AWS- Quantum Compute Cloud – QC2

AWS- Quantum Compute Cloud – QC2

 

Amazon AWS pubblica l’ultimo prodotto, il Quantum Compute Cloud, o QC2 in breve.

E’ il primo computer quantistico pronto per andare in produzione. Possiamo usarlo per risolvere determinati tipi di problemi di matematica e logica con velocità mozzafiato.

I computer ordinari usano collezioni di bit per rappresentare i loro stati. Ogni bit è definitivamente 0 o 1, e il numero di stati possibili è 2n. 1 bit può essere in uno dei 2 stati, 2 bit possono essere in uno dei 4 stati, e così via.

I computer quantistici come l’QC2 utilizzano una rappresentazione più sofisticata dei dati nota come qubit o quantum bit. Ogni qubit esiste in tutti i suoi possibili stati contemporaneamente, ma la probabilità che un qubit può essere in uno degli stati può cambiare. I computer Quantici lavorano manipolando la distribuzione di probabilità di ogni stato.

 

Come si programma un computer quantistico? Con algoritmi quantistici, naturalmente. Quasi tutto quello che si sa circa la programmazione tradizionale diventa obsoleta quando si passa alla QC2. Bisogna pensare in termini di probabilità, le distribuzioni di probabilità, e così via. Date un’occhiata alle algoritmo di Shor per trovare i fattori primi ad avere una idea della potenza di un computer quantistico.

Stanno lavorando inoltre al supporto per il linguaggio QCL di Bernhard Omer. Vediamo le sue tesi sulla programmazione strutturata Quantica per saperne di più. Ecco un esempio di codice QCL:

 

Dopo aver lanciato un istanza QC2 e caricato il nostro algoritmo, si deve campionare l’output (noto anche come “collasso dello stato quantistico“) per recuperare la distribuzione di probabilità che rappresenta la giusta risposta. Potremo fare questa operazione più di una volta per problemi particolari al fine di aumentare la fiducia nella soluzione. Il collasso dello stato quantistico è un’operazione distruttiva (proprio come la lettura da una memoria a nuclei magnetici);  assicuriamoci di tenerne conto nel nostro algoritmo. In effetti, la risposta non esiste finché non viene richiesta.

Fino ad ora, il più grande computer quantistico conteneva meno di 8 qubit. AWS è riuscita a spingere questo valore fino alla 32 nella prima generazione di QC2. Questo ci permetterà di rappresentare i problemi con un massimo di 232 stati diversi.

Stanno lanciando il QC2 nei datacenter US East in più availability zones.

La versione di QC2 è beta limitata.

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9 Comments

  1. Fabio Cecaro 20 maggio 2010 at 14:07

    Una interessante news dalla Cina:

    Il concetto di teletrasporto quantico è un po’ differente dal teletrasporto tradizionale al quale Star Trek ci ha abituati: non si tratta di spostare da un punto A ad un punto B un oggetto o un fotone, ma si tratta di sfruttare una particolarità del fenomeno definito “entaglement”, che misteriosamente lega a distanza due oggetti, siano essi ioni o fotoni, senza alcuna apparente connesione.

    Fino ad ora, il teletrasporto quantico non era stato mai sperimentato su distanze medio-lunghe, rimanendo un esperimento confinato tra le mura di un laboratorio. Ma e di ieri la notizia che si è appena giunti ad una pietra miliare del teletrasporto quantico: il teletrasporto ad una distanza di 10 miglia, circa 16 km, effettuato dai ricercatori del Hefei National Laboratory for Physical Sciences, Cina.

    Cosa significa? Significa che siamo più vicino ad una nuova era delle telecomunicazioni, in cui non serviranno i canali ed i segnali tradizionali per trasportare informazioni da un punto all’altro della Terra, o addirittura dello spazio. Oltre ad aver effettuato un ulteriore passo avanti in prospettiva della realizzazione del cosidetto quantum computing.

    Il teletrasporto quantico di fotoni (o ioni) prevede di trasferire lo stato di un fotone ad un altro, distante da quello iniziale. Come “stato” possiamo immaginarsi “acceso” o “spento”, per semplificare le cose; quando il fotone A è in stato “acceso”, anche il fotone B, benchè separato nello spazio e non connesso attraverso alcun sistema tradizionale di comunicazione, cambia stato, coerentemente con quello del fotone di partenza.

    I fotoni legati attraverso uno stato quantico sono come connessi da un filo invisibile: quando uno cambia stato, anche l’altro cambia allo stesso modo, contemporaneamente. Einstein definì questo effetto come “una sinistra azione a distanza”.

    In passato era stato possibile sfruttare l’entaglement per connettere due o più fotoni, in modo tale che condividessero lo stesso stato a distanza. Si è sempre trattato tuttavia di distanze misurabili in metri, non in centinaia, ma in decine. A dire il vero, esperimenti di teletrasporto quantico per qualche centinaio di metri sono stati fatti in passato, ma sfruttando la fibra ottica come canale per evitare interferenze nello stato dei fotoni.

    In questo caso però, i fotoni sono stati “legati” attraverso un tunnel di 10 miglia privo di fibre ottiche, senza utilizzo di alcun medium fisico, e con una fedeltà dell’ 89%. Abbastanza per trasmettere informazioni, ma non sufficiente per le future applicazioni di crittografia, la trasmissione di dati, o per l’eventuale teletrasporto di qualcosa di più corposo di uno ione.

    Fonte: http://www.ditadifulmine.com/2010/05/teletrasporto-quantico-per-16.html

  2. Fabio Cecaro 20 gennaio 2012 at 12:26

    News dal mondo del quantum computing.
    Quantum mechanics enables perfectly secure cloud computing.
    Researchers have succeeded in combining the power of quantum computing with the security of quantum cryptography and have shown that perfectly secure cloud computing can be achieved using the principles of quantum mechanics. They have performed an experimental demonstration of quantum computation in which the input, the data processing, and the output remain unknown to the quantum computer. The international team of scientists will publish the results of the experiment, carried out at the Vienna Center for Quantum Science and Technology (VCQ) at the University of Vienna and the Institute for Quantum Optics and Quantum Information (IQOQI), in the forthcoming issue of Science.
    Quantum computers are expected to play an important role in future information processing since they can outperform classical computers at many tasks. Considering the challenges inherent in building quantum devices, it is conceivable that future quantum computing capabilities will exist only in a few specialized facilities around the world – much like today’s supercomputers. Users would then interact with those specialized facilities in order to outsource their quantum computations. The scenario follows the current trend of cloud computing: central remote servers are used to store and process data – everything is done in the “cloud.” The obvious challenge is to make globalized computing safe and ensure that users’ data stays private.

    The latest research, to appear in Science, reveals that quantum computers can provide an answer to that challenge. “Quantum physics solves one of the key challenges in distributed computing. It can preserve data privacy when users interact with remote computing centers,” says Stefanie Barz, lead author of the study. This newly established fundamental advantage of quantum computers enables the delegation of a quantum computation from a user who does not hold any quantum computational power to a quantum server, while guaranteeing that the user’s data remain perfectly private. The quantum server performs calculations, but has no means to find out what it is doing – a functionality not known to be achievable in the classical world.

    The scientists in the Vienna research group have demonstrated the concept of “blind quantum computing” in an experiment: they performed the first known quantum computation during which the user’s data stayed perfectly encrypted. The experimental demonstration uses photons, or “light particles” to encode the data. Photonic systems are well-suited to the task because quantum computation operations can be performed on them, and they can be transmitted over long distances.

    The process works in the following manner. The user prepares qubits – the fundamental units of quantum computers – in a state known only to himself and sends these qubits to the quantum computer. The quantum computer entangles the qubits according to a standard scheme. The actual computation is measurement-based: the processing of quantum information is implemented by simple measurements on qubits. The user tailors measurement instructions to the particular state of each qubit and sends them to the quantum server. Finally, the results of the computation are sent back to the user who can interpret and utilize the results of the computation. Even if the quantum computer or an eavesdropper tries to read the qubits, they gain no useful information, without knowing the initial state; they are “blind.”

    More information: “Demonstration of Blind Quantum Computing” Stefanie Barz, Elham Kashefi, Anne Broadbent, Joseph Fitzsimons, Anton Zeilinger, Philip Walther. DOI: 10.1126/science.1214707

    Provided by University of Vienna (news : web)

    Fonte
    http://www.physorg.com/news/2012-01-quantum-mechanics-enables-perfectly-cloud.html

  3. Fabio Cecaro 23 gennaio 2012 at 23:00

    Computer quantico nella nuvola? Riservatissimo

    Un team di ricercatori internazionale descrive un sistema in cui l’impiego dei computer quantici e dei server remoti permette di processare informazioni nella più assoluta segretezza
    Roma – Un team internazionale di ricercatori disseminati fra Vienna, Edimburgo, Singapore e Dublino ha messo alla prova un sistema di quantum computing che garantirebbe il massimo della privacy e della sicurezza nell’elaborare informazioni usando server remoti.

    Nella nuova ricerca internazionale il computer quantico incontra il cloud computing: il processing dei dati viene eseguito in remoto, su informazioni di cui il client (anch’esso quantico) non ha modo di sapere alcunché, né sull’input, né sulle operazioni eseguite, né sull’output finale.

    Il data processing quantico-remoto avviene insomma in una vera e propria “black box”, che nel caso dell’esperimento dei ricercatori funziona su principi ottici (fotoni): all’utente spetta preparare il qubit (l’unità di dati fondamentale nei computer quantici) iniziale in uno stato noto solo a lui, per inviarlo poi al quantum computer che fa l’entanglement secondo uno “schema standard”.

    Il tipo di calcoli previsti dal sistema è basato sulla semplice misurazione dello stato del qubit: l’utente stabilisce istruzioni precise per quale tipo di misurazione fare sui qubit e le invia al server remoto, che interpreta le istruzioni e le spedisce indietro per l’utente che può interpretarle e utilizzarle come preferisce.

    I ricercatori sostengono che in un simile sistema non è possibile intercettare le comunicazioni, perché senza conoscere lo stato iniziale del qubit non si potrebbe interpretare correttamente l’output proveniente dal server remoto.

    Fonte:
    http://punto-informatico.it/3406711/PI/News/computer-quantico-nella-nuvola-riservatissimo.aspx

  4. Fabio Cecaro 20 febbraio 2012 at 23:17

    NATURE NANOTECHNOLOGY | LETTER
    A single-atom transistor

    Martin Fuechsle, Jill A. Miwa, Suddhasatta Mahapatra, Hoon Ryu, Sunhee Lee, Oliver Warschkow, Lloyd C. L. Hollenberg, Gerhard Klimeck & Michelle Y. Simmons

    Nature Nanotechnology (2012)

    The ability to control matter at the atomic scale and build devices with atomic precision is central to nanotechnology. The scanning tunnelling microscope1 can manipulate individual atoms2 and molecules on surfaces, but the manipulation of silicon to make atomic-scale logic circuits has been hampered by the covalent nature of its bonds. Resist-based strategies have allowed the formation of atomic-scale structures on silicon surfaces3, but the fabrication of working devices—such as transistors with extremely short gate lengths4, spin-based quantum computers5, 6, 7, 8 and solitary dopant optoelectronic devices9—requires the ability to position individual atoms in a silicon crystal with atomic precision. Here, we use a combination of scanning tunnelling microscopy and hydrogen-resist lithography to demonstrate a single-atom transistor in which an individual phosphorus dopant atom has been deterministically placed within an epitaxial silicon device architecture with a spatial accuracy of one lattice site. The transistor operates at liquid helium temperatures, and millikelvin electron transport measurements confirm the presence of discrete quantum levels in the energy spectrum of the phosphorus atom. We find a charging energy that is close to the bulk value, previously only observed by optical spectroscopy10.

    Methods References Acknowledgements Author information
    Silicon technology is now approaching a scale at which both the number and location of individual dopant atoms within a device will determine its characteristics11, and the variability in device performance caused by the statistical nature of dopant placement12 is expected to impose a limit on scaling before the physical limits associated with lithography and quantum effects13 are reached. Controlling the precise position of dopants within a device and understanding how this affects device behaviour have therefore become essential14, 15, 16, 17. Devices based on the deterministic placement of single dopants in silicon are also leading candidates for solid-state quantum computing architectures, because the dopants can have extremely long spin-coherence18 and spin-relaxation times19, and because this approach would be compatible with existing complementary metal-oxide-semiconductor (CMOS) technology.

    One of the earliest proposals for a solid-state quantum computer involved arrays of single 31P atoms in a silicon crystal, with the two nuclear spin states of the 31P atom providing the basis for a quantum bit (qubit)5. Subsequently, qubits based on the electron spin states6, 7 or charge degrees of freedom20 of dopants in silicon were proposed. This has led to increased interest in measuring the electronic spectrum of individual dopants in field-effect transistor architectures, where the dopants are introduced by low-energy implantation16 or in-diffusion from highly doped contact regions14, 15, 17. However, these approaches are limited to a precision of ~10 nm in the position of the dopants, and the practical implementation of a quantum computing device based on this approach requires the ability to place individual phosphorus atoms into silicon with atomic precision21 and to register electrostatic gates and readout devices to each individual dopant.

    Figure 1 shows the approach we used to deterministically place a single phosphorus atom between highly phosphorus-doped source and drain leads in a planar, gated, single-crystal silicon transport device. This involved the use of hydrogen-resist lithography22, 23, 24 to control the dissociation of the dopant precursor, phosphine (PH3), before incorporation of the phosphorus atom at the required position in the silicon substrate. We found that three adjacent desorbed dimers (pairs of silicon surface atoms) along one dimer row result in the reliable incorporation of a single dopant, as illustrated in Fig. 1c. The incorporation pathway comprises a succession of well-understood dissociative processes25 governed by the availability of bare silicon sites within the three-dimer patch. High dose rates at room temperature ensure that three PH3 molecules dissociate within the three-dimer site into PH2 + H, inhibiting any further reactions. Subsequent heating of the surface to 350 °C allows one PH2 fragment to recombine with a hydrogen atom and desorb. The resulting availability of one free silicon site enables the immediate dissociation of another PH2 to PH + H. Further reactions are inhibited until the final PH2 recombines with H, creating another free site for the remaining PH to dissociate to P. Still at 350 °C, the phosphorus atom subsequently incorporates into the top layer of the silicon surface, resulting in the ejection of a silicon adatom (Fig. 1c, part V). The incorporated phosphorus atom therefore substitutes for one of the six silicon atoms within the designated three-dimer patch, which translates to a lateral spatial positioning accuracy of ±1 lattice site (±3.8 Å).

    a, Perspective STM image of the device, in which the hydrogen-desorbed regions defining source (S) and drain (D) leads and two gates (G1, G2) appear raised due to the increased tunnelling current through the silicon dangling bond states that were created. Upon subsequent dosing with phosphine, these regions form highly phosphorus-doped co-planar transport electrodes of monatomic height, which are registered to a single phosphorus atom in the centre of the device. Several atomic steps running across the Si(100) surface are also visible. b, Close-up of the inner device area (dashed box in a), where the central bright protrusion is the silicon atom, which is ejected when a single phosphorus atom incorporates into the surface. c, Schematic of the chemical reaction to deterministically incorporate a single phosphorus atom into the surface. Saturation dosing of a three-dimer patch (I) at room temperature (RT) followed by annealing to 350 °C allows successive dissociation of PH3 (II–IV) and subsequent incorporation of a single phosphorus atom in the surface layer, ejecting a silicon adatom in the process (V).

    The properties of isolated dopants in bulk silicon are well understood10, but transport devices such as transistors contain electrodes that have profound effects on the energetics of single dopant atoms14. To tune the electrostatic potential at the position of the dopant, two in-plane gates G1 and G2 were patterned on either side of the transport channel defined by the S and D leads, at a distance of 54 nm from the central donor (Fig. 1a). All four planar electrodes were highly phosphorus-doped and therefore conducted at cryogenic temperatures, while the surrounding low-doped substrate became insulating as a result of carrier freeze-out24. Both the tunnel coupling of the donor to the leads as well as the capacitive coupling to the gates are determined by the device architecture, which can be controlled with atomic precision by scanning tunnelling microscope (STM)–lithography.

    To understand quantitatively how the nearby transport electrodes affect the electronic properties of the donor, we have calculated the electrostatic potential landscape of the innermost part of the device, treating the heavily doped gate regions in a self-consistent atomistic approach (see Methods) using a Thomas–Fermi approximation. This is illustrated for equilibrium conditions (that is, no biases applied to the gates) in Fig. 2a, in which we find that the presence of highly doped electrodes strongly alters the usual Coulombic potential of the donor. This can be seen in the two perpendicular line cuts along the S–D and G1–G2 axes, respectively (Fig. 2b), which illustrate the anisotropy of the donor potential in our device, with electrodes closer to the donor resulting in shallower barriers. Here, the potential within the leads (at the edges of these traces) remains below the conduction band-edge of bulk silicon due to the high doping density in the electrodes. The float-up of the central electrostatic potential arises from the very large gradient in the free charge and has previously been observed in resonant tunnelling diodes26.

    a, False-colour plot showing how the calculated potential (at equilibrium) varies with position in the region between the highly doped electrodes. The superimposed donor potential U represents the single phosphorus atom in the centre of the device. b, Line profiles showing how the potential varies with position between the source and drain electrodes (left) and the two gate electrodes (right) (the position of the profiles are indicated by dashed white lines in a). The potential is plotted with respect to the conduction band-edge of bulk silicon, Ecb, indicated by the red dashed line. Apparent oscillations at the edges of the plots correspond to the phosphorus donor potentials within the highly doped electrodes, as represented by the self-consistent atomistic model. c, Close-up of the area indicated by the rectangle in the left panel of b comparing the potential profile between the source and drain electrodes in our device (blue line) to an isolated bulk phosphorus donor (dashed grey line), where the D0 state resides 45.6 meV below Ecb. In contrast, the D0 state in the single-atom transistor resides closer to the top of the potential barrier.

    Having established the electrostatic potential of the device, we then calculated the donor electronic states using a tight-binding approach14. The position of the resulting one-electron ground state D0 for the solitary phosphorus dopant is depicted in Fig. 2c (blue line). As expected, due to the electrostatic environment, the energy levels of our device are raised significantly from the bulk case (dashed grey line), where the unperturbed Coulombic donor potential asymptotically approaches the silicon conduction band minimum Ecb (red dashed line) and D0 has a binding energy10 of EB ≈ –45.6 meV. In contrast, D0 in the effective donor potential of our transport device resides much closer to the top of the barrier (solid line) along the S–D transport direction. However, it is important to note that—in contrast to the bulk case—the binding energy in our device is not simply given by the separation between the donor levels and the top of the barrier along S–D. This is because the donor resides in an anisotropic potential, as shown in Fig. 2b, with stronger confinement along the transverse (G1–G2) direction. Because the binding energies are not accessible in our device (as a result of the limited gate range), we therefore calculated the charging energy, that is, the energy difference between D0 and the two-electron D− state, which can be directly determined from the transport data.

    Figure 3a presents the measured stability diagram of the single donor, in which we can easily identify three charge states of the donor: the ionized D+ state, the neutral D0 state and the negatively charged D− state. The diamond below VG ≈ 0.45 V does not close, as expected14 for the ionized D+ state, because a donor cannot lose more than its one valence electron. The conductance remains high (on the order of microsiemens) down to the lower end of the gating range, making the possibility of additional charge transitions unlikely. Importantly, the D+ ↔ D0 charge transition occurs reproducibly at VG = 0.45±0.03 V for multiple cool-downs of the device. This consistent behaviour is a testament to the high stability of the device and the inherent influence of the nearby electrodes on the position of the donor eigenstates relative to the Fermi level of the leads. The detuning of these states as a function of gate voltage (with both gates at the same potential) is calculated self-consistently for the potential landscape of our device (Fig. 3c), and we find that the D0 level (blue line) shifts downwards linearly as a function of gate voltage. We note that the Fermi level (EF) in the leads is pulled ~80 meV below the conduction band minimum of bulk silicon due to the extremely high doping density. The first charge transition within our model, when one electron occupies the donor, occurs when the D0 level aligns with the Fermi level, at VG = 0.45 V. The agreement with the experimental value is striking, in particular as no fitting parameters for our device were used in our calculations—only the actual device dimensions. At this gate bias (VG = 0.45 V), the barrier height is significantly reduced along the transport direction (Fig. 3d) compared to the equilibrium case (Fig. 2c). This results from the non-proximal coupling of the gates; the applied gate voltage shifts the electrochemical potential of the donor states and also modulates the potential landscape between the donor and the leads.

    a, Stability diagram showing the drain current ISD (on a logarithmic scale) as a function of source–drain bias VSD and gate voltage VG (applied to both gates in parallel). The D+ D0 and D0 D− transitions occur reproducibly at VG ≈ 0.45 V and 0.82 V, respectively. b, Differential conductance dISD/dVSD (on a linear scale) as a function of VSD and VG in the region of the D0 diamond shown in a. From this we determine the charging energy Ec to be ~47±3 meV. c, Calculated energies of the D0 and D− ground states (GS) as a function of VG. The difference in the energy of these two ground states gives a charging energy of Ec ≈ 46.5 meV, which is in excellent agreement with experiment. Charge transitions occur when a ground state crosses the Fermi level (EF) in the leads. d–g, Potential profiles between source and drain electrodes calculated for VG = 0.45 V (d) and 0.72 V (f). The effective barrier height is lower for the higher value of VG. The calculated orbital probability density of the ground state for the D0 potential (e) is more localized around the donor than for the D− potential (g), which is screened by the bound electron.

    At VG > 0.45 V, the bound electron effectively screens the donor core potential. We can account for this theoretically by self-consistently filling the initial Coulomb potential with one electron. The resulting D− state is thus much closer to the top of the barrier along the transport direction (Fig. 3f), and the corresponding orbital probability density (Fig. 3g) is considerably less localized than in the D0 case (Fig. 3e). However, the remaining effective barrier (~12 meV) and strong confinement in the G1–G2 direction explains the larger extent of the D− region in Fig. 3b, which exceeds the value expected for a bulk donor (~1.7 meV).

    For the screened donor potential, we again calculated the shift of the D− level as a function of gate voltage. We found that the D− state comes into resonance with EF at VG = 0.72 V (Fig. 3c), close to the experimentally observed VG value from Fig. 3a. The discrepancy with respect to the experimental value (~0.82 V) for this second charge transition is probably due to necessary simplifications in our modelling approach. In particular, by neglecting depletion effects arising from band bending26 at the edges of the highly doped gate electrodes at positive gate voltages, our model overestimates the effective lever arm, which is a measure for the electrostatic coupling strength between the gates and the donor. Because the depletion effect increases with applied gate voltage, the deviation is expected to be more significant for the second charge transition, which occurs at a higher value of VG.

    Importantly, from the transport data of Fig. 3, we can determine the charging energy (Ec), and compare this with values extracted from absorption spectroscopy10 for a bulk donor in silicon. From a close-up of the stability diagram in Fig. 3b we can extract a charging energy of 47±3 meV, in which the error arises from the asymmetry of the diamond height for VSD > 0 and VSD < 0 resulting from the different capacitive coupling of the one- and two-electron donor states to the electrodes. Despite the presence of nearby electrodes, the experimental value for Ec in our device is remarkably similar to the value expected for isolated phosphorus donors based on the binding energies (45.6 meV for D0 and ~1.7 meV for D−, respectively)10 in bulk silicon. This is in sharp contrast to previous experiments on single dopant in silicon transport devices, which have reported charging energies that significantly differ from the bulk case14, 17, 27. There, the difference was attributed either to screening effects resulting from strong capacitive coupling to a nearby gate14 or strong electric fields27, or to an enhanced donor ionization energy in the proximity of a dielectric interface17. Importantly, these effects are expected to be small for our phosphorus dopant, which is symmetrically positioned between the two gates and encapsulated deep within an epitaxial silicon environment. The bulk-like charging energy observed experimentally is fully supported by the modelling (Fig. 3c), in which Ec is given by the energy separation between the D0 and D− states. The calculated value of 46.5 meV is slightly larger than the ~44 meV expected from the binding energies determined for the bulk case10, and probably results from the artificial confinement represented by the simulation domain boundaries in our model27 (see Methods), which overestimates the energy for D−. At the same time, the presence of electron–electron interactions, which are not fully captured by the mean-field self-consistent method27 to calculate the effective D− potential, may also contribute to the slight discrepancy between calculated and experimental values. We have fabricated a single-atom transistor in which a single phosphorus atom is positioned between highly doped source and drain leads with a lateral spatial accuracy of ±1 atomic lattice spacing. We demonstrate that we are able to register source, drain and gate contacts to the individual donor atom and observe well-controlled transitions for 0, 1 and 2 electron states, in agreement with atomistic modelling of the device. Our results show that encapsulating phosphorus dopant atoms deep within an epitaxial silicon environment allows them to retain both their discrete quantum states and their bulk-like charging energy, despite the presence of highly doped electrodes. These results demonstrate that single-atom devices can in principle be built and controlled with atomically thin wires, where the active component represents the ultimate physical limit of Moore's law. As such, these results are highly relevant to the development of atomic-scale silicon transistors, and our approach could also be applied to the fabrication of single-dopant optoelectronic devices and spin-based quantum computation. Methods Abstract Main Methods References Acknowledgements Author information The STM was used in lithography mode to selectively desorb the hydrogen resist on the Si(100)-2 × 1 surface of a p-type (boron) low-doped substrate. The planar device structure was defined in two steps. First, the innermost parts of the leads and the central three-dimer patch were desorbed, PH3-dosed at 14 langmuir, and annealed for 5 s at 350 °C. The outer structures (gates, lead extensions and micrometre-sized contact patches) were aligned and desorbed, PH3-dosed at ~1.4 langmuir, followed by a 60 s incorporation anneal at 350 °C. The entire structure was then overgrown with ~180 nm silicon from a sublimation source, with the sample held at 250 °C. Electrical measurements were carried out in a 3He/4He dilution refrigerator at base temperature (~20 mK) with a d.c. voltage VSD applied to the S electrode while keeping D grounded. An atomistic tight-binding approach implemented in NEMO-3D (Nanoelectronic Modeling tool)28 was used to generate the electrostatic potential26 and Fermi energy of the highly doped leads29, 30 in a self-consistent manner for a range of gate biases. A Coulomb potential (U) was then superimposed on the potential landscape to represent the quantum confinement of the solitary phosphorus dopant in the transport channel. Different calculated potentials were used at the appropriate gate biases to represent the one-electron ground state D0 and the two-electron D− state. The fully characterized electrostatic environment coupled with a tight-binding Schrödinger solver was used to calculate the eigenstates of the deterministically placed dopant. The simulation domain used to calculate the donor potential was limited along S–D (but included the barrier maxima regions) to prevent the formation of artificial potential wells and consequently charge accumulation at the edges. Fonte http://www.nature.com/nnano/journal/vaop/ncurrent/full/nnano.2012.21.html

  5. Fabio Cecaro 29 febbraio 2012 at 22:00

    News da IBM

    I computer quantistici, ogni giorno che passa, diventano sempre più concreti. IBM ha annunciato grandi passi avanti in questo settore, che in futuro ci darà soluzioni in grado di eseguire calcoli grazie a fenomeni di meccanica quantistica, ben più potenti di qualsiasi supercomputer attuale. Al centro di tutto il qubit, ben diverso dal bit rappresentato da 1 o 0, in quanto può raffigurare entrambi i valori contemporaneamente (superposizione).
    Gli scienziati di IBM Research hanno raggiunto nuovi traguardi nella riduzione dell’errore nei calcoli elementari, oltre che nel mantenimento dell’integrità delle proprietà meccaniche quantistiche nei qubit. L’azienda statunitense ha inoltre lavorato con qubit “superconduttivi”, che sfruttano tecniche di micro-fabbricazione già note sviluppate per la produzione con il silicio, aprendo la strada alla futura produzione di migliaia o milioni di qubit.

    Secondo IBM questo è un dispositivo con qubit “3D” superconduttivo dove il qubit è con una lunghezza di 1mm, è sospeso al centro della cavità su un piccolo chip di zaffiro
    Le speciali proprietà dei qubit consentono a un computer quantistico di realizzare milioni di calcoli alla volta, mentre un PC desktop può realizzarne molti meno nello stesso momento. “Un singolo stato di 250 qubit contiene più bit di informazione rispetto alle particelle presenti nell’Universo”, ha dichiarato IBM.
    Le proprietà dei computer quantistici avranno implicazioni soprattutto nel campo della crittografia dei dati, ma anche la ricerca in database d’informazioni non strutturate, fare operazioni di ottimizzazione e risolvere nuovi problemi matematici. “Il lavoro che stiamo facendo dimostra che non si tratta più solo di un esperimento. È il momento d’iniziare a creare sistemi basati su questa scienza che porterà il computing a un livello completamente nuovo”, ha affermato lo scienziato di IBM Matthias Steffen.

    Un chip in silicio con tre qubit. Secondo IBM, il chip è posto su una scheda madre ed è connesso a linee di I/O coassiali attraverso fili, in una scala 8mm x 4mm
    Una delle grandi sfide per gli scienziati è controllare o rimuovere la cosiddetta “decoerenza quantistica”, cioè la creazione di errori nei calcoli causati da interferenze dovute a fattori quali il calore, la radiazione elettromagnetica e difetti dei materiali. Per ovviare a questo problema, gli scienziati hanno cercato modi per ridurre il numero di errori e allungare i periodi durante i quali i qubit conservano le loro proprietà meccaniche quantistiche.

    Chip al silicio di IBM con tre qubit
    Infatti, quando questo tempo è sufficientemente lungo, gli schemi di correzione degli errori diventano efficaci, permettendo di eseguire calcoli lunghi e complessi. Ci sono molti sistemi che possono portare ad avere un computer quantistico funzionante e IBM si sta concentrando sull’uso di qubit superconduttivi che permettano una transizione più facile verso la produzione e lo scaling.
    IBM, recentemente, ha fatto esperimenti con un unico qubit superconduttore “tridimensionale” (3D qubit). Il team di IBM ha usato un qubit 3D per estendere il tempo in cui i qubit mantengono i loro stati quantici fino a 100 microsecondi. Questo valore supera leggermente la soglia minima per attivare schemi di correzione degli errori efficaci e indica che gli scienziati possono iniziare a concentrarsi su aspetti come la scalabilità.

    Ingrandimento di un singolo bit quantistico
    In altri esperimenti IBM ha dimostrato un qubit a due dimensioni e implementato una logica operativa a due qubit – un’operazione controlled-NOT (CNOT), fondamentalmente il blocco di base di un grande sistema di calcolo quantistico. Il funzionamento di questi qubit ha mostrato un tasso di successo del 95%, dovuto in parte per il lungo tempo di coerenza di circa 10 microsecondi. Questi valori sono all’apice degli schemi di correzione degli errori e aprono la strada a futuri esperimenti con multi-qubit.
    “Ora possiamo vedere i blocchi che saranno usati per dimostrare che la correzione degli errori può essere efficace, e che possono essere realizzati qubit logici affidabili”, ha dichiarato David DiVincenzo, professore presso l’Institute of Quantum Information. Insomma, il computer quantistico è sempre più realtà.

    Fonte
    http://www.tomshw.it/cont/news/il-chip-quantistico-ibm-straccera-i-supercomputer-di-oggi/36146/1.html#xtor=RSS-998

  6. Fabio Cecaro 3 gennaio 2013 at 17:09

    D-Wave una società con la mission di costruire sistemi di computer quantici per aiutare a risolvere i problemi più complessi.
    http://www.dwavesys.com

  7. my blog 15 marzo 2014 at 8:33

    Executive Summary: You must be able to supply highlighting features of the company, and express your small business objectives. When identifying this, always think particularly with regards to one more deliverable (usually another report).

  8. Fabio Cecaro 31 maggio 2014 at 11:05

    Un articolo scientifico su science magazine.
    Kavli Institute of Nanoscience Delft, Delft University of Technology, P.O. Box 5046, 2600 GA Delft, Netherlands.
    Element Six, Ltd., Kings Ride Park, Ascot, Berkshire SL5 8BP, UK.
    Department of Applied Physics, Yale University, New Haven, CT 06511, USA
    http://www.sciencemag.org/content/early/2014/05/28/science.1253512.abstract

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