WELFARE EFFECTS OF AGRICULTURAL TRADING BLOCS: THE SIMULATION OF A NORTH AMERICAN CUSTOMS UNION

Agricultural trade liberalization among the three North American Free Trade Agreement (NAFTA) signatories is modeled using a political preference function. The model distinguishes among Canada, Mexico, the United States, and a politically passive rest of the world. Through the use of intracountry compensation, the analysis shows that, from an agricultural perspective, economic integration is in the best interest of the group as a whole, although not in the best interest of individual countries. More specifically, of the agricultural production sectors, Canadian dairy, Mexican corn, and U.S. beef producers suffer the greatest losses from the formation of North American customs union.International Relations/Trade,

Ultra Luminous X-ray sources - new distance indicators?

In this paper we fit the NuSTAR and XMM-Newton data of three sources: NGC7793~P13, NGC5907~ULX1, and Circinus~ULX5. Our single model contains emission form non-spherical system: neutron star plus accretion disk directed towards observer. We obtained the very good fit with the reduced $\chi^2$ per degree of freedom equal 1.08 for P13, 1.01 for ULX1, and 1.14 for ULX5.The normalization of our model constrains the distance to the source. The resulting distances are $D=3.41^{+0.11}_{-0.10}$, $6.55_{-0.81}^{+0.69}$ and $2.60^{+0.05}_{-0.03}$~Mpc for P13, ULX1 and ULX5 respectively. The distances to P13 and ULX5 are in perfect agreement with previous distance measurements to their host galaxies. Our results confirm that P13, ULX1 and ULX5 may contain central hot neutron star. When the outgoing emission is computed by integration over the emitting surface and successfully fitted to the data, then the resulting model normalization is the direct distance indicator.Comment: 5 pages, 3 figures, accepted for publication in A&A Letter

Resource-Efficient Chemistry on Quantum Computers with the Variational Quantum Eigensolver and the Double Unitary Coupled-Cluster Approach.

Applications of quantum simulation algorithms to obtain electronic energies of molecules on noisy intermediate-scale quantum (NISQ) devices require careful consideration of resources describing the complex electron correlation effects. In modeling second-quantized problems, the biggest challenge confronted is that the number of qubits scales linearly with the size of the molecular basis. This poses a significant limitation on the size of the basis sets and the number of correlated electrons included in quantum simulations of chemical processes. To address this issue and enable more realistic simulations on NISQ computers, we employ the double unitary coupled-cluster (DUCC) method to effectively downfold correlation effects into the reduced-size orbital space, commonly referred to as the active space. Using downfolding techniques, we demonstrate that properly constructed effective Hamiltonians can capture the effect of the whole orbital space in small-size active spaces. Combining the downfolding preprocessing technique with the variational quantum eigensolver, we solve for the ground-state energy of H2, Li2, and BeH2 in the cc-pVTZ basis using the DUCC-reduced active spaces. We compare these results to full configuration-interaction and high-level coupled-cluster reference calculations

Spin-nematic order in the frustrated pyrochlore-lattice quantum rotor model

As an example of ordering due to quantum fluctuations, we examine the nearest-neighbor antiferromagnetic quantum O(n) rotor model on the pyrochlore lattice. Classically, this system remains disordered even at zero temperature; we find that adding quantum fluctuations induces an ordered phase that survives to positive temperature, and we determine how its phase diagram scales with the coupling constant and the number of spin components. We demonstrate, using quantum Monte Carlo simulations, that this phase has long-range spin-nematic order, and that the phase transition into it appears to be first order.Comment: 10 pages, 8 figure

Elevated cystatin-C concentration is associated with progression to prediabetes: the Western New York Study

OBJECTIVE – We conducted a nested case-control investigation to examine if elevated baseline concentrations of cystatin-C predicted progression from normoglycaemia to prediabetes over 6 years of follow-up from the Western New York Health Study. RESEARCH DESIGN AND METHODS – 1,455 participants from the Western New York Health Study, free of type 2 diabetes and known cardiovascular disease at baseline (1996-2001), were reexamined in 2002-2004. An incident case of prediabetes was defined as one with fasting glucose below 100 mg/dl at the baseline examination and ≥ 100 mg/dl and ≤ 125 mg/dl at the follow-up examination. All cases (n=91) were matched 1:3 to control participants based upon sex, race/ethnicity and year of study enrollment. All controls had fasting glucose levels < 100 mg/dl at both baseline and follow-up examinations. Cystatin-C concentrations and the urinary albumin to creatinine ratio were measured from frozen (-196 Cº) baseline blood and urine samples. Serum creatinine concentrations were available from the baseline examination. RESULTS –Multivariate conditional logistic regression analyses adjusted for age, baseline glucose level, HOMA-IR, body mass index, hypertension, eGFR, cigarette smoking, and alcohol use revealed a significantly increased risk of progression to prediabetes among those with elevated baseline concentrations of cystatin-C (Odds Ratio, 95% CI: 3.04, 1.34, 6.89) (upper quintile vs. the remainder). Results of secondary analyses that considered hs-CRP, IL-6, E-selectin, or sICAM did not alter these results. CONCLUSIONS - These results suggest that early renal impairment indexed with cystatin-C imparted a three-fold excess risk of progression to prediabetes in this study population. Recent evidence from randomized clinical trials (1,2) among people with prediabetes have provided convincing evidence that early intervention can significantly delay or prevent the progression to type 2 diabetes. The identification of those with prediabetes is assuming greater importance (3) especially in light of the fact that approximately 35 million adults aged 40-74 years old in the United States have prediabetes defined as impaired fasting glucose (4). Microalbuminuria occurs frequently in nondiabetic subjects and places them at increased risk for cardiovascular disease (5-7). The mechanisms behind this observation are poorly understood, however. Albuminuria may reflect underlying vascular damage (8), hypertension (9, 10) endothelial dysfunction (11, 12) and/or low-grade inflammation (13). A large percentage of type 2 individuals pass through a period of prediabetes (14) and may experience early renal dysfunction e.g., a glomerular filtration rate (GFR) above 60 ml/minute per 1.73m2. Currently used estimating equations are poor at identifying early renal impairment and better indices are of great interest (15, 16). Recently, several studies have suggested that cystatin-C levels may be a more sensitive marker of early renal impairment than either albuminuria or serum creatinine concentration (17-20). Therefore, a better understanding of a putative role for cystatin-C in the etiology of prediabetes could shed light on the renal/heart disease connection (21). Given the reported superiority of cystatin C over conventional measures of renal function, we hypothesized that cystatin-C would predict progression to prediabetes independent of serum creatinine or estimated GFR. We also investigated the role of intervening mechanisms including hypertension, insulin resistance, endothelial dysfunction and inflammation

Quantum flow algorithms for simulating many-body systems on quantum computers

We conducted quantum simulations of strongly correlated systems using the quantum flow (QFlow) approach, which enables sampling large sub-spaces of the Hilbert space through coupled eigenvalue problems in reduced dimensionality active spaces. Our QFlow algorithms significantly reduce circuit complexity and pave the way for scalable and constant-circuit-depth quantum computing. Our simulations show that QFlow can optimize the collective number of wave function parameters without increasing the required qubits using active spaces having an order of magnitude fewer number of parameters

Generating random density matrices

We study various methods to generate ensembles of random density matrices of a fixed size N, obtained by partial trace of pure states on composite systems. Structured ensembles of random pure states, invariant with respect to local unitary transformations are introduced. To analyze statistical properties of quantum entanglement in bi-partite systems we analyze the distribution of Schmidt coefficients of random pure states. Such a distribution is derived in the case of a superposition of k random maximally entangled states. For another ensemble, obtained by performing selective measurements in a maximally entangled basis on a multi--partite system, we show that this distribution is given by the Fuss-Catalan law and find the average entanglement entropy. A more general class of structured ensembles proposed, containing also the case of Bures, forms an extension of the standard ensemble of structureless random pure states, described asymptotically, as N \to \infty, by the Marchenko-Pastur distribution.Comment: 13 pages in latex with 8 figures include