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At least 181 records · Page 10

Exchange-correlation functional challenges in modeling quaternary chalcogenides

The development of next-generation quaternary chalcogenides, such as Cu2ZnSnS4 (CZTS) and Cu2ZnGeS4 (CZGS), for solar energy and thermoelectric applications hinges upon both careful experimentation and accurate quantum mechanical modeling. To address the latter, many have turned to density functional theory (DFT), which offers several choices for the approximate treatment of electron exchange and correlation (XC). Popular XC functionals include the Perdew-Burke-Ernzerhof (PBE) generalized gradient approximation (GGA) and the recently developed strongly constrained and appropriately normed (SCAN) meta-GGA. Extensions of DFT functionals, such as adding a Hubbard U correction and introducing a fraction of the Fock exchange (hybrid functionals), have been used widely to model systems containing 3d metal ions. However, no studies yet have compared comprehensively PBE(+U) and SCAN(+U) in the quality of their predictions of the bulk and defect thermodynamics of quaternary chalcogenides, which play a critical role in device fabrication and performance. Hence, here we calculate the (i) 0 K formation energies of bulk Ge compounds and (ii) neutral defect formation energies including charge-balanced (e.g., CuZn + ZnCu) and charge-imbalanced (e.g., CuSn) combinations of antisites and vacancies in CZTS and CZGS using the PBE, PBE +U, SCAN, SCAN +U, and the hybrid Heyd-Scuseria-Ernzerhof XC frameworks. We find that the formation energies of charge-imbalanced defects are more sensitive to the choice of the XC functional than those of charge-balanced defects, which can be explained by the differences in the extent of penalization of defect-generated delocalized electrons/holes by PBE, PBE +U, SCAN, and SCAN +U. Additionally, our results show that SCAN systematically underbinds Ge-containing compounds, thus highlighting the need for even further improvement of XC functionals. Based on our findings, we recommend the use of SCAN for modeling quaternary chalcogenides because its errors are systematic, and it has the firmest theoretical underpinning. Our work provides guidance for future modeling of quaternary chalcogenides.

14 SOLAR ENERGY↗

Temperature-dependent electronic structure in a higher-order topological insulator candidate EuIn 2 As 2

Higher-order topological insulators (HOTIs) have enticed enormous research interests owing to their novelty in supporting gapless states along the hinges of a crystal. Despite several theoretical predictions, enough experimental confirmation of the HOTI state in crystalline solids is still lacking. Here, it is shown that interplay between topology and magnetism can give rise to various magnetic topological states, including HOTI and axion insulator states. Here, using high-resolution angle-resolved photoemission spectroscopy combined with the first-principles calculations, we report a systematic study of the electronic structure and its evolution across the magnetic phase transition in EuIn 2 As 2 which possesses an antiferromagnetic ground state below 16 K. Antiferromagnetic EuIn 2 As 2 has been predicted to host both the axion insulator and the HOTI states.We directly observe the linearly dispersing holelike bands crossing the Fermi level and the change in their dispersion across the magnetic phase transition. Our paper points to EuIn 2 As 2 as being a promising material for the exploration of interplay between topology and magnetism.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Symmetry instability induced by topological phase transitions

The symmetry-topology interplay dictates how to define order parameters and classify material ordered phases. However, current understanding of this interplay has been predominately approached from a one-sided perspective, with topological states being classified within the constraints imposed by specific fixed symmetries. Here, in this study, we complete this full circle by demonstrating spontaneous symmetry breaking that results from a periodic alteration of topological phases induced by light in a centrosymmetric Dirac material ZrTe 5 . The distinguishing feature is the observation of robust correlation and striking anomalies in the fluence and temperature dependence of key transport parameters. First, both shift current 𝐽 𝑠 and displacement current 𝐽 𝑑 , arising from interband transition and infrared phonon driving, respectively, along with charge carrier pumping, exhibit similar behaviors. Second, they all peak at similar low pump fluence, followed by a subsequent reduction as the fluence further increases. This behavior cannot be explained by conventional energetically allowed, direct excitations. Third, all the three observables exhibit anomalies when they approach the topological phase transition temperature. These results highlight the unique low-energy pumping behaviors in ZrTe 5 , characterized by reversible fluence dependence and a “hinge-like” interaction that connects various electronic and lattice observables, including phonons, charge carriers, and currents. Our findings, supported by model analysis, provide key insights into the fragility of crystalline (inversion) and time-reversal symmetries during the dynamics of topological phase transitions. This fragility drives spontaneous symmetry breaking, evidenced by the synchronized emergence of off-resonant infrared phonons and broken-symmetry photocurrents.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Impact of late-time neutrino emission on the diffuse supernova neutrino background

In the absence of high-statistics supernova neutrino measurements, estimates of the diffuse supernova neutrino background (DSNB) hinge on the precision of simulations of core-collapse supernovae. Understanding the cooling phase of protoneutron star (PNS) evolution (≳ 1 s after core bounce) is crucial, since approximately 50% of the energy liberated by neutrinos is emitted during the cooling phase. We model the cooling phase with a hybrid method by combining the neutrino emission predicted by 3D hydrodynamic simulations with several cooling-phase estimates, including a novel two-parameter correlation depending on the final baryonic PNS mass and the time of shock revival. We find that the predicted DSNB event rate at Super-Kamiokande can vary by a factor of ~2–3 depending on the cooling-phase treatment. Here we also find that except for one cooling estimate, the range in predicted DSNB events is largely driven by the uncertainty in the neutrino mean energy. With a good understanding of the late-time neutrino emission, more precise DSNB estimates can be made for the next generation of DSNB searches.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Connecting GRBs from binary neutron star mergers to nuclear properties of neutron stars

The fate of the binary neutron star (NS) merger remnants hinges sensitively upon the NS equation of state and the threshold mass, M ls , that separates a long-lived from a short-lived NS remnant. The nature of the electromagnetic counterparts is also influenced by the remnant type, particularly in determining whether a gamma-ray burst from a compact binary merger (cbGRB) is of short or long duration. We propose a novel approach to probe Mls by linking it to the estimated observed ratio of long to short cbGRBs. We find that current observations broadly favor a relatively high value for this transition, M ls ≃ 1.3M TOV , for which M TOV ≲ 2.6M ⊙ , consistent with numerical simulations, as also shown here. Furthermore, our results disfavor nuclear physics scenarios that would lead to catastrophic pressure loss at a few times nuclear density and temperatures of tens of MeV, leading to a rapid gravitational collapse of binaries with total mass M ≲ 1.3M TOV . Future individual gravitational wave events with on-axis cbGRBs can further bound Mls.

79 ASTRONOMY AND ASTROPHYSICS↗

Mechanism of endosomal escape by p H -responsive nucleic-acid vectors

Successful intracellular delivery of nucleic acids (NAs) hinges on many factors, one of them being NAs’ efficacious escape from endosomes. As competent NA vectors, pH-responsive gemini surfactants (GSs) might achieve high efficacy by facilitating endosomal escape. However, how the GSs assist the escape remains debated as many proposed mechanisms still lack experimental support, which hinders replication and further improvement of the efficient delivery. Here, via UV, fluorescence spectroscopy, and small-angle neutron scattering (SANS), we examined a pH-responsive GS's and a pH-unresponsive GS's capabilities to compact DNA and withstand binding competition, and their interactions with model endosomal and lysosomal membranes, at varied pHs. Acidification-driven enhancement of DNA-compaction capability and of stability against binding competition were found specific to the pH-responsive GS. Alongside the pH-responsive GS's structural perturbation to the membranes as observed with SANS, the features suggest that pH-responsive GSs facilitate endosomal escape by releasing excess GS molecules from DNA-GS complexes upon acidification in endosome maturation, with the released GS molecules disrupting endosomal and lysosomal membranes and thereby assisting the escape. Here a general design principle for NA vectors is proposed on the basis of this experimental finding.

59 BASIC BIOLOGICAL SCIENCES↗

Inference-Based Quantum Sensing

In a standard quantum sensing (QS) task one aims at estimating an unknown parameter θ, encoded into an n-qubit probe state, via measurements of the system. The success of this task hinges on the ability to correlate changes in the parameter to changes in the system response $\mathscr{R}$⁡(θ) (i.e., changes in the measurement outcomes). For simple cases the form of $\mathscr{R}$⁡(θ) is known, but the same cannot be said for realistic scenarios, as no general closed-form expression exists. Here, in this Letter, we present an inference-based scheme for QS. We show that, for a general class of unitary families of encoding, $\mathscr{R}$⁡(θ) can be fully characterized by only measuring the system response at 2⁢n+1 parameters. This allows us to infer the value of an unknown parameter given the measured response, as well as to determine the sensitivity of the scheme, which characterizes its overall performance. We show that inference error is, with high probability, smaller than δ, if one measures the system response with a number of shots that scales only as Ω⁢(log 3 ⁡(n)/δ 2 ). Furthermore, the framework presented can be broadly applied as it remains valid for arbitrary probe states and measurement schemes, and, even holds in the presence of quantum noise. We also discuss how to extend our results beyond unitary families. Finally, to showcase our method we implement it for a QS task on real quantum hardware, and in numerical simulations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Radiative Corrections to Superallowed β Decays in Effective Field Theory

The accuracy of V u d determinations from superallowed β decays critically hinges on control over radiative corrections. Recently, substantial progress has been made on the single-nucleon, universal corrections, while nucleus-dependent effects, typically parametrized by a quantity δ NS , are much less well constrained. Here, we lay out a program to evaluate this correction from effective field theory (EFT), highlighting the dominant terms as predicted by the EFT power counting. Moreover, we compare the results to a dispersive representation of δ NS and show that the expected momentum scaling applies even in the case of low-lying intermediate states. Our EFT framework paves the way toward calculations of δ NS and thereby addresses the dominant uncertainty in V u d . Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

High-throughput determination of Hubbard $U$ and Hund $J$ values for transition metal oxides via the linear response formalism

DFT+U provides a convenient, cost-effective correction for the self-interaction error (SIE) that arises when describing correlated electronic states using conventional approximate density functional theory (DFT). The success of a DFT+U(+J) calculation hinges on the accurate determination of its Hubbard U and Hund J parameters, and the linear response (LR) methodology has proven to be computationally effective and accurate for calculating these parameters. This study provides a high-throughput computational analysis of the U and J values for transition metal d-electron states in a representative set of over 1000 magnetic transition metal oxides (TMOs), providing a frame of reference for researchers who use DFT+U to study transition metal oxides. In order to perform this high-throughput study, an ATOMATE workflow is developed for calculating U and J values automatically on massively parallel supercomputing architectures. Here, to demonstrate an application of this workflow, the spin-canting magnetic structure and unit cell parameters of the multiferroic olivine LiNiPO4 are calculated using the computed Hubbard U and Hund J values for Ni-d and O-p states, and are compared with experiment. Both the Ni-d U and J corrections have a strong effect on the Ni-moment canting angle. Additionally, including a O-pU value results in a significantly improved agreement between the computed lattice parameters and experiment

36 MATERIALS SCIENCE↗

Learning to Predict Arbitrary Quantum Processes

We present an efficient machine-learning (ML) algorithm for predicting any unknown quantum process ℰ over 𝑛 qubits. For a wide range of distributions 𝒟 on arbitrary 𝑛-qubit states, we show that this ML algorithm can learn to predict any local property of the output from the unknown process ℰ, with a small average error over input states drawn from 𝒟. The ML algorithm is computationally efficient even when the unknown process is a quantum circuit with exponentially many gates. Our algorithm combines efficient procedures for learning properties of an unknown state and for learning a low-degree approximation to an unknown observable. The analysis hinges on proving new norm inequalities, including a quantum analogue of the classical Bohnenblust-Hille inequality, which we derive by giving an improved algorithm for optimizing local Hamiltonians. Numerical experiments on predicting quantum dynamics with evolution time up to 10 6 and system size up to 50 qubits corroborate our proof. Overall, our results highlight the potential for ML models to predict the output of complex quantum dynamics much faster than the time needed to run the process itself.

quantum computation↗

Monomeric crystal structure of the vaccine carrier protein CRM 197 and implications for vaccine development

CRM 197 is a genetically detoxified mutant of diphtheria toxin (DT) that is widely used as a carrier protein in conjugate vaccines. Protective immune responses to several bacterial diseases are obtained by coupling CRM 197 to glycans from these pathogens. Wild-type DT has been described in two oligomeric forms: a monomer and a domain-swapped dimer. Their proportions depend on the chemical conditions and especially the pH, with a large kinetic barrier to interconversion. A similar situation occurs in CRM 197 , where the monomer is preferred for vaccine synthesis. Despite 30 years of research and the increasing application of CRM 197 in conjugate vaccines, until now all of its available crystal structures have been dimeric. Here, CRM 197 was expressed as a soluble, intracellular protein in an Escherichia coli strain engineered to have an oxidative cytoplasm. The purified product, called EcoCRM, remained monomeric throughout crystallization. The structure of monomeric EcoCRM is reported at 2.0 Å resolution with the domain-swapping hinge loop (residues 379–387) in an extended, exposed conformation, similar to monomeric wild-type DT. The structure enables comparisons across expression systems and across oligomeric states, with implications for monomer–dimer interconversion and for the optimization of conjugation.

60 APPLIED LIFE SCIENCES↗

3D domain swapping in the TIM barrel of the α subunit of Streptococcus pneumoniae tryptophan synthase

Tryptophan synthase catalyzes the last two steps of tryptophan biosynthesis in plants, fungi and bacteria. It consists of two protein chains, designated α and β, encoded by trpA and trpB genes, that function as an αββα complex. Structural and functional features of tryptophan synthase have been extensively studied, explaining the roles of individual residues in the two active sites in catalysis and allosteric regulation. TrpA serves as a model for protein-folding studies. In 1969, Jackson and Yanofsky observed that the typically monomeric TrpA forms a small population of dimers. Dimerization was postulated to take place through an exchange of structural elements of the monomeric chains, a phenomenon later termed 3D domain swapping. The structural details of the TrpA dimer have remained unknown. Here, the crystal structure of the Streptococcus pneumoniae TrpA homodimer is reported, demonstrating 3D domain swapping in a TIM-barrel fold for the first time. The N-terminal domain comprising the H0–S1–H1–S2 elements is exchanged, while the hinge region corresponds to loop L2 linking strand S2 to helix H2′. The structural elements S2 and L2 carry the catalytic residues Glu52 and Asp63. As the S2 element is part of the swapped domain, the architecture of the catalytic apparatus in the dimer is recreated from two protein chains. The homodimer interface overlaps with the α–β interface of the tryptophan synthase αββα heterotetramer, suggesting that the 3D domain-swapped dimer cannot form a complex with the β subunit. In the crystal, the dimers assemble into a decamer comprising two pentameric rings.

3D domain swapping↗

How Distinct Structural Flexibility within SARS-CoV-2 Spike Protein Reveals Potential Therapeutic Targets

The emergence and rapid worldwide spread of the novel coronavirus disease, COVID-19, has prompted concerted efforts to find successful treatments. The causative virus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), uses its spike (S) protein to gain entry into host cells. Therefore, the S protein presents a viable target to develop a directed therapy. Here, we deployed an integrated artificial intelligence with all-atom molecular dynamics simulation approach to provide new details of the S protein structure. Based on a comprehensive structural analysis of S proteins from SARS-CoV-2 and previous human coronaviruses, we found that the protomer state of S proteins is structurally flexible. Without the presence of a stabilizing beta sheet from another protomer chain, two regions in the S2 domain and the hinge connecting the S1 and S2 subunits lose their secondary structures. Interestingly, the region in the S2 domain was previously identified as an immunodominant site in the SARS-CoV-1 S protein. We anticipate that the molecular details elucidated here will assist in effective therapeutic development for COVID-19.

Chen, Serena↗

Understanding Quantum Control Processor Capabilities and Limitations through Circuit Characterization

Continuing the scaling of quantum computers hinges on building classical control hardware pipelines that are scalable, extensible, and provide real time response. The instruction set architecture (ISA) of the control processor provides functional abstractions that map high-level semantics of quantum programming languages to low-level pulse generation by hardware. Here, we provide a methodology to quantitatively assess the effectiveness of the ISA to encode quantum circuits for intermediate-scale quantum devices with O(10 2 ) qubits. The characterization model that we define reflects performance, the ability to meet timing constraint implications, scalability for future quantum chips, and other important considerations making them useful guides for future designs. Using our methodology, we propose scalar (QUASAR) and vector (qV) quantum ISAs as extensions and compare them with other ISAs in metrics such as circuit encoding efficiency, the ability to meet real-time gate cycle requirements of quantum chips, and the ability to scale to more qubits.

97 MATHEMATICS AND COMPUTING↗

Novel Technique for Developing Linearized Convex System Models from Experimentally Derived Data

This paper presents a novel technique for generating a convex system model from an experimentally derived data set which features variance among repeated measurements. The convex system model developed as a test case characterizes the dynamic system losses of a vanadium redox flow battery as a function of the active power output and the battery state of charge. The technique hinges on a pre-cleaning via clustering procedure which precedes the formation of a planar convex hull comprised of triangular simplices. The clustering procedure efficiently reduces the experimental data set while mitigating variance among repeated measurements and removes outliers. Ultimately, the lower evelope of the planar convex hull serves as the desired convex system model. The proposed technique reduces systematic model error which is otherwise present when directly developing a planar convex hull model based on an unreduced data set.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Molecular Symmetry in VQE: A Dual Approach for Trapped-Ion Simulations of Benzene

Understanding complex chemical systems—such as biomolecules, catalysts, and novel materials—is a central goal of quantum simulations. Near-term strategies hinge on the use of variational quantum eigensolver (VQE) algorithms combined with a suitable ansatz. However, straightforward application of many chemically-inspired ansatze yields prohibitively deep circuits. In this work, we employ several circuit optimization methods tailored for trapped-ion quantum devices to enhance the feasibility of intricate chemical simulations. The techniques aim to lessen the depth of the unitary coupled cluster with singles and doubles (uCCSD) ansatz's circuit compilation, a considerable challenge on current noisy quantum devices. Furthermore, we use symmetry-inspired classical post-selection methods to further refine the outcomes and minimize errors in energy measurements, without adding quantum overhead. Our strategies encompass optimal mapping from orbital to qubit, term reordering to minimize entangling gates, and the exploitation of molecular spin and point group symmetry to eliminate redundant parameters. The inclusion of error mitigation via post-selection based on known molecular symmetries improves the results to near milli-Hartree accuracy. These methods, when applied to a benzene molecule simulation, enabled the construction of an 8-qubit circuit with 69 two-qubit entangling operations, pushing the limits for variational quantum eigensolver (VQE) circuits executed on quantum hardware to date. 1 1 This manuscript has been authored in part by UT-Battelle, LLC, under contract DE-AC05-000R22725 with the US Department of Energy (DOE). The publisher acknowledges the US government license to provide public access under the DOE Public Access Plan(https://energy.gov/doe-public-access-plan).

Goings, Joshua↗

Online State Estimation for Time-Varying Systems

The paper investigates the problem of estimating the state of a time-varying system with a linear measurement model; in particular, the paper considers the case where the number of measurements available can be smaller than the number of states. In lieu of a batch linear least-squares (LS) approach well-suited for static networks, where a sufficient number of measurements could be collected to obtain a full-rank design matrix the paper proposes an online algorithm to estimate the possibly time-varying state by processing measurements as and when available. The design of the algorithm hinges on a generalized LS cost augmented with a proximal-point-type regularization. With the solution of the regularized LS problem available in closed-form, the online algorithm is written as a linear dynamical system where the state is updated based on the previous estimate and based on the new available measurements. Conditions under which the algorithmic steps are in fact a contractive mapping are shown, and bounds on the estimation error are derived for different noise models. Numerical simulations are provided to corroborate the analytical findings.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Enhancing Short-Term Flexibility through Characterization of HVDC Transmission Systems

Efficient power grid operation hinges on maintaining safety and reliability through adaptable system flexibility standards. However, in a future power grid characterized by extensive renewable energy integration, conventional system flexibility and predetermined requirements may falter under extreme conditions. This paper addresses the formidable challenge of sustaining secure and dependable power grid operations under these circumstances, emphasizing the role of controllable high voltage direct current (HVdc) transmission systems in amplifying overall system flexibility and tackling operational complexities. To quantitatively assess short-term flexibility and its associated economic benefits from HVdc within specific regions, we propose a Power Flow Distribution Factors (PTDFs) based approach. This methodology takes into account both dispatchable generators and HVdc systems, pinpointing their contributions. Through an analysis of the Western Electricity Coordinating Council (WECC) system, we demonstrate the practical application of this approach to scrutinize the impacts of existing and future HVdc lines.

Operational Flexibility, Multi-terminal HVdc, tran↗