Contact in the Unitary Fermi Gas across the Superfluid Phase Transition

A quantity known as the contact is a fundamental thermodynamic property of quantum many-body systems with short-range interactions. Determination of the temperature dependence of the contact for the unitary Fermi gas of infinite scattering length has been a major challenge, with different calculations yielding qualitatively different results. Here we use finite-temperature auxiliary-field quantum Monte Carlo (AFMC) methods on the lattice within the canonical ensemble to calculate the temperature dependence of the contact for the homogeneous spin-balanced unitary Fermi gas. We extrapolate to the continuum limit for 40, 66, and 114 particles, eliminating systematic errors due to finite-range effects. We observe a dramatic decrease in the contact as the superfluid critical temperature is approached from below, followed by a gradual weak decrease as the temperature increases in the normal phase. Our theoretical results are in excellent agreement with the most recent precision ultracold atomic gas experiments. We also present results for the energy as a function of temperature in the continuum limit

Flow transitions in two-dimensional foams

For sufficiently slow rates of strain, flowing foam can exhibit inhomogeneous flows. The nature of these flows is an area of active study in both two-dimensional model foams and three dimensional foam. Recent work in three-dimensional foam has identified three distinct regimes of flow [S. Rodts, J. C. Baudez, and P. Coussot, Europhys. Lett. {\bf 69}, 636 (2005)]. Two of these regimes are identified with continuum behavior (full flow and shear-banding), and the third regime is identified as a discrete regime exhibiting extreme localization. In this paper, the discrete regime is studied in more detail using a model two dimensional foam: a bubble raft. We characterize the behavior of the bubble raft subjected to a constant rate of strain as a function of time, system size, and applied rate of strain. We observe localized flow that is consistent with the coexistence of a power-law fluid with rigid body rotation. As a function of applied rate of strain, there is a transition from a continuum description of the flow to discrete flow when the thickness of the flow region is approximately 10 bubbles. This occurs at an applied rotation rate of approximately $0.07 {\rm s^{-1}}$

Phase Transitions in a Symmetry-Conserving Framework

Phase transitions are often associated with the breaking of a symmetry in the low-temperature phase described by non-vanishing values of certain order parameters. However, in finite-size systems the correlated equilibrium configuration preserves the symmetries of the underlying Hamiltonian. We discuss a method to calculate the statistical distribution of the order parameters without breaking the corresponding symmetries. The maxima of these statistical distributions mimic the phase transitions that are found in a mean-field approximation. We demonstrate the method for the case of shape transitions in atomic nuclei

Controlled Gate Networks Applied to Eigenvalue Estimation

We introduce a new scheme for quantum circuit design called controlled gate networks. Rather than trying to reduce the complexity of individual unitary operations, the new strategy is to toggle between all of the unitary operations needed with the fewest number of gates. We illustrate our approach using two examples. The first example is a variational subspace calculation for a two-qubit system. We demonstrate an approximately five-fold reduction in the number of two-qubit gates required for computing inner products and Hamiltonian matrix elements. The second example is estimating the eigenvalues of a two-qubit Hamiltonian via the Rodeo Algorithm using a specific class of controlled gate networks called controlled reversal gates. Again, a fivefold reduction in the number of two-qubit gates is demonstrated. We use the Quantinuum H1-2 and IBM Perth devices to realize the quantum circuits. Our work demonstrates that controlled gate networks are a useful tool for reducing gate complexity in quantum algorithms for quantum many-body problems.Comment: 10 pages and 9 figures (main text); 2 pages and no figures (supplemental material

Microbial Successions Are Associated with Changes in Chemical Profiles of a Model Refrigerated Fresh Pork Sausage during an 80-Day Shelf Life Study

Fresh pork sausage is produced without a microbial kill step and therefore chilled or frozen to control microbial growth. In this report, the microbiota in a chilled fresh pork sausage model produced with or without an antimicrobial combination of sodium lactate and sodium diacetate was studied using a combination of traditional microbiological methods and deep pyrosequencing of 16S rRNA gene amplicons. In the untreated system, microbial populations rose from 102 to 106 CFU/g within 15 days of storage at 4°C, peaking at nearly 108 CFU/g by day 30. Pyrosequencing revealed a complex community at day 0, with taxa belonging to the Bacilli, Gammaproteobacteria, Betaproteobacteria, Actinobacteria, Bacteroidetes, and Clostridia. During storage at 4°C, the untreated system displayed a complex succession, with species of Weissella and Leuconostoc that dominate the product at day 0 being displaced by species of Pseudomonas (P. lini and P. psychrophila) within 15 days. By day 30, a second wave of taxa (Lactobacillus graminis, Carnobacterium divergens, Buttiauxella brennerae, Yersinia mollaretti, and a taxon of Serratia) dominated the population, and this succession coincided with significant chemical changes in the matrix. Treatment with lactate-diacetate altered the dynamics dramatically, yielding a monophasic growth curve of a single species of Lactobacillus (L. graminis), followed by a uniform selective die-off of the majority of species in the population. Of the six species of Lactobacillus that were routinely detected, L. graminis became the dominant member in all samples, and its origins were traced to the spice blend used in the formulation

Microbial Successions Are Associated with Changes in Chemical Profiles of a Model Refrigerated Fresh Pork Sausage during an 80-Day Shelf Life Study

Fresh pork sausage is produced without a microbial kill step and therefore chilled or frozen to control microbial growth. In this report, the microbiota in a chilled fresh pork sausage model produced with or without an antimicrobial combination of sodium lactate and sodium diacetate was studied using a combination of traditional microbiological methods and deep pyrosequencing of 16S rRNA gene amplicons. In the untreated system, microbial populations rose from 102 to 106 CFU/g within 15 days of storage at 4°C, peaking at nearly 108 CFU/g by day 30. Pyrosequencing revealed a complex community at day 0, with taxa belonging to the Bacilli, Gammaproteobacteria, Betaproteobacteria, Actinobacteria, Bacteroidetes, and Clostridia. During storage at 4°C, the untreated system displayed a complex succession, with species of Weissella and Leuconostoc that dominate the product at day 0 being displaced by species of Pseudomonas (P. lini and P. psychrophila) within 15 days. By day 30, a second wave of taxa (Lactobacillus graminis, Carnobacterium divergens, Buttiauxella brennerae, Yersinia mollaretti, and a taxon of Serratia) dominated the population, and this succession coincided with significant chemical changes in the matrix. Treatment with lactate-diacetate altered the dynamics dramatically, yielding a monophasic growth curve of a single species of Lactobacillus (L. graminis), followed by a uniform selective die-off of the majority of species in the population. Of the six species of Lactobacillus that were routinely detected, L. graminis became the dominant member in all samples, and its origins were traced to the spice blend used in the formulation

Push and Pull Policy in Market-Driven Management

Push and pull policies identify the different logics that underpin the relationship between a business and its final demand. Push policy refers to the development of processes that emanate from the company and go towards the market, while pull policy refers to processes that start from the market and go towards the company. Push and pull policies identify processes regarding project, production and distribution activities but also communication flows. This two policies differ for costs, and for their ability to adapt to the various competitive dynamics. In global dynamic markets, in over supply conditions, push and pull policies can be integrated to maximize the advantages of scale and the competitiveness of fast and personalized market reactions