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Tuesday. August E", ZOO2 IEEE-NAN0 2002 T A 5 Duantum mmDUtirYl Nanotechnology - Quantum Information Theory - and Quantum Computing Sergey Edward Lyshevski Department of Electrical Engineering Rochester Institute of Technology Rochester, NY 14623-5603 Abslracl- Significant progress has been made in various applications of nanotechnology, and much efforts have been concentrated on the theory of nanocomputers. There are the need to examine nanocomputer architectures which include the following major components: the arithmetic-logic unit, the memory unit, the inputloutput unit, and the control unit. The recent results illustrate that novel logic and memory nanoscale integrated circuits can be fabricated and implemented. This progress ais primarily due to the application of nanotechnology. Fundamental and applied results researched in this paper further expand the horizon of nanocomputer theory and nanotechnology practice. It is illustrated that novel nanocomputer architectures and organizations must be discovered and examined to ensure the highest level of efficiency, flexibility and robustness. I. INTRODUCTION First-, second-, third-, and fourth- generations of computers emerged, and tremendous progress has been achieved. The [email protected]@4 (2.4 GHz) processor was built using advanced Intel' NetBurstm microarcbitecture. This processor ensures high-performance processing, and is fabricated using 0.13 micron technology. The processor is integrated with high-performance memory systems, e.g., 8KB L1 data cache, 12K clops L1 Execution Trace Cache, 256 KB L2 Advanced Transfer Cache and 512 KB Advance Transfer Cache. The fifth generation of computers will be built using emerging nanoICs. Currently, 50 nm technologu is emerged to fabricate high-yield high-performance ICs with billions of transistors on a single 1 cm2 die. Synthesis, integration and implementation of new affordable high-yield nanoICs are critical to meet Moore's first law. Figure 1 illustrates the first and second Moore laws. Despite of the fact that some data and foreseen trends can be viewed as controversial and subject to adjustments, the major trends and tendencies are obvious, and most likely cannot be seriously argued and disputed. 1990 2wO 2010 2020 YCU Figure 1. Moore's laws High-performance computers architectures, novel organizations, pipelining, parallel processing, ICs hardware miniaturization and software optimization have advanced for CMOS-based computers. However, the fundamental physical limits are reached [I-41. As an alternative to current computers and classical theory of computation, quantum computers were proposed in the 1970s by Richard Feyman, Paul Benioff and Charles Bennett [l]. Quantum computing ensures fast computation using interacting quantum states in atoms, molecules or photons (in conventional computers, transistors switch due to the electron flow). To simulate a state vector in a 2"dimensional Hilbert space, classical computers manipulate vectors containing of order 2" complex numbers, whereas a quantum computer requires n qubits reducing memory requirements. Tremendous challenges are needed to be overcome, however, significant fundamental and experimental progress has been made [5,6]. For example, an IBM quantum complex which contains seven programmed (magnetic field) and detected (nuclear magnetic resonance) qubits (five fluorine and two carbon13 atoms) was researched. The dicarbonylcyclopentadienyl iron molecule CllHSF5OzFe forms a seven qubits complex. This complex can be used to form quantum logic gates. This paper describes the method for implementing the quantum logic gates to perform quantum computing. Due to a variety of unsolved problems in quantum computing, another viable paradigm in design of nanocomputers is introduced. In particular, this paper focuses on threedimensional computer architectures using nanoICs made using nanotechnology. We study the application of nanoscale devices and examine different computer architectures. The elementary quantum logic gates are I = lO)(Ol ')(I1 (identity) +I and N=10)(1(+/1)(01(NOT) This paper formulates and solves some long-standing fundamental and applied problems in design, analysis, and optimization of nanocomputers. The fundamentals of nanocomputer architectronics are reported, and the basic organizations and topologies are examined progressing from the general system-level consideration to the nanocomputer subsystem/unit/device-level study. NanoICs are examined using nanoscale field-effect transistors (NFET). In contrast to the classical information theory (only two logic gates result for a single bit, e.g., identity and NOT), there are an infmite number of single-qubit quantum gates (e.g., A = ( O ) + \ l ) ~ l+(io) I -1l)~OI) due to the quantum superposition. The possible unitary operators for a pair of qubits are expressed as lo)(ol @I+Il)([email protected] U , where I and U are the single-qubit identity and controlled gate. 11. QUANTUM COMPUTING Logical operations require multiple qubits. Two-qubit gate is Consider quantum logic gates which perform elementary quantum operations. The state of an isolated system is represented by a vector I (1)) in the Hilbert space. The position and momentum Hermitian operators X and P in the X-eigenbasis have the following matrix elements ] x') .1 (x The universal quantum gate and any unitary nxn matrix can be formed using a controlled-NOT (XOR) gate and a general single-bit gate = x6(x-x') 1 and (x P I X ' ) = - i A G ' ( x - x ' ) . The Schrodinger equation is d if"-$ ( t ) )= (O), Using the conditional S(Y1X) and mutual A'(X;Y)=S(+S(YlX) entropies, we have if X+Y+Z then S(X,z)SS(X,Y)This . is the data processing inequality. The channel capacity Cis found to be where H i s the quantum Hamiltonian operator. The Hadamard-type gate in the computational basis ao)3lo)l and C = max S ( X ; Y ) . IP(N is the schematically representation I x ) + [ ~ ] ~ ( - l ) " l x ) + l l - x ) forthestate Ix) with&, Let a qubit evolves as lO)+lo) The transient dynamics is studied. It was illustrated that the initial and final states are related by phase angles, is 1. e.g., eie and e'' . I (t)) = e!(')l-( I ) ) such that the phase change of the initial state I (0)) is given as For the state, we have and ll)+eimll). Then, the phase quantum logic gate is 0 = f ( r )- f(0) ' 310 IEEE-NAN0 ZOO2 Tuesday. August 27. 2002 TA!% Ouantum mmputing H = H , + 2nhJS, C 3S, , The evolution of the quantum system is given as and the energy level can be examined Though the quantum computing theory straightforwardly formulated, formidable challenges to implement quantum computing remain. Therefore, we concentrate our attention on other feasible direction. In particular, devising nanocomputers using nanoICs fabricated utilizing nanotechnology advantages. Thus, 6' is a function of the Hamiltonian and state changes, e.g., I( I B = -1 ' (t)l H (t))dt+ i ] ( ( t ) l $ I-(t))dt. h, 0 III. NANOCOMPUTER ARCHITECTURE AND NANACOMPUTERARCHITECTRONICS A single qubit density matrix is parameterized as p =+(I + s . 0 )= + s,l+s, +is, where s is the Bloch vector, Using the Rabi vector = 1"l sy s, --Isy The critical problems in the design of nanocomputers are focused on devising, designing, analyzing, optimizing and fully utilizing hardware and software. The current ICs are very large scale integration circuits (VLSI). Though 90 nm fabrication technologies have been developed and implemented by the leading computer manufacturers (Dell, IBM, Intel, Hewlett-Packard, Motorola, Sun Microsystems, Texas Instruments, etc.), and billions of transistors can be placed on a single multilayered die, the VLSI technology approaches the physical limits. 1-s, . J 1s. we have a, H=+A(Q,I+Q.cT). Thus, Alternative affordable, high-yield and robust technologies are sought, and nanotechnology promises further far-reaching revolutionary progress. It is envisioned that nanotechnology will lead to threedimensional nanocomputers with novel computer architectures to attain the superior overall performance level. Compared with the existing most advanced computers, in nanocomputers the execution time, switching frequency and size will be decreased by the order of millions, while the memory capacity will be increased by the order of millions. However, significant challenges must be overcome. Many difficult problems such as 1. novel nanocomputer architectures, 2. advanced organizations and topologies, 3. high-fidelity modeling, 4. data-intensive analysis, 5 . heterogeneous simulations, 6. optimization, 7. control, adaptation and reconfiguration, 8. self-organization, 9. robustness, IO. utilization, as well as other problems must be addressed, researched and solved. Many of the above mentioned problems have not been even addressed yet. iA-dP = [ H , p ] , dt and ds - = dt ~ x s . The Hamiltonian is exuressed as The two-spin Hamiltonian with two noninteractive half-spin particles S, and S, is Hu = AoJ, @Ib+AobIa @Sbz. H, =fh l 0 o,-oa 0 o 0 -o,+oa O 0 I For interactive system, 311 A nanocomputer architecture integrates the following major systems: input - output, memory, arithmetic and logic, and control units. The input unit accepts information from electronic devices or other computers through the cards (electromechanical devices, such as keyboards, can he also interfaced). The information received can be stored in the memory, and then, manipulated and processed by the arithmetic and logic unit (ALU). The results are output using the output unit. Information flow, propagation, manipulation, processing, and storage are coordinated by the control unit. The arithmetic and logic unit, integrated with control unit, is called the processor or central processing unit (CPU). Input and output systems are called the input-output unit (U0 unit). The memory unit, which integrates memory systems, stores programs and data. Figure 2. Nanocomputer organization There are two main classes of memory calledprimary (main) and secondary memory. In nanocomputers, the primary memory is implemented using nanoICs that can consist of billions of nanoscale storage cells (each cell can store one bit of information). These cells are accessed in groups of fixed size called words. The main memory is organized such that the contents of one word can be stored or rehieved in one hasic operation called a memory cycle. To provide a consistent direct access to any word in the main memory in the shortest time, a distinct address number is associated with each word location. IV. NANOCOMPUTERS AND NANOICS PERFORMANCE Current computers constantly irreversibly erase temporary results, and thus, the entropy changes. The average instruction execution speed (in millions of instructions executed per second Ips) and cycles per instruction are related to the time required to execute instructions as given by NanoICs can he effectively used to implement the additional memory systems to store programs and data forming secondary memory. Ti*s,=lK.lnck, where the clock frequencyf,,oct depends mainly on the ICs or nanoICs used and the fabrication technologies applied. The execution of most operations is performed by the ALU. In the ALU, the logic nanogates and nanoregisters used to perform the hasic operations (addition, subtraction, multiplication, and division) of numeric operands, and the comparison, shifting, and alignment operations of general forms of numeric and nonnumeric data. The processors contain a number of high-speed registers. which are used for temporruy storage of operands. Register, as a storage device for words, is a key sequential component, and registers are connected. Each register contains one word of data and its access time at least 10 times faster than the main memory access time. A register-level system consists of a set of registers connected by combinational data-processing and data-processing nanoICs. Tbe quantum mechanics implies an upper limit on the frequency at which the system can switch from one state to another. This limit is found as the difference between the total energy E of the system and ground state energy EO,e.g., 4 f , 2 -(E - E o ) , h .. where h is the Planck constant, h=6.626~10"~J-sec or J/HZ. An isolated nanodevice, consisting of a single electron at a potential of IV above its ground state, contains 1 eV of energy (leV=1.602~10-~~ J) and, therefore, cannot change its state faster than Figure 2 illustrates the possible nanocomputer organization, and, in general, three-dimensional nanocomuputer architectronics must he examined using the major units reported. f , <[email protected] 4 h 312 )U 1 . 6 0 2 ~ 1 0 -=' ~I X I O ' ~ Hz. -6.626~10~" In general, nanoICs ensure high density, superior bandwidth, high switching frequency, low power, et cetera [7-lo]. It is envisioned that in the near future nanocomputers will allow one to increase the computing speed by a factor of millions compared with the existing CMOS. Three-dimensional multiple-layered high-density nanoIC assemblies, shown in Figure 3, are envisioned to be used Hence, the switching frequency is 1 ~ 1 0 ' Hz. ~ Correspondingly, the switching frequency of nanoICs can be significantly increased compared with 'the currently used CMOS ICs. In asymptotically reversible nanocomputers, the generated entropy is S=b/f, where b is the entropy coefficient ( b varies from 1x10' to 1x106 hits/GHz for ICs, and from 1 to IO bitslGHz for quantum FETs): f is the length of time over which the operation is performed. Correspondingly, the minimum entropy and processing (operation) rate for quantum devices are S=l biWoperation and r,=lx1026 operation/sec-cm2, while CMOS technology allows one to achieve S=1x106 bitsloperation and re=3.5x10l6operation/sec-cm2. Using the number of instructions executed (N), the number of cycles per instruction C (), and the clock frequency (h,,~), the program execution time is Figure 3. Three-dimensional multiple-layered highdensity nanoIC assemblies (crossbar switching, logic or memory arrays), 3nm wide parallel (six-atomwide) erbium disilicide (Er&) nanowires (HewlettPickard [7, IO]), and carbon nanotube array In general, the hardware defines the clock frequency j & ~ ,the software influences the number of instructions executed N, while the nanocomputer architecture defines the number of cycles per instruction Cpl. One of the major performance characteristic for computer systems is the time that takes to execute a program. Suppose A',,,,,is the number of the machine instructions needed to be executed. A program is written in high-level language, translated by compiler into machine language, and stored. An operating system software routine loads the machine language program into the main memory for execution. Assume that each machine language instruction requires Ns,epbasic steps for execution. If basic steps are executed at the constant rate of Rr [stepslsec], then, the time to execute the program is V. NANOICS In addition to molecular wires [7, 10, 111 and molecular electronics [8], different nanodevices (switches, logics, memories, etc.) can be implemented using the illustrated in Figure 3 three-dimensional nanoelectronics arrays. It must be emphasized that the extremely higbfrequency logic gates can he fabricated using carbon nanotubes, which are from 1 to 10 nm in diameter. P- and n-type carbon nanotube field-effect transistors (CNFETs) with single- and multi-wall carbon nanotubes as the channel were fabricated and tested [12-141. The atomic force microscope image of a single-wall CNFET (50 nm total length) and CNFET are documented in Figure 4.a. Carbon nanotube strnchue can be utilized to devise and built different transistors with distinct characteristics utilizing different phenomena [12-141. For example, twisted carbon nanotubes can be used. Carbon nanotubes can be grown on the surface using chemical vapor deposition, deposited on the surface from solvent, etc. The main goal is to minimize T,. Optimal memory and processor design allows one to achieve this goal. The access to operands in processor registers is significantly faster than access to the main memory. The application of different memory systems results in a memory hierarchy concept. 313 T u d a y . August 27. ZOO? TA5: Ouantum computing IEEE-NAN0 2002 Photolithography can be used to attain the devicelevel structural and functional integration connecting source, drain, gate, etc. One concludes that different transistors topologies and configurations are available, and these results are reported in 112-143. Taking note of this fact, we use NFET to synthesize and analyze the nanoICs. REFERENCES 1. 2. The carbon nanotube inverter, formed using the series combination of p - and n-CNFETs, is illustrated in Figure 4.b. The gates and drains of two CNFETs are connected together to form the input and output. The voltage characteristics can be examined studying the various transistor bias regions. When the inverter input voltage Vjn is either a logic 0 or a logic 1, the current in the circuit is zero because one of the CNFETs is cut off. When the input voltage vary in the region Yhrechold <K a < - 1 Yhmshdd 1, 3. 4. 5. 6. CNFETs are 7. conducting and a current exists in the inverter. Carbon nanotube FET I 8. . 9. IO 11 -- -SiOi Si samao a-* Gate Silicon I2 (a) Inverter with n- andp-CNFETs 13 14 15 16 Vd. @) Figure 4. (a) Carbon nanotube FETs; @) inverter with CNFETs 17 The recent results reported in 115-171 allow one to conclude that high-yield, affordable and high-performance nanoelectronics will be implemented in nanocomputers 314 E. K. Drexler, Nanosystems: Molecular Machinery, Manufacturing, and Computations, Wiley-Interscience, New York, 1992. M. P. Frank and T. F. Kingght, “Ultimate theoretical models of nanocomputers,” Nanotechnology, vol. 9, no. 3, pp. 162-176,1998. S. E. Lyshevski, WMS and NEM5: System, Devices, and Smcmres, CRC Press, Boca Raton, FL, 2002. S. E. Lyshevski, Nanocomputers and Nanoachifechonics, Handbook of Nanoscience, Enginewing and Technology, Ed. W. Goddard, D. Brenner, S. Lyshevski and G. Iahte, CRC Press, Boca Raton, FL, 2002. M. Mosca, R. Jozsa, A. Steane and A. Ekert, “Quantumenhanced information processing,”Tram. R. Soc., vol. A 358, pp. 261-279,2000. A. Steane and E. Reiffel, “Beyond bits: The Future of Quantum Information Processing,” Computer, vol. 33, no. 1, pp. 3845,2000. Y. Chen, D. A. A. Ohlberg, G. Medeiros-Ribeiro, Y. A. Chang and R. S. Williams, “Self-assembled growth of epitaxial erbium disilicide nanowires on silicon (001): Appl. Phys. Lett., vol. 76, pp. 4004-4006,2000. J. C. Ellenhogen and J. C. Love, “Architechlres for molecular electronic computers: Logic structures and an adder designed !?om molecular electronic diodes,” Proc. IEEE, vol. 88, no. 3, pp. 386-426,2000. T.I. Kamins and D.P. Basile, “Interaction of self-assembled Ge islands and adjacent Si layers grown on unpanemed and panemed Si (001) substrates,”J. Electronic Materials, vol. 29, pp. 570-575,2000, T. I. Kamins, R. S. Williams, D. P. Basile, T. Hesjedal and J. S. Hams, “Ti-catalyzedSi nanowires by chemical vapor deposition: Microscopy and growth mechanism,” J. Appl. Phys., vol. 89,pp. 1008-1016,2001. W. T. Tian, S. Dam, S. Hong, R. Reifenherger, J. I. Henderson and C. P. Kubiak, “Conductance spectra of molecular wires,” Int. J. Chemical Physics, vol. 109, no. 7, pp. 2874-2882, 1998. V. Derycke, R. Ma&. J. Appenzeller and P. Avouris, “Carban nanotube inter- and inramolecular logic gates,” Nan0 Leners, 2001. R. Martel, H. S. P. Wong, K. Chan, and P. Avouris, “Carbon nanotuhe field effect transistors for logic applications,” Proc. Electron Devices Meeting, IEDM TechnicalDiges1,pp.7.5.1 -754,2001. R. Saito, G. Dresselhaus and M. S. Dresselhaus, Physical Properties of Carbon Nanohrbes, Imperial College Press, London, 1999. S. C. Goldstein, “Electronic nanotechnology and recontigurahle computing,” Proc. Computer Society Workshop on VLSI,pp. I O -15,2001. P. L. McEuen, J. Park, A. Bachtold, M. Woodside, M. S. Fuhrer, M. Bockrath, L. Shi, A. Majumdar and P. Kim, ‘Wanotuhe nanoelectronics,”Proc. Device Research Con$, pp. 107-110,2001. K. Tsukagoshia, A. Kanda, N. Yoneya, E. Watanabe, Y. Ootukah, and Y. Aoyagi, “Nano-electronics in a multiwall Microprocesses and carbon nanotube,” Proc. Nanotechnology Conf, pp. 280-281,2001.