depending on the use of the total or the differential cross sections, and the method of extrapolating the data to threshold in the case of a low-statistics data sample, such as the near threshold J/ψ photoproduction dataset. We estimate a range for |αJ/ψp| of 0.003–0.025 fm as extracted from experimental data within the VMD model and discuss possible reasons for such lower values compared to the theoretical results.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Measurements of the Antiquark Flavor Asymmetry in the Proton by the Drell-Yan Experiment SeaQuest

The antiquark flavor asymmetry \bar{d}/\bar{u} d ‾ / u ‾ in the proton gives an insight on the non-perturbative structure of the proton. The SeaQuest experiment measured the Drell–Yan cross section ratio of proton-deuterium to proton-proton to determine the antiquark flavor asymmetry \bar{d}/\bar{u} d ‾ / u ‾ precisely in the range of 0.13 0.13 < x < 0.45 . SeaQuest provides the evidence of \bar{d}/\bar{u} > 1.0 d ‾ / u ‾ > 1.0 over a wide range of momenta. Some theoretical models reproduce this result.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

A Novel Measurement of the Anomalous Muon Spin Precession Frequency in the Muon $g-2$ Experiment at Fermilab

The Muon $g-2$ Experiment operated at Fermi National Accelerator Laboratory (FNAL, or Fermilab) between 2018 and 2023 to produce the world's most precise measurement of the muon's \textit{anomalous magnetic moment}, $a_\mu = \frac{g_\mu - 2}{2}$, which expresses the relative deviation in the muon's $g$-factor from a baseline theoretical expectation that $g_\mu = 2$. In the Standard Model of particle physics, $g_\mu > 2$ and hence $a_\mu > 0$ by a calculable amount that depends on all possible interactions between the muon and all other fundamental particles, including any potentially undiscovered interactions beyond the Standard Model. For this reason, measurements of the electron anomaly $a_e$ and later the muon anomaly $a_\mu$ have helped guide the development of the Standard Model since the inception of quantum field theory, and the measured value of $a_\mu$ provides a valuable constraint for new hypotheses that extend the Standard Model. As of 2006, the leading measurement and Standard Model prediction for $a_\mu$ exhibited tension at the level of about three standard deviations, motivating an improved measurement at Fermilab that could test the tension more precisely. The experiment functions by storing a polarized beam of $\mu^+$ in a uniform magnetic field, which simultaneously induces circular motion and spin precession. As the stored muons undergo the Michel decay $\mu^+ \to e^+ + \nu_e + \bar{\nu}_\mu$, mediated by the parity-violating weak interaction, the rest-frame $e^+$ emission direction is correlated with the parent $\mu^+$ spin orientation. Boosting into the laboratory frame encodes this correlation in the decay $e^+$ energy, which is higher when the emission (i.e. $\mu^+$ spin direction) is aligned with the $\mu^+$ momentum, and lower when opposite. Detectors then count the rate of high-energy decay $e^+$, which modulates at the difference between the $\mu^+$ revolution and spin precession frequencies. This observed frequency, called the \textit{anomalous spin precession frequency} $\omega_a$, is directly proportional to $a_\mu$. The extraction of $\omega_a$ proceeds by fitting the time spectrum of detected $e^+$, which requires precise modeling of the $\omega_a$ oscillation as well as any perturbations from beam dynamics and detector acceptance. Using the $\omega_a$ analysis presented in this work, based on Runs 4 -- 6 of the Muon $g-2$ Experiment at Fermilab, we find that $a_\mu = 0.001\,165\,920\,738(162)$ with a relative uncertainty of 139 parts per billion.

Barrett, Tyler [Cornell U.]↗

Unleashing the full power of LHCb to probe stealth new physics

In this paper, we describe the potential of the LHCb experiment to detect stealth physics. This refers to dynamics beyond the standard model that would elude searches that focus on energetic objects or precision measurements of known processes. Stealth signatures include long-lived particles and light resonances that are produced very rarely or together with overwhelming backgrounds. We will discuss why LHCb is equipped to discover this kind of physics at the Large Hadron Collider and provide examples of well-motivated theoretical models that can be probed with great detail at the experiment.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Enhancing the accuracy of density functional tight binding models through ChIMES many-body interaction potentials

Semi-empirical quantum models such as Density Functional Tight Binding (DFTB) are attractive methods for obtaining quantum simulation data at longer time and length scales than possible with standard approaches. However, application of these models can require lengthy effort due to the lack of a systematic approach for their development. In this work, we discuss the use of the Chebyshev Interaction Model for Efficient Simulation (ChIMES) to create rapidly parameterized DFTB models, which exhibit strong transferability due to the inclusion of many-body interactions that might otherwise be inaccurate. We apply our modeling approach to silicon polymorphs and review previous work on titanium hydride. We also review the creation of a general purpose DFTB/ChIMES model for organic molecules and compounds that approaches hybrid functional and coupled cluster accuracy with two orders of magnitude fewer parameters than similar neural network approaches. In all cases, DFTB/ChIMES yields similar accuracy to the underlying quantum method with orders of magnitude improvement in computational cost. In conclusion, our developments provide a way to create computationally efficient and highly accurate simulations over varying extreme thermodynamic conditions, where physical and chemical properties can be difficult to interrogate directly, and there is historically a significant reliance on theoretical approaches for interpretation and validation of experimental results.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Closing the loop between microstructure and charge transport in conjugated polymers by combining microscopy and simulation

A grand challenge in materials science is to identify the impact of molecular composition and structure across a range of length scales on macroscopic properties. We demonstrate a unified experimental–theoretical framework that coordinates experimental measurements of mesoscale structure with molecular-level physical modeling to bridge multiple scales of physical behavior. Here we apply this framework to understand charge transport in a semiconducting polymer. Spatially-resolved nanodiffraction in a transmission electron microscope is combined with a self-consistent framework of the polymer chain statistics to yield a detailed picture of the polymer microstructure ranging from the molecular to device relevant scale. Using these data as inputs for charge transport calculations, the combined multiscale approach highlights the underrepresented role of defects in existing transport models. Short-range transport is shown to be more chaotic than is often pictured, with the drift velocity accounting for a small portion of overall charge motion. Local transport is sensitive to the alignment and geometry of polymer chains. At longer length scales, large domains and gradual grain boundaries funnel charges preferentially to certain regions, creating inhomogeneous charge distributions. While alignment generally improves mobility, these funneling effects negatively impact mobility. The microstructure is modified in silico to explore possible design rules, showing chain stiffness and alignment to be beneficial while local homogeneity has no positive effect. This combined approach creates a flexible and extensible pipeline for analyzing multiscale functional properties and a general strategy for extending the accesible length scales of experimental and theoretical probes by harnessing their combined strengths.

42 ENGINEERING↗

Linac_Gen: Integrating Machine Learning and Particle-in-Cell Methods for Enhanced Beam Dynamics at Fermilab

Here, we introduce Linac_Gen, a tool developed at Fermilab, which combines machine learning algorithms with Particle-in-Cell methods to advance beam dynamics in linacs. Linac_Gen employs techniques such as Random Forest, Genetic Algorithms, Support Vector Machines, and Neural Networks, achieving a tenfold increase in speed for phase-space matching in Linacs over traditional methods, through the use of genetic algorithms. Crucially, Linac_Gen's adept handling of 3D field maps elevates the precision and realism in simulating beam instabilities and resonances, marking a key advancement in the field. Benchmarked against established codes, Linac_Gen demonstrates not only improved efficiency and precision in beam dynamics studies but also in the design and optimization of Linac systems, as evidenced in its application to Fermilab's PIP-II Linac project. This work represents a notable advancement in accelerator physics, marrying ML with PIC methods to set new standards for efficiency and accuracy in accelerator design and research. Linac_Gen exemplifies a novel approach in accelerator technology, offering substantial improvements in both theoretical and practical aspects of beam dynamics.

43 PARTICLE ACCELERATORS↗

From wide to ultrawide-bandgap semiconductors for high power and high frequency electronic devices

Abstract Wide and ultrawide-bandgap (U/WBG) materials have garnered significant attention within the semiconductor device community due to their potential to enhance device performance through their substantial bandgap properties. These exceptional material characteristics can enable more robust and efficient devices, particularly in scenarios involving high power, high frequency, and extreme environmental conditions. Despite the promising outlook, the physics of UWBG materials remains inadequately understood, leading to a notable gap between theoretical predictions and experimental device behavior. To address this knowledge gap and pinpoint areas where further research can have the most significant impact, this review provides an overview of the progress and limitations in U/WBG materials. The review commences by discussing Gallium Nitride, a more mature WBG material that serves as a foundation for establishing fundamental concepts and addressing associated challenges. Subsequently, the focus shifts to the examination of various UWBG materials, including AlGaN/AlN, Diamond, and Ga 2 O 3 . For each of these materials, the review delves into their unique properties, growth methods, and current state-of-the-art devices, with a primary emphasis on their applications in power and radio-frequency electronics.

Materials Science↗