Full stack development toward a trapped ion logical qubit

Quantum error correction is a key step toward the construction of a large-scale quantum computer, by preventing small infidelities in quantum gates from accumulating over the course of an algorithm. Detecting and correcting errors is achieved by using multiple physical qubits to form a smaller number of robust logical qubits. The physical implementation of a logical qubit requires multiple qubits, on which high fidelity gates can be performed. The project aims to realize a logical qubit based on ions confined on a microfabricated surface trap. Each physical qubit will be a microwave dressed state qubit based on 171Yb+ ions. Gates are intended to be realized through RF and microwave radiation in combination with magnetic field gradients. The project vertically integrates software down to hardware compilation layers in order to deliver, in the near future, a fully functional small device demonstrator. This thesis presents novel results on multiple layers of a full stack quantum computer model. On the hardware level a robust quantum gate is studied and ion displacement over the X-junction geometry is demonstrated. The experimental organization is optimized through automation and compressed waveform data transmission. A new quantum assembly language purely dedicated to trapped ion quantum computers is introduced. The demonstrator is aimed at testing implementation of quantum error correction codes while preparing for larger scale iterations.Open Acces

Resilient entangling gates for trapped ions

Constructing a large-scale ion trap quantum processor will require entangling gate operations that are robust in the presence of noise and experimental imperfection. We experimentally demonstrate how a new type of Mølmer-Sørensen gate protects against infidelity caused by heating of the motional mode used during the gate. Furthermore, we show how the same technique simultaneously provides significant protection against slow fluctuations and mis-sets in the secular frequency. Since this parameter sensitivity is worsened in cases where the ions are not ground-state cooled, our method provides a path towards relaxing ion cooling requirements in practical realizations of quantum computing and simulation

From pain to tumor immunity: influence of peripheral sensory neurons in cancer

The nervous and immune systems are the primary sensory interfaces of the body, allowing it to recognize, process, and respond to various stimuli from both the external and internal environment. These systems work in concert through various mechanisms of neuro-immune crosstalk to detect threats, provide defense against pathogens, and maintain or restore homeostasis, but can also contribute to the development of diseases. Among peripheral sensory neurons (PSNs), nociceptive PSNs are of particular interest. They possess a remarkable capability to detect noxious stimuli in the periphery and transmit this information to the brain, resulting in the perception of pain and the activation of adaptive responses. Pain is an early symptom of cancer, often leading to its diagnosis, but it is also a major source of distress for patients as the disease progresses. In this review, we aim to provide an overview of the mechanisms within tumors that are likely to induce cancer pain, exploring a range of factors from etiological elements to cellular and molecular mediators. In addition to transmitting sensory information to the central nervous system, PSNs are also capable, when activated, to produce and release neuropeptides (e.g., CGRP and SP) from their peripheral terminals. These neuropeptides have been shown to modulate immunity in cases of inflammation, infection, and cancer. PSNs, often found within solid tumors, are likely to play a significant role in the tumor microenvironment, potentially influencing both tumor growth and anti-tumor immune responses. In this review, we discuss the current state of knowledge about the degree of sensory innervation in tumors. We also seek to understand whether and how PSNs may influence the tumor growth and associated anti-tumor immunity in different mouse models of cancer. Finally, we discuss the extent to which the tumor is able to influence the development and functions of the PSNs that innervate it

Molecular psychiatry of zebrafish

Due to their well-characterized neural development and high genetic homology to mammals, zebrafish (Danio rerio) have emerged as a powerful model organism in the field of biological psychiatry. Here, we discuss the molecular psychiatry of zebrafish, and its implications for translational neuroscience research and modeling central nervous system (CNS) disorders. In particular, we outline recent genetic and technological developments allowing for in vivo examinations, high-throughput screening and whole-brain analyses in larval and adult zebrafish. We also summarize the application of these molecular techniques to the understanding of neuropsychiatric disease, outlining the potential of zebrafish for modeling complex brain disorders, including attention-deficit/hyperactivity disorder (ADHD), aggression, post-traumatic stress and substance abuse. Critically evaluating the advantages and limitations of larval and adult fish tests, we suggest that zebrafish models become a rapidly emerging new field in modern molecular psychiatry research

Modeling Neurodegeneration in Zebrafish

The zebrafish, Danio rerio, has been established as an excellent vertebrate model for the study of developmental biology and gene function. It also has proven to be a valuable model to study human diseases. Here, we reviewed recent publications using zebrafish to study the pathology of human neurodegenerative diseases including Parkinson’s, Huntington’s, and Alzheimer’s. These studies indicate that zebrafish genes and their human homologues have conserved functions with respect to the etiology of neurodegenerative diseases. The characteristics of the zebrafish and the experimental approaches to which it is amenable make this species a useful complement to other animal models for the study of pathologic mechanisms of neurodegenerative diseases and for the screening of compounds with therapeutic potential

Machine learning discriminates a movement disorder in a zebrafish model of Parkinson's disease

Animal models of human disease provide an in vivo system that can reveal molecular mechanisms by which mutations cause pathology, and, moreover, have the potential to provide a valuable tool for drug development. Here, we have developed a zebrafish model of Parkinson's disease (PD) together with a novel method to screen for movement disorders in adult fish, pioneering a more efficient drug-testing route. Mutation of the PARK7 gene (which encodes DJ-1) is known to cause monogenic autosomal recessive PD in humans, and, using CRISPR/Cas9 gene editing, we generated a Dj-1 loss-of-function zebrafish with molecular hallmarks of PD. To establish whether there is a human-relevant parkinsonian phenotype in our model, we adapted proven tools used to diagnose PD in clinics and developed a novel and unbiased computational method to classify movement disorders in adult zebrafish. Using high-resolution video capture and machine learning, we extracted novel features of movement from continuous data streams and used an evolutionary algorithm to classify parkinsonian fish. This method will be widely applicable for assessing zebrafish models of human motor diseases and provide a valuable asset for the therapeutics pipeline. In addition, interrogation of RNA-seq data indicate metabolic reprogramming of brains in the absence of Dj-1, adding to growing evidence that disruption of bioenergetics is a key feature of neurodegeneration.This article has an associated First Person interview with the first author of the paper.</p

A scalable helium gas cooling system for trapped-ion applications

Microfabricated ion-trap devices offer a promising pathway towards scalable quantum computing. Research efforts have begun to focus on the engineering challenges associated with developing large-scale ion-trap arrays and networks. However, increasing the size of the array and integrating on-chip electronics can drastically increase the power dissipation within the ion-trap chips. This leads to an increase in the operating temperature of the ion-trap and limits the device performance. Therefore, effective thermal management is an essential consideration for any large-scale architecture. Presented here is the development of a modular cooling system designed for use with multiple ion-trapping experiments simultaneously. The system includes an extensible cryostat that permits scaling of the cooling power to meet the demands of a large network. Following experimental testing on two independent ion-trap experiments, the cooling system is expected to deliver a net cooling power of 111 W at ∼70 K to up to four experiments. The cooling system is a step towards meeting the practical challenges of operating large-scale quantum computers with many qubits

Deletion of the WD40 Domain of LRRK2 in Zebrafish Causes Parkinsonism-Like Loss of Neurons and Locomotive Defect

LRRK2 plays an important role in Parkinson's disease (PD), but its biological functions are largely unknown. Here, we cloned the homolog of human LRRK2, characterized its expression, and investigated its biological functions in zebrafish. The blockage of zebrafish LRRK2 (zLRRK2) protein by morpholinos caused embryonic lethality and severe developmental defects such as growth retardation and loss of neurons. In contrast, the deletion of the WD40 domain of zLRRK2 by morpholinos targeting splicing did not induce severe embryonic developmental defects; rather it caused Parkinsonism-like phenotypes, including loss of dopaminergic neurons in diencephalon and locomotion defects. These neurodegenerative and locomotion defects could be rescued by over-expressing zLRRK2 or hLRRK2 mRNA. The administration of L-dopa could also rescue the locomotion defects, but not the neurodegeneration. Taken together, our results demonstrate that zLRRK2 is an ortholog of hLRRK2 and that the deletion of WD40 domain of zLRRK2 provides a disease model for PD