Neutron-state entanglement with overlapping paths
Not Available
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
SEARCH · Engineering Papers
Results for “quantum state complexity”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Microstate distinguishability, quantum complexity, and the eigenstate thermalization hypothesis
In this work, we use quantum complexity theory to quantify the difficulty of distinguishing eigenstates obeying the eigenstate thermalization hypothesis (ETH). After identifying simple operators with an algebra of low-energy observables and tracing out the complementary high-energy Hilbert space, the ETH leads to an exponential suppression of trace distance between the coarse grained eigenstates. Conversely, we show that an exponential hardness of distinguishing between states implies ETH-like matrix elements. Finally, the BBBV lower bound on the query complexity of Grover search then translates directly into a complexity-theoretic statement lower bounding the hardness of distinguishing these reduced states
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Capturing the Page curve and entanglement dynamics of black holes in quantum computers
Quantum computers are emerging technologies expected to become important tools for exploring various aspects of fundamental physics in the future. Therefore, we pose the question of whether quantum computers can help us to study the Page curve and the black hole information dynamics, which has been a key focus in fundamental physics. In this regard, we rigorously examine the qubit transport model, a toy qubit model of black hole evaporation on IBM’s superconducting quantum computers, to shed light on this question. Specifically, we implement the quantum simulation of the scrambling dynamics in black holes using an efficient random unitary circuit. Furthermore, we employ the swap-based many-body interference protocol and the randomized measurement protocol to measure the entanglement entropy of Hawking radiation qubits in this model. Finally, by incorporating quantum error mitigation techniques into our challenging implementation of entanglement entropy measurement protocols on the IBM quantum hardware, we accurately determine the Rényi entropy in the qubit transport model, thus showcasing the utility of quantum computers for future investigations of complex quantum systems.
97 MATHEMATICS AND COMPUTING↗
Designing a quantum-accurate machine-learning potential to enable large-scale simulations of deuterium under shock
Large-scale molecular dynamics of deuterium under shock can elucidate kinetic processes vital to the target design in inertial confinement fusion and high-energy-density experiments. However, modeling the complex evolution of this material from an insulating molecular state at ambient pressure to an ionized, atomic fluid under strong shock is beyond the capability of simple pair and even bond order potentials. We thus train a quantum-accurate and broadly transferable machine-learning interatomic potential for deuterium using the Chebyshev Interaction Model for Efficient Simulations framework. We show that due to an improved description of the molecular-to-atomic transition, our model is able to better reproduce the ab initio equation of state, radial distribution functions, and principal Hugoniot than bond order potentials. This represents an important step toward large-scale quantum-accurate and nonequilibrium simulations of complicated systems under dynamic changes including phase transitions.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Accelerating resonant spectroscopy simulations using multishifted biconjugate gradient
Resonant spectroscopies, which involve intermediate states with finite lifetimes, provide important insights into collective excitations in quantum materials that are otherwise inaccessible. However, theoretical understanding in this area is often limited by the numerical challenges of solving Kramers-Heisenberg-type response functions for large-scale systems. To address this, we introduce a multishifted biconjugate gradient algorithm that exploits the shared structure of Krylov subspaces across spectra with varying incident energies, effectively reducing the computational complexity to that of linear spectroscopies. Both mathematical proofs and numerical benchmarks confirm that this algorithm substantially accelerates spectral simulations, achieving constant complexity independent of the number of incident energies, while ensuring accuracy and stability. This development provides a scalable, versatile framework for simulating advanced spectroscopies in quantum materials.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
Limitations of Fault-Tolerant Quantum Linear System Solvers for Quantum Power Flow
Quantum computers hold promise for solving problems intractable for classical computers, especially those with high time or space complexity. Practical quantum advantage can be said to exist for such problems when the end-to-end time for solving such a problem using a classical algorithm exceeds that required by a quantum algorithm. Reducing the power flow (PF) problem into a linear system of equations allows for the formulation of quantum PF (QPF) algorithms, which are based on solving methods for quantum linear systems such as the Harrow-Hassidim-Lloyd (HHL) algorithm. Speedup from using QPF algorithms is often claimed to be exponential when compared to classical PF solved by state-of-the-art algorithms. Here, we investigate the potential for practical quantum advantage in solving QPF compared to classical methods on gate-based quantum computers. Notably, this paper does not present a new QPF solving algorithm but scrutinizes the end-to-end complexity of the QPF approach, providing a nuanced evaluation of the purported quantum speedup in this problem. Our analysis establishes a best-case bound for the HHL-based quantum power flow complexity, conclusively demonstrating that the HHL-based method has higher runtime complexity compared to the classical algorithm for solving the direct current power flow (DCPF) and fast decoupled load flow (FDLF) problem. Notably, our analysis and conclusions can be extended to any quantum linear system solver with rigorous performance guarantees, based on the known complexity lower bounds for this problem. Additionally, we establish that for potential practical quantum advantage (PQA) to exist it is necessary to consider DCPF-type problems with a very narrow range of condition number values and readout requirements.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
The structure of liquid carbon elucidated by in situ X-ray diffraction
Carbon has a central role in biology and organic chemistry, and its solid allotropes provide the basis of much of our modern technology. However, the liquid form of carbon remains nearly uncharted, and the structure of liquid carbon and most of its physical properties are essentially unknown. But liquid carbon is relevant for modelling planetary interiors and the atmospheres of white dwarfs, as an intermediate state for the synthesis of advanced carbon materials, inertial confinement fusion implosions, hypervelocity impact events on carbon materials and our general understanding of structured fluids at extreme conditions. Here we present a precise structure measurement of liquid carbon at pressures of around 1 million atmospheres obtained by in situ X-ray diffraction at an X-ray free-electron laser. Our results show a complex fluid with transient bonding and approximately four nearest neighbours on average, in agreement with quantum molecular dynamics simulations. The obtained data substantiate the understanding of the liquid state of one of the most abundant elements in the universe and can test models of the melting line. The demonstrated experimental abilities open the path to performing similar studies of the structure of liquids composed of light elements at extreme conditions.
74 ATOMIC AND MOLECULAR PHYSICS↗
Procrustean entanglement concentration in quantum-classical networking
The success of a future quantum internet will rest in part on the ability of quantum and classical signals to coexist in the same optical fiber infrastructure, a challenging endeavor given the orders of magnitude differences in flux of single-photon-level quantum fields and bright classical traffic. Here, we theoretically describe and experimentally implement Procrustean entanglement concentration for polarization-entangled states contaminated with classical light, showing significant mitigation of crosstalk noise in dense wavelength-division multiplexing. Our approach leverages a pair of polarization-dependent loss emulators to attenuate highly polarized crosstalk that results from imperfect isolation of conventional signals copropagating on shared fiber links. We demonstrate our technique both on the tabletop and over a deployed quantum local area network, finding a substantial improvement of two-qubit entangled state fidelity from approximately 75% to over 92%. This local filtering technique could be used as a preliminary step to reduce asymmetric errors, potentially improving the overall efficiency when combined with more complex error-mitigation techniques in future quantum repeater networks.
97 MATHEMATICS AND COMPUTING↗
Solving differential‐algebraic equations in power system dynamic analysis with quantum computing
Abstract Power system dynamics are generally modeled by high dimensional non‐linear differential‐algebraic equations (DAEs) given a large number of components forming the network. These DAEs' complexity can grow exponentially due to the increasing penetration of distributed energy resources, whereas their computation time becomes sensitive due to the increasing interconnection of the power grid with other energy systems. This paper demonstrates the use of quantum computing algorithms to solve DAEs for power system dynamic analysis. We leverage a symbolic programming framework to equivalently convert the power system's DAEs into ordinary differential equations (ODEs) using index reduction methods and then encode their data into qubits using amplitude encoding. The system non‐linearity is captured by Hamiltonian simulation with truncated Taylor expansion so that state variables can be updated by a quantum linear equation solver. Our results show that quantum computing can solve the power system's DAEs accurately with a computational complexity polynomial in the logarithm of the system dimension. We also illustrate the use of recent advanced tools in scientific machine learning for implementing complex computing concepts, that is, Taylor expansion, DAEs/ODEs transformation, and quantum computing solver with abstract representation for power engineering applications.
computational complexity↗
Tree tensor network hierarchical equations of motion based on time-dependent variational principle for efficient open quantum dynamics in structured thermal environments
In this work, we introduce an efficient method, TTN-HEOM, for exactly calculating the open quantum dynamics for driven quantum systems interacting with highly structured bosonic baths by combining the tree tensor network (TTN) decomposition scheme with the bexcitonic generalization of the numerically exact hierarchical equations of motion (HEOM). The method yields a series of quantum master equations for all core tensors in the TTN that efficiently and accurately capture the open quantum dynamics for non-Markovian environments to all orders in the system–bath interaction. These master equations are constructed based on the time-dependent Dirac–Frenkel variational principle, which isolates the optimal dynamics for the core tensors given the TTN ansatz. The dynamics converges to the HEOM when increasing the rank of the core tensors, a limit in which the TTN ansatz becomes exact. We introduce TENSO, tensor equations for non-Markovian structured open systems, as a general-purpose Python code to propagate the TTN-HEOM dynamics. We implement three general propagators for the coupled master equations: two fixed-rank methods that require a constant memory footprint during the dynamics and one adaptive-rank method with a variable memory footprint controlled by the target level of computational error. We exemplify the utility of these methods by simulating a two-level system coupled to a structured bath containing one Drude–Lorentz component and eight Brownian oscillators, which is beyond what can presently be computed using the standard HEOM. Our results show that the TTN-HEOM is capable of simulating both dephasing and relaxation dynamics of driven quantum systems interacting with structured baths, even those of chemical complexity, with an affordable computational cost.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Helimagnetic Structure and Heavy-Fermion-Like Behavior in the Vicinity of the Quantum Critical Point in Mn 3 P
Antiferromagnet Mn 3 P with Neel temperature T N =30 K is composed of Mn tetrahedrons and zigzag chains formed by three inequivalent Mn sites. Due to the nearly frustrated lattice with many short Mn-Mn bonds, competition of the exchange interactions is expected. We here investigate the magnetic structure and physical properties including pressure effect in single crystals of this material, and reveal a complex yet well-ordered helimagnetic structure. The itinerant character of this materials is strong, and the ordered state with small magnetic moments is easily suppressed under pressure, exhibiting a quantum critical point at ~1.6 GPa. The remarkable mass renormalization, even in the ordered state, and an incoherent-coherent crossover in the low-temperature region, characterize an unusual electronic state in Mn 3 P, which is most likely effected by the underlying frustration effect.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
Quantum Algorithms for Representation-Theoretic Multiplicities
Kostka, Littlewood-Richardson, Plethysm, and Kronecker coefficients are the multiplicities of irreducible representations in the decomposition of representations of the symmetric group that play an important role in representation theory, geometric complexity, and algebraic combinatorics. We give quantum algorithms for computing these coefficients whenever the ratio of dimensions of the representations is polynomial. We show that there is an efficient classical algorithm for computing the Kostka numbers under this restriction and conjecture the existence of an analogous algorithm for the Littlewood-Richardson coefficients. We argue why such classical algorithm does not straightforwardly work for the Plethysm and Kronecker coefficients and conjecture that our quantum algorithms lead to superpolynomial speedups. The conjecture about Kronecker coefficients was disproved by Panova [Polynomial time classical versus quantum algorithms for representation theoretic multiplicities, arXiv:2502.20253] with a classical algorithm which, if optimal, points to a 𝒪(𝑛 4+2𝑘 ) vs $\tilde{Ω}$(𝑛 4𝑘 2 +1 ) polynomial gap in quantum vs classical computational complexity for an integer parameter 𝑘.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Near-optimal ground state preparation
Preparing the ground state of a given Hamiltonian and estimating its ground energy are important but computationally hard tasks. However, given some additional information, these problems can be solved efficiently on a quantum computer. We assume that an initial state with non-trivial overlap with the ground state can be efficiently prepared, and the spectral gap between the ground energy and the first excited energy is bounded from below. With these assumptions we design an algorithm that prepares the ground state when an upper bound of the ground energy is known, whose runtime has a logarithmic dependence on the inverse error. When such an upper bound is not known, we propose a hybrid quantum-classical algorithm to estimate the ground energy, where the dependence of the number of queries to the initial state on the desired precision is exponentially improved compared to the current state-of-the-art algorithm proposed in [Ge et al. 2019]. These two algorithms can then be combined to prepare a ground state without knowing an upper bound of the ground energy. We also prove that our algorithms reach the complexity lower bounds by applying it to the unstructured search problem and the quantum approximate counting problem.
97 MATHEMATICS AND COMPUTING↗
Dissociative electron recombination and rotational cooling of the deuterated triatomic hydrogen ions H 2 D + and D 2 H +
We have measured the dissociative recombination (DR) of the deuterated triatomic hydrogen ions H 2 D + and D 2 H + as a function of storage time at the Cryogenic Storage Ring (CSR). Both molecular ions were stored for up to 1000 s inside the cryogenic vacuum of the CSR prior to the electron recombination measurements, allowing them to cool to their lowest rotational states. We implement a comprehensive model for all relevant processes to predict the internal state evolution of the ions during storage inside the CSR, employing calculated radiative transition strengths and state-selective rate coefficients for electron collisions. Our DR rate coefficient measurements with deuterated triatomic hydrogen ions in defined quantum states allow for meaningful comparisons with state-of-the-art theoretical calculations, paving the way for a better understanding of the complex DR process for polyatomic molecular ions.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Bimolecular Chemistry in the Ultracold Regime
Advances in atomic, molecular, and optical physics techniques allowed the cooling of simple molecules down to the ultracold regime ([Formula: see text]1 mK) and opened opportunities to study chemical reactions with unprecedented levels of control. This review covers recent developments in studying bimolecular chemistry at ultralow temperatures. We begin with a brief overview of methods for producing, manipulating, and detecting ultracold molecules. We then survey experimental works that exploit the controllability of ultracold molecules to probe and modify their long-range interactions. Further combining the use of physical chemistry techniques such as mass spectrometry and ion imaging significantly improved the detection of ultracold reactions and enabled explorations of their dynamics in the short range. We discuss a series of studies on the reaction KRb + KRb → K 2 + Rb 2 initiated below 1 μK, including the direct observation of a long-lived complex, the demonstration of product rotational state control via conserved nuclear spins, and a test of the statistical model using the complete quantum state distribution of the products.
Chemistry↗
Dynamics and Transport in Strongly-Anisotropic Quantum Magnets (Final Report)
This DOE Award has evolved from a set of projects centered on the thermal transport phenomena in quantum magnets to the broader effort in the theory of dynamical properties of complex magnets, with the focus on their enigmatic ground states, disorder-induced phenomena, and novel spectroscopic and transport effects in them. Most recent emphasis of the research under the umbrella of this Award has been on the rare-earth- and transition-metal-based strongly-anisotropic magnets, the effort that has utilized a significant experience of our group in the studies of excitations, transport, and disorder in these new materials. The studies performed in our group have advanced basic understanding of fundamental physical properties of a diverse group of materials and yielded predictions of new phenomena in them. The research under this Award has targeted the problems that are at the forefront of the modern condensed matter physics and has also addressed the need for the theoretical understanding of experiments. Our work has influenced experiments conducted at the national and international facilities and provided an impact on the DOE basic energy science missions and areas of thrust in new electronic materials, energy transport, neutron- and X-ray scattering science, and in nanoscale science.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
PhILMs: Collaboratory on Mathematics and Physics-Informed Learning Machines for Multiscale and Multiphysics Problems
The landscape of computational science and engineering is continually evolving, with the challenge of high-dimensional regression problems standing as a significant hurdle in numerous scientific endeavors. Addressing this challenge, our research, funded by this award, has led to the development of an innovative computational framework known as Probabilistic Partition of Unity Networks (PPOU-Nets). This initiative represents a collaborative effort to harness the potential of mathematics and physics-informed machine learning in tackling multiscale and multiphysics problems prevalent in high-dimensional spaces. Through this work, we have proposed a novel methodology that seamlessly integrates adaptive dimensionality reduction and a mixture of experts model, thereby facilitating a more efficient and accurate approximation of complex functions. This research effort has not only advanced the state of computational science but also opened new avenues for exploration in quantum computing and beyond. This report outlines the motivation, methodology, key findings, and implications of our work, underscoring our contributions to the broader scientific community and the potential pathways for future research.
97 MATHEMATICS AND COMPUTING↗
Slow magnetic relaxation in a europium(II) complex
Single-ion anisotropy is vital for the observation of Single-Molecule Magnet (SMM) properties (i.e., a slow dynamics of the magnetization) in lanthanide-based systems. In the case of europium, the occurrence of this phenomenon has been inhibited by the spin and orbital quantum numbers that give way to J = 0 in the trivalent state and the half-filled population of the 4f orbitals in the divalent state. Herein, by optimizing the local crystal field of a quasi-linear bis(silylamido) Eu II complex, the [Eu II (N{SiMePh 2 } 2 ) 2 ] SMM is described, providing an example of a europium complex exhibiting slow relaxation of its magnetization. This behavior is dominated by a thermally activated (Orbach-like) mechanism, with an effective energy barrier of approximately 8 K, determined by bulk magnetometry and electron paramagnetic resonance. Ab initio calculations confirm second-order spin-orbit coupling effects lead to non-negligible axial magnetic anisotropy, splitting the ground state multiplet into four Kramers doublets, thereby allowing for the observation of an Orbach-like relaxation at low temperatures.
36 MATERIALS SCIENCE↗