Relaxation of concentration perturbation in chemical kinetic systems

In a linear approximation, the relaxation of a concentration perturbation can be described by a matrix exponential, which can be evaluated using Jordan decomposition. In time-scale analysis, this approach has advantages when the Jacobian has degenerate eigenvalues, which may occur when the mechanism contains identical rate constants, characteristic to tropospheric chemistry and low-temperature combustion.     

Weakly reversible CF-decompositions of chemical kinetic systems

Journal of Mathematical Chemistry - This paper studies chemical kinetic systems which decompose into weakly reversible complex factorizable (CF) systems. Among power law kinetic systems, CF systems...     

Optimal transition paths of stochastic chemical kinetic systems

We present a new framework for finding the optimal transition paths of metastable stochastic chemical kinetic systems with large system sizes. The optimal transition paths are identified, in terms of reaction advancement coordinates, to be the most probable paths according to large deviation theory for the limiting dynamics governed by stochastic differential equations. Dynamical equations for the optimal transition paths are obtained using the variational principle. A multiscale minimum action method is proposed as a numerical scheme to solve the optimal transition paths. Applications to the toggle switch model are presented.     

Toward practical quantum embedding simulation of realistic chemical systems on near-term quantum computers

Quantum computing has recently exhibited great potential in predicting chemical properties for various applications in drug discovery, material design, and catalyst optimization. Progress has been made in simulating small molecules, such as LiH and hydrogen chains of up to 12 qubits, by using quantum algorithms such as variational quantum eigensolver (VQE). Yet, originating from the limitations of the size and the fidelity of near-term quantum hardware, the accurate simulation of large realistic molecules remains a challenge. Here, integrating an adaptive energy sorting strategy and a classical computational method—the density matrix embedding theory, which respectively reduces the circuit depth and the problem size, we present a means to circumvent the limitations and demonstrate the potential of near-term quantum computers toward solving real chemical problems. We numerically test the method for the hydrogenation reaction of C₆H₈ and the equilibrium geometry of the C₁₈ molecule, using basis sets up to cc-pVDZ (at most 144 qubits). The simulation results show accuracies comparable to those of advanced quantum chemistry methods such as coupled-cluster or even full configuration interaction, while the number of qubits required is reduced by an order of magnitude (from 144 qubits to 16 qubits for the C₁₈ molecule) compared to conventional VQE. Our work implies the possibility of solving industrial chemical problems on near-term quantum devices.

Quantum embedding simulation greatly enhanced the capability of near-term quantum computers on realistic chemical systems and reach accuracy comparable to advanced quantum chemistry methods.     

Exact wave functions for few-particle systems: The choice of expansion for coulomb potentials

We discuss a procedure for calculating numerical Hartree–Fock orbitals that can be applied to polyatomic systems. This approach is formulated in momentum space to avoid Coulomb singularities and uses fast Fourier transforms to solve integral convolutions. Results for a number of simple systems are presented.     

Nested stochastic simulation algorithm for chemical kinetic systems with disparate rates

An efficient simulation algorithm for chemical kinetic systems with disparate rates is proposed. This new algorithm is quite general, and it amounts to a simple and seamless modification of the classical stochastic simulation algorithm (SSA), also known as the Gillespie [J. Comput. Phys. 22, 403 (1976); J. Phys. Chem. 81, 2340 (1977)] algorithm. The basic idea is to use an outer SSA to simulate the slow processes with rates computed from an inner SSA which simulates the fast reactions. Averaging theorems for Markov processes can be used to identify the fast and slow variables in the system as well as the effective dynamics over the slow time scale, even though the algorithm itself does not rely on such information. This nested SSA can be easily generalized to systems with more than two separated time scales. Convergence and efficiency of the algorithm are discussed using the established error estimates and illustrated through examples.     

An uncommon form of multistationarity in a realistic kinetic model

The stationary behaviour of a kinetic model close to that describing the real nitric acidhydroxylamine reaction is studied under conditions of a continuously fed stirred tank reactor (c.s.t.r.). It is shown that this system has an interesting mathematical property — three positive stationary states in anunbounded region of the feed concentration. Two of these states are always locally asymptotically stable to perturbation while one is always unstable.     

A new kinetic approach to flowing chemical systems with linearly dependent reactions

A new kinetic approach to flowing chemical system is introduced, based on the elimination of reaction extents attached to linearly dependent reactions. The method is applied to analyze the propagation of acoustic waves in a reacting chemical mixture.

---

, , . .

     

Exact solutions for kinetic models of macromolecular dynamics

Dynamic biological processes such as enzyme catalysis, molecular motor translocation, and protein and nucleic acid conformational dynamics are inherently stochastic processes. However, when such processes are studied on a nonsynchronized ensemble, the inherent fluctuations are lost, and only the average rate of the process can be measured. With the recent development of methods of single-molecule manipulation and detection, it is now possible to follow the progress of an individual molecule, measuring not just the average rate but the fluctuations in this rate as well. These fluctuations can provide a great deal of detail about the underlying kinetic cycle that governs the dynamical behavior of the system. However, extracting this information from experiments requires the ability to calculate the general properties of arbitrarily complex theoretical kinetic schemes. We present here a general technique that determines the exact analytical solution for the mean velocity and for measures of the fluctuations. We adopt a formalism based on the master equation and show how the probability density for the position of a molecular motor at a given time can be solved exactly in Fourier-Laplace space. With this analytic solution, we can then calculate the mean velocity and fluctuation-related parameters, such as the randomness parameter (a dimensionless ratio of the diffusion constant and the velocity) and the dwell time distributions, which fully characterize the fluctuations of the system, both commonly used kinetic parameters in single-molecule measurements. Furthermore, we show that this formalism allows calculation of these parameters for a much wider class of general kinetic models than demonstrated with previous methods.     

Field induced gradient simulations: a high throughput method for computing chemical potentials in multicomponent systems

We present a simulation method for direct computation of chemical potentials in multicomponent systems. The method involves application of a field to generate spatial gradients in the species number densities at equilibrium, from which the chemical potential of each species is theoretically estimated. A single simulation yields results over a range of thermodynamic states, as in high throughput experiments, and the method remains computationally efficient even at high number densities since it does not involve particle insertion at high densities. We illustrate the method by Monte Carlo simulations of binary hard sphere mixtures of particles with different sizes in a gravitational field. The results of the gradient Monte Carlo method are found to be in good agreement with chemical potentials computed using the classical Widom particle insertion method for spatially uniform systems.     

Electrostatic molecular potentials in hydrogen-bonded systems

A study is made of the modifications of the electrostatic molecular potential brought about by hydrogen bonding both in the hydrogen-bond region itself and in the external regions of the proton-acceptor and proton-donor molecules. Systems up to four successive units in a chain of donor-acceptors are considered. The possibility of obtaining a satisfactory picture of the global potential by a simple superposition of the potentials of the individual units is evaluated.     

A comparison of different methods for the calculation of the chemical potentials of polymer systems

In an earlier publication we had presented a Monte Carlo method to calculate the incremental chemical potential between a chain of length v and one of length v+1 at any density. (Ref.9) In this paper we begin by formally proving that the chemical potential of a whole chain of length v can be obtained by sequentially summing the incremental chemical potentials of all chains whose lengths are smaller than v under the same conditions. We then compare the numerical value of chain chemical potentials computed in this fashion to those obtained by inserting whole chains into the simulation cell following the configurational bias procedure proposed by Smit and Frenkel. (Ref.5) It is found, for the two cases considered here, that the results obtained from the two different calculations agree within simulation uncertainty, thus verifying the validity of the proposed arguments.     

A simulation method for the calculation of chemical potentials in small, inhomogeneous, and dense systems

We present a modification of the gauge cell Monte Carlo simulation method [A. V. Neimark and A. Vishnyakov, Phys. Rev. E 62, 4611 (2000)] designed for chemical potential calculations in small confined inhomogeneous systems. To measure the chemical potential, the system under study is set in chemical equilibrium with the gauge cell, which represents a finite volume reservoir of ideal particles. The system and the gauge cell are immersed into the thermal bath of a given temperature. The size of the gauge cell controls the level of density fluctuations in the system. The chemical potential is rigorously calculated from the equilibrium distribution of particles between the system cell and the gauge cell and does not depend on the gauge cell size. This scheme, which we call a mesoscopic canonical ensemble, bridges the gap between the canonical and the grand canonical ensembles, which are known to be inconsistent for small systems. The ideal gas gauge cell method is illustrated with Monte Carlo simulations of Lennard-Jones fluid confined to spherical pores of different sizes. Special attention is paid to the case of extreme confinement of several molecular diameters in cross section where the inconsistency between the canonical ensemble and the grand canonical ensemble is most pronounced. For sufficiently large systems, the chemical potential can be reliably determined from the mean density in the gauge cell as it was implied in the original gauge cell method. The method is applied to study the transition from supercritical adsorption to subcritical capillary condensation, which is observed in nanoporous materials as the pore size increases.     

The role of kinetic energy in chemical binding

The wavefunctions and various partitions of the energy are examined for a variety of small molecules (H₂, H₃, H₄, HeH, HeH₂, He₂, LiH, and BH) in order to isolate the factors crucial for bond formation. We find that a natural partition of the energy leads to the conclusion that the crucial factor is the exchange, or nonclassical, part of the kinetic energy, T ^x. The change in T ^xupon pushing the atoms towards one another is the dominant term in the binding energy; it is negative when the resulting molecule is stable and positive when it is unstable. We show that T ^x is related to the interference kinetic energy considered by Ruedenberg.

---

Zusammenfassung Die Wellenfunktionen und verschiedene Zerlegungen der Energie werden für eine Reihe kleiner Moleküle untersucht (H₂, H₃, H₄, HeH, HeH₂, He₂, LiH und BH), um die Faktoren zu finden, die für die Bindungsbildung ausschlaggebend sind. Die natürliche Zerlegung der Energie läßt die Folgerung zu, daß der bestimmende Faktor der Austauschanteil T ^x(oder nichtklassische Anteil) der kinetischen Energie ist. Die Änderung von T ^xbeim Zusammenführen der Atome ist der dominierende Term für die Bindungsenergie; er ist negativ, wenn das resultierende Molekül stabil ist, und positiv, falls es instabil ist. Es wird gezeigt, daß T ^x im Zusammenhang zum Wechselwirkungsanteil der kinetischen Energie nach Ruedenberg steht.

---

---

Partially supported by a grant (GP-15423) from the National Science Foundation. This paper is based on a portion of the PhD thesis (California Institute of Technology, 1970) by CWW.

---

National Science Foundation Predoctoral Trainee.

---

Alfred P. Sloan Foundation Research Fellow.

---

Contribution No. 3917.     

Symmetry considerations in closed first-order kinetic systems

The analysis of a highly symmetric type of exactly lumpable, closed system of coupled, first-order rate equations shows that complete information about the equilibrium solution and all modes of relaxation is calculable from matrices with dimensions less than the number of states in the system.