RDMS

Recent advances in quantum crystallography have shown that, beyond conventional charge density refinement, a one-electron reduced density matrix (1-RDM) satisfying N-representability conditions can be reconstructed using jointly experimental X-ray structure factors and directional Compton profiles (DCP) through semidefinite programming. So far, such reconstruction methods for 1-RDM, not constrained to idempotency, have been tested only on a toy model system (CO2 ). In this work, a new method is assessed on crystalline urea [CO(NH2 )2 ] using static (0 K) and dynamic (50 K) artificial experimental data...

The implementation of multireference configuration interaction (MRCI) methods in quantum systems with large active spaces is hindered by the expansion of configuration bases or the intricate handling of reduced density matrices (RDMs). In this work, we present a spin-adapted renormalized-residue-based MRCI (RR-MRCI) approach that leverages renormalized residues to effectively capture the entanglement between active and inactive orbitals. This approach is reinforced by a novel efficient algorithm, which also facilitates an efficient deployment of spin-adapted matrix product state MRCI (MPS-MRCI)...

BACKGROUND: Immunotherapies such as immune checkpoint inhibitors (ICI) are effective in multiple tumor entities but induce a plethora of side effects. Comprehensive real-world analyses are essential to identify new signals, characterize diagnostic features, enable risk assessment, determine pathomechanisms, assess effectiveness of side effect management and compare tumor outcomes. METHODS: The international online `Side-Effect Registry Immuno-Oncology´ (SERIO; www...

In this work, an internally contracted stochastic complete active space second-order perturbation theory, stochastic-CASPT2, is reported. The method relies on stochastically sampled reduced density matrices (RDMs) up to rank four and contractions thereof with the generalized Fock matrix. A new protocol for calculating higher-order RDMs in full configuration interaction quantum Monte Carlo (FCIQMC) has been designed based on (1) restricting sampling of the corresponding excitations to a deterministic subspace, (2) averaging the RDMs from independent dynamics and (3) projecting them onto the closest positive semi-definite matrix...

Recombination is a key evolutionary driver in shaping novel viral populations and lineages. When unaccounted for, recombination can impact evolutionary estimations or complicate their interpretation. Therefore, identifying signals for recombination in sequencing data is a key prerequisite to further analyses. A repertoire of recombination detection methods (RDMs) have been developed over the past two decades; however, the prevalence of pandemic-scale viral sequencing data poses a computational challenge for existing methods...

Sydney Harbour (Australia). is one of the most metal-contaminated in the world and sediments are toxic over large areas. The major source of metals is stormwater, however there remains considerable debate regarding the source of metals in water entering the estuary. The current review and critical assessment of a large source of data accumulated from over three decades of research, supplemented by global studies, identified road-derived metals (RDMs) as the chief contributor of metals to stormwater and consequently to pollution of the estuary...

In this work, we present a detailed analysis of statistical errors in reduced density matrices (RDMs) of active space wavefunctions sampled from quantum circuit simulation and the impact on results obtained by the multireference theories. From the sampling experiments, it is shown that the errors in sampled RDMs have a larger value for higher-order RDMs, and that the errors in sampled RDMs for excited states are larger than those for the ground state. We analytically derive the expected value of the sum of squared errors between the true distribution and sample distribution of weights of the electron configurations based on a multinomial distribution model, with which we present an assessment of the dependency of RDM errors on the number of shots for the observation ( N shot ) and on the character of the target electronic state...

Thanks to the high compression of the matrix product state (MPS) form of the wave function and the efficient site-by-site iterative sweeping optimization algorithm, the density matrix normalization group (DMRG) and its time-dependent variant (TD-DMRG) have been established as powerful computational tools in accurately simulating the electronic structure and quantum dynamics of strongly correlated molecules with a large number (101-2 ) of quantum degrees of freedom (active orbitals or vibrational modes). However, the quantitative characterization of the quantum many-body behaviors of realistic strongly correlated systems requires a further consideration of the interaction between the embedded active subsystem and the remaining correlated environment, e...

According to a classical view of face perception (Bruce and Young, 1986, Haxby et al., 2000) face identity and facial expression recognition are performed by separate neural substrates (ventral and lateral temporal face-selective regions, respectively). However, recent studies challenge this view, showing that expression valence can also be decoded from ventral regions (Skerry and Saxe, 2014, Li et al., 2019), and identity from lateral regions (Anzellotti and Caramazza, 2017) These findings could be reconciled with the classical view if regions specialized for one task (either identity or expression) contain a small amount of information for the other task (that enables above-chance decoding)...

Here we present a many-body theory based on a solution of the N-representability problem in which the ground-state two-particle reduced density matrix (2-RDM) is determined directly without the many-particle wave function. We derive an equation that re-expresses physical constraints on higher-order RDMs to generate direct constraints on the 2-RDM, which are required for its derivation from an N-particle density matrix, known as N-representability conditions. The approach produces a complete hierarchy of 2-RDM constraints that do not depend explicitly upon the higher RDMs or the wave function...

Due to the concerns about radiation dose associated with medical imaging, radiation dose monitoring systems (RDMSs) are now utilized by many radiology providers to collect, process, analyze, and manage radiation dose-related information. Currently, most commercially available RDMSs focus only on radiation dose information and do not track any metrics related to image quality. However, to enable comprehensive patient-based imaging optimization, it is equally important to monitor image quality as well. This article describes how RDMS design can be extended beyond radiation dose to simultaneously monitor image quality...

A systematic literature review was carried out to explore articles that reported the use of radiation dose management systems (RDMSs) in computed tomography (CT). The preferred reporting items for systematic review and meta-analysis flow chart were used to screen articles in PubMed, EBSCOhost, Web of Science, SCOPUS and Cochrane Library. A total of 1041 articles were retrieved and screened. After evaluation against criteria, 38 articles were selected and synthesised narratively. The results revealed that several RDMSs have been used in CT...

Plasmon resonance energy transfer (PRET), which occurs between plasmonic nanoparticles (NPs) and organic dyes, shows significant potential in sensing chemistry due to its high sensitivity at the single-particle level. In this work, a PRET-based sensing strategy was presented for the ultrasensitive sensing of nitric oxide (NO) in living cells. Supramolecular cyclodextrin (CD) molecules that exhibited different binding abilities to various molecules due to its unique rigid structure and annular cavity was applied and modified on gold NPs (GNPs) to construct the PRET nanosensors...

We extend molecular bootstrap embedding to make it appropriate for implementation on a quantum computer. This enables solution of the electronic structure problem of a large molecule as an optimization problem for a composite Lagrangian governing fragments of the total system, in such a way that fragment solutions can harness the capabilities of quantum computers. By employing state-of-art quantum subroutines including the quantum SWAP test and quantum amplitude amplification, we show how a quadratic speedup can be obtained over the classical algorithm, in principle...

A multiconfigurational adiabatic connection (AC) formalism is an attractive approach to compute the dynamic correlation within the complete active space self-consistent field and density matrix renormalization group (DMRG) models. Practical realizations of AC have been based on two approximations: (i) fixing one- and two-electron reduced density matrices (1- and 2-RDMs) at the zero-coupling constant limit and (ii) extended random phase approximation (ERPA). This work investigates the effect of removing the "fixed-RDM" approximation in AC...

We present an algorithm for evaluating analytic nuclear energy gradients of the state-averaged density matrix renormalization group complete-active-space self-consistent field (SA-DMRG-CASSCF) theory based on the newly derived coupled-perturbed (CP) DMRG-CASSCF equations. The Lagrangian for the conventional SA-CASSCF analytic gradient theory is extended to the SA-DMRG-CASSCF variant that can fully consider a whole set of constraints on the parameters of multi-root canonical matrix product states formed at all the DMRG block configurations...

Within this perspective article, we intend to summarise definitions and terms that are often used in the context of open science and data-driven R&D and we discuss upcoming European regulations concerning data, data sharing and handling. With this background in hand, we take a closer look at the potential connections and permeable interfaces of open science and digital economy, in which data and resulting immaterial goods can become vital pieces as tradeable items. We believe that both science and the digital economy can profit from a seamless transition and foresee that the scientific outcomes of publicly funded research can be better exploited...

INTRODUCTION: The COVID-19 pandemic disrupted newborn care and breastfeeding practices across most healthcare facilities. We undertook this study to explore the barriers and enablers for newborn care and breastfeeding practices in hospitals in Delhi, India for recently delivered mother (RDM)-newborn dyads during the first wave of the COVID-19 pandemic (2020) and inductively design a "pathway of impaction" for informing mitigatory initiatives during the current and future pandemics, at least in the initial months...

Random Dot Motion (RDM) displays refer to clouds of independently moving dots that can be parametrically manipulated to provide a perception of the overall cloud moving coherently in a specified direction of motion. As a well-studied probe of motion perception, RDMs have been widely employed to understand underlying neural mechanisms of motion perception, perceptual decision-making, and perceptual learning, among other processes. Despite their wide use, RDM stimuli implementation is highly dependent on the parameters and the generation algorithm of the stimuli; both can greatly influence behavioral performance on RDM tasks...

Electrocardiographic imaging (ECGI) can aid in identifying the driving sources that cause and sustain atrial fibrillation (AF). Traditional regularization strategies for addressing the ECGI inverse problem are not currently concerned about the multi-scale analysis of the inverse problem, and these techniques are not clinically reliable. We have previously investigated the solution based on uniform phase mode decomposition (UPEMD-based) to the ECGI inverse problem. Numerous other methods for the time-frequency analysis derived from empirical mode decomposition (EMD-based) have not been applied to the inverse problem in ECGI...