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Diabatic error and propagation of Majorana zero modes in interacting quantum dots systems

Motivated by recent experimental progress in realizing Majorana zero modes (MZMs) using quantum dot systems, we investigate the diabatic errors associated with the movement of those MZMs. The movement is achieved by tuning time-dependent gate potentials applied to individual quantum dots, effectively creating a moving potential wall. To probe the optimized movement of MZMs, we calculate the experimentally accessible time-dependent fidelity and local density-of-states using many-body time-dependent numerical methods. Furthermore, our analysis reveals that an optimal potential wall height is crucial to preserve the well-localized nature of the MZM during its movement. Moreover, we analyze diabatic errors in realistic quantum-dot systems, incorporating the effects of repulsive Coulomb interactions and disorder in both hopping and pairing terms. Additionally, we provide a comparative study of diabatic errors arising from the simultaneous versus sequential tuning of multiple gates during the MZMs movement. Finally, we estimate the timescale required for MZM transfer in a six-quantum-dot system, demonstrating that MZM movement is feasible and can be completed well within the qubit's operational lifetime in practical quantum-dot setups.

Density of states↗

Performance optimization of solar cells based on colloidal lead sulfide nanocrystals

Colloidal semiconducting quantum dot nanocrystals (NCs) have attracted extensive interest as active building-block for low-cost solution-processed photovoltaic due to their size tunable absorption from the visible to near IR. Among various nanocrystal composition, lead sulfide (PbS), having a bulk bandgap of 0.41 eV, are particularly attractive for photovoltaic applications due to their excellent photosensitivity in the near IR. Starting from colloidal synthesis, in this project functional solar cells are fabricated and characterized based on the nearly monodispersed colloidal PbS nanocrystals that we synthesized. These NC-solar cells are fabricated under a “depleted heterojunction” device architecture containing a planar “tipe II” heretojunction formed by a layer of electron-transporting TiO{sub 2} and a layer of PbS NCs. Relevant structural, optical, and electrical characterizations are performed on NCs and their devices. To understand the operational mechanism of these NC-based solar cells, various material and device aspects are investigated in this work aiming for optimized photovoltaic performance. These aspects include the effect of: (1) NC dimensions (and thus their band gaps); (2) passivation of surface traps through post-synthesis treatments; (3) NC surface ligand-exchange; and (4) interfacial modifications at the heterojunction. The most optimized photovoltaic performance is found after combining the surface trap passivation strategy by halides, ligand-exchange by 3-mercaptopropionic acids, and interfacial TiCl4 treatment, leading to a peak open-circuit voltage of 0.53 V, a short-circuit current density of 14.03 mAcm{sup −2}, and a power conversion efficiency of 3.25%.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Al{sub x}Ga{sub 1-x}N-based back-illuminated solar-blind photodetectors with external quantum efficiency of 89%

We report on high performance Al{sub x}Ga{sub 1−x}N-based solar-blind ultraviolet photodetector (PD) array grown on sapphire substrate. First, high quality, crack-free AlN template layer is grown via metalorganic chemical vapor deposition. Then, we systematically optimized the device design and material doping through the growth and processing of multiple devices. After optimization, uniform and solar-blind operation is observed throughout the array; at the peak detection wavelength of 275 nm, 729 μm{sup 2} area PD showed unbiased peak external quantum efficiency and responsivity of ∼80% and ∼176 mA/W, respectively, increasing to 89% under 5 V of reverse bias. Taking the reflection loses into consideration, the internal quantum efficiency of these optimized PD can be estimated to be as high as ∼98%. The visible rejection ratio measured to be more than six orders of magnitude. Electrical measurements yielded a low-dark current density: <2 × 10{sup −9} A/cm{sup 2}, at 10 V of reverse bias.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Quantum Circuits for the Preparation of Spin Eigenfunctions on Quantum Computers

The application of quantum algorithms to the study of many-particle quantum systems requires the ability to prepare wave functions that are relevant in the behavior of the system under study. Hamiltonian symmetries are important instruments used to classify relevant many-particle wave functions and to improve the efficiency of numerical simulations. In this work, quantum circuits for the exact and approximate preparation of total spin eigenfunctions on quantum computers are presented. Two different strategies are discussed and compared: exact recursive construction of total spin eigenfunctions based on the addition theorem of angular momentum, and heuristic approximation of total spin eigenfunctions based on the variational optimization of a suitable cost function. The construction of these quantum circuits is illustrated in detail, and the preparation of total spin eigenfunctions is demonstrated on IBM quantum devices, focusing on three- and five-spin systems on graphs with triangle connectivity.

97 MATHEMATICS AND COMPUTING↗

Bi-photon generation with optimized wavefront by means of adaptive optics

The generation of entangled photon pairs using an optimal pump wavefront was realized in order to achieve a desirable free-space propagation. This optimization exploits a closed loop whis is based on a deformable mirror, a nonlinear crystal for spontaneous parametric down-conversion, the free-space propagation line and the single-photon coincidence electronics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Selective and Scalable Control of Spin Quantum Memories in a Photonic Circuit

A central goal in many quantum information processing applications is a network of quantum memories that can be entangled with each other while being individually controlled and measured with high fidelity. This goal has motivated the development of programmable photonic integrated circuits (PICs) with integrated spin quantum memories using diamond color center spin-photon interfaces. However, this approach introduces a challenge into the microwave control of individual spins within closely packed registers. Here, we present a quantum memory-integrated photonics platform capable of (i) the integration of multiple diamond color center spins into a cryogenically compatible, high-speed programmable PIC platform, (ii) selective manipulation of individual spin qubits addressed via tunable magnetic field gradients, and (iii) simultaneous control of qubits using numerically optimized microwave pulse shaping. The combination of localized optical control, enabled by the PIC platform, together with selective spin manipulation opens the path to scalable quantum networks on intrachip and interchip platforms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Computational Advances in Ionic Liquid Applications for Green Chemistry: A Critical Review of Lignin Processing and Machine Learning Approaches

The valorization and dissolution of lignin using ionic liquids (ILs) is critical for developing sustainable biorefineries and a circular bioeconomy. This review aims to critically assess the current state of computational and machine learning methods for understanding and optimizing IL-based lignin dissolution and valorization processes reported since 2022. The paper examines various computational approaches, from quantum chemistry to machine learning, highlighting their strengths, limitations, and recent advances in predicting and optimizing lignin-IL interactions. Key themes include the challenges in accurately modeling lignin’s complex structure, the development of efficient screening methodologies for ionic liquids to enhance lignin dissolution and valorization processes, and the integration of machine learning with quantum calculations. These computational advances will drive progress in IL-based lignin valorization by providing deeper molecular-level insights and facilitating the rapid screening of novel IL-lignin systems.

09 BIOMASS FUELS↗

In-plane selective area InSb–Al nanowire quantum networks

Abstract Strong spin–orbit semiconductor nanowires coupled to a superconductor are predicted to host Majorana zero modes. Exchange (braiding) operations of Majorana modes form the logical gates of a topological quantum computer and require a network of nanowires. Here, we utilize an in-plane selective area growth technique for InSb–Al semiconductor–superconductor nanowire networks. Transport channels, free from extended defects, in InSb nanowire networks are realized on insulating, but heavily mismatched InP (111)B substrates by full relaxation of the lattice mismatch at the nanowire/substrate interface and nucleation of a complete network from a single nucleation site by optimizing the surface diffusion length of the adatoms. Essential quantum transport phenomena for topological quantum computing are demonstrated in these structures including phase-coherence lengths exceeding several micrometers with Aharonov–Bohm oscillations up to five harmonics and a hard superconducting gap accompanied by 2 e -periodic Coulomb oscillations with an Al-based Cooper pair island integrated in the nanowire network.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Quantum computing for finance

Quantum computers are expected to surpass the computational capabilities of classical computers and have a transformative impact on numerous industry sectors. Here, we present a comprehensive summary of the state of the art of quantum computing for financial applications, with particular emphasis on stochastic modelling, optimization and machine learning. This Review is aimed at physicists, so it outlines the classical techniques used by the financial industry and discusses the potential advantages and limitations of quantum techniques. Finally, we look at the challenges that physicists could help tackle. Quantum computers are expected to surpass classical computers and transform industries. This Review focuses on quantum computing for financial applications and provides a summary for physicists on potential advantages and limitations of quantum techniques, as well as challenges that physicists could help tackle.

97 MATHEMATICS AND COMPUTING↗

Detailed Structural and Chemical Analysis of Amorphous Compounds in Superconducting Qubit Systems

With massive improvements in device coherence times and gate fidelity over the past two decades, superconducting quantum devices have emerged as a leading technology platform for next generation quantum computing. While many of these improvements have been driven through optimized device designs and geometries, the presence of defects, impurities, interfaces, and surfaces in the constituent materials continue to limit performance and present a critical barrier in achieving scalable quantum systems with long coherence times. As part of the Superconducting Quantum Materials and Systems (SQMS) center, we have applied state-of-the-art materials characterization techniques, such as scanning/transmission electron microscopy, secondary ion mass spectrometry, and atom probe tomography, to identify structural defects and chemical inhomogeneities in superconducting qubits. In this review, we discuss the findings of these efforts as they relate to the inherent surfaces, interfaces, impurities, and defects in superconducting qubits. Through this comprehensive investigation, we provide insight into possible sources of dissipation in these systems. Further, we supplement these findings with potential strategies for mitigating these undesired features in an effort to systematically and intelligently improve the coherence times of superconducting qubits.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Physics successfully implements Lagrange multiplier optimization

Optimization is a major part of human effort. While being mathematical, optimization is also built into physics. For example, physics has the Principle of Least Action; the Principle of Minimum Power Dissipation, also called Minimum Entropy Generation; and the Variational Principle. Physics also has Physical Annealing, which, of course, preceded computational Simulated Annealing. Physics has the Adiabatic Principle, which, in its quantum form, is called Quantum Annealing. Thus, physical machines can solve the mathematical problem of optimization, including constraints. Binary constraints can be built into the physical optimization. In that case, the machines are digital in the same sense that a flip–flop is digital. A wide variety of machines have had recent success at optimizing the Ising magnetic energy. We demonstrate in this paper that almost all those machines perform optimization according to the Principle of Minimum Power Dissipation as put forth by Onsager. Further, we show that this optimization is in fact equivalent to Lagrange multiplier optimization for constrained problems. We find that the physical gain coefficients that drive those systems actually play the role of the corresponding Lagrange multipliers.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A modified cosmic brane proposal for holographic Renyi entropy

We propose a new formula for computing holographic Renyi entropies in the presence of multiple extremal surfaces. Our proposal is based on computing the wave function in the basis of fixed-area states and assuming a diagonal approximation for the Renyi entropy. For Renyi index n ≥ 1, our proposal agrees with the existing cosmic brane proposal for holographic Renyi entropy. For n < 1, however, our proposal predicts a new phase with leading order (in Newton’s constant G) corrections to the cosmic brane proposal, even far from entanglement phase transitions and when bulk quantum corrections are unimportant. Recast in terms of optimization over fixed-area states, the difference between the two proposals can be understood to come from the order of optimization: for n < 1, the cosmic brane proposal is a minimax prescription whereas our proposal is a maximin prescription. We demonstrate the presence of such leading order corrections using illustrative examples. In particular, our proposal reproduces existing results in the literature for the PSSY model and high-energy eigenstates, providing a universal explanation for previously found leading order corrections to the n < 1 Renyi entropies.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Electronic and Magnetic Properties of Mn-doped and (Mn,C)-codoped w-AlN with the Presence of N Vacancy

In this paper, we discover the structural, electronic, and magnetic properties of Mn-doped (6.25 and 12.5%) and Mn-C-codoped wurtzite AlN with the presence of nitrogen vacancy. These properties have been investigated using density functional theory implemented in Quantum ESPRESSO package. AlN doped and codoped were optimized by using Broyden-Fletcher-Goldfarb-Shanno (BFGS) approximation. The electronic and magnetic properties are determined by the total and partial density of states. The presence of impurities and nitrogen vacancy induces magnetic properties, indicating that these materials are good candidates for electromagnetic and spintronics applications. Our results are in good agreement with experimental and other theoretical studies. We can conclude from this study that this material can be used as diluted magnetic semiconductors.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Engineering stable Pt nanoparticles and oxygen vacancies on defective TiO 2 via introducing strong electronic metal-support interaction for efficient CO 2 photoreduction

This work for the first time reports the promoting effect of strong electronic metal-support interaction (EMSI) in Pt/TiO 2 -V O (V O : oxygen vacancy) for gas-phase CO 2 photoreduction. A novel in-situ surface hydrogenation was developed to prepare hydrogenated Pt/TiO 2 -V O in a continuous, high throughput diffusion flame aerosol reactor. The combined results of various characterization techniques confirmed the presence of EMSI between Pt and defective TiO 2 -V O resulted in the enhanced electronic density of Pt nanoparticles. Both the modulated electronic structure of Pt and surface oxygen vacancies simultaneously promoted the activation of surface adsorbed carbon intermediates and facilitated the separation of photogenerated charges, eventually boosting the photocatalytic activity of Pt/TiO 2 -V O . The optimized Pt/TiO 2 -V O demonstrated a high quantum yield of 1.49% with high CH 4 selectivity (81%), which rendered 5.8- and 1.2-fold enhancements over its counterparts of TiO 2 -V O and Pt/TiO 2 . More importantly, the EMSI also played a critical role in preserving the surface metallic Pt 0 and oxygen vacancies, and in sustaining high activity of the Pt/TiO 2 -V O , whereas rapid catalytic deactivation are observed for both TiO 2 -V O and Pt/TiO 2 .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Excited-State Diffusion Monte Carlo Calculations: A Simple and Efficient Two-Determinant Ansatz

We perform excited-state variational Monte Carlo and diffusion Monte Carlo calculations using a simple and efficient wave function ansatz. This ansatz follows the recent variation-after-response formalism, accurately approximating a configuration interaction singles wave function as a sum of only two nonorthogonal Slater determinants and further including important orbital relaxation. The ansatz is used to perform diffusion Monte Carlo calculations with large augmented basis sets, comparing to benchmarks from near-exact quantum chemical methods. Here, the significance of orbital optimization in excited-state diffusion Monte Carlo is demonstrated, and the excited-state optimization procedure is discussed in detail. Diffuse excited states in water and formaldehyde are studied, in addition to the formaldimine and benzonitrile molecules.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Heterogeneous data-processing optimization with CLARA’s adaptive workflow orchestrator

The hardware landscape used in HEP and NP is changing from homogeneous multi-core systems towards heterogeneous systems with many different computing units, each with their own characteristics. To achieve maximum performance with data processing, the main challenge is to place the right computing on the right hardware. In this paper, we discuss CLAS12 charge particle tracking workflow orchestration that allows us to utilize both CPU and GPU to improve the performance. The tracking application algorithm was decomposed into micro-services that are deployed on CPU and GPU processing units, where the best features of both are intelligently combined to achieve maximum performance. In this heterogeneous environment, CLARA aims to match the requirements of each micro-service to the strength of a CPU or a GPU architecture. A predefined execution of a micro-service on a CPU or a GPU may not be the most optimal solution due to the streaming data-quantum size and the data-quantum transfer latency between CPU and GPU. So, the CLARA workflow orchestrator is designed to dynamically assign micro-service execution to a CPU or a GPU, based on the online benchmark results analyzed for a period of real-time data-processing.

Gyurjyan, Vardan↗

High-efficiency AlGaInP solar cells grown by molecular beam epitaxy

AlGaInP is an ideal material for ultra-high efficiency, lattice-matched multi-junction solar cells grown by molecular beam epitaxy (MBE) because it can be grown lattice-matched to GaAs with a wide 1.9–2.2 eV bandgap. Despite this potential, AlGaInP grown by molecular beam epitaxy (MBE) has yet to be fully explored, with the initial 2.0 eV devices suffering from poor performance due to low minority carrier diffusion lengths in both the emitter and base regions of the solar cell. In this work, we show that implementing an AlGaInP graded layer to introduce a drift field near the front surface of the device enabled greatly improved internal quantum efficiency (IQE) across all wavelengths. In addition, optimizing growth conditions and post-growth annealing improved the long-wavelength IQE and the open-circuit voltage of the cells, corresponding to a 3× increase in diffusion length in the base. Taken together, this work demonstrates greatly improved IQE, attaining peak values of 95%, combined with an uncoated AM1.5G efficiency of 10.9%, double that of previously reported MBE-grown devices.

Faucher, J.↗