Search

Solving the electronic Schrodinger equation for strongly correlated ground states is a long-standing challenge. We present quantum algorithms for the variational optimization of wave functions correlated by products of unitary operators, such as Local Unitary Cluster Jastrow (LUCJ) ansatzes, using stochastic reconfiguration (SR) and the linear method (LM). While an implementation on classical computing hardware would require exponentially growing compute cost, the cost (number of circuits and shots) of our quantum algorithms is polynomial in system size. We find that classical simulations of optimization with the linear method consistently find lower energy solutions than with the L-BFGS-B optimizer across the dissociation curves of the notoriously difficult N2and C2dimers; LUCJ predictions of the ground-state energies deviate from exact diagonalization by 1 kcal/mol or less at all points on the potential energy curve. While we do characterize the effect of shot noise on the LM optimization, these noiseless results highlight the critical but often overlooked role that optimization techniques must play in attacking the electronic structure problem (on both classical and quantum hardware), for which even mean-field optimization is formally NP hard. We also discuss the challenge of obtaining smooth curves in these strongly correlated regimes, and propose a number of quantum-friendly solutions ranging from symmetry-projected ansatz forms to a symmetry-constrained optimization algorithm.

Green’s function methods lead to ab initio, systematically improvable simulations of molecules and materials while providing access to multiple experimentally observable properties such as the density of states and the spectral function. The calculation of the exact one-particle Green’s function remains a significant challenge for classical computers and was attempted only on very small systems. Here, we present a hybrid quantum-classical algorithm to calculate the imaginary-time one-particle Green’s function. The proposed algorithm combines the variational quantum eigensolver and the quantum subspace expansion methods to calculate Green’s function in Lehmann’s representation. We demonstrate the validity of this algorithm by simulating H2and H4on quantum simulators and on IBM’s quantum devices.

Introduction: Non-critically ill neonates at times require venous access to provide peripherally compatible infusions for a limited period (more than 3 days). In such a situation, short peripheral cannulas are not appropriate as their average duration is about 2 days, while—on the other hand—epicutaneous-caval catheters may be too invasive. In these patients, insertion of long peripheral cannulas may be an effective option.Methods: In this observational retrospective study, we revised all “long” peripheral catheters (4 and 6 cm long) inserted by direct Seldinger technique in our neonatal intensive care unit when peripheral venous access was required for more than 3 days.Results: We inserted 52 2Fr polyurethane catheters, either 4 cm long (n= 25) or 6 cm long (n= 27) in 52 patients. Mean dwelling time was 4.17 days (range 1–12). Most devices were inserted in the cephalic vein (n= 18, 35%), and the rest in the saphenous vein (n= 11, 21%) and other superficial veins. There was no significant correlation between the duration of the device and type of infusion (p=0.40). The main complications were infiltration (n= 16, 31%) and phlebitis (n= 8, 15%). The rate of removal due to complications was significantly higher (p< 0.01) in neonates with bodyweight <2000 g at the time of insertion.Conclusion: In our experience, 2 Fr 4–6 cm long peripheral catheters may be a valid option for neonates requiring peripherally compatible infusions for more than 3 days. The limits of this study are the necessity of training in the technique of insertion and the small size of our sample. The longest dwell was observed in neonates weighing >2000 g at the time of LPC insertion.

Quantum computers promise to solve certain computational problems much faster than classical computers. However, current quantum processors are limited by their modest size and appreciable error rates. Recent efforts to demonstrate quantum speedups have therefore focused on problems that are both classically hard and naturally suited to current quantum hardware, such as sampling from complicated—although not explicitly useful—probability distributions1–3. Here we introduce and experimentally demonstrate a quantum algorithm that is similarly well suited to current hardware, but which samples from complicated distributions arising in several applications. The algorithm performs Markov chain Monte Carlo (MCMC), a prominent iterative technique4, to sample from the Boltzmann distribution of classical Ising models. Unlike most near-term quantum algorithms, ours provably converges to the correct distribution, despite being hard to simulate classically. But like most MCMC algorithms, its convergence rate is difficult to establish theoretically, so we instead analysed it through both experiments and simulations. In experiments, our quantum algorithm converged in fewer iterations than common classical MCMC alternatives, suggesting unusual robustness to noise. In simulations, we observed a polynomial speedup between cubic and quartic over such alternatives. This empirical speedup, should it persist to larger scales, could ease computational bottlenecks posed by this sampling problem in machine learning5, statistical physics6and optimization7. This algorithm therefore opens a new path for quantum computers to solve useful—not merely difficult—sampling problems.

The performance of computational methods for many-body physics and chemistry is strongly dependent on the choice of the basis used to formulate the problem. Hence, the search for similarity transformations that yield better bases is important for progress in the field. So far, tools from theoretical quantum information have not been thoroughly explored for this task. Here we take a step in this direction by presenting efficiently computable Clifford similarity transformations for the molecular electronic structure Hamiltonian, which expose bases with reduced entanglement in the corresponding molecular ground states. These transformations are constructed via block-diagonalization of a hierarchy of truncated molecular Hamiltonians, preserving the full spectrum of the original problem. We show that the bases introduced here allow for more efficient classical and quantum computations of ground-state properties. First, we find a systematic reduction of bipartite entanglement in molecular ground states as compared to standard problem representations. This entanglement reduction has implications in classical numerical methods, such as those based on the density matrix renormalization group. Then, we develop variational quantum algorithms that exploit the structure in the new bases, showing again improved results when the hierarchical Clifford transformations are used.

Advances in quantum computation for electronic structure, and particularly heuristic quantum algorithms, create an ongoing need to characterize the performance and limitations of these methods. Here we discuss some potential pitfalls connected with the use of hardware-efficient Ansätze in variational quantum simulations of electronic structure. We illustrate that hardware-efficient Ansätze may break Hamiltonian symmetries and yield nondifferentiable potential energy curves, in addition to the well-known difficulty of optimizing variational parameters. We discuss the interplay between these limitations by carrying out a comparative analysis of hardware-efficient Ansätze versus unitary coupled cluster and full configuration interaction, and of second- and first-quantization strategies to encode Fermionic degrees of freedom to qubits. Our analysis should be useful in understanding potential limitations and in identifying possible areas of improvement in hardware-efficient Ansätze.

Quantum many-body systems subjected to unitary evolution with the addition of interspersed measurements exhibit a variety of dynamical phases that do not occur under pure unitary evolution. However, these systems remain challenging to investigate on near-term quantum hardware owing to the need for numerous ancilla qubits or repeated high-fidelity mid-circuit measurements, a capability that has only recently become available. Here we report the realization of a measurement-induced entanglement phase transition with a hybrid random circuit on up to 14 superconducting qubits with mid-circuit readout capability. We directly observe extensive and sub-extensive scaling of entanglement entropy in the volume- and area-law phases, respectively, by varying the rate of the measurements. We also demonstrate phenomenological critical behaviour by performing a data collapse of the measured entanglement entropy. Our work establishes the use of mid-circuit measurement as a powerful resource for quantum simulation on near-term quantum computers.

The process of achieving decarbonization and greenhouse emissions’ reduction goals is facilitated and accelerated by the implementation of renewable-based DH rather than multiple individual renewables systems. This work presents an application case that demonstrates how an energy system based on conventional and carbon-emitting heat supply sources can be converted in a fully renewable network.

District heating networks have present and future great potential in decarbonization and in general for improving the environmental profile of the European building sector. It is due to the integration of solar-thermal energy and other renewable sources, flexibility by thermal storage, and mainly the ability to recover industrial and municipal waste heat: providing benefits at the element (energy system) and city level. However, individual appliances, such as electric-driven heat pumps, are and will be an attractive option; the decarbonization process of the European electricity grid makes them very appealing from an environmental perspective (from an energy system viewpoint). In this paper, the authors investigate the environmental competitiveness of a district heating network to provide space heating and domestic hot water using the Life Cycle Assessment method. The evaluation was carried out for a new building area (approx. 26 500 m2of net surface) located in Milan. The present and future (2030) environmental profiles of North Milan’s district heating network were assessed and compared with three individual electric-driven heat pumps (groundwater-source and 450 kW capacity each), as an alternative energy system. 16 potential impact categories were evaluated using, 1 kWh of thermal energy as a functional unit, ecoinvent as background database, and the Environmental Footprint 3.0 as impact assessment method. The results indicated that despite the higher CO2eq emissions compared to the heat pumps (208 vs 118 gCO2eq/kWhth), district heating could potentially have an almost equivalent climate change impact in the future, due to the integration of renewables sources, feasible with the 4th generation. The value of district heating and electric-driven heat pumps were 89 and 81 gCO2eq/kWhth, respectively for 2030. In contrast, the weighting results showed a better environmental profile for the district heating in both scenarios, allowing a reduction of 67% (in the present) and 19% (in the future).

The goal of this work is to present challenges and opportunities for the development of 4th generation district heating in future decarbonized scenarios for the Italian city of Milano. The work has been developed in the framework of a Climate-KIC project to support Milano municipality in developing decarbonization measures. The first part of the work consists in the evaluation of a geographical distribution of the civil sector heat demand according to a bottom-up approach based on open data. Thanks to this statistical tool, also buildings retrofit can be analysed. Three retrofit scenarios are simulated according to policy goals for 2030 and 2050, foreseeing a retrofit priority of worst energy performances buildings, resulting in 8.8TWh, for the first two scenarios, and 9.4TWh for the last one. The areas characterized by the majority of retrofit can be identified as the most suitable for low temperature district heating development. Renewables and low temperature waste heat sources are also assessed, resulting in 9.8TWh of available heat. The application of district heating in combination with the identified renewables is assessed in these scenarios with a clustering approach. The evaluation of potential diffusion of 4GDH is based on the comparison between the overall cost of district heating and the competing individual systems costs: district heating is considered feasible only in retrofitted buildings where district heating cost is lower than individual systems cost (about 0.7TWh in each scenarios). The retrofitting scenarios combined with the diffusion of renewable based 4GDH are assessed also in terms of environmental impact. The current greenhouse gas emissions related to the actual heating systems, evaluated through the Thermal Systems Regional Cadastre database, is compared to the district heating development scenarios and to individual heat pump system scenarios. The results show the highest reduction of emission in the district heating scenarios (65%).

The accurate computation of Hamiltonian ground, excited and thermal states on quantum computers stands to impact many problems in the physical and computer sciences, from quantum simulation to machine learning. Given the challenges posed in constructing large-scale quantum computers, these tasks should be carried out in a resource-efficient way. In this regard, existing techniques based on phase estimation or variational algorithms display potential disadvantages; phase estimation requires deep circuits with ancillae, that are hard to execute reliably without error correction, while variational algorithms, while flexible with respect to circuit depth, entail additional high-dimensional classical optimization. Here, we introduce the quantum imaginary time evolution and quantum Lanczos algorithms, which are analogues of classical algorithms for finding ground and excited states. Compared with their classical counterparts, they require exponentially less space and time per iteration, and can be implemented without deep circuits and ancillae, or high-dimensional optimization. We furthermore discuss quantum imaginary time evolution as a subroutine to generate Gibbs averages through an analogue of minimally entangled typical thermal states. Finally, we demonstrate the potential of these algorithms via an implementation using exact classical emulation as well as through prototype circuits on the Rigetti quantum virtual machine and Aspen-1 quantum processing unit.

We describe an algorithm to reduce the cost of auxiliary-field quantum Monte Carlo (AFQMC) calculations for the electronic structure problem. The technique uses a nested low-rank factorization of the electron repulsion integral (ERI). While the cost of conventional AFQMC calculations in Gaussian bases scales as O(N4), where Nis the size of the basis, we show that ground-state energies can be computed through tensor decomposition with reduced memory requirements and subquartic scaling. The algorithm is applied to hydrogen chains and square grids, water clusters, and hexagonal BN. In all cases, we observe significant memory savings and, for larger systems, reduced, subquartic simulation time.

The application of life cycle thinking and the life cycle assessment method is becoming increasingly important in Europe, with the decarbonization targets set by the European Commission. Electric heat pumps (vapor compression) are considered one of the most promising solutions for reducing a building's greenhouse gas emissions. Applying the life cycle assessment method could be challenging when only limited information are available. Reliable tools, for instance, power-law relationships, could be useful for the purpose. Power-law relationships were derived in this article to evaluate the environmental profile of electric heat pumps. 17 745 machines were cataloged according to data from the Italian database “Conto Termico”. 10 empirical relationships were created to correlate the mass of the appliance and the refrigerant content for different heat pump technologies (i.e., air-air, air-water, brine-water, and water-water) and refrigerant gases (i.e., R410a, R134a, and R32). The power-law relationships are proven by considering 16 environmental impact categories, based on Environmental Footprint 3.1 EN 15804 method, using deterministic and stochastic approaches. The validation process shows that correlations related to heat pump manufacturing are reliable for all impact categories, while power-refrigerant gas correlations must be used more carefully as they are affected by a more significant error.

We address the computation of ground-state properties of chemical systems and realistic materials within the auxiliary-field quantum Monte Carlo method. The phase constraint to control the Fermion phase problem requires the random walks in Slater determinant space to be open-ended with branching. This in turn makes it necessary to use back-propagation (BP) to compute averages and correlation functions of operators that do not commute with the Hamiltonian. Several BP schemes are investigated, and their optimization with respect to the phaseless constraint is considered. We propose a modified BP method for the computation of observables in electronic systems, discuss its numerical stability and computational complexity, and assess its performance by computing ground-state properties in several molecular systems, including small organic molecules.

Quantum simulations of the hydroxide anion and hydroxyl radical are reported, employing variational quantum algorithms for near-term quantum devices. The energy of each species is calculated along the dissociation curve, to obtain information about the stability of the molecular species being investigated. It is shown that simulations restricted to valence spaces incorrectly predict the hydroxyl radical to be more stable than the hydroxide anion. Inclusion of dynamical electron correlation from nonvalence orbitals is demonstrated, through the integration of the variational quantum eigensolver and quantum subspace expansion methods in the workflow of N-electron valence perturbation theory, and shown to correctly predict the hydroxide anion to be more stable than the hydroxyl radical, provided that basis sets with diffuse orbitals are also employed. Finally, we calculate the electron affinity of the hydroxyl radical using an aug-cc-pVQZ basis on IBM’s quantum devices.

Neonates receiving fresh frozen plasma (FFP) should do so according to evidence-based guidelines so as to reduce inappropriate use of this life-saving and costly blood product and to minimize associated adverse effects. The consensus-based uses of FFP in neonatology involve neonates with active bleeding and associated coagulopathy. However, because of limited and poor-quality evidence, considerable FFP utilization occurs outside these recommendations. In this review, we describe what we conclude are currently the best practices for the use of FFP in neonates, including interpreting neonatal coagulation tests and strategies for reducing unnecessary FFP transfusions.

Similarly to the development of the plasma coagulation system, which matures during the early weeks and months of life, age-dependent mechanisms and developmental changes influence platelet production and function in neonates. Platelet function testing on cord blood and peripheral blood demonstrates a generalized platelet hyporeactivity, during the first days of life. This reactivity reaches normal adult levels between the fifth and ninth day of life. The persistence of hyporeactivity after the tenth day of life might indeed suggest a platelet disorder.

In 90% of cases, women with rheumatoid arthritis suffer a disease flare within 3 months of delivery of their baby. Drug treatment is, therefore, required; however, such therapies have implications for mothers who decide to nurse their infants. Unfortunately, because of a paucity of data, little is known about the transfer of antirheumatic drugs into breast milk, and even less is known about whether small amounts of these agents ingested during nursing could harm the infant. Our review of the literature indicates that paracetamol, prednisone, antimalarial agents, sulfasalazine and most NSAIDs can safely be used by lactating mothers. Expert opinions differ regarding the use of azathioprine, ciclosporin, and methotrexate during lactation because of varying views on the potential for short-term and long-term adverse effects. Evidence regarding the transfer of leflunomide and biologic drugs into breast milk is insufficient; therefore, until more studies are conducted, the use of these drugs in breastfeeding mothers should be restricted. At present, many patients feel they have to choose between postpartum disease control and lactation. Extended studies of the transfer of antirheumatic drugs into breast milk and the resulting consequences are, therefore, urgently needed.

Coronavirus disease 2019 outbreak has a growing impact on global health; vertical transmission of severe acute respiratory syndrome coronavirus 2 infection is still controversial. In this article, we describe a case of vertical transmission of severe acute respiratory syndrome coronavirus 2 in a newborn with respiratory and gastrointestinal symptoms.

Rheumatic diseases in women of childbearing years may necessitate drug treatment during a pregnancy, to control maternal disease activity and to ensure a successful pregnancy outcome. This survey is based on a consensus workshop of international experts discussing effects of anti-inflammatory, immunosuppressive and biological drugs during pregnancy and lactation. In addition, effects of these drugs on male and female fertility and possible long-term effects on infants exposed to drugs antenatally are discussed where data were available. Recommendations for drug treatment during pregnancy and lactation are given.

Infants born from mothers with antiphospholipid antibody (aPL) -positive autoimmune disease were prospectively evaluated for anticardiolipin and anti-?2 glycoprotein I antibodies (group 1) and for growth and neurological development. The results were compared with those obtained from two age-matched control groups (group 2 and 3). All infants were negative for anticardiolipin at 12 months of life, whereas 14 (63.6%), eight (33.3%), and 10 (55.5%) of infants from group 1, 2, and 3, respectively, were positive for anti-beta 2 glycoprotein I. At follow-up, all infants had normal growth and neurological development. No thrombotic complication was observed. The negativity of anticardiolipin in all infants at 12 months suggests that anticardiolipin detection is the best assay to evaluate the disappearance of maternal aPL and to estimate the potential risk of thrombosis associated with these antibodies. The high rate of anti-beta 2 glycoprotein I positivity in all three groups of infants may indicate that the synthesis of this antibody is stimulated by aspecific factors.

Congenital central hypoventilation syndrome (CCHS) is a rare syndrome characterized by failure of autonomic respiratory control, often presenting with other dysfunctions of the autonomic nervous system. Segregation analysis suggested a complex model of inheritance with a major locus involved. Disruption of the Rnx gene, a member of the Hox11 family of homeobox genes, in embryonic stem cells produced mice showing a phenotype similar to CCHS. Based on this observation, we have carried out mutation screening of the RNX gene in a set of 13 patients affected with CCHS, 2 of whom showing association with Hirschsprung disease. Single-strand conformational polymorphism analysis and direct sequencing of the whole coding portion of the RNX gene and of 1,311 bp of 5' flanking region were performed. No sequence variant was identified, with the exception of a private nucleotide change at position −874 bp from the ATG codon in two siblings affected with isolated CCHS. A functional test, performed by using the luciferase gene reporter system, has not shown any significant difference in the activity of the promoter region carrying this latter nucleotide change with respect to the wild-type allele. We conclude that RNX, and presumably its expression, are not altered in our index cases of CCHS. © 2002 Wiley-Liss, Inc.

This work aims at showing the unexploited potential of waste and renewable heat in Italy through detailed mapping of these sources. The ambition is to highlight the areas with an important heat recovery potential that could be exploited through DH expansion. The recoverable heat sources have been analysed in terms of geographical location, and recovery aspects with a special focus on temperature levels and technological implications for temperature upgrades. The methodology presented in this work addresses not only the theoretical potential of waste heat and renewable heat use in DH, but also several technical aspects to get a result as closer as possible to the realistic potential at national level. Two different approaches have been used to map potential heat: one to quantify existing waste heat recovery from industrial processes, waste to energy plants, wastewater treatment plants and one to estimate the energy coming from potential new plants based on biomass, geothermal energy and solar thermal. Results shows that for a total heat demand for the civil sector of 329 TWh, out of which 114 TWh come out being suitable for a DH connection, the national available waste and renewable heat that could be integrated in DH amounts to 156 TWh. These results show the significant unexpressed potential of waste heat use in Italy and how its mapping is essential to properly estimate the utilization potential. This work has been commissioned by AIRU, Italian DH association.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

We report our initial results with an original modification of Yachia corporoplasty to correct congenital and acquired ventral penile deviations.