Efficient Reduction of Casimir Forces by Self-assembled Bio-molecular Thin Films

Casimir forces, related to London-van der Waals forces, arise if the spectrum of electromagnetic fluctuations is restricted by boundaries. There is great interest both from fundamental science and technical applications to control these forces on the nano scale. Scientifically, the Casimir effect being the only known quantum vacuum effect manifesting between macroscopic objects, allows to investigate the poorly known physics of the vacuum. In this work, we experimentally investigate the influence of self-assembled molecular bio and organic thin films on the Casimir force between a plate and a sphere. We find that molecular thin films, despite being a mere few nanometers thick, reduce the Casimir force by up to 14%. To identify the molecular characteristics leading to this reduction, five different bio-molecular films with varying chemical and physical properties were investigated. Spectroscopic data reveal a broad absorption band whose presence can be attributed to the mixing of electronic states of the underlying gold layer and those of the molecular film due to charge rearrangement in the process of self-assembly. Using Lifshitz theory we calculate that the observed change in the Casimir force is consistent with the appearance of the new absorption band due to the formation of molecular layers. The desired Casimir force reduction can be tuned by stacking several monolayers, using a simple self-assembly technique in a solution. The molecules - each a few nanometers long - can penetrate small cavities and holes, and cover any surface with high efficiency. This process seems compatible with current methods in the production of micro-electromechanical systems (MEMS), which cannot be miniaturized beyond a certain size due to `stiction' caused by the Casimir effect. Our approach could therefore readily enable further miniaturization of these devices.Comment: Preprint versio

Laser ablation of energetic polymer solutions: effect of viscosity and fluence on the splashing behavior

Laser plasma thrusters are a new kind of propulsion system for small satellites, and work with the thrust created by the laser ablation of a target. Liquid polymer solutions are very promising fuels for such systems, provided that no splashing of the target occurs, because ejection of droplets strongly decreases the performances of the system. We have investigated the nanosecond infrared laser ablation of glycidyl azide polymer solutions containing carbon nanoparticles as absorber. Shadowgraphy imaging revealed two cases, namely splashing regime and solid-like behavior. The transition between both regimes depends on the viscosity of the solution and on the laser fluence, and is explained by the recoil force acting on the target. Appropriate conditions to avoid splashing were identified, showing that this liquid polymer solution is a suitable fuel for laser plasma thruster

Microscope objective for imaging atomic strontium with 0.63 micrometer resolution

Imaging and manipulating individual atoms with submicrometer separation can be instrumental for quantum simulation of condensed matter Hamiltonians and quantum computation with neutral atoms. Quantum gas microscope experiments in most cases rely on quite costly solutions. Here we present an open-source design of a microscope objective for atomic strontium consisting solely of off-the-shelf lenses that is diffraction-limited for 461${\,}$nm light. A prototype built with a simple stacking design is measured to have a resolution of 0.63(4)${\,\mu}$m, which is in agreement with the predicted value. This performance, together with the near diffraction-limited performance for 532${\,}$nm light makes this design useful for both quantum gas microscopes and optical tweezer experiments with strontium. Our microscope can easily be adapted to experiments with other atomic species such as erbium, ytterbium, and dysprosium, as well as Rydberg experiments with rubidium

Solving correlation clustering with QAOA and a Rydberg qudit system: a full-stack approach

We study the correlation clustering problem using the quantum approximate optimization algorithm (QAOA) and qudits, which constitute a natural platform for such non-binary problems. Specifically, we consider a neutral atom quantum computer and propose a full stack approach for correlation clustering, including Hamiltonian formulation of the algorithm, analysis of its performance, identification of a suitable level structure for ${}^{87}{\rm Sr}$ and specific gate design. We show the qudit implementation is superior to the qubit encoding as quantified by the gate count. For single layer QAOA, we also prove (conjecture) a lower bound of $0.6367$ ($0.6699$) for the approximation ratio on 3-regular graphs. Our numerical studies evaluate the algorithm's performance by considering complete and Erd\H{o}s-R\'enyi graphs of up to 7 vertices and clusters. We find that in all cases the QAOA surpasses the Swamy bound $0.7666$ for the approximation ratio for QAOA depths $p \geq 2$. Finally, by analysing the effect of errors when solving complete graphs we find that their inclusion severely limits the algorithm's performance.Comment: 22 + 11 page

Solving correlation clustering with QAOA and a Rydberg qudit system: a full-stack approach

We study the correlation clustering problem using the quantum approximate optimization algorithm (QAOA) and qudits, which constitute a natural platform for such non-binary problems. Specifically, we consider a neutral atom quantum computer and propose a full stack approach for correlation clustering, including Hamiltonian formulation of the algorithm, analysis of its performance, identification of a suitable level structure for 87Sr and specific gate design. We show the qudit implementation is superior to the qubit encoding as quantified by the gate count. For single layer QAOA, we also prove (conjecture) a lower bound of 0.6367 (0.6699) for the approximation ratio on 3-regular graphs. Our numerical studies evaluate the algorithm's performance by considering complete and Erdős-Rényi graphs of up to 7 vertices and clusters. We find that in all cases the QAOA surpasses the Swamy bound 0.7666 for the approximation ratio for QAOA depths p≥2. Finally, by analysing the effect of errors when solving complete graphs we find that their inclusion severely limits the algorithm's performance

Solving correlation clustering with QAOA and a Rydberg qudit system: a full-stack approach

We study the correlation clustering problem using the quantum approximate optimization algorithm (QAOA) and qudits, which constitute a natural platform for such non-binary problems. Specifically, we consider a neutral atom quantum computer and propose a full stack approach for correlation clustering, including Hamiltonian formulation of the algorithm, analysis of its performance, identification of a suitable level structure for 87Sr and specific gate design. We show the qudit implementation is superior to the qubit encoding as quantified by the gate count. For single layer QAOA, we also prove (conjecture) a lower bound of 0.6367 (0.6699) for the approximation ratio on 3-regular graphs. Our numerical studies evaluate the algorithm’s performance by considering complete and Erdős-Rényi graphs of up to 7 vertices and clusters. We find that in all cases the QAOA surpasses the Swamy bound 0.7666 for the approximation ratio for QAOA depths p ≥ 2. Finally, by analysing the effect of errors when solving complete graphs we find that their inclusion severely limits the algorithm’s performance

Solving correlation clustering with QAOA and a Rydberg qudit system: a full-stack approach

We study the correlation clustering problem using the quantum approximate optimization algorithm (QAOA) and qudits, which constitute a natural platform for such non-binary problems. Specifically, we consider a neutral atom quantum computer and propose a full stack approach for correlation clustering, including Hamiltonian formulation of the algorithm, analysis of its performance, identification of a suitable level structure for 87Sr and specific gate design. We show the qudit implementation is superior to the qubit encoding as quantified by the gate count. For single layer QAOA, we also prove (conjecture) a lower bound of 0.6367 (0.6699) for the approximation ratio on 3-regular graphs. Our numerical studies evaluate the algorithm’s performance by considering complete and Erdős-Rényi graphs of up to 7 vertices and clusters. We find that in all cases the QAOA surpasses the Swamy bound 0.7666 for the approximation ratio for QAOA depths p ≥ 2. Finally, by analysing the effect of errors when solving complete graphs we find that their inclusion severely limits the algorithm’s performance

Solving correlation clustering with QAOA and a Rydberg qudit system: a full-stack approach

We study the correlation clustering problem using the quantum approximate optimization algorithm (QAOA) and qudits, which constitute a natural platform for such non-binary problems. Specifically, we consider a neutral atom quantum computer and propose a full stack approach for correlation clustering, including Hamiltonian formulation of the algorithm, analysis of its performance, identification of a suitable level structure for 87Sr and specific gate design. We show the qudit implementation is superior to the qubit encoding as quantified by the gate count. For single layer QAOA, we also prove (conjecture) a lower bound of 0.6367 (0.6699) for the approximation ratio on 3-regular graphs. Our numerical studies evaluate the algorithm's performance by considering complete and Erdős-Rényi graphs of up to 7 vertices and clusters. We find that in all cases the QAOA surpasses the Swamy bound 0.7666 for the approximation ratio for QAOA depths p≥2. Finally, by analysing the effect of errors when solving complete graphs we find that their inclusion severely limits the algorithm's performance