Quantum Volume for Photonic Quantum Processors.

Defining metrics for near-term quantum computing processors has been an integral part of the quantum hardware research and development efforts. Such quantitative characteristics are not only useful for reporting the progress and comparing different quantum platforms but also essential for identifying the bottlenecks and designing a technology road map. Most metrics such as randomized benchmarking and quantum volume were originally introduced for circuit-based quantum computers and were not immediately applicable to measurement-based quantum computing (MBQC) processors such as in photonic devices. In this Letter, we close this long-standing gap by presenting a framework to map physical noises and imperfections in MBQC processes to logical errors in equivalent quantum circuits, whereby enabling the well-known metrics to characterize MBQC. To showcase our framework, we study a continuous-variable cluster state based on the Gottesman-Kitaev-Preskill (GKP) encoding as a near-term candidate for photonic quantum computing, and derive the effective logical gate error channels and calculate the quantum volume in terms of the GKP squeezing and photon transmission rate.

A theoretical study of new polar and magnetic double perovskites for photovoltaic applications.

Searching for novel functional materials has attracted significant interest for the breakthrough in photovoltaics to tackle the prevalent energy crisis. Through density functional theory calculations, we evaluate the structural, electronic, magnetic, and optical properties of new double perovskites Sn2MnTaO6 and Sn2FeTaO6 for potential photovoltaic applications. Our structural optimizations reveal a non-centrosymmetric distorted triclinic structure for the compounds. Using total energy calculations, antiferromagnetic and ferromagnetic orderings are predicted as the magnetic ground states for Sn2MnTaO6 and Sn2FeTaO6, respectively. The empty d orbitals of Ta5+-3d0 and partially filled d orbitals of Mn/Fe are the origins of ferroelectricity and magnetism in these double perovskites resulting in the potential multiferroicity. The studied double perovskites have semiconducting nature and possess narrow band gaps of approximately 1 eV. The absorption coefficient (α) calculations showed that the value of α in the visible region is in the order of 105 cm-1. The structural stability, suitable band gap, and high absorption coefficient values of proposed compounds suggest they could be good candidates for photovoltaic applications.

Photonic Materials Cloud: An Online Interactive Open Tool for Creating, Comparing, and Testing Photonic Materials.

Recent advances in nanoscale fabrication and characterization further accelerated research on photonics and plasmonics, which has already attracted long-standing interest. Alongside morphological constraints, phenomena in both fields highly depend on the materials' optical properties, dimensions, and surroundings. Building up the required knowledge and experience to design next-generation photonic devices can be a complex task for novice and experienced researchers who intend to evaluate the impact of subtle material and morphology variations while setting up experiments or getting a general overview. Here, we introduce the Photonic Materials Cloud (PMCloud), a web-based, interactive open tool for designing and analyzing photonic materials. PMCloud allows identification of the subtle differences between optical material models generated from a database, experimental data input, and inline-generated materials from various analytical models. Furthermore, it provides a fully interactive interface to evaluate their performance in important fundamental (numerical) optical experiments. We demonstrate PMCloud's applicability to state-of-the-art research questions, namely the comparison of the novel plasmonic materials aluminium-doped zinc oxide and zirconium nitride and the design of an optical, dielectric thin-film Bragg reflector. PMCloud opens a rapid, freely accessible path towards prototyping optical materials and simple fundamental devices and may serve as an educational platform for photonic materials research.

Measuring the customer satisfaction of public transportation in Tehran during the COVID-19 pandemic using MCDM techniques.

The expeditiously spreading of coronavirus disease 2019 (COVID-19) has affected every facet of human lives, including transportation. Due to some characteristics of COVID-19, like high infectivity, people prefer to use their private cars more than before. On the one hand, this circumstance caused public transportation to face an unprecedented decrease in demand and, consequently, revenue. On the other hand, it could intensify traffic congestion during rush hours. This study provides a computational framework to assess public transportation's customer satisfaction in Tehran during the COVID-19 pandemic. To this end, a combined multi-criteria decision-making (MCDM) approach based on the best-worst method (BWM) and fuzzy technique for order performance by similarity to ideal solution (fuzzy TOPSIS) is introduced, which benefits from all the advantages of BWM and fuzzy TOPSIS procedure and consequently provides consistent and reliable outcomes. Outcomes of the implemented model provide precious insight for improving service quality during and after the pandemic; for example, it reveals the performance of each transport mode about each criterion which can help policymakers and transit agencies to allocate resources more intelligently. Final results indicate that during the pandemic, taxis had a better performance compared to other transportation modes.

Designing new ferromagnetic double perovskites: the coexistence of polar distortion and half-metallicity.

Advancing technology and growing interdisciplinary fields raise the need for new materials that simultaneously possess several significant physics quantities to meet human demands. In this research, using density functional theory, we aim to design A2MnVO6 (A = Ca, Ba) as new double perovskites and investigate their structural, electronic, and magnetic properties. Structural calculations based on the total energies show the optimized monoclinic and orthorhombic crystal structures for the Ca2MnVO6 (CMVO) and Ba2MVO6 (BMVO) compounds, respectively. Through performing calculations, we reveal that the Jahn-Teller effect plays an important role in polar distortions of VO6 and elongation of MnO6 octahedra, resulting from the V5+(3d0) and Mn3+(3d4:t32ge1g) electron configurations. The spin-polarized calculations predict the half-metallic ferromagnetic ground state for CMVO and BMVO with a total magnetic moment of 4.00 µB f.u.-1 Our findings introduce CMVO and BMVO double perovskites as promising candidates for designing ferromagnetic polar half-metals and spintronic applications.

Density functional study of structural, electronic and magnetic properties of new half-metallic ferromagnetic double perovskite Sr2MnVO6.

In this paper, a new half-metallic (HM) double perovskite compound is predicted with the simultaneous presence of ferromagnetism and polar distortion. The structural, electronic and magnetic properties of Sr2MnVO6 (SMVO) are calculated by density functional theory (DFT) with both generalized gradient approximation (GGA) and GGA + U approaches, where U is the on-site Coulomb interaction parameter. Different orderings of B (B') cationic sites in A2BB'O6 double perovskite structure are evaluated, including rocksalt, columnar and layered arrangements for cubic, monoclinic and tetragonal crystal structures. It is found that the most stable ordering is obtained when B and B' are placed in a layered type ordering for a tetragonal crystal structure with I4/m space group, which is confirmed by phonon calculations. The B-site ordering of the Mn3+ and V5+ ions in a layered configuration leads to ferromagnetically coupled magnetic moments of 4.17 µ B at Mn site and 0.23 µ B at V site. Finally, SMVO is found to be a half-metallic ferromagnetic (HM-FM) compound with a band gap of 0.65 eV in a spin down channel with off-centered displacement of V atoms in the octahedral cage (second order Jahn -Teller effect) which can cause ferroelectricity. Therefore, SMVO is predicted to be a polar HM material and a promising candidate for multiferroic property with potential application in spintronics.

Risk factors associated with aortic calcification in hemodialysis patients.

BACKGROUND: There are some uncertainties among the risk factors of vascular calcification in the hemodialysis patients. This study was planned to examine the association between abdominal aortic calcification and concerned biochemical parameters in hemodialysis patients. METHODS: In this cross- sectional study, 84 stable hemodialysis patients admitted on hemodialysis section of Shahid Beheshti Hospital in 2013 were enrolled after obtaining informed consent. Pre-dialysis venous blood samples were taken from patients to determine the amount of intact parathyroid hormone (iPTH), alkaline phosphatase (Alk.P), C - reactive protein (CRP), calcium (Ca) and phosphorus (P). Patients underwent abdominal CT scanning and ACI (ACI) was calculated. Statistical analysis was performed using SPSS Version 20. Chi-square, Kruskal Wallis and One Way ANOVA tests were used. P-values < 0.05 were considered significant. RESULTS: The average age of participants was 50.15±17.03 years (18-83 y/o).A statistically significant correlation was observed between ACI and ALK-P serum levels (p=0.01). It was found that ACI had a significant relationship with phosphorus in women (p=0.01). ALK-P serum levels in men also had a significant relationship with ACI (p=0.02). In addition, there was a significant correlation between ACI and history of cerebro-cardiovascular disease and also duration of dialysis (p=0.004 and 0.0001, respectively). CONCLUSIONS: In patients with longer duration of dialysis, and patients with a history of cardiovascular and cerebrovascular events, ACI levels were significantly higher. ALK-P and phosphorus were correlated with aortic calcification in males and females respectively. No significant correlation was found between iPTH serum levels and aortic calcification.

Computational multiqubit tunnelling in programmable quantum annealers.

Quantum tunnelling is a phenomenon in which a quantum state traverses energy barriers higher than the energy of the state itself. Quantum tunnelling has been hypothesized as an advantageous physical resource for optimization in quantum annealing. However, computational multiqubit tunnelling has not yet been observed, and a theory of co-tunnelling under high- and low-frequency noises is lacking. Here we show that 8-qubit tunnelling plays a computational role in a currently available programmable quantum annealer. We devise a probe for tunnelling, a computational primitive where classical paths are trapped in a false minimum. In support of the design of quantum annealers we develop a nonperturbative theory of open quantum dynamics under realistic noise characteristics. This theory accurately predicts the rate of many-body dissipative quantum tunnelling subject to the polaron effect. Furthermore, we experimentally demonstrate that quantum tunnelling outperforms thermal hopping along classical paths for problems with up to 200 qubits containing the computational primitive.

Hessian facilitated analysis of optimally controlled quantum dynamics of systems with coupled primary and secondary states.

The efficacy of optimal control of quantum dynamics depends on the topology and associated local structure of the underlying control landscape defined as the objective as a function of the control field. A commonly studied control objective involves maximization of the transition probability for steering the quantum system from one state to another state. This paper invokes landscape Hessian analysis performed at an optimal solution to gain insight into the controlled dynamics, where the Hessian is the second-order functional derivative of the control objective with respect to the control field. Specifically, we consider a quantum system composed of coupled primary and secondary subspaces of energy levels with the initial and target states lying in the primary subspace. The primary and secondary subspaces may arise in various scenarios, for example, respectively, as sub-manifolds of ground and excited electronic states of a poly-atomic molecule, with each possessing a set of rotational-vibrational levels. The control field may engage the system through electric dipole transitions that occur either (I) only in the primary subspace, (II) between the two subspaces, or (III) only in the secondary subspace. Important insights about the resultant dynamics in each case are revealed in the structural patterns of the corresponding Hessian. The Fourier spectrum of the Hessian is shown to often be complementary to mechanistic insights provided by the optimal control field and population dynamics.

Vanishing quantum discord is necessary and sufficient for completely positive maps.

Two long-standing open problems in quantum theory are to characterize the class of initial system-bath states for which quantum dynamics is equivalent to (i) a map between the initial and final system states, and (ii) a completely positive (CP) map. The CP map problem is especially important, due to the widespread use of such maps in quantum information processing and open quantum systems theory. Here we settle both these questions by showing that the answer to the first is "all", with the resulting map being Hermitian, and that the answer to the second is that CP maps arise exclusively from the class of separable states with vanishing quantum discord.

Locally optimal control of quantum systems with strong feedback.

For quantum systems with high purity, we find all observables that, when continuously monitored, maximize the instantaneous reduction in the average linear entropy. This allows us to obtain all locally optimal feedback protocols with strong feedback, and explicit expressions for the best such protocols for systems of size N < or =4. We also show that for a qutrit the locally optimal protocol is the optimal protocol for observables with equispaced eigenvalues, providing the first fully optimal feedback protocol for a 3-state system.

Robust quantum error correction via convex optimization.

We present a semidefinite program optimization approach to quantum error correction that yields codes and recovery procedures that are robust against significant variations in the noise channel. Our approach allows us to optimize the encoding, recovery, or both, and is amenable to approximations that significantly improve computational cost while retaining fidelity. We illustrate our theory numerically for optimized 5-qubit codes, using the standard [5,1,3] code as a benchmark. Our optimized encoding and recovery yields fidelities that are uniformly higher by 1-2 orders of magnitude against random unitary weight-2 errors compared to the [5,1,3] code with standard recovery.