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a certain time. 7.5.9 Optimizer Client / Server Along with the Sweep Client / Server that performs n-dimensional sweeps, we have also developed an Optimizer Client and Server that uses the exact same execution model to perform n-dimensional optimization of a desired experimental quantity using several different optimization algorithms: Nelder Mead Simplex, Particle Swarm, or SPSA. The calling convention of the “Run”-Setting that the Optimizer uses is identical to that of the Sweeper, such that any setting that can be used with the Sweeper can be used without modification by the Optimizer. The only requirement that the Optimizer adds is that the settings return the value (either by itself or as part of an array) that is to be optimized. The optimization can either be a minimization, maximization, or an attempt to get it as close as possible to a given number. The Optimizer runs until it is manually stopped and sends data to the Data Vault that shows its progress. 7.5.10 Experiment Servers Below the Sweep/Optimizer Server sits a collection of Servers that provide different “Run”-Settings for the different types of experiments needed. Apart from hardware changes, these Servers should be the only part of the LabRAD 162
system that needs to be changed in order to implement new experiments. Since all that these Servers need to do is to provide a Setting that takes a single data point with the parameters provided by the Registry, these Servers are usually extremely simple and concise. This allows for very high turn-around for new experiments. This is further assisted by the fact that these Servers do not even need to know what parameters in the Registry are being swept for a given data run. This commonly allows the Settings to be used for a variety of different types of experiments. As an example, consider a Setting that runs a sequence that consists of only a single microwave pulse on each qubit followed by a delayed measurement. Such a Setting can be used to measure Rabi oscillations as a function of pulse power and pulse length, T 1 decays as a function of the delay of the measurement pulse, multi-qubit swap operations, and even step-edges and s-curves by setting the pulse amplitude to 0 (these experiments are explained in Chapter 8). When running an experiment, the Sweep Client selects an experimental setup with the Qubit Server that defines the list of qubits that are to be used in the experiment as well as the hardware channels that are needed to control them. The Qubit Server provides a Setting (“Experiment Involved Qubits”) that allows the Experiment Servers to request the list of qubits that are part of the current setup. This way, the Experiment Servers can automatically loop over all involved qubits and run the desired sequence on all qubits with the different sequence parame- 163
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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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104
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6.1 Physical Quality Control during
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6.1.3 Atomic Force Microscopy To re
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Figure 6.1: 4-Wire Measurement - a)
Page 140 and 141: 6.3 Quantum Measurements at 25 mK 6
Page 142 and 143: seems to be a box machined out of s
Page 144 and 145: Figure 6.2: Dilution Refrigerator W
Page 146 and 147: cessing data. This protects the vol
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
Page 170 and 171: listed in Table 7.3. For transmissi
Page 172 and 173: Architecture to manage network conn
Page 174 and 175: Manager. In fact, in our lab, the o
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Page 180 and 181: Since the API guarantees that all R
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Page 184 and 185: 7.5.3 DC Rack Server The DC Rack Se
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Page 188 and 189: keys and the ability to set Context
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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
Page 212 and 213: starts to tunnel to the neighboring
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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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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