9 research outputs found
The Aharonov-Bohm effect in mesoscopic Bose-Einstein condensates
Ultra-cold atoms in light-shaped potentials open up new ways to explore
mesoscopic physics: Arbitrary trapping potentials can be engineered with only a
change of the laser field. Here, we propose using ultracold atoms in
light-shaped potentials to feasibly realize a cold atom device to study one of
the fundamental problems of mesoscopic physics, the Aharonov-Bohm effect: The
interaction of particles with a magnetic field when traveling in a closed loop.
Surprisingly, we find that the Aharonov-Bohm effect is washed out for
interacting bosons, while it is present for fermions. We show that our atomic
device has possible applications as quantum simulator, Mach-Zehnder
interferometer and for tests of quantum foundation.Comment: 5 pages, 5 figures to be published in Physical Review A Rapid
Communication
Synchronization of a Self-Sustained Cold Atom Oscillator
Nonlinear oscillations and synchronisation phenomena are ubiquitous in
nature. We study the synchronization of self oscillating magneto-optically
trapped cold atoms to a weak external driving. The oscillations arise from a
dynamical instability due the competition between the screened magneto-optical
trapping force and the inter-atomic repulsion due to multiple scattering of
light. A weak modulation of the trapping force allows the oscillations of the
cloud to synchronize to the driving. The synchronization frequency range
increases with the forcing amplitude. The corresponding Arnold tongue is
experimentally measured and compared to theoretical predictions. Phase-locking
between the oscillator and drive is also observed.Comment: Corrected typo
Benchmarking Digital-Analog Quantum Computation
Digital-Analog Quantum Computation (DAQC) has recently been proposed as an
alternative to the standard paradigm of digital quantum computation. DAQC
creates entanglement through a continuous or analog evolution of the whole
device, rather than by applying two-qubit gates. This manuscript describes an
in-depth analysis of DAQC by extending its implementation to arbitrary
connectivities and by performing the first systematic study of its scaling
properties. We specify the analysis for three examples of quantum algorithms,
showing that except for a few specific cases, DAQC is in fact disadvantageous
with respect to the digital case.Comment: 16+5 pages, 11 figure
Co-Design quantum simulation of nanoscale NMR
Quantum computers have the potential to efficiently simulate the dynamics of nanoscale NMR systems. In this work, we demonstrate that a noisy intermediate-scale quantum computer can be used to simulate and predict nanoscale NMR resonances. In order to minimize the required gate fidelities, we propose a superconducting application-specific Co-Design quantum processor that reduces the number of SWAP gates by over 90% for chips with more than 20 qubits. The processor consists of transmon qubits capacitively coupled via tunable couplers to a central co-planar waveguide resonator with a quantum circuit refrigerator (QCR) for fast resonator reset. The QCR implements the nonunitary quantum operations required to simulate nuclear hyperpolarization scenarios.The authors would like to thank Caspar Ockeloen-Korppi,
Alessandro Landra, and Johannes Heinsoo for their help in de-
veloping the idea of the star-architecture chip, Jani Tuorila for
his support in developing the gate theory, Amin Hosseinkhani
and Tianhan Liu for reviewing the manuscript, and Hen-
rikki Mäkynen and Hoang-Mai Nguyen for graphic design.
J.C. additionally acknowledges the Ramón y Cajal program
(RYC2018-025197-I). We further acknowledge support from
Atos with the Quantum Learning Machine (QLM). Finally,
the authors acknowledge financial support to BMBF through
the Q-Exa Project No. FZK: 13N16062
How market structure drives commodity prices
We introduce an agent-based model, in which agents set their prices to maximize profit. At steady state the market self-organizes into three groups: excess producers, consumers and balanced agents, with prices determined by their own resource level and a couple of macroscopic parameters that emerge naturally from the analysis, akin to mean-field parameters in statistical mechanics. When resources are scarce prices rise sharply below a turning point that marks the disappearance of excess producers. To compare the model with real empirical data, we study the relationship between commodity prices and stock-to-use ratios in a range of commodities such as agricultural products and metals. By introducing an elasticity parameter to mitigate noise and long-term changes in commodities data, we confirm the trend of rising prices, provide evidence for turning points, and indicate yield points for less essential commodities
Noisy intermediate-scale quantum algorithms
A universal fault-tolerant quantum computer that can efficiently solve problems such as integer factorization and unstructured database search requires millions of qubits with low error rates and long coherence times. While the experimental advancement toward realizing such devices will potentially take decades of research, noisy intermediate-scale quantum (NISQ) computers already exist. These computers are composed of hundreds of noisy qubits, i.e., qubits that are not error corrected, and therefore perform imperfect operations within a limited coherence time. In the search for achieving quantum advantage with these devices, algorithms have been proposed for applications in various disciplines spanning physics, machine learning, quantum chemistry, and combinatorial optimization. The overarching goal of such algorithms is to leverage the limited available resources to perform classically challenging tasks. In this review, a thorough summary of NISQ computational paradigms and algorithms is provided. The key structure of these algorithms and their limitations and advantages are discussed. A comprehensive overview of various benchmarking and software tools useful for programming and testing NISQ devices is additionally provided