arXiv subjects

A. Chakraborti

Publications and source records attributed to A. Chakraborti.

7 recordsLinked to original sources

arXiv2026

Nanosecond timescale plasticity in shock-compressed polycrystalline MgO: evidence for transition in mechanism above 100 GPa

The mechanical properties of ceramics under extreme conditions directly impact applications ranging from shielding spacecrafts, designing plasma facing materials in nuclear fusion to understanding the rheology of deep planetary interiors. Here, we use polycrystalline MgO as a model ceramic to understand the high-pressure-temperature mechanical behaviour of such materials under extreme strain rates. We use laser-driven shock compression up to 175(15) GPa on the principal Hugoniot along with ultrafast diagnostics at the European X-ray Free Electron Laser to probe the dominant deformation mechanisms with changing P -T conditions. These near-instantaneous time-resolved snapshots, coupled with elasto-viscoplastic self-consistent (EVPSC) simulations, strongly suggest that MgO attains plastic regime in the nanoseconds scale accompanied by a pressure-mediated change in dominant slip system between 95 and 175 GPa. This work provides a new direct window into the deformation dynamics of polycrystalline ceramics under high-velocity impacts.

cond-mat.mtrl-sci↗

arXiv2026

Volume Collapse Without a Structural Transition in Shock-Compressed FeO

We report x-ray diffraction and emission spectroscopy of FeO under laser-driven shock compression between 31-199 GPa. FeO retains the B1 (rocksalt) structure along the Hugoniot to the melt boundary at 191 GPa. While the phase and volume are broadly consistent with results from static compression, we observe an anomalous 7-10% volume collapse around 60 GPa absent in static experiments. We identify this as an isostructural high-spin to low-spin metallic transition in FeO. The low-spin state is directly evidenced by x-ray emission spectroscopy at 180 GPa.

cond-mat.mtrl-sci↗

arXiv2007

Financial time-series analysis: A brief overview

Prices of commodities or assets produce what is called time-series. Different kinds of financial time-series have been recorded and studied for decades. Nowadays, all transactions on a financial market are recorded, leading to a huge amount of data available, either for free in the Internet or commercially. Financial time-series analysis is of great interest to practitioners as well as to theoreticians, for making inferences and predictions. Furthermore, the stochastic uncertainties inherent in financial time-series and the theory needed to deal with them make the subject especially interesting not only to economists, but also to statisticians and physicists. While it would be a formidable task to make an exhaustive review on the topic, with this review we try to give a flavor of some of its aspects.

q-fin.ST↗

arXiv2003

Asset trees and asset graphs in financial markets

This paper introduces a new methodology for constructing a network of companies called a dynamic asset graph. This is similar to the dynamic asset tree studied recently, as both are based on correlations between asset returns. However, the new modified methodology does not, in general, lead to a tree but a graph, or several graphs that need not be inter-connected. The asset tree, due to the minimum spanning tree criterion, is forced to ``accept'' edge lengths that are far less optimal (longer) than the asset graph, thus resulting in higher overall length for the tree. The same criterion also causes asset trees to be more fragile in structure when measured by the single-step survival ratio. Over longer time periods, in the beginning the asset graph decays more slowly than the asset tree, but in the long-run the situation is reversed. The vertex degree distributions indicate that the possible scale free behavior of the asset graph is not as evident as it is in the case of the asset tree.

cond-mat.stat-mech↗

arXiv2003

Dynamics of market correlations: Taxonomy and portfolio analysis

The time dependence of the recently introduced minimum spanning tree description of correlations between stocks, called the ``asset tree'' have been studied to reflect the economic taxonomy. The nodes of the tree are identified with stocks and the distance between them is a unique function of the corresponding element of the correlation matrix. By using the concept of a central vertex, chosen as the most strongly connected node of the tree, an important characteristic is defined by the mean occupation layer (MOL). During crashes the strong global correlation in the market manifests itself by a low value of MOL. The tree seems to have a scale free structure where the scaling exponent of the degree distribution is different for `business as usual' and `crash' periods. The basic structure of the tree topology is very robust with respect to time. We also point out that the diversification aspect of portfolio optimization results in the fact that the assets of the classic Markowitz portfolio are always located on the outer leaves of the tree. Technical aspects like the window size dependence of the investigated quantities are also discussed.

cond-mat.stat-mech↗

arXiv2002

Dynamic asset trees and Black Monday

The minimum spanning tree, based on the concept of ultrametricity, is constructed from the correlation matrix of stock returns. The dynamics of this asset tree can be characterised by its normalised length and the mean occupation layer, as measured from an appropriately chosen centre called the `central node'. We show how the tree length shrinks during a stock market crisis, Black Monday in this case, and how a strong reconfiguration takes place, resulting in topological shrinking of the tree.

cond-mat.stat-mech↗

arXiv2002

Dynamic asset trees and portfolio analysis

The minimum spanning tree, based on the concept of ultrametricity, is constructed from the correlation matrix of stock returns and provides a meaningful economic taxonomy of the stock market. In order to study the dynamics of this asset tree we characterize it by its normalized length and by the mean occupation layer, as measured from an appropriately chosen center. We show how the tree evolves over time, and how it shrinks particularly strongly during a stock market crisis. We then demonstrate that the assets of the optimal Markowitz portfolio lie practically at all times on the outskirts of the tree. We also show that the normalized tree length and the investment diversification potential are very strongly correlated.

cond-mat.stat-mech↗