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fastopcalc.pyx
828 lines (703 loc) · 36.4 KB
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fastopcalc.pyx
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# encoding: utf-8
# cython: profile=False
# cython: linetrace=False
# filename: fastcalc.pyx
import numpy as np
from libc.stdlib cimport malloc, free
from libcpp.algorithm cimport sort as stdsort
from libcpp.unordered_map cimport unordered_map
from libcpp.vector cimport vector
from libcpp.string cimport string
from cython.operator cimport dereference as deref, preincrement as inc
from ..tools import symplectic
cimport numpy as np
cimport cython
#Use 64-bit integers
ctypedef long long INT
ctypedef unsigned long long UINT
def test_map(s):
cdef string st = s.encode('UTF-8')
cdef unordered_map[int, complex] my_map
cdef unordered_map[int, complex] my_map2
cdef unordered_map[int, complex].iterator it
cdef vector[string] v
v = vector[string](3)
v[0] = st
my_map[1]=3.0+2.0j
my_map[2]=6.2
my_map2 = my_map
my_map2[2]=10.0
my_map2[3]=20.0
print my_map[1],my_map[2]
print my_map2[1], my_map2[2],my_map2[3]
print("HELLO!!!")
#try to update map
it = my_map.begin()
while it != my_map.end():
deref(it).second = 12.0+12.0j
inc(it)
#Print map
it = my_map.begin()
while it != my_map.end():
print deref(it).first
print deref(it).second
inc(it)
# for x in my_map:
# print x.first
# print my_map[x]
@cython.boundscheck(False) # turn off bounds-checking for entire function
@cython.wraparound(False) # turn off negative index wrapping for entire function
def fast_bulk_eval_compact_polys(np.ndarray[np.int64_t, ndim=1, mode="c"] vtape,
np.ndarray[double, ndim=1, mode="c"] ctape,
np.ndarray[double, ndim=1, mode="c"] paramvec,
dest_shape):
cdef INT dest_size = np.product(dest_shape)
cdef np.ndarray[np.float64_t, ndim=1, mode="c"] res = np.empty(dest_size, np.float64)
cdef INT c = 0
cdef INT i = 0
cdef INT r = 0
cdef INT vtape_sz = vtape.size
cdef INT nTerms
cdef INT m
cdef INT k
cdef INT nVars
cdef double a;
cdef double poly_val;
while i < vtape_sz:
poly_val = 0.0
nTerms = vtape[i]; i+=1
#print "POLY w/%d terms (i=%d)" % (nTerms,i)
for m in range(nTerms):
nVars = vtape[i]; i+=1 # number of variable indices in this term
a = ctape[c]; c+=1
#print " TERM%d: %d vars, coeff=%s" % (m,nVars,str(a))
for k in range(nVars):
a *= paramvec[ vtape[i] ]; i+=1
poly_val += a
#print " -> added %s to poly_val = %s" % (str(a),str(poly_val))," i=%d, vsize=%d" % (i,vtape.size)
res[r] = poly_val; r+=1
# = dest_shape # reshape w/out possibility of copying
return res.reshape(dest_shape)
#Same as above, just takes a complex ctape
@cython.boundscheck(False) # turn off bounds-checking for entire function
@cython.wraparound(False) # turn off negative index wrapping for entire function
def fast_bulk_eval_compact_polys_complex(np.ndarray[np.int64_t, ndim=1, mode="c"] vtape,
np.ndarray[np.complex128_t, ndim=1, mode="c"] ctape,
np.ndarray[double, ndim=1, mode="c"] paramvec,
dest_shape):
cdef INT dest_size = np.product(dest_shape)
cdef np.ndarray[np.complex128_t, ndim=1, mode="c"] res = np.empty(dest_size, np.complex128)
cdef INT c = 0
cdef INT i = 0
cdef INT r = 0
cdef INT vtape_sz = vtape.size
cdef INT nTerms
cdef INT m
cdef INT k
cdef INT nVars
cdef double complex a;
cdef double complex poly_val;
while i < vtape_sz:
poly_val = 0.0
nTerms = vtape[i]; i+=1
#print "POLY w/%d terms (i=%d)" % (nTerms,i)
for m in range(nTerms):
nVars = vtape[i]; i+=1 # number of variable indices in this term
a = ctape[c]; c+=1
#print " TERM%d: %d vars, coeff=%s" % (m,nVars,str(a))
for k in range(nVars):
a *= paramvec[ vtape[i] ]; i+=1
poly_val += a
#print " -> added %s to poly_val = %s" % (str(a),str(poly_val))," i=%d, vsize=%d" % (i,vtape.size)
res[r] = poly_val; r+=1
# = dest_shape # reshape w/out possibility of copying
return res.reshape(dest_shape)
@cython.boundscheck(False) # turn off bounds-checking for entire function
@cython.wraparound(False) # turn off negative index wrapping for entire function
def fast_compact_deriv(np.ndarray[np.int64_t, ndim=1, mode="c"] vtape,
np.ndarray[np.complex128_t, ndim=1, mode="c"] ctape,
np.ndarray[np.int64_t, ndim=1, mode="c"] wrtParams):
#Note: assumes wrtParams is SORTED but doesn't assert it like Python version does
cdef INT c = 0
cdef INT i = 0
cdef INT j,k, m, nTerms, nVars, cur_iWrt, j0, j1, cur_wrt, cnt, off
cdef INT vtape_sz = vtape.size
cdef INT wrt_sz = wrtParams.size
cdef double complex coeff
#Figure out buffer sizes fro dctapes & dvtapes
cdef INT max_nTerms = 0
cdef INT max_vsz = 0
cdef INT nPolys = 0
while i < vtape_sz:
j = i # increment j instead of i for this poly
nTerms = vtape[j]; j+=1
if nTerms > max_nTerms:
max_nTerms = nTerms
for m in range(nTerms):
nVars = vtape[j] # number of variable indices in this term
j += nVars + 1
if (j-i) > max_vsz:
max_vsz = j-i # size of variable tape for this poly
i = j; c += nTerms; nPolys += 1
#print "MAX vtape-sz-per-poly = %d, MAX nTerms = %d, WRT size = %d" % (max_vsz, max_nTerms, wrt_sz)
#Allocate space
cdef INT vstride = max_vsz+1 # +1 for nTerms insertion
cdef double complex* dctapes = <double complex *>malloc(wrt_sz * max_nTerms * sizeof(double complex))
cdef INT* dvtapes = <INT *>malloc(wrt_sz * vstride * sizeof(INT))
cdef INT* dnterms = <INT *>malloc(wrt_sz * sizeof(INT))
cdef INT* cptr = <INT *>malloc(wrt_sz * sizeof(INT))
cdef INT* vptr = <INT *>malloc(wrt_sz * sizeof(INT))
#cdef np.ndarray dctapes = np.empty( (wrt_sz, max_nTerms), np.complex128)
#cdef np.ndarray dvtapes = np.empty( (wrt_sz, max_vsz+1), np.int64) # +1 for nTerms insertion
#cdef np.ndarray dnterms = np.zeros( wrt_sz, np.int64 )
#cdef np.ndarray cptr = np.zeros( wrt_sz, np.int64 ) # how much of each dctapes row is used
#cdef np.ndarray vptr = np.zeros( wrt_sz, np.int64 ) # how much of each dvtapes row is used
cdef INT res_vptr = 0, res_cptr = 0
cdef np.ndarray[np.int64_t, ndim=1, mode="c"] result_vtape = np.empty( nPolys*wrt_sz*vstride, np.int64 )
cdef np.ndarray[np.complex128_t, ndim=1, mode="c"] result_ctape = np.empty( nPolys*wrt_sz*max_nTerms, np.complex128 )
#print "TAPE SIZE = %d" % vtape_sz
#print "RESULT SIZE = %d" % result_vtape.size
c = 0; i = 0
while i < vtape_sz:
j = i # increment j instead of i for this poly
nTerms = vtape[j]; j+=1
#print "POLY w/%d terms (i=%d)" % (nTerms,i)
# reset/clear dctapes, dvtapes, dnterms for this poly
for k in range(wrt_sz):
cptr[k] = 0
vptr[k] = 1 # leave room to insert nTerms at end
dnterms[k] = 0
for m in range(nTerms):
coeff = ctape[c]; c += 1
nVars = vtape[j]; j += 1 # number of variable indices in this term
#print " TERM%d: %d vars, coeff=%s" % (m,nVars,str(coeff))
cur_iWrt = 0
j0 = j # the vtape index where the current term starts
j1 = j+nVars # the ending index
#Loop to get counts of each variable index that is also in `wrt`.
# Once we've passed an element of `wrt` process it, since there can't
# see it any more (the var indices are sorted).
while j < j1: #loop over variable indices for this term
# can't be while True above in case nVars == 0 (then vtape[j] isn't valid)
#find an iVar that is also in wrt.
# - increment the cur_iWrt or j as needed
while cur_iWrt < wrt_sz and vtape[j] > wrtParams[cur_iWrt]: #condition to increment cur_iWrt
cur_iWrt += 1 # so wrtParams[cur_iWrt] >= vtape[j]
if cur_iWrt == wrt_sz: break # no more possible iVars we're interested in;
# we're done with all wrt elements
# - at this point we know wrt[cur_iWrt] is valid and wrt[cur_iWrt] >= tape[j]
cur_wrt = wrtParams[cur_iWrt]
while j < j1 and vtape[j] < cur_wrt:
j += 1 # so vtape[j] >= wrt[cur_iWrt]
if j == j1: break # no more iVars - we're done
#print " check j=%d, val=%d, wrt=%d, cur_iWrt=%d" % (j,vtape[j],cur_wrt,cur_iWrt)
if vtape[j] == cur_wrt:
#Yay! a value we're looking for is present in the vtape.
# Figure out how many there are (easy since vtape is sorted
# and we'll always stop on the first one)
cnt = 0
while j < j1 and vtape[j] == cur_wrt:
cnt += 1; j += 1
#Process cur_iWrt: add a term to tape for cur_iWrt
off = cur_iWrt*vstride
dctapes[ cur_iWrt*max_nTerms + cptr[cur_iWrt] ] = coeff*cnt; cptr[cur_iWrt] += 1
dvtapes[ off + vptr[cur_iWrt] ] = nVars-1; vptr[cur_iWrt] += 1
off += vptr[cur_iWrt] # now off points to next available slot in dvtape
for k in range(j0,j1):
if k == j-1: continue # remove this index
dvtapes[ off ] = vtape[k]; off += 1
#print " k=%d -> var %d" % (k,vtape[k])
vptr[cur_iWrt] += (nVars-1) # accounts for all the off += 1 calls above.
dnterms[cur_iWrt] += 1
#print " wrt=%d found cnt=%d: adding deriv term coeff=%s nvars=%d" % (cur_wrt, cnt, str(coeff*cnt), nVars-1)
cur_iWrt += 1 # processed this wrt param - move to next one
#Now term has been processed, adding derivative terms to the dctapes and dvtapes "tape-lists"
# We continue processing terms, adding to these tape lists, until all the terms of the
# current poly are processed. Then we can concatenate the tapes for each wrtParams element.
j = j1 # move to next term; j may not have been incremented if we exited b/c of cur_iWrt reaching end
#Now all terms are processed - concatenate tapes for wrtParams and add to resulting tape.
for k in range(wrt_sz):
off = k*vstride
dvtapes[off] = dnterms[k] # insert nTerms into space reserverd at beginning of each dvtape
for l in range(vptr[k]):
result_vtape[res_vptr] = dvtapes[off]; off += 1; res_vptr += 1
off = k*max_nTerms
for l in range(cptr[k]):
result_ctape[res_cptr] = dctapes[off]; off += 1; res_cptr += 1
#Use numpy, but still slower than above C-able code
#result_vtape[res_vptr:res_vptr+vptr[k]] = dvtapes[k,0:vptr[k]]; res_vptr += vptr[k]
#result_ctape[res_cptr:res_cptr+cptr[k]] = dctapes[k,0:cptr[k]]; res_cptr += cptr[k]
#result_vtape = np.concatenate( (result_vtape, dvtapes[k,0:vptr[k]]) ) # SLOW!
#result_ctape = np.concatenate( (result_ctape, dctapes[k,0:cptr[k]]) ) # SLOW!
i = j # update location in vtape after processing poly - actually could just use i instead of j it seems??
free(dctapes)
free(dvtapes)
free(dnterms)
free(cptr)
free(vptr)
return result_vtape[0:res_vptr], result_ctape[0:res_cptr]
def fast_prs_as_polys(circuit, rho_terms, gate_terms, E_terms, E_indices_py, int numEs, int max_order,
int stabilizer_evo):
#NOTE: circuit and gate_terms use *integers* as operation labels, not Label objects, to speed
# lookups and avoid weird string conversion stuff with Cython
#print("DB: pr_as_poly for ",str(tuple(map(str,circuit))), " max_order=",self.max_order)
#cdef double complex *pLeft = <double complex*>malloc(len(Es) * sizeof(double complex))
#cdef double complex *pRight = <double complex*>malloc(len(Es) * sizeof(double complex))
cdef int N = len(circuit)
cdef int* p = <int*>malloc((N+2) * sizeof(int))
cdef int i,j,k,order,nTerms
cdef int max_poly_order=-1, max_poly_vars=-1
cdef int gn
#extract raw data from gate_terms dictionary-of-lists for faster lookup
#gate_term_prefactors = _np.empty( (nOperations,max_order+1,dim,dim)
cdef unordered_map[int, vector[vector[unordered_map[int, complex]]]] gate_term_coeffs
cdef vector[vector[unordered_map[int, complex]]] rho_term_coeffs
cdef vector[vector[unordered_map[int, complex]]] E_term_coeffs
cdef vector[vector[int]] E_indices
cdef vector[int] Einds
for gl in gate_terms.keys():
gn = gl
gate_term_coeffs[gn] = extract_term_coeffs(gate_terms[gl], max_order,
max_poly_vars, max_poly_order)
rho_term_coeffs = extract_term_coeffs(rho_terms, max_order,
max_poly_vars, max_poly_order)
E_term_coeffs = extract_term_coeffs(E_terms, max_order,
max_poly_vars, max_poly_order)
k = len(E_indices_py)
E_indices = vector[vector[int]](k)
for ii,inds in enumerate(E_indices_py):
k = len(inds)
E_indices[ii] = vector[int](k)
for jj,indx in enumerate(inds):
k = indx; E_indices[ii][jj] = k
#OLD
# for order in range(max_order+1):
# nTerms = len(gate_terms[gl][order])
# gate_term_coeffs[gn][order] = vector[unordered_map[int, complex]](nTerms)
# for i,term in enumerate(gate_terms[gl][order]):
# #gate_term_coeffs[gn][order][i] = fastpoly_to_unorderedmap(term.coeff)
# polymap = unordered_map[int, complex]()
# poly = term.coeff
# if max_poly_order == -1: max_poly_order = poly.max_order
# else: assert(max_poly_order == poly.max_order)
# if max_poly_vars == -1: max_poly_vars = poly.max_num_vars
# else: assert(max_poly_vars == poly.max_num_vars)
# for k,v in poly.items(): polymap[k] = v
# gate_term_coeffs[gn][order][i] = polymap
# gate_term_prefactors[igl][order] = vector( GateObj(term.pre_ops[0]).acton_fn for term in gate_terms[gl][order] ) # assume all terms collapsed?
assert(max_order <= 2) # only support this partitioning below (so far)
cdef vector[ unordered_map[int, complex] ] prps = vector[ unordered_map[int, complex] ](numEs)
#prps_chk = [None]*numEs
for order in range(max_order+1):
#print("DB: pr_as_poly order=",order)
#for p in partition_into(order, N):
for i in range(N+2): p[i] = 0 # clear p
factor_lists = [None]*(N+2)
coeff_lists = vector[vector[unordered_map[int, complex]]](N+2)
if order == 0:
#inner loop(p)
#factor_lists = [ gate_terms[glbl][pi] for glbl,pi in zip(circuit,p) ]
factor_lists[0] = rho_terms[p[0]]
coeff_lists[0] = rho_term_coeffs[p[0]]
for k in range(N):
gn = circuit[k]
factor_lists[k+1] = gate_terms[circuit[k]][p[k+1]]
coeff_lists[k+1] = gate_term_coeffs[gn][p[k+1]]
if len(factor_lists[k+1]) == 0: continue
factor_lists[N+1] = E_terms[p[N+1]]
coeff_lists[N+1] = E_term_coeffs[p[N+1]]
Einds = E_indices[p[N+1]]
#print("Part0 ",p)
pr_as_poly_innerloop(factor_lists,coeff_lists,Einds,max_poly_vars,
max_poly_order, stabilizer_evo, &prps) #, prps_chk)
elif order == 1:
for i in range(N+2):
p[i] = 1
#inner loop(p)
factor_lists[0] = rho_terms[p[0]]
coeff_lists[0] = rho_term_coeffs[p[0]]
for k in range(N):
gn = circuit[k]
factor_lists[k+1] = gate_terms[circuit[k]][p[k+1]]
coeff_lists[k+1] = gate_term_coeffs[gn][p[k+1]]
if len(factor_lists[k+1]) == 0: continue
factor_lists[N+1] = E_terms[p[N+1]]
coeff_lists[N+1] = E_term_coeffs[p[N+1]]
Einds = E_indices[p[N+1]]
#print("Part1 ",p)
pr_as_poly_innerloop(factor_lists,coeff_lists,Einds,
max_poly_vars, max_poly_order,
stabilizer_evo, &prps) #, prps_chk)
p[i] = 0
elif order == 2:
for i in range(N+2):
p[i] = 2
#inner loop(p)
factor_lists[0] = rho_terms[p[0]]
coeff_lists[0] = rho_term_coeffs[p[0]]
for k in range(N):
gn = circuit[k]
factor_lists[k+1] = gate_terms[circuit[k]][p[k+1]]
coeff_lists[k+1] = gate_term_coeffs[gn][p[k+1]]
if len(factor_lists[k+1]) == 0: continue
factor_lists[N+1] = E_terms[p[N+1]]
coeff_lists[N+1] = E_term_coeffs[p[N+1]]
Einds = E_indices[p[N+1]]
#print("Part2a ",p)
pr_as_poly_innerloop(factor_lists, coeff_lists,Einds,
max_poly_vars, max_poly_order,
stabilizer_evo, &prps) #, prps_chk)
p[i] = 0
for i in range(N+2):
p[i] = 1
for j in range(i+1,N+2):
p[j] = 1
#inner loop(p)
factor_lists[0] = rho_terms[p[0]]
coeff_lists[0] = rho_term_coeffs[p[0]]
for k in range(N):
gn = circuit[k]
factor_lists[k+1] = gate_terms[circuit[k]][p[k+1]]
coeff_lists[k+1] = gate_term_coeffs[gn][p[k+1]]
if len(factor_lists[k+1]) == 0: continue
factor_lists[N+1] = E_terms[p[N+1]]
coeff_lists[N+1] = E_term_coeffs[p[N+1]]
Einds = E_indices[p[N+1]]
#print("Part2b ",p)
pr_as_poly_innerloop(factor_lists, coeff_lists, Einds,
max_poly_vars, max_poly_order,
stabilizer_evo, &prps) #, prps_chk)
p[j] = 0
p[i] = 0
else:
assert(False) # order > 2 not implemented yet...
return prps
cdef pr_as_poly_innerloop(factor_lists, factor_coeff_lists, vector[int]& Einds,
int max_poly_vars, int max_poly_order, int stabilizer_evo,
vector[ unordered_map[int, complex] ]* prps): #, prps_chk):
#print("DB partition = ","listlens = ",[len(fl) for fl in factor_lists])
cdef int i,j
cdef int fastmode = 1 # HARDCODED - but it has been checked that non-fast-mode agrees w/fastmode
cdef unordered_map[int, complex].iterator it1, it2, itk
cdef unordered_map[int, complex] result, coeff, coeff2, curCoeff
cdef double complex scale, val, newval, pLeft, pRight, p
cdef vector[vector[unordered_map[int, complex]]] reduced_coeff_lists
cdef int incd
cdef int nFactorLists = len(factor_lists) # may need to recompute this after fast-mode
cdef int* factorListLens = <int*>malloc(nFactorLists * sizeof(int))
cdef int last_index = nFactorLists-1
for i in range(nFactorLists):
factorListLens[i] = len(factor_lists[i])
if factorListLens[i] == 0: return # nothing to loop over!
cdef int* b = <int*>malloc(nFactorLists * sizeof(int))
for i in range(nFactorLists): b[i] = 0
#DEBUG
#if debug > 0:
# print "nLists = ", nFactorLists
# for i in range(nFactorLists):
# print factorListLens[i]
assert(nFactorLists > 0), "Number of factor lists must be > 0!"
if fastmode: # filter factor_lists to matrix-compose all length-1 lists
leftSaved = [None]*(nFactorLists-1) # saved[i] is state after i-th
rightSaved = [None]*(nFactorLists-1) # factor has been applied
coeffSaved = [None]*(nFactorLists-1)
incd = 0
#for factors in _itertools.product(*factor_lists):
#for incd,fi in incd_product(*[range(len(l)) for l in factor_lists]):
while(True):
#if debug > 0: # DEBUG
# debug += 1
# print "DEBUG iter", debug, " b="
# for i in range(nFactorLists): print b[i]
# In this loop, b holds "current" indices into factor_lists
if incd == 0: # need to re-evaluate rho vector
factor = factor_lists[0][b[0]]
rhoVecL = factor.pre_ops[0].todense()
for j in range(1,len(factor.pre_ops)):
rhoVecL = factor.pre_ops[j].acton(rhoVecL)
leftSaved[0] = rhoVecL
rhoVecR = factor.post_ops[0].todense()
for j in range(1,len(factor.post_ops)):
rhoVecR = factor.post_ops[j].acton(rhoVecR)
rightSaved[0] = rhoVecR
coeff = factor_coeff_lists[0][b[0]]
coeffSaved[0] = coeff
incd += 1
else:
rhoVecL = leftSaved[incd-1]
rhoVecR = rightSaved[incd-1]
coeff = coeffSaved[incd-1]
# propagate left and right states, saving as we go
for i in range(incd,last_index):
factor = factor_lists[i][b[i]]
for j in range(len(factor.pre_ops)):
rhoVecL = factor.pre_ops[j].acton(rhoVecL)
leftSaved[i] = rhoVecL
for j in range(len(factor.post_ops)):
rhoVecR = factor.post_ops[j].acton(rhoVecR)
rightSaved[i] = rhoVecR
coeff = mult_polys(coeff, factor_coeff_lists[i][b[i]],
max_poly_vars, max_poly_order)
coeffSaved[i] = coeff
# for the last index, no need to save, and need to construct
# and apply effect vector
if stabilizer_evo == 0:
factor = factor_lists[last_index][b[last_index]] # the last factor (an Evec)
EVec = factor.post_ops[0].todense() # TODO USE scratch here
for j in range(1,len(factor.post_ops)): # evaluate effect term to arrive at final EVec
EVec = factor.post_ops[j].acton(EVec)
pLeft = np.vdot(EVec,rhoVecL) # complex amplitudes, *not* real probabilities
EVec = factor.pre_ops[0].todense() # TODO USE scratch here
for j in range(1,len(factor.pre_ops)): # evaluate effect term to arrive at final EVec
EVec = factor.pre_ops[j].acton(EVec)
pRight = np.conjugate(np.vdot(EVec,rhoVecR)) # complex amplitudes, *not* real probabilities
else: # CLIFFORD - can't propagate effects, but can act w/adjoint of post_ops in reverse order...
factor = factor_lists[last_index][b[last_index]] # the last factor (an Evec)
EVec = factor.post_ops[0]
for j in range(len(factor.post_ops)-1,0,-1): # (reversed)
rhoVecL = factor.post_ops[j].adjoint_acton(rhoVecL)
#OLD: p = stabilizer_measurement_prob(rhoVecL, EVec.outcomes)
#OLD: pLeft = np.sqrt(p) # sqrt b/c pLeft is just *amplitude*
pLeft = rhoVecL.extract_amplitude(EVec.outcomes)
EVec = factor.pre_ops[0]
for j in range(len(factor.pre_ops)-1,0,-1): # (reversed)
rhoVecR = factor.pre_ops[j].adjoint_acton(rhoVecR)
#OLD: p = stabilizer_measurement_prob(rhoVecR, EVec.outcomes)
#OLD: pRight = np.sqrt(p) # sqrt b/c pRight is just *amplitude*
pRight = np.conjugate(rhoVecR.extract_amplitude(EVec.outcomes))
result = mult_polys(coeff, factor_coeff_lists[last_index][b[last_index]],
max_poly_vars, max_poly_order)
scale_poly(result, (pLeft * pRight) )
final_factor_indx = b[last_index]
Ei = Einds[final_factor_indx] #final "factor" index == E-vector index
add_polys_inplace(deref(prps)[Ei], result)
#assert(debug < 100) #DEBUG
#increment b ~ itertools.product & update vec_index_noop = _np.dot(self.multipliers, b)
for i in range(nFactorLists-1,-1,-1):
if b[i]+1 < factorListLens[i]:
b[i] += 1; incd = i
break
else:
b[i] = 0
else:
break # can't increment anything - break while(True) loop
else: # "slow" mode
#for factors in _itertools.product(*factor_lists):
while(True):
# In this loop, b holds "current" indices into factor_lists
# print "Inner loop", b
#OLD - now that spams are factors to, nFactorLists should always be >= 2
##coeff = _functools.reduce(lambda x,y: x.mult_poly(y), [f.coeff for f in factors])
#if nFactorLists == 0:
# #coeff = _FastPolynomial({(): 1.0}, max_poly_vars, max_poly_order)
# coeff = unordered_map[int,complex](); coeff[0] = 1.0
#else:
coeff = factor_coeff_lists[0][b[0]] # an unordered_map (copies to new "coeff" variable)
# CHECK POLY MATH
#print "\n----- PRE MULT ---------"
#coeff_check = factor_lists[0][b[0]].coeff
#checkpolys(coeff, coeff_check)
for i in range(1,nFactorLists):
coeff = mult_polys(coeff, factor_coeff_lists[i][b[i]],
max_poly_vars, max_poly_order)
#CHECK POLY MATH
#print "\n----- MULT ---------"
#coeff_check = coeff_check.mult_poly(factor_lists[i][b[i]].coeff) # DEBUG
#checkpolys(coeff, coeff_check)
#pLeft = self.unitary_sim_pre(rhoLeft,Es, factors, comm, memLimit, pLeft)
#pRight = self.unitary_sim_post(rhoRight,Es, factors, comm, memLimit, pRight) \
# if not self.unitary_evolution else 1
#NOTE: no unitary_evolution == 1 support yet...
#pLeft / "pre" sim
factor = factor_lists[0][b[0]] # 0th-factor = rhoVec
rhoVec = factor.pre_ops[0].todense()
for j in range(1,len(factor.pre_ops)):
rhoVec = factor.pre_ops[j].acton(rhoVec)
for i in range(1,last_index):
factor = factor_lists[i][b[i]]
for j in range(len(factor.pre_ops)):
rhoVec = factor.pre_ops[j].acton(rhoVec)
factor = factor_lists[last_index][b[last_index]] # the last factor (an Evec)
if stabilizer_evo == 0:
EVec = factor.post_ops[0].todense() # TODO USE scratch here
for j in range(1,len(factor.post_ops)): # evaluate effect term to arrive at final EVec
EVec = factor.post_ops[j].acton(EVec)
pLeft = np.vdot(EVec,rhoVec) # complex amplitudes, *not* real probabilities
else: # CLIFFORD - can't propagate effects, but can act w/adjoint of post_ops in reverse order...
EVec = factor.post_ops[0]
for j in range(len(factor.post_ops)-1,0,-1): # (reversed)
rhoVec = factor.post_ops[j].adjoint_acton(rhoVec)
#OLD: p = stabilizer_measurement_prob(rhoVec, EVec.outcomes)
#OLD: pLeft = np.sqrt(p) # sqrt b/c pLeft is just *amplitude*
pLeft = rhoVec.extract_amplitude(EVec.outcomes)
#pRight / "post" sim
factor = factor_lists[0][b[0]] # 0th-factor = rhoVec
rhoVec = factor.post_ops[0].todense()
for j in range(1,len(factor.post_ops)):
rhoVec = factor.post_ops[j].acton(rhoVec)
for i in range(1,last_index):
factor = factor_lists[i][b[i]]
for j in range(len(factor.post_ops)):
rhoVec = factor.post_ops[j].acton(rhoVec)
factor = factor_lists[last_index][b[last_index]] # the last factor (an Evec)
if stabilizer_evo == 0:
EVec = factor.pre_ops[0].todense() # TODO USE scratch here
for j in range(1,len(factor.pre_ops)): # evaluate effect term to arrive at final EVec
EVec = factor.pre_ops[j].acton(EVec)
pRight = np.conjugate(np.vdot(EVec,rhoVec)) # complex amplitudes, *not* real probabilities
else: # CLIFFORD - can't propagate effects, but can act w/adjoint of post_ops in reverse order...
EVec = factor.pre_ops[0]
for j in range(len(factor.pre_ops)-1,0,-1): # (reversed)
rhoVec = factor.pre_ops[j].adjoint_acton(rhoVec)
#OLD: p = stabilizer_measurement_prob(rhoVec, EVec.outcomes)
#OLD: pRight = np.sqrt(p) # sqrt b/c pRight is just *amplitude*
pRight = np.conjugate(rhoVec.extract_amplitude(EVec.outcomes))
#Add result to appropriate poly
result = coeff # use a reference?
scale_poly(result, (pLeft * pRight) )
final_factor_indx = b[last_index]
Ei = Einds[final_factor_indx] #final "factor" index == E-vector index
#CHECK POLY MATH
#res = coeff_check.mult_scalar( (pLeft * pRight) ) #DEBUG
#print "\n----- Post SCALE by ",(pLeft * pRight),"---------"
#print "pLeft, pRight = ",pLeft,pRight
#checkpolys(result, res)
#if prps_chk[Ei] is None: prps_chk[Ei] = res
#else: prps_chk[Ei] += res
add_polys_inplace(deref(prps)[Ei], result)
#CHECK POLY MATH
#print "\n---------- PRPS Check ----------",Ei
#checkpolys(deref(prps)[Ei], prps_chk[Ei])
#print("DB: pr_as_poly factor coeff=",coeff," pLeft=",pLeft," pRight=",pRight, "res=",res,str(type(res)))
#increment b ~ itertools.product & update vec_index_noop = _np.dot(self.multipliers, b)
for i in range(nFactorLists-1,-1,-1):
if b[i]+1 < factorListLens[i]:
b[i] += 1
break
else:
b[i] = 0
else:
break # can't increment anything - break while(True) loop
#print("DB: pr_as_poly partition=",p,"(cnt ",db_part_cnt," with ",db_nfactors," factors (cnt=",db_factor_cnt,")")
cdef unordered_map[int, complex] mult_polys(unordered_map[int, complex]& poly1,
unordered_map[int, complex]& poly2,
int max_poly_vars, int max_poly_order):
cdef unordered_map[int, complex].iterator it1, it2
cdef unordered_map[int, complex].iterator itk
cdef unordered_map[int, complex] result = unordered_map[int,complex]()
cdef double complex val
it1 = poly1.begin()
while it1 != poly1.end():
it2 = poly2.begin()
while it2 != poly2.end():
k = mult_vinds_ints(deref(it1).first, deref(it2).first, max_poly_vars, max_poly_order) #key to add
itk = result.find(k)
val = deref(it1).second * deref(it2).second
if itk != result.end():
deref(itk).second = deref(itk).second + val
else: result[k] = val
inc(it2)
inc(it1)
return result
cdef void add_polys_inplace(unordered_map[int, complex]& poly1,
unordered_map[int, complex]& poly2):
""" poly1 += poly2 """
cdef unordered_map[int, complex].iterator it2, itk
cdef double complex val, newval
it2 = poly2.begin()
while it2 != poly2.end():
k = deref(it2).first # key
val = deref(it2).second # value
itk = poly1.find(k)
if itk != poly1.end():
newval = deref(itk).second + val
if abs(newval) > 1e-12:
deref(itk).second = newval # note: += doens't work here (complex Cython?)
else: poly1.erase(itk)
elif abs(val) > 1e-12:
poly1[k] = val
inc(it2)
return
cdef void scale_poly(unordered_map[int, complex]& poly,
double complex scale):
"""" poly *= scale """
cdef unordered_map[int, complex].iterator it
it = poly.begin()
while it != poly.end():
deref(it).second = deref(it).second * scale # note: *= doesn't work here (complex Cython?)
inc(it)
return
cdef vinds_to_int(vector[int] vinds, int max_num_vars, int max_order):
cdef int ret = 0
cdef int i,m = 1
for i in vinds: # last tuple index is most significant
ret += (i+1)*m
m *= max_num_vars+1
return ret
cdef int_to_vinds(int indx, int max_num_vars, int max_order):
cdef vector[int] ret
cdef int nxt, i
while indx != 0:
nxt = indx // (max_num_vars+1)
i = indx - nxt*(max_num_vars+1)
ret.push_back(i-1)
indx = nxt
stdsort(ret.begin(),ret.end())
return ret
cdef mult_vinds_ints(int i1, int i2, int max_num_vars, int max_order):
cdef vector[int] vinds1 = int_to_vinds(i1, max_num_vars, max_order)
cdef vector[int] vinds2 = int_to_vinds(i2, max_num_vars, max_order)
vinds1.insert( vinds1.end(), vinds2.begin(), vinds2.end() )
stdsort(vinds1.begin(),vinds1.end())
return vinds_to_int(vinds1, max_num_vars, max_order)
def checkpolys(unordered_map[int,complex] coeff, coeff_check):
cdef int mismatch = 0
cdef unordered_map[int,complex].iterator it = coeff.begin()
while it != coeff.end():
k = deref(it).first # key
if k in coeff_check and abs(coeff_check[k]-deref(it).second) < 1e-6:
inc(it)
else:
mismatch = 1; break
print "MISMATCH = ", mismatch
print"coeff="
it = coeff.begin()
while it != coeff.end():
print deref(it); inc(it)
print "coeff_check=",coeff_check
# assert(0),"Mismatch!"
cdef vector[vector[unordered_map[int, complex] ]] extract_term_coeffs(python_terms, int max_order, int& max_poly_vars, int& max_poly_order):
ret = vector[vector[unordered_map[int, complex] ]](max_order+1)
for order in range(max_order+1):
nTerms = len(python_terms[order])
ret[order] = vector[unordered_map[int, complex]](nTerms)
for i,term in enumerate(python_terms[order]):
#ret[order][i] = fastpoly_to_unorderedmap(term.coeff)
polymap = unordered_map[int, complex]()
poly = term.coeff
if max_poly_order == -1: (&max_poly_order)[0] = poly.max_order #reference assignment workaround (known Cython bug)
else: assert(max_poly_order == poly.max_order)
if max_poly_vars == -1: (&max_poly_vars)[0] = poly.max_num_vars
else: assert(max_poly_vars == poly.max_num_vars)
for k,v in poly.items(): polymap[k] = v
ret[order][i] = polymap
return ret
cdef double stabilizer_measurement_prob(state_sp_tuple, moutcomes):
#Note: an abridged version from what is in ForwardSimulator... (no qubit_filter or return_state)
#TODO: make this routine faster - port pauli_z_measurement to C?
cdef float p = 1.0
state_s, state_p = state_sp_tuple
for i,outcm in enumerate(moutcomes):
p0,p1,ss0,ss1,sp0,sp1 = symplectic.pauli_z_measurement(state_s, state_p, i)
if outcm == 0:
p *= p0; state_s, state_p = ss0, sp0
else:
p *= p1; state_s, state_p = ss1, sp1
return p
def dot(np.ndarray[double, ndim=1] f, np.ndarray[double, ndim=1] g):
cdef long N = f.shape[0]
cdef float ret = 0.0
cdef int i
for i in range(N):
ret += f[i]*g[i]
return ret