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1.2 The Power of Quantum Computers The power of quantum computers roots in two revolutionary concepts that quantum mechanics introduced: Superpositions and Entanglement. 1.2.1 Superpositions According to quantum mechanics any system is described by a set of discrete states in which it can exist: the system’s “eigenstates”. It is possible for the system to exist in a superposition of these states, i.e. to be in multiple states at the same time. For example, a quantum bit can not only be in the 0 or 1 state, but it can be in both, 0 and 1, at the same time. To describe the full state of a quantum system, each eigenstate is given a complex amplitude that describes its weight, called the “probability amplitude”. A measurement of the system will then force it to “choose” between one of its eigenstates (in the basis of the measurement). The probability for each eigenstate to be chosen is given by the square of its probability amplitude. After the measurement, the system’s state “collapses” to the chosen eigenstate, i.e. the chosen eigenstate’s probability amplitude becomes 1, while all others go to 0. Since measurements always yield an answer, the square of the probability amplitudes for all states needs to sum to 1, i.e. one of the states has to be chosen. 6
In terms of quantum bits, this means that a quantum computer can not only use the two states of the bit (0 and 1) to do binary calculations, but can instead use the complex probability amplitude of the 1 state, which provides two analog values (the relative phase and amplitude of the 0 and 1 state) for calculations. This concept is discussed further in Chapter 3.3.1. 1.2.2 Entanglement Superpositions of single qubits alone do not provide a significant advantage, though, since they can be efficiently simulated by a classical computer by using a collection of classical bits to store the probability amplitudes. The true “magic” happens when several quantum systems are allowed to interact. According to quantum mechanics, the state of a collection of interacting quantum systems can no longer be described as a collection of the states of the individual systems, but instead needs to be described in terms of a new set of states that consists of all possible combinations of the individual states. For example, for three quantum bits, the combined system is not described in terms of the three qubits’ individual states that each are 0 or 1, but instead by the eight new states 000, 001, 010, 011, 100, 101, 110, and 111. In general, a system consisting of n interacting quantum bits needs to be described in terms of 2 n quantum states. A quantum computer can then be in a superposition of these 2 n 7
Page 1: UNIVERSITY of CALIFORNIA Santa Barb
Page 5: Benchmarking the Superconducting Jo
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Page 11 and 12: Curriculum Vitæ Markus Ansmann Edu
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Page 15 and 16: Abstract Benchmarking the Supercond
Page 17 and 18: Contents Contents List of Figures L
Page 19 and 20: 4.1.3 Readout Squid Parameters . .
Page 21 and 22: 7.5.5 Grapher . . . . . . . . . . .
Page 23 and 24: 11.5 Analysis and Verification . .
Page 25 and 26: List of Figures 2.1 Inductor-Capaci
Page 27 and 28: List of Tables 3.1 Transition Matri
Page 29 and 30: Chapter 1 Quantum Computation 1.1 M
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Page 33: if present encrypted data will rema
Page 37 and 38: 1.2.3 Implications - The EPR Parado
Page 39 and 40: proposed architecture of quantum bi
Page 41 and 42: “coherence times”, i.e. the tim
Page 43 and 44: Chapter 2 Superconducting Josephson
Page 45 and 46: of the glue-circuitry needed to con
Page 47 and 48: Figure 2.1: Inductor-Capacitor Osci
Page 49 and 50: • The circuit needs to be cooled
Page 51 and 52: Figure 2.2: Josephson Tunnel Juncti
Page 53 and 54: the trace along the V-axis, gives c
Page 55 and 56: Figure 2.4: Josephson Qubits: Sligh
Page 57 and 58: the cosine forms a local minimum al
Page 59 and 60: Figure 2.5: Example Qubit Coupling
Page 61 and 62: Readout schemes can further be cate
Page 63: states in the qubit’s inductor, t
Page 66 and 67: at time t. r is not restricted to b
Page 68 and 69: 3.1.2 Effects of a Time Dependent P
Page 70 and 71: In some cases, it is possible to so
Page 72 and 73: Figure 3.1: Examples of Numerical S
Page 74 and 75: • The energy difference between t
Page 76 and 77: like this: V = ( V (−1, −1), V
Page 78 and 79: Figure 3.2: Simulation of LC Oscill
Page 80 and 81: Table 3.1: Transition Matrix Elemen
Page 82 and 83: 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)
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6.3 Quantum Measurements at 25 mK 6
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seems to be a box machined out of s
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Figure 6.2: Dilution Refrigerator W
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cessing data. This protects the vol
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6.3.9 Anritsu Microwave Source The
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122
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ment, the scalability requirements,
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people without any formal training
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7.2.4 Performance Last, but certain
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or a Client Module. Client Modules
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second Module talks to all these an
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puters to talk to each other. Usual
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7.3.4 Performance Addressing the Pe
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is designed such that the LabRAD Ma
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Table 7.3: LabRAD Type Annotations
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listed in Table 7.3. For transmissi
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Architecture to manage network conn
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Manager. In fact, in our lab, the o
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waiting for their completion. The C
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mentation of pipelining and certain
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Since the API guarantees that all R
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one microwave line for X/Y-rotation
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7.5.3 DC Rack Server The DC Rack Se
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data taking on the lab servers and
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keys and the ability to set Context
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a certain time. 7.5.9 Optimizer Cli
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ters read from different sub-direct
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efore the execution of the sequence
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can achieve very-close-to hardware
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type to provide a one-stop location
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172
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8.1 Squid I/V Response As explained
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a digital signal via the use of a c
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energy landscape (see Chapter 2.2.3
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Figure 8.3: Squid Steps Failure Mod
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At this point, the squid ramp can b
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starts to tunnel to the neighboring
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Figure 8.5: General Bias Sequence -
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Figure 8.7: Spectroscopy - a) Bias
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Figure 8.8: Rabi Oscillation - a) B
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ensemble with respect to each other
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Figure 8.10: T 1 - a) Bias sequence
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Figure 8.11: Ramsey - a) Bias seque
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phase shift into the middle of the
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photon excitation behaves similarly
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is desirable to modularize the cont
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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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