What can quantum optics say about computational complexity theory?

Considering the problem of sampling from the output photon-counting probability distribution of a linear-optical network for input Gaussian states, we obtain results that are of interest from both quantum theory and the computational complexity theory point of view. We derive a general formula for calculating the output probabilities, and by considering input thermal states, we show that the output probabilities are proportional to permanents of positive-semidefinite Hermitian matrices. It is believed that approximating permanents of complex matrices in general is a #P-hard problem. However, we show that these permanents can be approximated with an algorithm in BPP^NP complexity class, as there exists an efficient classical algorithm for sampling from the output probability distribution. We further consider input squeezed-vacuum states and discuss the complexity of sampling from the probability distribution at the output.Comment: 5 pages, 1 figur

Exact Boson Sampling using Gaussian continuous variable measurements

BosonSampling is a quantum mechanical task involving Fock basis state preparation and detection and evolution using only linear interactions. A classical algorithm for producing samples from this quantum task cannot be efficient unless the polynomial hierarchy of complexity classes collapses, a situation believe to be highly implausible. We present method for constructing a device which uses Fock state preparations, linear interactions and Gaussian continuous-variable measurements for which one can show exact sampling would be hard for a classical algorithm in the same way as Boson Sampling. The detection events used from this arrangement does not allow a similar conclusion for the classical hardness of approximate sampling to be drawn. We discuss the details of this result outlining some specific properties that approximate sampling hardness requires

Boson Sampling from Gaussian States

We pose a generalized Boson Sampling problem. Strong evidence exists that such a problem becomes intractable on a classical computer as a function of the number of Bosons. We describe a quantum optical processor that can solve this problem efficiently based on Gaussian input states, a linear optical network and non-adaptive photon counting measurements. All the elements required to build such a processor currently exist. The demonstration of such a device would provide the first empirical evidence that quantum computers can indeed outperform classical computers and could lead to applications

Serum BUN and creatinine estimation in patients of overt hypothyroidism: a case control study

Background: Hypothyroidism or underactive thyroid or low thyroid is a common endocrine disorder characterized by low serum T3 (triiodothyronine), T4 (thyroxine) and raised TSH (thyroid stimulating hormone). Thyroid hormones are involved in renal development and hemodynamic, kidney structure and GFR (glomerular filtration rate). Aim of this study was to see the alteration of basic renal markers in patients of hypothyroidism.Methods: A total of seventy subjects were included in the study. Thirty-five were patients of hypothyroidism and thirty-five were age and sex matched normal controls. Serum T3, T4, TSH, creatinine and BUN (blood urea nitrogen) were estimated in both groups.Results: Serum T3, T4 were significantly decreased and TSH was significantly raised among cases as compared to controls. Mean value of serum creatinine and BUN were within normal range in both the groups but these values were significantly raised among cases as compared to controls with p value 0.02 and 0.003 respectively. Also, there was positive correlation of TSH with BUN and creatinine among cases

Rank-based model selection for multiple ions quantum tomography

The statistical analysis of measurement data has become a key component of many quantum engineering experiments. As standard full state tomography becomes unfeasible for large dimensional quantum systems, one needs to exploit prior information and the "sparsity" properties of the experimental state in order to reduce the dimensionality of the estimation problem. In this paper we propose model selection as a general principle for finding the simplest, or most parsimonious explanation of the data, by fitting different models and choosing the estimator with the best trade-off between likelihood fit and model complexity. We apply two well established model selection methods -- the Akaike information criterion (AIC) and the Bayesian information criterion (BIC) -- to models consising of states of fixed rank and datasets such as are currently produced in multiple ions experiments. We test the performance of AIC and BIC on randomly chosen low rank states of 4 ions, and study the dependence of the selected rank with the number of measurement repetitions for one ion states. We then apply the methods to real data from a 4 ions experiment aimed at creating a Smolin state of rank 4. The two methods indicate that the optimal model for describing the data lies between ranks 6 and 9, and the Pearson $\chi^{2}$ test is applied to validate this conclusion. Additionally we find that the mean square error of the maximum likelihood estimator for pure states is close to that of the optimal over all possible measurements.Comment: 24 pages, 6 figures, 3 table

Quantum teleportation on a photonic chip

Quantum teleportation is a fundamental concept in quantum physics which now finds important applications at the heart of quantum technology including quantum relays, quantum repeaters and linear optics quantum computing (LOQC). Photonic implementations have largely focussed on achieving long distance teleportation due to its suitability for decoherence-free communication. Teleportation also plays a vital role in the scalability of photonic quantum computing, for which large linear optical networks will likely require an integrated architecture. Here we report the first demonstration of quantum teleportation in which all key parts - entanglement preparation, Bell-state analysis and quantum state tomography - are performed on a reconfigurable integrated photonic chip. We also show that a novel element-wise characterisation method is critical to mitigate component errors, a key technique which will become increasingly important as integrated circuits reach higher complexities necessary for quantum enhanced operation.Comment: Originally submitted version - refer to online journal for accepted manuscript; Nature Photonics (2014

BHLHE40 regulates the T-cell effector function required for tumor microenvironment remodeling and immune checkpoint therapy efficacy

Immune checkpoint therapy (ICT) using antibody blockade of programmed cell death protein 1 (PD-1) or cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) can provoke T cell-dependent antitumor activity that generates durable clinical responses in some patients. The epigenetic and transcriptional features that T cells require for efficacious ICT remain to be fully elucidated. Herein, we report that anti-PD-1 and anti-CTLA-4 ICT induce upregulation of the transcription factor BHLHE40 in tumor antigen-specific CD8+ and CD4+ T cells and that T cells require BHLHE40 for effective ICT in mice bearing immune-edited tumors. Single-cell RNA sequencing of intratumoral immune cells in BHLHE40-deficient mice revealed differential ICT-induced immune cell remodeling. The BHLHE40-dependent gene expression changes indicated dysregulated metabolism, NF-κB signaling, and IFNγ response within certain subpopulations of CD4+ and CD8+ T cells. Intratumoral CD4+ and CD8+ T cells from BHLHE40-deficient mice exhibited higher expression of the inhibitory receptor gene Tigit and displayed alterations in expression of genes encoding chemokines/chemokine receptors and granzyme family members. Mice lacking BHLHE40 had reduced ICT-driven IFNγ production by CD4+ and CD8+ T cells and defects in ICT-induced remodeling of macrophages from a CX3CR1+CD206+ subpopulation to an iNOS+ subpopulation that is typically observed during effective ICT. Although both anti-PD-1 and anti-CTLA-4 ICT in BHLHE40-deficient mice led to the same outcome-tumor outgrowth-several BHLHE40-dependent alterations were specific to the ICT that was used. Our results reveal a crucial role for BHLHE40 in effective ICT and suggest that BHLHE40 may be a predictive or prognostic biomarker for ICT efficacy and a potential therapeutic target

Impact of Surgical Timing on Neurological Outcomes for Spinal Arachnoid Cyst: A Single Institution Series

Objective Spinal arachnoid cysts (SACs) are rare lesions that often present with back pain and myelopathy. There is a paucity of literature evaluating the impact of surgical timing on neurological outcomes for primary SAC management. To compare long-term neurological outcomes in patients who were managed differently and to understand natural progression of SAC. Methods We conducted a retrospective analysis of adult patients treated for SAC at our institution from 2010 to 2021, stratified into 3 groups (conservative management only, surgical management, or conservative followed by surgical management). Study outcome measures were neurological outcomes as measured by modified McCormick Neurologic Scale (MNS), postoperative complications, and cyst recurrence. Nonparametric analysis was performed to evaluate differences between groups for selected endpoints. Results Thirty-six patients with SAC were identified. Eighteen patients were managed surgically. The remaining 18 patients were managed conservatively with outpatient serial imaging, 7 of whom (38.9%) ultimately underwent surgical treatment due to neurological decline. Most common presenting symptoms included back pain (50.0%), extremity weakness (36.1%), and numbness/paresthesia (36.1%). Initial/preoperative (p = 0.017) and 1-year postoperative (p = 0.006) MNS were significantly different between the 3 groups, but not at 6 weeks or 6 months postoperatively (p > 0.05). Additionally, at 1 year, there was no difference in MNS between patients managed surgically and those managed conservatively but ultimately underwent surgery (p > 0.99). Conclusion Delayed surgical intervention in minimally symptomatic patients does not seem to result in worse long-term neurofunctional outcomes. At 1 year, postoperative MNS were significantly higher in both surgical groups, when compared to the conservative group highlighting worsening clinical picture regardless of preoperative observational status

Neurologic Outcomes for Adult Spinal Cord Ependymomas Stratified by Tumor Location: A Retrospective Cohort Study and 2-Year Outlook

Determine whether craniocaudal spinal cord tumor location affects long-term neurologic outcomes in adults diagnosed with spinal ependymomas (SE). A retrospective cohort analysis of patients aged ≥ 18 years who underwent surgical resection for SE over a ten-year period was conducted. Tumor location was classified as cervical, thoracic, or lumbar/conus. Primary endpoints were post-operative McCormick Neurologic Scale (MNS) scores at \u3c 3 days, 6 weeks, 1 year, and 2 years. One-way ANOVA was performed to detect significant differences in MNS scores between tumor locations. Twenty-eight patients were identified. The average age was 44.2 ± 15.4 years. Sixteen were male, and 13 were female. There were 10 cervical-predominant SEs, 13 thoracic-predominant SEs, and 5 lumbar/conus-predominant SEs. No significant differences were observed in pre-operative MNS scores between tumor locations (p = 0.73). One-way ANOVA testing demonstrated statistically significant differences in post-operative MNS scores between tumor locations at \u3c 3 days (p = 0.03), 6 weeks (p = 0.009), and 1 year (p = 0.003); however, no significant difference was observed between post-operative MNS scores at 2 years (p = 0.13). The mean MNS score for patients with thoracic SEs were higher at all follow-up time points. Tumors arising in the thoracic SE are associated with worse post-operative neurologic outcomes in comparison to SEs arising in other spinal regions. This is likely multifactorial in etiology, owing to both anatomical differences including spinal cord volume as well as variations in tumor characteristics. No significant differences in 2-year MNS scores were observed, suggesting that patients ultimately recover from neurological insult sustained at the time of surgery

Effect of Oxygen Concentration on Viability and Metabolism in a Fluidized-Bed Bioartificial Liver Using 31 P and 13 C NMR Spectroscopy

Many oxygen mass-transfer modeling studies have been performed for various bioartificial liver (BAL) encapsulation types; yet, to our knowledge, there is no experimental study that directly and noninvasively measures viability and metabolism as a function of time and oxygen concentration. We report the effect of oxygen concentration on viability and metabolism in a fluidized-bed NMR-compatible BAL using in vivo 31P and 13C NMR spectroscopy, respectively, by monitoring nucleotide triphosphate (NTP) and 13C-labeled nutrient metabolites, respectively. Fluidized-bed bioreactors eliminate the potential channeling that occurs with packed-bed bioreactors and serve as an ideal experimental model for homogeneous oxygen distribution. Hepatocytes were electrostatically encapsulated in alginate (avg. diameter, 500 μm; 3.5×107 cells/mL) and perfused at 3 mL/min in a 9-cm (inner diameter) cylindrical glass NMR tube. Four oxygen treatments were tested and validated by an in-line oxygen electrode: (1) 95:5 oxygen:carbon dioxide (carbogen), (2) 75:20:5 nitrogen:oxygen:carbon dioxide, (3) 60:35:5 nitrogen:oxygen:carbon dioxide, and (4) 45:50:5 nitrogen:oxygen:carbon dioxide. With 20% oxygen, β-NTP steadily decreased until it was no longer detected at 11 h. The 35%, 50%, and 95% oxygen treatments resulted in steady β-NTP levels throughout the 28-h experimental period. For the 50% and 95% oxygen treatment, a 13C NMR time course (∼5 h) revealed 2-13C-glycine and 2-13C-glucose to be incorporated into [2-13C-glycyl]glutathione (GSH) and 2-13C-lactate, respectively, with 95% having a lower rate of lactate formation. 31P and 13C NMR spectroscopy is a noninvasive method for determining viability and metabolic rates. Modifying tissue-engineered devices to be NMR compatible is a relatively easy and inexpensive process depending on the bioreactor shape