Instrumentation of a high-sensitivity microwave vector detection system for low-temperature applications

We present the design and the circuit details of a high-sensitivity microwave vector detection system, which is aiming for studying the low-dimensional electron system embedded in the slots of a coplanar waveguide at low temperatures. The coplanar waveguide sample is placed inside a phase-locked loop; the phase change of the sample may cause a corresponding change in the operation frequency, which can be measured precisely. We also employ a double-pulse modulation on the microwave signals, which comprises a fast pulse modulation for gated averaging and a slow pulse modulation for lock-in detection. In measurements on real samples at low temperatures, this system provides much better resolutions in both amplitude and phase than most of the conventional vector analyzers at power levels below -65 dBm.Comment: 7 pages, 11 figures, 1 table, lette

Spontaneous Interlayer Charge Transfer near the Magnetic Quantum Limit

Experiments reveal that a confined electron system with two equally-populated layers at zero magnetic field can spontaneously break this symmetry through an interlayer charge transfer near the magnetic quantum limit. New fractional quantum Hall states at unusual total filling factors such as \nu = 11/15 (= 1/3 + 2/5) stabilize as signatures that the system deforms itself, at substantial electrostatic energy cost, in order to gain crucial correlation energy by "locking in" separate incompressible liquid phases at unequal fillings in the two layers (e.g., layered 1/3 and 2/5 states in the case of \nu = 11/15).Comment: 4 pages, 4 figures (1 color) included in text. Related papers at http://www.ee.princeton.edu/~hari/papers.htm

Switchable Lightweight Anti-symmetric Processing (SLAP) with CNN Outspeeds Data Augmentation by Smaller Sample -- Application in Gomoku Reinforcement Learning

To replace data augmentation, this paper proposed a method called SLAP to intensify experience to speed up machine learning and reduce the sample size. SLAP is a model-independent protocol/function to produce the same output given different transformation variants. SLAP improved the convergence speed of convolutional neural network learning by 83% in the experiments with Gomoku game states, with only one eighth of the sample size compared with data augmentation. In reinforcement learning for Gomoku, using AlphaGo Zero/AlphaZero algorithm with data augmentation as baseline, SLAP reduced the number of training samples by a factor of 8 and achieved similar winning rate against the same evaluator, but it was not yet evident that it could speed up reinforcement learning. The benefits should at least apply to domains that are invariant to symmetry or certain transformations. As future work, SLAP may aid more explainable learning and transfer learning for domains that are not invariant to symmetry, as a small step towards artificial general intelligence.Comment: Change title; 6 pages, 8 figure

Magnetic-Field-Induced Hybridization of Electron Subbands in a Coupled Double Quantum Well

We employ a magnetocapacitance technique to study the spectrum of the soft two-subband (or double-layer) electron system in a parabolic quantum well with a narrow tunnel barrier in the centre. In this system unbalanced by gate depletion, at temperatures T\agt 30 mK we observe two sets of quantum oscillations: one originates from the upper electron subband in the closer-to-the-gate part of the well and the other indicates the existence of common gaps in the spectrum at integer fillings. For the lowest filling factors $\nu=1$ and $\nu=2$, both the common gap presence down to the point of one- to two-subband transition and their non-trivial magnetic field dependences point to magnetic-field-induced hybridization of electron subbands.Comment: Major changes, added one more figure, the latest version to be published in JETP Let

Extrinsic Curvature Embedding Diagrams

Embedding diagrams have been used extensively to visualize the properties of curved space in Relativity. We introduce a new kind of embedding diagram based on the {\it extrinsic} curvature (instead of the intrinsic curvature). Such an extrinsic curvature embedding diagram, when used together with the usual kind of intrinsic curvature embedding diagram, carries the information of how a surface is {\it embedded} in the higher dimensional curved space. Simple examples are given to illustrate the idea.Comment: 22 pages, 4 figure