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At least 361 records · Page 20

Nexus of thermal resilience and energy efficiency in buildings: A case study of a nursing home

Extreme weather events become more frequent and severe due to climate change. Although energy efficiency technologies can influence thermal resilience of buildings, they are traditionally studied separately, and their interconnections are rarely quantified. This study developed a methodology of modeling and analysis to provide insights into the nexus of thermal resilience and energy efficiency of buildings. In this work, we conducted a case study of a real nursing home in Florida, where 12 patients died during Hurricane Irma in 2017 due to HVAC system power loss, to understand and quantify how passive and active energy efficiency measures (EEMs) can improve thermal resilience to reduce heat-exposure risk of patients. Results show that passive measures of opening windows and doors for natural ventilation, as well as miscellaneous load reduction, are very effective in eliminating the extreme dangerous occasions. However, to maintain safe conditions, active measures such as on-site power generators and thermal storage are also needed. The nursing home was further studied by changing its location to two other cities: San Francisco (mild climate) and Chicago (cold winter and hot summer). Results revealed that the EEMs' impacts on thermal resilience vary significantly by climate and building characteristics. The study also estimated the costs of EEMs to help stakeholders prioritize the measures. Passive measures that may not save energy may greatly improve thermal resilience, and thus should be considered in building design or retrofit. Findings from this study indicate energy efficiency technologies should be evaluated not only by their energy savings performance but also by their influence on a building's resilience to extreme weather events.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Prevalence of Self-Reported Voice Concerns and Associated Risk Markers in a Nonclinical Sample of Military Service Members

Introduction: Difficult communication environments are common in military settings, and effective voice use can be critical to mission success. This study aimed to estimate the prevalence of self-reported voice disorders among U.S. military service members and to identify factors that contribute to their voice concerns. Method: A nonclinical sample of 4,123 active-duty service members was recruited across Department of Defense hearing conservation clinics. During their required annual hearing evaluation, volunteers provided responses to voice-related questions including a slightly adapted version of the Voice Handicap Index-10 (VHI-10) as part of a larger survey about communication issues. Changepoint detection was applied to age and years of service to explore cohort effects in the reporting of voice concerns. Logistic regression analyses examined multiple available factors related to communication to identify factors associated with abnormal results on the VHI-10. Results: Among the respondents, 41% reported experiencing vocal hoarseness or fatigue at least several times per year, and 8.2% ( n = 336) scored above the recommended abnormal cut-point value of 11 on the VHI-10. Factors independently associated with the greatest risk for self-reported voice concerns were sex (female), cadmium exposure, vocal demands (the need for a strong, clear voice), and auditory health measures (frequency of experiencing temporary threshold shifts; self-reported hearing difficulties). Conclusions: Based on self-reported voice concerns and false negative rates reported in the literature, the prevalence of dysphonia in a large sample of active-duty service members is estimated to be 11.7%, which is higher than that in the general population. Certain predictors for voice concerns were expected based on previous literature, like female sex and voice use, but frequency of temporary threshold shifts and exposure to cadmium were surprising. The strong link between voice and auditory problems has particular implications regarding the need for effective communication in high-noise military and other occupational environments.

Audiology & Speech-Language Pathology↗

Time evolution of a pumped molecular magnet—A time-resolved inelastic neutron scattering study

Introducing an experimental technique of time-resolved inelastic neutron scattering (TRINS), we explore the time-dependent effects of resonant pulsed microwaves on the molecular magnet Cr 8 F 8 Piv 16 . The octagonal rings of magnetic Cr 3+ atoms with antiferromagnetic interactions form a singlet ground state with a weakly split triplet of excitations at 0.8 meV. A 4.6 tesla field was applied to tune the splitting between two members of the triplet excited level |1$\rangle$ ↔ |2$\rangle$ to resonance with 105 GHz (0.434 meV) microwaves. The time-dependent occupations of the ground state |0$\rangle$, lower lying levels |1$\rangle$ and |2$\rangle$, and higher energy states |λ ≥ 3$\rangle$ were extracted during and after 20 s long microwave pulses incident along the (101) direction of a Cr 8 F 8 Piv 16 crystal held at 1.9 K. At significantly elevated spin temperatures, we found underpopulation relative to thermal equilibrium of |2$\rangle$ and spin-lattice thermalization time scales ranging from 1.6(2) s to 5.7(2) s depending on the power level. This contrasts with the relaxation time τ 1 (T → 0) = 27(5) 𝛍 s inferred for |2$\rangle$ from in situ Electron Spin Resonance measurements. By probing a broad range of excited states during intense microwave pumping, TRINS thus provides a first view of long lived excited states in a molecular antiferromagnet.

Science & Technology - Other Topics↗

Multi-criteria thermal resilience certification scheme for indoor built environments during heat waves

With climate change, the indoor built environment is expected to significantly influence the occupant's safety and well-being. A novel multi-criteria thermal resilience certification scheme for indoor built environments during extreme heat events is proposed in this paper. The certification scheme considers overheating, thermal comfort, heat stress, and hygrothermal discomfort in built environments. These criteria are quantified using key performance indicators like indoor overheating degree, hours of exceedance, wet-bulb globe temperature, and heat index, respectively. This scheme is developed based on existing best practices like standards, rating systems, and literature. The scheme is implemented on a benchmark building energy performance model for detached post-World War II dwellings in Belgium as a case study using weather data measured from the City of Brussels. The indoor overheating in the reference dwelling is assessed with a static threshold of 27 °C for the bedrooms and adaptive thresholds for other areas. The analysis found that the building performance is within the defined threshold levels throughout the heat wave duration for all criteria. Therefore, the reference dwelling got a maximum attainable score of four points and is rated five-star for thermal resilience during heat waves. The proposed certification scheme is intended as a standardized framework and highlights the need for further revisions in building performance policies and guidelines.

Climate change↗

Data-Enabled Predictive Control for Building HVAC Systems

Model predictive control is widely used as a control technology for the computation of optimal control inputs of building heating, ventilating, and air conditioning (HVAC) systems. However, both the benefits and widespread adoption of model predictive control (MPC) are hindered by the effort of model creation, calibration, and accuracy of the predictions. In this paper, we apply the data-enabled predictive control (DeePC) algorithm for designing controls for building HVAC systems. The algorithm solely depends on input/output data from the system to predict future state trajectories without the need for system identification. The algorithm relies on the idea that a vector space of all input–output trajectories of a discrete-time linear time-invariant (LTI) system is spanned by time-shifts of a single measured trajectory, given the input signal is persistently exciting. Closed-loop simulations using EnergyPlus are performed to demonstrate the approach. The simulated building modeled in EnergyPlus is a modified commercial large office prototype building served by an air handling unit-variable air volume HVAC system. Temperature setpoints of zones are used as control variables to minimize the HVAC energy cost of the building considering a time-of-use electricity rate structure. Furthermore, sensitivity analysis is conducted to gain insights into the effect of parameter tuning on DeePC performance. Simulation results are used to illustrate the performance of the algorithm and compare the algorithm with model-based MPC and occupancy-based setpoint controller. Overall, DeePC achieves similar performance compared to MPC for lower engineering effort.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Human Factors and Technologies Design to Improve User Acceptance of Pooled Rideshare for Increasing Transportation System Energy Efficiency

This multi-year project delivered a comprehensive, human-factors-driven framework to understand, model, and improve pooled rideshare (PR) adoption in the United States. Through three large-scale national survey studies involving more than 16,000 participants across multiple cities and demographic groups, the research established one of the most extensive datasets to date on user perceptions, behavioral barriers, and service expectations related to pooled rideshare. These data revealed key human factors barriers of user acceptance of PR and suggested potential actionable experience optimizations that could lead to increased PR usage. This foundational knowledge guided the development of novel human-factors models and behavioral choice models that quantify how psychological, demographic, and trip-level factors influence willingness to pool. Building on these empirical insights, the project developed advanced behavioral modeling tools, including mixed logit and integrated choice and latent variable models, to capture both observable and latent influences on PR adoption. These models significantly improved the ability to predict riders’ acceptance of pooled trips, explaining choice heterogeneity through latent constructs such as safety, service experience, privacy concerns, time sensitivity, and environmental attitudes. Together, these models provide a robust analytical foundation for designing PR systems that more effectively meet user needs. The project translated human-factors insights and behavioral models into actionable technology innovations by extending POLARIS—an agent-based, activity-based travel simulation platform—into a fully functional pooled rideshare simulation environment. New PR modules, acceptance models, and regional scenarios were implemented for Greenville, SC and Austin, TX, enabling high-fidelity validation of algorithmic strategies under realistic demand and traffic conditions. The simulation platform supported the development and evaluation of adaptive discount-based assignment algorithms, enhanced willingness-to-pay formulations, demographic-aware incentive mechanisms, and a proactive joint assignment and repositioning strategy. Simulation results demonstrated substantial gains in pooling uptake, average vehicle occupancy, energy efficiency, and fleet profitability. In Greenville, pooling adoption more than doubled, while reductions in vehicle-miles traveled and energy consumption were significant. In Austin, pooling improvements were achieved with minimal service-quality trade-offs, and profitability increased across all fleet sizes. Through this research, we developed a comprehensive understanding of the human factors barriers that limit user acceptance of pooled rideshare services. These insights enabled the design of human-factors-aware pooled rideshare technologies that more effectively address user concerns and improve adoption rates. By integrating these models into an advanced agent-based simulation framework, we demonstrated that higher adoption of pooled rideshare can lead to measurable improvements in energy efficiency and system performance. Together, these contributions establish a validated pathway from human-centered analysis to technology development and energy-saving outcomes, supporting national goals for more sustainable and efficient mobility systems.

Jia, Yunyi↗

Low Temperature CO 2 Hydrogenation on Unsupported Mo 2 C Catalysts

CO 2 hydrogenation to methanol, a key reaction for decarbonizing the fuel and chemical industries, requires catalyst formulations that hydrogenate CO 2 selectively to methanol at temperatures where methanol conversion is not significantly equilibrium limited (<423 K). Herein we report continuous CO 2 hydrogenation at low temperatures (348-408 K, H 2 /CO 2 = 0.1-50, 5-35 bar) with high selectivity to methanol (up to ca. 80%) over unsupported β-Mo 2 C catalysts. Active site density quantification via titration with trifluoroacetic acid at reaction temperatures enables an assessment of site-specific rates. Methanation and reverse water gas shift (RWGS) occur concurrently with methanol synthesis during CO 2 hydrogenation over Mo 2 C. Reaction pathway analysis, product cofeeds, and reversibility formalisms show that all products form through primary reaction pathways from CO 2 , but secondary reactions of CO contribute significantly to rates of methanation. Dependences of forward rates on reactant and product concentration determined by independently varying the CO 2 , H 2 , CO, H 2 O, CH 3 OH, and CH 4 pressure in conjunction with reversibility formalisms reveal that all products form through H-assisted CO 2 activation and involve partially hydrogenated CO 2 -derived intermediates. Here, these inferences were verified by quantitative agreement between measured site-time yields and site-time yields predicted by closed form kinetic rate expressions in an integral reactor model over widely varying conditions (85-2000 kPa H 2 , 80-1500 kPa CO 2 , 0-45 kPa H 2 O, 0-21 kPa CO, 0-25 kPa CH 3 OH, 0-75 kPa CH 4 , 5-87 mol Mo s s mol CO 2 -1 ). Coverages calculated based on the kinetic model reveal that the Mo 2 C surface is covered with bidentate CO- and CO 2 -derived intermediates of the stoichiometry H 2 CO 2 and H 2 CO, indicating that H 2 and CO x do not compete for surface occupancy but instead adsorb cooperatively to form partially hydrogenated intermediates. Hydrogenation of the CO-derived H 2 CO** intermediate favors methanation, while hydrogenation of CO 2 -derived H 2 CO 2 ** favors methanol synthesis. Together, these findings demonstrate the ability of unsupported Mo 2 C to catalyze the hydrogenation of CO 2 to methanol at low temperatures and provide insight into the reaction network and mechanisms involved in its formation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Exploiting non-linear scales in galaxy–galaxy lensing and galaxy clustering: A forecast for the dark energy survey

ABSTRACT The combination of galaxy–galaxy lensing (GGL) and galaxy clustering is a powerful probe of low-redshift matter clustering, especially if it is extended to the non-linear regime. To this end, we use an N-body and halo occupation distribution (HOD) emulator method to model the redMaGiC sample of colour-selected passive galaxies in the Dark Energy Survey (DES), adding parameters that describe central galaxy incompleteness, galaxy assembly bias, and a scale-independent multiplicative lensing bias Alens. We use this emulator to forecast cosmological constraints attainable from the GGL surface density profile ΔΣ(rp) and the projected galaxy correlation function wp, gg(rp) in the final (Year 6) DES data set over scales $r_p=0.3\!-\!30.0\, h^{-1} \, \mathrm{Mpc}$. For a $3{{\ \rm per\ cent}}$ prior on Alens we forecast precisions of $1.9{{\ \rm per\ cent}}$, $2.0{{\ \rm per\ cent}}$, and $1.9{{\ \rm per\ cent}}$ on Ωm, σ8, and $S_8 \equiv \sigma _8\Omega _m^{0.5}$, marginalized over all halo occupation distribution (HOD) parameters as well as Alens. Adding scales $r_p=0.3\!-\!3.0\, h^{-1} \, \mathrm{Mpc}$ improves the S8 precision by a factor of ∼1.6 relative to a large scale ($3.0\!-\!30.0\, h^{-1} \, \mathrm{Mpc}$) analysis, equivalent to increasing the survey area by a factor of ∼2.6. Sharpening the Alens prior to $1{{\ \rm per\ cent}}$ further improves the S8 precision to $1.1{{\ \rm per\ cent}}$, and it amplifies the gain from including non-linear scales. Our emulator achieves per cent-level accuracy similar to the projected DES statistical uncertainties, demonstrating the feasibility of a fully non-linear analysis. Obtaining precise parameter constraints from multiple galaxy types and from measurements that span linear and non-linear clustering offers many opportunities for internal cross-checks, which can diagnose systematics and demonstrate the robustness of cosmological results.

79 ASTRONOMY AND ASTROPHYSICS↗

Electrochemical Control of Magnetism on the Breathing Kagome Network of Li x ScMo 3 O 8

Controlling properties within a given functional inorganic material structure type is often accomplished through tuning the electronic occupation, which is in turn dictated by the elemental composition determined at the time of material preparation. We employ electrochemical control of the lithium content, with associated electronic occupancy control, to vary the magnetic properties of a material where a kagome-derived network of Mo 3 triangles carry the spin. In this case, Li is electrochemically inserted into LiScMo 3 O 8 , a layered compound containing a breathing Mo kagome network. Up to two additional Li can be inserted into LiScMo 3 O 8 , transforming it into Li 3 ScMo 3 O 8 . Li 2 ScMo 3 O 8 prepared by electrochemical lithiation is compared to the quantum spin liquid candidate compound Li 2 ScMo 3 O 8 prepared through high-temperature solid-state methods, which has a slightly different structural stacking sequence but a similar kagome-derived network. Magnetic measurements are supported by first-principles calculations, showing that electrons remain localized on the Mo clusters throughout the doping series. As x is varied in Li x ScMo 3 O 8 , the measurements and calculations reveal the evolution from a diamagnetic band insulator at x = 1 to a geometrically frustrated magnet at x = 2, back to a diamagnetic insulator at x = 3. These results indicate a likelihood of strong coupling between the degree of Li disorder and charge/magnetic ordering over the Mo 3 clusters.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Puzzling 𝐵⁡(𝐸⁢2;0 + → 2 + ) strength in the proton dripline nucleus 36 Ca

Recent measurements of the 𝐸⁢2 transition rate from the ground state to the first 2 + excited state of the proton dripline nucleus 36 Ca show an unusual pattern when compared to its isotopic neighbor 38 Ca: despite having a higher 𝐸 𝑥 ⁡(2$^{+}_{1}$) excitation energy, the 𝐵⁡(𝐸⁢2;0$^{+}_{1}$ → 2$^{+}_{1}$) rate in 36 Ca is larger. The question that naturally arises is to what extent this observation can be attributed to the unbound character of the 2$^{+}_{1}$ state. To understand the influence of the continuum space on the low-energy properties of 36 Ca, we carried out Gamow shell model calculations that can account for the continuum coupling effects associated with the occupation of unbound 𝑓⁡𝑝 shells. We found that in the threshold 2 + state, 36 Ca is spatially diffused, which impacts the observed 𝐵⁡(𝐸⁢2) trend.

20 ≤ A ≤ 38↗

Challenges and Opportunities for Basic Efficiency Measures in Low-Income Homes: A Southeast Alaska Case Study

Juneau, Alaska is the state's capital city and has a renewable energy goal to reach 80% renewable energy for the space heating and transportation sectors by 2045. In practical terms, this indicates a need to electrify both sectors, to take advantage of the inexpensive hydropower available from the local electric utility, Alaska Energy Light & Power. In an effort to complement and enable electrification, researchers examined the feasibility to deploy storm windows via a case study of installing storm windows in two local low-income homes. Newer models of storm windows provide an extra layer of insulation over existing windows, while preserving operability and views. They can also improve comfort and reduce noise. Researchers worked with the regional housing authority and a local builder to install the storm windows and replace inoperable windows in the two houses in 2021, in addition to conducting pre- and post-installation air leakage tests, energy monitoring, and occupant interviews. The team encountered several challenges, including a lack of egress windows, energy data from a wide variety of heating systems, extremely leaky homes, and installation issues such as windows that were not square. These results point to several barriers to widespread deployment of storm windows in the area, but also open the door to opportunities to design deployment programs that improve safety as well as efficiency.

cold climate↗

Experimental evaluation of respiratory droplet spread to rooms connected by a central ventilation system

This article presents results from an experimental study to ascertain the transmissibility of the SARS-CoV-2 virus between rooms in a building that are connected by a central ventilation system. Respiratory droplet surrogates made of mucus and virus mimics were released in one room in a test building and measurements of concentration levels were made in other rooms connected via the ventilation system. The paper presents experimental results for different ventilation system configurations, including ventilation rate, filtration level (up to MERV-13), and fractional outdoor air intake. The most important finding is that respiratory droplets can and do transit through central ventilation systems, suggesting a mechanism for viral transmission (and COVID-19 specifically) within the built environment in reasonable agreement with well-mixed models. We also find the deposition of these droplets on room walls to be negligibly small. Furthermore, the energy use impact of the different configuration settings is also quantified to help inform intelligent building operation that can simultaneously address energy use and occupant health.

60 APPLIED LIFE SCIENCES↗

Ultra-Low SWaP CO 2 Sensing for Demand Control Ventilation (Final Report)

In this project PARC and Energy ETC aimed to develop an ultra-low cost, size, weight, and power (SWaP) printed CO 2 sensor system for occupancy detection to enable Demand Control Ventilation (DCV) on a per-room basis. The CO 2 sensor technology is based on the temperature variation when CO 2 reversibly physisorbs to a highly conductive and high surface area sorbent surface, and is compatible with integration with PARC innovations in printed sensors and flexible electronics, for which PARC is a globally leading research center. The printed CO 2 sensor itself is designed to be compatible with PARC’s “peel-and-stick” platform of ultra-low power, low-cost, distributed sensors, and to facilitate real-time DCV based on overall indoor air quality (IAQ). Previously, PARC has developed flexible hybrid electronics (FHE) compatible materials to measure humidity, temperature, light, strain, and gases such as carbon monoxide, methane, ammonia, and hydrogen sulfide. Through this project, PARC developed FHE-compatible materials to measure CO 2 . Thus, with one <$15 FHE “peel-and-stick” based sensor node, a building management system (BMS) will be able to capture a complete picture of the indoor environment. This includes IAQ, light, temperature, and other comfort factors that impact building operations. Combined with optimized DCV, this low-cost sensor capability can be a key enabler of annual primary energy savings of ~ 0.3-0.4 Quad in commercial buildings while ensuring healthy IAQ. Energy ETC is a leader in supplier-agnostic BMS deployments and will design the commissioning and deployment procedures to maximize system interoperability.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DESI mock challenge: Halo and galaxy catalogues with the bias assignment method

We present a novel approach to the construction of mock galaxy catalogues for large-scale structure analysis based on the distribution of dark matter halos obtained with effective bias models at the field level. We aim to produce mock galaxy catalogues capable of generating accurate covariance matrices for a number of cosmological probes that are expected to be measured in current and forthcoming galaxy redshift surveys (e.g. two- and three-point statistics). The construction of the catalogues shown in this paper is part of a mock-comparison project within the Dark Energy Spectroscopic Instrument (DESI) collaboration. We use the bias assignment method ( BAM ) to model the statistics of halo distribution through a learning algorithm using a few detailed N-body simulations, and approximated gravity solvers based on Lagrangian perturbation theory. We introduce cosmic-web-dependent corrections to modelling redshift-space distortions at the N-body level – both in the halo and galaxy distributions –, as well as a multi-scale approach for accurate assignment of halo properties. Using specific models of halo occupation distributions to populate halos, we generate galaxy mocks with the expected number density and central-satellite fraction of emission-line galaxies, which are a key target of the DESI experiment. BAM generates mock catalogues with per cent accuracy in a number of summary statistics, such as the abundance, the two- and three-point statistics of halo distributions, both in real and redshift space. In particular, the mock galaxy catalogues display ~3%-10% accuracy in the multipoles of the power spectrum up to scales of k ~ 0.4 h -1 Mpc. We show that covariance matrices of two- and three-point statistics obtained with BAM display a similar structure to the reference simulation. BAM offers an efficient way to produce mock halo catalogues with accurate two- and three-point statistics and is able to generate a variety of multi-tracer catalogues with precise covariance matrices of several cosmological probes. We discuss future developments of the algorithm towards mock production in DESI and other galaxy-redshift surveys.

79 ASTRONOMY AND ASTROPHYSICS↗

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.

97 MATHEMATICS AND COMPUTING↗

Coexistence of commensurate and incommensurate antiferromagnetic ground states in Co 𝑥 ⁢NbSe 2 single crystal

In Co 𝑥 ⁢NbSe 2 , crystal symmetry and cobalt site occupation drive the formation of two distinct magnetic phases. At 𝑥=1/4, the centrosymmetric structure (𝑃⁢6 3 /𝑚⁢𝑚⁢𝑐) promotes Co-Co interactions leading to the formation of an 𝐴-type antiferromagnetic structure phase with a transition temperature of 𝑇$^𝐴_𝑁$=169K. At 𝑥=1/3, the noncentrosymmetric structure (𝑃⁢6 3 ⁢22) induces a lower-temperature magnetic phase with 𝑇$^S_𝑁$=28K. We report the coexistence of both substructures within a superlattice, with a nuclear propagation vector of (1/3, 1/3, 0) relative to the host lattice. Single crystals of Co 0.28 ⁢NbSe 2 exhibit both magnetic transitions, with 𝑇$^𝐴_𝑁$ corresponding to the 𝑥∼1/4 phase and 𝑇$^S_𝑁$ corresponding to the 𝑥∼1/3 phase. Magnetic susceptibility and specific heat measurements confirm these transitions, although only the high-temperature 𝑇$^𝐴_𝑁$ phase significantly affects resistivity. We successfully isolate each phase in powder samples, while single crystals with an intercalation ratio of 𝑥=0.28 display the coexistence of both phases in a single sample. Using single-crystal neutron diffraction, we solved the magnetic structure of the high-temperature centrosymmetric phase (𝑇$^𝐴_𝑁$), and neutron powder diffraction revealed the double-𝑞 magnetic structure of the low-temperature noncentrosymmetric phase (𝑇$^S_𝑁$).

RKKY interaction↗

Exploring HOD-dependent systematics for the DESI 2024 Full-Shape galaxy clustering analysis

We analyze the robustness of the DESI 2024 cosmological inference from the full shape of the galaxy power spectrum to uncertainties in the Halo Occupation Distribution (HOD) model of the galaxy-halo connection and the choice of priors on nuisance parameters. We assess variations in the recovered cosmological parameters across a range of mocks populated with different HOD models and find that shifts are often greater than 20% of the expected statistical uncertainties from the DESI data. We encapsulate the effect of such shifts in terms of a systematic covariance term, C HOD , and an additional diagonal contribution quantifying the impact of our choice of nuisance parameter priors on the ability of the effective field theory (EFT) model to correctly recover the cosmological parameters of the simulations. These two covariance contributions are designed to be added to the usual covariance term, C stat , describing the statistical uncertainty in the power spectrum measurement, in order to fairly represent these sources of systematic uncertainty. This novel approach should be more general and robust to the choice of model or additional external datasets used in cosmological fits than the alternative approach of adding systematic uncertainties to the recovered marginalised parameter posteriors. We compare the approaches within the context of a fixed ΛCDM model and demonstrate that our method gives conservative estimates of the systematic uncertainty that nevertheless have little impact on the final posteriors obtained from DESI data.

79 ASTRONOMY AND ASTROPHYSICS↗