Demonstration of BITSS addressing the challenges associated with adaptive remeshing. (a) Snapshots of the BITSS method for the buckling of a cylinder with a changing mesh. The radial displacement relative to the unbuckled cylinder is shown, as well as the underlying triangular mesh. (b) Snapshots for the striped wetting example with different resolutions for the two states. Each grid cell denotes 50x50 lattice nodes. The zoomed axis shows the difference in the fluid interface between the two final states, as well as the approximated transition state (solid black line). This is compared to the transition state found using a high resolution (dashed line).

Demonstration of BITSS addressing the challenges associated with adaptive remeshing. (a) Snapshots of the BITSS method for the buckling of a cylinder with a changing mesh. The radial displacement relative to the unbuckled cylinder is shown, as well as the underlying triangular mesh. (b) Snapshots for the striped wetting example with different resolutions for the two states. Each grid cell denotes 50x50 lattice nodes. The zoomed axis shows the difference in the fluid interface between the two final states, as well as the approximated transition state (solid black line). This is compared to the transition state found using a high resolution (dashed line).

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Locating transition states is crucial for investigating transition mechanisms in wide-ranging phenomena, from atomistic to macroscale systems. Existing methods, however, can struggle in problems with a large number of degrees of freedom, on-the-fly adaptive remeshing and coarse-graining, and energy landscapes that are locally flat or discontinuous....

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Context 1
... we show in fig. 4a that BITSS is able to handle the discretisation adapting, and the number of degrees of freedom changing, as the method runs. For this we use the cylindrical buckling example with the resolution increasing from 40 to 100 triangles around the cylinder, corresponding to an increase from 1760 to 11,000 degrees of freedom. This demonstrates ...
Context 2
... the second test, shown in fig. 4b, we demonstrate the use of different meshes for the two states in the striped wetting example. In this case, the distance measure is adapted by interpolating one state onto the other mesh and computing the Euclidean distance. However, for some applications a simpler measure may be sufficient, such as the difference between average ...

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... Some methods are based on the principle of keeping the energies of the two nodes similar during the search. [5][6][7][8][9][10][11] We refer to these methods as same-energy methods. The same-energy principle helps avoid an early crossing of the barrier from one side, and the saddle point stays trapped between the two nodes throughout the search. ...
... The existing algorithms that are based on the same-energy principle [5][6][7][8][9] have not been widely used so far, and their efficiencies are difficult to assess because they either have not been tested for realistic chemical systems or the number of energy and force calculations has not been reported in the original papers. An exception is the elastic image pair method and its improved version 11 (i-EIP), which has been reported to have a very high efficiency needing only 45 energy and force evaluation on average to find saddle points of molecular reactions. ...
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We present an algorithm to find first order saddle points on the potential energy surface (PES). The algorithm is formulated as a constrained optimization problem that involves two sets of atomic coordinates (images), a time-varying distance constraint and a constraint on the energy difference. Both images start in different valleys of the PES and are pulled toward each other by gradually reducing the distance. The search space is restricted to the pairs of configurations that share the same potential energy. By minimizing the energy while the distance shrinks, a minimum of the constrained search space is tracked. In simple cases, the two images are confined to their respective sides of the barrier until they finally converge near the saddle point. If one image accidentally crosses the barrier, the path is split at suitable locations and the algorithm is repeated recursively. The optimization is implemented as a combination of a quasi-Newton optimization and a linear constraint. The method was tested on a set of Lennard-Jones-38 cluster transitions and a set of 121 molecular reactions using density functional theory calculations. The efficiency in terms of energy and force evaluation is better than with competing methods as long as they do not switch to single-ended methods. The construction of a continuous search path with small steps and the ability to focus on arbitrary subsegments of the path provide an additional value in terms of robustness and flexibility.
... The transition states are central to describing reconfiguration mechanisms in chemistry, condensed matter physics and engineering [13]. The methods used for identifying the energy threshold between the states of compounds in the field of chemistry are well suited to provide a transformation strategy between the stable states of multistable tensegrity structures. ...
... Over the years, literature has given a number of mountain pass solutions, such as the nudged elastic band method [18,19], the dimer method [20], and conjugate peak refinement method [21]. Avis [13] distinguishes the Mountain Pass methods by the given information: whether a single stable state or multiple stable states are provided. The Conjugate Peak Refinement (CPR) method was first investigated to estimate the energy bound in chemical processes [22,23,21]; later it was expanded and used to study post-buckling of thin-walled shells in structural engineering [15]. ...
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