We study a Szilard engine based on a Gaussian state of a system consisting of two bosonic modes placed in a noisy channel. As the initial state of the system is taken an entangled squeezed thermal state, and the quantum work is extracted by performing a measurement on one of the two modes. We use the Markovian Kossakowski-Lindblad master equation for describing the time evolution of the open system and the quantum work definition based on the second order Rényi entropy to simulate the engine. We also study the information-work efficiency of the Szilard engine as a function of the system parameters. The efficiency is defined as the ratio of the extractable work averaged over the measurement angle and the erasure work, which is proportional to the information stored in the system. We show that the extractable quantum work increases with the temperature of the reservoir and the squeezing between the modes, average numbers of thermal photons and frequencies of the modes. The work increases also with the strength of the measurement, attaining the maximal values in the case of a heterodyne detection. The extractable work is decreasing by increasing the squeezing parameter of the noisy channel and it oscillates with the phase of the squeezed thermal reservoir. The efficiency mostly has a similar behavior with the extractable quantum work evolution. However information-work efficiency decreases with temperature, while the quantity of the extractable work increases.
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http://dx.doi.org/10.1038/s41598-021-03752-4 | DOI Listing |
Spectrochim Acta A Mol Biomol Spectrosc
December 2024
School of Agriculture and Bioengineering, Heze University, Heze 274500, China. Electronic address:
Herin, the successful synthesis of a bis Schiff base (L) has been achieved using 2-hydroxy-1-naphthaldehyde and 1,3-diaminoguanidine as raw materials, which was further characterized by infrared spectroscopy, mass spectrometry, and nuclear magnetic resonance hydrogen spectrum. Moreover, spectroscopic experiments demonstrated that the probe L showed good selectivity and visual detectability for Al. Its detection limit (DL) is 2.
View Article and Find Full Text PDFAnal Biochem
December 2024
Pharmaceutical Analytical Chemistry Department, Faculty of Pharmacy, Al-Azhar University, 11751 Nasr City, Cairo, Egypt. Electronic address:
Magnesium is an essential mineral in biological systems and has a significant impact on brain health. Its deficiency has been found to correlate with irregular metabolic processes and neurodevelopmental disorders. The objective of this research was to establish and validate an analytical approach based on the standard addition methodology for determining endogenous magnesium levels in the serum of autistic and healthy children.
View Article and Find Full Text PDFLangmuir
December 2024
Department of Physics, National Institute of Technology, Jamshedpur-831014, India.
We have conducted a systematic study employing density functional theory (DFT) and quantum theory of atoms in molecules (QTAIM) to explore the gas sensing capabilities of nitrogen-doped single vacancy graphene quantum dots (SV/3N) decorated with transition metals (TM = Mn, Co, Cu). We have studied the interactions between TM@SV/3N and four different target gases (AsH, NH, PH, and HS) through the computation of adsorption energies, charge transfer, noncovalent interaction, density of states, band gap, and work function for 12 distinct adsorption systems. Our comprehensive analysis included an in-depth assessment of sensors' stability, sensitivity, selectivity, and reusability for practical applications.
View Article and Find Full Text PDFNat Comput Sci
December 2024
Department of Materials Science and Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.
Machine learning plays an important role in quantum chemistry, providing fast-to-evaluate predictive models for various properties of molecules; however, most existing machine learning models for molecular electronic properties use density functional theory (DFT) databases as ground truth in training, and their prediction accuracy cannot surpass that of DFT. In this work we developed a unified machine learning method for electronic structures of organic molecules using the gold-standard CCSD(T) calculations as training data. Tested on hydrocarbon molecules, our model outperforms DFT with several widely used hybrid and double-hybrid functionals in terms of both computational cost and prediction accuracy of various quantum chemical properties.
View Article and Find Full Text PDFSci Rep
December 2024
Department of Physics, University of Liverpool, Oxford Street, Liverpool, L69 7ZE, UK.
Topological semimetals have recently garnered widespread interest in the quantum materials research community due to their symmetry-protected surface states with dissipationless transport which have potential applications in next-generation low-power electronic devices. One such material, [Formula: see text], exhibits Dirac nodal arcs and although the topological properties of single crystals have been investigated, there have been no reports in crystalline thin film geometry. We examined the growth of [Formula: see text] heterostructures on a range of single crystals by optimizing the electron beam evaporation of Pt and Sn and studied the effect of vacuum thermal annealing on phase and crystallinity.
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