Parameter scaling in the decoherent quantum-classical transition for chaotic systems

The quantum to classical transition has been shown to depend on a number of parameters. Key among these are a scale length for the action, $\hbar$, a measure of the coupling between a system and its environment, $D$, and, for chaotic systems, the classical Lyapunov exponent, $\lambda$. We propose computing a measure, reflecting the proximity of quantum and classical evolutions, as a multivariate function of $(\hbar,\lambda,D)$ and searching for transformations that collapse this hyper-surface into a function of a composite parameter $\zeta = \hbar^{\alpha}\lambda^{\beta}D^{\gamma}$. We report results for the quantum Cat Map, showing extremely accurate scaling behavior over a wide range of parameters and suggest that, in general, the technique may be effective in constructing universality classes in this transition.Comment: Submitte

The Palomar Kernel Phase Experiment: Testing Kernel Phase Interferometry for Ground-based Astronomical Observations

At present, the principal limitation on the resolution and contrast of astronomical imaging instruments comes from aberrations in the optical path, which may be imposed by the Earth's turbulent atmosphere or by variations in the alignment and shape of the telescope optics. These errors can be corrected physically, with active and adaptive optics, and in post-processing of the resulting image. A recently-developed adaptive optics post-processing technique, called kernel phase interferometry, uses linear combinations of phases that are self-calibrating with respect to small errors, with the goal of constructing observables that are robust against the residual optical aberrations in otherwise well-corrected imaging systems. Here we present a direct comparison between kernel phase and the more established competing techniques, aperture masking interferometry, point spread function (PSF) fitting and bispectral analysis. We resolve the alpha Ophiuchi binary system near periastron, using the Palomar 200-Inch Telescope. This is the first case in which kernel phase has been used with a full aperture to resolve a system close to the diffraction limit with ground-based extreme adaptive optics observations. Excellent agreement in astrometric quantities is found between kernel phase and masking, and kernel phase significantly outperforms PSF fitting and bispectral analysis, demonstrating its viability as an alternative to conventional non-redundant masking under appropriate conditions.Comment: Accepted to MNRA

Conditions for the Quantum to Classical Transition: Trajectories vs. Phase Space Distributions

We contrast two sets of conditions that govern the transition in which classical dynamics emerges from the evolution of a quantum system. The first was derived by considering the trajectories seen by an observer (dubbed the ``strong'' transition) [Bhattacharya, et al., Phys. Rev. Lett. 85: 4852 (2000)], and the second by considering phase-space densities (the ``weak'' transition) [Greenbaum, et al., Chaos 15, 033302 (2005)]. On the face of it these conditions appear rather different. We show, however, that in the semiclassical regime, in which the action of the system is large compared to $\hbar$, and the measurement noise is small, they both offer an essentially equivalent local picture. Within this regime, the weak conditions dominate while in the opposite regime where the action is not much larger than Planck's constant, the strong conditions dominate.Comment: 8 pages, 2 eps figure

Nonlinear Quantum Dynamics

The vast majority of the literature dealing with quantum dynamics is concerned with linear evolution of the wave function or the density matrix. A complete dynamical description requires a full understanding of the evolution of measured quantum systems, necessary to explain actual experimental results. The dynamics of such systems is intrinsically nonlinear even at the level of distribution functions, both classically as well as quantum mechanically. Aside from being physically more complete, this treatment reveals the existence of dynamical regimes, such as chaos, that have no counterpart in the linear case. Here, we present a short introductory review of some of these aspects, with a few illustrative results and examples.Comment: 13 pages, 3 figures, invited talk at the NATO Advanced Workshop, "Nonlinear Dynamics and Fundamental Interactions," (October, 2004, Tashkent

The Palomar kernel-phase experiment: testing kernel phase interferometry for ground-based astronomical observations

At present, the principal limitation on the resolution and contrast of astronomical imaging instruments comes from aberrations in the optical path, which may be imposed by the Earth's turbulent atmosphere or by variations in the alignment and shape of the telescope optics. These errors can be corrected physically,with active and adaptive optics, and in post-processing of the resulting image.Arecently developed adaptive optics post-processing technique, called kernelphase interferometry, uses linear combinations of phases that are self-calibrating with respect to small errors, with the goal of constructing observables that are robust against the residual optical aberrations in otherwise well-corrected imaging systems. Here, we present a direct comparison between kernel phase and the more established competing techniques, aperture masking interferometry, point spread function (PSF) fitting and bispectral analysis.We resolve the α Ophiuchi binary system near periastron, using the Palomar 200-Inch Telescope. This is the first case in which kernel phase has been used with a full aperture to resolve a system close to the diffraction limit with ground-based extreme adaptive optics observations. Excellent agreement in astrometric quantities is found between kernel phase and masking, and kernel phase significantly outperforms PSF fitting and bispectral analysis, demonstrating its viability as an alternative to conventional non-redundant masking under appropriate conditions

Retroelement decay by the exonuclease XRN1 is a viral mimicry dependency in cancer

Viral mimicry describes the immune response induced by endogenous stimuli such as double-stranded RNA (dsRNA) from endogenous retroelements. Activation of viral mimicry has the potential to kill cancer cells or augment anti-tumor immune responses. Here, we systematically identify mechanisms of viral mimicry adaptation associated with cancer cell dependencies. Among the top hits is the RNA decay protein XRN1 as an essential gene for the survival of a subset of cancer cell lines. XRN1 dependency is mediated by mitochondrial antiviral signaling protein and protein kinase R activation and is associated with higher levels of cytosolic dsRNA, higher levels of a subset of Alus capable of forming dsRNA, and higher interferon-stimulated gene expression, indicating that cells die due to induction of viral mimicry. Furthermore, dsRNA-inducing drugs such as 5-aza-2'-deoxycytidine and palbociclib can generate a synthetic dependency on XRN1 in cells initially resistant to XRN1 knockout. These results indicate that XRN1 is a promising target for future cancer therapeutics

Multiplexed Cre-dependent selection yields systemic AAVs for targeting distinct brain cell types

Recombinant adeno-associated viruses (rAAVs) are efficient gene delivery vectors via intravenous delivery; however, natural serotypes display a finite set of tropisms. To expand their utility, we evolved AAV capsids to efficiently transduce specific cell types in adult mouse brains. Building upon our Cre-recombination-based AAV targeted evolution (CREATE) platform, we developed Multiplexed-CREATE (M-CREATE) to identify variants of interest in a given selection landscape through multiple positive and negative selection criteria. M-CREATE incorporates next-generation sequencing, synthetic library generation and a dedicated analysis pipeline. We have identified capsid variants that can transduce the central nervous system broadly, exhibit bias toward vascular cells and astrocytes, target neurons with greater specificity or cross the blood–brain barrier across diverse murine strains. Collectively, the M-CREATE methodology accelerates the discovery of capsids for use in neuroscience and gene-therapy applications

Mutation-derived Neoantigen-specific T-cell Responses in Multiple Myeloma.

PURPOSE: Somatic mutations in cancer cells can give rise to novel protein sequences that can be presented by antigen-presenting cells as neoantigens to the host immune system. Tumor neoantigens represent excellent targets for immunotherapy, due to their specific expression in cancer tissue. Despite the widespread use of immunomodulatory drugs and immunotherapies that recharge T and NK cells, there has been no direct evidence that neoantigen-specific T-cell responses are elicited in multiple myeloma. EXPERIMENTAL DESIGN: Using next-generation sequencing data we describe the landscape of neo-antigens in 184 patients with multiple myeloma and successfully validate neoantigen-specific T cells in patients with multiple myeloma and support the feasibility of neoantigen-based therapeutic vaccines for use in cancers with intermediate mutational loads such as multiple myeloma. RESULTS: In this study, we demonstrate an increase in neoantigen load in relapsed patients with multiple myeloma as compared with newly diagnosed patients with multiple myeloma. Moreover, we identify shared neoantigens across multiple patients in three multiple myeloma oncogenic driver genes (KRAS, NRAS, and IRF4). Next, we validate neoantigen T-cell response and clonal expansion in correlation with clinical response in relapsed patients with multiple myeloma. This is the first study to experimentally validate the immunogenicity of predicted neoantigens from next-generation sequencing in relapsed patients with multiple myeloma. CONCLUSIONS: Our findings demonstrate that somatic mutations in multiple myeloma can be immunogenic and induce neoantigen-specific T-cell activation that is associated with antitumor activity in vitro and clinical response in vivo. Our results provide the foundation for using neoantigen targeting strategies such as peptide vaccines in future trials for patients with multiple myeloma