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one microwave line for X/Y-rotations, and one readout line to detect the switching of the squid. These lines get driven by several GHz DAC boards and one microwave source. The GHz DAC boards connect to a computer via ethernet and the microwave source uses a GPIB connection. Furthermore, the squid readout pre-amplifier gets configured via a serial link. These three hardware interfaces – GPIB, ethernet, and RS-232 – are exposed to the LabRAD system via one dedicated Server Module each – the GPIB Server, the Direct Ethernet Server, and the Serial Server. Above these sits a set of device Servers that each implement the communication protocol of one device type to provide higher level functions like “Set the output of the microwave source to 7 GHz at 2.7dBm”. The next level in the stack – the Qubit and DAC Calibration Servers – abstract the exact hardware configuration by allowing the user to, for example, load a sequence of voltages into the “Squid Bias” channel on “Qubit 2” (rather than “FO 1” on “GHz DAC 17”). This data is then corrected for imperfections in the analog electronics chain and automatically sent to the right GHz DAC board. Up to this level the software does not impose any limits on the hardware control beyond preventing erroneous configurations. Until here, starting from the hardware/software interface, the first layers in the software abstraction stack closely mimic the first layers in the hardware stack. 154
The next layers correspond to the “applications” (i.e. the experiments) that are to be run on the quantum computer. For now, at the base of this stack is a collection of Experiment Servers that provide functions to take one data point of a specific experiment (Rabi, T1, Bell Violation, etc.). These Servers are called by the “Sweep Server” which varies one or more of the experimental parameters to generate n-D datasets. At the highest level in the stack sit several Client Modules that allow the user to edit parameters, run sweeps, and view the resulting data sets. Let’s go over the different Modules in detail starting from the Client end. 7.5.2 DC Rack Controller Starting with the right-most branch of the diagram in Figure 7.1, the DC Rack Controller consists of a LabVIEW VI that provides an interface to the user to set up the DC bias rack, which houses the FastBias and PreAmp cards. Apart from configuring diagnostic outputs, the most important feature is the ability to control the cutoff voltage that the PreAmp uses to detect the squid’s switch to the voltage state. The only function of the DC Rack Controller is to translate user interactions with switches and dials on the front panel to calls to the DC Rack Server that performs the actual updates. 155
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UNIVERSITY of CALIFORNIA Santa Barb
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Benchmarking the Superconducting Jo
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viii
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Curriculum Vitæ Markus Ansmann Edu
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99:187006 Lisenfeld, J., Lukashenko
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Abstract Benchmarking the Supercond
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Contents Contents List of Figures L
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4.1.3 Readout Squid Parameters . .
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7.5.5 Grapher . . . . . . . . . . .
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11.5 Analysis and Verification . .
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List of Figures 2.1 Inductor-Capaci
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List of Tables 3.1 Transition Matri
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Chapter 1 Quantum Computation 1.1 M
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for such problems include factoring
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if present encrypted data will rema
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In terms of quantum bits, this mean
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1.2.3 Implications - The EPR Parado
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proposed architecture of quantum bi
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“coherence times”, i.e. the tim
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Chapter 2 Superconducting Josephson
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of the glue-circuitry needed to con
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Figure 2.1: Inductor-Capacitor Osci
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• The circuit needs to be cooled
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Figure 2.2: Josephson Tunnel Juncti
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the trace along the V-axis, gives c
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Figure 2.4: Josephson Qubits: Sligh
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the cosine forms a local minimum al
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Figure 2.5: Example Qubit Coupling
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Readout schemes can further be cate
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states in the qubit’s inductor, t
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at time t. r is not restricted to b
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3.1.2 Effects of a Time Dependent P
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In some cases, it is possible to so
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Figure 3.1: Examples of Numerical S
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• The energy difference between t
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like this: V = ( V (−1, −1), V
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Figure 3.2: Simulation of LC Oscill
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Table 3.1: Transition Matrix Elemen
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with ω mn = Em−En . Multiplying
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α, it can be ignored. Thus, the in
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e solved exactly: A(t + ∆t) = e
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qubits would be simulated using: A(
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This calculation assumes that the s
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Decoherence consists of two parts:
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Note the difference in signs of the
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Chapter 4 Designing the Phase Qubit
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mutual inductance between the qubit
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During the measurement, the | 1 〉
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the right impedance transformation
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excitations. Since these are a pote
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Figure 4.3: Squid I/V Traces - a) L
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Figure 4.5: Qubit Integrated Circui
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The geometry of the qubit junction
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squid loop. Thus, this tool can be
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now, amorphous silicon seems to pro
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Figure 5.1: L-Edit Mask Layout Tool
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Figure 5.2: Fabrication Building Bl
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Figure 5.3: Photolithography and Et
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times the removal can be a bit tric
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Figure 5.4: Clearing Vias from Nati
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5.6 Junction Layers 5.6.1 Oxidation
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top wiring layer to protect all low
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Page 134 and 135: 6.1 Physical Quality Control during
Page 136 and 137: 6.1.3 Atomic Force Microscopy To re
Page 138 and 139: Figure 6.1: 4-Wire Measurement - a)
Page 140 and 141: 6.3 Quantum Measurements at 25 mK 6
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Page 144 and 145: Figure 6.2: Dilution Refrigerator W
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Page 148 and 149: 6.3.9 Anritsu Microwave Source The
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Page 152 and 153: ment, the scalability requirements,
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Page 156 and 157: 7.2.4 Performance Last, but certain
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Page 164 and 165: 7.3.4 Performance Addressing the Pe
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Page 168 and 169: Table 7.3: LabRAD Type Annotations
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Page 172 and 173: Architecture to manage network conn
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Page 180 and 181: Since the API guarantees that all R
Page 184 and 185: 7.5.3 DC Rack Server The DC Rack Se
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Page 194 and 195: efore the execution of the sequence
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Page 202 and 203: 8.1 Squid I/V Response As explained
Page 204 and 205: a digital signal via the use of a c
Page 206 and 207: energy landscape (see Chapter 2.2.3
Page 208 and 209: Figure 8.3: Squid Steps Failure Mod
Page 210 and 211: At this point, the squid ramp can b
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Page 214 and 215: Figure 8.5: General Bias Sequence -
Page 216 and 217: Figure 8.7: Spectroscopy - a) Bias
Page 218 and 219: Figure 8.8: Rabi Oscillation - a) B
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Page 222 and 223: Figure 8.10: T 1 - a) Bias sequence
Page 224 and 225: Figure 8.11: Ramsey - a) Bias seque
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Page 228 and 229: photon excitation behaves similarly
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sequence was run. This allows for t
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possible to read out all qubits cor
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simultaneous application of such me
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Figure 9.4: Capacitive Coupling Swa
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Figure 9.6: Capacitive Coupling Pha
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a phase difference of 0 ◦ rather
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Figure 9.7: Fine Spectroscopy of Re
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Figure 9.8: Swapping Photon into Re
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esonator. The latter calibration is
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Figure 9.11: Resonator T 1 - a) Seq
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224
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He does not throw dice” [Einstein
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(independent of which axis it is),
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of E xy is measured by expressing i
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For a measurement of two particles
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10.2.1 Photons The first and most n
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10.2.3 Ion and Photon In the attemp
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238
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11.1 State Preparation Since the ab
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Figure 11.1: Bell State Preparation
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Table 11.1: Entangled State Density
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Figure 11.2: Bell Measurements - a)
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11.2.3 Statistical Analysis For the
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11.3 Calibration The most difficult
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Table 11.4: Sequence Parameters - R
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ally determine an optimal value for
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ages are based on this method, incl
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equires to converge. Since the algo
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Table 11.7: Bell Violation Results
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Table 11.9: Error Budget - Capaciti
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Bell inequality. To make this claim
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11.5.2 Dependence of S on Sequence
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point where the measurement happens
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The second qubit is not driven and
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Figure 11.6: Resonator Coupled Samp
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From the resulting states, the 16 p
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Table 11.14: Error Budget - Resonat
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sponding to a violation by 244.0σ.
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educe energy decay and dephasing an
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John F. Clauser, Michael A. Horne,
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J. Majer, J. M. Chow, J. M. Gambett
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Matthias Steffen, M. Ansmann, Rados
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