Probing Oxidation-Driven Amorphized Surfaces in a Ta(110) Film for Superconducting Qubit

Recent advances in superconducting qubit technology have led to significant progress in quantum computing, but the challenge of achieving a long coherence time remains. Despite the excellent lifetime performance that tantalum (Ta) based qubits have demonstrated to date, the majority of superconducting qubit systems, including Ta-based qubits, are generally believed to have uncontrolled surface oxidation as the primary source of the two-level system loss in two-dimensional transmon qubits. Therefore, atomic-scale insight into the surface oxidation process is needed to make progress toward a practical quantum processor. In this study, the surface oxidation mechanism of native Ta films and its potential impact on the lifetime of superconducting qubits were investigated using advanced scanning transmission electron microscopy (STEM) techniques combined with density functional theory calculations. The results suggest an atomistic model of the oxidized Ta(110) surface, showing that oxygen atoms tend to penetrate the Ta surface and accumulate between the two outermost Ta atomic planes; oxygen accumulation at the level exceeding a 1:1 O/Ta ratio drives disordering and, eventually, the formation of an amorphous Ta2O5 phase. In addition, we discuss how the formation of a noninsulating ordered TaO1-δ (δ < 0.1) suboxide layer could further contribute to the losses of superconducting qubits. Subsurface oxidation leads to charge redistribution and electric polarization, potentially causing quasiparticle loss and decreased current-carrying capacity, thus affecting superconducting qubit coherence. The findings enhance the comprehension of the realistic factors that might influence the performance of superconducting qubits, thus providing valuable guidance for the development of future quantum computing hardware.

Quantum AI and hybrid simulators for a Universal Quantum Field Computation Model

Quantum field theory (QFTh) simulators simulate physical systems using quantum circuits that process quantum information (qubits) via single field (SF) and/or quantum double field (QDF) transformation. This review presents models that classify states against pairwise particle states | i j 〉 , given their state transition (ST) probability P | i j 〉 . A quantum AI (QAI) program, weighs and compares the field's distance between entangled states as qubits from their scalar field of radius R ≥ | r i j | . These states distribute across 〈 R 〉 with expected probability 〈 P distribute 〉 and measurement outcome 〈 M ( P distribute ) 〉 = P | i j 〉 . A quantum-classical hybrid model of processors via QAI, classifies and predicts states by decoding qubits into classical bits. For example, a QDF as a quantum field computation model (QFCM) in IBM-QE, performs the doubling of P | i j 〉 for a strong state prediction outcome. QFCMs are compared to achieve a universal QFCM (UQFCM). This model is novel in making strong event predictions by simulating systems on any scale using QAI. Its expected measurement fidelity is 〈 M ( F ) 〉 ≥ 7 / 5 in classifying states to select 7 optimal QFCMs to predict 〈 M 〉 's on QFTh observables. This includes QFCMs' commonality of 〈 M 〉 against QFCMs limitations in predicting system events. Common measurement results of QFCMs include their expected success probability 〈 P success 〉 over STs occurring in the system. Consistent results with high F 's, are averaged over STs as 〈 P distribute 〉 yielding 〈 P success 〉 ≥ 2 / 3 performed by an SF or QDF of certain QFCMs. A combination of QFCMs with this fidelity level predicts error rates (uncertainties) in measurements, by which a P | i j 〉 = 〈 P success 〉 < ∼ 1 is weighed as a QAI output to a QFCM user. The user then decides which QFCMs perform a more efficient system simulation as a reliable solution. A UQFCM is useful in predicting system states by preserving and recovering information for intelligent decision support systems in applied, physical, legal and decision sciences, including industry 4.0 systems.

Comparison of Methods for Quantifying Extracellular Vesicles of Gram-Negative Bacteria

There are a variety of methods employed by laboratories for quantifying extracellular vesicles isolated from bacteria. As a result, the ability to compare results across published studies can lead to questions regarding the suitability of methods and buffers for accurately quantifying these vesicles. Within the literature, there are several common methods for vesicle quantification. These include lipid quantification using the lipophilic dye FM 4-64, protein quantification using microBCA, Qubit, and NanoOrange assays, or direct vesicle enumeration using nanoparticle tracking analysis. In addition, various diluents and lysis buffers are also used to resuspend and treat vesicles. In this study, we directly compared the quantification of a bacterial outer membrane vesicle using several commonly used methods. We also tested the impact of different buffers, buffer age, lysis method, and vesicle diluent on vesicle quantification. The results showed that buffer age had no significant effect on vesicle quantification, but the lysis method impacted the reliability of measurements using Qubit and NanoOrange. The microBCA assay displayed the least variability in protein concentration values and was the most consistent, regardless of the buffer or diluent used. MicroBCA also demonstrated the strongest correlation to the NTA-determined particle number across a range of vesicle concentrations. Overall, these results indicate that with appropriate diluent and buffer choice, microBCA vs. NTA standard curves could be generated and the microBCA assay used to estimate the particle number when NTA instrumentation is not readily available.

SARS-CoV-2 spike and ACE2 entanglement-like binding

We describe the binding between the glycoprotein Spike of SARS-CoV-2 and the human host cell receptor ACE2 as a quantum circuit, comprising the one-qubit Hadamard quantum logic gate performing the quantum superposition of the S₁ subunit of the Spike protein, and the two-qubit quantum logic gate CNOT, which performs maximum entanglement between the Spike-qubit S₁ and the ACE2 receptor protein. Also, we consider two strategies to prevent the binding process between the Spike-qubit S₁ and the ACE2 receptor. The first one is the use of competitive peptidomimetic inhibitors that can selectively bind to the receptor binding domain (RBD) of the Spike glycoprotein with much higher affinity than the cell surface receptor itself. These inhibitors are targeted to the CNOT quantum logic gate and will get maximally entangled with the S₁ qubit in place of the natural ACE2 receptor. The second one is to use covalent inhibitors, which will destroy S₁ by acting as a projective quantum measurement. Finally, the conjecture that S₁ is a quantum bio-robot is formulated.

The QBIT Theory: Consciousness from Entangled Qubits

How does the brain generate consciousness? The present paper is an attempt to answer this question from the perspective of the QBIT theory. In sum, the theory argues that the brain has a prior belief (P) about the stimulus that has caused a sensory representation (R) to be created in the brain. When the conditional entropy of P given R becomes less than zero, the brain becomes more than certain about (i.e. becomes conscious of) the stimulus. Conditional entropy can become negative (and thus the brain can become more than certain) only if the brain uses entangled quantum information in its computations. The QBIT theory suggests that, at the most fundamental level, consciousness is nothing but a special kind of entangled information.

Unitary two-state quantum operators realized by quadrupole fields in the electron microscope

In this work, a novel method for using a set of electromagnetic quadrupole fields is presented to implement arbitrary unitary operators on a two-state quantum system of electrons. In addition to analytical derivations of the required quadrupole and beam settings which allow an easy direct implementation, numerical simulations of realistic scenarios show the feasibility of the proposed setup. This is expected to pave the way not only for new measurement schemes in electron microscopy and related fields but even one day for the implementation of quantum computing in the electron microscope.

Comparison of five assays for DNA extraction from bacterial cells in human faecal samples

Aim

To determine the most effective DNA extraction method for bacteria in faecal samples.

Materials and Results

This study assessed five commercial methods, that is, NucliSens easyMag, QIAamp DNA Stool Mini kit, PureLink Microbiome DNA purification kit, QIAamp PowerFecal DNA kit and RNeasy PowerMicrobiome kit, of which the latter has been optimized for DNA extraction. The DNA quantity and quality were determined using Nanodrop, Qubit and qPCR. The PowerMicrobiome kit recovered the highest DNA concentration, whereby this kit also recovered the highest gene copy number of Gram positives, Gram negatives and total bacteria. Furthermore, the PowerMicrobiome kit in combination with mechanical pre‐treatment (bead beating) and with combined enzymatic and mechanical pre‐treatment (proteinase K+mutanolysin+bead beating) was more effective than without pre‐treatment.

Conclusion

From the five DNA extraction methods that were compared, the PowerMicrobiome kit, preceded by bead beating, which is standard included, was found to be the most effective DNA extraction method for bacteria in faecal samples.

Significance and Impact of the Study

The quantity and quality of DNA extracted from human faecal samples is a first important step to optimize molecular methods. Here we have shown that the PowerMicrobiome kit is an effective DNA extraction method for bacterial cells in faecal samples for downstream qPCR purpose.

Comparative assessment of DNA extraction procedures for Ascaris spp. eggs

A central and critical step in the molecular detection of soil-transmitted helminths from environmental sources is the extraction of DNA from the eggs. In this study, we investigated the yield of DNA extracted from known quantities (500, 100, 50, 20, 10 and 5) of Ascaris suum eggs, as well as directly from wastewater and sludge samples containing Ascaris spp. eggs, using six commercial DNA extraction kits. The amount of DNA extracted was quantified with NanoDrop, Qubit and Ct values from quantitative polymerase chain reaction (qPCR) assay using CFX96 Touch™ real-time PCR equipment. The PowerLyzer Ultraclean Microbial DNA isolation kit and PowerSoil DNA isolation kit gave the highest yield of DNA based on the NanoDrop, Qubit and Ct values. However, the qPCR results indicate that in some of the kits, PCR inhibitors may have been carried over to the PCR reaction. DNA extraction kits that incorporate a bead-beating step as well as other mechanical eggshell disruption steps were superior in extracting DNA from Ascaris spp. eggs. Additionally, for the accurate quantification of extracted DNA, the use of Ct values from qPCR and Qubit readings gives better results compared to the NanoDrop readings. For efficient downstream applications, the use of DNA extraction kits with superior inhibitor removal technology is essential, in addition to a high yield of DNA.

Detection of phenol contamination in RNA samples and its impact on qRT-PCR results

Residual phenol, carried over from RNA purification, can alter RNA concentration measurements and is assumed to inhibit PCR. Here, we demonstrate that Impurities A260 values of spectral content profiling (SCP) UV/Vis measurements correlated with phenol concentration, whereas absorbance ratios of classical UV/Vis systems failed to reliably detect phenol in RNA samples. Phenol contamination led to over- or underestimation of RNA concentration on UV/Vis systems, whereas it had no influence on fluorometry quantification. Wrong RNA concentration results led to altered template input in qRT-PCR and consequently caused quantification cycle (Cq) shifts, although ≤ 0.01% phenol had no direct influence.

Quantum Entanglement in Double Quantum Systems and Jaynes-Cummings Model

In the paper, we proposed a new approach to producing the qubits in electron transport in low-dimensional structures such as double quantum wells or double quantum wires (DQW). The qubit could arise as a result of quantum entanglement of two specific states of electrons in DQW structure. These two specific states are the symmetric and antisymmetric (with respect to inversion symmetry) states arising due to tunneling across the structure, while entanglement could be produced and controlled by means of the source of nonclassical light. We examined the possibility to produce quantum entanglement in the framework of Jaynes-Cummings model and have shown that at least in principle, the entanglement can be achieved due to series of "revivals" and "collapses" in the population inversion due to the interaction of a quantized single-mode EM field with a two-level system.

Gate-Sensing Coherent Charge Oscillations in a Silicon Field-Effect Transistor

Quantum mechanical effects induced by the miniaturization of complementary metal-oxide-semiconductor (CMOS) technology hamper the performance and scalability prospects of field-effect transistors. However, those quantum effects, such as tunneling and coherence, can be harnessed to use existing CMOS technology for quantum information processing. Here, we report the observation of coherent charge oscillations in a double quantum dot formed in a silicon nanowire transistor detected via its dispersive interaction with a radio frequency resonant circuit coupled via the gate. Differential capacitance changes at the interdot charge transitions allow us to monitor the state of the system in the strong-driving regime where we observe the emergence of Landau-Zener-Stückelberg-Majorana interference on the phase response of the resonator. A theoretical analysis of the dispersive signal demonstrates that quantum and tunneling capacitance changes must be included to describe the qubit-resonator interaction. Furthermore, a Fourier analysis of the interference pattern reveals a charge coherence time, T2 ≈ 100 ps. Our results demonstrate charge coherent control and readout in a simple silicon transistor and open up the possibility to implement charge and spin qubits in existing CMOS technology.