A rational secret sharing scheme is a game in which each party responsible for reconstructing a secret tries to maximize his or her utility by obtaining the secret alone. Quantum secret sharing schemes, derived either from quantum teleportation or from quantum error correcting code, do not succeed when we assume rational participants. This is because all existing quantum secret sharing schemes consider that the secret is reconstructed by a party chosen by the dealer. In this paper, for the first time, we propose a quantum secret sharing scheme which is resistant to rational parties. The proposed scheme is fair (everyone gets the secret), is correct, and achieves strict Nash equilibrium.

There is an exigency of transformation of the enormous amount of biological data available in various forms into some significant knowledge. We have tried to implement Machine Learning (ML) algorithm models on the protein–ligand binding affinity data already available to predict the binding affinity of the unknown. ML methods are appreciably faster and cheaper as compared to traditional experimental methods or computational scoring approaches. The prerequisites of this prediction are sufficient and unbiased features of training data and a prediction model which can fit the data well. In our study, we have applied Random forest and Gaussian process regression algorithms from the Weka package on protein–ligand binding affinity, which encompasses protein and ligand binding information from PdbBind database. The models are trained on the basis of selective fundamental information of both proteins and ligand, which can be effortlessly fetched from online databases or can be calculated with the availability of structure. The assessment of the models was made on the basis of correlation coefficient (R²) and root mean square error (RMSE). The Random forest model gave R² and RMSE of 0.76 and 1.31 respectively. We have also used our features and prediction models on the dataset used by others and found that our model with our features outperformed the existing ones.

In quantum private query (QPQ), a client obtains values corresponding to his or her query only, and nothing else from the server, and the server does not get any information about the queries. V. Giovannetti et al. [ Phys. Rev. Lett. 100, 230502 (2008)] gave the first QPQ protocol and since then quite a few variants and extensions have been proposed. However, none of the existing protocols are device independent; i.e., all of them assume implicitly that the entangled states supplied to the client and the server are of a certain form. In this work, we exploit the idea of a local CHSH game and connect it with the scheme of Y. G. Yang et al. [ Quantum Info. Process. 13, 805 (2014)] to present the concept of a device-independent QPQ protocol.

Established heat engines in quantum regime can be modeled with various quantum systems as working substances. For example, in the non-relativistic case, we can model the heat engine using infinite potential well as a working substance to evaluate the efficiency and work done of the engine. Here, we propose quantum heat engine with a relativistic particle confined in the one-dimensional potential well as working substance. The cycle comprises of two isothermal processes and two potential well processes of equal width, which forms the quantum counterpart of the known isochoric process in classical nature. For a concrete interpretation about the relation between the quantum observables with the physically measurable parameters (like the efficiency and work done), we develop a link between the thermodynamic variables and the uncertainty relation. We have used this model to explore the work extraction and the efficiency of the heat engine for a relativistic case from the standpoint of uncertainty relation, where the incompatible observables are the position and the momentum operators. We are able to determine the bounds (the upper and the lower bounds) of the efficiency of the heat engine through the thermal uncertainty relation.

According to the Landauer principle, any logically irreversible process accompanies entropy production, which results in heat dissipation in the environment. Erasing of information, one of the primary logically irreversible processes, has a lower bound on heat dissipated into the environment, called the Landauer bound (LB). However, the practical erasure processes dissipate much more heat than the LB. Recently, there have been a few experimental investigations to reach this bound both in the classical and quantum domains. There has also been a spate of activities to enquire about this LB in finite time, with finite-size heat baths, non-Markovian and nonequilibrium environments in the quantum regime where the effects of fluctuations and correlation of the systems with the bath can no longer be ignored. This article provides a comprehensive review of the recent progress on the LB, which serves as a fundamental principle in the thermodynamics of computation. We also provide a perspective for future endeavors in these directions. Furthermore, we review the recent explorations toward establishing energetic bounds of a computational process. We also discuss the thermodynamic aspects of error correction, which is an indispensable part of information processing and computations. In doing so, we briefly discuss the basics of these fields to provide a complete picture.

Quantum cycles in established heat engines can be modeled with various quantum systems as working substances. For example, a heat engine can be modeled with an infinite potential well as the working substance to determine the efficiency and work done. However, in this method, the relationship between the quantum observables and the physically measurable parameters—i.e., the efficiency and work done—is not well understood from the quantum mechanics approach. A detailed analysis is needed to link the thermodynamic variables (on which the efficiency and work done depends) with the uncertainty principle for better understanding. Here, we present the connection of the sum uncertainty relation of position and momentum operators with thermodynamic variables in the quantum heat engine model. We are able to determine the upper and lower bounds on the efficiency of the heat engine through the uncertainty relation.