Investigating the Feasibility of Integrating Pavement Friction and Texture Depth Data in Modeling for INDOT PMS

Under INDOT’s current friction testing program, the friction is measured annually on interstates but only once every three years on non-interstate roadways. The state’s Pavement Management System, however, would require current data if friction were to be included in the PMS. During routine pavement condition monitoring for the PMS, texture data is collected annually. This study explored the feasibility of using this pavement texture data to estimate the friction during those years when friction is not measured directly. After multi0ple approaches and a wide variety of ways of examining the currently available data and texture measuring technologies, it was determined that it is not currently feasible to use the texture data as a surrogate for friction testing. This is likely because the lasers used at this time are not capable of capturing the small-scale pavement microtexture. This situation may change, however, with advances in laser or photo interpretation technologies and improved access to materials data throughout the INDOT pavement network

Sub-system self-consistency in coupled cluster theory

In this Communication, we provide numerical evidence indicating that the standard single-reference coupled-cluster (CC) energies can be calculated alternatively to its copybook definition. We demonstrate that the CC energies can be reconstructed by diagonalizing the effective Hamiltonians describing correlated sub-systems of the many-body system. In the extreme case, we provide numerical evidence that the CC energy can be reproduced through the diagonalization of the effective Hamiltonian describing sub-system composed of a single electron. These properties of CC formalism can be exploited to design protocols to define effective interactions in sub-systems used as a probe to calculate the energy of the entire system and introduce a new type of self-consistency for approximate CC approaches.Comment: arXiv admin note: text overlap with arXiv:2111.0321

Mapping renormalized coupled cluster methods to quantum computers through a compact unitary representation of non-unitary operators

Non-unitary theories are commonly seen in the classical simulations of quantum systems. Among these theories, the method of moments of coupled-cluster equations (MMCCs) and the ensuing classes of the renormalized coupled-cluster (CC) approaches have evolved into one of the most accurate approaches to describe correlation effects in various quantum systems. The MMCC formalism provides an effective way for correcting energies of approximate CC formulations (parent theories) using moments, or CC equations, that are not used to determine approximate cluster amplitudes. In this paper, we propose a quantum algorithm for computing MMCC ground-state energies that provide two main advantages over classical computing or other quantum algorithms: (i) the possibility of forming superpositions of CC moments of arbitrary ranks in the entire Hilbert space and using an arbitrary form of the parent cluster operator for MMCC expansion; and (ii) significant reduction in the number of measurements in quantum simulation through a compact unitary representation for a generally non-unitary operator. We illustrate the robustness of our approach over a broad class of test cases, including ~40 molecular systems with varying basis sets encoded using 4~40 qubits, and exhibit the detailed MMCC analysis for the 8-qubit half-filled, four-site, single impurity Anderson model and 12-qubit hydrogen fluoride molecular system from the corresponding noise-free and noisy MMCC quantum computations. We also outline the extension of MMCC formalism to the case of unitary CC wave function ansatz

Integrating Subsystem Embedding Subalgebras and Coupled Cluster Green's Function: A Theoretical Foundation for Quantum Embedding in Excitation Manifold

In this study, we introduce a novel approach to coupled-cluster Green's function (CCGF) embedding by seamlessly integrating conventional CCGF theory with the state-of-the-art sub-system embedding sub-algebras coupled cluster (SES-CC) formalism. This integration focuses primarily on delineating the characteristics of the sub-system and the corresponding segments of the Green's function, defined explicitly by active orbitals. Crucially, our work involves the adaptation of the SES-CC paradigm, addressing the left eigenvalue problem through a distinct form of Hamiltonian similarity transformation. This advancement not only facilitates a comprehensive representation of the interaction between the embedded sub-system and its surrounding environment but also paves the way for the quantum mechanical description of multiple embedded domains, particularly by employing the emergent quantum flow algorithms. Our theoretical underpinnings further set the stage for a generalization to multiple embedded sub-systems. This expansion holds significant promise for the exploration and application of non-equilibrium quantum systems, enhancing the understanding of system-environment interactions. In doing so, the research underscores the potential of SES-CC embedding within the realm of quantum computations and multi-scale simulations, promising a good balance between accuracy and computational efficiency

Quantum flow algorithms for simulating many-body systems on quantum computers

We conducted quantum simulations of strongly correlated systems using the quantum flow (QFlow) approach, which enables sampling large sub-spaces of the Hilbert space through coupled eigenvalue problems in reduced dimensionality active spaces. Our QFlow algorithms significantly reduce circuit complexity and pave the way for scalable and constant-circuit-depth quantum computing. Our simulations show that QFlow can optimize the collective number of wave function parameters without increasing the required qubits using active spaces having an order of magnitude fewer number of parameters