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At least 451 records · Page 25

Strong Constraints on Jet Quenching in Centrality-Dependent p + Pb Collisions at 5.02 TeV from ATLAS

Jet quenching is the process of color-charged partons losing energy via interactions with quark-gluon plasma droplets created in heavy-ion collisions. The collective expansion of such droplets is well described by viscous hydrodynamics. Similar evidence of collectivity is consistently observed in smaller collision systems, including p p and p + Pb collisions. In contrast, while jet quenching is observed in Pb + Pb collisions, no evidence has been found in these small systems to date, raising fundamental questions about the nature of the system created in these collisions. The ATLAS experiment at the Large Hadron Collider has measured the yield of charged hadrons correlated with reconstructed jets in 0.36 nb -1 of p + Pb and 3.6 pb -1 of pp collisions at 5.02 TeV. The yields of charged hadrons with ${p}^{ch}_{T}$ > 0.5 GeV near and opposite in azimuth to jets with ${p}^{jet}_{T}$ > 30 or 60 GeV, and the ratios of these yields between p + Pb and pp collisions, I pPb , are reported. The collision centrality of p + Pb events is categorized by the energy deposited by forward neutrons from the struck nucleus. The I pPb values are consistent with unity within a few percent for hadrons with ${p}^{ch}_{T}$ > 4 GeV at all centralities. These data provide new, strong constraints that preclude almost any parton energy loss in central p + Pb collisions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Dark Matter Constraints from Isomeric 178⁢m Hf

In this article, we describe a first measurement of the radiation from a 178⁢m Hf sample to search for dark matter. The $\gamma$ flux from this sample, possessed by Los Alamos National Laboratory nuclear chemistry, was measured with a Ge detector at a distance of 1.2 m due to its high activity. We search for $\gamma$’s that cannot arise from the radioactive decay of 178⁢m Hf but might arise from the production of a nuclear state due to the inelastic scattering with dark matter. The limits obtained on this $\gamma$ flux are then translated into constraints on the parameter space of inelastic dark matter. Finally, we describe the potential reach of future studies with 178⁢m Hf.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Observation of the $γγ → ττ$ Process in $\mathrm{Pb + Pb}$ Collisions and Constraints on the $\tau$-Lepton Anomalous Magnetic Moment with the ATLAS Detector

This Letter reports the observation of τ-lepton pair production in ultraperipheral lead-lead collisions, Pb+Pb→Pb(γγ→ττ)Pb, and constraints on the τ-lepton anomalous magnetic moment, a τ . The dataset corresponds to an integrated luminosity of 1.44 nb -1 of LHC Pb+Pb collisions at $\sqrt{s_{NN}}$ =5.02 TeV recorded by the ATLAS experiment in 2018. Selected events contain one muon from a τ-lepton decay, an electron or charged-particle track(s) from the other τ-lepton decay, little additional central-detector activity, and no forward neutrons. The γγ→ττ process is observed in Pb+Pb collisions with a significance exceeding 5 standard deviations, and a signal strength of μ ττ =1.03$^{+0.06}_{-0.05}$ assuming the Standard Model value for a τ . To measure a τ , a template fit to the muon transverse-momentum distribution from τ-lepton candidates is performed, using a dimuon (γγ→μμ) control sample to constrain systematic uncertainties. The observed 95% confidence-level interval for aτ is -0.057 < a τ < 0.024.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Reanalysis of the 𝛽− $\overline{v}$ 𝑒 Angular Correlation Measurement from the aSPECT Experiment with New Constraints on Fierz Interference

On the basis of revisions of some of the systematic errors, we reanalyzed the electron-antineutrino angular correlation (𝑎 coefficient) in free neutron decay inferred from the recoil energy spectrum of the protons which are detected in 4⁢𝜋 by the aSPECT spectrometer. With 𝑎=−0.104 02⁢(82), the new value differs only marginally from the one published in 2020. Here, the experiment also has sensitivity to 𝑏, the Fierz interference term. From a correlated (𝑏,𝑎) fit to the proton recoil spectrum, we derive a limit of 𝑏 =−0.0098⁢(193) which translates into a somewhat improved 90% confidence interval region of −0.041 ≤ 𝑏 ≤ 0.022 on this hypothetical term. Tighter constraints on 𝑏 can be set from a combined analysis of the PERKEO III (𝛽 asymmetry) and aSPECT measurement which suggests a finite value of 𝑏 with 𝑏 (𝑐) =−0.0181 ± 0.0065 deviating by 2.82⁢𝜎 from the standard model.

Beta decay↗

Constraints on Covariant Dark-Matter–Nucleon Effective Field Theory Interactions from the First Science Run of the LUX-ZEPLIN Experiment

The LUX-ZEPLIN (LZ) experiment is a dual-phase xenon time project chamber operating in the Sanford Underground Research Facility in South Dakota, USA. We report on the results of a relativistic extension to the nonrelativistic effective field theory (NREFT) from a 5.5 t fiducial mass and 60 live days of exposure. We present constraints on couplings from covariant interactions arising from the coupling of vector, axial currents, and electric dipole moments of the nucleon to the magnetic and electric dipole moments of the weakly interacting massive particle which cannot be described by recasting previous results described by an NREFT. Using a profile-likelihood ratio analysis, in an energy region between 0 keV nr to 270 keV nr , we report 90% confidence level exclusion limits on the coupling strength of five interactions in both the isoscalar and isovector bases. Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Constraints on Local Primordial Non-Gaussianity with 3D Velocity Reconstruction from the Kinetic Sunyaev-Zeldovich Effect

The cosmic velocity field is an unbiased probe of the total matter distribution but is challenging to measure directly at intermediate and high redshifts. The large-scale velocity field imprints a signal in the cosmic microwave background (CMB) through the kinetic Sunyaev-Zeldovich (kSZ) effect. We perform the first 3D reconstruction of the large-scale velocity field from the kSZ effect by applying a quadratic estimator to CMB temperature maps and the 3D positions of galaxies. We do so by combining CMB data from the fifth data release of the Atacama Cosmology Telescope (in combination with Planck) and a spectroscopic galaxy sample from the Sloan Digital Sky Survey. We then measure the galaxy-velocity cross-power spectrum and detect the presence of the kSZ signal at a signal-to-noise ratio of 7.2⁢𝜎. Using this galaxy-velocity cross-correlation alone, we constrain the amplitude of local primordial non-Gaussianity finding 𝑓 NL =−9⁢0$^{+210}_{−350}$. In conclusion, this pathfinder measurement sets the stage for joint galaxy-CMB kSZ constraints to significantly enhance the 𝑓 NL information obtained from galaxy surveys through sample variance cancellation.

79 ASTRONOMY AND ASTROPHYSICS↗

New Constraints on Axionlike Particles with the NEON Detector at a Nuclear Reactor

We report new constraints on axionlike particles (ALPs) using data from the NEON experiment, which features 16.7 kg of NaI(Tl) target located 23.7 m from a 2.8 GW thermal power nuclear reactor. Analyzing a total exposure of 3063 kg · day , with 1596 kg · day during reactor-on and 1467 kg · day during reactor-off periods, we compared energy spectra to search for ALP-induced signals. No significant signal was observed, enabling us to set exclusion limits at the 95% confidence level. These limits probe previously unexplored regions of the ALP parameter space, particularly for axion masses ( m a ) near 1 MeV / c 2 . For ALP-photon coupling ( g a γ ), limits reach as low as 6.24 × 10 − 6 GeV − 1 at m a = 3.0 MeV / c 2 , while for ALP-electron coupling ( g a e ), limits reach 4.95 × 10 − 8 at m a = 1.02 MeV / c 2 . This Letter demonstrates the potential for future reactor experiments to probe unexplored ALP parameter space. Published by the American Physical Society 2025

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Revisiting the gluon density from the Balitsky-Kovchegov equation with kinematical constraints and large 𝑥 terms

We perform analysis of the small 𝑥 nonlinear evolution equation formulated in momentum space supplemented by higher order terms. The equation is defined in the wide range of transverse momentum and longitudinal momentum fractions extending previous studies performed in Kutak and Kwiecinski [Screening effects in the ultrahigh-energy neutrino interactions, Eur. Phys. J. C 29, 521 (2003).] and in Kutak and Stasto [Unintegrated gluon distribution from modified BK equation, Eur. Phys. J. C 41, 343 (2005).]. The linear part of the equation is motivated by the renormalization group improved small 𝑥 approach, which accounts for resummation of higher orders, and includes collinear splitting functions and kinematical constraints. The solution to the equation is then used to perform the fit to deep inelastic scattering reduced cross section data.

Perturbative QCD↗

Distributed Inertia Management Under Communication Constraints

This paper presents a framework for distributed inertia management based on consensus algorithm. We propose a methodology to achieve optimal operation of inertia sources such as distributed energy resources (DERs) and synchronous generators in real time. Additionally, we analyze the algorithm under communication constraints and evaluate its robustness under scenarios involving communication time delays and packet losses. The proposed approach is validated via simulations on a 4-node system test feeder, demonstrating its effectiveness and resilience.

Yadav, Ajay [ORNL] (ORCID:000000016111881X)↗

A Sparse and Low Rank Penalized Signal Decomposition Model with Constraints: Anomaly Detection in PV Systems

Recently, robust PCA has seen its wide application in various industries for its ability to perform the task of anomaly detection. The essence of robust PCA approach is to break down the signal into a low rank component and sparse component. In many applications, a simple breakdown of the signal without accounting for the signs of low rank components and sparse components would violate the physical constraints of the decomposed signal. In addition, often times, the signals in the real world collected for a long duration has smooth changes within a day and between days. As an example, the power signals collected in a photovoltaic (PV) system are cyclostationary, exhibiting these characteristics. Neglecting the smoothness of signals would result in miss detection of anomalous signals which are smooth within a day but non-smooth between days and vice versa. In this paper, we developed a signal decomposition approach for the purpose of anomaly detection based on the idea of low rank and sparse decomposition taking into consideration the signs of the decomposed low rank and sparse components and the within-day and between-day smooth changes in the original signals. The proposed unsupervised approach for fault detection eliminates the need for faulty samples required by other machine learning methods. It does not require the full I-V characteristics to work. Furthermore, there is no need for complex modelling of PV systems as in the case of power loss analysis. Using Monte Carlo simulations, we demonstrate the ability of our proposed approach for detecting anomalies of different duration and severity in PV systems.

14 SOLAR ENERGY↗

Online Optimization for Networked Distributed Energy Resources With Time-Coupling Constraints

This paper proposes a Lyapunov optimization-based online distributed (LOOD) algorithmic framework for active distribution networks (ADNs) with numerous photovoltaic inverters and inverter air conditionings (IACs). In the proposed scheme, ADNs can track an active power setpoint reference at the substation in response to transmission-level requests while concurrently minimizing the social utility loss and ensuring the security of voltages. Conventional distributed optimization methods are rarely feasible to track the optimal solutions in fast variable environments using a fine-grained sampling interval where the underlying optimization problem evolves with the iterations of the algorithms. In contrast, based on the framework of online convex optimization (OCO), the developed approach uses a distributed algebraic update to compute the next round decisions relying on the current feedback of measurements. Notably, the time-coupling constraints of IACs are decoupled for online implementation with Lyapunov optimization technique. An incentive scheme is tailored to coordinate the customer-owned assets in lieu of the direct control from network operators. Optimality and convergency are characterized analytically. Finally, we corroborate the proposed method on a modified version of 33-node test feeder. Benchmark tests show that the proposed method is computationally and economically efficient, and outperforming existing algorithms.

active distribution networks↗

Co-Optimization of Velocity and Charge-Depletion for Plug-In Hybrid Electric Vehicles: Accounting for Acceleration and Jerk Constraints

Abstract Recent advances in vehicle connectivity and automation technologies promote advanced control algorithms that co-optimize the longitudinal dynamics and powertrain operation of hybrid electric vehicles. Typically, a sequential optimization with the vehicle dynamics optimized followed by powertrain optimization is adopted to manage a number of complexities such as the inherent mixed-integer nature of the hybrid powertrain, the numerous state and control variables, the differing time scales of vehicle and powertrain subsystems, time-varying state constraints, and large horizon lengths. Instead, we solve the offline optimization problem in a centralize manner assuming exact knowledge of the lead vehicle's position over the entire trip by applying a discrete-time single shooting-based numerical approach, Discrete Mixed-Integer Shooting (DMIS), including a linearly increasing computational complexity to the problem horizon. In particular, the hierarchical problem structure is exploited to decompose the computationally intensive Hamiltonian minimization step into a set of low-dimensional optimizations. DMIS allows us to compute the direct fuel minimization problem including the vehicle and powertrain dynamics in a centralized manner to its full horizon while systematically tuning weighting factors that penalize passenger discomfort. For the first time, this study reveals that practically implemented sequential optimization exhibits similar fuel optimality as co-optimization when a certain level of passenger comfort is required.

Automation & Control Systems↗

Reducing the aerosol forcing uncertainty using observational constraints on warm rain processes

Global climate models (GCMs) disagree with other lines of evidence on the rapid adjustments of cloud cover and liquid water path to anthropogenic aerosols. Attempts to use observations to constrain the parameterizations of cloud processes in GCMs have failed to reduce the disagreement. We propose using observations sensitive to the relevant cloud processes rather than only to the atmospheric state and focusing on process realism in the absence of aerosol perturbations in addition to the process susceptibility to aerosols. We show that process-sensitive observations of precipitation can reduce the uncertainty on GCM estimates of rapid cloud adjustments to aerosols. The feasibility of an observational constraint depends on understanding the precipitation intensity spectrum in both observations and models and also on improving methods to compare the two.

54 ENVIRONMENTAL SCIENCES↗

Clumped isotope constraints on changes in latest Pleistocene hydroclimate in the northwestern Great Basin: Lake Surprise, California

Abstract During the Last Glacial Maximum (LGM) and subsequent deglaciation, the Great Basin in the southwestern United States was covered by numerous extensive closed-basin lakes, in stark contrast with the predominately arid climate observed today. This transition from lakes in the Late Pleistocene to modern aridity implies large changes in the regional water balance. Whether these changes were driven by increased precipitation rates due to changes in atmospheric dynamics, decreased evaporation rates resulting from temperature depression and summer insolation changes, or some combination of the two remains uncertain. The factors contributing to these large-scale changes in hydroclimate are critical to resolve, given that this region is poised to undergo future anthropogenic-forced climate changes with large uncertainties in model simulations for the 21st century. Furthermore, there are ambiguous constraints on the magnitude and even the sign of changes in key hydroclimate variables between the Last Glacial Maximum and the present day in both proxy reconstructions and climate model analyses of the region. Here we report thermodynamically derived estimates of changes in temperature, precipitation, and evaporation rates, as well as the isotopic composition of lake water, using clumped isotope data from an ancient lake in the northwestern Great Basin, Lake Surprise (California). Compared to modern climate, mean annual air temperature at Lake Surprise was 4.7 °C lower during the Last Glacial Maximum, with decreased evaporation rates and similar precipitation rates to modern. During the mid-deglacial period, the growth of Lake Surprise implied that the lake hydrologic budget briefly departed from steady state. Our reconstructions indicate that this growth took place rapidly, while the subsequent lake regression took place over several thousand years. Using models for precipitation and evaporation constrained from clumped isotope results, we determine that the disappearance of Lake Surprise coincided with a moderate increase in lake temperature, along with increasing evaporation rates outpacing increasing precipitation rates. Concomitant analysis of proxy data and climate model simulations for the Last Glacial Maximum are used to provide a robust means to understand past climate change, and by extension, predict how current hydroclimates may respond to expected future climate forcings. We suggest that an expansion of this analysis to more basins across a larger spatial scale could provide valuable insight into proposed climate forcings, and aid in climate model process depiction. Ultimately, our analysis highlights the importance of temperature-driven evaporation as a mechanism for lake growth and retreat in this region.

Geology↗

A Probabilistic Scheme for Semilinear Nonlocal Diffusion Equations with Volume Constraints

This work presents a probabilistic scheme for solving semilinear nonlocal diffusion equations with volume constraints and integrable kernels. The nonlocal model of interest is defined by a time-dependent semilinear partial integro-differential equation (PIDE), in which the integro-differential operator consists of both local convection-diffusion and nonlocal diffusion operators. Here, our numerical scheme is based on the direct approximation of the nonlinear Feynman–Kac formula that establishes a link between nonlinear PIDEs and stochastic differential equations. The exploitation of the Feynman–Kac representation avoids solving dense linear systems arising from nonlocal operators. Compared with existing stochastic approaches, our method can achieve first-order convergence after balancing the temporal and spatial discretization errors, which is a significant improvement of existing probabilistic/stochastic methods for nonlocal diffusion problems. Error analysis of our numerical scheme is established. The effectiveness of our approach is shown in two numerical examples. The first example considers a three-dimensional nonlocal diffusion equation to numerically verify the error analysis results. The second example presents a physics problem motivated by the study of heat transport in magnetically confined fusion plasmas.

97 MATHEMATICS AND COMPUTING↗

Experimental constraints on the properties of $P_c$ states

Using new experimental data on photoproduction and $\Lambda _b^0$ decays, we derive constraints on the properties of the LHCb $P_c$ states. We conclude that $P_c(4312)$, $P_c(4380)$ and $P_c(4440)$ can be described as $\Sigma _c\bar{D}$, $\Sigma _c^*\bar{D}$ and $\Sigma _c\bar{D}^*$ molecules, but that $P_c(4457)$ does not fit into the same picture. Based on the apparent absence of additional partner states, and the striking disparity between $\Lambda _c^+\bar{D}^0$ and $\Lambda _c^+\bar{D}^{*0}$ decays, we conclude that $P_c(4440)$ has $3/2^-$ quantum numbers. Using heavy-quark symmetry we predict large experimental signals for $P_c$ states in $\eta _c p K^-$, $\Lambda _c^+\bar{D}^{*0}K^-$, and $\Sigma _c^{(*)}\bar{D}K^-$. We also argue that current experimental data on photoproduction is almost at the level of sensitivity required to observe $P_c$ states.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

New constraints on heavy neutral leptons from Super-Kamiokande data

Abstract Heavy neutral leptons are predicted in many extensions of the Standard Model with massive neutrinos. If kinematically accessible, they can be copiously produced from kaon and pion decays in atmospheric showers, and subsequently decay inside large neutrino detectors. We perform a search for these long-lived particles using Super-Kamiokande multi-GeV neutrino data and derive stringent limits on the mixing with electron, muon and tau neutrinos as a function of the long-lived particle mass. We also present the limits on the branching ratio versus lifetime plane, which are helpful in determining the constraints in non-minimal models where the heavy neutral leptons have new interactions with the Standard Model.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Direct constraint on the Higgs–charm coupling from a search for Higgs boson decays into charm quarks with the ATLAS detector

A search for the Higgs boson decaying into a pair of charm quarks is presented. The analysis uses proton–proton collisions to target the production of a Higgs boson in association with a leptonically decaying W or Z boson. The dataset delivered by the LHC at a centre-of-mass energy of $\sqrt{s}$ = 13 TeV and recorded by the ATLAS detector corresponds to an integrated luminosity of 139 fb -1 . Flavour-tagging algorithms are used to identify jets originating from the hadronisation of charm quarks. The analysis method is validated with the simultaneous measurement of WW, WZ and ZZ production, with observed (expected) significances of 2.6 (2.2) standard deviations above the background-only prediction for the $(W/Z)Z( → c\bar{c})$ process and 3.8 (4.6) standard deviations for the $(W/Z)W(→cq)$ process. The $(W/Z)Z( → c\bar{c})$ search yields an observed (expected) upper limit of 26 (31) times the predicted Standard Model cross-section times branching fraction for a Higgs boson with a mass of 125 GeV, corresponding to an observed (expected) constraint on the charm Yukawa coupling modifier |$k_c$| < 8.5 (12.4), at the 95% confidence level. A combination with the ATLAS $(W/Z)H,H → b\bar{b}$ analysis is performed, allowing the ratio $k_c/k_b$ to be constrained to less than 4.5 at the 95% confidence level, smaller than the ratio of the b- and c-quark masses, and therefore determines the Higgs-charm coupling to be weaker than the Higgs-bottom coupling at the 95% confidence level.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗