Search

Computational models are an essential tool for the design, characterization, and discovery of novel materials. Computationally hard tasks in materials science stretch the limits of existing high-performance supercomputing centers, consuming much of their resources for simulation, analysis, and data processing. Quantum computing, on the other hand, is an emerging technology with the potential to accelerate many of the computational tasks needed for materials science. In order to do that, the quantum technology must interact with conventional high-performance computing in several ways: approximate results validation, identification of hard problems, and synergies in quantum-centric supercomputing. In this paper, we provide a perspective on how quantum-centric supercomputing can help address critical computational problems in materials science, the challenges to face in order to solve representative use cases, and new suggested directions.

A prominent goal in quantum chemistry is to solve the molecular electronic structure problem for ground state energy with high accuracy. While classical quantum chemistry is a relatively mature field, the accurate and scalable prediction of strongly correlated states found, e.g., in bond breaking and polynuclear transition metal compounds remains an open problem. Within the context of a variational quantum eigensolver, we propose a new family of ansatzes which provides a more physically appropriate description of strongly correlated electrons than a unitary coupled cluster with single and double excitations (qUCCSD), with vastly reduced quantum resource requirements. Specifically, we present a set of local approximations to the unitary cluster Jastrow wavefunction motivated by Hubbard physics. As in the case of qUCCSD, exactly computing the energy scales factorially with system size on classical computers but polynomially on quantum devices. The local unitary cluster Jastrow ansatz removes the need for SWAP gates, can be tailored to arbitrary qubit topologies (e.g., square, hex, and heavy-hex), and is well-suited to take advantage of continuous sets of quantum gates recently realized on superconducting devices with tunable couplers. The proposed family of ansatzes demonstrates that hardware efficiency and physical transparency are not mutually exclusive; indeed, chemical and physical intuition regarding electron correlation can illuminate a useful path towards hardware-friendly quantum circuits.

Modeling chemical reactions with quantum chemical methods is challenging when the electronic structure varies significantly throughout the reaction and when electronic excited states are involved. Multireference methods, such as complete active space self-consistent field (CASSCF), can handle these multiconfigurational situations. However, even if the size of the needed active space is affordable, in many cases, the active space does not change consistently from reactant to product, causing discontinuities in the potential energy surface. The localized active space SCF (LASSCF) is a cheaper alternative to CASSCF for strongly correlated systems with weakly correlated fragments. The method is used for the first time to study a chemical reaction, namely the bond dissociation of a mono-, di-, and triphenylsulfonium cation. LASSCF calculations generate smooth potential energy scans more easily than the corresponding, more computationally expensive CASSCF calculations while predicting similar bond dissociation energies. Our calculations suggest a homolytic bond cleavage for di- and triphenylsulfonium and a heterolytic pathway for monophenylsulfonium. [ABSTRACT FROM AUTHOR]

The simulation of chemical reactions is an anticipated application of quantum computers. Using a Diels– Alder reaction as a test case, in this study we explore the potential applications of quantum algorithms and hardware in investigating chemical reactions. Our specific goal is to calculate the activation barrier of a reaction between ethylene and cyclopentadiene forming a transition state. To achieve this goal, we use quantum algorithms for near-term quantum hardware (entanglement forging and quantum subspace expansion) and classical post-processing (many-body perturbation theory) in concert. We conduct simulations on IBM quantum hardware using up to 8 qubits, and compute accurate activation barrier in the reaction between cyclopentadiene and ethylene by accounting for both static and dynamic electronic correlation. This work illustrates a hybrid quantum-classical computational workflow to study chemical reactions on near-term quantum devices, showcasing the potential for performing quantum chemistry simulations on quantum hardware to predict activation barriers in agreement with those predicted by CASCI. [ABSTRACT FROM AUTHOR]

A star-filled sky has long been a source of awe and inspiration, and its loss adversely affects human, nonhuman, and environmental health. In one generation, this majestic nighttime overstory has been lost due to national and international overuse of light-emitting diodes lighting. This article canvasses ill health effects of excessive light at night. Blue wavelengths of light are damaging to many forms of life, and glare from unshielded light compromises road safety and infiltrates bedrooms, suppressing melatonin production, undermining sleep quality and duration, and exacerbating susceptibility to many kinds of illness. [ABSTRACT FROM AUTHOR]

The aim is to assess the impact of the civil sector's heat demand electrification on the entire energy system, in the Italian case study. The hourly heat demand profiles are estimated at census cells level using the BIN method or monitoring data. Profiles are used as input in the oemof-based NEMeSI model employed to optimize both the capacity expansion of power generation and the operation of the power system in 2030, with hourly temporal resolution and NUTS2 spatial detail, in three heat demand electrification scenarios. The model considers the availability of sources, the import and export profiles, and the limit on renewable sources. The results show that no additional capacity of renewable energy is driven by the increasing electrification in fact the installed capacity remains the same in the three scenarios (97GW of photovoltaic and 33GW of wind turbines). The increase of power demand results in a reduction of overgeneration (48.6TWh to 38.3TWh), an increase in installed batteries (40.6GWh to 115.3GWh) and in CHP (+10%) and CCPP systems (+16%). The results show a slight increase of natural gas in electricity generation (+5.2TWh) respect to a high reduction in its use in civil sector's heat demand (-68.5TWh). [ABSTRACT FROM AUTHOR]

District heating and cooling networks represent a compelling energy system solution due to their capacity to integrate renewable energies and leverage local surpluses of thermal resources. The meticulous design and optimization of network infrastructure are imperative to fully exploiting the potential of these energy systems. The Life Cycle Assessment of district heating and cooling networks for the purpose of environmental sustainability is a crucial and increasingly demanded aspect, particularly in light of the progressively stringent European regulations. The Life Cycle Assessment methodology could offer an evaluation throughout the entire life cycle of such networks. The proposed review scrutinizes the application of the Life Cycle Assessment methodology to evaluating the environmental profile of district heating and cooling systems. The methods, findings, and challenges are examined through a literature review and case study analysis. The results highlight variations in the climate profile influenced by the network generation type and multifunctionality approaches. The analysis revealed a range of emission factors, spanning from 11 gCO2eq/kWhth to 470 gCO2eq/kWhth for district heating and 6 gCO2eq/kWhth to 64 gCO2eq/kWhth for district cooling. The discussion emphasizes integrating district heating and cooling network management considerations and addressing methodological challenges. This study concludes by proposing future research directions for developing a universal LCA-based tool for district heating and cooling network analysis. [ABSTRACT FROM AUTHOR]

We present numerical results for the equation of state of an infinite chain of hydrogen atoms. A variety of modern many-body methods are employed, with exhaustive cross-checks and validation. Approaches for reaching the continuous space limit and the thermodynamic limit are investigated, proposed, and tested. The detailed comparisons provide a benchmark for assessing the current state of the art in many-body computation, and for the development of new methods. The ground-state energy per atom in the linear chain is accurately determined versus bond length, with a confidence bound given on all uncertainties.

The computation of excited electronic states is an important application for quantum computers. In this work, we simulate the excited state spectra of four aromatic heterocycles on IBM superconducting quantum computers, focussing on active spaces of $ \pi \to \pi ^* $ π → π ∗ and $ n \to \pi ^* $ n → π ∗ excitations. We approximate the ground state with the entanglement forging method, a qubit reduction technique that maps a spatial orbital to a single qubit, rather than two qubits. We then determine excited states using the quantum subspace expansion method. We showcase these algorithms on quantum hardware using up to 8 qubits and employing readout and gate error mitigation techniques. Our results demonstrate a successful application of quantum computing in the simulation of active-space electronic wavefunctions of substituted aromatic heterocycles, and outline challenges to be overcome in elucidating the optical properties of organic molecules with hybrid quantum-classical algorithms. [ABSTRACT FROM AUTHOR]