Parameter Estimation with Mixed-State Quantum Computation

We present a quantum algorithm to estimate parameters at the quantum metrology limit using deterministic quantum computation with one bit. When the interactions occurring in a quantum system are described by a Hamiltonian $H= \theta H_0$, we estimate $\theta$ by zooming in on previous estimations and by implementing an adaptive Bayesian procedure. The final result of the algorithm is an updated estimation of $\theta$ whose variance has been decreased in proportion to the time of evolution under H. For the problem of estimating several parameters, we implement dynamical-decoupling techniques and use the results of single parameter estimation. The cases of discrete-time evolution and reference-frame alignment are also discussed within the adaptive approach.Comment: 12 pages. Improved introduction and technical details moved to Appendi

Necessary Condition for the Quantum Adiabatic Approximation

A gapped quantum system that is adiabatically perturbed remains approximately in its eigenstate after the evolution. We prove that, for constant gap, general quantum processes that approximately prepare the final eigenstate require a minimum time proportional to the ratio of the length of the eigenstate path to the gap. Thus, no rigorous adiabatic condition can yield a smaller cost. We also give a necessary condition for the adiabatic approximation that depends on local properties of the path, which is appropriate when the gap varies.Comment: 5 pages, 1 figur

A Quantum Approach to Classical Statistical Mechanics

We present a new approach to study the thermodynamic properties of $d$-dimensional classical systems by reducing the problem to the computation of ground state properties of a $d$-dimensional quantum model. This classical-to-quantum mapping allows us to deal with standard optimization methods, such as simulated and quantum annealing, on an equal basis. Consequently, we extend the quantum annealing method to simulate classical systems at finite temperatures. Using the adiabatic theorem of quantum mechanics, we derive the rates to assure convergence to the optimal thermodynamic state. For simulated and quantum annealing, we obtain the asymptotic rates of $T(t) \approx (p N) /(k_B \log t)$ and $\gamma(t) \approx (Nt)^{-\bar{c}/N}$, for the temperature and magnetic field, respectively. Other annealing strategies, as well as their potential speed-up, are also discussed.Comment: 4 pages, no figure

Spin dynamics of the S=1/2 antiferromagnetic zig-zag ladder with anisotropy

We use exact diagonalization and the modified Lanczos method to study the finite energy and finite momentum spectral weight of the longitudinal and transverse spin excitations of the anisotropic zig-zag ladder. We find that the spin excitations form continua of gapless or gapped spinons in the different regions of the phase diagram. The results obtained are consistent with a picture previously proposed that in the anisotropic case there is a transition from a gapped regime to a gapless regime, for small interchain coupling. In this regime we find a sharp low-energy peak in the structure function for the transverse spin excitations, consistent with a finite stiffness.Comment: 17 figure

Atrial fibrillation impairs the diagnostic performance of cardiac natriuretic peptides in dyspneic patients. results from the BACH Study (Biomarkers in ACute Heart Failure)

Objectives: The purpose of this study was to assess the impact of atrial fibrillation (AF) on the performance of mid-region amino terminal pro-atrial natriuretic peptide (MR-proANP) in comparison with the B-type peptides (BNP and NT-proBNP) for diagnosis of acute heart failure (HF) in dyspneic patients. Background: The effects of AF on the diagnostic and prognostic performance of MR-proANP in comparison with the B type natriuretic peptides have not been previously reported. Methods: A total of 1,445 patients attending the emergency department with acute dyspnea had measurements taken of MR-proANP, BNP, and NT-proBNP values on enrollment to the BACH trial and were grouped according to presence or absence of AF and HF. Results: AF was present in 242 patients. Plasma concentrations of all three peptides were lowest in those with neither AF nor HF and AF without HF was associated with markedly increased levels (p < 0.00001). HF with or without AF was associated with a significant further increment (p < 0.00001 for all three markers). Areas under receiver operator characteristic curves (AUCs) for discrimination of acute HF were similar and powerful for all peptides without AF (0.893 to 0.912; all p < 0.001) with substantial and similar reductions (0.701 to 0.757) in the presence of AF. All 3 peptides were independently prognostic but there was no interaction between any peptide and AF for prediction of all-cause mortality. Conclusions: AF is associated with increased plasma natriuretic peptide (MR-proANP, BNP and NT-proBNP) levels in the absence of HF. The diagnostic performance of all three peptides is impaired by AF. This warrants consideration of adjusted peptide thresholds for diagnostic use in AF and mandates the continued search for markers free of confounding by AF

Approximating Fractional Time Quantum Evolution

An algorithm is presented for approximating arbitrary powers of a black box unitary operation, $\mathcal{U}^t$, where $t$ is a real number, and $\mathcal{U}$ is a black box implementing an unknown unitary. The complexity of this algorithm is calculated in terms of the number of calls to the black box, the errors in the approximation, and a certain `gap' parameter. For general $\mathcal{U}$ and large $t$, one should apply $\mathcal{U}$ a total of $\lfloor t \rfloor$ times followed by our procedure for approximating the fractional power $\mathcal{U}^{t-\lfloor t \rfloor}$. An example is also given where for large integers $t$ this method is more efficient than direct application of $t$ copies of $\mathcal{U}$. Further applications and related algorithms are also discussed.Comment: 13 pages, 2 figure

Potentiating vascular-targeted photodynamic therapy through CSF-1R modulation of myeloid cells in a preclinical model of prostate cancer

Vascular-targeted photodynamic therapy (VTP) induces rapid destruction of targeted tissues and is a promising therapy for prostate cancer. However, the resulting immune response, which may play an important role in either potentiating or blunting the effects of VTP, is still incompletely understood. Myeloid cells such as myeloid-derived suppressor cells (MDSCs) and macrophages are often found in tumors and are widely reported to be associated with cancer angiogenesis, tissue remodeling, and immunosuppression. These cells are also known to play a critical role in wound-healing, which is induced by rapid tissue destruction. In this study, we investigated the effects of VTP on the recruitment of tumor-infiltrating myeloid cells, specifically MDSCs and tumor-associated macrophages (TAMs), in the Myc-Cap and TRAMP C2 murine prostate cancer models. We report that VTP increased the infiltration of myeloid cells into the tumors, as well as their expression of CSF1R, a receptor required for myeloid differentiation, proliferation, and tumor migration. As anti-CSF1R treatment has previously been used to deplete these cells types in other murine models of prostate cancer, we hypothesized that combining anti-CSF1R with VTP therapy would lead to decreased tumor regrowth and improved survival. Importantly, we found that targeting myeloid cells using anti-CSF1R in combination with VTP therapy decreased the number of tumor MDSCs and TAMs, especially M2 macrophages, as well as increased CD8 T cell infiltration, decreased tumor growth and improved overall survival. These results suggest that targeting myeloid cells via CSF1R targeting is a promising strategy to potentiate the anti-tumor effects of VTP