Possibility of "magic" trapping of three-level system for Rydberg blockade implementation

The Rydberg blockade mechanism has shown noteworthy promise for scalable quantum computation with neutral atoms. Both qubit states and gate-mediating Rydberg state belong to the same optically-trapped atom. The trapping fields, while being essential, induce detrimental decoherence. Here we theoretically demonstrate that this Stark-induced decoherence may be completely removed using powerful concepts of "magic" optical traps. We analyze "magic" trapping of a prototype three-level system: a Rydberg state along with two qubit states: hyperfine states attached to a J=1/2 ground state. Our numerical results show that, while such a "magic" trap for alkali metals would require prohibitively large magnetic fields, the group IIIB metals such as Al are suitable candidates.Comment: 5 pages, 3 figure

Possibility of "magic" co-trapping of two atomic species in optical lattices

Much effort has been devoted to removing differential Stark shifts for atoms trapped in specially tailored "magic" optical lattices, but thus far work has focused on a single trapped atomic species. In this work, we extend these ideas to include two atomic species sharing the same optical lattice. We show qualitatively that, in particular, scalar J = 0 divalent atoms paired with non-scalar state atoms have the necessary characteristics to achieve such Stark shift cancellation. We then present numerical results on "magic" trapping conditions for 27Al paired with 87Sr, as well as several other divalent atoms.Comment: 5 pages, 2 figures, 1 tabl

“Magic” trapping of Rydberg states for quantum information

Recent experiments using neutral atoms to manipulate quantum information show promise for constructing a large-scale, practical quantum computer. Achieving such a quantum computer will require less destructive optical traps for the atoms. Using theoretical and computational tools, we consider the feasibility of one possible “magic” trap for rubidium. Preliminary results suggest such trapping may be possible, but more accurate calculations are necessary to reach definitive conclusion

Modeling multi-particle complexes in stochastic chemical systems

Large complexes of classical particles play central roles in biology, in polymer physics, and in other disciplines. However, physics currently lacks mathematical methods for describing such complexes in terms of component particles, interaction energies, and assembly rules. Here we describe a Fock space structure that addresses this need, as well as diagrammatic methods that facilitate the use of this formalism. These methods can dramatically simplify the equations governing both equilibrium and non-equilibrium stochastic chemical systems. A mathematical relationship between the set of all complexes and a list of rules for complex assembly is also identified

Statistical Mechanics of Problems in Transcription Regulation

As the quantity of sequenced genome data continues to multiply, our understanding of the transcriptional regulation of genomes has lagged behind. This deficit impinges on research throughout biology, from fundamental questions of how evolution proceeds to eminently practical questions such as how antibiotic resistance arises. In this thesis we present three threads that address the question of transcriptional regulation from distinct perspectives. The first thread focuses on the simplest nontrivial regulation motif common in bacteria. We analyze in turn a sampling of the myriad mathematical models previously proposed in the literature for this system. We attempt to shine light on the similarities and differences of the models’ predictions, clarify their microscopic interpretations, and offer guidance as to situations when one model or another should be preferred or even distinguishable. The second thread considers a substantially more complicated genetic circuit, for which we build a minimal phenomenological model that retains intuitive microscopic meaning for all its parameters. The model neatly explains recent experimental observations of bistability in the circuit, and suggests natural generalizations to other metabolically important gene circuits with qualitatively similar architectures. Motivation for the third thread comes from even more complicated transcriptional regulation problems with a multitude of regulatory proteins and binding sites, where even enumerating all possible DNA-protein complexes manually is a formidable challenge. Here we propose a method to tackle this complexity that uses ideas from quantum field theory to encode assembly rules for macromolecular complexes. By specifying a small set of rules, we avoid manual enumeration of the much larger set of complexes, allowing the formalism to automatically generate this set for us.</p

Reconciling kinetic and thermodynamic models of bacterial transcription

The study of transcription remains one of the centerpieces of modern biology with implications in settings from development to metabolism to evolution to disease. Precision measurements using a host of different techniques including fluorescence and sequencing readouts have raised the bar for what it means to quantitatively understand transcriptional regulation. In particular our understanding of the simplest genetic circuit is sufficiently refined both experimentally and theoretically that it has become possible to carefully discriminate between different conceptual pictures of how this regulatory system works. This regulatory motif, originally posited by Jacob and Monod in the 1960s, consists of a single transcriptional repressor binding to a promoter site and inhibiting transcription. In this paper, we show how seven distinct models of this so-called simple-repression motif, based both on thermodynamic and kinetic thinking, can be used to derive the predicted levels of gene expression and shed light on the often surprising past success of the thermodynamic models. These different models are then invoked to confront a variety of different data on mean, variance and full gene expression distributions, illustrating the extent to which such models can and cannot be distinguished, and suggesting a two-state model with a distribution of burst sizes as the most potent of the seven for describing the simple-repression motif

Reconciling Kinetic and Equilibrium Models of Bacterial Transcription

The study of transcription remains one of the centerpieces of modern biology with implications in settings from development to metabolism to evolution to disease. Precision measurements using a host of different techniques including fluorescence and sequencing readouts have raised the bar for what it means to quantitatively understand transcriptional regulation. In particular our understanding of the simplest genetic circuit is sufficiently refined both experimentally and theoretically that it has become possible to carefully discriminate between different conceptual pictures of how this regulatory system works. This regulatory motif, originally posited by Jacob and Monod in the 1960s, consists of a single transcriptional repressor binding to a promoter site and inhibiting transcription. In this paper, we show how seven distinct models of this so-called simple-repression motif, based both on equilibrium and kinetic thinking, can be used to derive the predicted levels of gene expression and shed light on the often surprising past success of the equilibrium models. These different models are then invoked to confront a variety of different data on mean, variance and full gene expression distributions, illustrating the extent to which such models can and cannot be distinguished, and suggesting a two-state model with a distribution of burst sizes as the most potent of the seven for describing the simple-repression motif