Energy Dynamics Research Articles

The Excess of JWST Bright Galaxies: A Possible Origin in the Ground State of Dynamical Dark Energy in the Light of DESI 2024 Data

Recent observations by JWST yield a large abundance of luminous galaxies at z ≳ 10 compared to that expected in the ΛCDM scenario based on extrapolations of the star formation efficiency measured at lower redshifts. While several astrophysical processes can be responsible for such observations, here we explore to what extent such an effect can be rooted in the assumed dark energy (DE) sector of the current cosmological model. This is motivated by recent results from different cosmological probes combined with the last data release of the Dark Energy Spectroscopic Instrument, which indicate a tension in the DE sector of the concordance ΛCDM model. We have considered the effect of assuming a DE characterized by a negative Λ as the ground state of a quintessence field on the galaxy luminosity function at high redshifts. We find that such models naturally affect the galaxy UV luminosities in the redshift range 10 ≲ z ≲ 15 needed to match the JWST observations, and with the value of ΩΛ = [−0.6, −0.3] remarkably consistent with that required by independent cosmological probes. A sharp prediction of such models is the steep decline of the abundance of bright galaxies in the redshift range 15 ≲ z ≲ 16.

Role of dynamical vacuum energy in the closed universe: implications for bouncing scenario

Role of dynamical vacuum energy in the closed universe: implications for bouncing scenario

Updated Cosmological Constraints in Extended Parameter Space with Planck PR4, DESI Baryon Acoustic Oscillations, and Supernovae: Dynamical Dark Energy, Neutrino Masses, Lensing Anomaly, and the Hubble Tension

We present updated constraints on cosmological parameters in a 12-parameter model, extending the standard six-parameter ΛCDM by including dynamical dark energy (DE; w 0, w a ), the sum of neutrino masses (∑m ν ), the effective number of non-photon radiation species (N eff), the lensing amplitude scaling (A lens), and the running of the scalar spectral index (α s ). For cosmic wave background (CMB) data, we use the Planck Public Release (PR) 4 (2020) HiLLiPoP and LoLLiPoP likelihoods, Planck PR4+Atacama Cosmology Telescope (ACT) DR6 lensing, and Planck 2018 low-ℓ TT likelihoods, along with DESI DR1 baryon acoustic oscillations (BAO) and Pantheon+ and DESY5 uncalibrated Type Ia supernovae (SNe) likelihoods. Key findings are the following: (i) Contrary to DESI results, CMB+BAO+Pantheon+ data include a cosmological constant within 2σ, while CMB+BAO+DESY5 excludes it at over 2σ, indicating the dynamical nature of DE is not yet robust. Potential systematics in the DESY5 sample may drive this exclusion. (ii) Some data combinations show a 1σ+ detection of nonzero ∑m ν , indicating possible future detection. We also provide a robust upper bound of ∑m ν ≲ 0.3 eV (95% confidence limit (CL)). (iii) With CMB+BAO+SNe, A lens = 1 is included at 2σ (albeit not at 1σ), indicating no significant lensing anomaly in this extended cosmology with Planck PR4 likelihoods. (iv) The Hubble tension persists at 3.2 to 3.9σ, suggesting these simple extensions do not resolve it. (v) The S 8 tension with Dark Energy Survey Year 3 weak lensing is reduced to 1.4σ, likely due to additional parameters and the Planck PR4 likelihoods.

Elucidating Dynamical Behaviors in Kinetically Constrained Models via Energy-Activity Double-Biased Matrix Product State Analysis.

We investigate dynamical phase transitions in two representative kinetically constrained models: the 1D Fredrickson-Andersen and East Models. A recently developed energy-activity double-bias approach utilizing both s and g fields, conjugated with dynamical activity and trajectory energy, is combined with matrix product state (MPS) methods. It is demonstrated that MPS methods facilitate the numerical approximation of large-deviation statistics of dynamics by determining the eigenvalues of tilted dynamical generators under the influence of double-biasing fields. Specifically, by focusing on the g-field, a nearly "half-filled" state at moderate negative g values is identified, indicating the potential existence of an anomalous phase. Additionally, dynamical quantities under various s, g, and T conditions are obtained via tensor networks, showing good qualitative consistency with mean-field results and our previous extensive numerical simulation results obtained by the path sampling method. Our study introduces novel methodologies for examining decoupled dynamical behaviors that, although energetically active, remain dynamically inactive within the system. This approach offers a fresh perspective on the theoretical framework and computational strategies for studying dynamical phase transitions in kinetically constrained systems.

Unravelling the protective effects of peptide isolated from marine sponge extract MS01 against SH-SY5Y cell line and its in-silico pharmacokinetic analysis

Parkinson's disease (PD) is characterised by developing postural instability, resting seizures, tremors, and a movement problem coupled with stiffness. All the available drugs can improve motor function considerably, but they can also have negative side effects, especially if the problem gets worse. The structure-activity relation was performed in the DISCOVERY STUDIO V2.5.5 pharmacophore model using the HypoGen algorithm for a training set of 15 compounds. Here, xenin peptide fits well with a least cost difference and a fit value of 10.46, indicating a favourable pharmacological characteristic. Therefore, we tried applying gene network analysis in cytoHubba to find the hub gene for PD in Danio rerio and Homo sapiens, as zebrafish and humans share many disease proteins and processes. Molecular docking studies for the hub gene polyubiquitin B from Danio rerio and Parkin from Homo sapiens, as well as the peptide xenin obtained from the marine sponge extract MS01 was performed. The peptide exhibits a substantial binding affinity with the receptor UBB through 8 and PRKN through 4 intermolecular hydrogen bonds in their bonded and non-bonded interactions, although it has little effect on the protein structure, according to simulation studies and dynamical free energy calculations. The protein structure has also been stabilised in terms of energy, secondary structure, and flexibility by the peptide binding. In addition to in-silico analysis the extract was tested in-vitro on SH-SY5Y cells for its effectiveness against ROS and cell viability, which proved its qualitative effect.

Precise Immobilization Strategy Combined with Rational Design to Improve β-Agarase Stability.

Recently, the orientational immobilization of enzymes has attracted extensive attention. In this study, we report the development of a strategy combined with rational design to achieve precise site-specific covalent immobilization of β-agarase. We first rationally screened six surface sites that can be mutated to cysteine by combining molecular dynamics simulation and energy calculation. Site-specific immobilization was successfully achieved by Michael addition reaction of mutant enzymes and maleimide-modified magnetic nanoparticles (MAL-MNPs). The enzyme activity retention rate of R66C-MAL-MNPs and K588C-MAL-MNPs was greater than 96%. The thermal deactivation kinetics study revealed that the site-specific immobilization strategy significantly improved the thermal stability of Aga50D, resulting in a substantial increase in its antidenaturation activity at elevated temperatures, and the highest t1/2 of the immobilized mutant enzymes was increased by an impressive 21.25-fold at 40 °C. The immobilized mutant enzymes also showed significantly enhanced tolerance to metal ions and organic reagents. For instance, all of the immobilized enzymes maintained over 90% of their enzymatic activity in the 50% (v/v) acetone/water solution. The present work may pave the way for the design of precisely immobilized enzymes, which can help promote green manufacturing.

In Silico Analysis of Vitamin D Interactions with Aging Proteins: Docking, Molecular Dynamics, and Solvation Free Energy Studies

Aging is a natural process that is also influenced by some factors like the food someone eats, lifestyle decisions, and impacts on general health. Despite the recognized role of nutrition in modulating the molecular and cellular mechanisms underlying aging, there is a lack of comprehensive exploration into potential interventions that can effectively mitigate these effects. In this study, we investigated the potential anti-aging properties of vitamin D by examining its interactions with key molecular targets involved in aging-related pathways. By using molecular docking and dynamics techniques, we evaluate the interactions and stability of vitamins D2 and D3 with key proteins involved in aging pathways, such as SIRT1, mTOR, AMPK, Klotho, AhR, and MAPK. Our results reveal promising binding affinities between vitamin D and SIRT1 forms, with energy values of −48.33 kJ/mol and −45.94 kJ/mol for vitamins D2 and D3, respectively, in aqueous environments. Moreover, molecular dynamics simulations revealed that the vitamin D3–SIRT1 complex exhibited greater stability compared with the vitamin D2–SIRT1 complex. The study calculated the solvation free energy to compare the solubility of vitamins D2 and D3 in water and various organic solvents. Despite their strong interactions with water, both vitamins exhibited low solubility, primarily due to the high energy cost associated with cavity formation in the aqueous environment. Compared with other solvents, water demonstrated particularly low solubility for both vitamins. This suggested that vitamins D2 and D3 preferred binding to aging receptors over dissolving in bulk aqueous environments, supporting their strong therapeutic interactions with these receptors. These findings shed light on the molecular mechanisms underlying vitamin D’s potential anti-aging effects and lay the groundwork for developing nutraceuticals targeting aging and associated diseases. Understanding these mechanisms holds promise for future interventions aimed at promoting healthy aging and enhancing overall well-being.

Nonlinear behavior and energy harvesting performance of a new tunable quasi-zero stiffness system.

Energy harvesting from vibrations is a popular research topic. However, it is difficult to change the values of its dynamic stiffness characteristics during the operation of device. This paper analyzes the nonlinear dynamical behavior and energy harvesting performance of an energy harvesting device with a gear unit and an inertial amplifier. The Melnikov method is used to discriminate the chaos behavior of the system and is illustrated by numerical simulations. Chaotic dynamics analysis provides a simplified analytical idea that offers more insight into the performance of this energy harvesting device. In addition, the basins of attraction of the coexistence solution of the system are plotted, and the trajectory and energy harvesting efficiency of the system are analyzed for changes in the initial value. The results show that the device has the convenience to change the form and efficiency of system energy harvesting. The theory of Melnikov functions recognizes the presence of chaos and can provide solutions for the parameterization of the system. The choice of initial value greatly affects the energy harvesting efficiency.

Screening of FDA-approved Drugs against Protein Thymidine Kinase 2 Using Machine Learning Method Validated Applying Molecular Dynamics and Free Energy Landscape Calculation

Background: Thymidine kinase 2 (TK2) is a crucial enzyme in the mitochondrial pyrimidine salvage pathway, strongly associated with several mitochondrial diseases. Current treatments frequently damage mitochondria, leading to a decrease in cellular energy output. Objective: This study aimed to use computational approaches to identify inhibitors of TK2 that could prevent these harmful consequences. Method: The initial screening process entailed the application of machine learning algorithms, more particularly a Random Forest model, which was trained on 189 FDA-approved drugs and decoy datasets obtained from the DUD-E database. Its purpose was to identify potential inhibitors. The molecular docking technique was employed to evaluate the affinity of the chosen medicines towards TK2. Molecular dynamics (MD) simulations lasting 100 nanoseconds were employed to conduct additional validation by examining the dynamic interactions between the top-found compounds and TK2. Results: Three hit compounds (3168, 5209502, and 135402009) were identified through the screening process for their high affinity for TK2. Compound 5209502 had the most stable interaction with the lowest root-mean-square deviation (RMSD) in the molecular dynamics (MD) simulations and maintained 12 hydrogen bonds consistently. MM/GBSA computations verified that 5209502 exhibited the strongest binding affinity with a binding free energy of -62.14 kcal/mol, which was notably lower than that of the control ligand. Conclusion: Compound 5209502 is a promising candidate for additional experimental evaluation because of its notable stability and great affinity for TK2. This chemical may provide a focused and less harmful treatment for mitochondrial illnesses linked to TK2 malfunction.

Directional excitation of structural vibrations due to correlated sources

Dynamical Energy Analysis (DEA) is an approach used to compute the vibro-acoustic response of complex structures to externally applied high-frequency excitation. DEA tracks the global energy flow in a structure in terms of a local ray tracing approach implemented on meshes. Due to its in-built directional set-up, the approach is ideally suited for modelling the response of structures to directional excitation. Examples thereof are dipole sources or - more generally - correlated and distributed source excitation such as due to a Turbulent Boundary Layer (TBL) excitation across an aircraft wing during flight. We will demonstrate here how such directional sources are implemented in a DEA setting. TBL induced sources or general correlated sources can be described in terms of appropriate force or wave correlation functions (CF). Using Wigner-transformation, these CFs can be associated with a directional energy flow source. Vibrational energy field results are presented for a pair of phase-locked point forces. Results are also presented for 9 point-sources, which demonstrate the ability to channel the energy flow away from the sources by carefully choosing their relative phases. An implementation of this approach within DEA is also presented, with results demonstrating strong agreement with direct calculations.

Robust preference for Dynamical Dark Energy in DESI BAO and SN measurements

Recent Baryon Acoustic Oscillation (BAO) measurements released by DESI, when combined with Cosmic Microwave Background (CMB) data from Planck and two different samples of Type Ia supernovae (Pantheon-Plus and DESY5) reveal a preference for Dynamical Dark Energy (DDE) characterized by a present-day quintessence-like equation of state that crossed into the phantom regime in the past. A core ansatz for this result is assuming a linear Chevallier-Polarski-Linder (CPL) parameterization w(a) = w 0 + wa (1-a) to describe the evolution of the DE equation of state (EoS). In this paper, we test if and to what extent this assumption impacts the results. To prevent broadening uncertainties in cosmological parameter inference and facilitate direct comparison with the baseline CPL case, we focus on 4 alternative well-known models that, just like CPL, consist of only two free parameters: the present-day DE EoS (w0 ) and a parameter quantifying its dynamical evolution (wa ). We demonstrate that the preference for DDE remains robust regardless of the parameterization: w0 consistently remains in the quintessence regime, while wa consistently indicates a preference for a dynamical evolution towards the phantom regime. This tendency is significantly strengthened by DESY5 SN measurements. By comparing the best-fit χ2 obtained within each DDE model, we notice that the linear CPL parameterization is not the best-fitting case. Among the models considered, the EoS proposed by Barboza and Alcaniz consistently leads to the most significant improvement.

Cosmological forecasts from the combination of Stage-IV photometric galaxy surveys and the magnification from forthcoming GW observatories

In this work we have investigated the synergy between Stage-IV galaxy surveys and future GW observatories for constraining the underlying cosmological model of the Universe, focussing on photometric galaxy clustering, cosmic shear and GW magnification as cosmological probes. We have implemented a Fisher matrix approach for the evaluation of the full 6×2pt statistics composed by the angular power spectra of the single probes together with their combination. For our analysis, we have in particular considered dynamical dark energy and massive neutrino scenarios. We have found that the improvement to galaxy survey performance is below 1%, in the case of ℓ GW max=100 and a luminosity distance error of σ dL /dL =10%. However, when extending the analysis to ℓ GW max=1000, we find that the GW magnification improves the galaxy survey performance on all the cosmological parameters, reducing their errors by 3%-5%, when σ dL /dL =10%, and by 10%-18% when σ dL /dL =1%, especially for Mν , w 0 and wa . However, here our analysis is unavoidably optimistic: a much more detailed and realistic approach will be needed, especially by including systematic effects. But we can conclude that, in the case of future gravitational wave observatories, the inclusion of the gravitational wave magnification can improve Stage-IV galaxy surveys performance on constraining the underlying cosmological model of the Universe.

Light-Induced Complete Reversal of Ferroelectric Polarization in Sliding Ferroelectrics.

Previous experiments have provided evidence of sliding ferroelectricity and photoexcited interlayer shear displacement in two-dimensional materials, respectively. Herein, we find that a complete reversal of vertical ferroelectric polarization can be achieved within an astonishing 0.5ps in h-BN bilayer by laser illumination. Comprehensive analysis suggests that ferroelectric polarization switching originates from laser-induced interlayer sliding triggered by selective excitation of multiple phonons. The interlayer electron excitation from the p_{z} orbitals of the upper layer N atoms to the p_{z} orbitals of the lower layer B atoms produces desirable and directional interlayer forces activating the in-plane optical TO-1 and LO-1 phonon modes. The atomic motions driven by the coupling of TO-1 and LO-1 modes are coherent with ferroelectric soft mode, thus modulating the dynamical potential energy surface and resulting in ultrafast ferroelectric polarization reversal. Our work provides a novel microscopic insight into ultrafast polarization switching in sliding ferroelectrics.

Building the Bridge: How System Dynamics Models Operationalise Energy Transitions and Contribute towards Creating an Energy Policy Toolbox

The complexity and multi-dimensionality of energy transitions are broadly recognised, and insights from transition research increasingly support policy decision making. Sustainability transition scholars have been developing mostly qualitative socio-technical transition (STT) frameworks, and modelling has been argued to be complementary to these frameworks, for example for policy testing. We systematically evaluate five system dynamics (SD) energy models on their representation of key STT characteristics. Our results demonstrate that (i) the evaluated models incorporate most of the core characteristics of STT, and (ii) the policies tested in the models address different levels and aspects of the multi-level perspective (MLP) framework. In light of the increasing emergence of energy (transition) models, we recommend to systematically map models and their tested policy interventions into the MLP framework or other sustainability transition frameworks, creating an overview of tested policies (a “policy navigator”). This navigator supports policy makers and modellers alike, facilitating them to find previously tested policy options and related models for particular policy objectives.

Time of day of infection shapes development of a eukaryotic algal-Nucleocytoviricota virocell.

Aureococcus anophagefferens forms a model host-virus system with the "giant virus" Kratosvirus quantuckense. Studies to define its ribocell (uninfected) and virocell (virus-infected) forms are needed as these states co-occur during algal blooms. Previously, a link between light-derived energy, virus particle production, and virocell formation was noted. We explored how the time of day (morning, midday, or late day) of virus-host contact shaped virocell ontogeny. In parallel, we explored the dependence on light-derived energy in this mixotrophic plankter by inhibiting photosystem II, testing the role of heterotrophic energy in infection dynamics. Using flow cytometry and photochemical assessments, we examined the physiology of infected cells and controls, and estimated virus particle production. We observed differences between ribocell and virocell response to treatments, including reductions in virus particle production during reduced light duration) and PSII inhibition (i.e. "forced heterotrophy"). This work demonstrates the importance of light in shaping the fate of infected cells and provides insight into factors that constrain in situ blooms. Most significantly, we show that time of the solar day when a virus and host come into contact influences viral particle production, and therefore bloom dynamics; a factor that needs to be considered in bloom modeling work.

Multi-body dynamics modeling and energy consumption optimization of electromagnetic mechanical fully variable valve system

Electromagnetic Mechanical Variable Valve Actuation (EMVVA) technology has the capability to improve engine performance and decrease pollutant emissions. A new type of EMVVA composed of electromagnetic driver and mechanical transmission is proposed to realize the flexible adjustment of valve parameters whether the valve is open or closed process. The geometric mathematical model of the mechanical transmission is developed based on the motion laws of the valve and the geometrical construction of the mechanical transmission, and the conjugate cam curve is solved. A multi-body dynamic model is constructed to calculate the driving torque and energy consumption needed by the mechanical transmission based on the mass, rotational inertia, centroid position of the parts, combining the normal contact force model and the friction model of the clearance contact pair at the same time. Based on the geometric model and multi-body dynamics model, the test platform is established. The test results demonstrated that within the specified valve lift, EMVVA system could accomplish variable valve lift, variable valve timing, and variable valve duration at maximum lift. The maximum timing error does not exceed 1° crank angle, and the maximum valve lift error does not exceed 0.25 mm at 11 mm valve lift. In addition, the error of driving torque between the multi-body dynamics model and the test is less than 0.3 [Formula: see text].Low energy optimization of mechanical transmission was completed using the NSGA-II method and multi-body model. According to the results of the optimization, energy consumption was reduced by 14%, and the peak driving torque was decreased by 54.3%.

The future of cosmological likelihood-based inference: accelerated high-dimensional parameter estimation and model comparison

We advocate for a new paradigm of cosmological likelihood-based inference, leveraging recent developments in machine learning and its underlying technology, to accelerate Bayesian inference in high-dimensional settings. Specifically, we combine (i) emulation, where a machine learning model is trained to mimic cosmological observables, e.g. CosmoPower-JAX; (ii) differentiable and probabilistic programming, e.g. JAX and NumPyro, respectively; (iii) scalable Markov chain Monte Carlo (MCMC) sampling techniques that exploit gradients, e.g. Hamiltonian Monte Carlo; and (iv) decoupled and scalable Bayesian model selection techniques that compute the Bayesian evidence purely from posterior samples, e.g. the learned harmonic mean implemented in harmonic. This paradigm allows us to carry out a complete Bayesian analysis, including both parameter estimation and model selection, in a fraction of the time of traditional approaches. First, we demonstrate the application of this paradigm on a simulated cosmic shear analysis for a Stage IV survey in 37- and 39-dimensional parameter spaces, comparing ΛCDM and a dynamical dark energy model ( w0waCDM). We recover posterior contours and evidence estimates that are in excellent agreement with those computed by the traditional nested sampling approach while reducing the computational cost from 8 months on 48 CPU cores to 2 days on 12 GPUs. Second, we consider a joint analysis between three simulated next-generation surveys, each performing a 3x2pt analysis, resulting in 157- and 159-dimensional parameter spaces. Standard nested sampling techniques are simply unlikely to be feasible in this high-dimensional setting, requiring a projected 12 years of compute time on 48 CPU cores; on the other hand, the proposed approach only requires 8 days of compute time on 24 GPUs. All packages used in our analyses are publicly available.

A new diagnostic for the null test of dynamical dark energy in light of DESI 2024 and other BAO data

We introduce a new diagnostic for the null tests of dynamical dark energy alongside two other combined equivalent diagnostics. These diagnostics are useful, especially when we include anisotropic baryon acoustic oscillation (BAO) data in an analysis, to quantify the deviations from the standard ΛCDM model. We also consider another diagnostic for isotropic BAO observations. These null tests are independent of any late-time dark energy model or parametrization. With these diagnostics, we study the evidence for dynamical dark energy in light of Dark Energy Spectroscopic Instrument (DESI) 2024 data combined with cosmic microwave background (CMB) observations of the Planck 2018 mission and local H 0 measurements. We find no strong evidence for dynamical dark energy. The exclusion of the individual deviations at the effective redshift 0.51 of the DESI 2024 data makes the evidence even weaker. We get nearly similar results for other non-DESI BAO data. Both for DESI 2024 and other non-DESI BAO data, the evidence is almost independent of early-time physics. The evidence corresponding to the SHOES value of H 0 is higher than the corresponding tRGB value of H 0 for all combinations of data, but still not strong enough to reject the flat ΛCDM model.

Cosmological constraints on curved quintessence

Dynamical dark energy has gained renewed interest due to recent theoretical and observational developments. In the present paper, we focus on a string-motivated dark energy set-up, and perform a detailed cosmological analysis of exponential quintessence with potential V = V 0 e λϕ -, allowing for non-zero spatial curvature. We first gain some physical intuition into the full evolution of such a scenario by analysing the corresponding dynamical system. Then, we test the model using a combination of Planck CMB data, DESI BAO data, as well as recent supernovae datasets. For the model parameter λ, we obtain a preference for nonzero values: λ = 0.48+0.28 -0.21, 0.68+0.31 -0.20, 0.77+0.18 -0.15 at 68% C.L. when combining CMB+DESI with Pantheon+, Union3 and DES-Y5 supernovae datasets respectively. We find no significant hint for spatial curvature. We discuss the implications of current cosmological results for the exponential quintessence model, and more generally for dark energy in string theory.

Nonlocal-in-time finite-velocity diffusion approach on a ring.

The ubiquitous telegrapher's equationis presented in the context of a non-local-in-time master equationon the lattice. From the exact solution of this transport equation, for different hopping models, the second moment in the infinite lattice and the time evolution of the probability in the ring have been analyzed as a function of the two characteristic timescales appearing in the memory kernel of the finite-velocity approach: the rate of energy loss and the timescale characterizing the jumping process in the lattice. We have demonstrated how these timescales characterize the constraint to find positive solutions, the time variation of entropy and therefore the approach to the disordered stationary state on the ring. This lattice model provides an analytic treatment. Thus, this result is relevant in the study of Shannon entropy, transport of information, and waves in lattices and sheds light on the functional role of the loss of energy in the finite-velocity diffusion dynamics.