Abstract Under appropriate conditions, the activity of phosphofructokinase of skeletal muscle from frog and mouse is extremely sensitive to small changes in pH in the physiological range, a low pH decreasing the affinity of the enzyme for fructose 6-phosphate. It is concluded that shifts in intracellular pH are important in the regulation of phosphofructokinase, but that this effect makes interpretation of data from intact muscle quite difficult.
In this paper, a gradient flow model is proposed for conducting ground state calculations in Wigner formalism of many-body system in the framework of density functional theory. More specifically, an energy functional for the ground state in Wigner formalism is proposed to provide a new perspective for ground state calculations of the Wigner function. Employing density functional theory, a gradient flow model is designed based on the energy functional to obtain the ground state Wigner function representing the whole many-body system. Subsequently, an efficient algorithm is developed using the operator splitting method and the Fourier spectral collocation method, whose numerical complexity of single iteration is $O(n_{\rm DoF}\log n_{\rm DoF})$. Numerical experiments demonstrate the anticipated accuracy, encompassing the one-dimensional system with up to $2^{21}$ particles and the three-dimensional system with defect, showcasing the potential of our approach to large-scale simulations and computations of systems with defect.
Joshua Finkelstein, Emanuel H. Rubensson, Susan M. Mniszewski
et al.
Time-independent quantum response calculations are performed using Tensor cores. This is achieved by mapping density matrix perturbation theory onto the computational structure of a deep neural network. The main computational cost of each deep layer is dominated by tensor contractions, i.e. dense matrix-matrix multiplications, in mixed precision arithmetics which achieves close to peak performance. Quantum response calculations are demonstrated and analyzed using self-consistent charge density-functional tight-binding theory as well as coupled-perturbed Hartree-Fock theory. For linear response calculations, a novel parameter-free convergence criterion is presented that is well-suited for numerically noisy low precision floating point operations and we demonstrate a peak performance of almost 200 Tflops using the Tensor cores of two Nvidia A100 GPUs.
Molecular dynamics (MD) has become a powerful tool for studying biophysical systems, due to increasing computational power and availability of software. Although MD has made many contributions to better understanding these complex biophysical systems, there remain methodological difficulties to be surmounted. First, how to make the deluge of data generated in running even a microsecond long MD simulation human comprehensible. Second, how to efficiently sample the underlying free energy surface and kinetics. In this short perspective, we summarize machine learning based ideas that are solving both of these limitations, with a focus on their key theoretical underpinnings and remaining challenges.
We present a detailed quasinormal mode analysis of gold bowtie nanoantennas, and highlight the unusual role of the substrate and the onset of multi-mode behaviour. In particular, we show and explain why the directional radiatiave beta factor is completely dominated by emission into the substrate, and explain how the beta factors and quenching depend on the underlying mode properties. We also quantitatively explain the generalized Purcell factors and explore the role of gap size and substrate in detail. These rich modal features are essential to understand for future applications such as sensing, lasing, and quantum information processing, for example in the design of efficient single photon emitters.
Free energy calculations based on atomistic Hamiltonians and sampling are key to a first principles understanding of biomolecular processes, material properties, and macromolecular chemistry. Here, we generalize the Free Energy Perturbation method and derive non-linear Hamiltonian transformation sequences for optimal sampling accuracy that differ markedly from established linear transformations. We show that our sequences are also optimal for the Bennett Acceptance Ratio (BAR) method, and our unifying framework generalizes BAR to small sampling sizes and non-Gaussian error distributions. Simulations on a Lennard-Jones gas show that an order of magnitude less sampling is required compared to established methods.
The effects of thermal diffuse scattering on the transmission and eventual diffraction of highly accelerated electrons are investigated with a method that incorporates the frozen phonon approximation to the exact numerical solution of the time-dependent Schrödinger equation. Unlike other methods in the related literature, in this approach the attenuation of diffraction features arises in a natural way by averaging over a number of wave-packet realizations, thus avoiding any additional experimentally obtained Debye-Waller factors or artificial modulations. Without loss of generality, the method has been applied to analyze the transmission of an electron beam through a thin Al film in two dimensions, making use of Einstein's model to determine the phonon configuration for each realization at a given temperature. It is shown that, as temperature and hence atomic vibration amplitudes increase, incoherence among different electron wave-function realizations gradually increases, blurring the well-defined diffraction features characterizing the zero-temperature intensity.
Grain feeding often causes a decrease in ruminal pH, and experiments were conducted to define the role of pH in regulating the acetate to propionate ratio and production of CH4. Cows that were fed 90% concentrate had lower ruminal pH values (6.22 vs. 6.86), higher VFA concentrations (85 vs. 68 mM), and lower acetate to propionate ratios (2.24 vs. 4.12) than did cows that were fed forage only. When mixed ruminal bacteria from cows that were fed 90% concentrate or 100% forage were incubated (48 h) with hay (10 g/L) or cracked corn (5 g/L) in a medium containing bicarbonate (38 mM) and tricarballylate (50 mM), the final pH values were less than 0.3 units lower than the initial pH. At final pH values less than 5.7, hay fermentation was inhibited, the acetate to propionate ratio and CH4 production declined more than twofold, and the inoculum source was without effect. Small amounts of H2 were detected at pH values less than 5.5. Total VFA production from cracked corn decreased when pH declined, but only if the inoculum was obtained from cows that were fed 90% concentrate. The acetate to propionate ratio of cracked corn incubations declined from 1.2 to 0.6 when final pH was decreased from 6.5 to 5.3, and CH4, as a percentage of total VFA production, also decreased. At pH values less than 5.3, the acetate to propionate ratio of cracked corn increased more than fourfold, and large amounts of H2 could be detected. Over the final pH range of 6.5 to 5.3, CH4 production was highly correlated with acetate to propionate ratio, which was dependent on pH and substrate (CH4 = 0.02 + 0.05 pH; r2 = 0.80). Calculations based on the differences between pH 6.5 and 5.8 indicated that as much as 25% of the decrease in acetate to propionate ratio could be explained by the effect of pH alone.
Hamiltonian integration methods for the Vlasov-Maxwell equations are developed by a Hamiltonian splitting technique. The Hamiltonian functional is split into five parts, i.e., the electrical energy, the magnetic energy, and the kinetic energy in three Cartesian components. Each of the subsystems is a Hamiltonian system with respect to the Morrison-Marsden-Weinstein Poisson bracket and can be solved exactly. Compositions of the exact solutions yield Poisson structure preserving, or Hamiltonian, integration methods for the Vlasov-Maxwell equations, which have superior long-term fidelity and accuracy.