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At least 1,387 records · Page 77

A fitting algorithm for optimizing ion implantation energies and fluences

In this work we describe a method to automatically generate an ion implantation recipe, a set of energies and fluences, to produce a desired defect density profile in a solid using the fewest required energies. We simulate defect density profiles for a range of ion energies, fit them with an appropriate function, and interpolate to yield defect density profiles at arbitrary ion energies. Given Ν energies, we then optimize a set of Ν energy-fluence pairs to match a given target defect density profile. Finally, we find the minimum Ν such that the error between the target defect density profile and the defect density profile generated by the Ν energy-fluence pairs is less than a given threshold. Inspired by quantum sensing applications with nitrogen-vacancy centers in diamond, we apply our technique to calculate optimal ion implantation recipes to create uniform-density 1 μm surface layers of 15 N or vacancies (using 4 He).

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Irradiation route to aqueous synthesis of highly luminescent ZnSe quantum dots and its function as a copper ion fluorescence sensor

Highlights: • Radiation chemical technique can provide a useful route for synthesis of ZnSe QDs. • Chelating nature of ethylene diamine is exploited for capping nanoparticles. • ZnSe QDs can be a suitable sensitive alternative to toxic cadmium-based system. • Cu(II) ion is probed by QDs in the presence of other physiologically relevant ions. - Abstract: Size-controlled synthesis of stable ZnSe QDs with narrow distribution in aqueous environment through conventional soft chemical method still poses a challenge. The proposed radiation assisted strategy demonstrates aqueous synthesis of stable, monodisperse and luminescent ZnSe QDs capped with chelating ethylene diamine under ambient conditions and at room temperature. Radiation chemical method facilitates in slow and in-situ release of selenium ion from sodium selenosulfate. The concentrations of precursors, such as zinc salt, selenium source, ethylene diamine and absorbed radiation (7–90 kGy) dose were optimized for obtaining good quality particles. Selective quenching of luminescence of as-synthesized quantum dots (QDs) by Cu{sup 2+} ions vis-à-vis other physiologically important cations provide evidence for use of ZnSe quantum dots as alternative to toxic Cd-based quantum dots to probe Cu{sup 2+} ions. The linear relation of ratio of loss in emission intensity as a function of concentration of Cu(II) indicates detection limit in nano-molar range.

36 MATERIALS SCIENCE↗

Nonlinear bioheat transfer models and multi-objective numerical optimization of the cryosurgery operations

Numerical computation of the three dimensional problem of the freezing interface propagation during the cryosurgery coupled with the multi-objective optimization methods is used in order to improve the efficiency and safety of the cryosurgery operations performing. Prostate cancer treatment and cutaneous cryosurgery are considered. The heat transfer in soft tissue during the thermal exposure to low temperature is described by the Pennes bioheat model and is coupled with an enthalpy method for blurred phase change computations. The finite volume method combined with the control volume approximation of the heat fluxes is applied for the cryosurgery numerical modeling on the tumor tissue of a quite arbitrary shape. The flux relaxation approach is used for the stability improvement of the explicit finite difference schemes. The method of the additional heating elements mounting is studied as an approach to control the cellular necrosis front propagation. Whereas the undestucted tumor tissue and destucted healthy tissue volumes are considered as objective functions, the locations of additional heating elements in cutaneous cryosurgery and cryotips in prostate cancer cryotreatment are considered as objective variables in multi-objective problem. The quasi-gradient method is proposed for the searching of the Pareto front segments as the multi-objective optimization problem solutions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Clifford Circuit Optimization with Templates and Symbolic Pauli Gates

The Clifford group is a finite subgroup of the unitary group generated by the Hadamard, the CNOT, and the Phase gates. This group plays a prominent role in quantum error correction, randomized benchmarking protocols, and the study of entanglement. Here we consider the problem of finding a short quantum circuit implementing a given Clifford group element. Our methods aim to minimize the entangling gate count assuming all-to-all qubit connectivity. First, we consider circuit optimization based on template matching and design Clifford-specific templates that leverage the ability to factor out Pauli and SWAP gates. Second, we introduce a symbolic peephole optimization method. It works by projecting the full circuit onto a small subset of qubits and optimally recompiling the projected subcircuit via dynamic programming. CNOT gates coupling the chosen subset of qubits with the remaining qubits are expressed using symbolic Pauli gates. Software implementation of these methods finds circuits that are only 0.2% away from optimal for 6 qubits and reduces the two-qubit gate count in circuits with up to 64 qubits by 64.7% on average, compared with the Aaronson-Gottesman canonical form.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

High polarization InAlGaAs/AlGaAs photocathodes grown using MBE

Strained superlattices of GaAs/GaAsP grown using molecular beam epitaxy (MBE) have been used for more than 20 years to generate high polarization electron beams for nuclear physics. GaAs/GaAsP superlattices have several manufacturing challenges, including the thick graded layer required for the virtual GaAsP substrate, the significant difference in optimal growth temperatures for GaAs and GaAsP, and the scarcity of MBE systems using phosphorus. InAlGaAs/AlGaAs strained superlattice photocathode are an alternative structure that eliminates many of hurdles to growing GaAs/GaAsP in MBE systems. Measurements of quantum efficiency and polarization from InAlGaAs/AlGaAs will be presented. These include studies on a variety of growth parameters to optimize performance, including digital alloys, growth temperature variations, and variation in structure.

Stutzman, Marcy L↗

Optimal structure and parameter learning of Ising models

Reconstruction of the structure and parameters of an Ising model from binary samples is a problem of practical importance in a variety of disciplines, ranging from statistical physics and computational biology to image processing and machine learning. The focus of the research community shifted toward developing universal reconstruction algorithms that are both computationally efficient and require the minimal amount of expensive data. Here, we introduce a new method, interaction screening, which accurately estimates model parameters using local optimization problems. The algorithm provably achieves perfect graph structure recovery with an information-theoretically optimal number of samples, notably in the low-temperature regime, which is known to be the hardest for learning. Here, the efficacy of interaction screening is assessed through extensive numerical tests on synthetic Ising models of various topologies with different types of interactions, as well as on real data produced by a D-Wave quantum computer. Finally, this study shows that the interaction screening method is an exact, tractable, and optimal technique that universally solves the inverse Ising problem.

97 MATHEMATICS AND COMPUTING↗

Electronic structure with direct diagonalization on a D-wave quantum annealer

Quantum chemistry is regarded to be one of the first disciplines that will be revolutionized by quantum computing. Although universal quantum computers of practical scale may be years away, various approaches are currently being pursued to solve quantum chemistry problems on near-term gate-based quantum computers and quantum annealers by developing the appropriate algorithm and software base. This work implements the general Quantum Annealer Eigensolver (QAE) algorithm to solve the molecular electronic Hamiltonian eigenvalue-eigenvector problem on a D-Wave 2000Q quantum annealer. The approach is based on the matrix formulation, efficiently uses qubit resources based on a power-of-two encoding scheme and is hardware-dominant relying on only one classically optimized parameter. We demonstrate the use of D-Wave hardware for obtaining ground and excited electronic states across a variety of small molecular systems. The approach can be adapted for use by a vast majority of electronic structure methods currently implemented in conventional quantum-chemical packages. The results of this work will encourage further development of software such as qbsolv which has promising applications in emerging quantum information processing hardware and has expectation to address large and complex optimization problems intractable for classical computers.

97 MATHEMATICS AND COMPUTING↗

Optimization of the design and mode of operation of a QD laser for reducing the heat-to-bitrate ratio

Heat dissipation under the high-speed modulation of quantum dot edge-emitting lasers is considered. It is shown that, for a given laser diode, there is a bias current at which the heat-to-bitrate ratio is minimized. Moreover, there exists a certain optimal optical loss of the laser cavity at which the lowest heat-to-bitrate ratio is provided for any design of edge-emitting lasers that can be fabricated from an epitaxial structure. The heat-to-bitrate ratio and the corresponding bitrate are numerically calculated and analytical expressions are derived. It is demonstrated that the heat-to-bitrate ratio of quantum dot edge-emitting lasers can be less than 0.4 pJ/bit at a bitrate exceeding 10 Gbit/s.

36 MATERIALS SCIENCE↗

Super-resolving quantum radar: Coherent-state sources with homodyne detection suffice to beat the diffraction limit

There has been much recent interest in quantum metrology for applications to sub-Raleigh ranging and remote sensing such as in quantum radar. For quantum radar, atmospheric absorption and diffraction rapidly degrades any actively transmitted quantum states of light, such as N00N states, so that for this high-loss regime the optimal strategy is to transmit coherent states of light, which suffer no worse loss than the linear Beer's law for classical radar attenuation, and which provide sensitivity at the shot-noise limit in the returned power. We show that coherent radar radiation sources, coupled with a quantum homodyne detection scheme, provide both longitudinal and angular super-resolution much below the Rayleigh diffraction limit, with sensitivity at shot-noise in terms of the detected photon power. Our approach provides a template for the development of a complete super-resolving quantum radar system with currently available technology.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A Two-Stage Quantum Reinforcement Learning Method for Multi-Objective Transmission Switching

Multi-objective transmission switching (MO-TS) problems involve the strategic reconfiguration of network topology to simultaneously optimize multiple objectives. As the system scale increases, finding feasible solutions becomes increasingly challenging due to the problem's nonlinearity and high computational complexity. To address these challenges, this paper proposes a two-stage quantum reinforcement learning method that leverages potential quantum advantages for MO-TS. In the first stage, candidate switching lines are identified using a graph-theoretical approach to reduce the problem's dimensionality. The second stage introduces a quantum-classical reinforcement learning framework, where a learnable measurement-based CNN-ResVQC architecture is developed to effectively reduce the input dimension for quantum processing, mitigate vanishing gradients, and enhance trainability while improving the quantum circuit's flexibility in modeling complex decision policies for MO-TS. Numerical studies on IEEE 14-bus, 57-bus, and 118-bus systems demonstrate that the proposed algorithm achieves superior training stability and faster convergence with approximately 1% of the network parameters required by classical algorithms, highlighting its effectiveness, efficiency, and scalability. Furthermore, the practicality is validated through its stable convergence under three common quantum noise channels.

99 GENERAL AND MISCELLANEOUS↗

Nearly Optimal Lattice Simulation by Product Formulas

We consider simulating an n-qubit Hamiltonian with nearest-neighbor interactions evolving for time t on a quantum computer. We show that this simulation has gate complexity (nt)1+o(1) using product formulas, a straightforward approach that has been demonstrated by several experimental groups. While it is reasonable to expect this complexity—in particular, this was claimed without rigorous justification by Jordan, Lee, and Preskill—we are not aware of a straightforward proof. Furthermore, our approach is based on an analysis of the local error structure of product formulas, as introduced by Descombes and Thalhammer and significantly simplified here. We prove error bounds for canonical product formulas, which include well-known constructions such as the Lie-Trotter-Suzuki formulas. We also develop a local error representation for time-dependent Hamiltonian simulation, and we discuss generalizations to periodic boundary conditions, constant-range interactions, and higher dimensions. Combined with a previous lower bound, our result implies that product formulas can simulate lattice Hamiltonians with nearly optimal gate complexity.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Unified architecture for quantum lookup tables

Quantum access to arbitrary classical data encoded in unitary black-box oracles underlies interesting data-intensive quantum algorithms, such as machine learning or electronic structure simulation. The feasibility of these applications depends crucially on gate-efficient implementations of these oracles, which are commonly some reversible versions of the Boolean circuit for a classical lookup table. Here, we present a general parametrized architecture for quantum circuits implementing a lookup table that encompasses all prior work in realizing a continuum of optimal trade-offs between qubits, non-Clifford gates, and error resilience, up to logarithmic factors. Our architecture assumes only local 2D connectivity, yet recovers results, with the appropriate parameters, polylogarithmic error scaling. We also identify regimes, such as simultaneous sublinear scaling, in all parameters. These results enable tailoring implementations of the commonly used lookup table primitive to any given quantum device with constrained resources.

quantum circuits↗

A necessary condition of Pontryagin type for fuzzy control systems

In the present paper, we prove necessary optimality conditions of Pontryagin type for a class of fuzzy optimal control problems. The new results are illustrated by computing the extremals of two fuzzy optimal control systems, which improve recent results of Najariyan and Farahi.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Design and optimization of high temperature optocouplers as galvanic isolation

The commercial InGaN-based (blue and green) and AlGaInP-based (red) multiple quantum well (MQW) lighting emitting diodes (LEDs) were studied in a wide range of temperatures up to 800 K for their light emission and detection (i.e., LEDs operated under reverse bias as photodiodes (PDs)) characteristics. The results indicate the feasibility of integrating a pair of selected LEDs to fabricate high temperature (HT) optocouplers, which can be utilized as galvanic isolation to replace the bulky isolation transforms in the high-density power modules. A detailed study on LEDs and PDs were performed. The external quantum efficiency (EQE) of the LED and PDs were calculated. Higher relative external quantum efficiency (EQE) and lower efficiency droops with temperatures are obtained from the blue and green LEDs for display compared with the blue one for lighting and red LED for display. The blue for lighting and red for display devices show superior responsivity, specific detectivity (D*), and EQE compared with blue and green for display when operated as PDs. The results suggest that red LED devices for display can be used to optimize HT optocouplers due to the highest wavelength overlapping compared with others.

42 ENGINEERING↗

Equation of State Optimization and Uncertainty Quantization: Implementation in the LANL EOS Production Code OpenSesame

We detail the approaches of particle swarm optimization and Bayesian inference through Markov chain Monte Carlo for equation of state development. This work includes formulation of the modeling for the equation of state, numeric optimization of the parametric models via particle swarm optimization, and generation of probability distributions of equations of state from Markov chain Monte Carlo.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A characterization of robust radiation therapy treatment planning methods-from expected value to worst case optimization

Purpose: To characterize a class of optimization formulations used to handle systematic and random errors in radiation therapy, and to study the differences between the methods within this class. Methods: The class of robust methods that can be formulated as minimax stochastic programs is studied. This class generalizes many previously used methods, ranging between optimization of the expected and the worst case objective value. The robust methods are used to plan intensity-modulated proton therapy (IMPT) treatments for a case subject to systematic setup and range errors, random setup errors with and without uncertain probability distribution, and combinations thereof. As reference, plans resulting from a conventional method that uses a margin to account for errors are shown. Results: For all types of errors, target coverage robustness increased with the conservativeness of the method. For systematic errors, best case organ at risk (OAR) doses increased and worst case doses decreased with the conservativeness. Accounting for random errors of fixed probability distribution resulted in heterogeneous dose. The heterogeneities were reduced when uncertainty in the probability distribution was accounted for. Doing so, the OAR doses decreased with the conservativeness. All robust methods studied resulted in more robust target coverage and lower OAR doses than the conventional method. Conclusions: Accounting for uncertainties is essential to ensure plan quality in complex radiation therapy such as IMPT. The utilization of more information than conventional in the optimization can lead to robust target coverage and low OAR doses. Increased target coverage robustness can be achieved by more conservative methods.

60 APPLIED LIFE SCIENCES↗

Measure of quantum correlations that lies approximately between entanglement and discord

When a quantum system is divided into two local subsystems, measurements on the two subsystems can exhibit correlations beyond those possible in a classical joint probability distribution; these are partially explained by entanglement, and more generally by a wider class of measures such as the quantum discord. In this paper, I introduce a simple thought experiment defining a measure of quantum correlations, which I call the accord, and write the result as a minimax optimization over unitary matrices. I find the exact result for pure states as a simple function of the Schmidt coefficients and provide a complete proof, and I likewise provide and prove the result for several classes of mixed states, notably including all states of two qubits and the experimentally relevant case of a pure state mixed with colorless noise. I demonstrate that for two qubit states the accord provides a tight lower bound on the discord; for Bell diagonal states it is also an upper bound on entanglement.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

High Brightness Room Temperature III-Nitride Based Single Photon Source

Single photon sources (SPS) are quantum light sources where photons are emitted one at a time instead of randomly (e.g. lasers) or in a bunch (e.g. thermal) that can significantly impact quantum information science (computing and secure communications) and quantum metrology. Some highly desirable features of SPS are low second order correlation (g 2 ),controllable emission, electrically injected room temperature operation with high photon rate, high extraction efficiency and controllable directionality. Approaches taken thus far using different material systems have only addressed a subset of these features. III-nitride based approach offers a clear pathway to deterministic, room temperature (R.T.), electrically injected practical SPS as one can potentially also leverage the knowledge and technology from the light emitting diode (LED) world. Here we will describe a hybrid approach wherein a TiO2 based photonic crystal (PC) cavity is fabricated around an InGaN quantum dot (QD) embedded nanoscale post deterministically placed inside a photonic crystal cavity. This project takes the initial steps necessary to achieve a practical, compact SPS. We have used finite difference time domain simulations to optimize the cavity design to achieve high quality factor, mode overlap with QD and high extraction. We have fabricated InGaN quantum dots using a top-down approach involving dry etch and photoelectrochemical etch followed by electron beam lithography based nanofabrication of photonic crystal cavities.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗