{"title":"随机相互作用系统的动力学和极值。","authors":"Martin Girard","doi":"10.1088/1478-3975/aca9b2","DOIUrl":null,"url":null,"abstract":"<p><p>Biological environments such as the cytoplasm are comprised of many different molecules, which makes explicit modeling intractable. In the spirit of Wigner, one may be tempted to assume interactions to derive from a random distribution. Via this approximation, the system can be efficiently treated in the mean-field, and general statements about expected behavior of such systems can be made. Here, I study systems of particles interacting via random potentials, outside of mean-field approximations. These systems exhibit a phase transition temperature, under which part of the components precipitate. The nature of this transition appears to be non-universal, and to depend intimately on the underlying distribution of interactions. Above the phase transition temperature, the system can be efficiently treated using a Bethe approximation, which shows a dependence on extreme value statistics. Relaxation timescales of this system tend to be slow, but can be made arbitrarily fast by increasing the number of neighbors of each particle.</p>","PeriodicalId":20207,"journal":{"name":"Physical biology","volume":null,"pages":null},"PeriodicalIF":2.0000,"publicationDate":"2022-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"On kinetics and extreme values in systems with random interactions.\",\"authors\":\"Martin Girard\",\"doi\":\"10.1088/1478-3975/aca9b2\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Biological environments such as the cytoplasm are comprised of many different molecules, which makes explicit modeling intractable. In the spirit of Wigner, one may be tempted to assume interactions to derive from a random distribution. Via this approximation, the system can be efficiently treated in the mean-field, and general statements about expected behavior of such systems can be made. Here, I study systems of particles interacting via random potentials, outside of mean-field approximations. These systems exhibit a phase transition temperature, under which part of the components precipitate. The nature of this transition appears to be non-universal, and to depend intimately on the underlying distribution of interactions. Above the phase transition temperature, the system can be efficiently treated using a Bethe approximation, which shows a dependence on extreme value statistics. Relaxation timescales of this system tend to be slow, but can be made arbitrarily fast by increasing the number of neighbors of each particle.</p>\",\"PeriodicalId\":20207,\"journal\":{\"name\":\"Physical biology\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.0000,\"publicationDate\":\"2022-12-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Physical biology\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1088/1478-3975/aca9b2\",\"RegionNum\":4,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"BIOCHEMISTRY & MOLECULAR BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Physical biology","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1088/1478-3975/aca9b2","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
On kinetics and extreme values in systems with random interactions.
Biological environments such as the cytoplasm are comprised of many different molecules, which makes explicit modeling intractable. In the spirit of Wigner, one may be tempted to assume interactions to derive from a random distribution. Via this approximation, the system can be efficiently treated in the mean-field, and general statements about expected behavior of such systems can be made. Here, I study systems of particles interacting via random potentials, outside of mean-field approximations. These systems exhibit a phase transition temperature, under which part of the components precipitate. The nature of this transition appears to be non-universal, and to depend intimately on the underlying distribution of interactions. Above the phase transition temperature, the system can be efficiently treated using a Bethe approximation, which shows a dependence on extreme value statistics. Relaxation timescales of this system tend to be slow, but can be made arbitrarily fast by increasing the number of neighbors of each particle.
期刊介绍:
Physical Biology publishes articles in the broad interdisciplinary field bridging biology with the physical sciences and engineering. This journal focuses on research in which quantitative approaches – experimental, theoretical and modeling – lead to new insights into biological systems at all scales of space and time, and all levels of organizational complexity.
Physical Biology accepts contributions from a wide range of biological sub-fields, including topics such as:
molecular biophysics, including single molecule studies, protein-protein and protein-DNA interactions
subcellular structures, organelle dynamics, membranes, protein assemblies, chromosome structure
intracellular processes, e.g. cytoskeleton dynamics, cellular transport, cell division
systems biology, e.g. signaling, gene regulation and metabolic networks
cells and their microenvironment, e.g. cell mechanics and motility, chemotaxis, extracellular matrix, biofilms
cell-material interactions, e.g. biointerfaces, electrical stimulation and sensing, endocytosis
cell-cell interactions, cell aggregates, organoids, tissues and organs
developmental dynamics, including pattern formation and morphogenesis
physical and evolutionary aspects of disease, e.g. cancer progression, amyloid formation
neuronal systems, including information processing by networks, memory and learning
population dynamics, ecology, and evolution
collective action and emergence of collective phenomena.