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At least 523 records · Page 29

Semiclassical approach to atomic and molecular interactions

A general approach, combining quantum and classical mechanics, is used to determine the electron position and velocity distributions in atoms and atomic ions (positive and negative). The Hartree-Fock electronic wave functions and the classical central field approximation are used for evaluation of the dynamic properties of the localized electrons. The distributions, which are of fundamental importance in applications of the binary encounter approximation to description of atomic and ionic collissions, are obtained in the form of simple analytical expressions. The quantum-classical distributions of this work are compared with several other distributions in Ne, Ar, and Al atoms in the ground state.

Kunc, Joseph A.↗

III-V Infrared Research at the Jet Propulsion Laboratory

Jet Propulsion Laboratory is actively developing the III-V based infrared detector and focal plane arrays (FPAs) for NASA, DoD, and commercial applications. Currently, we are working on multi-band Quantum Well Infrared Photodetectors (QWIPs), Superlattice detectors, and Quantum Dot Infrared Photodetector (QDIPs) technologies suitable for high pixel-pixel uniformity and high pixel operability large area imaging arrays. In this paper we report the first demonstration of the megapixel-simultaneously-readable and pixel-co-registered dual-band QWIP focal plane array (FPA). In addition, we will present the latest advances in QDIPs and Superlattice infrared detectors at the Jet Propulsion Laboratory.

Dualband↗

Constructing Quantum Spin Liquids Using Combinatorial Gauge Symmetry

In this work, we introduce the notion of combinatorial gauge symmetry—a local transformation that includes single spin rotations plus permutations of spins (or swaps of their quantum states)—that preserve the commutation and anticommutation relations among the spins. We show that Hamiltonians with simple two-body interactions contain this symmetry if the coupling matrix is a Hadamard matrix, with the combinatorial gauge symmetry being associated with the automorphism of these matrices with respect to monomial transformations. Armed with this symmetry, we address the physical problem of how to build quantum spin liquids with physically accessible interactions. In addition to its intrinsic physical significance, the problem is also tied to that of how to build topological qubits.

36 MATERIALS SCIENCE↗

Magnon interactions in the quantum paramagnetic phase of CoNb 2 O 6

In this work, we study effects of magnon interactions in the excitation spectrum of CoNb 2 O 6 in the quantum paramagnetic phase in transverse field, where the 1/S spin-wave theory exhibits unphysical divergences at the critical field. We propose a self-consistent Hartree-Fock approach that eliminates such unphysical singularities while preserving the integrity of the singular threshold phenomena of magnon decay and spectrum renormalization that are present in both theory and experiment. With the microscopic parameters adopted from previous studies, this method yields a close quantitative agreement with the available experimental data for CoNb 2 O 6 in the relevant regime. Furthermore, insights into the general structure of the spin-anisotropic model of CoNb 2 O 6 and related zigzag chain materials are also provided and a discussion of the effects of additional longitudinal field on the spectrum is given.

1-dimensional spin chains↗

Tough Errors Are no Match (TEAM): Optimizing the Quantum Compiler for Noise Resilience

This report summarizes research performed under the Tough Errors Are no Match (TEAM) project. The primary focus of TEAM has been to research and develop a compilation toolbox leveraging techniques from quantum characterization and control, probabilistic programming, and approximate computing. Our goal was to develop robust protocols that can be integrated into quantum compilers to optimize and enhance the robustness of noisy computation. Here, we provide a summary of TEAM work focused on characterization and control of quantum systems.

97 MATHEMATICS AND COMPUTING↗

Graph decomposition techniques for solving combinatorial optimization problems with variational quantum algorithms

The quantum approximate optimization algorithm (QAOA) has the potential to approximately solve complex combinatorial optimization problems in polynomial time. However, current noisy quantum devices cannot solve large problems due to hardware constraints. In this work, we develop an algorithm that decomposes the QAOA input problem graph into a smaller problem and solves MaxCut using QAOA on the reduced graph. The algorithm requires a subroutine that can be classical or quantum—in this work, we implement the algorithm twice on each graph. One implementation uses the classical solver Gurobi in the subroutine and the other uses QAOA. We solve these reduced problems with QAOA. On average, the reduced problems require only approximately 1/10 of the number of vertices than the original MaxCut instances. Furthermore, the average approximation ratio of the original MaxCut problems is 0.75, while the approximation ratios of the decomposed graphs are on average of 0.96 for both Gurobi and QAOA. With this decomposition, we are able to measure optimal solutions for ten 100-vertex graphs by running single-layer QAOA circuits on the Quantinuum trapped-ion quantum computer H1-1, sampling each circuit only 500 times. This approach is best suited for sparse, particularly k-regular graphs, as k-regular graphs on n vertices can be decomposed into a graph with at most $\frac{nk}{k+1}$ vertices in polynomial time. Further reductions can be obtained with a potential trade-off in computational time. In conclusion, while this paper applies the decomposition method to the MaxCut problem, it can be applied to more general classes of combinatorial optimization problems.

97 MATHEMATICS AND COMPUTING↗

Quantum control of Hubbard excitons

Quantum control of the many-body wavefunction is a central challenge in quantum materials research, as it could yield a precise control knob to manipulate emergent phenomena. Floquet engineering, the coherent dressing of quantum states with periodic non-resonant optical fields, has become an important strategy for quantum control. Most applications to solid-state systems have targeted weakly interacting or single-ion states, leaving the manipulation of many-body wavefunctions largely unexplored. Here, in this work, we use Floquet engineering to achieve quantum control of a strongly correlated Hubbard exciton in the one-dimensional Mott insulator Sr 2 CuO 3 . A nonresonant midinfrared optical field coherently dresses the exciton wavefunction, driving its rotation between bright and dark states. We use resonant third-harmonic generation to quantify ultrafast π/2 rotations on the Bloch sphere spanned by these exciton states. Our work advances the quest towards programmable control of correlated states and exciton-based quantum sensing.

36 MATERIALS SCIENCE↗

Structural and magnetic characterization of CeTa 7 ⁢O 19 and YbTa 7 ⁢ O 19 with a two-dimensional pseudospin-$\frac{1}{2}$ triangular lattice

Triangular lattice antiferromagnets are prototypes for frustrated magnetism and may potentially realize novel quantum magnetic states such as a quantum spin-liquid ground state. A recent work suggests NdTa 7 ⁢O 19 with rare-earth triangular lattice is a quantum spin-liquid candidate and highlights the large family of rare-earth heptatantalates as a framework for quantum magnetism investigation. Here, in this paper, we report the structural and magnetic characterization of CeTa 7 ⁢ O 19 and YbTa 7 ⁢ O 19 . Both compounds are isostructural to NdTa 7 ⁢O 19 with no detectable structural disorder. For CeTa 7 ⁢O 19 , the crystal field energy levels and parameters are determined by inelastic neutron scattering measurements. Based on the crystal field result, the magnetic susceptibility data could be well fitted and explained, which reveals that CeTa 7 ⁢O 19 is a highly anisotropic Ising triangular-lattice antiferromagnet (𝑔 𝑧 ⁡/𝑔 𝑥⁢𝑦 ∼ 3) with very weak exchange interaction (J ∼ 0.22 K). For YbTa 7⁢ O 19 , millimeter-sized single crystals could be grown. The anisotropic magnetization and electron spin resonance data show that YbTa 7⁢ O 19 has a contrasting in-plane magnetic anisotropy with 𝑔 𝑧 ⁡/𝑔 𝑥⁢𝑦 ∼ 0.67 similar as that of YbMgGaO 4 . The above results indicate that CeTa7⁢ O 19 and YbTa 7 ⁢O 19 with pseudospin-1/2 ground states might either be quantum spin-liquid candidate materials or find applications in adiabatic demagnetization refrigeration due to the weak exchange interaction.

Pan, Feihao↗

Structure and Dynamics of Entanglement in Large Quantum Systems

Final technical report for he DOE QuantISED grant "Structure and Dynamics of Entanglement in Large Quantum Systems", awarded to Profs. Albion Lawrence and Matthew Headrick a Brandeis University. The work on this grant included entanglement in "matrix quantum mechanics", a system wih large numbers of degrees of freedom; the dynamics of a system coupled to a large environment; and the formulation of he "bit threads" picture of entanglement in quantum systems which are equivalent to a theory of quantum gravity.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Unsupervised quantum circuit learning in high energy physics

Unsupervised training of generative models is a machine learning task that has many applications in scientific computing. Here, in this work, we evaluate the efficacy of using quantum circuit-based generative models to generate synthetic data of high energy physics processes. We use nonadversarial, gradient-based training of quantum circuit Born machines to generate joint distributions over two and three variables.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Adaptive variational quantum eigensolvers for highly excited states

Highly excited states of quantum many-body systems are central objects in the study of quantum dynamics and thermalization that challenge classical computational methods due to their volume-law entanglement content. In this work, we explore the potential of variational quantum algorithms to approximate such states. We propose an adaptive variational quantum eigensolver (VQE) for excited states (X) that self-generates a variational ansatz for arbitrary eigenstates of a many-body Hamiltonian H by attempting to minimize the energy variance with respect to H. We benchmark the method by applying it to an Ising spin chain with integrable and nonintegrable regimes, where we calculate various quantities of interest, including the total energy, magnetization density, and entanglement entropy. We also compare the performance of adaptive VQE-X to an adaptive variant of the folded-spectrum method. For both methods, we find a strong dependence of the algorithm's performance on the choice of operator pool used for the adaptive construction of the ansatz. In particular, an operator pool including long-range two-body gates accelerates the convergence of both algorithms in the nonintegrable regime. Here, we also study the scaling of the number of variational parameters with system size, finding that an exponentially large number of parameters may be necessary to approximate individual highly excited states. Nevertheless, we argue that these methods lay a foundation for the use of quantum algorithms to study finite-energy-density properties of many-body systems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Quantum Transfer Learning to Boost Dementia Detection

Dementia is a devastating condition with profound implications for individuals, families, and healthcare systems. Early and accurate detection of dementia is critical for timely intervention and improved patient outcomes. While classical machine learning and deep learning approaches have been explored extensively for dementia prediction, these solutions often struggle with high-dimensional biomedical data and large-scale datasets, quickly reaching computational and performance limitations. To address this challenge, quantum machine learning (QML) has emerged as a promising paradigm, offering faster training and advanced pattern recognition capabilities. This work aims to demonstrate the potential of quantum transfer learning (QTL) to enhance the performance of a weak classical deep learning model applied to a binary classification task for dementia detection. Besides, we show the effect of noise on the QTL-based approach, investigating the reliability and robustness of this method. Using the OASIS 2 dataset, we show how quantum techniques can transform a suboptimal classical model into a more effective solution for biomedical image classification, highlighting their potential impact on advancing healthcare technology.

Bhowmik, Sounak [University of Tennessee, Knoxvill↗

Gate-based quantum computing for protein design

Protein design is a technique to engineer proteins by permuting amino acids in the sequence to obtain novel functionalities. However, exploring all possible combinations of amino acids is generally impossible due to the exponential growth of possibilities with the number of designable sites. The present work introduces circuits implementing a pure quantum approach, Grover’s algorithm, to solve protein design problems. Our algorithms can adjust to implement any custom pair-wise energy tables and protein structure models. Moreover, the algorithm’s oracle is designed to consist of only adder functions. Quantum computer simulators validate the practicality of our circuits, containing up to 234 qubits. However, a smaller circuit is implemented on real quantum devices. Our results show that using iterations, the circuits find the correct results among all N possibilities, providing the expected quadratic speed up of Grover’s algorithm over classical methods (i.e.,).

59 BASIC BIOLOGICAL SCIENCES↗

Environmentally Friendly Production of High-Quality and Multifunctional Carbon Quantum Dots from Coal

Researchers from the University of Wyoming and the University of Utah worked jointly to study the valorization of coal to carbon quantum dots (CQDs), a value-added product with a broad spectrum of applications. The CQDs were produced by an environmentally facile hydrothermal method, and the experimental factors influencing the properties of CQDs were investigated. We subsequently explored the applications of CQDs as co-sensitizers of dye-sensitized solar cells (DSSC) and photocatalysts of water treatment. As an outlook, techno-economic and environmental analysis studied the feasibility of mass production of CQDs.

01 COAL, LIGNITE, AND PEAT↗

Dynamical quantum phase transitions of quantum spin chains with a Loschmidt-rate critical exponent equal to $\frac{1}{2}$

In this work, we describe a new universality class of dynamical quantum phase transitions of the Loschmidt amplitude of quantum spin chains off equilibrium criticality. We demonstrate that in many cases it is possible to change the conventional linear singularity of the Loschmidt rate function into a smooth peak by tuning one parameter of the quench protocol. Exactly at the point when this change-over occurs, the singularity of the Loschmidt rate function persists, with a critical exponent equal to $\frac{1}{2}$. The nonequilibrium renormalization group fixed point controlling this universality class is described. An asymptotically exact renormalization group recursion relation is derived around this fixed point to obtain the critical exponent.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Unification of finite symmetries in the simulation of many-body systems on quantum computers

Symmetry is fundamental in the description and simulation of quantum systems. Leveraging symmetries in classical simulations of many-body quantum systems can result in significant overhead due to the exponentially growing size of some symmetry groups as the number of particles increases. Quantum computers hold the promise of achieving exponential speedup in simulating quantum many-body systems; however, a general method for utilizing symmetries in quantum simulations has not yet been established. In this work, we present a unified framework for incorporating symmetry group transforms on quantum computers to simulate many-body systems. The core of our approach lies in the development of efficient quantum circuits for symmetry-adapted projection onto irreducible representations of a group or pairs of commuting groups. We provide resource estimations for common groups, including the cyclic and permutation groups. Our algorithms demonstrate the capability to prepare coherent superpositions of symmetry-adapted states and to perform quantum evolution across a wide range of models in condensed-matter physics and ab initio electronic structure in quantum chemistry. Specifically, we execute a symmetry-adapted quantum subroutine for small molecules in first-quantization on noisy hardware and demonstrate the emulation of symmetry-adapted quantum phase estimation for preparing coherent superpositions of quantum states in various irreducible representations of a symmetry group. In addition, we present a discussion of open problems regarding treating symmetries in digital quantum simulations of many-body systems, paving the way for future systematic investigations into leveraging symmetries quantumly for practical quantum advantage. The broad applicability and rigorous resource estimation for symmetry transformations make our framework appealing for achieving provable quantum advantage on fault-tolerant quantum computers, especially for symmetry-related properties.

quantum algorithms↗

On the nonlocal predictions of quantum optics

We give a definition of locality in quantum optics based upon Bell's work, and show that locality has been violated in no experiment performed up to now. We argue that the interpretation of the Wigner function as a probability density gives a very attractive local realistic picture of quantum optics provided that this function is nonnegative. We conjecture that this is the case for all states which can be realized in the laboratory. In particular, we believe that the usual representation of 'single photon states' by a Fock state of the Hilbert space is not correct and that a more physical, although less simple mathematically, representation involves density matrices. We study in some detail the experiment showing anticorrelation after a beam splitter and prove that it naturally involves a positive Wigner function. Our (quantum) predictions for this experiment disagree with the ones reported in the literature.

Marshall, Trevor W.↗

Quantum effects on the dynamics and properties of soft materials

The quantum effects of nuclear and electronic motion play an important role in the structure, dynamics, and function of soft materials, yet they are difficult to capture with conventional classical simulations or static electronic–structure methods. In this work several complementary approaches for treating quantum effects in polymeric and soft–matter systems are demonstrated, with a focus being on the hydrogen-bonded networks, ion and charge transport, and photoactive chromophores. The proton transfer, tunneling, and isotope effects are captured within the reduced-dimensionality models by implementing grid-based nuclear quantum dynamics in terms of the discrete variable and Fourier bases. The nuclear quantum dynamics is extended to larger systems by employing the quantum trajectories and quantum–thermal bath schemes combined with on-the-fly electronic structure, enabling the description of high-dimensional polymeric environments at feasible cost. The dynamics in the electronic degrees of freedom, simulating the optical response in large chromophores such as chlorophylls, is performed using the real-time time-dependent density functional theory implemented in the real-space multigrid (RMG) code. These approaches are demonstrated on case studies of the proton and hydroxide transport in hydrated polymer membranes, charge transfer in conjugated polymers, and the optical spectra of chlorophyll chromophores relevant to polymerized chlorophyll materials and chlorophyll–polymer hybrids. The reviewed methods and applications highlight practical routes of including quantum effects in simulations of soft functional materials.

Garashchuk, Sophya [Univ. of South Carolina, Colum↗