We investigate the quench dynamics of an open quantum system involving a quantum phase transition. In the isolated case, the quench dynamics involving the phase transition exhibits a number of scaling relations with the quench rate as predicted by the celebrated Kibble-Zurek mechanism. In contact with an environment however, these scaling laws break down and one may observe an anti-Kibble-Zurek behavior: slower ramps lead to less adiabatic dynamics, increasing thus nonadiabatic effects with the quench time. In contrast to previous works, we show here that such anti-Kibble-Zurek scaling can acquire a universal form in the sense that it is determined by the equilibrium critical exponents of the phase transition, provided the excited states of the system exhibit singular behavior, as observed in fully connected models. This demonstrates novel universal scaling laws granted by a system-environment interaction in a critical system. We illustrate these findings in two fully connected models, namely, the quantum Rabi and the Lipkin-Meshkov-Glick models. In addition, we discuss the impact of nonlinear ramps and finite-size systems.
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http://dx.doi.org/10.1103/PhysRevLett.124.230602 | DOI Listing |
Clin Exp Med
January 2025
Department of Thoracic Surgery, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, China.
Introduction Recently, immune cells within the tumor microenvironment (TME) have become crucial in regulating cancer progression and treatment responses. The dynamic interactions between tumors and immune cells are emerging as a promising strategy to activate the host's immune system against various cancers. The development and progression of hepatocellular carcinoma (HCC) involve complex biological processes, with the role of the TME and tumor phenotypes still not fully understood.
View Article and Find Full Text PDFCell Physiol Biochem
January 2025
UR-UPJV 4667, UFR Sciences, Université de Picardie Jules Verne, Amiens, France,
Quiescent pancreatic stellate cells (PSCs) represent only a very low proportion of the pancreatic tissue, but their activation leads to stroma remodeling and fibrosis associated with pathologies such as chronic pancreatitis and pancreatic ductal adenocarcinoma (PDAC). PSC activation can be induced by various stresses, including acidosis, growth factors (PDGF, TGFβ), hypoxia, high pressure, or intercellular communication with pancreatic cancer cells. Activated PSC targeting represents a promising therapeutic strategy, but little is known regarding the molecular mechanisms underlying the activation of PSCs.
View Article and Find Full Text PDFIndian J Thorac Cardiovasc Surg
February 2025
Department of Cardiology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230001 Anhui China.
Purpose: Acute aortic dissection is a serious cardiovascular emergency with a high mortality rate. Its pathogenesis is complex and remains unclear. This study aimed to assess the connection between the levels of genetically predicted circulating metabolites and the risk of aortic dissection.
View Article and Find Full Text PDFEur J Prev Cardiol
January 2025
Brigham and Women's Hospital, Boston, MA.
Aims: Hepcidin regulates plasma and tissue iron levels. We studied the association of hepcidin levels with the risk of incident heart failure (HF) and cardiac dysfunction in older adults.
Methods: We included adults from the ongoing, longitudinal Atherosclerosis Risk in Communities (ARIC) study who were free from prevalent anemia and HF at Visit 5 (2011-2013) and had available hepcidin and covariate data.
Bioinformatics
January 2025
Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, United States.
Motivation: Recent experimental developments enable single-cell multimodal epigenomic profiling, which measures multiple histone modifications and chromatin accessibility within the same cell. Such parallel measurements provide exciting new opportunities to investigate how epigenomic modalities vary together across cell types and states. A pivotal step in using this type of data is integrating the epigenomic modalities to learn a unified representation of each cell, but existing approaches are not designed to model the unique nature of this data type.
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