Long-range photon-mediated gate scheme between nuclear spin qubits in diamond

Defect centers in diamond are exceptional solid-state quantum systems that can have exceedingly long electron and nuclear spin coherence times. So far, single-qubit gates for the nitrogen nuclear spin, a two-qubit gate with a nitrogen-vacancy (NV) center electron spin, and entanglement between nearby nitrogen nuclear spins have been demonstrated. Here, we develop a scheme to implement a universal two-qubit gate between two distant nitrogen nuclear spins. Virtual excitation of an NV center that is embedded in an optical cavity can scatter a laser photon into the cavity mode; we show that this process depends on the nuclear spin state of the nitrogen atom. If two NV centers are simultaneously coupled to a common cavity mode and individually excited, virtual cavity photon exchange can mediate an effective interaction between the nuclear spin qubits, conditioned on the spin state of both nuclei, which implements a universal controlled-$\textit{Z}$ gate. We predict operation times below 100 nanoseconds, which is several orders of magnitude faster than the decoherence time of nuclear spin qubits in diamond.Comment: 6 pages (including 2 appendices), 3 figures, 1 tabl

Entangled photons from the polariton vacuum in a switchable optical cavity

We study theoretically the entanglement of two-photon states in the ground state of the intersubband cavity system, the so-called polariton vacuum. The system consists of a sequence of doped quantum wells located inside a microcavity and the photons can interact with intersubband excitations inside the quantum wells. Using an explicit solution for the ground state of the system, operated in the ultrastrong coupling regime, a post-selection is introduced, where only certain two-photon states are considered and analyzed for mode entanglement. We find that a fast quench of the coupling creates entangled photons and that the degree of entanglement depends on the absolute values of the in-plane wave vectors of the photons. Maximally entangled states can be generated by choosing the appropriate modes in the post-selection.Comment: 9+ pages, 7 figure

Benchmarking Digital-Analog Quantum Computation

Digital-Analog Quantum Computation (DAQC) has recently been proposed as an alternative to the standard paradigm of digital quantum computation. DAQC creates entanglement through a continuous or analog evolution of the whole device, rather than by applying two-qubit gates. This manuscript describes an in-depth analysis of DAQC by extending its implementation to arbitrary connectivities and by performing the first systematic study of its scaling properties. We specify the analysis for three examples of quantum algorithms, showing that except for a few specific cases, DAQC is in fact disadvantageous with respect to the digital case.Comment: 16+5 pages, 11 figure

GAD antibody-associated limbic encephalitis in a young woman with APECED

The autoimmune polyendocrinopathy–candidiasis–ectodermal dystrophy (APECED) syndrome is a genetic disorder caused by a mutation in the autoimmune regulator (AIRE) gene. Immune deficiency, hypoparathyroidism and Addison’s disease due to autoimmune dysfunction are the major clinical signs of APECED. We report on a 21-year-old female APECED patient with two inactivating mutations in the AIRE gene. She presented with sudden onset of periodic nausea. Adrenal insufficiency was diagnosed by means of the ACTH stimulation test. Despite initiation of hormone replacement therapy with hydrocortisone and fludrocortisone, nausea persisted and the patient developed cognitive deficits and a loss of interest which led to the diagnosis of depression. She was admitted to the psychiatric department for further diagnostic assessment. An EEG showed a focal epileptic pattern. Glutamic acid decarboxylase (GAD) antibodies, which had been negative eight years earlier, were now elevated in serum and in the cerebrospinal fluid. Oligoclonal bands were positive indicating an inflammatory process with intrathecal antibody production in the central nervous system (CNS). The periodic nausea was identified as dialeptic seizures, which clinically presented as gastrointestinal aura followed by episodes of reduced consciousness that occurred about 3–4 times per day. GAD antibody-associated limbic encephalitis (LE) was diagnosed. Besides antiepileptic therapy, an immunosuppressive treatment with corticosteroids was initiated followed by azathioprine. The presence of nausea and vomiting in endocrine patients with autoimmune disorders is indicative of adrenal insufficiency. However, our case report shows that episodic nausea may be a symptom of epileptic seizures due to GAD antibodies-associated LE in patients with APECED

Major immunophenotypic abnormalities in patients with primary adrenal insufficiency of different etiology

INTRODUCTION Patients with primary adrenal insufficiency (PAI) suffer from increased risk of infection, adrenal crises and have a higher mortality rate. Such dismal outcomes have been inferred to immune cell dysregulation because of unphysiological cortisol replacement. As the immune landscape of patients with different types of PAI has not been systematically explored, we set out to immunophenotype PAI patients with different causes of glucocorticoid (GC) deficiency. METHODS This cross-sectional single center study includes 28 patients with congenital adrenal hyperplasia (CAH), 27 after bilateral adrenalectomy due to Cushing's syndrome (BADx), 21 with Addison's disease (AD) and 52 healthy controls. All patients with PAI were on a stable GC replacement regimen with a median dose of 25 mg hydrocortisone per day. Peripheral blood mononuclear cells were isolated from heparinized blood samples. Immune cell subsets were analyzed using multicolor flow cytometry after four-hour stimulation with phorbol myristate acetate and ionomycin. Natural killer (NK-) cell cytotoxicity and clock gene expression were investigated. RESULTS The percentage of T helper cell subsets was downregulated in AD patients (Th1 p = 0.0024, Th2 p = 0.0157, Th17 p < 0.0001) compared to controls. Cytotoxic T cell subsets were reduced in AD (Tc1 p = 0.0075, Tc2 p = 0.0154) and CAH patients (Tc1 p = 0.0055, Tc2 p = 0.0012) compared to controls. NKCC was reduced in all subsets of PAI patients, with smallest changes in CAH. Degranulation marker CD107a expression was upregulated in BADx and AD, not in CAH patients compared to controls (BADx p < 0.0001; AD p = 0.0002). In contrast to NK cell activating receptors, NK cell inhibiting receptor CD94 was upregulated in BADx and AD, but not in CAH patients (p < 0.0001). Although modulation in clock gene expression could be confirmed in our patient subgroups, major interindividual-intergroup dissimilarities were not detected. DISCUSSION In patients with different etiologies of PAI, distinct differences in T and NK cell-phenotypes became apparent despite the use of same GC preparation and dose. Our results highlight unsuspected differences in immune cell composition and function in PAI patients of different causes and suggest disease-specific alterations that might necessitate disease-specific treatment

Torpedo: Improving the State-of-the-Art RDF Dataset Slicing

Over the last years, the amount of data published as Linked Data on the Web has grown enormously. In spite of the high availability of Linked Data, organizations still encounter an accessibility challenge while consuming it. This is mostly due to the large size of some of the datasets published as Linked Data. The core observation behind this work is that a subset of these datasets suffices to address the needs of most organizations. In this paper, we introduce Torpedo, an approach for efficiently selecting and extracting relevant subsets from RDF datasets. In particular, Torpedo adds optimization techniques to reduce seek operations costs as well as the support of multi-join graph patterns and SPARQL FILTERs that enable to perform a more granular data selection. We compare the performance of our approach with existing solutions on nine different queries against four datasets. Our results show that our approach is highly scalable and is up to 26% faster than the current state-of-the-art RDF dataset slicing approach